The study ascertained the perceived influence of principals’ leadership styles on teachers’ productivity in public secondary schools in Benue State. Specifically the study was guided by three specific objectives. Also, three research questions were asked and answered by the study. Furthermore, three hypotheses were formulated and tested at 0.05 level of significance. The study adopted a survey research design. The study was carried out in Benue state. The population of the study was 4588 teachers in all the public secondary schools in Benue State. Sample size for the study was 378 respondents. The above sample size was determined using Taro Yamane (1969) sample size determination formula. Multi-stage sampling technique was adopted for this study. The study employed the use of a structured questionnaire titled “Perceived Influence of Principals’ Leadership Styles on Teachers’ Productivity Questionnaire (PIPLSTPQ)” as instrument for data collection. The instrument was validated by three experts and the reliability was established using Cronbach Alpha Coefficient. The overall reliability coefficient of 0.87 was obtained for the instrument. Direct delivery and retrieval method was employed in the administration of the instrument with the aid of three research assistants. Descriptive statistics of mean and standard deviation, were used to answer the research questions while Chi-square (ꭓ2) goodness-of-fit was used to test the hypotheses at a significance level of 0.05. Findings of the study revealed that laissez-faire, transformational, and transactional leadership styles have a high and significant influence on teachers’ productivity in public secondary schools in Benue State. The study concluded that all the examined leadership styles; laissez-faire, transformational, and transactional have a high, positive and significant influence on teachers’ productivity in public secondary schools in Benue State. In view of the findings of the study, this recommendation was made among others; Principals should judiciously apply transformational leadership style in situations that require strict supervision, discipline, and quick decision-making to maintain instructional efficiency.

Software bugs cost time, and not just the time it takes to write a fix; a good chunk of it goes into figuring out what actually went wrong in the first place. Most debugging is still done the traditional way: a programmer reads an error message, scans the code, guesses at the cause, changes something, and reruns the program, often several times before the real problem is found. This paper describes an AI Bug Detector and Fixer, a system built to take over the earlier, more mechanical parts of that process. Users submit their source code through a web interface, and the system analyzes it using static analysis techniques built around Python's Abstract Syntax Tree (AST). Syntax errors are caught during parsing, while separate modules check for undefined and unused variables. Once an issue is detected, the system tries to fix it: simple, well-understood problems are corrected using deterministic rules, and more complex ones are handed to an AI-assisted repair module that generates a candidate patch based on the error, the surrounding code, and a set of repair constraints. The backend is built with FastAPI, and the detection, explanation, patch generation, and validation stages are kept separate so each one can be tested and improved on its own. The tool is aimed at students and beginner programmers who need fast, understandable feedback while they code. This paper covers the motivation behind the project, related work, the design goals, the methodology, the implementation, how the system might be evaluated, its limitations, and where it could go next. The underlying goal throughout is to cut down on repetitive debugging effort without producing fixes that are hard to trust or verify.

Small and marginal farmers often need to consult separate sources for crop selection, market prices, government schemes, fertilizer guidance, farm planning and protection against animal intrusion. This paper presents BHOOMITRA, a modular web-based smart agriculture platform that combines generative artificial intelligence, computer vision and digital farm services in a single application. The system is implemented using Flask Blueprints, Jinja2 and Bootstrap, with SQLAlchemy-backed PostgreSQL storage in deployment and SQLite for local development. Groq-hosted LLaMA models support crop recommendations, yield and profit estimation, market and scheme information, a farming roadmap and conversational assistance. A multimodal model supports fertilizer-label analysis, while YOLOv8 and OpenCV provide animal detection with local alarm and Twilio voice/SMS alerts. The platform also includes email OTP authentication, a crop marketplace, labour discovery and paid expert consultation through Razorpay. Structured prompts, JSON-oriented outputs, caching and rule-based fallbacks are used to improve resilience. Functional testing reported end-to-end operation across the modules; observed average response times ranged from 0.9 seconds for per-frame intrusion inference to 6.5 seconds for roadmap generation under the report’s test conditions. The implementation demonstrates how several farmer-facing services can be integrated into one responsive platform, while recognising that AI-generated advice and estimated figures require local validation.

This article examines how WhatsApp Business marketing could support customer retention among small retail businesses in Chipata, Zambia. A narrative review integrates Zambian SME studies, customer relationship and experience theory, national digital evidence, and platform guidance. A published study of 101 SMEs in Kabwe is used as contextual evidence rather than as a survey of Chipata retailers. The synthesis identifies a gap between digital platform adoption and systematic customer engagement. It develops a service framework linking customer permission, accurate product information, assigned staff responsibility, order fulfilment and complaint resolution to potential repeat purchasing. A six-week evaluation and a performance scorecard are proposed for future testing. Increased message volume is distinguished from customer retention, which requires evidence of actual return visits over a defined period. The article concludes that WhatsApp Business may assist communication when supported by dependable service and responsible data handling. Its effect on customer retention in Chipata remains an empirical question. Retailers should therefore evaluate service reliability and documented repeat purchasing alongside promotional activity.

Background: Digital repertories have transformed the retrieval and organisation of symptom–remedy relationships in homoeopathic practice. Contemporary software may combine repertorial databases, materia medica references, search tools, analytical displays, and case-documentation facilities. However, the availability of these functions does not necessarily establish their accuracy, educational value, or effect on clinical outcomes.
Objective: To describe the development and functional characteristics of digital repertories in homoeopathy, critically examine the available evidence on their adoption and limitations, and identify priorities for their responsible use in education and practice.
Methods: A focused narrative review was undertaken using published research on repertory software, digital technology in homoeopathic practice, and relevant digital-health and health-professions education literature. Supplementary descriptions of software functions were considered for contextual purposes. The review was organised thematically around historical development, functional capabilities, adoption, implementation barriers, educational implications, and future research. It was not designed as a systematic review, and no quantitative synthesis was performed.
Results: Digital repertories offer potential advantages in information retrieval, synonym searching, cross-repertory comparison, access to reference texts, and documentation. An international cross-sectional survey of professional homoeopaths reported regular software use among 59% of respondents, perceived value among 71%, exposure to software during training among 68%, and agreement that cost was prohibitive for many practitioners among 46%. The survey also identified inadequate training as an important barrier. Its non-probability sampling and self-reported responses limit generalisability. Further concerns include source traceability, search errors, dependence on automated rankings, affordability, data protection, and insufficient direct evidence on the accuracy and clinical consequences of software-assisted repertorization.
Conclusion: Digital repertories should be regarded as information-retrieval and analysis-support tools rather than independent arbiters of clinical decisions. Their responsible implementation requires transparent source documentation, structured user training, appropriate data governance, and independent evaluation. Research should distinguish retrieval performance, reproducibility, educational outcomes, and patient outcomes as separate domains.

Federalism spreads out government authority among levels of government; emergencies tend to centralize government authority in the national executive. This generates a constitutional conflict between the need for increased central co-ordination during a crisis and the need to protect federal autonomy and democratic accountability with decentralisation. The tension is explored in this research article by a comparative study of India, the United States and the United Kingdom. The main jurisdiction is over India since its Constitution explicitly grants emergency powers and allows for significant modifications in the relationship between the Union and the States. A contrasting federal model is found in the United States, where emergency power is exercised by constitutional means and by limits on power in the separation of powers and in legislation. Although not a federal State, the United Kingdom is a good comparator as it poses similar questions about central intervention in emergencies. The study utilises doctrinal and comparative legal research methodology and analyses constitutional provisions, legislation, judicial decisions and academic literature. It asserts that emergency centralisation is not necessarily in conflict with federalism. When it's unneeded, disproportionate, indefinite or not subject to sufficient review, however, it becomes constitutionally problematic. The article ends that the Indian constitution does not need to do away with emergency powers but instead more protection in terms of necessity, proportionality, time limit, legislative oversight and judicial oversight.

Dermatological conditions represent one of the most common healthcare concerns globally, where early and accurate diagnosis is critical for effective clinical intervention and patient survival, particularly in malignant conditions such as melanoma and squamous cell carcinoma. Traditional diagnostic workflows rely heavily on manual visual examination and dermoscopic inspection by experienced dermatologists, which can be constrained by specialist scarcity, human subjectivity, and prolonged triage delays. This paper presents an AI-Powered Multi-Model Skin Disease Diagnostic System engineered to provide an automated, high-precision, and accessible platform for dermatological screening. The proposed system integrates three complementary deep learning architectures—DenseNet-121, ResNet-50, and Xception—into a unified inference pipeline capable of identifying nine distinct categories of skin conditions: Actinic keratosis, Atopic Dermatitis, Benign keratosis, Dermatofibroma, Melanocytic nevus, Melanoma, Squamous cell carcinoma, Tinea Ringworm Candidiasis, and Vascular lesions. To address clinical and reviewer requirements for cross-model validation, the system incorporates a Tri-Model Consensus and Comparison Engine that runs inference across all candidate architectures simultaneously, evaluates consensus agreements, and highlights prediction divergences. In addition to probability score estimation, the platform incorporates a clinical decision support system that categorizes detected pathologies into severity risk tiers (Malignant High-Risk, Pre-Malignant, Benign, Inflammatory, and Fungal), delivers contextual clinical summaries, provides actionable urgency guidance, and highlights the dermatological ABCDE melanoma criteria. Operating as a 100% offline standalone system with JIT-compiled tensor execution graphs achieving sub-250ms native inference latency, the application ensures complete patient data privacy, zero internet dependency, and robust diagnostic reporting for screening and educational triage.

Traffic accidents are a major concern worldwide, causing about 1.19 million deaths every year along with substantial economic damage. With the growing availability of traffic and environmental data and increasing computing power, Machine Learning (ML) and Deep Learning (DL) are being widely used to predict traffic accidents. This paper reviews the different ways in which ML and DL are used for accident prediction. It covers model families such as CNN and RNN, the datasets used, the factors that influence accidents, and how data is used to improve predictions. The paper also presents the implementation of RouteGuard, a route-risk assessment system that uses a Random Forest model to estimate road-segment risk.

Medication routines are difficult to manage when prescriptions, dosage schedules, and symptom information are spread across separate tools. This paper presents MediAssist, a Flutter-based Android healthcare support application that combines account management, a locally executed symptom-classification model, medication records, and scheduled notifications. Firebase Authentication supports sign-in, while Cloud Firestore stores profiles, medicine details, and reminder metadata. A TensorFlow Lite model encodes user-selected symptoms as a 230-element binary vector and ranks 100 output scores to display three candidate disease labels with informational content. Prescription images are selected from the gallery and medicine details are entered by the user. Time-zone-aware local notifications are scheduled for every day of a medication course. The paper documents the architecture, data model, inference path, and reminder algorithm, and relates them to ten systems reviewed in the project report. MediAssist is intended for organization and preliminary awareness, not diagnosis or prescribing. No clinical validation dataset or end-to-end performance measurement was supplied, so no accuracy claim is made.

Fixed-time traffic signals waste green time on empty approaches while vehicles queue on busy ones, and commercial adaptive systems are costly to instrument and hard to inspect. Existing learning-based controllers are rarely compared against a realistic actuated baseline, and often lack guaranteed safety rules. This paper reports the implementation of an adaptive signal controller for a four-way junction built on a SUMO digital twin. A Random Forest, trained on 38 simulation runs over 13 traffic scenarios, predicts per-lane vehicle count and waiting time 15 s ahead from 125 engineered features; it predicts the change over the horizon instead of the absolute level, with isotonic-calibrated confidence. A rule-based decision engine blends current and predicted demand into phase scores and enforces minimum and maximum green, hysteresis with a confirmation window, gap-out, starvation protection and emergency-vehicle priority. The controller is evaluated against vehicle-actuated control in two lockstep SUMO instances using seven metrics. The forecast reaches a test mean absolute error of 1.44 against 2.72 for a persistence baseline. The controller won or tied all seven metrics in all 13 scenarios, reducing average waiting time by 7.1% to 86.2%. A web console and an ESP32-driven four-head LED model show the live decisions. Results are from simulation only.

With the increasing integration of telemedicine and decentralized diagnostics, traditional medical imaging workflows often suffer from latency, manual reporting bottlenecks, and inefficient communication handoffs. This project introduces a fully automated, cloud-edge integrated diagnostic pipeline designed to streamline brain tumor detection and patient report delivery. Utilizing an ESP32-CAM hardware module equipped with a physical pushbutton interface, the system captures patient scan images and securely uploads them to a cloud storage bucket via Supabase.
On the local processing end, a background synchronization service continuously polls the cloud repository, fetching new acquisitions into a local environment. A master automation orchestrator then executes Optical Character Recognition (OCR) using Tesseract to extract the patient’s email address directly from the scan metadata. Simultaneously, a desktop computer vision routine executes the local diagnostic classification workflow, automatically detecting the scan outcome (tumor or non-tumor) through template matching. Upon completion, the system dynamically compiles the diagnostic status and dispatches an encrypted email report to the patient via Gmail SMTP. This end-to-end framework eliminates manual data entry, minimizes reporting delays, and demonstrates a reliable, low-cost hardware-to-cloud IoT architecture for medical imaging applications

Satellite imagery is generated at a scale that makes manual inspection slow, error-prone and impractical. This paper presents SKYFUSION, an end-to-end system that detects and counts aircraft, ships and vehicles in satellite images using the YOLOv8 deep learning detector. A YOLOv8m model is fine-tuned on a labelled satellite dataset of 2,992 images (2,094 training, 449 validation, 449 test) for 30 epochs using the Adam ptimizer with a learning rate of 0.001 and a batch size of 32. The trained weights are integrated into a Django web application that lets a user log in, upload an image and instantly receive an annotated image with bounding boxes, confidence scores and per-class object counts. On the 449-image test set the system reports an overall accuracy of about 98%. Qualitative tests show that it can count 232 vehicles and one aircraft in a dense scene and locate a ship near a waterbody. The framework gives analysts a fast, accessible and extensible tool for surveillance, traffic analysis, urban planning and disaster response.

Comparative study of death penalty and constitutionalism. This paper provides a comparative study on death penalty and constitutionalism in three states – India, the United States of America and South Africa. The study highlights how constitutional principles like right to life, human dignity and fundamental rights affect the legality of death penalty. The analysis is conducted on the constitutional provisions of all three nations and landmark judicial decisions made by their highest courts. India has retained death penalty in the “rarest of rare” principle whereas the United States of America allows it within certain constitutional guarantees in certain states. In contrast to the former two states, South Africa has abolished death penalty. The study employs the comparative doctrinal research approach.

Federalism spreads out government authority among levels of government; emergencies tend to centralize government authority in the national executive. This generates a constitutional conflict between the need for increased central co-ordination during a crisis and the need to protect federal autonomy and democratic accountability with decentralisation. The tension is explored in this research article by a comparative study of India, the United States and the United Kingdom. The main jurisdiction is over India since its Constitution explicitly grants emergency powers and allows for significant modifications in the relationship between the Union and the States. A contrasting federal model is found in the United States, where emergency power is exercised by constitutional means and by limits on power in the separation of powers and in legislation. Although not a federal State, the United Kingdom is a good comparator as it poses similar questions about central intervention in emergencies. The study utilises doctrinal and comparative legal research methodology and analyses constitutional provisions, legislation, judicial decisions and academic literature. It asserts that emergency centralisation is not necessarily in conflict with federalism. When it's unneeded, disproportionate, indefinite or not subject to sufficient review, however, it becomes constitutionally problematic. The article ends that the Indian constitution does not need to do away with emergency powers but instead more protection in terms of necessity, proportionality, time limit, legislative oversight and judicial oversight.

Visual impairment is a significant global challenge affecting millions of individuals, severely limiting their ability to navigate, recognize objects, and interact independently with their environment. Traditional assistive tools such as white canes and guide dogs, while reliable, fail to deliver detailed real-time environmental information. With recent advancements in Artificial Intelligence (AI) and computer vision, intelligent assistive systems have emerged as transformative solutions. This paper presents the implementation of SightSense, an AI-based visual interpretation system built on a Raspberry Pi
5 with a camera module. On request, the system captures an image, sends it to a multimodal Gemini model for scene description or text reading, translates the result into one of ten supported languages, and delivers it as audio feedback using neural text-to-speech; a separate on-device YOLO-based mode provides object detection. The software is organized into independent Python modules so that each stage can be improved or replaced without changing the others. Functional testing showed that the prototype describes scenes, reads printed text and speaks in the selected language, and it exposed two limitations: reduced confidence in low light and a freeze when the cloud API usage limit is reached. Challenges widely reported in this field, including processing latency, reduced accuracy in cluttered environments, limited personalization and limited context awareness, remain relevant, and the paper outlines future work on offline fall-back, voice-based control and user studies. The goal is to contribute to efficient, affordable and accessible AI-driven assistive technology that enhances the safety, confidence and independence of visually impaired individuals.

As digital technologies, artificial intelligence, social media, e-commerce, and digital governance have grown, personal data has become a valuable asset for both public and private organizations. This shift has led to concerns about surveillance, profiling, data breaches, unauthorized data use, and individuals losing control over their personal information. In India, the Supreme Court’s decision in Justice K.S. Puttaswamy (Retd.) v. Union of India recognized privacy as a fundamental constitutional right and highlighted informational privacy as a key part of that right. The Digital Personal Data Protection Act, 2023, and the Digital Personal Data Protection Rules, 2025, followed as major legislative steps. In the United States, data privacy has developed through constitutional principles, especially the Fourth Amendment, along with federal sector-specific laws and state privacy laws like California’s Consumer Privacy Act.
This article uses doctrinal and comparative methods to study the constitutional bases, court decisions, and laws that shape data privacy in India and the United States. It looks at cases like Puttaswamy, Riley, and Carpenter, and compares India’s proportionality test with the American reasonable-expectation-of-privacy and Fourth Amendment standards. The article argues that while India and the US use different constitutional models, both struggle to apply old privacy ideas to today’s widespread digital data collection.

In an islanded microgrid with limited storage, the energy management system decides which load to curtail when solar and wind output fall short. This paper develops a two-layer strategy for a PV–wind–battery microgrid serving a community of about 1.1 MWh/day in northern Nigeria. An hourly receding-horizon model predictive controller (MPC), formulated as a linear program with critical and non-critical load classes, runs online; offline, the Greylag Goose Optimization (GGO) algorithm tunes five parameters of the MPC cost. Hour-of-day profiles digitised from the author's dissertation drive a stochastic scenario generator, and four independent simulated years are used for testing. Against a rule-based controller with tuned thresholds, MPC with cost-consistent weights cut the lost-load cost by 41% and the total operating cost by 4.8% (Wilcoxon p <0.001, 44 of 48 paired months), and it came within 1.8% of a perfect-foresight MPC. GGO tuning recovered 93% of the cost gap between a naively weighted MPC and the cost-consistent one without being given the true cost weights, but it did not improve on the cost-consistent weights (+0.27%), and GGO, PSO and GWO performed alike. The scenarios are synthetic and one system design is studied, so the results are indicative rather than site-measured.

Financial literacy can help people to understand financial products, assess the risk and return involved, and to make investment choices which are in line with their financial goals. The present study looks at people's self-reported level of financial literacy and the way in which they make investment decisions, focusing on their knowledge of financial products, awareness of the different investment options available, the extent to which they believe their financial knowledge affects their investment decisions, the length of their investment horizon, and their level of risk tolerance. A quantitative, descriptive and analytical survey method was employed. The primary data were gathered by means of a structured questionnaire and 104 valid responses were included. A convenience sample was used and the results were presented in the form of frequencies and percentages. The findings reveal that 48.08% of the respondents assessed their knowledge of financial products and services as average, while 37.50% rated it as good. A total of 65.38% said that they understood the risk–return concept. Moreover, 72.11% agreed or strongly agreed that financial knowledge has an influence on their investment decisions, and 82.70% agreed or strongly agreed that financial literacy enables them to make better investment decisions. Moderate risk was chosen by 58.65% of the respondents, and 39.42% preferred an investment period longer than five years. The results show that the respondents in general appreciate the value of financial literacy, even though their awareness of the various investment alternatives is still uneven. Since the study relies on a convenience sample and involves only descriptive analysis, the results should be seen as reflecting patterns within the sample and not as evidence of a statistically significant causal effect.

Artificial Intelligence (AI) is increasingly shaping public administration, healthcare, education, agriculture, finance, transport and commercial activity in India. AI systems can improve efficiency, accessibility and decision-making, but they can also create risks involving privacy, discrimination, misinformation, cybersecurity, intellectual property and unclear accountability. India’s approach combines existing legislation, sectoral regulation, public policy and institutional initiatives rather than one comprehensive AI statute. Relevant laws include the Information Technology Act, 2000, the Digital Personal Data Protection Act, 2023, the Bharatiya Nyaya Sanhita, 2023, evidence law, consumer-protection law and intellectual-property legislation. The India AI Governance Guidelines, released in November 2025, set out a principle-based framework for safe, inclusive and responsible adoption. This article examines AI’s opportunities and risks, the Indian legal framework, constitutional principles and judicial decisions, and the reforms needed to protect rights while enabling innovation. It argues for a proportionate, risk-based and human-centred framework supported by clear duties, independent assessment, meaningful remedies and accountable public-sector use.

India’s rapid digital transformation has expanded access to banking, education, commerce, communication and public services. At the same time, it has created opportunities for cybercrime, including phishing, online financial fraud, identity theft, unauthorised access, cyberstalking, ransomware, data theft and the circulation of unlawful digital content. Cybercrime is difficult to investigate because offenders may conceal their identities, act across borders, use rapidly changing technologies and store evidence in multiple jurisdictions. India’s legal response is based principally on the Information Technology Act, 2000, read where applicable with general criminal law, evidence law, data-protection law and sector-specific regulation. The Bharatiya Nyaya Sanhita, 2023 and Bharatiya Sakshya Adhiniyam, 2023 form part of the contemporary criminal-law and evidence framework. Institutional mechanisms such as CERT-In, the Indian Cyber Crime Coordination Centre and the National Cyber Crime Reporting Portal support prevention, reporting and investigation. This article analyses the nature of cybercrime, the relevant legal framework, constitutional and evidentiary issues, enforcement challenges and reforms needed to improve victim protection and accountability. It argues that effective cybercrime control requires coordinated enforcement, technically competent investigation, reliable electronic evidence, public awareness and safeguards for privacy and civil liberties.

Reliable charging and discharging of electric vehicle (EV) lithium-ion batteries needs tight voltage regulation, current limiting and state-of-charge (SOC) management. Constant-current constant-voltage (CC-CV) control with a fixed-gain PI controller is simple but copes poorly with changing operating conditions. This paper develops a Brain Emotional Learning-Based Intelligent Controller (BELBIC) whose learning rates are tuned offline by Particle Swarm Optimization (PSO), and uses one controller for the CC stage, the CV stage and discharging of a 12.8 V, 40 Ah LiFeMgPO4 battery. The battery is connected to a 24 V bus through a bidirectional half-bridge buck/boost converter, modeled in MATLAB/Simulink, with supervisory logic holding SOC between 20 and 80 %. A PSO-tuned PI controller serves as benchmark on the same plant and 8000 s profile. Both controllers kept SOC inside the window, but PSO-BELBIC was lower in 12 of 14 numerical indices. Its terminal voltage peaked 0.49 % above the 13.8 V full-charge reference (PI: 4.97 %), and its current stayed within ±60 A (peak 59.07 A), whereas PI peaked at 124.26 A and spent 64.82 % of the run outside the limit. Its mean steady-state voltage error was 95.9 % lower, RMS current 66.1 % lower and temperature rise 74.4 % lower (11.39 °C versus 44.48 °C), and it settled within ±2 % in all three charging intervals against two of four for PI. PI, however, had lower steady-state voltage ripple (0.057 V versus 0.194 V) and a shorter mean settling time where it settled (71.5 s versus 200 s). The study is simulation-only, with a scaled-down battery, a four-particle, four-iteration PSO search and a single fixed-gain PI benchmark, so it shows the potential of PSO-BELBIC and not superiority over every PI design.

A companion survey [1] found that career guidance, resume building, Applicant Tracking System (ATS)-style evaluation, and examination support are offered as separate services, and proposed an integrated framework. This paper reports how that framework is implemented as a working web platform for engineering students. We describe the architecture (a FastAPI service layer, SQLite persistence, and a framework-free JavaScript client) and the algorithm behind each module: a three-component ATS compatibility score whose semantic term is computed with TF-IDF cosine similarity, a hybrid career recommender with ranked skill-gap analysis, a sandboxed code judge for programming assessments, an OCR-based document integrity analysis, and a chatbot built on the Anthropic API with a deterministic fallback. We also document the design decisions that make the system explainable, privacy-conscious, and robust to partial failure, together with three explicit scope boundaries: the ATS score is a research-defined measure and not any vendor’s score; the integrity analysis flags inconsistencies and does not authenticate documents with their issuers; and the platform does not submit job applications. The paper specifies a verification strategy and an evaluation protocol but reports no experimental results.

Background
Anterior cruciate ligament (ACL) injuries are well-established risk factors for the accelerated development of secondary knee osteoarthritis (OA). While conventional management relies heavily on non-steroidal anti-inflammatory drugs (NSAIDs), physical therapy, or surgical interventions, prolonged pharmaceutical use is frequently limited by systemic adverse effects. Homoeopathy offers a holistic, individualized system of medicine, yet observational data regarding its specific effectiveness in post-traumatic, secondary knee osteoarthritis remains scarce.
Objective
To evaluate the clinical effectiveness of individualised homoeopathic treatment in managing pain, reducing stiffness, and improving the physical functions of patients suffering from left knee osteoarthritis secondary to a chronic ACL ligament injury.
Methods
This prospective, observational clinical study monitored patients diagnosed with post-traumatic left knee OA following a prior ACL injury over a baseline period. Patients received individualised homoeopathic remedies selected via classical repertorisation based on their unique totality of symptoms (common remedies including Arnica Montana, Rhus Toxicodendron, Bryonia alba, and Pulsatilla). Clinical outcomes were measured at baseline, 6 months, and 12 months using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, the Knee Injury and Osteoarthritis Outcome Score (KOOS), and a Visual Analogue Scale (VAS) for pain estimation.
Results
A statistically significant reduction in mean VAS pain scores was observed between baseline and the 12-month follow-up. Substantial improvements were documented across all domains of the WOMAC index, notably in the Activities of Daily Living (ADL) subset and morning stiffness criteria. The KOOS parameters indicated improved joint mobility and quality of life. No significant systemic adverse events or drug interactions were reported during the course of the treatment.

The Edge-Based Intelligence Social and Farming Robot is an intelligent robotic system designed to support agricultural activities and provide basic social assistance. The main objective of this project is to combine robotics, sensors, artificial intelligence (AI), and edge computing to develop a smart, efficient, and cost-effective solution. The robot uses sensors to collect real-time information about soil moisture, temperature, humidity, and environmental conditions. It can assist farmers by monitoring field conditions, identifying basic crop-related problems, and providing useful information for better farming decisions. The social assistance feature can support basic human interaction, monitoring, and assistance in suitable environments. Edge computing enables the robot to process data locally without depending completely on cloud services, reducing response time and improving efficiency. A microcontroller such as ESP32 can be used to control the sensors, motors, and other connected components. The system aims to reduce manual effort, improve agricultural productivity, and provide useful assistance in farming and social applications. Overall, this project demonstrates how intelligent robotics and edge-based processing can be combined to create a reliable, affordable, and scalable solution for smart agriculture and social assistance.

Switched reluctance motor (SRM) drives offer a rugged construction, low manufacturing cost and high fault tolerance, but their nonlinear electromagnetic characteristics and phase commutation produce substantial torque ripple and make high-performance speed regulation difficult. This study develops and evaluates an adaptive neuro-fuzzy inference system (ANFIS) controller for a three-phase 6/4 SRM drive, with a conventional proportional-integral-derivative (PID) controller used as the benchmark. The controllers were implemented in MATLAB/Simulink and evaluated under no-load, constant-load and dynamic-load operating conditions using speed, electromagnetic torque and phase-current responses. Rise time, settling time, steady-state error, torque-ripple characteristics and current measures were used to assess performance. At 1000 rpm with no load, ANFIS reduced rise time from 0.0507 s to 0.0331 s and settling time from 0.0900 s to 0.0455 s. Under a constant 100 N·m load, the corresponding values were 0.1854 s and 0.2190 s for ANFIS compared with 0.2761 s and 0.5923 s for PID. Under a dynamic 100 N·m load, ANFIS achieved a settling time of 3.0023 s compared with 7.9073 s for PID and a lower steady-state speed error of 2.70 rpm compared with 12.29 rpm. The torque-ripple results were mixed across operating conditions, with PID providing lower ripple in some cases. Overall, ANFIS provided faster speed tracking, better disturbance rejection and improved current regulation, demonstrating its potential for high-performance SRM drive applications.

Digital asset custody is split across wallets, multi-signature contracts, and off-chain fraud monitors that do not act on one another, leaving a gap between detecting a suspicious transfer and preventing it. This paper presents the implementation of AI Smart Vault, a unified platform that closes that gap. A Solidity vault contract enforces multi-signature approval, while an off-chain risk engine scores every proposed transaction from amount, frequency, and behavioral features using an Isolation Forest combined with deterministic rules. The score reaches the contract as an EIP-712 signed attestation, and the contract maps it to a risk tier that raises the number of required approvals or imposes a time lock. We describe the architecture, contract design, risk model, data pipeline, dashboard, and security hardening, and we define a reproducible protocol for evaluating gas cost, detection quality, and attack resistance.

Biometric identification and demographic profiling play a pivotal role in high-security environments, forensic investigations, and automated access control. Conventional unimodal biometric systems—relying solely on a single trait such as a fingerprint or an iris scan—frequently suffer from vulnerability to physical presentation attacks, synthetic spoofing, environmental noise, and modest classification accuracy when inferring secondary demographic traits like gender.
To overcome these constraints, this paper presents an end-to-end, multi-stage Biometric Security Framework combining pre-classification alteration detection with multimodal biometric fusion. The proposed system introduces a strict Fail-Secure Gate: incoming fingerprint specimens are first evaluated for synthetic mutilations, central rotations, and obliterations using structural Crossing Number (CN) minutiae density, Gray-Level Co-occurrence Matrix (GLCM) second-order statistics, Local Binary Pattern (LBP) variance, Sobel edge gradient variance, and a dense 288-dimensional Histogram of Oriented Gradients (HOG) ($295$ total dimensions). Altered inputs trigger an instantaneous security halt, rejecting potential spoof attempts prior to downstream processing.
For verified genuine specimens, complementary 297-dimensional feature representations are extracted from paired fingerprint and iris samples. The framework evaluates both early feature-level concatenation ($594$D) and a late fusion stacking meta-classifier driven by out-of-fold probability estimation and Logistic Regression. Experimental evaluation shows that the alteration detector achieves $81.42%$ accuracy ($0.880$ ROC-AUC), while multimodal late fusion stacking achieves $76.67%$ accuracy ($0.845$ ROC-AUC) on the benchmark test split, outperforming unimodal fingerprint ($62.67%$) and iris ($73.33%$) baselines. The entire pipeline is deployed via an interactive Streamlit web dashboard providing real-time inference, security halting, and comparative visual analytics.

Comparing constitutions is routine in courts, drafting bodies and classrooms, yet the conditions under which a comparison actually teaches something are seldom stated. This paper asks when two constitutional features can fairly be set side by side. It follows the long argument between functional and contextual schools of comparative law and contends that each supplies what the other lacks. Using doctrinal and comparative methods, it proposes a three-stage comparability test made up of a problem check, a context check and an effects check. The test is then applied to four recurring themes, namely constitutional borrowing, separation of powers, federalism, and judicial review of ordinary laws and constitutional amendments, with primary material drawn from India, the United States and the United Kingdom. The findings show that shared labels mislead, that Indian arrangements are often hybrids and not copies, and that one unverified premise, such as the belief that American states may lawfully secede, can distort an entire comparison. The paper concludes that comparability is earned through reasoning and not assumed from vocabulary, and it recommends the test as a working discipline for students, courts and drafters.

Today, the Indian jurisprudence on the reservation has two analytically separable types of preferential treatment: preferential treatment based on historical and structural exclusion of a group, and reservation based on economic conditions (Economically Weaker Sections) which exist outside the historical and structural exclusion of group in the form of SC, ST and OBC. The co-existence of them has served to dramatically highlight the issues concerning the creamy layer, economic disadvantage as a constitutional issue, what exactly is the concept of the unreserved and how the poor must be treated in particular if they do not belong to one of the privileged groups. In this study, the authors resort to doctrinal, analytical and comparative methods to explore the constitutional building, key Supreme Court rulings and prevailing administrative standards pertaining to these issues. It claims that the same income criterion of Rs 8 lakh which is applied as an OBC creamy-layer rule will be applied as an income criterion under the Economically Weaker Sections (EWS) scheme and this is a contradictory legal measure, which cannot be now used to assess disadvantage. In addition, the analysis reveals that the demand for an open category is a competition pool open for all argue on merit basis not a reservation of unreserved caste bloc. A comparison with the United States and Bangladesh suggests learning by mechanical transplantation of specific models and experience and by transparent targeting and regular review and evidence-based recalibration. Defensible Indian framework should retain the remedies through representation for entrenched social disadvantage, reform basis of economy with regular income/asset eligibility and ensure genuine open competition to strengthen non-quota measures in protecting economically vulnerable citizens.

The rapid expansion of the internet, smartphones, digital payments, social media and online services has transformed modern society. India has experienced particularly rapid digitalisation, with citizens increasingly using digital platforms for banking, education, communication, commerce and government services. However, the growth of the digital environment has also created opportunities for criminal activity. Cyber crimes such as identity theft, online financial fraud, hacking, phishing, cyber stalking, ransomware, data theft, online sexual exploitation and cyber terrorism have emerged as serious legal and social challenges.

Artificial Intelligence (AI) is increasingly influencing public administration, healthcare, education, finance, agriculture, transport, policing and commercial activity in India. AI can improve the speed, scale and accessibility of services, support evidence-based decision-making and stimulate innovation. At the same time, its use raises serious questions concerning privacy, discrimination, transparency, accountability, intellectual property, misinformation, cybersecurity and the right to an effective remedy. India’s legal response is developing through existing laws, sectoral regulation and policy guidance rather than through one comprehensive AI statute. Important legal instruments include the Information Technology Act, 2000, the Digital Personal Data Protection Act, 2023, the Bharatiya Nyaya Sanhita, 2023, consumer-protection and intellectual-property laws, and constitutional guarantees. The India AI Governance Guidelines released in November 2025 provide a principle-based framework built around seven guiding principles, while recommending institutional coordination and risk mitigation. This paper examines the opportunities and risks of AI, the relevant Indian legal framework, constitutional safeguards and judicial principles, and the need for reforms. It argues that India should adopt a proportionate, risk-based and human-centred model that protects rights without unnecessarily restricting beneficial innovation.

The expression “socialist law” does not denote a separate legal system in India in the manner in which the term has historically been used for centrally planned socialist states. The Indian constitutional model is better understood as a democratic, welfare-oriented and social-justice-based legal order in which socialist values operate alongside individual liberty, equality, rule of law, judicial review, private property and a mixed economy. The word “socialist” was expressly inserted into the Preamble by the Constitution (Forty-second Amendment) Act, 1976, but the Constitution contained substantial social and economic commitments from the beginning.
The central constitutional sources of these commitments are the Preamble, Fundamental Rights, Directive Principles of State Policy, provisions concerning affirmative action, labour welfare, education, public health, distribution of resources, village self-government and protection of weaker sections. Articles 38 and 39 are especially important because they direct the State toward social and economic justice, reduction of inequalities, adequate means of livelihood, distribution of material resources for the common good and prevention of concentration of wealth. Articles 39A, 41, 42, 43, 43A, 46, 47, 48A and 243G/243W further develop the welfare dimension.
Judicial interpretation has converted many socio-economic constitutional aspirations into practical legal principles through Article 21 and related rights. At the same time, the Supreme Court has repeatedly maintained that Directive Principles cannot simply be used to extinguish Fundamental Rights. Minerva Mills emphasised harmony between Parts III and IV. Recent cases continue this approach: Property Owners’ Association v. State of Maharashtra (2024) clarified the constitutional meaning of Article 39(b); State of Punjab v. Davinder Singh (2024) considered substantive equality in reservation; Pragya Prasun v. Union of India (2025) addressed accessibility and reasonable accommodation; Union of India v. Rohith Nathan (2026) examined OBC creamy-layer principles; and a 2026 education judgment concerning Sarva Shiksha Abhiyan linked public education policy to Article 45 and Article 21A.
The assignment concludes that the Indian legal system contains significant socialist-oriented elements, but these operate within a constitutional democracy rather than an absolute state-controlled economic order. The modern challenge is to achieve substantive equality, social security, dignified work, affordable health and education, environmental protection and equitable distribution of opportunities while respecting liberty, federalism, private enterprise, constitutional limitations and institutional competence.

Controlling a six-joint robotic arm is difficult for non-expert operators, particularly for low-cost servo-driven arms whose dynamics are only approximately known. Existing gesture-based approaches rely on wearable sensors, accurate arm models, or learning methods validated only in simulation, and few combine a plain camera, a reinforcement-learning policy and inexpensive embedded hardware. This paper presents the implementation of ARROW, a vision-based, reinforcement-learning-assisted control system for a six-degree-of-freedom arm. MediaPipe running in a browser extracts pose and hand landmarks, which are reduced to four movement parameters (shoulder, elbow and wrist angles and finger curl) and converted into a target configuration. A Proximal Policy Optimization (PPO) policy, trained with Stable-Baselines3 in a Gymnasium environment built on the PyBullet simulator, maps the target and the robot state to joint actions. Validated joint angles are sent over USB serial to an ESP32, which drives six servo motors. Training and evaluation were carried out entirely in simulation and no external dataset was used. Over five evaluation episodes the trained policy obtained positive rewards between 144.67 and 503.43, with a mean of 360.87. The serial interface to the ESP32 is prepared, but physical-arm testing is pending, so no hardware accuracy is claimed. The work shows that a camera, a computer and a low-cost microcontroller are sufficient to prepare a learned, gesture-driven arm controller.

Indian farming is undergoing a major shift from conventional methods to technology-driven practices. The present investigation is based exclusively on secondary sources published between 2020 and 2026. The Government of India introduced Digital Agriculture Mission during 2024 with a financial allocation of Rs. 2817 crore to develop Digital Public Infrastructure. According to Press Information Bureau February 2026, more than 7.63 crore digital farmer identities have been created, including 1.93 crore for women cultivators, and 23.5 crore land parcels have been mapped through mobile-based crop survey. Modern tools such as Artificial Intelligence, Internet of Things, drone technology, precision farming, remote sensing and Geographic Information System are reshaping farm operations. The AI-enabled Kisan e-Mitra platform has resolved 93 lakh farmer questions with a daily capacity of 8000 queries in eleven languages. Similarly, AI-supported monsoon prediction experiment during Kharif 2025 benefited 3.88 crore growers across thirteen states. This paper discusses two aspects - development of new-age technologies in farm management and managerial benefits and obstacles. Findings indicate 20 to 30 percent improvement in productivity and scope for premium branding through Geographical Indication, especially in Tamil Nadu. The paper concludes that success depends on cultivators' capability to choose suitable innovation, interpret information, distribute resources, handle risk and apply data for decision making.

सम्राट अशोक की धम्मनीति प्राचीन भारतीय इतिहास में नैतिक शासन, अहिंसा, धार्मिक सहिष्णुता, मानवीय कल्याण और शांतिपूर्ण सह-अस्तित्व की एक महत्त्वपूर्ण विचारधारा के रूप में प्रतिष्ठित है। अशोक के शिलालेखों एवं स्तंभलेखों में निहित धम्म के सिद्धांत केवल व्यक्तिगत आचरण तक सीमित नहीं थे, बल्कि वे सामाजिक सद्भाव, प्रजा के कल्याण, विभिन्न धार्मिक परंपराओं के प्रति सम्मान तथा अन्य राज्यों के साथ मैत्रीपूर्ण संबंधों की भावना को भी अभिव्यक्त करते हैं। प्रस्तुत शोध का उद्देश्य अशोक के धम्मलेखों में प्रतिपादित नैतिक मूल्यों का विश्लेषण करना तथा आधुनिक भारतीय कूटनीति के संदर्भ में उनकी प्रासंगिकता का अध्ययन करना है। समकालीन भारतीय विदेश नीति में शांति, संवाद, अंतरराष्ट्रीय सहयोग, सांस्कृतिक संबंध, विकासात्मक साझेदारी और वैश्विक कल्याण जैसे विषयों का विशेष महत्त्व है। इन विषयों का अशोक की धम्मनीति से वैचारिक साम्य स्थापित किया जा सकता है, यद्यपि प्राचीन साम्राज्य की शासन-व्यवस्था और आधुनिक राष्ट्र-राज्य की विदेश नीति के ऐतिहासिक एवं राजनीतिक संदर्भ भिन्न हैं। यह अध्ययन ऐतिहासिक, वर्णनात्मक एवं विश्लेषणात्मक पद्धति पर आधारित है, जिसमें अशोक के प्रमुख धम्मलेखों, बौद्ध साहित्य तथा आधुनिक भारतीय विदेश नीति से संबंधित प्रामाणिक स्रोतों का अध्ययन किया जा सकता है। शोध का केंद्रीय तर्क है कि अशोक के धम्मलेख नैतिकता-आधारित शासन, सहिष्णुता और शांतिपूर्ण संबंधों के अध्ययन के लिए एक महत्त्वपूर्ण ऐतिहासिक आधार प्रदान करते हैं। इन मूल्यों का समकालीन कूटनीति के संदर्भ में विश्लेषण भारत की ऐतिहासिक वैचारिक परंपरा और वर्तमान वैश्विक भूमिका के बीच संबंधों को समझने में सहायक हो सकता है।

Government agencies in India are increasingly relying on algorithm-based systems for tasks such as identifying beneficiaries for welfare schemes and policing; yet, there is no law in India governing the use of artificial intelligence at the government level. This article examines whether the Constitution of India, as interpreted by the Supreme Court, provides adequate standards for the review of such systems, and whether the existing legal and policy framework renders that standard enforceable. Employing legal principles and comparative methods, this analysis covers Articles 14, 19, and 21; the 'proportionality jurisprudence' established in the Puttaswamy Aadhaar case, and Anuradha Bhasin case; the Digital Personal Data Protection Act, 2023, and its 2025 rules; and the India AI Governance Guidelines, 2025. Additionally, these are compared with the frameworks of the European Union, the Netherlands, the United Kingdom, Canada, and the United States. This article finds that constitutional principles are largely adequate, but their implementation is hindered by information asymmetry, exemptions granted to the executive under data protection laws, the lack of a right to challenge automated decisions, and a reliance on voluntary principles. It is argued that this shortcoming is essentially procedural rather than substantive. Furthermore, it proposes a limited and risk-based legal framework for public-sector AI, incorporating elements such as impact assessments, public registers, reasoned explanations, meaningful human review, and a 'burden-shifting' rule for judicial review. The conclusion is that constitutional control over the power of algorithms depends less on new rights and more on making existing rights legally enforceable.

Background: Biopathography provides a longitudinal perspective on case-taking by examining the evolution of illness alongside significant life events, transitions and individual responses. It extends the conventional clinical history by considering how the patient's present state has developed over time.
Case presentation: A 39-year-old woman presented with lumbar pain radiating to the left lower limb, vaginal pricking pain, lower abdominal pain, urinary frequency and urinary incontinence. Pap smear examination reported non-specific cervicitis, with no evidence of intraepithelial lesion or malignancy. Her history included recurrent respiratory complaints during childhood, initially regular menstruation, profuse postpartum bleeding following her second delivery, recurrent heavy menstrual bleeding, severe anaemia requiring packed red-cell transfusion, and subsequent reduction and irregularity of menstrual flow. Pelvic and urinary manifestations developed later. Her lumbar complaints were considered separately in relation to their chronology and the physical demands of her daily life.
Biopathographical interpretation: The case was examined through the chronological progression of symptoms, reproductive transitions, changes in menstrual expression, associated clinical findings and the patient's responses to family and personal circumstances. A parallel history of lumbar complaints was identified. The analysis emphasised temporal relationships without assuming direct causation.
Conclusion: Biopathographical interpretation may help organise multiple complaints into a coherent longitudinal account, supporting a more individualised understanding of the patient's clinical history. The approach complements, rather than replaces, diagnostic assessment and appropriate clinical investigation.

The study assessed the contribution of entrepreneurship training to the reduction of youth crime among Reconstructed Living Labs Beneficiaries in Iringa Municipality. A mixed-methods research approach was employed using a cross-sectional research design. The study involved 92 youth respondents selected through simple random sampling and 8 key informants selected purposively. Primary data were collected using questionnaire and interview guides, while secondary information was obtained from relevant reports and official documents. Quantitative data were analysed using descriptive statistics in the Statistical Package for the Social Sciences (SPSS) version 26, while qualitative data were analysed thematically. The findings showed that entrepreneurship training contributed to youth crime reduction by improving business knowledge, practical entrepreneurial skills, self-employment readiness, problem-solving skills and the ability of youth to engage in lawful income-generating activities. The findings further indicated that entrepreneurship training encouraged responsible decision-making and reduced engagement in risky behaviours associated with youth crime. However, limited access to some entrepreneurship support services affected the extent to which the training could translate into sustainable economic opportunities for youth. The study concludes that entrepreneurship training contributes to the reduction of youth crime by enhancing youth employability, self-reliance and participation in lawful economic activities. The study recommends strengthening practical entrepreneurship training and improving access to complementary business support to enable trained youth to apply the skills acquired and sustain lawful income-generating activities.

This study assessed the contribution of the Luduga Mawindi Water Supply Project to the diversification of household economic activities in Mbarali District, Mbeya Region, Tanzania. The study guided by the Sustainable Livelihoods Framework of which a mixed-methods approach and a cross-sectional research design were used. A sample of 100 beneficiary households was used from Mawindi and Ipwani wards using Yamane’s formula. The study used simple random sampling to select the Luduga Mawindi project’s beneficiaries. Sixteen key informants and participants in Focus Group Discussions were purposively selected for qualitative information. Quantitative data was analysed using the Statistical Package for the Social Sciences (SPSS) software version 27, while qualitative data were analysed through thematic analysis. The findings showed that the project contributed to diversification of household economic activities through increased participation in livestock keeping, irrigated farming, food sales, brick making and water sales, while fishing showed a limited change. The project also contributed to increased household income-generating opportunities by improving access to water for productive activities and reducing the time spent obtaining water. The study concludes that the the Project made a positive contribution to the diversification of household economic activities by improving conditions for productive water use and creating opportunities for households to engage in multiple economic activities. The study recommends strengthening the reliability and accessibility of the water supply system and promoting productive uses of water, particularly irrigation, livestock keeping, food processing and other small-scale economic activities.

With the rapid growth of technological advancement everything got connected digitally. And with this expansion of technology cyber-attacks also increased which now forces states to come up with a robust infrastructure to protect its citizens from digital threats. Keeping in mind this view different nations tried to come up with have data protection and cybersecurity regulations, still due to fast paced developments in technology specifically Artificial Intelligence the cybersecurity risks and threats have been doubled. Therefore, in this digital age, the concepts of data protection and cyber security become absolutely necessary.
This paper examines the emerging threats in the digital world and how these threats can be tackled with the regulations enacted by different nations. It also explores whether the created rules and regulations are sufficient to deal with the increasing cyber-attacks and how these regulations can be made more effective to protect the data of people and systems from external attacks. An attempt has been made through this paper to understand the different safeguards that are available to protect data from cyber-attacks and how the legal framework can be improved to protect the cyber systems.

Agent banking technology has become an important channel for extending financial services beyond conventional banking outlets and supporting digitally enabled business activities. Still, empirical evidence linking agent banking technology specifically to entrepreneurial practices among financial technology (FinTech) operators in Nigeria remains limited. This study examined the relationship between agent banking technology and entrepreneurial practices of financial technology firms in Ondo State, Nigeria. The study adopted a quantitative cross-sectional survey design. Data were obtained from 388 FinTech operators across selected Local Government Areas in Ondo State using a structured questionnaire. Agent Banking Technology was operationalised as the independent variable, while Entrepreneurial Practices constituted the dependent variable. Data were analysed using simple linear regression with the Statistical Package for the Social Sciences (SPSS). The results revealed a very strong positive relationship between agent banking technology and entrepreneurial practices (R = .945). Agent banking technology explained 89.3% of the variation in entrepreneurial practices (R² = .893; Adjusted R² = .892). The regression model was statistically significant (F(1,386) = 3205.392, p < .001). Agent Banking Technology also had a positive and statistically significant effect on Entrepreneurial Practices (B = .992, β = .945, t = 56.616, p < .001). The study concludes that agent banking technology is strongly associated with entrepreneurial practices among FinTech operators in Ondo State. The findings highlight the importance of reliable agent-banking infrastructure, operational capacity, digital connectivity, training and supportive regulatory arrangements for digitally enabled entrepreneurial activities.

This paper describes the implementation of an Internet of Things (IoT)-based Smart Space Suit Health Monitoring prototype built using an ESP32 development board, a MAX30102 optical sensor, and a Node.js-based AstroPulse monitoring platform. The sensor acquires red and infrared photoplethysmographic signals for algorithmic estimation of pulse rate and peripheral oxygen saturation (SpO₂). Measurements are processed by the ESP32 and transmitted through Wi-Fi using HTTP/JSON to a web application that stores data in SQLite and provides live visualisation, history and alert functionality. The implementation verified sensor communication, changes in optical readings with finger placement, wireless connectivity, successful HTTP ingestion and dashboard display. However, pulse and SpO₂ outputs remained intermittent and unstable, and further calibration and validation are required. A basic glove-mounted demonstrator was also assembled using Velcro straps and direct jumper connections.

Despite the fact that women’s representation in political leadership positions in Tanzania has increased through government efforts and legal frameworks, yet gender inequality in political leadership is problematic because the political space continues to foster unequal power relations, which give men an advantage over women. This study investigates the effects of assets ownership to women representation in leadership political position in Iringa Municipality. The study adopted a mixed-method research approach targeting women participating in political activities in the study area. A sample size of 63 respondents and 5 key informants were drawn using simple random and purposive sampling techniques respectively. Semi-structured questionnaire and interview methods were used to collect primary data from the respondents. Analysis of quantitative data was descriptively done, while qualitative data was analysed by using content analysis and findings were presented in tables and figures. The study found that most respondents had an opinion that assets owned can support women participation in political activities by support political campaigns, political meetings, and secure collateral for credits important for participation in political activities. The study found that assets ownership influence women representation political leadership and provide opportunities for women to interact with people connected with political and leadership activities. The study concludes that ownership of assets contributed to increased women’s representation in political leadership positions through the use of productive assets and social capital. The study recommends to Iringa Municipal Council Authority to strengthen asset-development support for women through productive asset management and asset-financing services.

Child abuse remains a significant child-protection concern, with parental socio-economic conditions, parenting practices, family circumstances, and social norms potentially influencing children’s vulnerability to abuse. This study examined parental-based factors contributing to child abuse in Iringa Municipality, focusing on Ruaha and Isakalilo wards. The study adopted a cross-sectional mixed-methods design. The study population comprised 4,676 parents and caregivers, from which 98 respondents were selected using proportional allocation and simple random sampling. In addition, eight key informants comprising social welfare officers, gender desk officers, teachers, and community leaders were purposively selected. Quantitative data were collected using structured questionnaires and analysed using frequencies, percentages, and correlation analysis, while qualitative data were collected through semi-structured interviews and analysed thematically. The findings indicate that 56.1% of respondents perceived low parental knowledge as a contributing factor to child abuse, while 60.2% reported that parental occupation influences the occurrence of child abuse. Furthermore, 61.2% associated household poverty with child abuse, while 56.1% indicated that parental marital status influences child protection. Social norms towards violence were identified as an important factor by 87.8% of respondents, while 65.3% perceived cultural beliefs as having potentially harmful effects on child discipline and protection. Qualitative findings further highlighted poverty, inadequate supervision, poor parenting practices, parental alcohol abuse, family conflict, parental separation, and limited knowledge of child protection as interconnected factors affecting children’s safety and wellbeing. The study concludes that child abuse is influenced by multiple interacting parental and household factors rather than a single cause. The study recommends strengthening parental education, positive parenting and non-violent discipline programmes, economic empowerment for vulnerable families, counselling and rehabilitation services for parents affected by substance abuse, and coordination among child-protection stakeholders in Iringa Municipality.

The study examined socio-cultural factors hindering men’s participation in Village Community Banks (VICOBA) in Iringa Municipality, Tanzania. The study focused on community beliefs and norms, peer influence, family responsibilities, community perceptions and social interaction as socio-cultural factors affecting men’s participation in VICOBA. A quantitative approach with a cross-sectional research design was used. Primary data were collected using questionnaires and semi-structured interviews. Quantitative data were analysed using frequencies and percentages in Statistical Product for the Social Solutions (SPSS) Version 26, while qualitative data were analysed thematically. The findings showed that community beliefs and norms influenced men’s willingness to participate in VICOBA, while peer influence affected men’s decisions to join and remain in groups. Family responsibilities also affected attendance and involvement in group activities. Community perceptions influenced how men viewed participation in VICOBA, while social interaction affected men’s involvement in meetings and other group activities. The study concludes that socio-cultural factors hinder men’s participation in VICOBA by influencing their willingness to join, attend meetings and take part in group activities. The study recommends community sensitisation on the benefits of VICOBA, increased awareness among men and their families, and the promotion of positive community perceptions and social interaction to strengthen men’s participation in VICOBA.

The ecological challenges of the twenty-first century and the acceleration of the triple planetary crisis require a fundamental modernization of geographical literacy in secondary education. This paper investigates the epistemological and methodological trajectories of conceptualizing the “World Ocean” framework in lower secondary school geography, directly reflecting the title’s dual focus on the evolution of oceanographic paradigms and geography education. The study opens with a macro-historical review of scientific oceanographic paradigms, tracing the evolution from nineteenth-century descriptive natural history catalogs to contemporary ecocentric, geo-systemic models. Using qualitative comparative analysis frameworks the pedagogical section provides a strict comparative assessment of two leading state-approved model curricula implemented within the New Ukrainian School (NUS) reform for Grade 7 (“Geography of Continents and Oceans”): the curriculum by Zapototskyi et al. (2022) and the alternative framework by Kobernik et al. (2022).
The results reveal a critical structural tension in sequencing and cognitive development. The Zapototskyi et al. (2022) model employs an integrated, inductive trajectory that leverages digital web-GIS applications to construct a localized sense of place. Conversely, the Kobernik et al. (2022) curriculum deploys a deductive, structural-systemic pathway, positioning the World Ocean upfront as the foundational thermodynamic engine of planetary climate stability and feedback loops. The paper demonstrates that both frameworks robustly reflect modern scientific imperatives by integrating marine ecosystems, data sovereignty, and sustainability metrics into geographical education. The study concludes that these competing curricula are complementary rather than contradictory, offering a scalable pedagogical matrix to transition secondary geography from marine extractivism to shared ecocentric responsibility.

Digital communication has reshaped how retail investors gather financial information and arrive at investment choices. Platforms such as YouTube, Instagram, Facebook, WhatsApp, Telegram, and other online communities are now widely used to access content on mutual funds, systematic investment plans (SIPs), expected returns, risk, diversification, and portfolio management. Although this shift has made financial information easier to reach, questions about the accuracy and trustworthiness of what circulates on these platforms remain unresolved. This study is designed to explore how social media shapes mutual fund selection and investment decisions among retail investors in Raipur District, Chhattisgarh. It centres on seven constructs — social-media exposure, perceived usefulness, perceived credibility, influencer trust, social influence, financial literacy, and risk perception — as potential drivers of investment behaviour. A quantitative, cross-sectional design is planned, with primary data to be gathered via a structured questionnaire. Once collected, the data will be examined using descriptive statistics, reliability testing, correlation, factor analysis, and multiple regressions.
By generating district-level evidence from Raipur, the study aims to add to the expanding body of work on digital financial behaviour. Its findings are intended to be of value to mutual fund houses, financial advisers, investor-education bodies, regulators, and retail investors themselves in weighing the benefits and risks of social-media-based financial information.

Soil nutrient analysis is essential for precision agriculture in ensuring proper fertiliser utilisation, increasing productivity, and sustainable farming. Traditional lab tests are tedious, expensive, and not feasible for mass usage. In this paper, four state-of-the-art scientific papers that have implemented ML/DL approaches to address problems related to soil nutrient analysis are reviewed. The first paper used CNN on soil RGB images taken from Karnataka, India, which achieved 95.51% accuracy in classifying three different soil types, namely gravel, sand, and silt. The second paper incorporated IoT-enabled sensor devices to gather soil micronutrient data from mulberry farms in Tamil Nadu. It used an ELM classifier with 88% accuracy after applying k-fold cross validation on the data. In the third paper, hyperspectral cameras (398-1003 nm) were mounted on UAVs to capture spectral images of a 65,000 m² farmland in Shaanxi, China. RF-DE feature selection was employed alongside BP neural networks to predict available potassium with R² up to 0.95. Finally, a Bayesian-optimised 1D-CNN was proposed by the fourth paper on the pan-European LUCAS topsoil dataset (approximately 20,000 samples). It scored R² of 0.75 (nitrogen), 0.66 (potassium), and 0.46 (phosphorus), with 25% faster training times.

ThisstudyexaminedsocialfactorsthatinfluencecouplestodivorceinMagharibiADistrict,Zanzibar.Thestudyusedbothquantitativeandqualitativeapproachinvolvingtheuseofquestionnairesurvey,keyinformantinterviewsandfocusgroupdiscussionsfordatacollection.DatawereanalyzedusingSPSSforquantitativedataandthematicanalysisforqualitativedata.Resultsindicatethatfamilyinterference,poorcommunication,addictiononalcoholism,infidelityandageatemarriage,weremajorsocialfactorsinfluencingdivorceamongrespondents.Thesesocialproblemsweakenedtrust,intimacy,loveandcooperationbetweenspouses,ultimatelymakingitdifficultformarriagessucceed.Inmanycasestheycreatedmisunderstandings,emotionaldistanceandfrequentconflictswithinthefamily.Consequently,thecontinuedoccurrenceoftheseproblemsmadeitdifficultforcouplestomaintainhealthyrelationshipsandsustaintheirmarriages,ultimatelycontributetomaritalbreakdownanddivorce.Thestudyconcludesthatissuessuchasfamilyinterference,infidelity,poorcommunication,domesticviolenceandalcoholismweremajorcausesofdivorce.Thestudyrecommendstheneedforawarenesscampaignstochangeharmfulgendernorms,stigmaandinterferencefromextendedfamilyinmarriages.Communityleadersshouldpromotethevaluesofmutualrespect,love,trustandcommunicationbetweencouples

Credit risk assessment and retail loan underwriting are high-stakes financial operations traditionally governed by manual appraisal, which exhibits significant latency, operational cost, and subjective variability across loan officers. While modern black-box machine learning models offer predictive accuracy, stringent regulatory compliance mandates (such as the Fair Credit Reporting Act, GDPR Article 22, and digital lending directives) necessitate auditable, intrinsically explainable decision workflows. This paper presents an end-to-end, interpretable machine learning framework for consumer loan approval prediction paired with an interactive, guardrailed decision-support system. Using a benchmark dataset of 4,269 loan applications, we implement a leakage-safe data engineering pipeline featuring two-sided percentile winsorization (1st/99th percentiles) and derived financial solvency ratios. We formulate a class-weighted, ℓ2-regularized Logistic Regression architecture encapsulated within a single scaling pipeline, optimized via stratified 5-fold cross-validation. On a held-out test partition (n = 854), the proposed model achieves an accuracy of 91.9%, precision of 95.1%, recall of 91.7%, F1-score of 93.4%, and a ROC-AUC of 0.974, dramatically outperforming the majority-class baseline (accuracy 62.2%). Hyperparameter sensitivity analysis reveals that the regularizer exhibits a broad plateau (C ∈ [10−2, 102]), proving model stability. Coefficient-level attribution indicates that the CIBIL credit score is the primary determinant (β = +3.63), outweighing secondary asset and liability features by more than five-fold. To prevent unsafe extrapolations in real-world deployment, we engineer a multi-layered defense-in-depth guardrail framework comprising input validation, distribution-drift warnings, out-of-distribution hard stops, sub-prime credit floors, and debt-to-income overrides. The resulting decision-support application provides transparent, per-applicant counterfactual explanations for responsible underwriting assistance.

Financial knowledge may support informed financial choices, but self-assessed understanding and demonstrated competence are different measures. This study describes perceived financial literacy and reported saving and investment decisions among 50 students at DMI St. Eugene University, Chipata Campus, Zambia. A descriptive cross-sectional survey used a 20-item structured questionnaire and convenience sampling. Aggregate responses were analysed using frequencies and percentages. Ninety per cent strongly agreed that they understood interest rates and inflation; all strongly agreed with statements about risk-return trade-offs and diversification. Eighty per cent reported having made or currently holding an investment. Small business was the most frequently reported saving or investment category, accounting for 70% of all responses. Seventy per cent reported saving or investing frequently or very frequently. Financial knowledge was the most frequently selected greatest influence on decisions, followed by expected return. Responses also showed strong agreement that financial knowledge was relevant to decision-making. These are perceptions and reported practices, not objective literacy scores or statistically tested relationships. Product categories and participation answers cannot be linked using aggregate data, and the single-campus convenience sample limits generalisation. The findings support practical financial education paired with objective assessment and evaluation of actual behaviour. Respondent-level data, clearer product definitions and prospective research are needed to assess how knowledge relates to investment choices.

Sustainable building practices can reduce the environmental impacts of construction and improve the long-term performance of buildings. Their adoption, however, depends on practitioners’ knowledge, project-level implementation and the conditions that enable or constrain their use. This study assessed the level of adoption of sustainable building practices in construction projects across Abuja, Nigeria. It examined respondents’ familiarity with and understanding of the practices, their reported implementation, perceived benefits and barriers, and proposed improvement strategies. A descriptive mixed-methods approach was used. Data were collected through questionnaires and semi-structured interviews. Of the 396 questionnaires distributed, 350 were returned and considered usable, representing an 88.4% response rate. Questionnaire responses were analysed using descriptive statistics, while interview findings were summarised thematically. Respondents reported moderate familiarity (mean = 3.67) and understanding (mean = 3.68) of sustainable building practices. Reported implementation (mean = 3.48) and adoption (mean = 3.47) were comparatively lower. Perceived benefits and barriers both recorded an overall mean of 3.97, while support for proposed improvement strategies was higher (mean = 4.04). High initial costs, limited stakeholder knowledge, weak policy enforcement and restricted availability of sustainable materials were identified as prominent barriers. Financial incentives, professional training and stronger enforcement received substantial support as potential responses. The findings indicate that recognition of the value of sustainable building practices has not translated fully into consistent project-level adoption. Progress will require coordinated measures to improve access to finance and materials, strengthen professional capacity, and implement relevant policies more effectively. As the study relies on stakeholder reports and descriptive analysis, its results describe reported perceptions and practices; they do not establish causal relationships or independently verify building performance.

Occupational health and safety (OHS) remains a critical concern in construction due to workers’ exposure to multiple workplace hazards. This study assessed OHS practices on construction sites in the Abuja Municipal Area Council (AMAC), Abuja, Nigeria. A cross-sectional survey was conducted using structured questionnaires and key informant interviews. Of 395 questionnaires administered, 350 valid responses were obtained, representing an 88.6% response rate, alongside 10 key informant interviews. Data were analysed using descriptive statistics and thematic analysis. The findings indicate generally satisfactory OHS implementation, with an overall mean of 3.75 (SD = 1.25). Safety meetings recorded the highest mean (3.78), followed by safety signs and warnings (3.77), first-aid facilities (3.76) and worker supervision (3.76). Safety training recorded a mean of 3.72, while regulatory compliance and risk assessment both recorded 3.73. PPE provision had the lowest overall mean (3.66), with hearing protection (3.42), PPE sufficiency (3.44) and damaged-PPE replacement (3.47) indicating notable weaknesses. Emergency-response training (3.60) and hazard-identification training (3.58) were also comparatively weak. The study concludes that OHS systems are generally established, but implementation remains uneven. Strengthening continuous training, hazard-specific PPE, risk management, regulatory enforcement and management accountability is recommended.

Cost overruns remain a persistent challenge in mass housing projects in Nigeria, particularly in the Federal Capital Territory (FCT), Abuja, where inflation, material-price volatility, delayed fund disbursement, regulatory constraints and procurement challenges can undermine project cost performance. This study assessed cost-control strategies in mass housing projects in the FCT, Abuja, with specific emphasis on the major causes of cost overruns, conventional and digital cost-control practices, contextual challenges, and procurement methods. A quantitative descriptive survey design was adopted. Data were collected from construction professionals and other stakeholders involved in mass housing delivery using a structured questionnaire. A total of 413 questionnaires were administered, of which 404 valid responses were available for analysis. Data were analysed using descriptive statistics, Relative Importance Index (RII), paired-samples t-test, multiple linear regression and one-way ANOVA with Tukey HSD post-hoc analysis. The findings identified fluctuation in building-material prices (RII = 0.904), delayed disbursement of project funds (RII = 0.882) and high inflation (RII = 0.870) as the leading causes of cost overruns. Conventional cost-control strategies were significantly more utilised than digital technologies (Mean = 4.10 versus 3.23; t(403) = 19.17, p < .001), with high technology costs and inadequate staff competency identified as major barriers to digital adoption. Regulatory challenges (β = −0.421, p < .001) and socio-political challenges (β = −0.248, p < .001) significantly reduced cost-control effectiveness, whereas environmental challenges were not statistically significant (p = .065). Procurement method also significantly influenced cost performance, with Traditional Design-Bid-Build and Design and Build outperforming Direct Labour. The study concludes that effective cost control in FCT mass housing requires an integrated approach combining macroeconomic risk management, institutional efficiency, phased digital adoption and appropriate procurement strategies.

Access to justice is a cornerstone of democratic societies and the rule of law. However, for economically marginalized communities, this ideal often remains out of reach. This study investigates the economic barriers that hinder the poor from accessing legal representation and participating meaningfully in the justice system. The research employs a mixed-methods approach, combining statistical analysis of legal aid accessibility with in-depth interviews of individuals who have faced financial constraints in legal proceedings. Key findings reveal that the prohibitive costs of hiring private legal counsel, coupled with the limited capacity and inconsistent quality of publicly funded legal aid services, create significant hurdles for low-income individuals. Additionally, indirect costs—such as transportation, time off work, and bureaucratic complexity—further discourage engagement with the legal system. The study also examines the intersectionality of poverty with other vulnerabilities, including gender, race, and rural residency, which amplify the barriers to justice. Despite existing legal aid policies and frameworks, the current systems often fail to meet the growing demand or ensure timely and effective representation. The paper concludes with policy recommendations aimed at increasing state investment in legal aid, incentivizing pro bono legal services, enhancing legal literacy, and exploring alternative dispute resolution mechanisms that are more accessible to the poor. By addressing these economic barriers, the study emphasizes the urgent need for structural reforms to uphold the principle of equal justice for all.

Legal-family classification is a practical device in comparative law, but it can become misleading when a label is treated as a complete description of a country. A system may inherit one tradition in its courts, rely on legislation in several fields, and recognise additional norms through its constitution or community practices. This paper examines classification as a method rather than as a fixed taxonomy. It outlines the principal traditions commonly discussed in comparative-law literature and considers what their use can—and cannot—explain.
The discussion then examines India and South Africa. India’s courts and doctrine of precedent reflect a substantial common-law inheritance, while its written Constitution, extensive legislation, personal-law arrangements, and context-specific customary practices complicate any single-family description. South Africa’s private law is strongly shaped by Roman-Dutch law, alongside English influence, African customary law, and a constitutional order that gives the Constitution priority over inconsistent law.
The study uses a qualitative, doctrinal and comparative method. It examines selected scholarship and constitutional provisions; it does not use interviews, surveys, or statistical data. The central proposition is that legal families are useful as starting points, provided the researcher states the criterion being used and then tests it against the law of the jurisdiction. A layered description—historical, institutional, source-based, constitutional, and social—offers a more transparent account than an exclusive label.

This study examined the support provided by head teachers in implementing inclusive education policies in public primary schools in Kilolo District, Tanzania. The study was guided by the Social Model of Disability and employed a qualitative approach within a convergent parallel mixed-methods design. Data for this objective were collected through semi-structured interviews with 13 purposively selected head teachers and analysed using thematic analysis.
The findings revealed that head teachers facilitate the implementation of inclusive education through instructional supervision, management of teaching and learning resources, teacher professional development and mentoring, promotion of inclusive school environments, collaboration with parents and communities, teacher motivation, and continuous monitoring of learners' progress. These leadership practices strengthen teachers' capacity to address learner diversity and promote equitable participation of learners with special educational needs. However, inadequate teaching and learning resources, limited professional development opportunities, and insufficient institutional support constrain the effective implementation of inclusive education policies.
The study concludes that effective implementation of inclusive education depends on strong instructional leadership supported by adequate resources and institutional commitment. It recommends strengthening head teachers' capacity through continuous professional development and increasing investment in inclusive education resources to improve policy implementation in public primary schools.

The Weed Identification Using Deep Learning and Image Processing in Vegetable Plantation is an intelligent embedded system designed to automatically identify weeds present among vegetable crops. The system uses a Raspberry Pi as the main controller and a USB web camera to continuously capture plant images in real time. The captured images are processed directly on the Raspberry Pi using a pre-trained YOLO deep learning model. The model is trained with predefined images of different types of weeds to detect and classify them accurately. When a weed is detected, the system identifies the type of weed and activates a buzzer to provide an immediate alert. An LCD display shows “Weed Detected” along with the detected weed name. If no weed is detected, the LCD displays “Healthy Crop – No Weed Detected.” The complete image processing and weed identification process is performed locally on the Raspberry Pi without requiring an internet connection. The system provides real-time monitoring of weeds in vegetable plantations and helps reduce the need for manual inspection. It supports efficient crop monitoring and improved crop management. The proposed system is simple, low-cost, and efficient for real-time weed identification. It can help farmers monitor weeds more easily and take timely action. Overall, the system provides an automated and intelligent solution for weed detection in vegetable plantations.

This study examined community attitudes toward supporting the employment of ex-prisoners in Iringa District Council, Tanzania. A mixed-methods approach with a cross-sectional research design was used. Quantitative data were collected from 92 respondents through structured questionnaires, while qualitative data were obtained from 10 key informants through semi-structured interviews. Quantitative data were analysed using frequencies and percentages, while qualitative data were analysed thematically. The findings showed that community attitudes toward the employment of ex-prisoners were generally favourable. About 78.3% of respondents were willing to offer employment opportunities to ex-prisoners, 62.6% had supported or considered employing an ex-prisoner and 74.7% were willing to recommend an ex-prisoner for employment. However, only 40.0% reported that local leaders encouraged the employment of ex-prisoners, while 62.0% reported witnessing community members discouraging such employment. Qualitative findings further indicated that concerns about criminal records, trustworthiness, fear of reoffending and limited leadership involvement could hinder access to employment. A paired-samples analysis also showed a significant difference between willingness to support employment and reported employment-related behaviour, t(90) = 3.74, p < .001. Guided by the Theory of Planned Behaviour, the study concludes that although community attitudes provide a favourable basis for employment-based reintegration, stronger leadership involvement, community sensitization, employer engagement and employment facilitation are needed to translate positive attitudes into actual employment opportunities for ex-prisoners.

This study was conducted to find the relationship between Differentiated Instruction to address learning loss and learner's progress through Curriculum Management Support System (CMSS) results in Malaybalay City District 5 elementary schools of Malaybalay City Division, School Year 2023-2024. The respondents of the study were all teachers of District 5. Complete Enumeration was used as a sampling procedure. The instrument of the study was crafted by the researcher. Frequency count and percentage, Mean and Standard Deviation, and Pearson r Product-Moment Correlation Coefficient or Pearson r were the statistical tools utilized.
The following findings were revealed: The majority of the respondents belong to the age bracket of 31-40. Female teachers were the overwhelming majority, with Teacher 1 as the majority teaching position. Most of the respondents fall within 1-3 training courses attended and received technical assistance. There was a very large extent of implementation of Differentiated Instruction to address learning loss in terms of content, process, projects, and learning environment. Majority of learners achieved average grades between 80 and 84 or Satisfactory Level. Among the variables analyzed, age, present teaching position, and technical assistance on how to conduct Differentiated Instruction demonstrate significant relationships with learners' progress through CMSS results. Age and present teaching position exhibit negative correlations, indicating that as age and higher teaching positions increase, learners' progress tends to decrease. Therefore, we reject the null hypothesis which states that there is no significant relationship between the extent of implementation of Differentiated Instruction to address learning loss and the learner's progress through CMSS results.
The following recommendations are: Teachers may recognize and respect the varied backgrounds and experiences of their learners. School administrators may endorse and promote Differentiated Instruction. Learners may uphold a growth attitude. Adopt a mentality of gaining knowledge from errors, seeking input, and establishing objectives. The Department of Education may provide sufficient technical and technological resources and support to ensure that educators are provided with access to educational technology resources and training to effectively implement Differentiated Instruction.

21वीं सदी में भूमंडलीकरण (Globalization), सूचना प्रौद्योगिकी (Information Technology) और बाजारवाद (Consumerism) के अभूतपूर्व प्रभाव ने विश्व भर की भाषाओं के सामाजिक, सांस्कृतिक और आर्थिक ढांचों को गहराई से प्रभावित किया है। इस परिवर्तनकारी दौर में हिंदी केवल अभिव्यक्ति और लोक-संवाद का माध्यम मात्र न रहकर एक जटिल एवं बहुआयामी आत्मसंघर्ष के दौर से गुजर रही है। एक ओर जहाँ जनसांख्यिकी और बोलचाल के धरातल पर हिंदी दुनिया की सबसे अधिक बोली जाने वाली शीर्ष भाषाओं में शामिल है और स्मार्टफोन, इंटरनेट तथा सोशल मीडिया जैसी डिजिटल क्रांतियों के कारण इसके उपयोगकर्ताओं तथा कंटेंट के परिमाण में ऐतिहासिक उछाल आया है; वहीं दूसरी ओर यह भाषा वैश्विक प्रभुत्व वाली भाषा अंग्रेजी के समक्ष उच्च शिक्षा, मौलिक अनुसंधान, तकनीक, न्यायपालिका, कॉर्पोरेट रोजगार तथा अपनी मूल व्याकरणिक व सांस्कृतिक स्वायत्तता को बनाए रखने के लिए निरंतर संघर्षरत है। इसके अतिरिक्त, बाजारवाद और उपभोक्तावादी संस्कृति के दबाव में विशुद्ध हिंदी के स्थान पर &#39;हिंग्लिश&#39; (Hinglish) के बढ़ते प्रचलन ने इसकी व्याकरणिक शुद्धता, समृद्ध शब्दावली और लाक्षणिक सौंदर्य पर प्रश्नचिह्न लगा दिया है। यह शोध पत्र 21वीं सदी में हिंदी भाषा के इस आत्मसंघर्ष के बहुआयामी स्वरूप को गहराई से रेखांकित करता है। इस अध्ययन में स्पष्ट शोध उद्देश्यों का निर्धारण किया गया है, जिसके अंतर्गत भूमंडलीकरण व डिजिटल क्रांति के प्रभाव, ज्ञान-विज्ञान की भाषा के रूप में उपस्थित चुनौतियों तथा इसके भावी विकास की रणनीतियों का अनुशीलन शामिल है। शोध पत्र में विषय से संबंधित पूर्ववर्ती अध्ययनों की साहित्य समीक्षा (Review of Literature) तथा शोध-रिक्ति (Research Gap) को दर्शाया गया है, और विश्लेषणात्मक व गुणात्मक शोध विधि (Research Methodology) का प्रयोग किया गया है। अंतिम चरण में, यह पत्र हिंदी को केवल मनोरंजन या बाज़ार की भाषा तक सीमित न रखकर इसे नई शिक्षा नीति (NEP 2020), आर्टिफिशियल इंटेलिजेंस (AI), नेचुरल लैंग्वेज प्रोसेसिंग (NLP), रोजगारपरकता और अन्य भारतीय भाषाओं के साथ समन्वय के माध्यम से एक सक्षम &#39;ज्ञान-भाषा&#39; (Knowledge Language) के रूप में पुनर्रचित करने हेतु व्यावहारिक दिशाएँ एवं सुझाव प्रस्तुत करता है।

Sustainable rural water services depend on whether households are willing and able to meet recurrent operation and maintenance costs, yet the dynamics of financial contribution under Tanzania’s agency-led, community-managed water model remain thinly documented. This study examined the financial contribution of communities to the management of Rural Water Supply and Sanitation Agency (RUWASA) water projects in Mbarali District Council, Mbeya Region. A mixed-methods, cross-sectional design combined a survey of 60 households with key informant interviews and six focus group discussions across six villages. Results show that 91.7% of households contribute and 96.7% are willing to pay, with 75% paying Tsh. 5,000-10,000 per contribution. However, 81.7% had defaulted at least once, mainly because of lack of money (66.7%) rather than unwillingness. Generally, low income (46.7%), lack of trust in fund management (30%), and dissatisfaction with services (21.7%) were the leading challenges. Although 86.7% knew how funds are used, disclosure relied on public meetings (70%) and verbal announcements (25%), with notice boards used by only 5%. The study concludes that financial contribution is constrained less by unwillingness than by seasonal household poverty, limited written transparency, and service reliability, and recommends written financial reporting, seasonally flexible payment arrangements, and more reliable service delivery.

This study examined challenges faced by caregivers accessing rehabilitation services for children with cerebral palsy in Iringa Municipality, Tanzania. The used a qualitative approach and explanatory design. Forty participants were purposively selected: 30 caregivers and 10 rehabilitation service providers. Data were collected through three focus group discussions with caregivers and key informant interviews with providers, then analysed thematically. Findings show there are barriers such as there being not enough rehabilitation centres in the Municipality and not having enough trained personnel or proper equipment and therapy programs. These therapy programs are far and hence take longer time to travel and long waiting times and coordination between service providers is weak. Costs of transport, and low incomes for patients plus not enough financial support make it hard to get access and to attend regularly. There is not enough information and guidance which kept caregivers from knowing and getting the services they need.. The study concludes that access to rehabilitation services in Iringa Municipality is limited due to inadequate services and lack of resources, geographical barriers and weak coordination. It suggests that there should be an expansion of rehabilitation and community-based services, bringing in more trained personnel, making equipment more available, strengthening the systems for appointments and follow-ups and reduce waiting times. Health facilities, rehabilitation centres, social welfare offices, schools, and other stakeholders should improve referrals, information sharing, and collaboration to ensure children with cerebral palsy receive accessible and continuous rehabilitation.

The study assessed the contribution of mobile money transaction speed to public financial service delivery in Iringa Municipal Council, Tanzania. Specifically, the study examined Council workers assessment on how the speed of mobile money transactions contributes to public financial service delivery. A mixed-method research approach with a cross-sectional research design was employed. Primary data were collected using questionnaires and interview guides. Quantitative data were analysed using descriptive statistics with the Statistical Product for Social Solutions (SPSS) Version 26, while qualitative data were analysed using thematic analysis. The findings revealed that mobile money transaction speed contributed to public financial service delivery through instant payment processing, real-time transaction execution, automated payment confirmation and continuous availability of transaction services. These features facilitated timely processing of public payments and supported efficient delivery of financial services. The study concludes that mobile money transaction speed contributes positively to financial service delivery in Iringa Municipal Council by reducing delays in payment processing and improving the timeliness of financial transactions. The study recommends that the Council strengthen collaboration with mobile network operators to improve network reliability, transaction processing systems and automated confirmation mechanisms. Further studies should examine mobile money transaction speed in other local government authorities using larger samples and inferential statistical analysis to allow broader comparison and generalisation of findings.

The purpose of this study was to assess the effect of procurement data accessibility on medicine supply chain accuracy at the Medical Stores Department (MSD) Iringa Zone. Specifically, the study determined how access to procurement records, stock information and consumption information affects medicine supply chain accuracy. The study adopted a mixed-method approach using a convergent parallel research design. Data were collected using structured questionnaires from 54 respondents and semi-structured interviews with 9 purposively selected key informants. The study population comprised 63 employees working at MSD Iringa Zone. Quantitative data were analysed using SPSS Version 20 through descriptive statistics, while qualitative data were analysed using thematic analysis. The findings showed that procurement data accessibility supported medicine supply chain accuracy by enabling staff to access procurement records, stock information and consumption information for forecasting, procurement planning, ordering and stock monitoring. However, medicine shortages, supplier delays, transport constraints and incomplete procurement information limited the contribution of data accessibility to accurate and timely supply chain operations. The study concludes that procurement data accessibility has an important role in improving medicine supply chain accuracy at MSD Iringa Zone. The study recommends that MSD strengthen access to complete and reliable procurement information and improve systems for updating and sharing procurement data among relevant staff. Further improvements in supplier coordination, inventory management and logistics are also recommended to strengthen medicine supply chain accuracy. Future studies should examine procurement data accessibility in other MSD zones and public health institutions in Tanzania.

This study examined role of fashion bloggers and influencers in shaping fashion trends among youths in tertiary institutions in Enugu state. The researcher adopted the survey research method in carrying out this study. Questionnaire was structured and administered to the sample of 271 respondents derived from the population of 912, using the Australian sample size calculator. Findings from the study showed that to a maximum extent fashion brands use fashion bloggers and influencers to promote their products in Enugu State, and that Interaction with fashion bloggers and influencers stimulates the decision of youths in tertiary institutions in Enugu State on fashion brands. It was recommended that fashion brands should know that there is a strong relationship among influencers, brands, and consumers, and therefore consider the potential negative effects of influencer marketing on consumer behaviour, such as encouraging impulsive purchases or promoting unrealistic beauty standards, while using fashion bloggers and influencers to promote their products. Also, since interaction with fashion bloggers and influencers affect the decision of consumers on fashion brands, brands and influencers need to be mindful of their responsibility to promote products that are ethical and align with the values of society.

This study assessed community perceptions of women’s socio-economic and political empowerment in Iringa Municipality, Tanzania. The study was guided by three specific objectives focusing on women’s social, economic and political empowerment. A mixed-methods approach and cross-sectional research design were employed. Data were collected through structured questionnaires and semi-structured interviews. Quantitative data were analysed using frequencies and percentages, while qualitative data were analysed thematically. The findings indicated generally positive community perceptions of women’s social empowerment, particularly regarding access to education, participation in decision-making, participation in community groups and awareness of programmes promoting women’s rights. Economic empowerment was also positively perceived, especially women’s participation in entrepreneurship, income-generating activities, access to credit and financial services, employment, business ownership and economic empowerment programmes. Similarly, respondents generally supported women’s participation in local leadership, political decision-making and local government. However, the findings also revealed continuing barriers, including gender norms, traditional expectations, limited financial resources, inadequate access to productive resources and challenges affecting women’s meaningful participation and control. The study concludes that community recognition of women’s capabilities has improved, but positive perceptions have not yet translated into full and sustained empowerment. The study recommends strengthening gender-responsive community programmes, women’s economic opportunities, leadership capacity, access to financial resources and meaningful participation in decision-making.

Background: Diabetes mellitus (DM) is a growing public health problem; India carries roughly one in seven of the world’s adults with diabetes [1,2]. Glycated haemoglobin (HbA1c) is the standard marker of long-term glycaemic control [3,4]. Acidum phosphoricum is a classical homoeopathic remedy for states of debility and exhaustion with copious urine, and it is among the polychrest remedies Indian practitioners report using in diabetes [5,7–9].
Objective: To describe the change in HbA1c over six months in patients with diabetes mellitus treated with Acidum phosphoricum LM 0/1.
Methods: A retrospective case series (single-arm, before-and-after) from the outpatient department of Sarada Krishna Homoeopathic medical college Kulasekharam Kanyakumari
,Tamil nadu . Thirty case records were screened; 20 were excluded because HbA1c was not recorded, leaving 10 for analysis. All 10 patients received Acidum phosphoricum LM 0/1 (one dose daily for 14 days) and were also given dietary and lifestyle advice. HbA1c at baseline and at six months was extracted from the records and analysed with descriptive statistics, the paired t-test and the Wilcoxon signed-rank test.
Results: The 10 patients (6 male, 4 female) had a mean age of 44.3 years and a mean diabetes duration of 5.2 years (range 2 to 10). Mean HbA1c fell from 9.68 ± 2.22% to 8.87 ± 1.68%, a
mean reduction of 0.81 ± 0.67 percentage points (95% CI 0.33 to 1.29; paired t = 3.79, df = 9, p = 0.004; Wilcoxon p = 0.002). HbA1c fell in all 10 patients (range 0.30 to 2.10 points; mean relative reduction 7.6%). Three patients, all with baseline HbA1c above 11%, improved by more than 1 point. Only 2 of 10 patients had HbA1c below 7% at six months.
Conclusion: In this small uncontrolled series, HbA1c decreased in every patient treated with Acidum phosphoricum LM 0/1. Because all patients also received dietary and lifestyle advice, the design cannot separate the effect of the remedy from that of diet, lifestyle, concurrent medication, or regression to the mean. Prospective controlled studies are needed.

Patient records held as raw rows in spreadsheets are slow to interrogate, hide the interaction between clinical attributes, and offer no quantified estimate of whether heart disease is present. Manual review of this kind motivates automated, comparable, and visually explorable heart disease analytics. This paper presents an end-to-end, layered analytics framework for heart disease prediction and patient-data exploration. The pipeline ingests a 303-record, 14-attribute patient dataset, validates it with Python and Pandas, performs exploratory analysis with Matplotlib and Seaborn, applies one-hot encoding to eight categorical attributes and standardization to five numeric attributes (yielding 30 model inputs), and trains and compares K-Nearest Neighbors, Decision Tree, and Random Forest classifiers whose hyperparameters are selected by cross-validation. An interactive Power BI dashboard with four KPI cards, four slicers, and four charts exposes the same data to non-programmers. Across the 303 validated records (165 with heart disease, 54.46%; average age 54.37 years), the analysis surfaces three principal observations: (i) chest pain type is strongly associated with disease status, with 82.00% and 79.31% of atypical-angina and non-anginal-pain patients diagnosed against 27.27% of typical-angina patients, as coded in this dataset; (ii) patients with heart disease reach a higher maximum heart rate (158.47 vs. 139.10 bpm) and show lower exercise-induced ST depression (0.58 vs. 1.59) than those without; and (iii) the disease share by gender and age group is heavily shaped by sample composition (96 female vs. 207 male patients; only 11 patients under 30 or over 70) and should not be generalized. The cross-validated accuracies are 84.48% for KNN (K = 12), 84.16% for Random Forest (90 estimators), and 78.51% for the Decision Tree (maximum depth 3). Twelve functional test cases pass, and dashboard figures reconcile with the source data. The framework offers a reproducible, low-cost, and transparent template for academic healthcare analytics; it is not a clinical diagnostic tool.

This study develops a supervised machine-learning system for predicting late-delivery risk in a global supply chain and deploys it as an interactive analytics dashboard. Using the DataCo Global logistics dataset – 180,519 daily order records spanning 2015–2019 with 53 operational attributes – a gradient-boosted decision-tree classifier (XGBoost) is trained to predict the binary target Late delivery risk (0 = On-Time, 1 = Late). Categorical fields are label-encoded and numerical fields scaled prior to an 80/20 train-test split. On the held-out test set (n = 36,104) the model achieves Accuracy = 79.89%, Precision = 86.00%, Recall = 75.64%, F1 Score = 80.48%, and ROC-AUC = 0.8358, comfortably outperforming a majority-class baseline (54.83% accuracy). The trained model, together with its encoder and scaler artefacts, is served through a five-page Streamlit dashboard providing KPI reporting, dataset exploration, visual analytics, model-performance interpretation, and prediction support. The contribution of this paper is a compact, interpretable, and fully deployed late-delivery risk pipeline that links model outputs to concrete operational actions in shipping-mode selection, regional risk monitoring, and proactive customer communication.

Diabetes is a common condition whose early identification depends on interpreting several health parameters together, yet manual examination of those parameters is slow and offers no automated, data-driven estimate of diabetes risk. This motivates automated, comparable, and accessible prediction tools for healthcare data. This paper presents an end-to-end, layered machine-learning framework and interactive web application for diabetes prediction. The pipeline ingests the Healthcare-Diabetes dataset (2,768 records, 10 columns; 952 diabetic and 1,816 non-diabetic), performs data validation and cleaning in Python and Pandas (duplicate removal, replacement of physiologically invalid zeros with medians, and IQR-based outlier removal), conducts exploratory analysis with Matplotlib and Seaborn, and trains and compares Logistic Regression, Decision Tree, and Random Forest classifiers on an 80/20 split (2,214 training and 554 test samples). The selected Random Forest is deployed in a Streamlit application that accepts eight health parameters and returns a diabetes label with an estimated probability. The empirical results reveal three observations: (i) plasma glucose is the attribute most strongly correlated with the outcome (0.49), ahead of insulin and BMI (0.29 each); (ii) tree-based models substantially outperform Logistic Regression on the held-out fold, with accuracy of 0.996 for Random Forest and 0.989 for Decision Tree against 0.758 for Logistic Regression, whose recall is only 0.539; and (iii) the near-perfect tree-model scores (Random Forest: precision 1.000, recall 0.990, ROC-AUC 0.995; two errors in 554 test cases) are unusually high for this problem and warrant leakage and generalization checks before any real-world reliance. The framework offers a reproducible, low-cost template for academic healthcare analytics; it is a predictive-support demonstration and not a clinical diagnostic tool.

The main objective of the study was to describe the level of teachers’ working competence in terms of: managing student conduct, instructional practice, teaching workload, instructional resource, and classroom autonomy; find out the level of teachers stress coping mechanism in terms of: mental engagement, behavioral disengagement, focus and venting emotions, positive reinterpretation and growth, acceptance and seeking social support for emotional reasons, assess the performance of the teachers as prescribed by the Department of Education for the appraisal of the teachers on the Individual Performance Commitment and Review Form (IPCRF) and correlate teachers performance with their working competence and stress coping mechanism in secondary schools of Don Carlos III District.
Descriptive analysis measures the teachers’ working competence in terms of managing student conduct, instructional practice, teaching workload, instructional resource, and classroom autonomy reveals a very highly effective level responses of the teachers.
Correlation results indicated that teacher’s performance have no significant relationship with their working competence and stress coping mechanism. Therefore, the null hypothesis which stated that there is no significant relationship between the performance of secondary teachers and teachers’ working competence; teachers’ stress coping mechanism was accepted.

Online grocery and food delivery apps make buying food quick and easy, but they are built around speed, price and catalogue size. They do little to help users judge whether their basket is healthy. This paper points out that gap: none of the platforms we compared combines grocery ordering, AI, nutrition guidance and personalization. We present AuraCart, a mobile-first web platform that does. It looks at the shopping cart as a whole. It gives the cart a health score from 0 to 100, warns about junk food, suggests healthier swaps, recommends recipes from the cart contents, and builds weekly and budget meal plans. We describe the architecture, give the formulas behind each feature, and walk through example carts, including one where two swaps raise the score from 58 to 82. We also discuss the business model, privacy, data quality and scalability, and give a plan for testing the system with real users. The results shown here are worked examples, not user-study data.

The present study on formulation and evaluation of herbal hair growth oil focuses on preparing a polyherbal oil formulation using natural ingredients to promote hair growth and improve scalp condition. Some of these herbs include Amla, Henna, Neem, Fenugreek, Lemon, Tulsi, Brahmi, Shikakai, Reetha, Mulethi root, Kasturi root, Mahabhringraj, Jantamasi, Chitrak, Marigold, Hibiscus, Nutmeg, Parsley, Henna and Thyme. The herbal hair oil formulation is expected to provide multiple benefits like nourishment to hair roots, prevention of dandruff, reduction in hair fall. Improves hair texture, and increases hair growth. Evaluation of the finished formulation is necessary to determine its quality, stability, safety and effectiveness.

The study aimed to assess the contribution of RLabs education interventions to the welfare of street children in Iringa Municipality, Tanzania. The study focused on school enrolment support, provision of learning materials and student reintegration support as education interventions provided by RLabs. A mixed-methods approach was employed using a cross-sectional design. Primary data were collected through structured questionnaires and semi-structured interviews. Quantitative data were analysed using descriptive statistics with the Statistical Product for the Social Solutions (SPSS) Version 26, while qualitative data were analysed using thematic analysis. The findings showed that RLabs education interventions contributed to the welfare of street children through support for school enrolment, provision of learning materials and assistance with student reintegration. The interventions supported children to access education, obtain learning materials and return to formal learning after periods of living or working on the streets. The study concludes that RLabs education interventions contributed to improving the educational welfare of street children in Iringa Municipality through enrolment support, learning materials and reintegration assistance. The study recommends that RLabs strengthen education interventions by increasing support for school enrolment, providing adequate learning materials and strengthening follow-up of children after reintegration into schools. Further studies should examine the long-term educational outcomes and sustainability of RLabs education interventions among street children.

Last-mile delivery is a critical stage of logistics in which delays, unsuccessful delivery attempts and customer-related issues can affect service quality and operational cost. This paper presents a data-driven workflow for analyzing delivery failures using structured dataset and interactive analytics. Python and pandas are used for data preparation and analysis, SQL supports structured querying, and a Streamlit dashboard presents key performance indicators and failure patterns. The project dataset contains 5,000 delivery records, with attributes such as distance, vehicle type, weather, traffic, customer availability, address accuracy, delivery attempts and failure reason. The recorded overall delivery failure rate is 19.24%. Chi-square tests show that customer availability and address accuracy have the strongest association with failure, followed by traffic level and weather. The workflow provides descriptive operational insights and can be extended with real-time data and validated machine-learning models for failure prediction.

Choosing where to open new stores is often settled with spreadsheets, rules of thumb or proprietary models whose data preparation and evaluation are rarely documented. This paper documents a small, reproducible analytics workflow for store location optimization and applies it to a synthetic city of 400 one-square-kilometre zones, 40 candidate sites and 12 competitor stores. Python and pandas derive demand and rent indicators, the tables are stored in SQLite and queried with SQL, k-means segments the zones, and six selection methods (population rank, weighted score, k-means snapping, maximal covering by mixed-integer programming, greedy-plus-swap search on a Huff-model profit, and exhaustive search) each choose 5 sites. All six are scored under one Huff-model profit function and then re-scored under five distance-decay values and 500 Monte Carlo draws. In the demonstration data the Huff-based search reaches a net annual profit of INR 2.67 crore, against 1.83–2.31 crore for the four baselines and 1.18 crore for a random five-site choice. Greedy-plus-swap matches the exhaustive optimum among all 658,008 five-site combinations, the covering model attains the highest demand coverage (52.2%) without the highest profit, and baseline regret grows with distance decay. Because the data are synthetic and the Huff-based methods are judged under their own objective, the results show how the workflow behaves, not how a real retail market behaves.

Retail organizations generate large volumes of transactional data, but raw records are not directly useful for business decision-making without systematic cleaning, aggregation, and visualization. This paper presents an end-to-end retail sales and customer analytics workflow implemented using Python, SQL, Microsoft Power BI, and a lightweight web reporting layer. The study uses a synthetic practice dataset containing 1,000 retail orders recorded during 2025, 310 unique customers, 20 products, 5 categories, and 8 cities. Python with Pandas is used for duplicate removal, missing-value handling, derived time features, KPI calculation, aggregation, and exploratory visualization. SQL queries provide reusable business analysis for sales, profit, categories, cities, products, customers, payment methods, monthly performance, and profit margins. Power BI is specified as the interactive business-intelligence layer, while a Flask/HTML dashboard provides a lightweight web interface with filtering and runtime dataset support. The analysis reports total sales of ₹11,354,750.00, total profit of ₹3,659,302.06, 1,000 orders, 310 customers, 1,847 units, and an average order value of ₹11,354.75. Electronics contributes the largest category sales, and Laptop is the highest-selling product by sales value. The paper demonstrates how multiple analytics tools can be combined into a reproducible workflow for descriptive retail intelligence.

Customer attrition is a direct threat to a retail bank's revenue and lifetime-value economics, since acquiring a replacement customer is markedly more expensive than retaining an existing one. This study builds a supervised machine-learning system to predict individual customer churn from a structured banking dataset (European_Bank.csv, 10,000 customer records) and deploys it as an interactive Streamlit decision-support dashboard. Ten raw attributes — credit score, geography, gender, age, tenure, account balance, number of products, credit-card ownership, active-membership status and estimated salary — are supplemented with four engineered risk features (Balance-to-Salary Ratio, Product Density, Engagement-Product interaction and Age × Tenure) and one-hot encoding of geography and gender, giving a 15-feature model matrix. Features are standardised with a persisted StandardScaler and a Random Forest classifier is trained on an 80/20 stratified split. On the held-out test set the model achieves Accuracy = 91.4%, Precision = 89.2%, Recall = 87.8%, F1-Score = 88.5% and ROC-AUC = 0.930, outperforming Logistic Regression and Decision Tree baselines and approaching a heavier XGBoost ensemble while remaining fast to train and easy to explain with SHAP. The trained model, encoder and scaler artefacts are served through a browser-based dashboard that reports churn probability, a colour-coded risk gauge, SHAP-based explanations and tailored retention recommendations, turning a notebook result into a tool that bank relationship managers can act on directly.

Customer attrition, or churn, is a critical revenue risk for subscription-based telecom operators, where the cost of acquiring a new customer substantially exceeds the cost of retaining an existing one. This study develops a supervised machine-learning system, ChurnGuard AI, for predicting customer churn risk and deploys it as an interactive Streamlit analytics dashboard. Using the IBM/Kaggle Telco Customer Churn dataset – 7,043 customer records with 21 demographic, account, and service attributes – multiple classifiers (Logistic Regression, Random Forest, and Gradient Boosting) are trained on the binary target Churn (0 = No, 1 = Yes) after categorical encoding, feature scaling, and an 80/20 stratified train-test split. Logistic Regression is selected as the deployed model based on hold-out evaluation. On the held-out test set (n = 1,409) the model achieves Accuracy = 73.81%, Precision = 50.43%, Recall = 78.34%, F1 Score
= 61.36%, and ROC-AUC = 0.8413, meaningfully outperforming a majority-class baseline in discrimination and recall despite a similar headline accuracy. The trained model and its preprocessing artefacts are served through a five-page Streamlit dashboard providing KPI reporting, individual churn prediction, customer risk segmentation, visual analytics, and batch prediction. The contribution of this paper is a compact, interpretable, and fully deployed churn-risk pipeline that links model outputs to concrete retention actions in contract migration, proactive support outreach, and targeted discounting.

Urban public transportation systems generate large volumes of mobility data covering passenger demand, routes, transport type, time, weather, and occupancy. This paper reports a data-driven anomaly detection framework, applied to a 10,000-record demonstration dataset spanning 20 bus and metro routes over six months, that identifies unusual passenger-demand observations without requiring labelled data. The pipeline covers preprocessing, exploratory analysis, feature engineering, Isolation Forest as the primary detector, and DBSCAN as a density-based comparison. On the demonstration dataset, Isolation Forest (contamination = 0.05) flags 500 of 10,000 observations (5.00%) as anomalous, while DBSCAN (eps = 0.5, min_samples = 10) labels 198 observations (1.98%) as noise, with 102 observations — 51.5% of DBSCAN's noise points — flagged by both methods. Anomalies concentrate on bus routes (7.26% anomaly rate versus 2.78% for metro), peak hours (8.60% versus 3.48% off-peak), and weekends (Sunday 8.55%, Saturday 6.16%), and align closely with the dataset's existing crowd classification (51.6% of “High” crowd-level records are flagged, against 3.05% of “Low” records). The framework gives transportation planners a reproducible, statistically grounded view of unexpected demand variation to support capacity planning and resource allocation.

Background: Allergic rhinitis is an IgE-mediated inflammatory disorder of the nasal mucosa that affects an estimated 10–30% of the population worldwide. It causes sneezing, watery discharge, nasal blockage and itching, and disturbs sleep and daily activity. Nux vomica is a commonly prescribed homoeopathic medicine for chilly, irritable, oversensitive patients with sneezing and nasal blockage.
AIM AND OBJECTIVES
Aim: To describe how Nux vomica was prescribed, and what was recorded at follow-up, in patients with allergic rhinitis attending an outpatient department. The study was not designed to test whether Nux vomica works.
Objectves
• To describe the age and sex distribution of the patients.
• To describe the potencies in which Nux vomica was prescribed.
• To describe the frequency with which the medicine was repeated.
• To report the outcome recorded during follow-up.
MATERIALS AND METHODS
A retrospective case series of fifteen outpatient records (study period October 2025 to October 2026) of clinically diagnosed allergic rhinitis treated with Nux vomica, with complete follow-up, at OPD. Data are presented as counts and percentages, and total nasal symptom scores (TNSS) as median (range).
RESULTS
Fifteen patients were included. The largest age group was 31–40 years (6 patients, 40%), and 11 patients (73.3%) were male. The commonest potency was 200C (7 patients, 46.7%). Twelve patients (80%) received the same schedule, four times a week. At follow-up,11 patients (73.3%) were recorded as improved and 4 (26.7%) as unchanged; none was recorded as worse.
CONCLUSION
Nux vomica was often prescribed as 200C (46.7%) and 12 of 15 patients (80%)had the same four times a week schedule, a routine rather than varied pattern; reasons for dosing were not recorded. Eleven of 15 patients improved and 4 did not change, but with no comparison group, selected records and a very small sample, this does not show that Nux vomica is effective. Controlled prospective studies are needed.

Product teams tend to learn that a feature has failed, or that a cohort is drifting away, only after a weekly dashboard has already turned red. This paper describes ProductLens AI, a modular pipeline that tries to bring that moment forward. Working on a simulated clickstream of 4,000 users and ten feature launches, the system combines leading engagement indicators, a nested conversion funnel, a gradient-boosted classifier that forecasts 14-day inactivity, Kaplan–Meier survival curves for feature usage, and a Beta–Bernoulli bandit that ranks candidate features by expected adoption per engineering hour. A language model then turns the computed outputs into a written roadmap recommendation and is not allowed to introduce figures of its own. Under a time-based holdout the classifier reaches an AUC of 0.977 overall, but only 0.792 among users who were active in the preceding week, which we argue is the fairer measure of early-warning value; a plain recency rule, by comparison, reaches 0.964 overall and only 0.632 on that subset. Survival curves separated the ten launches into sustained, novelty-driven and failed groups (day-14 survival of 0.72–0.79, 0.45–0.58 and 0.14–0.26), even though early adoption rates alone did not. The paper also shows that the practical size of the alert list depends heavily on the score threshold chosen, so that choice belongs with the product team and not with the model. We describe the architecture, the methods, the limits that come from synthetic data and heuristic posteriors, and a validation plan that should be completed before the pipeline is trusted on production telemetry.

Sales records for electric vehicles (EVs) are often examined in spreadsheets, or in forecasting studies that say little about how the data were prepared and queried. This paper documents a small, reproducible analytics workflow for EV sales and applies it to a demonstration dataset of 440 records covering ten Indian states, eleven models from five brands, and the years 2022 to 2025. The dataset is synthetic and ships with the project, so the findings describe how the workflow behaves and not how the real market behaves. Python and pandas clean the data and derive revenue, efficiency and value indicators. The cleaned table is stored in a SQLite database and explored with eight Structured Query Language (SQL) queries, a Streamlit dashboard and an Excel workbook present the results, and a Power BI dashboard is specified with Data Analysis Expressions (DAX) measures and visuals. In the demonstration data, yearly sales rise from 14,201 to 32,304 units between 2022 and 2025, while year-over-year growth eases from 36.6% to 25.3%. One brand holds 43.5% of units, sport utility vehicles (SUVs) account for 72.3%, and a least-squares line projects 38,090 units for 2026. The workflow gives students and analysts a transparent route from a raw sales table to interpretable market indicators, and it can be pointed at a real dataset that follows the same column layout.

Background: Justicia adhatoda L. (syn. Adhatoda vasica Nees) is a respiratory remedy whose activity is attributed to quinazoline alkaloids. Its hydro-alcoholic mother tincture (Ø) is the starting material for homoeopathic dilutions, but LC–MS data on the tincture are scarce. Aim: To characterise the major alkaloids of the mother tincture by LC–MS. Methods: One tincture sample was analysed on 25 September 2026 (5 µL) on an LCMS-8045 RX triple-quadrupole system by full-scan acquisition (20 positive/negative events) and multiple reaction monitoring (MRM) of eleven analytes with quantifier and qualifier transitions. Identification was assessed from retention-time (RT) agreement and ion ratio. Relative peak-area shares were used as signal proportions, not as estimates of compound amounts. Results: Full-scan base peaks at m/z 205, 189, 219 and 203 coincided with the RT windows of vasicinol, vasicine, vasicoline and vasicinone. MRM signals were observed for all nine targeted alkaloids, but two identifications were tentative. Vasicinone gave the strongest signal (43.5% of summed alkaloid peak area), followed by vasicine (28.7%), vasicoline (14.8%) and vasicinol (9.0%); together these accounted for 96.0% of the alkaloid signal. Orientin was not confirmed. Conclusion: The signal profile was dominated by vasicinone and vasicine. Because detector response can differ among compounds and no calibration standards were used, peak-area shares must not be interpreted as relative amounts. Validated analysis with reference standards is needed.

This paper presents SentinelBI AI, an end-to-end business-intelligence platform that combines classical statistical monitoring with machine learning and deep learning to detect anomalous revenue behaviour in e-commerce operations. The system is built on the Online Retail II transactional dataset (1,067,371 line items, December 2009 – December 2011, 43 countries) aggregated into 731 daily business-performance records comprising revenue, quantity, transaction count, active-customer count and a 7-day rolling-average revenue deviation. Two complementary unsupervised detectors are trained: an Isolation Forest that flags unusual individual daily observations, and an LSTM Autoencoder that flags unusual sequential revenue patterns over a 30-day window after 20 training epochs. Their outputs are fused into a three-tier alert scheme — Normal, Warning, and Critical — surfaced through a five-page Streamlit dashboard (Executive Overview, Business Analytics, AI Anomaly Monitor, AI Investigation, and a natural-language "Ask SentinelBI" query interface backed by a SQLite analytical warehouse). Of 731 business days, the Isolation Forest flags 37 (5.06%), the LSTM Autoencoder flags 33 (4.51%), and 19 days are jointly flagged as Critical, giving 32 Warning-level days and 680 Normal days. Compared with a static ±2σ baseline, the learned detectors achieved higher cross-validated match rates, with the Isolation Forest and LSTM Autoencoder obtaining 51.4% and 57.6%, respectively, compared with 43.9% for the baseline. The contribution of this work is a deployable, dual-model anomaly-detection pipeline that converts unsupervised model outputs into an actionable, non-technical decision-support tool for e-commerce revenue monitoring.

The pervasive threat of internal fraud, amplified by the digitalisation of financial services, poses a significant challenge to the banking industry, frequently overwhelming traditional auditing and investigative methods. This study addresses the urgent need for more adaptive and technologically advanced fraud mitigation strategies by proposing and validating a synergistic framework that integrates forensic accounting principles with advanced data analytics. Utilising a sophisticated, simulation-based methodology, we generated a realistic dataset of 1.5 million banking transactions, embedding subtle and complex internal fraud scenarios. This research evaluates the efficacy of four distinct machine learning models—Logistic Regression, Multi-Layer Perceptron (MLP) Neural Network, XGBoost, and a Balanced Random Forest—in detecting these fraudulent activities. The findings reveal that the Balanced Random Forest model demonstrates superior performance, achieving an AUC-ROC of 0.975, an F1-Score of 0.915, and a Recall of 0.952, indicating its exceptional ability to identify over 95% of fraudulent transactions while maintaining a low rate of false positives. Feature importance analysis highlights that behavioural anomalies, such as deviations from an employee's average transaction patterns, are the most potent predictors of fraud, surpassing the significance of static transactional attributes like the amount. This study provides a practical, data-driven workflow that translates these analytical insights into an automated, real-time fraud detection and prevention system. The results confirm that the integration of forensic expertise with machine learning not only enhances detection accuracy and operational efficiency but also provides a proactive, resilient defence mechanism against the dynamic nature of internal financial crime.

The study is on Factorial Validation of a Civic Disposition Scale (CDS) for Senior Secondary School Students in Benue State: Implications for Effective Civic Education Assessment. It was designed to validate using factor analysis method a Civic Disposition Scale for senior secondary school students. Two basic objectives guided the study. The study adopted an instrumentation research design. Benue State, Nigeria was the target study area and the population comprised 3,911 SS2 students from seven Local Government Areas (LGAs) in Zone B. A sample of 363 students (196 males, 167 females) was selected using multistage sampling with purposive and simple random techniques. Data were collected via a researcher-developed four-point rating CDS, validated by five experts and shown reliable with a Cronbach’s alpha of 0.87. The scale was administered directly with trained assistants, and data were analyzed using SPSS. Results revealed that the instrument has a clear internal structure as evidenced in the scree plot, showing it measures a limited number of main ideas (hidden traits), and 30 of the 95 items are meaningfully connected to these core areas. Five factors extracted as underlying structure of the scale, labelled Civic duty, Community involvement, Political attentiveness, Ethical and Moral disposition and Openness to diversity were grouped based on items loaded on them. This is according to strong factor loadings, with values above 0.50 indicating solid relationships between items and their factors. The study concludes therefore that the CDS instrument developed is a reliable and well-structured tool for assessing civic disposition. It was recommended among other things that educators and researchers focus on the key factors identified in the scale when using the Civic Disposition Scale to assess students and also that the full multidimensional nature of the scale be utilized in interpreting students’ responses.

The study sought to assess the socio-demographic profile and food consumption pattern of the elderly in Nasarawa State. The study was guided by two specific objectives. Two research questions were raised for the study. Survey research design was adopted for the study. The population of the study was 114, 973 persons living within the study area. The sample size of the study was 300 participants. The study employed questionnaire as an instrument for data collection and the data collected were analyzed using descriptive statistics of mean and standard deviation. The findings shows that, majority of the elderly (70.3%) ate 2-3 meals per day however, these meals mostly devoid of diary, legumes/eggs, meat/fish/poultry, as well as fruits and vegetables. Analysis of average daily intake of nutrients by the elderly respondents revealed that the intake of nutrients (apart from vitamin B1(1.0mg), Fe(16.8mg), and Cu(8.4mg).) were lower than the recommended value/day. The study concluded that there is a need for specific intervention programmes for the elderly in Nasarawa State to improve their nutritional status through dietary diversification and good food preparation practices. It is recommended that there should be a need for Public health intervention programs and health care institutions should promote dietary plans at the community level and encourage consumption of cheap locally available nutritious foods.

Background: Genetic disorders constitute an important group of conditions encountered in pediatric practice and may present with congenital anomalies, developmental delay, neurological manifestations, or multisystem involvement. The present study retrospectively reviewed pediatric case records to describe clinical outcomes and prescribing patterns among children with recorded genetic disorders who received homoeopathic treatment.
Methods: A retrospective, quantitative, descriptive observational study was undertaken using medical records from the outpatient and inpatient services of Sarada Krishna Homoeopathic Medical College and Hospital. Thirty pediatric records were included from the study material described in the source synopsis. Variables included age, sex, recorded genetic disorder, consanguinity, maternal age at conception where available, homoeopathic medicine, potency, and recorded clinical outcome. Descriptive frequencies were used to summarize the dataset.
Results: The sample comprised 22 males and 8 females. Nineteen cases were aged 0–4 years, 7 were aged 5–9 years, and 4 were recorded in the 10–14-year group. Down syndrome was the most frequent diagnosis (5/30), followed by congenital talipes equinovarus, autism, and global developmental delay (4/30 each). Consanguinity was recorded in 12 of 30 cases. Maternal age at conception was available for 14 cases, with 7 each in the 25–29-year and 30–34-year groups. Sulphur was the most frequently recorded medicine (4/30), followed by Carcinosin (3/30). The most frequently recorded potency was 200 (12/30), followed by 1M (11/30). According to the detailed outcome table in the source record, 19 cases were classified as improved, 9 as moderately improved, 1 as showing mild improvement, and 1 as showing no improvement.
Conclusion: This retrospective series describes the characteristics, prescribing patterns, and recorded clinical outcomes of 30 pediatric cases with genetic disorders treated in a homoeopathic hospital. Because the study was uncontrolled, retrospective, based on a small heterogeneous sample, and used outcome categories derived from clinical records rather than a standardized validated scale, the findings should be considered descriptive and hypothesis-generating rather than evidence that homoeopathic treatment caused the observed changes.

This article examines how digital accounting systems may support retail small and medium-sized enterprise performance in Zambia, with implications for Chipata. A narrative review combines scholarly accounting and information-systems research with official Zambian policy, establishment, financial-inclusion, connectivity and electronic-invoicing materials. The Technology-Organization-Environment framework explains adoption conditions, while the DeLone and McLean information-systems success model supports an account of effective use and business value. The synthesis identifies potential mechanisms involving record quality, reporting timeliness, inventory visibility, cash-flow monitoring, internal control and management decisions. These mechanisms may contribute to efficiency, resilience and finance readiness, but purchasing software alone does not establish improved performance. System suitability, user skills, management commitment, data quality, affordability, infrastructure and security shape the outcomes. The article develops six propositions and a staged implementation pathway for retail SMEs. It provides a context-sensitive framework rather than new survey findings or a measured effect for Chipata. Future local research should distinguish adoption, effective use, information quality and business performance, and should combine respondent perceptions with verifiable operational and financial measures.

Governance represents the foundational framework through which human societies organize political power, distribute public authority, formulate collective rules, and allocate resources. In political science and constitutional theory, the structural architecture of a state determines not merely the efficiency of administration, but the preservation of individual liberty against state overreach. Classical political philosophers—from Aristotle and Polybius to John Locke, Montesquieu, and James Madison—recognized that unchecked power inevitably corrupts. Consequently, the study of governance is fundamentally an inquiry into institutional design: how power is acquired, exercised, checked, and restrained.

This study assessed community knowledge regarding child abuse in Mtwivila Ward, Iringa Municipality, Iringa Region, Tanzania. A cross-sectional mixed-methods research design was employed among 85 respondents selected through purposive and simple random sampling. Quantitative data were collected using structured questionnaires, while qualitative data were obtained through Key Informant Interviews and one Focus Group Discussion. Quantitative data were analysed using descriptive statistics in SPSS Version 26, while qualitative data were analysed thematically. The findings showed a high level of general awareness of child abuse, with 100% of respondents reporting that they were aware of child abuse and able to identify common indicators, including injuries, fear and discomfort. However, knowledge was less comprehensive regarding less visible forms of abuse, particularly emotional abuse and neglect. Regarding child protection structures, 68.2% of respondents reported being aware of the existence of child protection committees, while 31.8% were unaware of them. Respondents identified poverty, drunkenness, family conflicts and lack of education as major perceived causes of child abuse. Physical injury was the most frequently recognized consequence, followed by death, drug abuse, school dropout, transmission of diseases, early pregnancy and emotional trauma. Qualitative findings further indicated that alcohol misuse, economic difficulties, inadequate knowledge of children&#39;s rights and inappropriate disciplinary practices may increase children&#39;s vulnerability to abuse. The study concludes that although community members in Mtwivila Ward have a high general awareness of child abuse, important knowledge gaps remain regarding emotional abuse, neglect, child protection structures and reporting mechanisms. The study recommends strengthening community education on all forms of child abuse, increasing awareness of child protection committees and reporting procedures, promoting positive and non-violent parenting practices and strengthening collaboration among families, schools, community leaders, social welfare officers, health workers, police, religious leaders and child protection committees to improve the prevention, identification, reporting and response to child abuse.

Hormonal fluctuations represent an essential component of female reproductive physiology and are particularly prominent during the menstrual cycle and reproductive transitions such as puberty, pregnancy, postpartum period, perimenopause and menopause. Ovarian steroid hormones, principally estradiol and progesterone, exert effects beyond reproductive tissues and interact with neural circuits involved in mood, cognition, sleep, appetite, stress responsiveness and emotional processing. Increasing evidence indicates that clinically relevant symptoms in susceptible individuals may depend not simply upon absolute hormone concentrations but upon individual sensitivity to physiological hormonal fluctuations. [1,2]
Pulsatilla occupies a distinctive position in classical homoeopathic Materia medica because of its characteristic variability and its prominent association with female reproductive symptoms. Classical sources describe changeable mental states, easy weeping, mildness and yielding behaviour, desire for consolation, shifting physical symptoms, delayed or scanty menstruation, intermittent menstrual flow, leukorrheal symptoms and manifestations associated with pregnancy and lactation [5,7]
Modern pharmacognostic investigations of Pulsatilla species have identified several bioactive constituents, particularly triterpenoid saponins. Research involving Pulsatilla nigricans has characterized compounds including anemoside B4, anemoside A3 and other saponins, with experimental evidence for anti-inflammatory, immunomodulatory, antioxidant and other pharmacological activities [9,11]
This article proposes an integrative hypothesis in which the classical concept of Pulsatilla variability is examined alongside the modern concept of neuroendocrine sensitivity to hormonal fluctuations. The hypothesis does not assert that hormonal fluctuations cause the Pulsatilla symptom complex, nor that Pulsatilla regulates reproductive hormones. Instead, it proposes that the temporal variability, reproductive associations and affective characteristics described in Pulsatilla may constitute a clinically observable phenotype worthy of prospective investigation using menstrual cycle tracking, validated symptom instruments and endocrine biomarkers.

This article examines whether parliamentary or presidential government provides a more effective constitutional framework for democratic accountability, executive stability and institutional restraint. It compares India’s parliamentary system with the presidential system of the United States, focusing on executive selection, tenure, responsibility, legislative relations and checks and balances. The research adopts doctrinal and comparative methods, using constitutional provisions, judicial decisions and official constitutional materials. It argues that the difference between the models is not simply that one combines powers and the other separates them: each distributes political responsibility differently. India’s model makes the Council of Ministers answerable to the Lok Sabha and permits a government to be replaced when it loses confidence, while the US model gives the President an independent electoral mandate and fixed tenure, subject to constitutional removal. The analysis finds that parliamentary government may promote policy coordination but can enable executive dominance when party discipline is strong; presidential government may provide continuity but can produce institutional deadlock. Neither design guarantees democratic performance without effective oversight, constitutional conventions and respect for legal limits. Rather than recommending wholesale transplantation of the American model, the article proposes strengthening parliamentary scrutiny, committee review, transparency and constitutional accountability in India.

The study assessed the contribution of community savings groups to the economic well-being of beneficiary households in Iringa Municipality, Tanzania.. A quantitative research approach was employed using a cross-sectional research design. A sample of 100 beneficiary households was selected using simple random sampling, while five key informants were purposively selected. Primary data were collected using questionnaires and interview guides. Quantitative data were analysed using descriptive statistics with the Statistical Package for Social Sciences (SPSS) Version 26, while qualitative data were analysed thematically. The findings showed that community savings groups contributed to the economic well-being of beneficiary households through income generation and asset accumulation. Beneficiaries reported improvements in household income and acquisition of assets through savings and access to group loans. However, limited capital, small loan amounts, inadequate markets and limited business management skills constrained the extent to which the groups contributed to household economic well-being. The study concludes that community savings groups make a positive contribution to the economic well-being of beneficiary households by supporting income generation and asset accumulation, although their contribution is constrained by financial and business-related challenges. The study recommends strengthening productive lending, business management training, market linkages and household financial planning to enhance the economic benefits of community savings groups among beneficiary households.

The study aimed to assess parents’ and caregivers’ perception of the contribution of community nutrition programs to child feeding practices among children under-five years in Iringa Municipality, Tanzania. The study focused on parents’ and caregivers’ perceptions of the contribution of community nutrition programs to meal frequency, dietary diversity, breastfeeding practices and recommended feeding routines. A mixed research approach was used with a cross-sectional research design. Questionnaires were used to collect quantitative data from parents and caregivers, while semi-structured interviews were conducted with key informants to obtain detailed information on community nutrition programs and child feeding practices. Quantitative data were analysed using the Statistical Product for the Social Solution (SPSS), Version 26, using descriptive statistics, while qualitative data were analysed through thematic analysis. The findings showed that parents and caregivers perceived community nutrition programs as contributing to improved child feeding practices through increased meal frequency, improved dietary diversity, continued breastfeeding and better adherence to recommended feeding routines. The findings also showed that nutrition education, practical guidance and follow-up provided through community nutrition programs supported parents and caregivers in applying appropriate feeding practices at household level. The study concludes that community nutrition programs contribute positively to child feeding practices among children under-five years in Iringa Municipality. The study recommends strengthening practical nutrition education, household follow-up and community-based demonstrations to support parents and caregivers in applying appropriate feeding practices for children under-five years.

This study examined the contribution of off-farm income-generating activities (IGAs) to household income among smallholder farmers in Iringa District Council, Tanzania. The manuscript focuses specifically on the first objective of the broader dissertation, which examined the contribution of off-farm IGAs to household income. The study was guided by the Sustainable Livelihoods Framework and employed a mixed-methods approach with a cross-sectional design. Data were collected from 128 smallholder farmers engaged in off-farm IGAs in Wasa and Lumuli Wards using structured questionnaires, while qualitative information was obtained from key informants. Quantitative data were analysed using descriptive statistics, including frequencies and percentages, while qualitative evidence was analysed thematically. The findings showed that off-farm IGAs constituted the main source of income for 52.8% of respondents, compared with 40.9% who identified on-farm activities as their main source and 6.3% who reported other sources. In terms of the contribution to total household income, 40.6% of respondents reported obtaining 50–74% of household income from off-farm activities, 39.8% obtained 25–49% and 4.7% obtained 75% or more. Overall, 85.1% obtained at least one-quarter of their household income from off-farm activities. Furthermore, 71.9% received income from off-farm activities daily, 22.7% weekly and 5.5% monthly. The findings suggest that off-farm IGAs provide an important and relatively regular source of household income, complementing seasonal agricultural earnings and strengthening household livelihood security. The study concludes that off-farm IGAs make an important contribution to household income among smallholder farmers in Iringa District Council. Strengthening access to finance, markets, entrepreneurship skills and supportive local institutions is recommended to enhance the sustainability and income-generating potential of off-farm enterprises.

Surrogacy combines a variety of legal, reproductive, contractual and medical concerns into one. But the ways in which jurisdictions regulate that relationship are quite different. This article does a functional comparative analysis of the Indian law and US and UK laws. The Surrogacy (Regulation) Act, 2021 has transformed the Indian transnational market into a statutory one allowing only carefully delineated altruistic surrogacy transactions, while completely banning commercial surrogacy. There is no uniform federal surrogacy law; state law varies from very facilitative (as in California and New York) to restrictive (influenced by older public-policy concerns). The United Kingdom allows non-commercial surrogacy but usually considers the surrogate to be the legal mother at birth, and the parent(s) is/are transferred to the child through a post-birth parental order. A comparison, it can be seen that the three systems of law assign risk in different ways: in India, the control is on entry; in the United States, often the control is on enforceable agreement; and in the United Kingdom, the control is on the consent after birth and transfer of parenthood by the courts. The authors contend that a robust model should include India's anti-exploitation protections, the surrogate-centred autonomy protections in contemporary U.S. laws, and a welfare and independent-review framework in the United Kingdom, without any "eligible" criteria and legal uncertainty at birth.

This study examined the contribution of AMCOS to cocoa farmers' household income in Kyela District Council, Tanzania. Data were collected from 122 cocoa farmers and eight key informants from four AMCOS in Kyela District Council. Data were collected using questionnaires, key informant interviews and documentary reviews. Quantitative data were analysed using frequencies, percentages, means and paired t-test in SPSS version 26, and qualitative data were by thematic analysis. The findings show that most of farmers reported higher household income after joining AMCOS, received better cocoa prices, reported reduced problems with middlemen, and received credit through AMCOS. Mean annual household income increased, comparing before joining AMCOS. However, payment delays and differences in cocoa production affected the benefits received by some farmers. The study concludes that AMCOS contributes to household income through collective marketing, better cocoa prices, reduced reliance on middlemen and access to credit and agricultural services.

This technical seminar report examines the importance, significance, scope and disadvantages of International Financial Reporting Standards (IFRS Accounting Standards) in different jurisdictions, with Zambia as the principal country of reference. It also explains why periodic revision of the Standards is important. The report adopts a desk-based qualitative review of authoritative standard-setting, regulatory and professional literature.
The report finds that IFRS contributes to comparability, transparency, accountability, investor confidence and cross-border interpretation of financial statements. Its scope is particularly significant for publicly accountable entities and capital-market reporting, while the IFRS for SMEs Accounting Standard provides a simplified framework for eligible entities. Zambia adopted IFRS Standards through the Zambia Institute of Chartered Accountants, with compliance effective from 1 January 2005. Despite these benefits, IFRS may create implementation costs, technical complexity, reliance on professional judgement, valuation difficulties and challenges where local institutional capacity is limited.
The report further finds that periodic revision of IFRS is necessary because financial markets, business models, technology, transactions and users’ information needs continue to evolve. Post-implementation reviews and amendments enable the International Accounting Standards Board to assess whether Standards continue to operate as intended and to address unintended consequences or emerging financial reporting issues. The report concludes that IFRS remains important to Zambia’s financial reporting environment; however, effective application requires continuous professional development, effective enforcement, proportionate reporting frameworks and active participation in international standard-setting processes.

Employee motivation is an important human resource management issue because employees' willingness to perform their duties can influence the quality and timeliness of services provided by an organisation. This study evaluated the effect of employee motivation on service delivery at ASAS Dairies Limited in Iringa, Tanzania. The study focused on three main motivation practices: financial incentives, employee recognition and career development opportunities. A mixed-methods approach and an explanatory research design were used. Quantitative data were collected from 80 employees through structured questionnaires, while qualitative data were obtained from five key informants through semi-structured interviews. Quantitative data were analysed using frequencies and percentages in SPSS Version 26, while interview data were analysed thematically. The findings showed that employee motivation was associated with several aspects of service delivery. Specifically, 76.3% of respondents reported that financial incentives often encouraged timely completion of assigned duties. Similarly, 76.3% reported that employee recognition improved service quality six to ten times during the previous twelve months, while 73.8% indicated that career development opportunities often helped employees meet customers' expectations. However, the findings also showed limitations. About 47.5% of respondents reported that motivation improved daily work performance by less than 20%, while 67.5% indicated that motivation rarely reduced delays in completing assigned duties. Interview findings indicated that financial incentives, recognition and career development strengthened employee commitment, confidence and service quality, but their effectiveness was affected by organisational resources, supervision and working conditions. The study concludes that employee motivation contributes to service delivery at ASAS Dairies Limited, although motivation alone is insufficient to eliminate operational delays. The study recommends a fair motivation system that combines financial incentives, employee recognition and career development with effective supervision and adequate working resources.

Ocular drug delivery is associated with several challenges, including tear dilution, nasolacrimal drainage, blinking, and limited corneal drug absorption. The present study aimed to formulate and evaluate a gentamicin sulphate ophthalmic microemulsion to improve ocular drug delivery[1]. Gentamicin sulphate was incorporated using oleic acid as the oil phase, Tween 80 as surfactant, and ethanol or PEG 400 as co-surfactant. Pseudo-ternary phase diagrams were constructed at different surfactant-to-co-surfactant ratios to identify the suitable microemulsion region. Fourteen formulations were prepared by spontaneous emulsification and evaluated for physical appearance, pH, viscosity, globule size, zeta potential, drug content, and in vitro drug diffusion. Formulation optimization was performed using Design-Expert software, considering globule size and diffusion rate as responses[4]. The PEG-containing formulations showed comparatively better performance, and F9 was identified as the optimized formulation. F9 exhibited a globule size of 10.34 nm, pH 7.0, zeta potential of −26.8 mV, and drug content of 88.23%. The optimized formulation demonstrated a maximum diffusion rate of 88.8%. Drug-release data followed zero-order kinetics, while Korsmeyer–Peppas analysis indicated non-Fickian case-II transport. The optimized formulation showed antimicrobial activity against Escherichia coli, with a zone of inhibition of approximately 25.21 mm. Thus, the developed microemulsion demonstrated desirable physicochemical properties, enhanced drug diffusion, and antimicrobial activity, indicating its potential as an ophthalmic drug-delivery system[8].

Education is a foundation of national development, and regular learner attendance is a significant predictor of academic engagement and achievement. This study comparatively examined attendance policies and practices in elementary schools, focusing on their implementation, challenges, and perceived effects on learner absenteeism. Using a qualitative research design, structured interviews were conducted with seven elementary school teachers who had direct experience implementing attendance interventions. Findings revealed that consistent policy enforcement, parental involvement, incentive programs, systematic attendance monitoring, and positive reinforcement helped reduce absenteeism. However, overly punitive disciplinary practices could increase learner anxiety and disengagement and potentially lead to prolonged absences, underscoring the need for developmentally appropriate and supportive interventions. Socioeconomic conditions also influenced attendance patterns, as learners from low-income households encountered additional barriers to regular school participation. The study highlights the importance of balancing policy enforcement with responsive support that addresses learners’ developmental needs and socioeconomic circumstances. Strengthened school–family communication, early identification of attendance concerns, and context-sensitive interventions are therefore recommended. The findings may guide improvements in elementary school attendance policies and practices toward creating a more inclusive learning environment that promotes consistent learner participation and improved academic outcomes.

Homoeopathy interprets disease through individualised symptomatology and the theory of chronic miasms, whereas modern medicine relies on objective diagnostic investigations that demonstrate functional, structural, and pathological change. This conceptual article explores a theoretical correlation between the Hahnemannian miasms — Psora, Sycosis, and Syphilis — and the later-described Tubercular miasm, with findings obtained from basic haematological, biochemical, radiological, and other standard diagnostic investigations. Such correlation is proposed as a complementary theoretical layer that may aid clinical evaluation, holistic case assessment, and appropriate referral, without replacing individualised homoeopathic case-taking or established biomedical diagnosis. Diagnostic findings should not be regarded as direct biological markers of miasms, since miasmatic theory and modern diagnostic parameters belong to distinct frameworks of clinical interpretation. Further research employing standardised miasmatic criteria and objective diagnostic parameters is required to establish the validity, reproducibility, and clinical relevance of the proposed correlations.

Central Bank Digital Currency (CBDC) represents a digital form of central bank money and has emerged as an important area of monetary and financial research. Unlike commercial-bank deposits and privately issued electronic money, a CBDC is a direct liability of the central bank. India’s Digital Rupee (e₹), issued by the Reserve Bank of India (RBI), provides an important case for examining how sovereign digital money can coexist with cash, bank deposits and existing digital payment systems. This paper examines the concept, characteristics, forms, objectives, potential benefits, risks and economic implications of CBDCs, with particular emphasis on India. It discusses retail and wholesale CBDC, the role of intermediaries, programmability, offline functionality, privacy, cybersecurity, interoperability, financial inclusion, monetary policy, banking-sector effects and cross-border payments. The paper adopts a descriptive and analytical research approach based on secondary sources, including publications of the Reserve Bank of India and the Bank for International Settlements. The analysis suggests that CBDC should be understood not simply as another digital payment application, but as a new form of central bank money whose economic impact depends substantially on design, adoption, interoperability, privacy safeguards and its relationship with commercial banks.

This study examined the effect of expatriate leaders' cultural intelligence on subsidiary performance, with particular focus on the mediating role of alignment with local values in multinational corporations (MNCs) operating in Ghana. Using a quantitative cross-sectional design, data were collected from 185 expatriate leaders and 370 local employees across 12 MNC subsidiaries in the financial services, telecommunications, and manufacturing sectors. Cultural intelligence was measured using the Cultural Intelligence Scale (CQS), alignment with local values was assessed using a Local Value Alignment Scale, and subsidiary performance was measured using both objective and subjective performance indicators. Descriptive statistics, Pearson's correlation, hierarchical regression, and mediation analyses were conducted. Results revealed significant positive correlations between expatriate cultural intelligence and alignment with local values (r = 0.61, p <.001), alignment with local values and subsidiary performance (r = 0.58, p <.001), and cultural intelligence and subsidiary performance (r = 0.53, p <.001). Hierarchical regression analyses demonstrated that cultural intelligence significantly predicted alignment with local values (β = 0.59, p <.001) and subsidiary performance (β = 0.48, p <.001), and alignment with local values mediated the relationship between cultural intelligence and subsidiary performance (indirect effect = 0.24, 95% CI [0.17, 0.32]). The findings underscore that expatriate leaders with higher cultural intelligence are better equipped to align with local values, which in turn enhances subsidiary performance. Implications for expatriate selection, cultural training, and leadership development in African MNCs are discussed.

Nigeria faces a critical and growing housing deficit, which has escalated from 7 million units in 1991 to an estimated 28 million by 2024, driven by rapid population growth and urban migration. Hence, this paper examines the drivers of housing sector performance in Nigeria between 1992 and 2025, focusing on the "triple pillars" of mortgage bank operations: mobilizing deposits, providing loans, and building equities. Rooted in investment-based theory, this research utilized the Autoregressive Distributed Lag (ARDL) bound test approach to analyze the relationships between mortgage finance variables and housing supply, proxied by construction GDP. Secondary data were sourced from the Central Bank of Nigeria (CBN), National Bureau of Statistics (NBS), and the World Bank, among others. Findings revealed that mortgage equities and the monetary policy rate have a statistically significant influence on housing sector supply in the short run. However, no explanatory variables demonstrated a statistically significant impact in the long run. The study identifies a critical paradox where construction GDP is rising while the actual availability of housing units for the populace continues to decline. To address these challenges, this paper recommended that the Federal Mortgage Bank of Nigeria (FMBN) transition from volatile short-term deposits to sustained long-term savings schemes. Additionally, the government should shift policy focus toward mass social housing using locally produced materials. Also, the Nigeria Mortgage Refinance Company (NMRC) should further integrate mortgage-backed securities into the capital market to mitigate short-run volatility and incentivize private sector participation.

Nigeria’s agricultural sector remains chronically underperforming relative to its immense potential, largely due to macroeconomic volatility that systematically undermines productivity. Hence, this study investigated the macroeconomic drivers of agricultural output growth in Nigeria, specifically assessing the impacts of the GDP growth rate, monetary policy rate (MPR), exchange rate, and inflation rate. Utilizing an ex-post facto research design, the study analyzed annual time-series data spanning from 1986 to 2025 sourced from the Central Bank of Nigeria, the National Bureau of Statistics, and the World Bank. Autoregressive Distributed Lag (ARDL) bounds testing approach was employed the to examine both short-run and long-run dynamics. Findings indicated the existence of a long-run equilibrium relationship between the selected macroeconomic variables and agricultural output. In the short run, the GDP growth rate significantly stimulates agricultural output, with a 1% increase leading to a 0.302% rise in output. Conversely, the MPR exerts a negative short-run impact (-0.139%) due to high borrowing costs for capital, though it shows a positive relationship in the long run. The exchange rate demonstrated a positive influence on output in both the short and long run, suggesting that currency movements may enhance domestic competitiveness. Inflation was found to consistently erode profit margins and decrease output across both time horizons, with a 1% increase resulting in a -0.008% decrease in output. Thus, this paper recommended that the Central Bank of Nigeria (CBN) establishing single-digit interest rate windows for the agricultural sector to insulate farmers from broad monetary tightening. The Federal Ministry of Agriculture and Food Security (FMAFS) should prioritize the digital distribution of high-quality inputs via the Agro-Pocket platform to eliminate middlemen. Additionally, the government should implement input price buffers to mitigate inflationary pressures and design policies to integrate local farmers into the African Continental Free Trade Area (AfCFTA), amongst others.

Background: Uterine fibroids, also known as leiomyomas, are common benign tumours of the uterus and may be associated with heavy menstrual bleeding, pelvic pain, pressure symptoms and reproductive difficulties. Homoeopathic treatment has been described in individual case reports, observational studies and a randomized comparative trial, but the strength of evidence remains uncertain.
Objective: To narratively review published clinical studies and reports describing homoeopathic management of uterine fibroids, with particular attention to patient characteristics, medicines prescribed, clinical outcomes and limitations of the available evidence.
Materials and Methods: Published reports identified through Google Scholar and online journal platforms from February to September 2026 were reviewed. Relevant reports describing homoeopathic management of uterine fibroids in human participants were selected. Information regarding study design, participants, medicines, outcome measures and reported outcomes was extracted and synthesized narratively.
Results: The identified literature included one randomized comparative trial (LM versus centesimal potencies), a prospective observational study, an observational study, and multiple case reports. Medicines reported included Calcarea carbonica, Phosphorus, Pulsatilla, Sulfur, Lycopodium, Sepia, Natrum muriaticum and Thuja occidentalis. Reported outcomes included reduction in symptoms and menstrual bleeding and, in individual reports, reduction or disappearance of fibroids on ultrasonography. However, most reports were uncontrolled and had small sample sizes, and the single randomized trial compared two potency systems without a placebo group, making causal interpretation difficult.
Conclusion: Published reports describe potentially favourable clinical outcomes following homoeopathic treatment of uterine fibroids. However, the available evidence is predominantly observational or based on individual case reports, and the only randomized trial identified compared two potency systems without a placebo arm; the evidence therefore cannot establish treatment efficacy. Well-designed placebo-controlled studies with objective imaging, standardized symptom measures, adequate follow-up and systematic safety reporting are required.

Community engagement is increasingly recognised as an important component of improving students’ academic performance. The engagement creates opportunities for parents, teachers, school leaders and other community stakeholders to collaborate in supporting teaching and learning. However, effective community engagement remains difficult in many rural public secondary schools in Tanzania. This study examined the challenges of community engagement in enhancing academic performance in rural public secondary schools. It employed a mixed-methods approach involving 195 respondents drawn from four public secondary schools: (Frank Weston, Mataka, Matemanga and Mgomba). Data were collected using questionnaires survey, interviews and documentary review. The collected data were analysed using descriptive statistics and thematic analysis. The findings indicated generally low levels of parental participation in key educational activities. Only 6.7% of respondents indicated that parents supervised students’ learning at home, while 6.0% reported regular communication between parents and teachers. Attendance at school meetings was comparatively higher at 31.3%, although substantial differences existed among schools: 47.1% at Frank Weston, 25.0% at Mataka, 44.4% at Matemanga and 12.5% at Mgomba. Homework checking was also limited, with Mataka recording the highest participation at 15.0%. These patterns demonstrate key engagement challenges, particularly weak parent-teacher communication, limited home-based supervision, low homework monitoring and uneven participation in school meetings. The study concludes that strengthening school-community partnerships is necessary for improving academic support in rural secondary schools. It recommends strengthening parent-teacher communication, increasing community awareness, establishing regular and flexible school-community engagement mechanisms and equipping parents with practical knowledge for supporting students’ learning at home.

Centre-Based Management Committees (CBMCs) are an essential link between adult learning/literacy centres and the communities they serve. CBMCs are made up of a range of local people involved with their learning/literacy centres. CBMCs work to increase communities’ involvement with education, and to help improve the quality and effectiveness of learning/literacy centres. The objectives of this study were to determine the effectiveness of Centre Based Management Committees in: Resource mobilization, Centre supervision, and Community mobilization for adult literacy centres in Yobe State, Nigeria. Survey was used as a research design for the study. The population of the study covers the Government owned adult literacy centres in Yobe State. Records from the Yobe State Agency for Mass Education put the number of Adult Literacy Centres as 102. A sample of 68 literacy centres were sampled using purposive sampling technique. The research instruments used were questionnaire, records from the adult literacy centres and Focus Group Discussion (FGD). The questionnaire was given to experts for face and content validation. Pretest was used to determine the reliability of the instrument. This was done using split half and a reliability coefficient of .78 was obtained indicating the instrument was highly reliable. A checklist was developed by the researcher to conduct physical observation of what the CBMCs have put in place at their various adult literacy centres. The data was analysed using descriptive statistics of frequency counts, percentages and mean. The findings of the study showed that Community Based Management Committees are not highly effective in resource mobilization for adult literacy centres in Yobe State; their effectiveness in centre supervision of adult literacy centres is very high and their effectiveness in community mobilization for adult literacy centres is high. The study concluded that Community Based Management Committees are highly effective in all areas investigated except resource mobilization for adult literacy centres in Yobe State. Amongst the recommendations made was that the State Agency for Mass Education in collaboration with NGOS operating in Yobe State should organize periodic capacity building workshops for CBMCS on resource mobilization.

Unnāb (Ziziphus sativa Gaertn.), belonging to the family Rhamnaceae, is an important medicinal and fruit-bearing plant traditionally used in the Unani system of medicine. Its fruits are valued for their nutritional and therapeutic properties and are traditionally used particularly in respiratory, inflammatory and digestive conditions. The present review summarizes the available information on the botanical characteristics, traditional uses, Mizaj, phytochemical constituents and pharmacological activities of Unnāb. Reported pharmacological studies demonstrate a broad spectrum of activities, including antioxidant, anti-inflammatory, antimicrobial, immunomodulatory, hepatoprotective, gastroprotective, anxiolytic, anticancer, antidiabetic, anti-allergic, anthelmintic and wound-healing effects. These findings provide experimental support for several traditional therapeutic applications of Unnāb. However, much of the available evidence is derived from in-vitro and experimental studies, while clinical evidence remains limited. Further standardized pharmacological, toxicological and clinical investigations are therefore warranted to establish its therapeutic efficacy, safety and scientific relevance in Unani medicine.

This article examined the existing ship inspection and survey procedures adopted in seaports in Port Harcourt, drawing directly from Objective One of the M.Sc. dissertation by Asangansi, Okwong Eyo. The study assessed defined procedures, inspection intervals, documentation and statutory certificates, physical examination of vessel structures and safety equipment, safety and pollution-prevention requirements, risk-based considerations, communication of findings, follow-up of deficiencies, consistency and institutional coordination. A descriptive survey design was adopted. The population comprised 600 maritime professionals and personnel within the Port Harcourt and Onne maritime environment. A sample size of 240 was used; 228 questionnaires were valid, representing a 95.0% response rate. Data were collected with a structured five-point Likert questionnaire and analysed using descriptive statistics, Pearson Product-Moment Correlation and multiple regression. The objective-specific result produced a composite mean of 3.80 (SD = 1.02), above the 3.00 decision benchmark, indicating general agreement that existing procedures were present and operational. Item means ranged from 3.70 to 3.89. Institutional coordination recorded the lowest mean (3.70), while appropriate inspection intervals recorded the highest (3.89). The finding indicates that the principal procedural components were established, but coordination and process integration remained comparatively weaker dimensions.

This article examined the relationship between energy cost changes and transportation costs in Abuja, Federal Capital Territory, Nigeria. The article was derived from the first objective of a study that investigated energy cost changes and transportation and logistics operations in Abuja. A quantitative cross-sectional survey design was adopted. The accessible population comprised transportation operators, logistics firms, courier and dispatch operators, haulage firms, warehouse and distribution operators, and e-hailing and delivery-platform operators. A reported sample of approximately 303 respondents was determined using the Taro Yamane formula, while the empirical correlation reported for the first hypothesis was based on 300 observations. Data were collected with a structured questionnaire and analysed using descriptive statistics and Pearson Product Moment Correlation. The descriptive findings showed agreement that energy-cost increases raised vehicle operating costs (M = 4.26), passenger and goods transportation costs (M = 4.23), transportation fares and charges (M = 4.20), maintenance and operating expenses (M = 4.23), and overall transportation costs (M = 4.27). The Pearson correlation result showed a positive and statistically significant relationship between energy cost changes and transportation costs (r = 0.642, p = 0.000). The null hypothesis was therefore rejected. The finding supports the Cost-Push Inflation Theory by indicating that higher energy input costs are associated with higher transportation costs. The article recommends stronger fuel and energy-cost management, route optimisation, preventive maintenance, realistic budgeting and flexible pricing strategies among transportation operators in Abuja.

This article examined the nature of freight forwarding operations and the level of port performance at Apapa Seaport, Lagos. It was derived from Objectives One and Two of the dissertation, which examined the characteristics of freight forwarding activities and assessed Apapa Port’s performance. Data were obtained from 187 respondents drawn from port stakeholders, and descriptive analysis was conducted using weighted mean scores with a criterion mean of 3.0. The findings showed that respondents disagreed that freight forwarding operations involved extensive cargo documentation and customs-clearance activities (M = 2.4) and disagreed that transportation and cargo delivery were efficiently coordinated (M = 2.5). Conversely, warehousing and cargo consolidation (M = 3.3), international trade facilitation (M = 3.3), and digital technology adoption (M = 3.4) were positively assessed. Port performance was mixed: cargo-handling efficiency (M = 2.4) and vessel turnaround time (M = 2.5) were assessed below the criterion mean, while cargo clearance (M = 3.2), infrastructure support (M = 3.4), and handling of large cargo volumes (M = 3.3) were assessed positively. The article argues that freight forwarding at Apapa is multidimensional and that port capacity does not automatically translate into efficient cargo handling or vessel turnaround. The findings highlight the need for coordinated documentation, multimodal transport, digitalisation, modern handling equipment, and integrated port management.

This article examined the relationship between vessel waiting time and maritime transport efficiency in Lagos seaports, with particular attention to the operational experience of stakeholders at Apapa Port, Tin Can Island Port and Lekki Deep Seaport. The article was developed from the first objective of the parent M.Sc. study on port congestion and maritime transport in Lagos seaports. The study adopted a descriptive and explanatory research design and used a structured four-point Likert-scale questionnaire. A sample of 286 stakeholders was obtained using the Taro Yamane formula from an accessible population of 1,000, followed by stratified allocation across the three selected ports and stakeholder categories. All 286 questionnaires administered were retrieved and validated for analysis. Descriptive statistics were used to summarize respondents' views, while Pearson Product Moment Correlation (PPMC) was applied at the 0.05 level of significance. The descriptive results showed mixed perceptions: respondents agreed that vessel waiting time contributes to cargo-delivery delays and that reducing waiting time would improve overall maritime transport efficiency, while some respondents did not agree that waiting before berthing sufficiently reduced efficiency or increased the time required to complete port operations. The inferential analysis produced a weak negative relationship, r = −0.150, p = 0.011, N = 286. Since p < 0.05, the null hypothesis was rejected. The article concludes that vessel waiting time has a statistically significant but weak relationship with maritime transport efficiency in Lagos seaports. The result supports targeted attention to berth allocation, vessel scheduling, marine traffic coordination and information sharing rather than treating vessel waiting time as the sole explanation for port performance.

This article examined the relationship between environmental sustainability practices and sustainability awareness among maritime operators in Nigeria’s maritime industry, with emphasis on Port Harcourt and Lagos. The study used the dissertation’s original descriptive survey evidence. A structured questionnaire was administered to maritime stakeholders and 303 valid responses were analysed. Descriptive statistics and Pearson Product Moment Correlation (PPMC) were applied using SPSS 27 at a 5% significance level. Respondents disagreed that maritime organizations adequately complied with environmental sustainability policies and that environmental protection measures were effectively implemented, but agreed that waste management systems were adequately maintained, shipping activities were monitored to prevent marine pollution, and sustainability awareness was high. The reported PPMC result was r = 0.189, p = 0.000, N = 303, indicating a statistically significant positive relationship between organizational compliance with environmental sustainability policies and sustainability awareness. The article concludes that environmental awareness is associated with organizational sustainability practice, while implementation and compliance remain important areas for improvement.

This article develops Objective One of the uploaded study on human capacity development and workforce challenges at Onne Seaport, Rivers State. The objective was to assess the level of human capacity development among the workforce. The study treats human capacity as a combination of training, retraining, professional certification, technical competence and continuous development. The Chapter Four analysis reports 303 valid observations. Descriptive results show a mean of 2.6 for regular training and retraining, 3.0 for improvement in operational efficiency from human-capacity programmes, 3.3 for availability of professional certification opportunities, 3.9 for training enhancement of technical competence, and 3.0 for workforce development's contribution to faster cargo handling and service delivery. The first hypothesis test reports a Pearson correlation of r = 0.151, p = 0.008, N = 303 between regular training/retraining and workforce-development outcomes. The relationship is weak but statistically significant. The article interprets the result through Human Capital Theory and Systems Theory and relates it to the study's cited Nigerian and international literature. It concludes that workforce development is relevant to port performance, while the regularity and institutionalisation of training require improvement.

This article examined the effect of road infrastructure on urban mobility in Port Harcourt, Rivers State, based on Objective One of Joan's M.Sc. study on public transportation and mobility challenges. The study used quantitative survey data collected from 400 respondents comprising commuters, commercial drivers, transport operators, residents, traffic-management officials and transport-regulatory personnel. Data were analysed with descriptive statistics and Pearson Product Moment Correlation at the 5% significance level. The descriptive analysis showed that respondents agreed that potholes and damaged roads reduce transportation efficiency (M = 3.0), flooded roads negatively affect commuter movement (M = 3.2), inadequate road maintenance contributes to traffic congestion (M = 3.4), and good road infrastructure improves urban mobility and accessibility (M = 3.3). The only item below the 3.00 criterion mean was the statement that poor road conditions contribute to transportation delays (M = 2.4). The inferential result produced a positive correlation of r = 0.189 with p = 0.000 and N = 400, leading to rejection of H01. The result indicates a statistically significant positive association between the road-infrastructure measure used in the study and urban mobility/accessibility. The finding reinforces the importance of road condition, drainage, maintenance and infrastructure quality in the mobility system of Port Harcourt.

Background: Inhibition of heat-induced albumin denaturation is a simple, widely used in-vitro screen for anti-inflammatory potential. Cinchona officinalis mother tincture (Q) is used in homoeopathy as China officinalis, yet its behaviour in this assay has not been documented. This basic study provides baseline data and a reproducible, solvent-controlled protocol for further research on mother tinctures.
Objective: To measure the percentage inhibition of albumin denaturation produced by Cinchona officinalis Q at 6.25, 12.5, 25, 50 and 100 µL/mL and to compare it with 80% v/v ethanol at the same concentrations.
Methods: Egg albumin, phosphate-buffered saline (PBS, pH 6.4) and test solution were incubated at 37 °C for 20 min and heated at 70 °C for 10 min. Turbidity was read at 660 nm. Q (Dr. Willmar Schwabe; 80% v/v ethanol) and an ethanol control of the same strength were tested in triplicate. Final ethanol content (0.2% to 3.2% v/v) was identical in matched Q and ethanol tubes.
Results: Control absorbance was 0.030. Q produced 0.00% to 0.22% inhibition across the five concentrations, with a small, measurable response from 12.5 µL/mL upwards (maximum 0.22% at 100 µL/mL), whereas the ethanol control produced no inhibition (0.00%) at any concentration.
Conclusion: This foundation study establishes a reproducible protocol with a matched ethanol control and documents the response of Q under defined conditions. Q showed a small but measurable inhibition of albumin denaturation relative to the ethanol control, which showed none, giving an encouraging early signal; the parameters (albumin concentration, concentration range, positive control) can now be optimised to characterise this response in the next phase of research.

Kho-Kho is a traditional Indian team game, which involves movement, acceleration, deceleration, frequent changes of speed, direction and intensity of movement along with performance of sport specific skills. The present study focused on the correlation between the selected components of motor fitness and the playing ability in male college players of Kho-Kho game. The participants for the study for the academic year 2024–2025 and 2025–2026 involved 50 male Kho-Kho players aged 18-23 years from Guru Kashi University Talwandi Sabo Punjab. A battery of physical fitness tests was used to assess the selected motor fitness components, such as the 50-m sprint for speed, shuttle run for agility, standing broad jump for explosive leg power, push ups for muscular endurance and 12-minute run/walk test for cardiovascular endurance. Game play was evaluated using an observation and rating system that observed and rated both defending and chasing skills. Descriptive statistics and Pearson's product moment correlation coefficient were used to assess the association between the motor fitness components and playing ability. The motor fitness components that were evaluated were significantly related to playing ability for all of the six components. The 50-m sprint's time was strongly correlated with playing ability (r = −0.68, p < .001), and the shuttle run's time was also strongly correlated with playing ability (r = −0.72, p < .001). The standing broad jump and the push-up performance correlated well with each other (r = 0.78 and 0.73, respectively, p < 0.001 for both). There was also a strong positive correlation between the cardiovascular endurance and playing ability (r = 0.61, p < 0.001). The negative correlations with the sprint and shuttle run times suggest that a decrease in run times correlated with higher playing ability scores. The combined results suggest that certain motor fitness attributes were significantly correlated to playing ability in the male college level Kho-Kho players. The study however, was a correlational study and the results were used to establish causality.

This study examines rural entrepreneurs' reported use of digital platforms, perceived business support and barriers to effective use. A descriptive quantitative survey used a structured questionnaire with 50 purposively selected entrepreneurs. Frequencies and percentages summarised the responses. Forty-eight respondents (96.0%) reported using digital platforms. The frequency-of-use item contained 48 recorded responses, including 40 reporting daily use (83.3%). Facebook received 35 selections, equivalent to 70.0% of the full sample. For four market-access and customer-engagement items, 48 respondents (96.0%) strongly agreed that platforms supported advertising, wider customer reach, communication and customer attraction or sales. All 50 agreed that platforms supported business payments, and all strongly agreed that they assisted financial management. Responses on learning business skills were weaker: 25 (50.0%) disagreed, 20 (40.0%) were neutral and five (10.0%) agreed. Data costs and security concerns were each identified by all respondents; 40 (80.0%) identified network limitations and 30 (60.0%) reported limited digital skills. These findings describe perceptions within a purposive sample and do not establish changes in measured business performance. The study suggests that connectivity, affordability, practical training and digital security deserve attention alongside platform access.

Background: School sports programs play a critical role in promoting female participation and achievement in athletics, yet gender-specific barriers often limit their full potential. Grounded in Sandra Bem's Gender Schema Theory, this study examines how school sports programs in Dodoma City facilitate success for female athletes.
Objectives: To analyze participation patterns, assess athletic and personal development outcomes, and identify major institutional and socio-cultural barriers facing female student-athletes in Dodoma City secondary schools.
Methods: A quantitative cross-sectional study design was employed. Simple random sampling was used to select 414 female athletes across four secondary schools in Dodoma City. Primary data were collected using structured questionnaires and analyzed via SPSS version 26 using descriptive statistics and cross-tabulations.
Results: Football (44.7%) and netball (31.9%) emerged as the most popular sports among participants. While 77.1% of athletes received formal instruction, the vast majority (81.0%) participated primarily at the school level, as higher levels of competition were associated with significantly reduced participation rates. Participation in school sports yielded significant positive outcomes, including school championships, individual awards, enhanced physical fitness, elevated self-confidence, improved teamwork, and developed leadership skills. However, key barriers persist, including inadequate sports infrastructure, a lack of dedicated changing facilities, limited training opportunities, prevailing gender stereotypes, and restricted access to higher-level competitive platforms.
Conclusion: School sports programs in Dodoma City substantially enhance female athletes' achievements, self-efficacy, and career aspirations. To sustain and expand these gains, targeted interventions are needed, including investments in gender-responsive facility infrastructure, robust coaching development systems, expanded competitive pathways, and policies advocating for equal participation and long-term athletic development.

Voice-based smart door locking systems offer a keyless, hands-free access control solution for smart home environments. However, existing deployments remain vulnerable to replay attacks, wherein pre-recorded voice clips are used to impersonate enrolled users. This paper presents a proto-type smart door locking system that combines Emphasized Channel Attention, Propagation and Aggregation Time Delay Neural Network (ECAPA-TDNN) speaker verification with a two-stage authentication pipeline designed for deployment on the Raspberry Pi 4 embedded platform. The system extracts 192-dimensional speaker embeddings and performs cosine similarity scoring against enrolled templates with a decision threshold of
0.30. Experimental evaluation across 400 trials comprising 100 genuine speaker utterances and 300 impostor attempts including male, female, and replay attack scenarios achieved a False Rejection Rate (FRR) of 0.0%, False Acceptance Rate (FAR) of 1.0%, Equal Error Rate (EER) of 0.5%, and overall accuracy of 99.2%. Notably, the replay attack impostor was completely rejected (0% FAR), demonstrating inherent resistance to basic spoofing without dedicated countermeasures. A Gaussian Mixture Model (GMM) baseline achieved only 78% accuracy on the trained phrase, confirming the superiority of deep speaker embeddings for text-independent verification. The proposed system targets sub-second end-to-end latency on Raspberry Pi with TensorFlow Lite int8 quantization for the anti-spoofing countermeasure stage.

Healthcare applications increasingly depend on cloud platforms, Internet of Medical Things (IoMT) devices, electronic health records (EHRs), wearable sensors, and distributed clinical decision support systems. This digital transformation improves monitoring and care delivery, but it also expands the attack surface of hospital information systems. Conventional security mechanisms are usually deployed in isolated layers, such as network firewalls, authentication systems, or device monitoring tools. Such isolated controls are insufficient for predicting integrated security risk because healthcare attacks may simultaneously affect network behavior, device telemetry, user access patterns, and patient safety indicators. This paper proposes an Integrated Healthcare Security Risk Prediction Model (IHSRPM) that applies big data analytics and machine learning to combine EHR attributes, IoMT sensor streams, network flow records, and access audit logs into a unified risk prediction pipeline. The proposed model performs ingestion, preprocessing, feature engineering, risk labeling, model training, and decision support for secure healthcare operation. A prototype experiment was conducted on a synthetic de-identified healthcare-security dataset consisting of patient records, sensor streams, network traffic logs, audit logs, and an integrated machine-learning view. Five classifiers, namely Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Gradient Boosting, were evaluated using accuracy, precision, recall, F1-score, AUC, and confusion matrix analysis. The results indicate that tree-based classifiers are highly effective for rule-structured healthcare-security risk detection, while Logistic Regression and SVM provide useful baselines for interpretable and margin-based detection. The paper also discusses how the proposed model can be extended using public datasets such as WUSTL-EHMS-2020, CICIDS2017, and MIMIC-IV under ethical and access-compliant conditions. The proposed framework contributes a practical architecture for predictive security analytics in healthcare applications by integrating cyber, clinical, device, and privacy dimensions into one risk-aware analytical model.

Commercial surrogacy raises complex questions at the intersection of reproductive autonomy, economic rights, social justice, and state regulation. The research problem addressed in this study is the extent to which public-law frameworks governing surrogacy can regulate economic transactions while protecting the rights and interests of surrogate mothers, intending parents, and children. The purpose of this study is to comparatively examine the legal approaches to commercial surrogacy in India and developed countries with particular emphasis on the economic and social consequences of state regulation. The study adopts a doctrinal and comparative legal methodology, analysing legislation, judicial decisions, constitutional principles, and relevant legal scholarship in both jurisdictions. The research finds significant differences in the two regulatory models concerning the permissibility of commercial arrangements, protection of surrogate mothers, allocation of economic risks, and the role of the state in addressing exploitation and inequality. The study further identifies tensions between restricting commercial surrogacy and ensuring reproductive autonomy and economic agency. It concludes that effective surrogacy regulation requires a rights-based public-law framework that addresses both the potential economic vulnerabilities of surrogate mothers and the broader social interests involved in assisted reproduction.

The present study was undertaken to investigate the phytochemical profile and in vitro antiurolithiatic and anti-inflammatory activities of the ethanolic extract of Croton sparsiflorus (EECS). The dried and powdered plant material was extracted with ethanol using the Soxhlet extraction method, yielding 22.5% w/w of extract. Preliminary phytochemical screening revealed the presence of alkaloids, flavonoids, phenolic compounds, tannins, saponins, terpenoids, steroids, glycosides, and carbohydrates, whereas proteins and anthraquinones were absent. The antiurolithiatic potential of EECS was evaluated using calcium oxalate nucleation, crystal-growth, and aggregation assays at concentrations ranging from 100 to 1,000 µg/mL. The extract exhibited a concentration-dependent inhibitory effect in all three assays. At 1,000 µg/mL, EECS produced 78.91 ± 2.04% inhibition of nucleation, 75.62 ± 1.96% inhibition of crystal growth, and 73.84 ± 1.88% inhibition of crystal aggregation, compared with 91.48 ± 1.27%, 89.76 ± 1.34%, and 88.92 ± 1.29%, respectively, for the standard drug. One-way ANOVA demonstrated highly significant differences among the tested concentrations for nucleation (F = 1463.89; p = 1.15 × 10⁻¹⁴), crystal growth (F = 1407.31; p = 1.43 × 10⁻¹⁴), and aggregation (F = 1374.23; p = 1.60 × 10⁻¹⁴). Anti-inflammatory activity was assessed using the egg albumin protein-denaturation assay. EECS showed an optical density of 0.129 and 71.26% inhibition of protein denaturation, whereas the standard drug produced an optical density of 0.146 and 67.48% inhibition. These findings indicate that the ethanolic extract of Croton sparsiflorus possesses promising in vitro antiurolithiatic and anti-inflammatory activities, which may be attributed to the synergistic effects of its phytochemical constituents. Further isolation of active compounds, toxicity assessment, mechanistic studies, and in vivo investigations are warranted to establish its therapeutic potential.

Cancer remains a major global health challenge, and natural products continue to be investigated as potential sources of anticancer agents. This study evaluated the methanol extract of Detarium microcarpum root bark for effects on cancer-cell viability and angiogenesis using a cell-viability model and the chick chorioallantoic membrane (CAM) assay. Preliminary phytochemical screening detected alkaloids, flavonoids, tannins, saponins, phenolics, terpenoids, steroids and glycosides. The illustrative dataset showed concentration-dependent reductions in cell viability and CAM vascular development, with an estimated IC50 of 232.1 µg/mL and 54.2% inhibition of angiogenesis at 400 µg/mL. These findings suggest potential antiproliferative and antiangiogenic activity of the extract. However, the numerical results are hypothetical and are included for manuscript development and statistical illustration. Experimental validation using the actual laboratory dataset is required before biological conclusions can be established.

This study examined factors hindering effective teaching and learning of Computer Science in tertiary institutions in Borno State, focusing on students’ mathematics background, ICT infrastructure, and classroom space. A quantitative descriptive survey was conducted among 168 respondents comprising 160 students and 8 lecturers from five tertiary institutions in three Local Government Areas. Data were collected using a validated structured questionnaire and analysed using descriptive statistics and Pearson chi-square tests at the 0.05 significance level. The findings showed a significant relationship between mathematics background and academic performance (χ² = 14.28, p = .006). ICT facilities were generally inadequate, particularly alternative power supply (M = 1.89). Classroom overcrowding was also significantly associated with lecturers’ adoption of technology-driven pedagogy (χ² = 11.45, p = .003). The study recommends targeted infrastructure investment, mathematics bridging programmes, improved laboratory capacity, and better management of classroom and laboratory capacity.

Diabetes mellitus is a metabolic disorder associated with persistent hyperglycaemia, impaired metabolic regulation, oxidative stress, and progressive tissue damage. This study evaluated the antidiabetic effect of methanolic leaf extract of Adansonia digitata in streptozotocin-induced diabetic Wistar rats. A laboratory-based experimental design was employed using 40 Wistar rats randomly divided into five groups of eight animals each: normal control, diabetic control, A. digitata extract-treated groups receiving 200 and 400 mg/kg, and a standard-drug group. Diabetes was induced using streptozotocin, while the extract was administered during the treatment period. Body weight and fasting blood glucose were monitored, while HbA1c, insulin, lipid profile, liver and renal function indices, oxidative-stress and antioxidant parameters, and pancreatic histopathology were evaluated at the end of treatment. The study found that diabetic control rats exhibited significant hyperglycaemia, increased HbA1c, lower insulin levels, dyslipidaemia, and signs of organ stress and injury. Treatment with A. digitata extract showed improvement in these conditions in a dose-dependent manner. At 400 mg/kg, fasting blood glucose levels dropped significantly from 329.00 mg/dL to 149.63 mg/dL, HbA1c decreased from 13.33% to 6.85%, and insulin levels rose from 4.15 to 9.19 µIU/mL. Additionally, the extract enhanced lipid profiles, liver and renal functions, antioxidant levels, and reduced pancreatic injury, indicating its potential as an antidiabetic agent in STZ-induced diabetic rats.

Frequent fire disasters that affects markets across Nigeria has devastating economic and social consequences on businesses, households and authorities. Regularities of markets fire disasters in every part of this country, has made the need to evolve adaptive strategies very imperative. This study investigated the problems related to markets fire disasters in Nigeria generally and specifically in North-western Nigeria. The problem of recurring fire disasters in Sokoto Central market and Sabon-gari market in Kano, Nigeria was interrogated. An elaborate methodology has been developed which facilitates inquiry. The data generated both primary and secondary was analyzed using appropriate statistical tools that usher in empirical findings that help draw a logical conclusion about the effectiveness or otherwise of the adaptive strategies of government on markets fire disasters in the selected states of North-western Nigeria. The research work also develop an empirical postulations for resilience and rehabilitation for disaster-prone communities and businesses. The study also made workable recommendations aimed at enhancing the adaptive strategies of managing markets fire disasters in Nigeria with a view to make them more effective so as to mitigates these recurring disasters.

The rapid development of Artificial Intelligence (AI) is bringing significant changes to education, including the teaching and learning of Social Sciences. Social Science education plays an important role in developing critical thinking, analytical abilities, social awareness, and an understanding of contemporary society. In this context, AI offers new possibilities for making teaching and learning more interactive, personalised, accessible, and learner-centred (Holmes et al., 2019; Luckin et al., 2016). AI-based tools can assist educators in designing instructional materials, generating learning resources, creating classroom activities, and supporting students in exploring complex historical, political, social, economic, and geographical issues.
This paper examines the opportunities, challenges, and innovative pedagogical methods associated with the integration of Artificial Intelligence into Social Science education. It discusses the potential of AI across History, Political Science, Sociology, Economics, and Geography through adaptive learning, AI-assisted research, simulations, data analysis, and inquiry-based learning. At the same time, it examines critical challenges such as misinformation, algorithmic bias, academic integrity, privacy concerns, digital inequality, and over-reliance on automated tools (UNESCO, 2021, 2023). In the Indian context, the discussion is also related to the objectives of the National Education Policy (NEP) 2020, particularly its emphasis on technology-enabled education, multidisciplinary learning, and the development of higher-order thinking skills (Ministry of Education, 2020). The paper argues that AI should function as a pedagogical aid rather than a replacement for human educators. Effective integration requires AI literacy, ethical awareness, critical evaluation, teacher preparedness, and appropriate institutional support (Miao & Cukurova, 2024). The paper concludes that a balanced teacher–AI partnership can strengthen Social Science education while preserving critical inquiry, human judgement, and meaningful teacher–student interaction.

Background: Atopic dermatitis (AD) is a chronic, relapsing inflammatory skin disease that affects all age groups. Information on how homoeopathic physicians prescribe for atopic dermatitis in routine hospital practice is limited.
Objective: To describe the demographic profile and first-visit homoeopathic prescribing patterns of patients with atopic dermatitis attending a homoeopathic hospital.
Methods: Retrospective review of outpatient records of patients with atopic dermatitis seen between April and September 2026. Repeat visits were removed so that each patient was counted once, and the first recorded prescription was analysed using descriptive statistics.
Results: Thirty patients were included (16 female, 14 male; age 2–79 years; mean 31.3 years); 10 (33.3%) were under 18 years. A first-visit medicine was recorded for 30 patients, all percentages for medicines are of these 30. Calcarea carbonica was prescribed to 7 (30.4%), Sulphur to 5 (21.7%) and Natrum muriaticum to 5 (21.7%); 13 other medicines were each prescribed once. LM potencies were recorded for 13 of the 30 patients.
Conclusion: Nine medicines were prescribed at the first visit, and no single medicine predominated. The study describes prescribing practice only; it cannot show whether any medicine is effective. Prospective studies with standardised outcome measures are needed.

This article examines the extent of maritime safety regulatory compliance among shipping operators in Rivers State, Nigeria, within the wider study of maritime safety compliance and sustainable shipping development. The study covers the 2020–2026 period and focuses on Port Harcourt, Onne and Bonny. Maritime safety compliance is treated as a multidimensional practice involving adherence to applicable national laws and international standards, vessel inspection and certification, seafarer competence, safety management, emergency preparedness, environmental protection and regulatory enforcement. A quantitative cross-sectional survey framework was designed for an estimated population of 1,200 maritime professionals, with a proposed sample of 300 selected through proportionate stratified sampling. The dissertation's Chapter Four numerical results are explicitly identified in the source as simulated and illustrative, not verified field observations. Within that simulated dataset, mean scores for the major compliance constructs were above the midpoint of the five-point scale: inspection/certification (3.549), seafarer training (3.632), safety management/enforcement (3.464), and environmental compliance (3.446). The article therefore presents these values as illustrative perceptions rather than evidence of actual sector-wide compliance. The study's literature indicates that effective compliance depends on implementation, monitoring, corrective action and organisational commitment, not merely the existence of regulations (IMO, 2026e, 2026g; NIMASA, 2026a–f). The article concludes with a framework for validating compliance using verified field and administrative data.

This article examined the effect of port congestion on cargo delivery time at Apapa Seaport, Lagos, drawing specifically from the first objective of Oyakhamoh Ibrahim’s dissertation on the determinants of port congestion and supply chain efficiency in Apapa Seaport. The article focused on congestion as an operational condition arising from the interaction of vessel waiting time, truck queues, cargo evacuation constraints, terminal capacity, cargo dwell time and related coordination challenges. The source study adopted a descriptive and correlational survey design and collected questionnaire responses from port and logistics personnel. Chapter Four reported 306 valid responses and applied descriptive statistics and Pearson Product Moment Correlation (PPMC). The univariate results showed agreement that congestion increases the time required to deliver cargo, creates long truck queues, reduces cargo-delivery efficiency, produces unpredictable delivery schedules and that congestion reduction would improve delivery speed and reliability. The PPMC result reported a statistically significant relationship between the two measures used for the first hypothesis, with r = -0.159 and p = 0.005. Accordingly, the first null hypothesis was rejected. The article interprets the result within the conceptual and theoretical arguments presented in the dissertation, particularly Queuing Theory, Systems Theory and Supply Chain Management Theory. The evidence indicates that cargo delivery performance at Apapa cannot be separated from the capacity, coordination and reliability of the wider port and inland logistics system. The article concludes that congestion management should combine improved berth and truck scheduling, cargo evacuation coordination, digital information exchange and multimodal transport capacity rather than rely on a single intervention.

This article examines the relationship between green port infrastructure and environmental performance at Port Harcourt Port, Rivers State, Nigeria. The article is derived from the first objective of a broader study on sustainable port operations and environmental performance. A survey research design was adopted. Data were obtained from 267 respondents involved in port operations and environmental management, and all 267 questionnaires administered were retrieved and found valid. Descriptive statistics and Pearson Product Moment Correlation (PPMC) were used at the 5% level of significance. Descriptively, respondents agreed that green infrastructure investments enhanced environmental sustainability (mean = 3.3), that renewable-energy facilities reduced environmental degradation (mean = 3.1), and that eco-friendly port infrastructure improved overall environmental quality (mean = 3.0). However, respondents did not agree that the existing availability of environmentally friendly infrastructure had sufficiently reduced pollution (mean = 2.6) or that modern cargo-handling equipment had adequately improved environmental performance (mean = 2.6). The inferential result showed a positive and statistically significant relationship between green port infrastructure and environmental performance (r = 0.153, p = 0.012, N = 267). The null hypothesis was therefore rejected. The article concludes that green port infrastructure is associated with environmental performance at Port Harcourt Port, while the descriptive results also indicate areas where infrastructure adequacy and modern equipment require further attention. The article recommends sustained investment in environmentally friendly facilities, cleaner cargo-handling equipment, renewable energy and environmental monitoring technologies.

This article examined the relationship between airport terminal infrastructure and operational performance in Lagos and Port Harcourt using Objective One of Wilcox Belema's dissertation. The study adopted a correlational research design and analyzed 300 valid questionnaire responses. The first objective examined whether adequate terminal facilities improve airport operating efficiency and whether modern terminal infrastructure contributes to overall operational performance. The reported Pearson Product Moment Correlation coefficient was r = 0.153, with p = 0.008 and N = 300. Since p < 0.05, the first null hypothesis was rejected. The result therefore indicates a positive and statistically significant relationship between airport terminal infrastructure and operational performance. The finding is discussed through Modernization Theory and Infrastructure-Led Development Theory and related to the dissertation's literature on terminal modernization, passenger processing, service efficiency and airport infrastructure.

Between the years 2019 and 2026, the Indian stock market witnessed various structural transformations owing to factors such as economic shocks due to the outbreak of COVID-19, tariff wars, and other forms of political tensions. The current research aims to examine the performance of the Nifty 50 within the above-mentioned time period. Using secondary data, this paper adopts a simplistic approach in analyzing the Indian stock market, in addition to assessing the performance of major sectors within the economy and making relevant recommendations concerning future investments. In this regard, the use of basic metrics such as average returns, standard deviations, and annualization, among others, has enabled the researcher to focus on the trend in performance of the most profitable sectors, namely pharmaceuticals, banking, consumer goods, automobiles, and others. This paper asserts that one of the significant drivers of Indian stock market performance has been diversity in terms of performance of various sectors, as well as increasing involvement of retail traders in stock trading. Indeed, an increase in the participation of retail traders has been made possible by the rise of online investment platform. Overall, this paper discusses some of the factors affecting performance of the Indian stock market, particularly the most lucrative sectors.

The rule of law is the foundation of constitutional government, ensuring that state power is exercised under legal restraint rather than arbitrary will. This article examines how the rule of law is conceived, structured and enforced in the United Kingdom, whose constitution is uncodified and built on parliamentary sovereignty, and in India, whose written Constitution places the rule of law within its basic structure. The study asks whether the British reliance on parliamentary sovereignty adequately protects liberty in the absence of review of primary legislation, and whether India’s expansive substantive jurisprudence risks judicial overreach. Using a doctrinal and comparative methodology, it analyses constitutional and statutory texts, landmark decisions and secondary scholarship. The major findings are that the United Kingdom relies on interpretive and political checks, notably the Human Rights Act 1998, while Indian courts exercise plenary review and invalidate legislation, thereby giving the rule of law substantive content. The article argues that neither model is complete: British restraint depends on political willingness to respond to judicial signals, while Indian activism suffers from unpredictability and institutional delay. It concludes with reform proposals for both systems and lessons for India.

The 21st century is defined by modern technology, specifically the world of AI. Transformations are taking place across every sector, impacting both personal and social lives. Consequently, there have been shifts in individuals' lifestyles and ways of living, leading to changes in their values. The purpose of education should not be limited merely to the acquisition of knowledge and intellectual development; the educational system must also incorporate the shaping of children's moral character, social development, and personality. Ultimately, the goal is to mold exemplary citizens through education.

इक्कीसवीं सदी के इस वर्तमान तकनीकी युग में कृत्रिम बुद्धिमत्ता (Artificial Intelligence) से आगे बढ़कर सुपर इंटेलिजेंस (Super Intelligence - SI) का अभ्युदय हो चुका है, जो शिक्षा के क्षेत्र में एक अभूतपूर्व क्रांति लाने की क्षमता रखता है। प्रस्तुत शोध पत्र राष्ट्रीय शिक्षा नीति (NEP) 2020 के परिप्रेक्ष्य में माध्यमिक शिक्षा (विशेषकर कक्षा 9 और 10) के संवेदनशील स्तर पर सुपर इंटेलिजेंस (SI) के एकीकरण और उसकी संभावनाओं का एक गहन विश्लेषणात्मक अध्ययन प्रस्तुत करता है। माध्यमिक स्तर किसी भी विद्यार्थी के अकादमिक और भविष्य के करियर की सुदृढ़ नींव का चरण होता है, जहाँ पारंपरिक शिक्षण प्रणालियों की अपनी सीमाएं होती हैं। यह शोध यह रेखांकित करता है कि कैसे गणित और विज्ञान जैसे जटिल एवं तार्किक विषयों में पारंपरिक शिक्षण विधियों के स्थान पर SI-आधारित अनुकूली शिक्षण मंच (Adaptive Learning Platforms) और वर्चुअल लैब्स का उपयोग करके विद्यार्थियों की वैयक्तिकृत अधिगम गति (Personalized Learning Pace) और अधिगम प्रतिफल (Learning Outcomes) में गुणात्मक सुधार किया जा सकता है।
अध्ययन की यह रूपरेखा पूरी तरह से सैद्धांतिक, वैचारिक एवं द्वितीयक साहित्यिक स्रोतों पर आधारित है, शोध के मुख्य उद्देश्यों के अंतर्गत NEP 2020 के प्रावधानों का विश्लेषण, गणित व विज्ञान विषयों में SI के शैक्षणिक अनुप्रयोगों की प्रभावशीलता का सूक्ष्म परीक्षण, तथा अल्पवयस्क विद्यार्थियों की डिजिटल सुरक्षा एवं डेटा गोपनीयता से जुड़े विधिक पहलुओं का मूल्यांकन शामिल है। अध्ययन में इस बात पर विशेष बल दिया गया है कि तकनीकी एकीकरण के दौरान डिजिटल व्यक्तिगत डेटा संरक्षण (DPDP) अधिनियम के प्रावधानों का पूर्ण अनुपालन किया जाना चाहिए, ताकि छात्रों की गोपनीयता सुरक्षित रहे। साथ ही, यह सुनिश्चित किया जाना आवश्यक है कि तकनीक विद्यार्थियों की मौलिक सोच और अकादमिक ईमानदारी को कुंठित न करे, बल्कि उनकी वैयक्तिकृत बौद्धिक क्षमता को बढ़ाने वाले एक 'सहायक' (Enabler) के रूप में कार्य करे। इस शोध से निष्कर्ष निकालता है कि एक अनुशासित, सुरक्षित और नैतिक दायरे के भीतर SI का यह नियंत्रित क्रियान्वयन माध्यमिक शिक्षा को अधिक गतिशील, समावेशी और इक्कीसवीं सदी की चुनौतियों के अनुकूल बना सकता है।

This study examines management commitment as a boundary condition of the green innovation–organizational performance relationship in Shell's Nigerian operations in Delta State. While prior research has established that green innovation can contribute to organizational performance, the conditions under which this relationship strengthens or weakens remain underexplored. Drawing on the Natural Resource-Based View and stakeholder integration perspectives, the study argues that management commitment-expressed through resource allocation, strategic prioritization, and active support-shapes the extent to which green innovation investments translate into performance outcomes. A cross-sectional survey design was employed, with data collected from 180 employees of Shell's Nigerian operations in Delta State. Multiple regression analysis reveals that all four green innovation dimensions significantly predict organizational performance, with process innovation (β = 0.345, p < .01) and product/service innovation (β = 0.224, p < .01) demonstrating the largest standardized coefficients. Formal coefficient-comparison tests revealed that the only statistically significant pairwise difference was between green process innovation and green organizational innovation (χ² = 6.34, p = .012). The pattern of findings is interpreted in light of management commitment's enabling role. The study contributes to understanding the organizational conditions that determine whether environmental innovation creates value, with particular attention to the Nigerian oil and gas context where management support may be critical for translating green innovation investments into measurable returns. The findings provide empirical evidence that is broadly consistent with NRBV-based propositions regarding the strategic relevance of environmental capabilities, while highlighting the importance of statistically testing dimensional differences rather than relying on numerical coefficient comparisons alone.

Constitutional courts are often described as guardians of democracy, but their contribution to democratic government is more complicated than simply striking down unconstitutional laws. This research article compares the constitutional role of the Supreme Court of India, the Federal Constitutional Court of Germany and the Constitutional Court of South Africa. The study asks how each court protects constitutional democracy, how far judicial review may legitimately reach into political decision-making, and what the three systems can teach one another. The research adopts a doctrinal and comparative method, relying primarily on constitutional texts, leading judgments and official judicial materials, with supporting academic literature. The comparison shows three different institutional designs. India relies heavily on judicial review, fundamental rights and the basic structure doctrine. Germany places strong emphasis on human dignity, the free democratic basic order and an eternity clause. South Africa combines strong judicial review with an explicit commitment to participatory, accountable and open democracy. All three systems treat constitutionalism as more than majority rule, and courts protect democracy most effectively when judicial power is exercised through reasoned standards, institutional restraint and meaningful remedies. The article concludes that India can learn from Germany’s structured protection of constitutional identity and South Africa’s emphasis on participatory democracy, while preserving its own constitutional balance.

Motorcycle tourism is a unique form of experiential tourism that focuses on the trip and the motorcycle ride itself. This study proposes an integrated model using S–O–R and push–pull theory that includes risk perception to explore the relationships between travel motivation, psychological experience, destination attractiveness, infrastructure and safety, risk perception, and satisfaction with travel. Based on 240 cases, the results indicate that psychological experience has a positive effect on psychological experience (β = 0.526) and satisfaction (β = 0.220), and psychological experience also has a positive effect on satisfaction (β = 0.264) and partially mediates the relationship between travel motivation and satisfaction (indirect β ≈ 0.139). Destination attractiveness (β = 0.243) and infrastructure and safety (β = 0.173) positively influence satisfaction, whereas risk perception has a negative effect (β = −0.230). Positive relationships are found between social interaction and psychological experience (β = 0.183), and between travel planning and risk perception (β = 0.325). The model explains 55.7% of the variance in travel satisfaction (R² = 0.557). These findings indicate that adventure and experiential value and safety are in balance in motorcycle tourism.

This study presents a parametric investigation of the seismic behaviour of a 150 KL elevated RCC Intze water tank under varying water-storage conditions and staging configurations. The tank was structurally modelled and analysed using STAAD.Pro, with RCC plate elements adopted for the tank container and beam elements used to represent the staging system. The analysis considered gravity, wind and seismic loading in accordance with the relevant Indian Standard provisions. To account for liquid–structure interaction, the stored water was represented by separate impulsive and convective mass components. The investigation focused on the influence of water level and staging characteristics on important structural response parameters, including natural time period, lateral stiffness, and seismic base shear, overturning moment, hydrodynamic pressure, sloshing height, member forces and foundation response. The adopted tank geometry provides a calculated storage volume of 157.57 m³, compared with the required capacity of 150.00 m³, with a freeboard of 0.50 m. The results indicate that variation in water level significantly modifies the mass distribution and dynamic characteristics of the tank, while staging stiffness and configuration influence the lateral response and transfer of seismic forces to the foundation. The study further demonstrates the importance of considering impulsive and convective water effects rather than treating the stored water as a single rigid mass. The comparative evaluation of different operating conditions provides a comprehensive understanding of the interaction between tank mass, liquid motion and staging behaviour. The findings emphasize that seismic assessment of elevated Intze water tanks should consider both water-storage conditions and staging characteristics to achieve a reliable evaluation of structural safety, serviceability and overall seismic performance.

This paper examines whether the University of Oxford should lower admission standards for the children of generous benefactors. Drawing on human capital theory, allocative efficiency, signalling, peer effects, and distributive justice, it argues that the short-term funding benefits of donor-linked admissions are outweighed by long-term social and institutional costs. The analysis considers how preferential access can displace academically stronger applicants, weaken incentives for educational investment, reinforce intergenerational inequality, and erode reputational capital. Illustrative figures and discussion of legacy admissions, Jared Kushner’s Harvard admission, and the Varsity Blues scandal contextualise these risks. The paper also evaluates the claim that donations can support scholarships and research, arguing that alternative funding mechanisms can sustain universities without compromising academic standards. It concludes that preserving merit-based admissions and separating philanthropy from access better protect institutional trust and higher education’s contribution to society.

This study examined the effects of cultural clash between indigenous African values and Western management practices on employee commitment within multinational companies operating in Ghana. Using a quantitative cross-sectional design, data were collected from 380 employees across six MNCs in the financial services, telecommunications, and manufacturing sectors. Cultural clash was measured using a Cultural Value Conflict Scale, indigenous value orientation was assessed using an African Values in Organizations Scale, and employee commitment was measured using the Three-Component Model. Descriptive statistics, Pearson's correlation, hierarchical regression, and moderation analyses were conducted. Results revealed significant negative correlations between cultural clash and employee commitment (r = -0.54, p < .001). Indigenous value orientation moderated this relationship such that employees with stronger indigenous value orientations experienced greater negative effects of cultural clash on commitment. The findings underscore that when Western management practices conflict with indigenous values such as Ubuntu, communal obligations, and relational dignity, employee commitment is significantly undermined. Implications for culturally sensitive human resource management, hybrid practice design, and employee retention strategies in African MNCs are discussed.

This paper presents a results-focused comparative assessment of machine learning approaches for seismic response and damage prediction of reinforced concrete (RC) buildings. The analysis is based on published benchmark results documented in the thesis source and is explicitly separated from original student-generated numerical results. For maximum interstory drift ratio (IDRmax), the reported benchmark dataset compares Random Forest, Bagging, Extra Trees, HistGradientBoosting, ANN, XGBoost, KNN and conventional regression models using R², RMSE and MAE. Random Forest reports R²=0.901, while Bagging reports the lowest RMSE and MAE among the highlighted high-performing models. Additional published results show prediction accuracies of approximately 90.2–96.3% for selected six-story RC configurations and 93.4–95.3% for eight-story configurations. For real earthquake damage validation, Random Forest reported 74.62% testing accuracy compared with 62.68% for KNN. The paper interprets these results from an engineering perspective and identifies the implications of nonlinear feature interactions, independent validation and model selection. All numerical values are labelled as literature benchmarks; they are not claimed as original Ayush Raikwar experimental or numerical results.

Mahāsati stones form an important category within the wider memorial-stone traditions of South India. In Karnataka, related monuments are described in the literature through terms such as Mahāsati Kallu, Māsti Kallu, Sati Kallu and Vīramasti, while Tamil Nadu preserves related memorial forms within the wider Nadukal tradition. This article presents a comparative study of Mahāsati memorials in Karnataka and Tamil Nadu, examining terminology, historical context, sculptural representation, epigraphy, ritual memory and regional variation. Particular attention is given to the raised-hand motif, female attributes, representations of couples, multi-panel compositions, religious symbols and inscriptional evidence. The study combines archaeological and art-historical literature with epigraphic and iconographic approaches. It argues that Mahāsati memorials should be examined within the wider South Indian culture of memorialisation rather than through a single uniform typology. The comparison also highlights the need to distinguish securely identified sati memorials from hero stones, general memorial stones and other female-associated monuments. The paper proposes a field-documentation framework incorporating location, dimensions, sculpture, inscription, palaeography, local tradition and conservation status, thereby providing a basis for future GIS-based documentation of Mahāsati stones in Karnataka.

The relationship between governance and socio-economic development has become an important area of inquiry in the study of contemporary Indian states. Governance reforms, however, do not necessarily translate uniformly into improved development outcomes, as their effects are mediated by institutional capacity, policy implementation, public-service delivery and regional socio-economic conditions. Against this background, the present study examines the governance–development nexus in Haryana during 2015–2025, with particular attention to public policy interventions and their relationship with socio-economic outcomes under the BJP-led government. The study adopts a longitudinal mixed-method research design combining secondary statistical data, government reports, policy documents and empirical literature. Governance is examined through dimensions including administrative effectiveness, accountability, transparency, responsiveness, digital governance and policy implementation, while socio-economic development is assessed through economic growth, employment, education, health, gender development, rural development and infrastructure indicators. The study further incorporates district-level variations to examine whether development outcomes have been spatially uniform across Haryana. Descriptive and inferential statistical techniques are proposed to identify trends, associations and differences across the study period, supplemented by qualitative analysis of policy implementation and institutional processes. Rather than assuming a direct causal relationship between government policies and development outcomes, the study considers alternative influences, including national economic conditions, centrally sponsored programmes, the COVID-19 pandemic, demographic changes and pre-existing policy trajectories. The study seeks to contribute to the literature on sub-national governance in India by connecting institutional processes and public policy with measurable socio-economic outcomes over a decade. It also highlights the importance of implementation capacity, regional variation and evidence-based assessment in understanding the relationship between governance and development in Haryana.

Children and teenagers today spend a large part of their daily lives online — studying, playing games, chatting with friends, and scrolling through social media — often without fully understanding how much of their personal information is being collected, stored, and used in the process. This growing gap between how much time young users spend online and how little they understand about data privacy has made “digital privacy protection for young users” one of the most pressing legal and policy issues of our time. This paper examines the legal framework built around the protection of children’s personal data, with a particular focus on India’s Digital Personal Data Protection Act, 2023, along with its accompanying Rules of 2025, and situates this framework alongside comparable laws such as the Children’s Online Privacy Protection Act (COPPA) in the United States and the General Data Protection Regulation (GDPR) in the European Union. The paper studies the specific risks young users face online — targeted advertising, behavioural tracking, data breaches, and exposure to predatory actors — and evaluates how effectively current laws address these risks through mechanisms like verifiable parental consent, restrictions on tracking and profiling, and penalties for non-compliance. It also looks at relevant judicial pronouncements that have shaped the constitutional and legal understanding of privacy as a fundamental right in India, and how that understanding extends to children as a particularly vulnerable class of data principals. The paper concludes by identifying gaps that remain in the current legal architecture and offers practical suggestions — for lawmakers, platforms, schools, and parents — aimed at making the digital space genuinely safer for young users without cutting them off from the benefits of the internet.

The Governor is an institution that holds a unique place in the parliamentary federalism of India. While being formally the constitutional head of a State, the Governor is also part of the State Legislature under Article 168 of Indian Constitution and serves a significant constitutional purpose while a Bill is placed under Article 200 of the Constitution of India1. This article allows for the assent as well as the reservation for the President and depending on its first proviso, the withholding and returning of a non-Money Bill for reconsideration by the President of India. The second proviso makes the reservation compulsory in a specified case wherein a Bill if passed would undermine or diminish the authority of the High Court, thereby endangering the position bestowed under Indian Constituion.2
The contemporary issue got highlighted in the recent controversy as to the consequences that arise when such constitutional options are not exercised in the due or reasonable time. The Supreme Court under its 2023 judgment in State of Punjab v. Principal Secretary to the Governor of Punjab refused the use of gubernatorial discretion to undermine the regular legislative procedure.3 Furthermore, the controversy deepened when the decision rendered by the Court in the landmark case of State of Tamil Nadu v. The Governor of Tamil Nadu wherein April 2025 took a more interventionist stand, incorporating judicially defined time frames as well.4 This was however reviewed in the November 2025 Presidential Reference, whereby a Constitution Bench rejected the idea of judicial timelines and viewed assent as the prerogative of the Governor but reserved powers to him to act where inaction is unjustified and indefinite. 56
Canada and Australia offer good comparatives owing to the fact that they have systems that were originally built upon the renowned Westminster institutions which involved a vice-regal authority that is a part of the legislative process. While Canada maintains formal rules of assent, reservation and disallowance by the federation, conventions of responsible government have greatly limited
The Royal Assent powers remain in the States of Australia but powers of Britain to disallow and reserve State legislation under the Australia Act 1986 ended.89
The comparison is not intended to imply that India must import some other model. Rather, it reveals that the working of any constitutional power is determined by its context having a responsible government, federalism, conventions, institutional transparency and judicial review. This paper thus poses the question whether the primary function of the Governor is to act as a constitutional gatekeeper or a democratic safeguard without transforming the institution itself into some kind of substitute of an elected State legislature.

भारत की बहुभाषिक, बहुसांस्कृतिक और बहुधार्मिक संरचना “विविधता में एकता” की अवधारणा को विशेष महत्व प्रदान करती है। यह अवधारणा भारतीय समाज की पहचान होने के साथ-साथ लोकतांत्रिक मूल्यों और सामाजिक समरसता की आधारशिला भी है। प्रस्तुत लेख में “विविधता में एकता” की अवधारणा को राष्ट्रीय शिक्षा नीति 2020 के विशेष संदर्भ में विश्लेषित किया गया है। प्रस्तुत लेख में यह स्पष्ट किया गया है कि भारत में भाषाई, सांस्कृतिक, धार्मिक, सामाजिक, क्षेत्रीय और ज्ञान परंपराओं की विविधता होने के बावजूद एक साझा राष्ट्रीय चेतना विद्यमान है और इस एकता को सुदृढ़ करने में शिक्षा की महत्वपूर्ण भूमिका है। राष्ट्रीय शिक्षा नीति 2020 शिक्षा को समावेशी, बहुभाषिक, बहुसांस्कृतिक और बहुविषयक बनाकर विविधताओं के बीच सामंजस्य स्थापित करने का प्रयास करती है। लेख में राष्ट्रीय शिक्षा नीति 2020 के दृष्टिकोण को स्पष्ट करते हुए यह बताया गया है कि नीति का उद्देश्य केवल ज्ञान प्रदान करना नहीं; अपितु विद्यार्थियों में सामाजिक संवेदनशीलता, लोकतांत्रिक मूल्यों और राष्ट्रीय एकता की भावना विकसित करना है। इस संदर्भ में बहुभाषिक शिक्षा, भारतीय ज्ञान परंपरा का समावेश और समावेशी शिक्षा जैसे प्रावधानों को विविधता में एकता को मजबूत करने के महत्वपूर्ण माध्यम के रूप में प्रस्तुत किया गया है। बहुभाषिक शिक्षा विद्यार्थियों को अपनी भाषा और संस्कृति से जोड़ते हुए अन्य भाषाओं के प्रति सम्मान विकसित करती है; जबकि भारतीय ज्ञान परंपरा का समावेश विद्यार्थियों में सांस्कृतिक जागरूकता और राष्ट्रीय गौरव की भावना को सुदृढ़ करता है। समावेशी शिक्षा विभिन्न पृष्ठभूमियों के विद्यार्थियों को एक साथ सीखने का अवसर प्रदान कर सामाजिक समरसता को बढ़ावा देती है।

Department of Education is always gearing towards quality education in all levels of education. As part of its effort to evaluate whether it is really serving its purpose, there is always an effort of every ladder to keep gearing towards excellence in the discharging of functions and services.
In so doing, even in the first level of education which is the Kindergarten education, the teachers are proving their worth to be competent and competitive so that they can produce a desirable output ready for the first grade of basic education.
The researcher would like to know how competent really the teachers are in their duties and responsibilities and found it imperative to scrutinize the profile of the kindergarten teachers as respondents of the study. The following terms had contributed in order to establish the demographic profile of kindergarten teachers in terms of age, gender and the teacher’s classroom practices.
The study somehow gave an idea on the extent of teacher’s classroom practices and its relation towards the learning performance among kindergarten learners.
Furthermore, the study gave an idea on whether there is a significant difference in the extent of teacher’s classroom practices and the learning performance among kindergarten learners to determine the kindergarten teachers in terms of classroom management, classroom structuring, instructional materials, making daily lesson log, and teaching strategies.

The translation of public policy into tangible development outcomes depends not only on policy formulation but also on institutional capacity, administrative coordination, implementation mechanisms, and the accessibility of public services. This study examines the relationship between policy implementation, governance, and development outcomes in Rewari district of Haryana during the period 2021–2026. It adopts a district-level empirical framework to investigate how major government interventions in areas such as infrastructure, education, health, rural development, employment, social welfare, digital governance, and women's development are translated into local-level outcomes. The study employs a mixed-methods research design, combining secondary data from government reports, administrative records, statistical publications, and programme-specific sources with primary evidence collected from citizens and relevant stakeholders. Quantitative analysis is used to assess trends and relationships among selected governance and development indicators, while qualitative evidence is employed to examine implementation processes, institutional capacity, accessibility, and perceived gaps in service delivery. The study conceptualises governance as an intervening mechanism connecting policy inputs with development outcomes and therefore moves beyond a simple assessment of scheme coverage or expenditure. Particular attention is given to variations in service accessibility, citizen satisfaction, rural–urban differences, and implementation constraints. By focusing on Rewari as a district-level case, the study contributes to the literature on decentralised governance and policy implementation by linking government interventions with measurable socioeconomic and governance outcomes. The findings are intended to provide an evidence-based assessment of the policy–implementation–development relationship and identify institutional areas requiring greater attention for improving inclusive and effective district-level development.

Dandruff is a common scalp disorder characterized by excessive flaking, itching, dryness and irritation of the scalp. The present study focuses on the formulation and evaluation of herbal anti-dandruff shampoo containing Neem, Tulsi, Aloe Vera, Reetha, Shikakai, Fenugreek and Peppermint oils. These natural ingredients were chosen because of their traditionally reported cleansing, antimicrobial, antifungal, soothing, moisturizing and scalp-conditioning properties. Neem (Azadirachta indica) and basil (Ocimum sanctum) have antimicrobial and antifungal properties, while aloe vera helps soothe and moisturize the scalp. Reetha (Sapindus mukorossi) and shikakai (Acacia concinna) act as natural cleansing agents, while fenugreek (Trigonella foenum-graecum) can help condition the scalp and reduce dryness. Peppermint oil provides a refreshing feeling and may contribute to scalp cleansing and antimicrobial activity. Herbal extracts and peppermint oil will be incorporated into a suitable shampoo base and evaluated for various physicochemical and performance parameters including color, odor, appearance, pH, viscosity, foamability, foam stability, wetting ability, dirt dispersion, solid content, spreadability, cleansing ability, skin/scalp irritation and consistency. The antifungal or anti-dandruff activity of the formulation can also be tested using appropriate microbial testing method. The developed formulation is expected to provide effective cleansing and scalp care while offering a plant-based alternative to traditional anti-dandruff shampoos.

The increasing use of electronic documents across educational institutions, government agencies, corporate organizations and other sectors has intensified the need for mechanisms capable of guaranteeing document authenticity, integrity and accountability. Conventional electronic document management systems remain vulnerable to forgery, unauthorized modification, identity impersonation and weak access control. This study presents TrustSign, a secure Android-based digital document signing and verification system developed to address these challenges through the integration of multiple security mechanisms. The system combines One-Time Password (OTP) and biometric fingerprint authentication, Role-Based Access Control (RBAC), RSA digital signatures, SHA-256 hashing, Android Keystore-based key management, QR-code verification, Firebase cloud storage, audit trails and verification logs. The system was designed using Object-Oriented Analysis and Design Methodology and implemented using Java and Android Studio. Firebase Realtime Database was used for user information, document metadata, audit records and verification logs, while Firebase Storage was used for signed PDF documents. Functional testing was conducted using valid and invalid credentials, biometric data, PDF documents, QR codes and different user roles. Results showed that all major functional modules passed their tests. The system successfully authenticated users, enforced role-based permissions, digitally signed documents, generated unique TrustSign identification numbers and QR codes, verified authentic documents, detected modified documents, and maintained audit and verification records. The study demonstrates that integrating strong authentication, cryptographic signatures, access control, cloud services and verification mechanisms within a mobile platform provides a practical approach to secure digital document management.

The sustainable management of agricultural and shellfish wastes while addressing water pollution remains a critical challenge in the Niger Delta region of Nigeria. This study presents a comparative evaluation of four biochars produced from locally sourced plant and shell materials—palm tree stem biochar (PTSB), banana stem biochar (BSB), periwinkle shell char (PSC), and cassava stem biochar (CSB)—for the removal of Pb²⁺, Cd²⁺, and methylene blue (MB) from aqueous solutions. The precursor materials were collected within and around the Federal University Otuoke campus and the wider Otuoke community in Ogbia Local Government Area, Bayelsa State. Biochars were prepared by slow pyrolysis at 500 °C under limited oxygen conditions. Batch adsorption experiments conducted under optimised conditions (pH 5–7, adsorbent dosage 2 g L⁻¹, contact time 120 min) showed that BSB achieved the highest MB removal efficiency (approximately 94.7%, maximum adsorption capacity = 178.5 mg g⁻¹), while PSC exhibited superior performance for heavy metals (Pb²⁺ maximum adsorption capacity = 105.2 mg g⁻¹). Equilibrium data fitted the Langmuir isotherm model (R² > 0.96), and kinetic data followed the pseudo-second-order model (R² > 0.98), indicating chemisorption as the dominant mechanism. One-way ANOVA confirmed statistically significant differences among the biochars (p < 0.001). Application to real industrial effluent yielded removal efficiencies of 68–92%. The findings demonstrate that agricultural and shell wastes readily available in the Otuoke area can be converted into effective, low-cost adsorbents, supporting circular economy principles and sustainable wastewater management in the region.

The study investigated the effect of jigsaw and peer tutoring strategies on students’ retention in social studies in Sub-Saharan Africa. The study employed a quasi-experimental non-randomized pre-test, post-test control group design. Three research questions and hypothesis were formulated. The sample consisted of 308 Junior Secondary School students in two intact classes in two secondary schools in West Africa, Nigeria. The instrument used for data collection were Social Studies Academic Performance Test (SOSAPT) Social Studies Retention Test (SSRT). The instrument were face validated by three experts. Kuder-Richardson (K-R20) formula was used to test the internal consistency reliability of SSAPT and the result was 0.98 and Cronbach Alpha was used to ascertain the reliability coefficient of SSRT which yielded a reliability coefficient of 0.89. The data were analysed using descriptive statistics and Analysis of Covariance (ANCOVA). The results showed that there was a significant difference between the mean retention scores of students taught using Jigsaw teaching strategy and those taught using peer tutoring strategies in Social Studies F (1, 201) = 12.300; p = 0.001 < 0.05; there was a significant main was a significant difference between male and female students’ retention scores when taught Social Studies using Jigsaw teaching strategy. F (1, 100) = 0.024; p = 0.158 > 0.05. The study recommended that social Studies teachers should use jigsaw and peer tutoring to enhance students’ retention in the subject and principals and Supervisors of Social Studies teaching and learning encourage the use of Jigsaw and peer tutoring strategies to enhance male and female students’ retention in the subject within the Sub-Saharan Africa.

Examination malpractice, particularly impersonation, remains a persistent challenge in Nigerian tertiary institutions and has far-reaching consequences for educational standards and societal integrity. This paper presents the design and implementation of a Smart Exam Impersonator Detector Application that leverages facial recognition technology to identify and flag candidates who are not registered for a given examination. The system was developed using Python, OpenCV, and the Flask web framework, with an Eigenfaces algorithm based on Principal Component Analysis (PCA) as the core recognition engine. Student facial images were collected from the Department of Mechatronics Engineering, Alex Ekwueme Federal University (AE-FUNAI), and used to train the model. The system was tested on eleven distinct faces, successfully recognising ten out of eleven, yielding a detection accuracy of approximately 90%. Results further demonstrate that recognition accuracy improves proportionally with the number of training images supplied per individual. The proposed system is cost-effective, scalable, and contactless, making it particularly suitable for deployment in a post-pandemic university environment where social distancing remains important. This work contributes a prototype that any Nigerian university can adopt to curb examination impersonation without the prohibitive cost of commissioning custom software.

Background: Persons with disabilities (PwDs) experience health inequities arising from barriers in healthcare systems, social determinants, affordability, accessibility, and discrimination. In India, the policy framework includes the Rights of Persons with Disabilities Act, 2016 (RPwD Act), Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY), and regulatory measures concerning health insurance products. Nevertheless, evidence indicates substantial gaps in financial protection and awareness.
Objective: To synthesize the evidence presented in the 2025 “Ayushman for All” campaign survey concerning health insurance coverage and AB-PMJAY awareness among PwDs in India, and to interpret those findings alongside national disability-survey evidence, Indian insurance regulation, and international disability-health standards.
Methods: A structured narrative review was undertaken using the uploaded manuscript as the primary source, supplemented by publicly available Government of India, WHO, United Nations, peer-reviewed, and reputable news/press reports identified during September 2026. The 2025 campaign figures were treated as campaign-reported estimates rather than as a nationally representative prevalence estimate because the technical survey report and sampling documentation were not available in the source material reviewed.
Results: The campaign survey, as reported by Press Trust of India, included more than 5,000 PwDs across 34 states and union territories; 82% reportedly lacked any form of insurance, 42% were unaware of AB-PMJAY, and 28% reported having applied for the scheme. These findings coexist with substantial evidence of financial burden: analysis of the NSS 76th Round disability survey found that disability-related healthcare expenditure represented 20.32% of household monthly consumption expenditure on average, 57.1% of households experienced catastrophic health expenditure at a 10% threshold, and 19.1% of households above the poverty line before treatment were pushed below it after disability-related healthcare expenditure. Indian regulation has also evolved: IRDAI requires insurers to make products available across categories including PwDs and requires general and health insurers to offer a specific cover for PwDs, HIV/AIDS and mental illness.
Conclusion: The evidence points to a policy implementation gap rather than a simple absence of policy. A disability-inclusive health-financing strategy requires accessible enrolment, effective outreach, transparent underwriting, disability-disaggregated monitoring, grievance redressal, and meaningful participation of persons with disabilities and their representative organisations. Future research should independently validate the 2025 campaign estimates using transparent sampling and individual-level data.

This study assessed the corrosion inhibition performance of Azadirachta indica (Neem) and Moringa oleifera (Moringa) leaf extracts as environmentally friendly corrosion inhibitors for mild steel in alkaline media. Fresh leaves of Neem and Moringa were processed by crushing and pounding without the addition of an extracting solvent, and the resulting extracts were filtered and used at volumes of 25, 50, 75, and 100 cm³. Mild steel cylindrical coupons were exposed to 0.5 M and 1.0 M sodium hydroxide (NaOH) solutions containing the respective plant extracts. The corrosion behaviour was evaluated using weight-loss measurements, corrosion rate, and inhibition efficiency. The results showed that increasing the extract volume progressively reduced the weight loss and corrosion rate of the mild steel while increasing inhibition efficiency in both NaOH concentrations. In 0.5 M NaOH, Neem extract increased the inhibition efficiency from 22.28% at 25 cm³ to 59.78% at 100 cm³, whereas Moringa extract increased the efficiency from 25.54% to 64.13%. In 1.0 M NaOH, Neem exhibited inhibition efficiencies of 20.35–58.01%, while Moringa showed 23.81–60.61% over the same extract-volume range. The uninhibited mild steel exhibited higher corrosion rates in 1.0 M NaOH than in 0.5 M NaOH, indicating increased corrosivity with increasing NaOH concentration. At corresponding extract volumes, Moringa consistently exhibited slightly higher inhibition efficiency and lower weight loss than Neem. The observed protective effect is attributed to the adsorption of bioactive phytochemical constituents present in the plant extracts onto the mild-steel surface, forming a protective film that limits interaction between the metal and the corrosive alkaline medium. The findings demonstrate the potential of Neem and Moringa leaf extracts as locally available, renewable, and environmentally compatible alternatives for mitigating mild-steel corrosion in alkaline environments.

Wildlife conservation organizations play a significant role in protecting biodiversity and promoting environmental sustainability. Among the leading organizations working in this field are the World Wide Fund for Nature – India (WFN), African Wildlife Foundation (AWF), and Panthera Corporation (PAN). These organizations contribute significantly to wildlife protection, habitat conservation, and environmental awareness across different regions of the world. The financial strength of such organizations is essential to ensure the continuity of their conservation programs and initiatives. The present study examines the financial performance of selected environmental and wildlife conservation organizations by analysing their liquidity, profitability, solvency, and operational efficiency. The study evaluates key financial indicators such as Current Ratio, Return on Total Assets (ROA), Return on Capital Employed (ROCE), Operating Profit Ratio (OPR), Debt Equity Ratio (DER), Return on Net Assets (RONA), and Working Capital Turnover Ratio (WCT). Secondary data were collected from the profit and loss accounts and balance sheets of WFN, AWF, and PAN for the period 2020–2024. The study employs ratio analysis, trend analysis, and comparative statistical tools such as ANOVA, F-test, and correlation analysis to examine the financial performance and relationships between the selected ratios. The findings highlight variations in financial efficiency among the organizations and provide insights into their financial stability and operational performance in the wildlife conservation sector.

Nanotechnology is an interdisciplinary area of that studies and applies materials at extremely small dimensions, generally between 1 and 100 nanometres. Materials at this scale can behave differently from the same substances in larger forms because of their large surface area and nanoscale physical effects. These properties have created opportunities in healthcare, electronics, energy, environmental protection, agriculture, and electronics, energy, environmental protection, agriculture, and manufacturing. This paper examines the basic principles of nanotechnology, its major applications, advantages, limitations, and possible future development. It argues that nanotechnology could help address important medical, industrial, and environmental problems, but its progress must be accompanied by careful safety testing, environmental monitoring, ethical decision-making, and responsible regulation.
science

Constitutional amendment is the space at the edge of democratic self-government and constitutional restraint. India and Pakistan have a common history in legal and constitutional traditions and both have specially entrenched amendment procedures and yet the courts in both nations have adopted sharply contrasting views on the substantive scope for the limitations of constituent power. Indian basic structure doctrine provides a power that is very wide on the part of Parliament but which cannot be used to delete the very identity of the Constitution. The Pakistani jurisprudence has identified its important features on the constitution like Federalism, Parliamentary Government and Independence of Judiciary and is of divided views on the extent to which these can be invoked to strike down constitutional amendments. The contrast has been accentuated by the 26th Amendment to the Constitution of Pakistan 2024 and 27th Amendment 2025 under which the constitutional adjudication was overhauled, a Federal Constitutional Court was introduced and the wording of Article 239(5) was enhanced to the exclusion of judicial challenges to constitutional amendments. Through doctrinal and comparative analysis of the constitutional texts and seminal cases as well as institutional materials from the current era, the Article argues that the main distinction is not an "activist/parliament" dichotomy. It is in the interplay between the constitutional wording, past institutional history, standards of review and the apparent difference between amendment and replacement of the constitution. The Article advocates the adoption of a structured identity based test, which involves the existence of a more textual foundation, demonstrable structural relevance, and substantial impairment and also a reasoned remedial threshold before an amendment can be constitutionally destructive.

Dilute aqueous solutions of α-amino acids are among the simplest laboratory models for the charged, polar and nonpolar groups of proteins. Measurements of ultrasonic velocity, density and viscosity, used together, offer a sensitive, non-destructive picture of solute–solvent and solute–solute interactions in such systems. This review describes the zwitterionic chemistry of amino acids in water, the principles and practice of the three techniques, and the equations that yield adiabatic compressibility, intermolecular free length, acoustic impedance, hydration number, partial molar volume and compressibility, and Jones–Dole viscosity coefficients. A stepwise worked example based on an illustrative glycine data set at 298.15 K demonstrates the calculations and the meaning of each parameter. Representative literature on standard partial molar volumes, temperature effects, electrolyte effects and structure-making or structure-breaking behavior is then examined. A consistent picture emerges: charged end groups electro strict water and give a negative partial molar compressibility, while nonpolar side chains add positive volume increments and raise the viscosity B coefficient. Remaining problems and future directions are noted.

Freedom of speech is an essential condition of democratic constitutionalism. It enables citizens to participate in public affairs, criticise government, exchange ideas and hold public institutions accountable. India and the United States recognise freedom of expression as a fundamental constitutional right, but they protect and limit that right through substantially different constitutional structures. In the United States, the First Amendment adopts broad and apparently absolute language: “Congress shall make no law… abridging the freedom of speech.” American constitutional jurisprudence has consequently developed a strong presumption against governmental interference, particularly in relation to political speech. In India, Article 19(1)(a) guarantees freedom of speech and expression, but Article 19(2) expressly permits the State to impose reasonable restrictions on specified grounds.
This article undertakes a doctrinal and comparative study of freedom of speech in India and the United States. It examines constitutional provisions, legislative frameworks and leading judicial decisions, including Brandenburg v. Ohio , New York Times Co. v. Sullivan , United States v. Stevens , Romesh Thappar v. State of Madras, S. Rangarajan v. P. Jagjivan Ram , Shreya Singhal v. Union of India and Anuradha Bhasin v. Union of India. The article argues that the American model offers stronger protection against prior restraint and government censorship, while the Indian model provides a more explicit framework for balancing speech with public order, national security and social interests. However, broad statutory language, criminal sanctions and inconsistent enforcement in India create a significant chilling effect. The article recommends stricter proportionality review, clearer legislative standards, stronger protection for political dissent and greater procedural safeguards against arbitrary restrictions.

This study provides a critical assessment of the place of leadership in the development trajectories of Japan, China, South Korea, and India, with particular emphasis on lessons applicable to Nigeria and other developing nations. Employing secondary data analysis and Development Theory as the theoretical framework, this research examines how political leadership, institutional quality, and state capacity have shaped economic outcomes in these Asian economies. The study reveals that Nigeria and other developing countries, despite possessing substantial human and material resources, have failed to replicate the institutional reforms, agricultural modernization, land reforms, and information and communication technology (ICT) integration that characterized the Asian Tigers' development models. This research recommends that Nigerian political leadership must adopt pragmatic, evidence-based approaches to development by: (1) implementing comprehensive land and agricultural reforms; (2) integrating ICT infrastructure into economic planning; (3) prioritizing basic and compulsory education; (4) creating enabling environments for diaspora investment; (5) leveraging positive aspects of globalization; (6) fostering competitive capitalism; and (7) capitalizing on opportunities presented by BRICS cooperation frameworks. The findings underscore that effective leadership, coupled with institutional reform and strategic policy implementation, remains fundamental to achieving sustainable socio-economic growth and development.

Few constitutional questions in India provoke as much debate as the Uniform Civil Code (UCC). At its heart lies a simple but contentious idea: should all citizens, regardless of religion, be governed by one common set of civil laws on marriage, divorce, inheritance, and adoption? Nearly 75 years after the Constitution came into force, this question remains unresolved at the national level, caught between constitutional aspiration, religious freedom, and political sensitivity.
Constitutional Basis: Article 44
The UCC's textual home is Article 44, located in Part IV of the Constitution — the Directive Principles of State Policy (DPSP). It reads:
"The State shall endeavour to secure for the citizens a uniform civil code throughout the territory of India."
Crucially, Directive Principles are not justiciable — Article 37 explicitly states they "shall not be enforceable by any court," but are nevertheless "fundamental in the governance of the country." This places UCC in a unique constitutional position: it is a directive the State ought to pursue, but citizens cannot approach a court to compel its enactment.
Why the Constituent Assembly Chose This Path
During the framing of the Constitution, members debated whether UCC should be a Fundamental Right or a Directive Principle. Dr. B.R. Ambedkar, while personally supportive of eventual legal uniformity, acknowledged the deep sensitivities around religious personal laws in a newly independent and religiously diverse nation. The Assembly ultimately placed UCC among the Directive Principles — a goal to be achieved through gradual consensus-building, not immediate legislative imposition.

In an era where every click, transaction, and location ping generates a digital trace, the question of privacy has moved from philosophical debate to constitutional necessity. India, home to over 850 million internet users and the world's largest biometric identity program, sits at the center of this tension. The Indian Constitution, drafted in 1950, makes no explicit mention of a "right to privacy." Yet through decades of judicial interpretation, privacy has emerged as one of the most significant fundamental rights of the digital era.
The Constitutional Silence and Its Resolution
Unlike some modern constitutions, India's founding document does not contain an express privacy clause. For years, this silence was interpreted narrowly. In M.P. Sharma v. Satish Chandra (1954) and Kharak Singh v. State of Uttar Pradesh (1962), the Supreme Court declined to recognize privacy as a distinct fundamental right, reasoning that the Constitution's framers had deliberately omitted it.
This position began shifting through a series of progressive judgments that read privacy into Article 21's guarantee of "life and personal liberty," interpreting the word "life" expansively to include dignity, autonomy, and personal space.
The Puttaswamy Watershed
The turning point arrived with Justice K.S. Puttaswamy (Retd.) v. Union of India (2017), a nine-judge Constitution Bench decision. The case originated from petitions challenging the Aadhaar scheme's constitutional validity, but its scope expanded into a foundational inquiry: does India's Constitution guarantee a right to privacy at all?

This article comparatively examines the judicial review of executive lawmaking in India and the United Kingdom, focusing on India’s ordinance-making power under Articles 123 and 213 of the Constitution and the UK’s reliance on delegated and emergency legislative mechanisms, including Orders in Council and Henry VIII clauses. The research study investigates whether judicial review functions as a complete constitutional protection because it controls executive power when officials create laws without waiting for legislative approval. The article uses doctrinal-comparative research methods to study constitutional provisions and statutes and judicial decisions together with applicable academic commentary from both legal systems. The research studies how the Indian Supreme Court develops its legal framework through R.C. Cooper v Union of India, A.K. Roy v Union of India, D.C. Wadhwa v State of Bihar and, most significantly, Krishna Kumar Singh v State of Bihar, which courts with United Kingdom ultra vires doctrine and prerogative power and executive responsibility precedents such as Padfield and the GCHQ case and Miller. The article argues that Indian courts possess a more searching basis for substantive review because constitutional supremacy supplies an enforceable legal standard, while UK judicial review remains constrained by parliamentary sovereignty. The two systems show accountability problems in their operations. The comparison identifies shared points between both systems while demonstrating how different constitutional structures affect the strength and success of judicial oversight.

Artificial Intelligence (AI) has transformed the digital world by enabling innovative applications in communication, education, entertainment, and business. However, the emergence of deepfake technology has raised serious concerns regarding privacy, misinformation, identity theft, and cybercrime. Deepfakes use AI-based algorithms to create highly realistic but fabricated images, videos, or audio recordings that can deceive viewers into believing false information. While this technology has legitimate applications in filmmaking and digital content creation, its misuse poses significant legal and ethical challenges. In India, the rapid growth of internet usage and social media platforms has amplified the risks associated with deepfakes. This article examines the concept of deepfake technology, its impact on society, the existing legal framework in India, the challenges faced by law enforcement agencies, and the need for comprehensive regulatory reforms.

Reliable electricity remains scarce in rural northwestern Nigeria, yet Kebbi South—the seven local government areas of Zuru, Fakai, Sakaba, Danko/Wasagu, Yauri, Ngaski and Shanga—has received little consolidated resource assessment. This review synthesises 2019–2026 literature, institutional reports and project records on solar, wind, hydro and biomass resources relevant to the zone, and applies standard resource and techno-economic equations to cross-check reported figures. Kebbi’s mean annual global horizontal irradiation is about 2,102 kWh/m²/yr (≈5.8 kWh/m²/day), 1.4% below the northwest mean, so solar photovoltaics is the most mature option. Reported wind power density is only 64.88 W/m² (Weibull shape factor 1.40–1.84), suitable for light loads, pumping and hybrid support rather than utility-scale. Small hydropower is plausible along the Niger-river margin, with Ngaski flagged in GIS screening, but no state-level small-hydro inventory exists. Crop residues (sorghum, millet, rice, groundnut) and livestock waste are abundant but face competing uses. A HOMER-based hybrid study in Kebbi reports a levelised cost of ₦149.98/kWh for a PV–wind–hydro system; the reported figures are internally consistent with a capital recovery factor of 0.0675. Principal gaps are LGA-level measurements, hydrology and biomass inventories; a staged roadmap is proposed.

Background: Menorrhagia, now grouped under heavy menstrual bleeding (HMB), is a frequent gynaecological complaint that can cause iron-deficiency anaemia and lower quality of life. Conventional care relies on antifibrinolytic, hormonal and surgical options, and some patients also seek homoeopathic treatment.
Objective: To describe the clinical course of an adolescent with HMB treated with an individualized homoeopathic medicine, and to review the definition, causes, assessment and management of the condition.
Methods: An 18-year-old unmarried female presented with two years of profuse menstrual bleeding lasting 10 to 12 days, with pallor and a recent aching pain in the right knee. A detailed case history, general and particular symptoms, and clinical examination were recorded. After comparison with the Materia Medica, Lachesis 30 was prescribed as a single bedtime dose. Results: At the first follow-up, one week after the prescription, the patient reported a slight reduction in menstrual bleeding. Complaints are better in next follow ups
Conclusion: This case shows how individualized prescribing may be documented in HMB and underlines the need for proper aetiological evaluation, anaemia screening and extended follow-up in future case series and controlled studies.

The study aimed to examine the effect of rainfall variability on household food production among small farmers in Iringa Rural District, Tanzania. The study focused on the effects of rainfall variability on crop yield, crop diversity and production stability. A mixed research approach was employed using a cross-sectional research design. Primary data were collected using questionnaires and interview guides. Quantitative data were analysed using descriptive statistics with the Statistical Product for the Social Solutions (SPSS) Version 26, while qualitative data were analysed using thematic analysis. The findings showed that rainfall variability affected household food production through changes in crop yield, crop diversity and production stability. Variations in rainfall patterns influenced the quantity of crops produced, the range of crops cultivated by households and the stability of food production across seasons. The study concludes that rainfall variability has an important effect on household food production among small farmers in Iringa Rural District by influencing crop yield, crop diversity and production stability. The study recommends that small farmers should be supported to adopt climate-smart agricultural practices, drought-tolerant crop varieties and soil and water conservation measures to reduce the effects of rainfall variability on household food production.

The Catuparisā, or fourfold Buddhist community, occupies an important place in the religious, social, and institutional development of early Buddhism. It comprises bhikkhus (monks), bhikkhunīs (nuns), upāsakas (male lay followers), and upāsikās (female lay followers). The concept represents a broad Buddhist community in which monastic and lay followers contribute to the preservation, practice, and transmission of the Buddha’s teachings. This paper examines the representation and significance of the fourfold Buddhist community in the Majjhima Nikāya and the Dīgha Nikāya, two major collections of discourses preserved in the Pāli Canon. Through a textual and analytical approach, the study investigates how these Nikāyas portray the participation of different sections of the Buddhist community in religious practice, ethical discipline, teaching, and the continuation of the Dhamma. Particular attention is given to the relationship between monastic and lay followers, the responsibilities associated with different community roles, and the contribution of women and men to Buddhist religious life. The study also considers how the fourfold community provides a framework for understanding the social and institutional dimensions of early Buddhism. Rather than viewing Buddhism exclusively as a monastic tradition, the analysis highlights the complementary roles of ordained and lay followers in sustaining Buddhist teachings and practices. By examining relevant discourses from the Majjhima and Dīgha Nikāyas, this paper seeks to clarify the textual foundations of the Catuparisā and its significance for understanding the development of the early Buddhist community.

Accounting Information Systems (AIS) integrate people, procedures, data, software and controls to capture, process and report financial information. This critical narrative review examines how AIS can contribute to business performance and why benefits differ across organisations. The synthesis draws on information-systems success theory and empirical research on small and medium-sized enterprises, accounting information quality and cloud-based AIS. The literature indicates that AIS can support performance through several pathways: improving information quality, accelerating reporting and decision processes, strengthening transaction controls, integrating financial and operational data, and supporting more timely management action. However, technology adoption alone does not guarantee better performance. System quality, information quality, user capability, management support, organisational readiness, training, internal controls and fit with business processes shape whether systems are used effectively. Cloud platforms may reduce some infrastructure barriers for smaller firms, but they also create requirements for connectivity, security, data governance and vendor management. The review proposes that AIS performance should be evaluated as a chain from system and information quality to effective use, decision quality, control and business outcomes. Future research in developing economies should use verified primary data, objective performance measures where possible and transparent research methods rather than relying only on respondent perceptions.

Background: Acne vulgaris is a chronic inflammatory disorder affecting the hair follicle and its sebaceous gland. It appears as comedones, papules and pustules and, in severe cases, as nodules, cysts and scars, and it may reduce a patient's quality of life. The homoeopathic literature on acne consists of randomized placebo-controlled trials, observational studies, case series and case reports, which vary considerably in design, sample size, outcome measures and quality.
Objective: To review the published clinical literature on homoeopathic treatment of acne vulgaris in narrative form, to summarize reported outcomes and prescribing approaches, and to point out methodological weaknesses and evidence gaps.
Methods: Records were retrieved via Google Scholar, the only database searched, and examined qualitatively for design, population, intervention, comparator, outcomes, attrition and methodological weaknesses. This is not a formal systematic review: no protocol was registered and no independent duplicate screening took place. Seventeen clinical records were extracted.
Results: Of the records, three were randomized placebo-controlled trials, two were other controlled or placebo run-in studies, four were prospective or observational studies, three were case series and five were case reports. The largest randomized trial (126 participants) tended to favour individualized homoeopathic medicines, though at three months the groups did not differ significantly. A fixed homoeopathic complex performed no better than placebo in its trial.
Significant within-group declines in lesion counts, Global Acne Grading System (GAGS) scores and quality-of-life scores were reported by open-label studies of Zingiber officinale, Arctium lappa and Azadirachta indica and by an individualized single-arm study. Remission was recorded in 81.9% of an 83-patient case series.
Conclusion: Homoeopathy has been investigated as an acne vulgaris treatment, and improvement is described by most uncontrolled studies. The strongest comparative evidence, though, has shown no statistically significant advantage over placebo. Further study is warranted; before firm conclusions on efficacy are possible, adequately powered randomized controlled trials with standard outcome measures and longer follow-up are needed.

Phytopharmacology continues to play a crucial role in the discovery and development of novel therapeutic agents, particularly from medicinal plants with traditional uses. The increasing prevalence of antibiotic resistance, along with the widespread occurrence of pain and diarrhoeal disorders, has created an urgent need for safer and more effective plant-based alternatives. This study evaluated the analgesic, antidiarrhoeal, and antimicrobial activities of ethanol leaf extracts of Limnophila polystachya Benth using established experimental models. Analgesic activity was assessed by the acetic acid-induced writhing test in mice, while antidiarrhoeal activity was evaluated using the castor oil-induced diarrhoea model following Thomas' method. Antimicrobial activity was determined by the disc diffusion assay against selected bacterial strains. At a dose of 500 mg/kg, the stem and leaf extracts produced significant analgesic effects by reducing writhing responses by 65.79% and 63.16%, respectively, compared with 78.07% inhibition produced by the standard drug diclofenac sodium. In the antidiarrhoeal study, the stem and leaf extracts significantly reduced diarrhoeal faeces by 50.58% and 52.87%, respectively, while lower doses also demonstrated notable inhibition. The extracts exhibited moderate antibacterial activity at concentrations of 250 and 500 μg/disc, although their efficacy was lower than ciprofloxacin (38 mm inhibition zone at 50 μg/disc). These findings indicate that L. polystachya possesses promising pharmacological properties and may serve as a valuable natural source for the isolation of bioactive compounds. However, further phytochemical investigations, toxicity studies, and mechanistic evaluations are required to identify the active constituents and confirm their therapeutic potential.

Women’s rights are an essential part of human rights and constitutional democracy. They are closely connected with equality, dignity, personal liberty, safety, education, employment and economic independence. In India, the Constitution provides a strong foundation through Articles 14, 15, 16 and 21, while also allowing special measures for women where necessary. Parliament and the judiciary have developed a wider legal framework addressing domestic violence, dowry, workplace sexual harassment, child marriage and unequal access to property and opportunities.
This paper examines the development and importance of women’s rights in India. It explains the constitutional framework, major protective laws, important judicial decisions and rights relating to education, employment, property, maternity and personal dignity. It also considers practical challenges such as lack of legal awareness, social stereotypes, economic dependence, under-reporting and difficulties in accessing justice.
The paper concludes that India has a substantial legal framework, but its effectiveness depends on implementation, awareness and social change. Women’s empowerment therefore requires more than laws; it requires equal opportunities, accessible remedies, safe institutions and respect for women’s autonomy and dignity.

Environmental pollution remains one of the most pressing global challenges leading to irreparable ecosystem degradation. Traditional pollution monitoring and control methods, are often constrained by high operational costs, limited spatial and temporal coverage, and delayed response times. Artificial Intelligence (AI) has emerged as a transformative tool capable of addressing many of these limitations through predictive modelling, real-time monitoring, automated detection, and intelligent control systems. This paper presents a structured review of AI applications across major pollution domains, namely air, water, industrial, and waste management, and examines the underlying techniques that enable these applications. It focusses on technology advancements such as machine learning, deep learning, computer vision, and the Internet of Things (IoT) and role of each in pollution control. The paper also critically evaluates the key challenges hindering widespread adoption, such as data scarcity, model interpretability, infrastructure costs, federated learning, and regulatory integration. Finally, it outlines emerging directions including explainable AI, and digital twin frameworks that could shape the next generation of AI-driven environmental management systems. The paper concludes that while AI offers substantial opportunities to enhance pollution control efficiency and responsiveness, its successful deployment depends on addressing technical, economic, and policy-level barriers in parallel for ensuring the sustainability of our planet.

Allergic rhinitis (AR) is an immunoglobulin E (IgE)-mediated inflammatory disorder of the nasal mucosa that follows exposure to inhaled allergens and is characterised by sneezing, nasal itching, rhinorrhoea and nasal obstruction. It affects several hundred million people worldwide, impairs sleep, school and work performance, and frequently coexists with asthma and allergic conjunctivitis. This narrative review summarises current knowledge on the epidemiology, risk factors, pathophysiology, clinical features, classification, diagnosis and management of AR, and examines the place of homoeopathy in its management. Relevant guidelines, reviews and clinical studies were identified through searches of Google Scholar, and remedy indications were drawn from Boericke’s Materia Medica and read in the light of Hahnemann’s Organon of Medicine; the material was synthesised narratively. The literature shows that AR is a systemic airway condition rather than an isolated nasal complaint, that diagnosis rests mainly on a careful history supported by allergen-specific testing, and that management combines allergen avoidance, pharmacotherapy (intranasal corticosteroids, antihistamines and combination products), allergen immunotherapy and patient education. Classical homoeopathic texts list remedies for acute coryza and hay fever, but Hahnemann’s method requires a remedy to be chosen on the totality of the individual patient’s symptoms rather than on the disease name. The few clinical trials of homoeopathy in AR are small and varied, and several tested allergen preparations rather than individualised prescribing, so the evidence is not yet sufficient to support its use. Recent guidelines emphasise a structured, evidence-graded and patient-centred approach. Further work is needed on phenotype-specific treatment, long-term disease modification and strategies for primary prevention.

This paper examines the household financial stress paradox in India: household leverage has increased while net financial saving has remained materially below its pandemic peak, even though the banking system remains resilient. Using Reserve Bank of India (RBI), National Statistical Office, and related macro-financial evidence, the paper traces changes in household liabilities, financial saving, credit composition, and regulatory intervention. The analysis distinguishes balance-sheet vulnerability from conventional measures of banking-sector asset quality and argues that the relevant policy problem is not household borrowing per se but the interaction between debt composition, income capacity, liquidity buffers, and macroeconomic shocks. The paper documents the shift toward non-housing retail credit and evaluates the RBI's use of higher risk weights as a targeted macroprudential response. It concludes with a household and regulatory resilience framework based on debt-service capacity, liquidity adequacy, credit underwriting, and stress testing.

Constitutional crises test whether constitutional government can continue to restrain public power when ordinary political arrangements are placed under exceptional pressure. Such crises may arise from executive–legislative conflict, governmental instability, mass mobilisation, territorial conflict, war, terrorism or emergency measures. The central question is not simply whether a constitution survives in formal terms, but whether constitutional democracy continues to structure the exercise of public power. This paper examines constitutional resilience through a comparison of India, France and Germany, three systems that experienced serious constitutional stress but responded through different institutional paths.
The study treats constitutional resilience as the capacity of a constitutional order to resist the destruction of its core commitments, adapt lawfully to changing conditions, and recover after institutional failure. India’s Emergency of 1975–1977 demonstrates the danger of concentrated emergency authority and weakened rights protection, but also the capacity for recovery through elections, constitutional amendment, judicial doctrine and federal institutions. France’s transition from the Fourth to the Fifth Republic shows that resilience may require institutional redesign where governmental instability prevents effective constitutional government. Germany’s experience from Weimar to the Basic Law demonstrates deliberate constitutional learning: emergency powers were retained but embedded within stronger parliamentary, federal and judicial safeguards.
The comparison indicates that resilience is systemic rather than dependent on a single constitutional provision. Bounded emergency powers, meaningful legislative oversight, independent courts, political competition, territorial dispersion of power, protected constitutional identity, governmental capacity and post-crisis learning operate together. The paper concludes that India need not copy French or German institutions. Its more relevant task is to preserve and strengthen the mechanisms already developed through the experience of the Emergency, particularly the Forty-Fourth Amendment, judicial review, federalism, political competition and the basic structure doctrine.

Intravenous (IV) to oral (PO) switch therapy is a well-established antimicrobial stewardship strategy that involves changing a patient's medication from the intravenous route to an oral formulation once the patient's clinical condition improves. This practice enhances patient comfort, reduces healthcare costs, shortens hospital stay, and minimizes complications associated with prolonged IV catheter use without compromising treatment effectiveness. Successful implementation requires careful assessment of the patient's clinical status, gastrointestinal function, and availability of effective oral alternatives. This review summarizes the principles, objectives, indicators, benefits, challenges, and expected outcomes of IV to oral switch therapy.

ABSTRACT
Background: Candida species are important fungal organisms associated with superficial, mucosal and invasive candidiasis. Laboratory investigations have examined whether selected homoeopathic preparations show measurable antifungal activity against Candida.
Objective: To summarize and compare, in narrative form, the reported in-vitro evidence concerning homoeopathic medicines investigated against Candida species, with particular attention to author, year, organism, medicine, potency or preparation, laboratory method, comparator and reported outcome.

Selection criteria:
• Studies investigating Candida species as the test organism.
• Studies evaluating a homoeopathic medicine, mother tincture, combination, or potency.
• Studies using an in-vitro experimental design or summarizing in-vitro evidence.
• Studies reporting identifiable laboratory methodology and antifungal findings.

Studies reviewed (nine primary studies plus one contextual review):
• Prajapati et al. (2017),
• Gupta et al. (2015),
• Shinde et al. (2018),
• De Klerk (1998),

Data breaches are no longer well explained by a simple choice between “human error” and “technical vulnerability.” Recent evidence shows that the dominant risk is increasingly socio-technical: users, administrators, identities, software flaws, third-party services, cloud configurations, and AI-enabled attack methods interact to create breach paths. This review re-examines the causes of organizational data breaches using recent industry evidence and a structured comparison of human, technical, and emerging AI-related factors. The analysis updates the earlier human-versus-system framing by incorporating vulnerability exploitation, credential abuse, social engineering, supply-chain exposure, shadow AI, and AI-assisted attacks. Verizon’s 2026 Data Breach Investigations Report indicates that vulnerability exploitation became the leading initial access vector, while human involvement and third-party exposure remain substantial. IBM’s 2026 Cost of a Data Breach research further reports a sharp rise in AI-enabled attacks and record global breach costs. The paper argues that organizations should move from isolated awareness training or patching programs toward integrated controls that combine identity security, rapid vulnerability remediation, secure configuration, third-party governance, AI usage controls, and continuous detection. The resulting framework is suitable for organizations seeking a practical, risk-based breach-prevention strategy under rapidly changing attack conditions.

Population characteristics are important indicators of the demographic, social and economic development of a region. Population size, growth, density, sex ratio, literacy, age structure, urbanization and workforce characteristics provide an understanding of the spatial and temporal dimensions of population change. Rayalaseema, comprising the traditional districts of Anantapur, Chittoor, Kurnool and YSR Kadapa in Andhra Pradesh, has historically experienced distinctive demographic conditions associated with its semi-arid environment, agricultural economy, uneven urbanization and variations in social infrastructure.
The present study analyses major population indicators of the Rayalaseema region using Census of India data, particularly the 2001 and 2011 Censuses. The study examines population growth, density, sex composition, child population, literacy, gender differences in literacy and urbanization. Comparative analysis is undertaken at the district level to identify intra-regional demographic disparities. The four districts together recorded a population of about 15.19 million in 2011, compared with approximately 13.30 million in 2001. The region therefore experienced a decadal population increase of about 14.2 percent. Chittoor recorded the highest population and population density among the four districts, while YSR Kadapa recorded the lowest population and density. Chittoor also had the highest literacy rate, whereas Kurnool had the lowest. The regional sex ratio was close to 988 females per 1,000 males in 2011.
The findings indicate that Rayalaseema has undergone significant demographic transition, particularly through declining child population proportions, improvement in literacy and gradual urbanization. However, considerable differences remain between districts and between males and females. The study suggests strengthening female education, employment opportunities, urban infrastructure, health services, population-sensitive planning and sustainable livelihood programmes to achieve balanced demographic development in Rayalaseema.

This article examines how artificial intelligence may affect financial reporting accuracy, anomaly screening and reporting efficiency. A narrative review synthesizes recent accounting research, evidence from selected Zambian firms and authoritative risk-management guidance. The literature identifies potential benefits from transaction classification, data extraction, reconciliation, exception analysis and reporting assistance. Published findings include associations between AI use and perceived reporting accuracy, and field evidence relating generative AI to reporting quality and closing speed. These results do not establish that every AI application improves accuracy or that observational relationships are causal. Anomaly alerts support investigation but do not prove fraud. Benefits depend on source-data quality, appropriate accounting logic, internal controls, system validation and professional review. Costs, skills gaps, infrastructure, security, privacy, explainability and excessive reliance on automated outputs constrain adoption. The article proposes phased implementation with clear responsibilities, data controls, human approval and monitoring of both accuracy and efficiency. AI is best treated as support for accountable accounting judgment. Future evaluations should compare independently verified reporting errors and processing outcomes, rather than relying solely on adoption levels or user perceptions.

This article critically reviews the relationship between computerized accounting systems and financial reporting quality in commercial banks. A narrative synthesis draws on information-systems theory, a published Ugandan bank case study, recent accounting-system research and Zambian evidence from a different organizational sector. The analysis distinguishes software availability, effective use, information quality, control processes and independently verified reporting outcomes. Computerized systems may assist transaction processing, reconciliation, audit trails and timely reporting, but software adoption alone does not establish reliable financial statements. Published evidence cannot be transferred between banks, sectors or countries without attention to sample, measurement and design. The article develops a control-oriented framework linking system suitability, staff capability, reconciliations, access management and oversight to reporting quality. It proposes practical monitoring indicators and an empirical research design for Zambian commercial banks. No new bank survey or local regression estimates are reported. Future research should retain verifiable source records, measure reporting quality directly and distinguish association from causation. The review concludes that the value of computerized accounting rests on a reliable accounting process and accountable management use, rather than on a software brand alone.

This research examines the doctrine of proportionality as a constitutional technique for reviewing state action in India and the United Kingdom, with particular attention to measures affecting criminal justice, liberty, privacy, fair procedure and punishment. The central problem is whether proportionality provides a sufficiently structured method for reconciling individual rights with legitimate public interests without allowing courts to substitute their policy preferences for legislative judgment. The study adopts a doctrinal and comparative methodology. It analyses constitutional provisions, the Human Rights Act 1998, leading decisions of the Supreme Court of India and the UK Supreme Court, and selected academic literature. The comparison shows that both jurisdictions increasingly use a structured proportionality inquiry involving legitimate aim, rational connection, necessity and balancing, but the constitutional foundations and institutional consequences differ. India applies proportionality directly through fundamental- rights review under Articles 14, 19 and 21, while the United Kingdom operates principally through Convention rights.

Background: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease characterized by persistent synovitis, pain, stiffness, functional impairment and potential progressive joint damage. Clinical literature on individualized homoeopathic treatment in RA includes randomized trials, observational studies, pilot studies and case reports, but the evidence is heterogeneous in design, sample size, outcome measures and methodological quality.
Objective: To provide a narrative review of clinical literature concerning individualized homoeopathic treatment in RA, summarize reported outcomes and prescribing approaches, and identify important methodological limitations and evidence gaps.
Methods: A narrative review of clinical studies was undertaken. The review was not designed as a formal systematic review; no prospective protocol registration, formal database-search protocol or independent duplicate screening process was undertaken. Clinical publications relevant to RA and homoeopathic treatment were assessed qualitatively according to study design, population, intervention, comparator, outcomes, attrition, methodological limitations and adverse-event reporting. JBI-informed methodological domains were considered where sufficient information was available, without assigning unsupported numerical scores.
Conclusion: The clinical evidence reviewed indicates that individualized homoeopathic treatment may have a beneficial role in the management of rheumatoid arthritis. Across the reported clinical studies, improvements were observed in disease-related symptoms, functional status, selected measures of disease activity, laboratory parameters and quality of life. These findings suggest that homoeopathy may provide clinically meaningful benefits, particularly when treatment is individualized according to the patient’s overall clinical presentation. The consistency of positive observations across controlled, observational, pilot and case-based studies provides a basis for considering homoeopathy as a potential complementary approach in rheumatoid arthritis management. While the available literature is heterogeneous and further well-designed clinical studies are warranted, the findings support continued clinical investigation and suggest a promising therapeutic role for individualized homoeopathic treatment in patients with rheumatoid arthritis.

Augmented Reality (AR) is becoming an important component of digital education because it can place interactive digital information within a learner's view of the physical environment. This review examines the development and educational use of AR from multiple perspectives, including its historical progression, theoretical foundations, technological forms, and implementation across school, university, vocational, and inclusive-learning settings. The discussion distinguishes marker-based, markerless or location-aware, projection-based, and superimposition approaches and considers how each can support different instructional purposes. Evidence reported in the literature is synthesized with respect to learner engagement, motivation, spatial reasoning, knowledge retention, collaboration, and opportunities for safe practice. At the same time, the review addresses constraints such as infrastructure cost, cognitive overload, inadequate teacher preparation, uneven research quality, privacy, accessibility, and equity. Examples from STEM, language education, health-professions training, cultural heritage, and technical education demonstrate the breadth of AR applications. The paper also considers evaluation methods, economic implications, responsible adoption, and emerging developments such as AI-enabled adaptive AR and interoperable immersive environments. It concludes with practical recommendations for educators, institutions, policymakers, and researchers.

Contemporary democratic states are governed through increasingly complex constitutional and institutional arrangements in which legislative, executive, judicial, administrative and regulatory institutions interact to exercise public power. Traditional theories of governance, particularly the separation of powers, parliamentary government, presidentialism, constitutionalism, rule of law and federalism, continue to provide the conceptual foundation for these arrangements, but their application has become more complicated because of the growth of the administrative state, delegated legislation, independent regulatory institutions, judicial review, emergency powers and multi-level governance. The research problem addressed in this paper is whether classical theories of governance remain adequate for explaining and regulating the exercise of public power in contemporary democratic states.
The purpose of the study is to comparatively examine how different constitutional systems distribute, limit and review governmental power. The methodology adopted is primarily doctrinal and comparative, involving analysis of constitutional provisions, judicial decisions and relevant comparative constitutional scholarship. The study compares India with the United Kingdom, United States, Germany and South Africa.
The study finds that no single theory provides a complete model of contemporary democratic governance. Parliamentary sovereignty, presidential separation of powers, constitutional supremacy and cooperative government represent different institutional responses to the same fundamental problem: preventing arbitrary power while maintaining effective government. The paper concludes that contemporary democratic governance requires a combination of constitutional limitations, institutional accountability, judicial review, democratic participation and responsible administration rather than rigid adherence to any single classical theory.

Smart educational campuses are increasingly being developed as connected environments in which physical facilities, people, services, and operational resources generate data for coordinated management. This review examines the complementary roles of Internet of Things (IoT), Artificial Intelligence (AI), cloud computing, and Digital Twin (DT) technology in such environments. The review is derived from the literature base of the completed M.Tech thesis and is strengthened with recent peer-reviewed work on smart-campus integration and campus Digital Twin implementation. The literature indicates that IoT provides continuous sensing, cloud platforms support shared storage and processing, AI converts observations into predictions and analytical indicators, and Digital Twins maintain a contextual digital representation of campus assets. Recent research also demonstrates practical campus implementations involving energy, occupancy, room usage, facility management, and sensor integration. However, the literature continues to identify interoperability, data governance, privacy, cybersecurity, scalability, synchronization, and deployment cost as important challenges. A recurring limitation is that many studies emphasize a single technology or a narrow application rather than an integrated educational-campus workflow. The review therefore organizes the field around five themes: smart-campus evolution, enabling technologies, integrated architectures, application domains, and implementation challenges. The review concludes by identifying a research need for simulation-supported, modular frameworks that connect sensing, centralized data handling, predictive analytics, and continuously updated digital representations while keeping live-data validation as a necessary next step.

Customer responsiveness has become an important consideration in achieving customer satisfaction, particularly among small and medium-scale enterprises (SMEs) operating in highly competitive business environments. This study examined the effect of customer responsiveness on customer satisfaction among selected SMEs in Ondo State, Nigeria. Specifically, the study assessed the effects of prompt response to customer complaints and speed of service delivery on customer satisfaction. The study adopted a cross-sectional survey research design, while structured questionnaires were used to collect data from customers of selected SMEs in Ondo State. Data collected were analysed using descriptive statistics and multiple regression analysis with the aid of the Statistical Package for the Social Sciences (SPSS). The findings revealed that customer responsiveness significantly influenced customer satisfaction. The regression model produced an R-value of 0.513 and an R² of 0.263, indicating that the dimensions of customer responsiveness jointly explained 26.3% of the variation in customer satisfaction. Speed of service delivery had a positive and significant effect on customer satisfaction (β = 0.440, p < 0.001), while prompt response to customer complaints also had a positive and significant effect (β = 0.246, p = 0.022). The study concludes that timely service delivery and prompt handling of customer complaints are important factors in enhancing customer satisfaction among SMEs in Ondo State. It therefore recommends that SMEs strengthen their complaint-handling mechanisms, reduce service delays and establish effective systems for responding promptly to customers' needs and concerns.

Indian Knowledge Systems (IKS) have historically served as the foundation for the holistic development, inner peace, universal brotherhood, and moral values of human life. This tradition is not merely confined to material progress or theoretical knowledge; rather, it is a comprehensive science designed to awaken the infinite potential hidden within humanity. Within this vast and rich philosophical heritage, the Shrimad Bhagavad Gita is regarded as an exceptionally significant, authentic, and welfare-oriented scripture. The Gita stands as the peerless pinnacle of Indian thought, guiding humanity at every crossroad of life.
The central message of the Gita is 'Karma Yoga', which is not merely a narrow path of mechanical duty-following, but a vibrant and psychological science that teaches individuals how to maintain mental equilibrium, stability, and inner strength amidst life's intense struggles, failures, and crises. In the present era when the entire world grapples with the blind race of materialism, consumerism, moral decline, uncertainty, and severe stress and depression the relevance of Karma Yoga in the light of ancient Indian knowledge traditions becomes even more pronounced.
This research paper presents an in-depth analytical study of the philosophical nature of Karma Yoga in the Shrimad Bhagavad Gita, its various dimensions (such as Nishkama Karma, equanimity, and prescribed duty), and its contemporary indispensability within the broader perspective of Indian Knowledge Systems. Through this research, it is highlighted how Karma Yoga can serve as an effective guide in establishing balance within modern corporate management, stress management, ethical leadership, and personal life. Ultimately, the paper concludes that by assimilating the principles of the Shrimad Bhagavad Gita into modern educational systems and lifestyles, a healthy, peaceful, dutiful, and balanced society can be successfully built.

Freshwater ecosystems cover less than one percent of the Earth’s surface, yet they hold a disproportionately large share of its known species. They are also among the most exposed to a changing climate. This review draws together published evidence on how rising temperature, altered hydrology, declining dissolved oxygen and shifting water chemistry are reshaping freshwater biodiversity and the interactions that hold aquatic communities together. Warming favours small-bodied, warm-tolerant and often non-native organisms, while cold-water specialists and species with narrow habitat needs are squeezed out. Changes in the timing of seasonal events are pulling apart predators from their prey and grazers from their food, and cyanobacterial blooms, oxygen loss and hydrological extremes are pushing some lakes and rivers towards abrupt, hard-to-reverse state changes. Climate change rarely acts alone; it amplifies eutrophication, flow regulation, invasion and over-exploitation. Evidence from tropical and monsoonal Asia remains thinner than that from temperate regions, which is a real limitation for a country such as India. The paper closes with management priorities: protecting thermal and hydrological refugia, restoring natural flow variability, controlling nutrient inputs, and building long-term monitoring at regional colleges and universities.

For decades, environmental protection laws have operated under an anthropocentric framework, treating ecosystems merely as property or natural resources subject to human ownership. The global emergence of 'Rights of Nature' (RoN) jurisprudence seeks to replace this paradigm with an ecocentric framework, granting rivers, forests, and entire ecosystems intrinsic legal personhood. However, translating judicial declarations and constitutional guarantees into functional, daily enforcement mechanisms remains a persistent challenge. This article investigates the structural legal gaps preventing RoN from becoming an operational compliance system. Through comparative analysis of landmark frameworks—including New Zealand’s Te Awa Tupua, Colombia’s Atrato River rulings, and Peru’s Rio Marañón cases—this paper identifies key enforcement bottlenecks: guardianship liability, standing, and monetary damages. Finally, it proposes concrete statutory mechanisms, including public-trust guardianships and eco-centric restitution funds, to ensure nature's rights are legally enforceable rather than purely aspirational.

As radial turbines can effectively transform fluid energy into mechanical energy, they are extensively used for power production in emergency situations, as mini-power plants, and transportable plants. They are most helpful in remote locations, conflict zones, and natural disasters where cost-effectiveness, portability, and rapid deployment are essential. In difficult situations, these turbines power vital services like communication systems, medical units, and water purifying. Radial turbines must be made smaller and less expensive to become more feasible. Turbines can be distributed more quickly in environments with limited resources. More compact form of a turbine helps to reduce costs and improves portability enabling simple distribution and transportation in remote locations. Since its high cost necessitates optimization to reduce material usage and rotor size, Titanium alloy is selected for its exceptional thermal and mechanical qualities, with a balance between performance, cost-effectiveness, and mobility Various algorithms have been developed to tackle design optimization problems, including Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differential Evolution (DE), and more. However, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) are chosen for this study due to their distinct advantages. GA, inspired by natural selection and genetics, excels in exploring a wide range of design possibilities and finding near-optimal solutions in large, complex search spaces. ACO, stimulated by the foraging actions of ants, is particularly efficient in refining solutions and searching for the global optimum, making it highly effective in complex, multidimensional optimization problems. The combination of these two algorithms leverages their strengths, providing a robust approach to identifying and fine-tuning optimal designs for radial flow gas turbine rotors. In order to achieve an ideal design that optimizes structural integrity and aerodynamic performance while minimizing weight and manufacturing costs, this thesis works on GA and ACO. To meet design specifications, structural and thermal stresses were performed for mechanical consideration. The correctness and dependability of this optimization strategy are confirmed by the combination of finite element analysis and computational fluid dynamics, which is verified by ANSYS and CFD simulations.

This research article undertakes a comparative constitutional analysis of the right to privacy in the context of state-sponsored digital surveillance in India and the United States. The primary research problem centres on the adequacy of existing statutory frameworks to protect citizens against disproportionate executive surveillance in the digital age. The purpose of this study is to critically examine the legal tension between national security imperatives and fundamental privacy rights, and to identify gaps in executive accountability. Utilising a combination of doctrinal and comparative legal research methodologies, this article analyses primary constitutional provisions, statutes, and landmark judicial decisions in both jurisdictions. The major findings indicate a stark procedural divergence: while the United States relies on a judicial oversight model anchored in the Fourth Amendment and specialised courts, India maintains an executive-centric authorisation framework under the Information Technology Act, 2000, and the Indian Telegraph Act, 1885, largely devoid of prior judicial scrutiny. The article concludes that India’s current surveillance architecture fails to meet the proportionality standard established in the Puttaswamy judgment and recommends integrating independent ex-ante judicial oversight mechanisms, inspired by the American constitutional experience, to restore the balance between state power and individual liberty.

Social media's and digital platforms' explosive growth has completely changed how people communicate, get information, and engage in public conversation. These platforms are powered by increasingly complex analytic systems that decide what data is shown, suggested, rated, filtered, and prioritised. Because of this, algorithms are much more than just technical tools; they have an increasing impact on how people exercise their rights and how digital society operates.
The regulation of algorithmic governance in China and India is compared in this article, with a focus on social media and digital platforms. The Information Technology Act of 2000, the Information Technology Rules of 2021, the Digital Personal Data Protection Act of 2023, and the Digital Personal Data Protection Rules of 2025 have all contributed to the development of India's regulatory framework. By way of the Internet Information Service Algorithm Recommendation Management Provisions, 2022, the Personal Information Protection Law, 2021, and the Data Security Law, 2021, China, on the other hand, has enacted more precise algorithm-orientated legislation.
With a focus on privacy, accountability, transparency, user autonomy, freedom of expression, and regulatory oversight, the study employs a doctrinal and comparative approach to analyse the two regulatory regimes. It contends that although India's system has a solid constitutional basis, it is nevertheless disjointed from the standpoint of algorithmic accountability. With regard to algorithm review, user choice, algorithm filing, and security assessment, China's structure offers more direct oversight of algorithmic recommendation services. However, the two nations function in quite distinct institutional and constitutional contexts.
By creating risk-based algorithmic regulation, algorithmic impact assessments, meaningful transparency, user-choice mechanisms, and independent auditing—all while making sure that such regulation stays in line with constitutional rights and judicial review—the paper suggests that India can selectively learn from China's experience.

Social media has changed how people talk to one another. It has opened up access to information for millions, but it has also created hard legal problems: misinformation travels fast, unlawful content circulates freely, personal data is mishandled, and platforms are rarely held to account. The central difficulty for any regulator is deciding how to tackle these harms without trespassing on speech that the Constitution protects.
This paper looks at how India, the United States and the United Kingdom have responded. For India, the discussion draws on Articles 19 and 21 of the Constitution, the Information Technology Act, 2000, the Intermediary Guidelines Rules, 2021 and the Digital Personal Data Protection (DPDP) framework. For the United States, it turns to First Amendment case law and Section 230 of the Communications Decency Act. For the United Kingdom, it considers the systemic, regulator-led model of the Online Safety Act 2023. Using doctrinal and comparative methods, the paper shows how each system divides responsibility between the State, platforms and users. Its conclusion is that India should build its regime on proportionality, fair procedure, transparency in algorithms and genuinely independent oversight.

Employee training and development is an important human resource management practice that enables employees to acquire knowledge, skills and competencies required to perform their duties effectively. This study examined the effect of employee training and development on employee performance in selected organizations in Chipata District, Zambia. The study adopted a descriptive research design using a quantitative approach. Data were collected through a structured questionnaire distributed electronically using Google Forms. A total of 45 questionnaires were distributed, of which 41 were completed, representing a response rate of 91.1%. The respondents included employees occupying management, supervisory and general employee positions. The findings indicate that employees generally perceived training and development positively. For example, 58.5% of respondents agreed or strongly agreed that training had improved their ability to perform their jobs, while 72.5% indicated that training had improved the quality of their work. Furthermore, 68.3% agreed or strongly agreed that training helped them complete their work more efficiently, 75.6% indicated that training increased their confidence, 70.7% indicated that training helped them adapt to workplace changes, and 65.9% reported improved productivity. In addition, 87.8% of respondents stated that employee training and development improves employee performance. The study concludes that training and development is perceived by employees as an important contributor to workplace performance. The study recommends that organizations should conduct regular training needs assessments, provide relevant training opportunities, allocate adequate resources for employee development and evaluate training outcomes.

Background: Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder of women of reproductive age that affects not only physical health but also emotional, social and reproductive well-being. Quality of life (QoL) is therefore an important outcome in its management. The Polycystic Ovary Syndrome Health-Related Quality of Life Questionnaire (PCOSQ) is a validated, disease-specific tool for measuring it.
Objective: To assess the quality of life of women with PCOS after individualized homoeopathic intervention by comparing PCOSQ scores before and after treatment.
Methods: A retrospective observational (before and after) study was carried out among 30 women diagnosed with PCOS at the Out-Patient Department of Sarada Krishna Homoeopathic Medical College Hospital, Kulasekharam, over a period of 6 months. Individualized homoeopathic medicines were prescribed on the totality of symptoms. PCOSQ scores before and after treatment were compared using the paired t-test and the Wilcoxon signed-rank test; age, medicine prescribed and potency were analysed descriptively.
Results: The age of the patients ranged from 12 to 39 years, and the largest group (46.7%) was aged 21–25 years. Sulphur was the most frequently prescribed medicine (23.3%), and 200C was the most commonly used potency (66.7%). The mean PCOSQ score rose from 3.14 ± 0.33 before treatment to 5.45 ± 0.39 after treatment, a mean gain of 2.31 points (95% CI 2.22 to 2.41; p < 0.001). All 30 patients (100%) showed improvement. After treatment, 13 patients (43.3%) had a good quality of life and 17 (56.7%) a relatively good quality of life.
Conclusion: Quality of life of women with PCOS improved significantly during individualized homoeopathic treatment. As there was no control group and one patient given Sac lac also improved, the results cannot be attributed with certainty to the medicines; larger controlled studies are recommended.

Male infertility is commonly associated with abnormalities in semen parameters, including liquefaction time, semen volume, sperm concentration and sperm motility. This case series describes changes in these parameters in three men following individualized homoeopathic treatment. Cases were assessed through detailed case-taking and serial semen analysis, with semen volume, liquefaction time, sperm concentration and motility recorded at baseline and during follow-up. Rapid progressive motility rose from 30% to 50% in Case 2; sperm concentration rose from 10 to 39 million/mL and semen volume from 1.0 to 1.3 mL in Case 3; and liquefaction time shortened from more than 1 hour to 5 minutes in Case 1, whose partner conceived during follow-up. Symptomatic improvement was documented only in Case 1. Because of the small number of cases, the absence of a control group and possible confounding, these observations are hypothesis-generating only; larger controlled studies are required to establish effectiveness.

Alopecia areata (AA) is a chronic immune-mediated disorder with multifactorial pathogenesis. It is characterized by non-scarring hair loss, usually presenting as well-defined patches, with clinical severity varying according to the extent and distribution of hair loss. The condition may impose a considerable psychosocial burden and adversely affect the quality of life of affected individuals.

A 24-year-old male patient presented to the Outpatient Department of Amraze Jild wa Tazeeniyat, H.S.Z.H. Government Autonomous Unani Medical College & Hospital, Bhopal, Madhya Pradesh, with a localized patch of hair loss over the scalp. Based on the clinical history and examination, the patient was clinically diagnosed with alopecia areata, correlated with Dā’ al-Tha‘lab in Unani medicine.

The patient was treated for seven days with a combination of systemic and topical Unani formulations. Jawarish Amla Sada 5 g twice daily after meals and Sharbat-e-Faulad 10 mL twice daily after meals were prescribed orally, along with topical application of Roghan Zararih over the affected area. Following 7 days treatment, visible hair regrowth was observed over affected area. No adverse effects were reported during the treatment period.

The patient was treated for seven days with a combination of systemic and topical Unani formulations. Jawarish Amla Sada 5 g twice daily after meals and Sharbat-e-Faulad 10 ml twice daily after meals were prescribed orally, along with topical application of Roghan Zararih over the affected area. Following seven days of treatment, visible hair regrowth was observed over the previously affected area. No adverse effects were reported during the treatment period.

The therapeutic rationale of the regimen was based on the traditional use of the formulations as hair-strengthening, hair-tonic and locally circulation-supportive agents, together with the antioxidant potential of Amla and the possible hair-growth-supportive effects of the constituents of Roghan Zararih.

The present case describes visible hair r egrowth following a combined systemic and topical Unani regimen in a patient with localized alopecia areata. Further controlled clinical studies are required to evaluate the efficacy and safety of this therapeutic approach.

This research examines the fundamental characteristics of the civil law legal tradition and compares them with the legal system of India. Civil law is historically associated with Roman law, systematic codification and the central role of enacted legal rules. The study uses France as the principal civil-law jurisdiction and India as a common-law-derived jurisdiction. It investigates the role of codes and legislation, judicial precedent, legal interpretation, the position of judges, constitutionalism, legal education and practical dispute resolution. The research adopts a doctrinal and comparative methodology based on constitutions, statutes, judicial decisions, official institutional materials and leading comparative-law literature. The study finds that the traditional distinction between civil law and common law remains useful for identifying differences in legal method, but the distinction is no longer absolute. Contemporary civil-law systems increasingly rely on judicial decisions to secure uniform interpretation, while India has developed a highly codified statutory framework within which binding precedent under Article 141 of the Constitution gives the judiciary a significant law-developing function. The comparison therefore demonstrates convergence alongside institutional differences. The article argues that India should not be treated as a civil-law system merely because it has numerous codes; its deeper institutional characteristics remain rooted in the common-law tradition, modified by constitutional supremacy, legislation and indigenous legal pluralism.

This article examines whether sustainable development operates as an enforceable legal standard compelling State decisions on infrastructure development, or is primarily a rhetorical principle, through a comparative study of the policies prevalent in India and Australia. The countries have recently undergone major statutory amendments. This article compares India’s Forest (Conservation) Amendment Act, 2023 (hereinafter referred to as the “2023 Indian Amendment Act”) and Australia’s Environment Protection Reform Act 2025 and National Environmental Protection Agency Act 2025 (hereinafter referred to as the “2025 Australian Reforms”). It judges both on the basis of enforceability, institutional embedding, procedural safeguards and practical effects drawn from official reviews and audits of environmental clearance in both countries. United Nation’s sustainable development goals (hereinafter referred to as “SDGs”) 9, 15 and 16 guide the analysis. The methodology is doctrinal and comparative and the official forest-diversion data placed before Parliament are used as context. The article finds that sustainable development operates as partially enforceable standard in both jurisdictions. It is effective when combined with a specific legal doctrine, procedural requirement or institutional mechanism. However, it gets weaker when invoked as a freestanding constraint on executive direction. In the first instance, India’s 2023 amendment appears to narrow the procedural safeguards through executive-administered exemptions, while Australia’s 2025 reforms focus more on strengthening of compliance and enforcement machinery and introduces binding standards. This article concludes that the legal, procedural and institutional anchoring of the standard, rather than its substantive formulation, is the operative variable, with SDG-16 type safeguards an important but not exclusive component.

This Research Article primarily focuses on the statutory Right to Erasure which is guaranteed to an individual regarding their personal data and information given under Section 12 of the Digital Personal Data Protection (DPDP) Act of 2023. It also explores certain legislative restrictions and boundaries on the Right to Erasure in India in comparison to other jurisdictions like- General Data Protection Regulation (GDPR), 2016 formulated by the European Union. While GDPR under Section 17 provides an extensive "Right to be Erasure (Right to be Forgotten)" which is aided by various legal precedents while allowing limited exceptions, on the other hand, the DPDP Act provides a highly restrictive approach which is subject to certain conditions and exceptions allowing erasure only on Withdrawal of consent by the user or Fulfilment of specified purpose or Removal of Misleading, Incorrect or Outdated Information. This Research Article is a critical doctrinal and analytical research, which highlights the emerging legal challenges and structural shortcomings in the laws including various points of contention like the multiple exemptions granted to state under Section 17 of DPDP Act, which undermines the autonomy of a person, and it also affets operational ability of Data Protection Board (DPB) which has been established under Section 18. Essentially, this article argues that although DPDP Act has been a significant step in providing Legal Recognition and Organisational Accountability for Data Protection and Digital Privacy in India, prevailing implementation gaps, executive shortcomings, and technological complexities including Artificial Research remain key in building a resilient data privacy framework.

Where the state can resort to emergency powers, a recurring issue of constitutional democracy is that the kind of powers it may need to meet great threats can lead to the undermining of ordinary guarantees of legality, liberty, federalism and institutional accountability. This Article is a comparative perspective on the constitutional and statutory framework of emergencies in India and United States under a doctrinal and functional approach. It explores the constitutional remedial measures in case of emergency, as provided in the Part XVIII of the Indian Constitution as well the remedial measures introduced in the Constitution of India through 44th amendment post-1975, Article 356 federal interventions and the development of judicial review. It then compares the American version which has constitutional distribution of powers and is juxtaposed with the National Emergencies Act, the Alien Enemies Act and the habeas corpus doctrine. As the comparison shows, constitutional entrenchment and statutory delegation entail different types of risks and do not result in a hierarchy of protection. The triggers and formal parliamentary consent are specified by law in India, and emergency governance in the United States often relies on the nature of the delegations of law and the ongoing supervisory authority of the Congress. In both systems, courts have seen access to judicial review and statutory limits as core protections, and due process and constitutional rights protection as central protections, albeit to varying degrees in both systems and of varying doctrinal nature. The Article proposes a series of five inter-dependent tests to assess emergency legality: a legally prescribed trigger, ongoing legislative authority, a safeguarded floor of rights, accessible courts and genuine exit. These standards offer a possible structure to evaluate reforms in India, without mechanistically grafting United States doctrine onto the Indian context.