Background: Childhood is marked by rapid physical and psychological evolution, but deviations in behavior often manifest as significant distress for both the child and the caregiver. Conventional management typically focuses on symptom suppression or behavioral training. Homoeopathy, however, views these "behavioral problems"—such as temper tantrums, habit disorders, elective mutism, and functional enuresis—not as isolated diagnoses but as outward expressions of an underlying constitutional imbalance or a "disordered vital force". Objective: This presentation explores the holistic homoeopathic approach to identifying and managing common pediatric behavioral patterns by addressing the root emotional and physical causes. Methodology: The approach utilizes detailed case-taking, including the child's "goodness of fit" with their environment, prenatal history, and specific modalities of their behavioral outbursts. Key areas of focus include: Temper-Tantrums: Differentiating violent outbursts from developmental frustration to select remedies like Chamomilla or Belladonna.Habit Disorders: Addressing repetitive behaviors (e.g., nail-biting) through remedies that target underlying anxiety or sensory needs. Elective (Selective) Mutism: Understanding the internal withdrawal and emotional blocks that necessitate deep-acting constitutional remedies.Functional Enuresis: Identifying concomitant symptoms and physical predispositions to select targeted therapeutics.

This study investigates the critical factors that influence the development of a safety culture within organizations and formulates strategic frameworks for its enhancement. Utilizing a mixed-methods approach, data were collected from a sample of employees and safety managers across various industrial sectors through surveys and in-depth interviews. The findings reveal that leadership commitment, employee involvement, effective communication systems, and robust safety training are the most significant determinants of a positive safety culture. Furthermore, the study identifies a strong correlation between a mature safety culture and reduced incident rates, improved employee morale, and enhanced operational productivity. The analysis indicates that many organizations struggle with translating formal safety procedures into deeply ingrained cultural values. The study concludes by proposing a comprehensive strategy matrix that integrates top-down leadership engagement with bottom-up employee empowerment, supported by continuous learning and proactive hazard reporting mechanisms. This research provides organizational leaders and safety professionals with actionable insights for cultivating an intrinsic, resilient, and effective safety culture that extends beyond regulatory compliance to become a core organizational value.

This study investigates the effectiveness of Safety Leadership Training (SLT) in improving organizational safety outcomes and shaping positive employee safety behaviour. Drawing on a quantitative research approach, data were collected from employees and supervisory staff across selected high-risk sectors in Ghana, including construction, manufacturing, mining, and healthcare. The study examines whether structured safety leadership interventions translate into measurable improvements in safety performance indicators such as incident reduction, near-miss reporting, compliance levels, and proactive safety participation. The findings indicate that organizations that implement structured and continuous safety leadership training programs experience significant improvements in employee safety compliance, enhanced reporting culture, and stronger safety climate perceptions. Furthermore, the results demonstrate that leadership behaviour serves as a mediating factor between safety training and safety outcomes, reinforcing the importance of visible and consistent leadership engagement. However, the study also reveals that training effectiveness depends on organizational support systems, reinforcement mechanisms, and alignment between safety values and operational priorities. The research concludes by proposing an integrated safety leadership effectiveness model that links training content, leadership behavioural change, employee engagement, and safety performance metrics. The study contributes to the growing body of knowledge on safety culture development and provides practical insights for policymakers, organizational leaders, and safety professionals seeking to move beyond compliance-based training toward transformational safety leadership practices.

This study investigated the effect of maritime trade on real gross domestic product in Nigeria. The data used for the study were time series data sourced from the National Bureau of Statistics (NBS) annual abstract and Central Bank of Nigeria (CBN) statistical Bulletin, World Development Indicator (WDI), Nigerian Ports Authority (NPA) and Nigerian Shippers Council (NSC) which spanned between the period 1990 to 2023. For the dependent variables, the study utilized real GDP and the components of maritime trade (oil trade, non-oil trade and containerized trade) served as the independent variables The analytical techniques employed were Augmented Dickey Fuller (ADF) unit root test, Johansen cointegration test and bounds cointegration test. The unit root test revealed that all the variables were non-stationary at level but became stationary at first difference that is, integrated of order one I(1). The evidence of the presence of cointegration amongst the variables formed the basis for estimating the model using error correction model (ECM). The short run results showed that oil trade has a negative and non- significant effect on real GDP in Nigeria. Also, non-oil trade revealed an insignificant positive effect on real GDP in Nigeria. Furthermore, the short run result revealed that containerized trade has a negative and statistically insignificant effect on real GDP in Nigeria. Thus, the study recommended that government should prioritize agriculture, solid minerals, and manufacturing sectors through increased investment and export grants. Also, government should support indigenous businesses through export promotion strategies, trade openness, domestic protection measures. This will help generate employment, increase real GDP and put the country on a part to sustainable economic growth.

This study examines the challenges and risks associated with lone working in high-risk industries, with particular focus on construction and healthcare sectors. Lone working, defined as situations where employees perform tasks in isolation without direct supervision or immediate assistance, has become increasingly prevalent due to operational demands, workforce restructuring, and flexible service delivery models. While high-risk industries traditionally emphasize collective safety systems and team-based risk management, lone workers often operate under conditions that heighten their vulnerability to physical hazards, psychosocial stressors, delayed emergency response, and limited situational support. Drawing on a quantitative research approach, data were collected from employees and supervisors within selected construction firms and healthcare facilities to evaluate the nature, frequency, and severity of risks encountered by lone workers. The study investigates key dimensions including hazard exposure, emergency preparedness, communication systems, psychological strain, and organizational safety support. Findings indicate that lone workers experience significantly elevated risk perception levels, increased exposure to unmitigated hazards, and greater psychological stress compared to non-lone workers. The results further reveal that inadequate monitoring systems, weak communication protocols, and insufficient lone-worker-specific policies exacerbate safety vulnerabilities. The study concludes by proposing a risk mitigation framework integrating technological monitoring, structured supervision protocols, psychosocial support systems, and policy enforcement mechanisms. This research contributes to occupational safety literature by highlighting the unique risk dynamics of lone working arrangements and provides evidence-based recommendations for strengthening safety management systems in high-risk sectors.

Infrastructure-as-Code (IaC) has emerged as a foundational practice in modern cloud computing by enabling automated, consistent, and version-controlled infrastructure provisioning. However, dynamic cloud operations and manual interventions frequently introduced configuration drift, causing the deployed infrastructure to diverge from the intended state defined in IaC specifications. Such drift can lead to security vulnerabilities, compliance violations, service instability, and increased operational complexity. While prior research has primarily focused on detecting configuration drift, there remains a lack of comprehensive approaches that address continuous monitoring, impact analysis, and practical integration with DevOps workflows. This paper proposes an automated and systematic approach for the detection and analysis of configuration drift in IaC-based cloud systems. The proposed system establishes a baseline infrastructure state form IaC repositories and continuously compares it with the real-time deployed environment using state comparison and rule-based verification techniques. Detected deviations are analysed and logged to support informed decision-making by administrators. A prototype implementation using widely adopted IaC and cloud technologies demonstrates the feasibility and effectiveness of the approach. Experimental results indicate that the proposed system improves infrastructure consistency, enhances operational reliability, and supports security and compliance requirements in dynamic cloud environments.

The escalation of trade tensions between the United States and China has significantly altered global trade patterns, creating both challenges and opportunities for third-country economies. This study empirically examines the impact of the US trade war on India’s export performance using bilateral trade data for the period 2015–2022. Relying on mirror trade data from the UN Comtrade Database, the analysis compares India’s exports to the United States before and after the onset of the trade war and contrasts export trends with China over the same period. A dummy-variable framework and mean comparison analysis are employed to assess changes in export levels associated with the trade war period. The results indicate a statistically meaningful increase in India’s exports to the United States during the post-trade war phase, alongside clear differences between pre- and post-trade war export performance. Comparative evidence further suggests that India’s export trends to the United States differed from those to China, highlighting heterogeneous export responses across trading partners. The study contributes to the literature on trade wars by providing country-specific evidence on third-country export responses to major trade policy shocks. The findings offer policy-relevant insights for strengthening export preparedness, market diversification, and trade facilitation in an increasingly uncertain global trade environment.

Continuous unification and unending deployment (CI/CD) practices authorize speedy software childbirth in cloud surroundings but significantly increase the risk of arrangement-accompanying collapses that can impact service chance and consumer experience. Existing rollback means are principally manual or rule-based, lack exact misstep detection, and support restricted support for stateful services, multi-duty reliance’s, and procedure compliance. This paper presents a result-grade Autonomous Rollback Mechanism for Cloud Deployments that addresses these disadvantages through a multi-layered design. The projected whole integrates real-opportunity listening accompanying multi-signal anomaly discovery utilizing statistical baselines and inconsequential machine intelligence models to correctly identify arrangement missteps while minimizing fake rollbacks. It supports cautious rollback actions containing informer, blue–green, and dependency-knowledgeable rollback sequencing for microservices and stateful components. A procedure-knowledgeable decision diesel accompanying audit record and optional human supersede guarantees operational security and agreement. Post- rollbacks verification is acted utilizing health, thickness, and depiction checks to confirm profitable improvement. The system is evaluated utilizing blame injection and physical arrangement traces across single-cloud and multi-cloud surroundings. Experimental results display important reduction in 24-hour day to improvement (MTTR), low fake rollbacks rates, continued data thickness, and littlest performance overhead, reinforcing the influence and reliability of the projected approach.

Breast cancer is still a major worldwide health concern that requires novel techniques to both diagnosis and treatment. Single-stranded oligonucleotides called aptamers have shown great promise in the fight against breast cancer because of their high affinity and selectivity in at-taching to target molecules. This abstract delves into the various functions of aptamers in the treatment of breast cancer, with an emphasis on their use in targeted therapies and diagnos-tics. Compared to traditional therapeutic agents, aptamers have several benefits, such as min-imal immunogenicity, high specificity, and the capacity to target a variety of biomarkers linked to the advancement of breast cancer. They can be made to attach to cancer cells only, preventing tumour growth and metastasis and reducing unintended effects on healthy organs. Additionally, aptamers can be coupled with other payloads, such as imaging agents, nanopar-ticles, or chemotherapeutic medicines, to improve their therapeutic efficacy and allow for tar-geted administration to tumour locations. Apart from their promise as therapeutics, aptamers have transformed the field of breast cancer diagnostics by acting as precise and sensitive bi-omarkers for the identification and tracking of the illness. Breast cancer biomarkers can be quickly and accurately identified with the use of aptamer-based biosensors and imaging probes, which can lead to early detection and individualised treatment plans. Additionally, aptamers can be used in liquid biopsy tests to find circulating tumour DNA or cells, which can help with prognostication and treatment selection. All things considered, aptamers are a promising family of chemicals for the targeted diagnosis and therapy of breast cancer. In the fight against breast cancer, their adaptability, specificity, and low toxicity make them indis-pensable instruments in the creation of cutting-edge therapies and diagnostic systems, which will eventually improve patient outcomes and quality of life.

This study investigates the value relevance of accounting fundamentals in the Euronext 100 index; more specifically, it investigates the question of whether or not applying an accounting fundamental strategy to select stocks results in significant, positive excess market buy-and-hold returns after one and two years of portfolio formation. The purpose of this investigation is to determine whether or not accounting fundamentals can provide relevant information that can clarify firm value. This work offers a collection of accounting basic signals that represent information that might impact security prices, although the information may not necessarily be reflected in a timely way. This is accomplished by merging valuation theory with accounting research. After accounting for factors such as profits, the book-to-market ratio, and company size, annual financial and market data from companies included in the Euronext 100 index between the years 2000 and 2014 show that the basic approach offers investors information that is value-relevant. The connection between the accounting basic signals and the buy-and-hold market future returns (on a one- and two-year time horizon) is one that is both large and favourable. In other words, portfolios that are constructed on the basis of high scores on the signals have achieved a 13 percent market excess yearly return on average between the years 2000 and 2014. This study not only addresses the real-world issue of mispriced stocks, but it also makes a valuable contribution to the limited accounting research that has been conducted on European capital markets by elaborating on the "post-earnings" drift phenomenon that has been observed in the Euronext 100 index.

This study employs the TGARCH model to determine the impact of balance of payments factors on exchange rates volatility in Nigeria. Specifically, we examine the extent to which changes in trade balance, FDI, FPI, external debt, remittances and current account balance affect the volatility of the Dollar/Naira exchange rate using weekly time series data from 2010 to 2024. We find that exchange rate return is persistent while exchange volatility is mean-reverting and does not exhibit asymmetric effects. Also, exchange rate volatility is driven by changes in current account balance, foreign portfolio investment, external debt, and foreign direct investment. We therefore argue that tracking, prioritizing, and targeting the movements in current account balance, FPI, external debt, and FDI are necessary policy actions towards exchange rate stability in Nigeria.

The consciousness over the quality is the part and parcel of any consumer. Hygiene, health and positive consumer lifestyle is no exception to any buyer. And, in recent times the eyes of such consumers are turning towards the market of Organic food products. The buying behaviour and consumer brand loyalty is at state for the unhygienic products. The study also intent to examine that the quality consciousness of organic food products is furthered by the influencers in social media platforms. This research work congregate data from the buyers of organic products in Tamil Nadu and measures the Brand Loyalty of the consumers.

This study investigates digital wellbeing, screen time patterns, and coping strategies among 50 university students from the Computer Science Department at Abuissa College of Education, Zawia University. It aims to explore students’ awareness of digital wellbeing, examine their daily screen time habits, and identify strategies used to manage technology use effectively. A quantitative descriptive research design was employed, and data were collected using a Likert-scale items self-administered questionnaire. Descriptive statistical analyses, including frequencies, percentages, means, and standard deviations, were conducted using SPSS. The findings indicate that students demonstrate moderate to high awareness of digital wellbeing and recognize the negative effects of excessive screen time on mental health and academic performance. Most students reported spending 4–6 hours daily on digital devices, primarily for academic work and social media, while engagement with learning applications was comparatively low. Coping strategies such as prioritizing academic tasks and taking regular breaks were moderately applied, whereas offline activities, including sports, reading, or socializing, were less frequent. The study emphasizes the need for structured guidance, awareness programs, and institutional support to promote effective screen time management. These findings provide valuable insights for educators, curriculum designers, and policymakers aiming to balance digital engagement with academic responsibilities and personal wellbeing in higher education.

This study examined the effect of human capital development on organizational performance in the manufacturing sector, with Cowbell Company, Anambra State, as a case study. Specifically, it investigated the relationships between workers’ training and performance, and management development and employee motivation. A survey research design was adopted, with 118 staff sampled using convenience sampling, and data collected through structured questionnaires. Analysis using Pearson Correlation revealed a strong positive relationship between workers’ training and improved performance, as well as between management development and employee motivation. The findings confirm that investment in human capital is critical for enhancing productivity and fostering organizational growth. The study recommends that organizations should continuously invest in employee training and management development to achieve higher efficiency, motivation, and overall performance.

Stock market prediction remains a challenging nonlinear time-series forecasting problem due to volatility, noise, and non-stationary behavior. Traditional statistical models fail to capture dynamic market structures efficiently. This paper proposes an optimized hybrid forecasting framework integrating Adaptive Moving Average (AMA), Principal Component Analysis (PCA), Discrete Wavelet Transform (DWT), and an enhanced Deep Neural Network (DNN) trained using an improved Momentum-Based Gradient Descent (MBGD) algorithm. The proposed architecture decomposes financial time series into multi-resolution components using DWT, reduces dimensionality via PCA, and extracts smoothed trend features using AMA before deep learning-based prediction. Experimental evaluation demonstrates superior performance compared to conventional ARIMA, standalone DWT, and traditional ANN models. Performance metrics including MSE, MAE, MAPE, Regression Score (R²), and Accuracy validate the robustness of the proposed approach.

The present study explores the integration of Artificial Intelligence (AI) in inclusive education, focusing on opportunities, challenges and teacher perceptions. The objective was to identify AI applications that support students with disabilities, examine implementation barriers and analyze associations between demographic variables and educators’ attitudes toward AI-enabled inclusion. A descriptive survey method was adopted, with data collected from 50 teachers and special educators across various schools and institutions using a structured questionnaire. Percentage analysis and chi-square tests were employed for data analysis. Findings indicate that AI offers significant opportunities through personalized learning, assistive technologies (e.g., speech-to-text, adaptive platforms) and real-time feedback, enhancing accessibility and engagement for children with special needs (CwSN). However, major challenges include lack of teacher training, inadequate infrastructure, digital divide, algorithmic bias and data privacy concerns. Educators with prior AI exposure or training demonstrated significantly more positive perceptions (p < .05). The study highlights the need for systematic professional development, robust policy frameworks aligned with the National Education Policy (NEP) 2020 and the Rights of Persons with Disabilities (RPwD) Act, 2016 and ethical guidelines to harness AI for equitable and inclusive education.

Weed management remains one of the most persistent challenges in Indian agriculture, contributing significantly to crop yield losses and increased reliance on synthetic herbicides. Mycoherbicides—fungal-based bioherbicides—have emerged as environmentally sustainable alternatives. A novel evolution in this domain involves the use of cell-free fungal broth formulations, consisting of extracellular metabolites and bioactive compounds without viable fungal propagules. While scientifically promising, regulatory pathways governing such products in India remain ambiguous due to overlapping jurisdiction between the Insecticides Act, 1968 and the Fertilizer (Control) Order, 1985 (FCO), particularly after recent amendments recognizing microbial and cell-free products under biostimulant categories. This review critically examines the regulatory landscape applicable to cell-free mycoherbicides in India, compares global regulatory approaches, identifies policy gaps, and proposes a structured framework for streamlined approval. Establishing dedicated guidelines for microbial metabolite-based herbicides will accelerate innovation while ensuring biosafety and environmental protection.

The analysis conducted via computer simulation carried out in MATLAB/Simulink environment for the developed PID-LQR control system of Flexible Link Robot Manipulator reviewed that the combination of PID and LQR controller as a hybrid algorithm can enhance the transient and steady-state response characteristics of the system. Implementing the system with PID-LQR ensured stability and smooth response. The use of the PID-LQR technique guaranteed very much rapid response. This means that in practice it will be used to performed more task per operation time than either PID controller or LQR controller. All the control scenarios revealed that the controller was able to supress the link deflection. This means that with any of the controller’s design state, the deviation or vibration of the flexible link which could influence the ability of the manipulator to maintain or tracked a referenced position was eliminated in all cases.

This paper presents speed response and electromagnetic torque characteristics analysis of three-phase induction motor using thyristor-controlled method. Modelling, implementation, and testing of a thyristor-controlled three-phase induction motor system were carried out using MATLAB/Simulink to performed numerical and computer simulation analysis. Simulation was successfully conducted under four different loading conditions (0, 5, 10, and 20 N-m), and comprehensive performance data was collected and analysed. The results demonstrated that: the system exhibited stable operation across all tested load conditions. An obvious observation was that the dynamic performance degrades progressively with increasing load, and the controller maintains adequate speed regulation despite varying mechanical loading.

The efficiency of industrial grinding machines is improved by using a dynamic model that captures most of the system’s key characteristic parameters.in this paper, a good model of the industrial grinding machine was developed where the infeed velocity is considered amongst the goals in manufacturing, one of the commonest is to improve the quality and accuracy of the parts being fabricated without reducing productivity. This places a very high-performance demand on industrial machine tools. An industrial grinding machine is a typical example where adequate control of the process to improve efficiency and maximize productivity is required. But the presence of some transmission components induces wear, high friction, and other errors especially inadequate control which can be a limiting factor to the efficiency of an industrial grinding machine operation. This research is aimed at investigating the poor performance of an industrial grinding machine as well as designing a suitable controller to improve the grinding machine operation. Moreover, an appropriate controller that ensures stable control of the grinding machine with less than 5 percent overshoot, 1.6 second settling time and a rise time less than 5 seconds to a unit step input has been achieved.

The exponential growth of digital technologies has transformed the social, economic, and administrative landscape of India. The increasing use of the internet, smartphones, online banking, e-commerce platforms, social media, and digital governance systems has enhanced connectivity, efficiency, and access to information. However, this rapid digitalization has also led to a sharp rise in cyber crime, posing significant challenges to individuals, institutions, and national security. Cyber crime in India includes a wide range of illegal activities such as online fraud, identity theft, cyberstalking, hacking, data breaches, financial scams, ransomware attacks, and cyber terrorism. This article provides a comprehensive analysis of cyber crime in India by examining its nature, causes, patterns, socio-economic impact, legal framework, enforcement challenges, and preventive strategies. The study emphasizes that cyber crime is not merely a technological issue but a multidimensional problem involving legal, social, psychological, economic, and security dimensions. It argues for a holistic approach that integrates strong legislation, advanced technological safeguards, institutional capacity building, public awareness, and international cooperation. The article concludes that combating cyber crime is essential for ensuring digital trust, economic stability, and sustainable development in India.

Background: Acute sporadic diseases commonly affect rural populations due to climatic variations, environmental exposure, and lifestyle factors. Soorapallam Village in Kanniyakumari District experiences frequent rainfall, high humidity, and sudden climatic changes, predisposing residents to acute illnesses, particularly of the respiratory tract. Methods: An observational study was conducted at the rural health centre of Sarada Krishna Homoeopathic Medical College and Hospital, Soorapallam Village. A total of 30 acute sporadic cases were selected over a one-year period. Patients of all age groups presenting with acute sporadic diseases were included. Data were collected through clinical observation and case records, noting demographic details, diagnosis, exciting causes, and homoeopathic remedies prescribed. Treatment was given based on the principle of individualization. Results: Respiratory tract infections such as acute rhinitis, acute bronchitis, acute upper respiratory tract infection, pharyngitis, and laryngitis were the most common presentations. Frequently observed exciting causes included drenching in rain, cold exposure, head bath, intake of cold drinks or ice cream, and sudden climatic changes. Paediatric and middle-aged groups were more commonly affected. Individualized homoeopathic remedies resulted in satisfactory clinical improvement in most cases. Conclusion: Acute sporadic diseases are prevalent in Soorapallam Village, with respiratory tract infections predominating. Climatic and environmental factors play a significant role, and individualized homoeopathic treatment was effective in managing acute conditions in the rural setting.

The increasing integration of social media into daily life has raised concerns regarding its potential effects on attention, mood, sleep, and lifestyle behaviours among adolescents and young adults. This community based cross sectional study evaluated patterns of social media use, screen time, and their associations with attention and cognition, mood changes, sleep disturbance, and digital behaviour patterns. Data were collected from participants aged 15 years and above using a structured questionnaire assessing screen exposure, notification checking behaviour, time immersion, psychosocial effects, and lifestyle disruption. The findings indicated that moderate to high screen time and habitual social media engagement were commonly reported and were associated with perceived reductions in attention, mood fluctuations, late night screen use, and sleep disturbance. Frequent notification checking and prolonged immersion emerged as prominent behavioural patterns. Most observed effects were mild to moderate rather than severe; however, short-term physical symptoms such as eye strain and headaches were frequently reported. Participants who reduced screen use or practiced digital breaks often reported improvements in sleep quality, focus, and anxiety levels. Overall, the study suggests that social media use is associated with subtle but widespread behavioural and lifestyle effects, highlighting the importance of addressing usage patterns and timing rather than focusing solely on total screen time.

The purpose of this study was to examine the effect of skill-specific training on the performance efficiency of under-25 Kho-Kho players in the Anakapalli district, Andhra Pradesh State. A total of [insert sample size; e.g., 60] male Kho-Kho players aged below 25 years were selected from local schools and sports clubs using purposive sampling. Participants were randomly assigned to two groups: an experimental group (skill-specific training) and a control group (regular training). The experimental group underwent a 6-week skill-specific training program, designed to enhance core Kho-Kho competencies, including quick directional movement, diving techniques, chasing accuracy, defensive positioning, and reaction speed. The control group continued with standard team practice sessions without additional skill-focused drills. Pre- and post-tests were conducted using performance measures such as sprint speed (10 m & 20 m), agility (T-test), reaction time, catching accuracy, and successful tagging rate during simulated gameplay. Statistical analysis was performed using paired and unpaired t-tests at a 0.05 level of significance. Results indicated that the experimental group showed significant improvements (p

Historically, Company Secretaries (CS) and Human Resources (HR) departments operated in silos—one focused on the letter of the law, the other on the spirit of the people. However, in the modern regulatory landscape, these roles have converged. This paper examines how the Company Secretary acts as a bridge between the Board of Directors and HR administration. By analysing compliance frameworks, employee equity schemes, and ethical governance, the research demonstrates that a CS is no longer just a minute-taker but a strategic partner in HR administration, ensuring that "people's policies" align with "corporate protocols." This paper explores the evolving intersection between corporate governance and human capital management. In the Indian regulatory context, the Company Secretary (CS) has transitioned from a traditional compliance officer to a strategic advisor. This paper examines the integration of CS functions within HR administration, specifically regarding the Companies Act 2013, SEBI regulations, and the Prevention of Sexual Harassment (POSH) Act. By focusing on an Indian regional case study, the research highlights how the CS-HR partnership mitigates legal risks and enhances corporate reputation.

The rapid integration of automation, artificial intelligence (AI), robotics, and digital manufacturing systems in the global automotive industry is transforming not only production efficiency, quality control, and operational flexibility but also the fundamental nature of workforce roles, skill requirements, and organizational structures. While automation significantly enhances productivity, process optimization, cost efficiency, and global competitiveness, its influence on employee engagement—defined as the emotional, cognitive, and behavioral commitment of employees toward organizational goals—remains complex and multidimensional. This study examines the impact of automation on employee engagement by analyzing critical dimensions such as workforce adaptation, job redesign, psychological safety, skill transformation, reskilling and upskilling initiatives, leadership support, organizational culture, and human–machine collaboration. It also considers emerging challenges including technology-induced job insecurity, resistance to change, learning anxiety, and digital fatigue, alongside positive outcomes such as job enrichment, empowerment, innovation participation, and improved workplace safety.
By integrating perspectives from industrial engineering, organizational behavior, human resource management, and digital transformation, this research aims to provide a holistic understanding of how automation reshapes employee attitudes, motivation, and performance in automotive manufacturing environments. The findings are expected to contribute to both managerial decision-making and academic discourse, supporting the development of human-centered automation strategies, sustainable workforce models, and future-ready organizational frameworks within the evolving automotive ecosystem.

The purpose of the present study was to examine the impact of a structured yogic intervention on selected fitness and physiological variables among university-level basketball players of Sri Venkateswara University, Tirupati. A total of 80 male basketball players, aged between 18 and 24 years, were selected as subjects for the study. The participants were randomly assigned to two groups: an experimental group (n = 40), which underwent a yogic intervention programme, and a control group (n = 40), which followed their regular physical activity without yogic training. The yogic intervention consisted of selected asanas, pranayama, and meditation practices, administered for 12 weeks, five days per week. Selected fitness variables such as flexibility, muscular endurance, and agility, along with physiological variables including resting heart rate, vital capacity, and blood pressure, were assessed before and after the training period. The collected data were statistically analyzed using paired t-test and analysis of covariance (ANCOVA) at a 0.05 level of significance. The results revealed that the experimental group showed significant improvements in all selected fitness and physiological variables when compared to the control group. The findings of the study indicate that regular yogic practices can be an effective supplementary training method for enhancing physical fitness and physiological efficiency in university basketball players. It is concluded that the incorporation of yogic intervention into regular training schedules may contribute positively to overall athletic performance and health.

The extraction of silicon from Afikpo beach sand and rice husk using magnesiothermic reduction reaction was studied. The raw materials (beach sand and rice husk) were initially pre-treated by drying in sunlight and later in an oven for 3 hours at 150 oC. The rick husk was thermally treated in a gas kiln at 500 oC for 4 hours to obtain rice husk ash (RHA), while the Afikpo beach sand was ground and sieved using a 100 (150 µm) and 240 (63 µm)-mesh sieves. Chemical leaching was conducted using hydrochloric acid (HCl) for 2 hours for both Afikpo beach sand and RHA, while only the RHA was alkali treated using NaOH, after which the precipitates from both samples were dried and calcined in an air-gas atmosphere at 700 oC for 2 hours. The calcined products underwent magnesiothermic reduction in a nitrogen gas atmosphere at 750 oC for 2 hours, followed by a final acid leaching using HCl to remove unreacted magnesium and residual impurities. Characterization was performed using x-ray fluorescence (XRF) and scanning electron microscope (SEM). XRF results indicated high levels of retained impurities, with silicon content measured at 51.45 % for RHA and 70.53 % for beach sand extract. SEM micrographs revealed heterogeneous and irregular shaped microstructures, attributed to incomplete impurity removal and non-uniform reduction. These findings underscore the need for optimization of purification and processing steps to improve the quality and yield of silicon from these locally sourced materials for potential use in semiconductor devices, batteries, photovoltaic cells and electronic applications.

Digoxin, a cardenolide cardiac glycoside extracted from Digitalis lanata and D. purpurea (foxglove), exemplifies the fusion of herbal tradition and modern pharmacology in treating heart failure with reduced ejection fraction (HFrEF) and atrial fibrillation (AF). Isolated in 1930, its steroidal aglycone (digitoxigenin) with trisaccharide chain inhibits Na+/K+-ATPase, elevating intracellular Ca²⁺ for positive inotropy (+20-30% contractility) and vagal AV nodal slowing (rate control, ↓20-40 bpm). The DIG trial confirmed reduced HF hospitalizations (28% RR 0.72) without mortality benefit, positioning it as GDMT adjunct (target 0.5-0.9 ng/mL). Historically, William Withering's 1785 monograph standardized "dropsy" remedies from folklore. Chemically (C₄₁H₆₄O₁₄, MW 780.94), industrial ethanol extraction from year-2 leaves (0.3-0.8% yield) yields HPLC-purified API, with amphipathic properties aiding GI absorption (renal clearance 60-80%, t½ 36-48h). Clinical uses include symptomatic HFrEF (NYHA II-IV) and sedentary AF rate control. Toxicity (narrow index) manifests as GI (nausea), visual xanthopsia, and arrhythmias (bidirectional VT), exacerbated by hypoK, renal impairment, or P-gp inhibitors; DigiFab reverses severe cases. Pharmacognosy ensures standardization via microscopy, HPTLC/HPLC (≥95% purity), and ICH stability. Ongoing biotech (e.g., DBH cloning) enhances sustainable production, while nanoparticles address bioavailability. Digoxin's legacy underscores natural product rigor, pharmacogenomics, and precision cardiology amid rising CVD burdens.

This study assessed the implementation and effectiveness of the Failure Reduction Program at Public elementary schools, specifically focusing on the extent of assessment, the level of performance of intervention strategies, and the seriousness of problems encountered by teachers. Utilizing a descriptive quantitative research design, data were collected from 100 respondents using structured survey questionnaires. Findings revealed that the program is much assessed and much performed, suggesting that assessment mechanisms and intervention strategies are actively implemented and teacher-driven. However, several much serious challenges were identified, particularly low student motivation, irregular attendance, and limited teacher training in differentiated instruction. Hypothesis testing negated the assumption that the program was only moderately assessed and performed. Based on these findings, the study concludes that the assessment processes are generally functional but would benefit from improved communication strategies and more comprehensive evaluation frameworks. While early identification and intervention are strengths of the program, gaps remain in leadership engagement, impact evaluation, and strategic alignment with the School Improvement Plan (SIP). Furthermore, the presence of persistent implementation issues highlights the need for targeted measures to address barriers affecting learner participation and instructional delivery. The study recommends structured interventions, continuous capacity-building, and stronger stakeholder collaboration to enhance program sustainability.

This study investigated teachers’ Information and Communication Technology (ICT) competence and utilisation of digital instructional tools in secondary schools in Benue State, Nigeria. Two research questions guided the study and two null hypotheses were formulated and tested at 0.05 level of significance. The study adopted a descriptive survey research design. The population comprised 4,218 teachers in public secondary schools in Benue State, while a sample of 520 teachers was selected using stratified random sampling technique. Data were collected using a structured questionnaire titled Teachers’ ICT Competence and Digital Instructional Tools Utilisation Questionnaire (TICCDITUQ). Mean and standard deviation were used to answer the research questions, while Chi-square (χ²) statistics were employed to test the hypotheses. Findings revealed that teachers possessed moderate to high ICT competence and that ICT competence significantly influenced the utilisation of digital instructional tools in secondary schools. The study recommended sustained ICT training and adequate provision of digital facilities to enhance effective teaching and learning.

This study investigated the impact of construction costs and management techniques on housing projects in Katsina Metropolis, Nigeria, prompted by issues like cost overruns and project delays. Using a descriptive survey design, data collected from stakeholders were analyzed through statistical methods. Key findings indicated that high construction material costs, labor costs, inflation, and inadequate planning significantly contribute to rising expenses in housing projects. The study indicates that rising construction costs adversely impact housing projects by raising prices, causing delays, reducing scope, and leading to abandonment. A strong negative correlation between construction costs and project performance was found, with cost planning being the most significant factor influencing outcomes. The conclusion emphasizes the need for effective cost management to counteract these effects and enhance performance. Recommendations include improved cost planning, ongoing budget monitoring, value engineering, supportive government policies, and capacity building for construction professionals to ensure sustainable and affordable housing in Katsina Metropolis.

This study investigates the impact of staff training and development on service delivery within the Katsina State Civil Service, addressing concerns about declining public service efficiency despite increased human capital investment. Utilizing a descriptive survey research design, data were gathered from civil servants through structured questionnaires and interviews, analyzed using descriptive and inferential statistics. Results indicate that regular training enhances employee skills, productivity, and service delivery. However, issues such as inadequate funding and poor training assessment limit training effectiveness. The study concludes that ongoing staff training is vital for improving service delivery and recommends continuous training programs, sufficient funding, and effective monitoring for sustainable performance.

This study examined the effects of digital learning platforms on teaching and learning in hospitality management. The research adopted a descriptive survey design and involved both students and lecturers from hospitality management programmes. Data were collected using a structured questionnaire and analyzed using descriptive statistics, Chi-Square test, and Independent Samples t-test. Findings revealed that a majority of respondents have access to digital learning platforms; however, internet connectivity, lack of training, inadequate devices, and high data costs remain major challenges. The study further established a statistically significant relationship between access to digital learning platforms and perceived learning effectiveness. Lecturers were found to perceive digital learning platforms as slightly more effective than students. The study concludes that digital learning platforms enhance teaching and learning in hospitality management when supported by reliable infrastructure and adequate digital skills. It recommends improved internet facilities, continuous training, and institutional support to maximize the benefits of digital learning platforms.

The influence of social media addiction on the mental health of students has become an area of growing concern, particularly given the widespread use of social media platforms for communication, learning, and entertainment. This study examined the prevalence of social media addiction and its impact on mental health outcomes, including anxiety, depression, stress, and self-esteem, among students in the Department of Civil Engineering, Hassan Usman Katsina Polytechnic, Katsina State. The study adopted a descriptive survey research design, and data were collected using a structured questionnaire administered to 100 students. The data were analyzed using mean, standard deviation, percentages, and t-tests, while the reliability of the instrument was confirmed with a Cronbach’s Alpha of 0.73. Findings revealed that students exhibited moderate to high levels of social media addiction, with behaviors such as restlessness without social media, spending excessive time online, and neglecting academic tasks being common. Statistical analyses indicated a significant positive relationship between social media addiction and anxiety, depression, and stress, and a significant negative relationship with self-esteem. These results suggest that excessive social media use negatively affects the psychological well-being of students, corroborating prior research on social comparison, fear of missing out, and exposure to idealized online content as mechanisms influencing mental health outcomes. The study concludes that social media addiction poses a serious risk to students’ mental health and emphasizes the need for awareness programs, counseling services, and interventions aimed at promoting responsible social media use and improving psychological well-being. The findings provide important insights for educators, policymakers, and mental health professionals in developing strategies to support students in managing social media use while maintaining positive mental health.

This study investigated the impact of digital learning platforms on teaching and learning in hospital management education. It evaluated access to these platforms, internet availability, perceived learning effectiveness, challenges encountered, and differences in perceptions between students and lecturers. Data was collected from 385 respondents through a structured questionnaire using a descriptive survey research design. The analysis incorporated descriptive statistics and inferential statistics, including Chi-square and Independent Samples t-test, at a 0.05 significance level. The study found that most respondents had access to digital learning platforms, yet faced inconsistent internet connectivity. Participants viewed these platforms as moderately to highly effective but encountered challenges such as network issues, lack of training, inadequate devices, and high data costs. Statistical analysis indicated a significant link between access and perceived effectiveness, with lecturers rating effectiveness higher than students. The conclusion emphasizes that while digital platforms positively impact hospital management education, infrastructural and socioeconomic challenges inhibit their full potential. Recommendations include enhancing internet infrastructure, providing digital literacy training, and ensuring equitable device access.

The development of biochemical solutions for waste treatment and management has emerged as an innovative and sustainable approach to addressing the growing global challenge of waste accumulation and environmental pollution. This study explores the formulation and application of biochemical methods—such as microbial degradation, enzymatic treatment, and bio-oxidation processes—for the effective management of organic and inorganic wastes. The research emphasizes the role of naturally occurring and genetically engineered microorganisms in decomposing complex waste materials into harmless or reusable end-products, thereby reducing environmental hazards and promoting resource recovery. Various biochemical agents including bacteria, fungi, and specific enzyme systems were assessed for their efficiency in treating solid, liquid, and industrial wastes under controlled laboratory conditions. Results indicate that biochemical methods are cost-effective, environmentally friendly, and capable of achieving high levels of pollutant reduction compared to conventional physicochemical techniques. Furthermore, the study highlights the integration of biochemical treatment with modern waste management practices such as composting, anaerobic digestion, and bioremediation. It concludes that the adoption of biochemical solutions offers a promising pathway toward achieving sustainable waste management, reducing greenhouse gas emissions, and promoting a circular economy.

The present study is aiming to optimize solid rocket engine performance by using epoxy as fuel and potassium nitrate as the oxidizer to understand rocket dynamics through model rocketry. The propellant mixture is being prepared based on a weight-to-weight ratio to achieve optimum output parameters, namely exit velocity, static pressure, specific impulse, and nozzle temperature. The proposed mixture is offering less mechanical complexity compared to the existing rocket motor. Simulation is being carried out using the PROPEP main software. The results are showing that the lower performance of solid propellants (as compared to liquids) is not favoring their use as the primary propulsion system in modern medium-to-large launch vehicles typically used to orbit commercial satellites and launch major space probes. However, solids are frequently being used as strap-on boosters to increase payload capacity or as spin-stabilized add-on upper stages when higher-than-normal velocities are required. Solid rockets are also being used as light launch vehicles for low Earth orbit (LEO) payloads under 2 tons or escape payloads up to 1100 pounds.

This study investigates the industrial suitability of Igo clay deposit in Edo State, Nigeria, through an integrated assessment of its geotechnical, geochemical, and mineralogical characteristics. Geotechnical analysis shows that the clay is predominantly fine-grained, with high proportions of clay and silt and negligible sand content. The liquid limit ranges from 28.5-85% with a mean value of 58.9%, while the plasticity index varies between 9.35-34.49%, indicating medium to high plasticity and cohesive soil behavior. These properties suggest good mouldability and low to moderate expansivity, characteristic of kaolinitic clays. Geochemical analysis reveals that the clay is dominated by SiO₂ and Al₂O₃, confirming its aluminosilicate nature, with moderate Fe₂O₃ content responsible for its reddish-brown colour. Loss on ignition values averaging 11.9% indicate the presence of structurally bound water and minor organic matter. Trace element concentrations (Cu, Ni, Cr, Zn, and Ba) are generally within acceptable limits for ceramic and construction applications. Mineralogical analysis using X-ray diffraction shows that quartz is the most abundant mineral, while kaolinite is the dominant clay mineral, with minor amounts of illite/muscovite, feldspars, anatase, and hematite. This mineral assemblage closely compares with clay deposits previously reported from southern Nigeria that have been successfully utilized for brick, tile, and structural ceramic production. The combined results indicate that Igo clay is suitable for bricks, roofing tiles, earthenware, and other structural ceramic products, though it is less suitable for high-grade whitewares without beneficiation.

Remuneration systems are also often under investigation as economic levers of performance, besides being efficient symbolic carriers of institutional values concerning morality. This paper investigates remuneration within a moral economy frame, analysing its structure that links to employee commitment to ethics within the Nigerian public service sector that is replete with integrity issues. It analysed cross- sectional survey data from 114 Nigerian tax officers, and it was noted that the study found 76%, 73%, and 72% of the respondents relating basic salary, fringe benefits, and leave bonuses, respectively, to increased motivation, work ethic, and commitment. Crucially, analyses underpin theories of behaviour, equity, and agency; high remuneration per se is less important compared to procedural justice and transparency. Indeed, as findings suggest, equitable remuneration may be perceived as a moral signal in support of institutional authority and civic duty. What this research uncovers is that remuneration may be perceived to support integrity and trust in public service rather than merely being a transactional tool itself. By bridging organizational theory with public administration practice, this study offers evidence-based insights for policymakers and managers seeking to enhance integrity and performance in developing country public sectors.

The rapid growth of Internet of Things (IoT) applications has intensified the demand for seamless connectivity in wireless networks characterized by dynamic channel conditions and high mobility. Conventional handover mechanisms rely on static thresholds based on received signal strength, leading to frequent unnecessary handovers, increased latency, and degraded quality of service. This research proposes an intelligent data-driven adaptive handover framework that integrates binary data transmission modeling with machine learning-based decision mechanisms to optimize handover performance. The proposed system dynamically selects appropriate transmission techniques and access mechanisms based on real-time channel parameters. Extensive simulations demonstrate improvements in bit error rate, convergence speed, handover success probability, and network throughput compared with traditional baseline methods. The results confirm the effectiveness of automated data-driven handover strategies in next-generation IoT wireless networks.

In today's rapidly evolving educational landscape, academic knowledge alone is insufficient for holistic student development. Soft skills [2], such as communication, teamwork, and adaptability, combined with emotional intelligence (EI)—the ability to understand and regulate emotions—are critical for personal and professional success. This study explores the necessity of integrating soft skills and EI into academic curricula from a student-centric perspective. Employing a comprehensive literature review and case study analysis, the research highlights the benefits of fostering these competencies and their impact on students’ academic performance, career readiness, and overall well-being. The findings suggest that structured educational interventions can enhance self-awareness, interpersonal relationships, and employability. By advocating for a curriculum that balances cognitive and emotional skills, this paper contributes to the ongoing discourse on modern education reforms.

This research paper explores the significance of integrating financial literacy into higher education curricula to equip students with essential skills for navigating the complexities of personal and professional finance. Drawing upon interdisciplinary perspectives and practical learning methodologies, the paper discusses the rationale behind incorporating financial education, outlines effective strategies for curriculum design and implementation, and examines the impact of such initiatives on students' financial knowledge, attitudes, and behaviours. Through case studies, literature reviews, and empirical evidence, the paper advocates for a holistic approach to financial literacy education, emphasizing the role of institutions, faculty, technology, and industry partnerships in fostering financial well-being and empowering tomorrow's leaders.

The rapid proliferation of mobile phones and telecommunication infrastructure has increased public exposure to electromagnetic radiation (EMR), raising concerns about its potential effects on human health. This study examines the impact of electromagnetic radiation from mobile phones and telecommunication masts on community health awareness in Katsina Metropolis, Katsina State, Nigeria. A descriptive survey research design was adopted, utilizing structured questionnaires and interviews to assess the level of awareness, perceptions, and health-related concerns among residents. Data were collected from selected communities within the metropolis and analyzed using descriptive statistical tools. The findings reveal varying levels of awareness regarding electromagnetic radiation and its possible health implications, with a significant proportion of respondents demonstrating limited scientific understanding despite frequent exposure to mobile phone usage and proximity to telecommunication masts. The study also identifies key factors influencing awareness, including educational background, access to information, and media exposure. The research concludes that although mobile telecommunication services are indispensable, public knowledge of electromagnetic radiation risks remains inadequate. It therefore recommends enhanced public sensitization, regulatory enforcement, and collaboration between health agencies, policymakers, and telecommunication providers to promote safer usage practices and informed decision-making.

This paper examines the critical link between Human Resources (HR) management practices and the manifestation of psychological distress—specifically stress, anxiety, and depression—among employees in organizational settings. Utilizing a mixed-methods approach (or suggesting one), the study investigates how deficiencies in areas like performance management, conflict resolution, organizational justice, and work-life balance policies contribute to negative mental health outcomes. The findings underscore the necessity for proactive and ethically guided HR strategies to mitigate distress and foster a psychologically healthy workplace.

The present study aimed to assess the physical fitness, physiological parameters, and mental health variables among high school girls of Chittoor District, Andhra Pradesh. A total of 120 school girls aged under 16 years (U-16) were selected using a random sampling technique from government and private high schools across the district. The study adopted a descriptive and comparative research design to examine the interrelationships among selected fitness components, physiological indicators, and mental health factors. Physical fitness variables included cardiorespiratory endurance, muscular strength, flexibility, and body composition. Physiological parameters assessed were resting heart rate, systolic and diastolic blood pressure, and lung capacity (vital capacity). Mental health variables were measured using a standardized mental health inventory covering domains such as self-confidence, emotional stability, anxiety, and social adjustment. Data were analyzed using descriptive statistics (mean and standard deviation) and inferential statistics (Pearson’s correlation and one-way ANOVA) to determine the level of association and group differences among variables. The results revealed a significant positive relationship between physical fitness and selected physiological parameters, as well as a moderate association between higher fitness levels and better mental health status. The findings highlight the importance of regular physical activity and structured physical education programs in promoting holistic development and psychological well-being among adolescent girls. The study concludes that integrated school-based fitness interventions can play a vital role in enhancing physical health, physiological efficiency, and mental wellness among high school girls in the Chittoor District.

The purpose of this study was to examine the role of combined aerobic and skill training in enhancing fitness components and game performance of 80 inter-collegiate male football players (aged 18–25 years) from Sri Venkateswara University, Tirupati. The experimental group participated in a structured training program integrating aerobic conditioning (continuous runs, high-intensity interval training) with football skill-based drills (small-sided games, ball control, passing, shooting) over a defined competitive period, while the control group continued regular football practice. Pre- and post-training assessments were conducted on selected fitness components—including cardiorespiratory endurance (e.g., VO₂max/Yo-Yo test), speed, agility, and muscular endurance—and game performance indicators such as technical execution under match conditions and tactical involvement. Research evidence supports that combined training protocols improve aerobic capacity and game-relevant physical and technical parameters more effectively than isolated training approaches in football populations, due to their simultaneous stimulation of physiological and skill-specific adaptations. Results showed significant improvements in aerobic endurance, agility, and skill performance tests following the intervention, indicating that a combined aerobic and skill training regimen can enhance both fitness components and competitive performance outcomes in collegiate football players. Based on the findings, it is recommended that comprehensive conditioning programs for inter-collegiate football incorporate integrated aerobic and skill training to optimize players’ physical readiness and on-field performance.

The dual challenges of financial exclusion and environmental degradation represent two of the most pressing issues facing sustainable development in the Global South. While these problems are often addressed in isolation, a transformative opportunity exists at their intersection. This study proposes to investigate this relationship by exploring the potential of green finance initiatives to empower unbanked and underbanked populations. This study examined how green finance initiatives can empower unbanked populations in Iringa Municipal by enhancing financial inclusion, promoting sustainable livelihoods, and strengthening resilience to economic and environmental shocks. The research employed a qualitative approach, involving 215 purposively selected participants, including unbanked individuals, smallholder farmers, community leaders, and representatives from financial institutions and NGOs implementing green finance programs. Data were collected through semi-structured interviews and focus group discussions and analyzed using thematic content analysis to identify key patterns, themes, and insights. The findings revealed that a significant proportion of unbanked populations faced financial exclusion due to limited access to financial institutions, socio-economic constraints, and lack of awareness. Green finance initiatives demonstrated considerable potential in addressing these challenges by enabling households to adopt sustainable livelihood practices, access climate-smart technologies, and improve economic stability. However, the effectiveness of these initiatives varied across participants, influenced by factors such as program accessibility, scalability, affordability, and outreach. In general, the study concluded that green finance represents a promising strategy for empowering marginalized communities, but its success depends on inclusive, well-designed interventions that deal with structural barriers to participation. These findings contribute to the broader discourse on financial inclusion, sustainable development, and climate resilience in Tanzania and similar contexts.

Background: Pilates training is a widely used conditioning method that enhances core strength, flexibility, and muscular endurance, all of which are essential for badminton performance. It is particularly effective in improving arm explosive power and flexibility, which contribute to better shot execution, injury prevention, and overall athletic efficiency. Aim: This study aimed to examine the effects of a six-week Pilates training program on selected physical fitness components, specifically arm explosive power and flexibility, among college men badminton players. Material and Methods: Thirty (N=30) college-level male badminton players from Vanavarayar Institute of Agriculture, Pollachi, Tamil Nadu, participated in the study. The players were divided into an experimental group (n=15) and a control group (n=15). The experimental group underwent a structured Pilates training program, while the control group followed their regular routine without additional training.
Statistical Applications: The dependent t-test was used to analyze pre-test and post-test differences, with significance set at 0.05. Results: The findings indicated significant improvements in arm explosive power (t = 3.49, p ≤ 0.05) and flexibility (t = 3.60, p ≤ 0.05) in the experimental group compared to the control group. Conclusions: A six-week Pilates training program positively influences arm explosive power and flexibility in badminton players, making it a beneficial addition to their conditioning regimen.

Objective: This work presents a comprehensive baseline preprocessing methodology designed specifically for deep learning models that forecast student academic outcomes using smartphone usage patterns. We introduce the Adaptive Multimodal Imputation & Normalization (AMIN) approach—a practical preprocessing pipeline that standardizes heterogeneous mobile sensor inputs before model training, bridging a critical gap in the literature where preprocessing strategies remain inconsistent across studies. Approach: Through systematic analysis of recent research spanning 2023-2025 on mobile-based student outcome prediction and preprocessing best practices, we compare conventional baseline techniques (mean and median replacement, Min-Max and Z-score normalization, temporal aggregation, and categorical encoding) with our proposed AMIN framework. We outline a comprehensive evaluation strategy utilizing multimodal datasets and establish how preprocessing decisions influence downstream model performance. Key Findings: Literature demonstrates that preprocessing methodologies account for substantial portions of performance variation across architectures. Research consistently shows that time-aware replacement strategies and modality-specific normalization substantially enhance deep learning model stability and cross-dataset transferability. The AMIN framework integrates temporal replacement awareness, modality-specific scaling, per-subject centering, and lightweight feature augmentation to produce more consistent training dynamics and superior transfer capabilities across different student populations and institutions. Contribution: Our contributions include establishing a single reproducible baseline preprocessing framework tailored to mobile phone signals in educational outcome prediction, and proposing AMIN—a straightforward, transparent hybrid preprocessing approach that unifies time-series replacement and modality-aware scaling. We provide an evaluation roadmap ensuring reproducibility and fair comparative analysis.

As the global climate crisis intensifies, carbon pricing has emerged as a central pillar of climate policy designed to internalize the external costs of greenhouse gas emissions. This paper provides a comprehensive comparative analysis of two dominant market-based instruments: carbon taxes and cap-and-trade systems, with a specific focus on their impact on electricity market performance and economic efficiency. Both mechanisms aim to correct market failures by incentivizing the adoption of energy-saving technologies and fostering a transition to a low-carbon economy. Through an examination of theoretical frameworks—such as Pigouvian taxes versus quantity controls—and empirical case studies—including the European Union Emissions Trading Scheme (EU ETS), British Columbia’s carbon tax, and California’s cap-and-trade program—the study evaluates these tools across dimensions of price certainty, environmental integrity, and administrative complexity. The analysis finds that while carbon taxes offer superior price predictability and simplicity, cap-and-trade systems provide higher environmental certainty through fixed emission limits. Furthermore, the paper highlights that market efficiency is optimized when marginal abatement costs are equalized across emitters. The study concludes that no single mechanism is universally optimal; instead, successful implementation depends on tailoring policies to local institutional capacities and economic structures. Increasingly, hybrid approaches—integrating price floors and stability reserves—offer the most viable pathway for balancing environmental objectives with electricity price stability and sustained economic growth.

The significance of effective satellite attitude control system is that it can ensure both quality and reliability of data acquisition by a microsatellite. This work presents enhancing of the dynamic response and stability of microsatellite yaw-axis attitude using intelligent based control system. In order to achieve this, the transfer function models of amplifier, actuator, and satellite structure for determining the transfer function a microsatellite yaw-axis attitude were obtained. Then a composite controller based on the integration of fuzzy logic control (FLC) algorithm and proportional-derivative (PD) algorithm called Fuzzy-PD was developed. A MATLAB/Simulink model, which was computer-based model, was developed using the mathematical models of the closed-loop control system. The MATLAB/Simulink model was initially used to conduct computer simulation of microsatellite yaw-axis attitude control system without any controller. The result obtained in terms of response to unit step input in degree indicated a rise time of 1.89 s, settling time of 3.49 s and 0% overshoot. Thus, in terms of the performance criteria defined for the system, all conditions were not met specifically the settling time. Hence, with the developed Fuzzy-PD controller added to the closed-loop network of the ACS, simulation results revealed that the control system offered rise time of 0.7 s, settling time of 1.23 s, overshoot of 0%, and steady-state error 0. Generally, simulation results revealed that the Fuzzy-PD controller met all the performance criteria. When compared to other controllers, such as, PD, FLC, integral time absolute error (ITAE) based PID (ITAE-PID), ITAE PID plus pre-filter (ITAE-PIDf), ITAE-PD, and ITAE-PD plus pre-filter (ITAE-PDf) controllers, the developed system offered the best step response performance with respect to rise time (0.7s), and overshoot 0. The significance of this work is that a composite controller with intelligent based algorithm and classical PD has been developed and offered a more smooth and stable dynamic response advantage for the microsatellite yaw-axis ACS.

This study investigates the effect of corporate ownership structure on tax planning among listed deposit money banks (DMBs) in Nigeria over the period 2015–2024. Motivated by agency theory and tax planning theory, the research examines whether managerial, institutional, foreign, public, and family ownership influence banks’ effective tax rates (ETR) as a proxy for tax planning. An ex-post facto research design was adopted, utilizing secondary data extracted from audited annual reports of nine purposively selected banks, yielding a balanced panel of 90 firm-year observations. Robust pooled ordinary least squares regression was employed to address issues of non-normality and heteroscedasticity. The results show that managerial ownership (β = –0.775, p = 0.031), institutional ownership (β = –0.309, p = 0.040), and family ownership (β = –1.932, p = 0.032) have significant negative effects on ETR, indicating more aggressive tax planning in banks where these ownership types are concentrated. Conversely, foreign ownership (β = –0.109, p = 0.464) and public ownership (β = –0.342, p = 0.303) exert negative but insignificant effects, suggesting limited influence on tax outcomes. Overall, the findings highlight that concentrated insider and institutional ownership fosters tax minimization, while dispersed public and foreign investors play a relatively passive role. The study contributes to literature by providing context-specific evidence from an emerging market and offers practical insights for regulators, investors, and policymakers concerned with tax compliance and corporate governance. It concludes that aligning managerial incentives and strengthening institutional monitoring can enhance tax efficiency, while improved regulatory frameworks are needed to activate the monitoring potential of foreign and retail investors.

Bridges are very special type of structures. They are characterized by their simplicity in geometry and loading conditions. The reinforced concrete bridges usually carried uniformly distributed dead load, vehicular live load to its surface and transfers same to the support by flexure, shear and torsion. Newly designed bridges are often skew. This is due to space constraints in congested urban areas. It can be also needed due to geographical constraints such as mountainous terrains. However force flow in skew bridges is much more complicated than straight bridges. Many recent bridges are often skewed due to space and alignment constraints in most urban areas. The use of skew bridge allows a designer to choose the best solution in roadway alignments. Staad Pro and CSI Bridge, software’s are used to Design and Analysis of skew bridges. These bridges has been affected by external factors such as weather and temperature. Substructure and foundation of the skew bridges are also affected by Velocity and Discharge of water flow. Our Project is Using Staad Pro, software to Analyzing the Skew structure and Using Staad Pro and ETABS and Leap Bridge software to Checking crack widths, distress and other Damages are Assesse

This study examined the level of motivation and manifestation of transformative leadership among teachers in Mankayan District Elementary Schools, focusing on job satisfaction, professional engagement, willingness to innovate, and leadership dimensions such as teaching effectiveness, collegial partnership, and external collaboration. Using a descriptive survey design with 43 teacher-respondents, the findings revealed that teachers are generally highly motivated, particularly in exercising autonomy in teaching strategies, fostering student learning, and embracing innovative classroom practices. Intrinsic motivators such as professional fulfillment, commitment to students, and collegial support were rated highly, while extrinsic factors such as salary adequacy, workload balance, and research participation received moderate ratings. In terms of transformative leadership, teachers exemplified practices in curriculum alignment, use of technology, and maintaining respectful and collaborative relationships with colleagues, as well as engaging parents and promoting the school’s mission to external stakeholders. However, their application of evidence-based teaching strategies, participation in mentoring, and collaboration with broader community organizations were manifested at proficient rather than exemplary levels. The overall results highlight the centrality of teacher motivation and leadership in sustaining quality education, while also identifying areas where institutional support is necessary. The study underscores the importance of strengthening professional development, research engagement, and school-community linkages to enhance transformative leadership practices. For educational administrators and supervisors, the findings provide valuable insights for designing policies and programs that balance intrinsic and extrinsic motivators, cultivate collaborative professional cultures, and reinforce partnerships, thereby advancing instructional effectiveness and organizational improvement in the basic education system.

In this work, we introduce a novel analysis framework for studying and comparing brain MRI data from non-standard animal models, such as sheep, without the use of predefined neuroanatomical priors. The proposed pipeline integrates automated MRI segmentation with graph neural networks (GNNs) to address the shortcomings of conventional approaches. Traditional neuroimaging methods typically rely on fixed anatomical atlases and struggle to generalize to developing brains or atypical species. By deriving regions of interest directly from MRI data and representing the brain as a graph, our method reduces template-induced bias and increases adaptability. Experimental results demonstrate that the GNN-based pipeline achieves higher accuracy in an age prediction task (63.22%) than a standard convolutional neural network (CNN) model (59.77%). In addition to improved performance, GNNs enhance model interpretability and effectively capture complex relationships between brain regions. These findings highlight the potential of the proposed framework as a flexible, unbiased, and interpretable solution for brain MRI analysis in developmental and non-conventional animal studies.

Objective: The current study focused on establishing the standardization of the physicochemical and phytochemical parameters of the Alstonia scholaris leaf and its aqueous formulation. Methods: Alstonia scholaris leaves are gathered, then dried in the shade, and finally extracted with demineralized water. Standardization parameters such as identification, organoleptic evaluation, ash values, loss on drying, extractive values, pH, viscosity, specific gravity, solubility, TLC profiling, phytochemical screening, microbial analysis, and total dissolved solids were assessed. To maintain reproducibility and authenticity, all experiments were performed thrice. Results: The aqueous extract was dark brown in colour and bitter in taste. The presence of alkaloids, glycosides, steroids, tannins, terpenoids, carbohydrates, saponins, and reducing sugars was indicated by TLC & was confirmed Phytochemical Screening. The total ash value was around 0.1%, pH was 7. The physicochemical and phytochemical properties of the drug were similar to those of the drug with improved Formulation (palatability). Conclusion: The analytical parameters generated may be used as the first quality control benchmarks of Alstonia scholaris s leaf and its aqueous formulation. The use of leaves is in line with the concept of ecological conservation and at the same time, phytochemical integrity is maintained. More pharmacological and clinical investigations are advised, especially for metabolic disorders.

Financial well-being has emerged as a critical component of overall personal welfare in the twenty-first century, particularly in the context of increasing financial complexities and expanding economic participation among women. Financial literacy, broadly defined by scholars such as Annamaria Lusardi and Olivia S. Mitchell as the knowledge and ability to apply financial concepts effectively, plays a pivotal role in shaping individuals’ financial behaviors and long-term security. This study examines the relationship between financial literacy and personal well-being among female college students in Chandigarh, India, with a specific focus on saving habits, investment decisions, and financial management practices.

Background: Decubitus ulcers (pressure sores) represent a significant clinical challenge, particularly in patients with limited mobility or metabolic comorbidities like Diabetes Mellitus. While conventional management focuses on local wound care and pressure relief, Constitutional Homoeopathy offers a systemic approach by stimulating the body's inherent healing vitality. Objective: This review aims to evaluate the therapeutic evidence regarding the role of constitutional remedies in accelerating the stages of wound healing, reducing secondary infections, and improving the Dermatology Life Quality Index (DLQI) in patients with decubitus ulcers. Methodology: A comprehensive search of databases including PubMed, The Integrated Health Evidence (IHE), and Google Scholar was conducted. Studies involving individualized homoeopathic prescriptions based on miasmatic background, mental generals, and physical characteristics were analyzed. The Modified Naranjo Criteria was used to assess the causal relationship between the intervention and clinical recovery. Results: Evidence suggests that constitutional remedies such as Silicea, Lachesis, and Arsenicum album not only target local tissue necrosis but also address the underlying stasis and poor vitality that prevent healing. Clinical case reports indicate a notable reduction in ulcer size and exudate levels when the remedy aligns with the patient's constitutional totality rather than local symptoms alone.

The stringency of environmental policy has become an important tool for fostering sustainable development and greening market throughout the world economy. This review paper is intended to combine the existing literature on EPS and the development of a green market, focusing on green innovation, renewable energy usage, and sustainable industrial routines. Applying a systematic and thematic review method, the paper reviews seminal contributions in the fields of environmental economics, energy policy and sustainable research to analyze how policy-led market transitions are understood in these research domains. The review suggests that strong environmental regulations are important for promoting environmental innovation, renewable energy diffusion, and environmentally sustainable manufacturing. In addition, environmental policy regimes can foster green market development indirectly through innovation incentives, regulatory schemes, and complementary policy tools. Nevertheless, the degree of influence of environmental policy stringency on the environmental quality is different in different nations because of variation in their institutional quality, technological capability, and regulatory enforcement. Overall, the study concludes that well-designed and balanced environmental policies are essential for fostering green market expansion and long-term sustainable economic growth. The paper also identifies key research gaps, including the need for integrated measurement of green market development and more comparative cross-country analyses, thereby offering important implications for policymakers and future research.

Pharmaceutical product failure poses significant risks to patient safety, regulatory compliance, and industry credibility. Failures may arise during manufacturing, analytical testing, stability studies, distribution, or post-marketing surveillance. Global regulatory authorities including the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), World Health Organization (WHO), U.S. Food and Drug Administration (USFDA), and the European Commission (EU-GMP framework) emphasize lifecycle-based quality management and risk-based Pharmaceutical Quality Systems (PQS) to minimize such failures. This review comprehensively discusses the classification of pharmaceutical product failures, root cause analysis methodologies, prevention strategies under ICH Q8–Q10, and the Corrective and Preventive Action (CAPA) framework. The article highlights the importance of integrating Quality by Design (QbD), risk management, validation, and structured CAPA within a robust PQS to ensure sustainable regulatory compliance and protection of public health.

Cancer is classified as one of the leading causes of global mortality. It has affected millions of people, often with poor prognosis. There is a need for innovative drug discovery and design as existing cancer therapies are costly and not readily available. Ayurveda and traditional medicine have utilised natural resources such as plants and trees as part of their regime to treat various illness and diseases with positive outcomes. One such tree is Moringa oleifera. Since ancient times, Moringa oleifera has been a common vegetable in many nations. It has a large number of phenolic compounds with a diverse range of biological activity. It has anticancer properties that can be exploited to create novel medications for the treatment of various malignancies. Lung cancer is one of the most common malignant tumors diagnosed worldwide. Moringa oleifera Lam. is a valuable medicinal plant native to India and Pakistan. However, the antilung cancer activity of M. oleifera alkaloid extract (MOAE) is unknown. present study aimed to evaluate the regulatory effect of MOAE on A549 cells by examination of the proliferation, apoptosis, cell cycle, and migration of cells and to elucidate the possible mechanism of action of MOAE. We tested five types of cancer cells and four types of lung cancer cells and found MOAE exerted the strongest growth inhibitory effect against A549 cells but had low toxicity to GES-1 cells (human gastric mucosal epithelial cells). Simultaneously, MOAE induced apoptosis and increased the expression of the apoptosis related proteins caspase-3 and caspase-9 in A549 cells. Furthermore, MOAE induced cell cycle arrest in the S phase through a decrease in the expression of the proteins cyclin D1 and cyclin E and an increase in the expression of the protein p21.

The integration of digital technologies in education has significantly transformed teaching and learning processes, making e-learning an essential component of teacher education programme. The present study aimed to examine the level of attitude towards e-learning among B.Ed. students and to analyze differences based on gender and locality. A normative survey method was adopted, and a stratified random sampling technique was used to select a sample of 1000 B.Ed. students from government, government-aided, and private colleges across selected districts of Tamil Nadu. The data were collected using a self-constructed and validated Attitude Towards E-Learning Scale comprising five dimensions: e-learning and teacher attitude, ICT and computer uses, e-learning and teacher anxiety, benefits from e-learning, and teacher competency. Percentage analysis and t-test were employed for data analysis. The findings revealed that the majority of B.Ed. students possessed a moderate level of attitude towards e-learning. Significant differences were found between male and female students in the dimension of e-learning and teacher anxiety, while rural and urban students differed significantly in ICT and computer uses, e-learning and teacher anxiety, and overall attitude towards e-learning. The study highlights the need for targeted interventions in teacher education to strengthen positive attitudes towards e-learning and reduce technology-related anxiety among B.Ed. students.

Optimizing school facilities has become a critical concern in contemporary education reforms aimed at improving learning quality and equity, particularly within the framework of Sustainable Development Goal 4 (SDG 4). This systematic literature review examined empirical and policy-oriented studies on the adequacy, accessibility, utilization, and challenges of school facilities, with a specific focus on intermediate learners’ perceptions. Guided by content analysis and semantic thematic analysis, the review synthesized findings from peer-reviewed international and Philippine-based literature published between 2019 and 2024, sourced from academic databases and authoritative institutional reports. The results revealed four dominant themes: perceived adequacy of school facilities, accessibility of learning spaces and basic services, perceived importance and utilization of facilities for effective learning, and persistent facility-related challenges such as overcrowding and poor ventilation. Across studies, learners’ perceptions consistently emerged as significant indicators of engagement, comfort, and perceived learning effectiveness, highlighting the limitations of purely administrative and compliance-driven facility assessments. The review further demonstrated that effective facility optimization is closely linked to instructional leadership, learner-centered management, and evidence-based supervision. These findings align with current education reform priorities, including the Philippine Education Commission II (EDCOM II), which emphasize quality-focused, learner-informed decision-making and accountability in basic education. The study concludes that integrating learner voice into facility assessment and supervision can strengthen teaching–learning conditions, support equitable resource utilization, and advance national and global education goals. The review contributes to educational administration and supervision literature by reframing school facilities as instructional resources central to learning effectiveness rather than as peripheral infrastructure concerns.

This paper provides a critical study of Dr. B.R. Ambedkar’s philosophy of social justice, emphasizing his transformative vision of a society free from discrimination and inequality. Dr. Ambedkar’s concept of social justice is deeply rooted in his fight against caste-based oppression, his advocacy for the annihilation of caste, and his unwavering commitment to liberty, equality, and fraternity as fundamental values. The study examines his critique of the social, economic, and political structures that perpetuate injustice and marginalization, particularly against Dalits and other oppressed communities. It explores Ambedkar’s strategies for achieving social justice, including constitutional safeguards, educational reforms, and the promotion of democratic principles. Furthermore, the paper evaluates the enduring relevance of Ambedkar’s ideas in contemporary society and their potential to address global issues of inequality and exclusion.

In an era defined by rapid technological change and complex societal challenges, research ecosystems have become central to knowledge-driven development. Research ecosystems comprise interconnected networks of institutions, researchers, policies, infrastructures, and societal actors that collectively support the production, dissemination, and application of knowledge. This article examines the role of research ecosystems in fostering sustainable development, with particular emphasis on their contribution to innovation, evidence-informed policymaking, and social transformation. Drawing on contemporary literature, the paper conceptualizes research ecosystems as dynamic and adaptive systems whose effectiveness depends on coordination, inclusiveness, and supportive governance structures. The study identifies key challenges confronting research ecosystems globally, including institutional fragmentation, funding instability, human capital attrition, governance constraints, and persistent inequalities in global knowledge production. These challenges often limit the ability of research to address development priorities, especially in resource-constrained contexts. To address these limitations, the article proposes strategic pathways for strengthening research ecosystems, including sustained investment in research infrastructure, capacity building for researchers, promotion of cross-sector collaboration, adoption of open science practices, and alignment of research policy with broader development goals. The article concludes that strengthening research ecosystems is essential for transforming knowledge into societal value and achieving inclusive, resilient, and sustainable development. By positioning research ecosystems as strategic development assets, the paper contributes to ongoing debates on how knowledge systems can better serve societal needs in an increasingly interconnected world.

Recent tax reforms in Nigeria represent a strategic attempt to strengthen domestic revenue mobilization, reduce dependence on oil revenues, and support sustainable economic growth. This study evaluates the effectiveness of these reforms by examining their implications for revenue performance, economic growth, institutional efficiency, and policy implementation. Drawing on recent empirical evidence and policy developments, the paper synthesizes quantitative findings on the relationship between major tax revenue components and gross domestic product, while also considering broader institutional and socioeconomic dimensions. However, the findings also reveal significant implementation challenges related to administrative capacity, compliance costs, equity concerns, intergovernmental coordination, and public trust. The study concludes that while Nigeria’s tax reforms provide a credible framework for fiscal sustainability and growth, their effectiveness depends on complementary policies that promote transparency, equity, digital readiness, and institutional accountability. The paper contributes to the literature on tax reform and development by offering evidence-based insights into how comprehensive fiscal reforms can support economic transformation in emerging economies.

Education plays a transformative role in shaping human civilization by nurturing moral, spiritual, and intellectual growth. In fifteenth-century Assam, Mahapurusha Srimanta Sankardeva emerged as a visionary reformer who not only revitalized religious life through the Neo-Vaishnavite movement but also laid the foundation for a distinctive educational philosophy. His ideas integrated spirituality, social equality, moral discipline, artistic expression, and experiential learning. This paper explores the philosophical foundations of Sankardeva’s educational thought and critically examines its relevance in the contemporary globalised world. The study adopts an analytical and descriptive methodology based on primary texts and secondary scholarly sources. The findings reveal that Sankardeva’s educational ideals—centered on character formation, inclusive learning, cultural integration, and value-based education—remain highly significant in modern educational discourse.

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has transformed the landscape of modern web development. This paper explores the integration of AI/ML APIs into the MERN stack—comprising MongoDB, Express.js, React.js, and Node.js—to build intelligent web applications that deliver dynamic, personalized, and context-aware user experiences. By leveraging external AI services such as OpenAI, Google Cloud Vision, and TensorFlow.js, developers can embed capabilities like natural language understanding, image classification, and predictive analytics into full-stack JavaScript applications. The study presents a modular architecture for seamless API integration, evaluates performance and scalability, and demonstrates real-world use cases including chatbots, recommendation engines, and smart dashboards. Results show that combining AI/ML APIs with MERN enhances interactivity, reduces development complexity, and opens new possibilities for responsive and intelligent web solutions.

Consumer choice in real-world markets frequently deviates from the rational behavior assumed by classical microeconomic theory. This study investigates how behavioral biases—specifically loss aversion, present bias, overconfidence, and status quo bias—distort consumer decisions and reduce welfare even in perfectly competitive markets. Using a behavioral utility framework and welfare comparison analysis, the paper demonstrates how biased demand functions shift equilibrium outcomes away from socially optimal consumption levels. The findings suggest that conventional models systematically overestimate market efficiency by ignoring predictable behavioral distortions. The study contributes to behavioral welfare economics by highlighting the importance of low-cost policy instruments such as nudges, default settings, and information regulation in correcting market inefficiencies, particularly in developing economies where consumer protection frameworks remain weak.

Objective: This review aims to provide a comprehensive understanding of Nabhi Marma, integrating classical Ayurvedic knowledge and modern anatomical and clinical perspectives. Data Source: Primary Ayurvedic texts, including Sushruta Samhita, Charaka Samhita, Ashtang Hridaya, along with authentic commentaries; modern anatomy textbooks; peer-reviewed journals; and online academic databases including PubMed and AYUSH portals. Review Methods: A systematic literature survey was conducted to collate historical, anatomical, physiological, and clinical information on Nabhi Marma. Classical descriptions were compared with modern anatomical correlations. Methods included comparative analysis, data synthesis, and interpretation of both primary and secondary sources. Results: Nabhi Marma, classified as a Sira Marma and Sadyapranahara, is situated at the umbilicus. It serves as the hub for Siras, Dhamanis, Prana, and Agni 1. Trauma to this marma may result in fatality or severe complications. Modern anatomy confirms its centrality, vascular significance, and embryological importance. Ayurvedic therapies like Nabhi Basti and oil massage positively influence digestive, reproductive, and psychophysiological functions.1,2,3 Conclusion: Nabhi Marma exemplifies the convergence of ancient Ayurvedic wisdom and modern biomedical understanding. Knowledge of this marma enhances surgical safety, clinical interventions, and holistic health practices, highlighting its enduring releva nce.

Maize has emerged as one of the most important cereal crops in India due to its expanding utilization in food consumption, livestock feed, and various agro-based industries. In Assam, maize cultivation is increasingly being recognized as a viable option for agricultural diversification, supported by suitable agro-climatic conditions and rising market demand. The present study examines the prospects and challenges of maize farming and marketing in Assam, with special emphasis on its growing demand in the food, feed, and industrial sectors from an economic perspective. Based on secondary data collected from government publications, agricultural statistics, and relevant research studies, the paper analyzes trends in area, production, productivity, and marketing structures of maize in the state. The analysis reveals that Assam has considerable potential for expanding maize cultivation, particularly due to the rapid growth of the poultry and livestock feed industry and increasing industrial use. However, maize farmers face several economic and institutional challenges such as limited adoption of improved production technologies, inadequate irrigation facilities, price fluctuations, lack of storage and processing infrastructure, and weak market linkages. The study emphasizes the need for appropriate policy measures focusing on strengthening extension services, improving access to quality inputs and credit, promoting value addition, and developing efficient marketing systems. Addressing these challenges can enhance farmers’ income, ensure price stability, and contribute to sustainable agricultural and agro-industrial development in Assam.

समकालीन हिंदी आलोचक जितेंद्र श्रीवास्तव अपने आलोचनात्मक लेखन में विविध समस्याओं पर विचार प्रस्तुत करते हुए कालजयी कृतियों पर केंद्रित आलोचना के माध्यम से साहित्य की गुणवत्ता और प्रासंगिकता में वृद्धि करने में सक्षम हुए हैं। अपने आलोचना-कर्म के माध्यम से वे कवियों और रचनाकारों के मूल्यांकन के साथ-साथ नई विचारधाराओं और विमर्शों के अंतर्द्वंद्वों को भी चिह्नित करते हैं। उनकी आलोचनात्मक कृतियों में कविता, कहानी, उपन्यास और सिनेमा—सभी पर सम्यक और संतुलित दृष्टि मिलती है, जो पाठक को सहज ही अपनी ओर आकर्षित करती है। स्त्री मुक्ति तथा दलित-वंचित वर्गों की सामाजिक उन्नति के संदर्भ में वे अपनी आलोचनात्मक रचनाओं के माध्यम से सामाजिक बंधनों को तोड़ने का प्रयास करते हैं। समकालीन चुनौतियों पर विचार करते हुए वे समाज की उन प्रवृत्तियों और द्वंद्वों पर भी प्रकाश डालते हैं, जो वर्तमान परिस्थितियों में उत्पन्न समस्याओं के समाधान की दिशा में सहायक सिद्ध हो सकते हैं।

Association Rule Mining (ARM) is a fundamental data mining technique used to discover hidden relationships among variables in large datasets. Despite its wide applicability, ARM often suffers from the generation of an overwhelming number of rules, many of which are redundant or influenced by noise. These issues significantly reduce the interpretability, reliability, and practical usability of mined rules. The problem becomes more critical in Numerical Association Rule Mining (NARM), where continuous attributes introduce additional complexity in preserving numeric semantics and statistical robustness. This paper presents a comprehensive survey of redundancy and noise issues in ARM, reviewing classical and contemporary approaches for rule pruning, redundancy elimination, and noise handling. Furthermore, the paper analyzes the limitations of existing interestingness measures and highlights the need for integrated penalty mechanisms. Finally, a unified Redundancy and Noise Penalty (RNP) framework is proposed as a solution to generate compact, robust, and meaningful association rules, particularly for numerical datasets. The survey aims to serve as a valuable reference for researchers and practitioners working on rule quality enhancement in data mining.

The article tries to find out the level of rural youth and rural adult awareness towards consumer protection in Cuddalore district. One objective of this study is reached through proper methodology. Sample size is 1066 in all obtained through stratified simple random sampling technique in Cuddalore district. Researcher designed questionnaire is with 5 point scale in the continuum of agreeing. Reliability of this tool is 0.88. It is identify from the analysis that the rural youth and rural adult consumers are having medium level of awareness about the consumer protection awareness with respect to gender, education qualification and occupation of the consumers. It is recommended that the consumers should involve acquiring awareness about the consumer protection movements, voluntary consumer organization should motivate the consumers about the consumer awareness and the respected State and Central Government should also conduct the awareness programmes about the consumer awareness in various dimensions at rural areas in India. It is concluded that Government must interfere and reform the Consumer Protection Centre and make suitable changes to enhance its effectiveness of creating awareness among the rural youth and rural adult consumers in Cuddalore District.

This case study examines how Meesho restructured its logistics and fulfilment architecture to address the structural cost challenges of value-focused e-commerce in India. Operating with one of the lowest average order values (AOVs) in the industry, Meesho could not rely on conventional, asset-heavy logistics models without eroding demand or incurring persistent losses. By developing an asset-light, software-orchestrated logistics network, the company leveraged underutilized capacity within India’s fragmented transport ecosystem to realign delivery costs with customer willingness to pay. The case highlights how logistics design evolved into a core strategic capability and enabled Meesho to achieve operational profitability at scale.

Legal provisions in Tanzania formally recognize gender equality in land ownership and control; however, these guarantees have not translated into secure tenure for many women living in rural areas. In practice, women’s land rights remain fragile due to ineffective implementation of land legislation and the continued dominance of customary systems that frequently marginalize women’s claims. These challenges are most pronounced in rural contexts, where limited legal literacy and constrained access to formal justice institutions restrict women’s ability to assert their rights. Within this setting, community-based paralegals have emerged as a critical mechanism for improving access to justice at the local level. This study examines the role played by paralegals in promoting and protecting women’s land rights in Mkinga District, Tanzania. Specifically, it investigates the forms of support provided to women facing land-related disputes, the methods employed by paralegals in addressing these challenges, and the implications of such interventions for women’s land tenure security.
The study utilized a cross-sectional mixed-methods design. Quantitative data were gathered from 100 respondents through structured questionnaires, while qualitative insights were obtained through key informant interviews with community paralegals, village authorities, and local government officials. The analysis focused on women’s experiences with paralegal services, dispute resolution processes, and perceived changes in their capacity to claim and safeguard land rights. The results show that paralegal engagement has a positive influence on women’s legal capacity. A majority of respondents reported increased knowledge of land rights (56 percent), greater confidence in asserting land claims (59 percent), and improved understanding of land laws and administrative procedures (62 percent). These outcomes were facilitated through legal awareness initiatives, mediation of disputes, assistance with documentation, and referrals to formal institutions. Overall, the findings highlight the importance of community-based paralegals as an effective link between statutory land governance structures and local customary systems. Institutionalizing and strengthening paralegal programs is therefore essential for enhancing women’s land tenure security and advancing gender equality in rural Tanzania.

The study examined the impact of parental demographics, survival needs, and dialect challenges on the school attendance of Indigenous Peoples (IP) learners in Sumilao District, Bukidnon. Guided by Bronfenbrenner’s Ecological Systems Theory, Maslow’s Hierarchy of Needs, and Cummins’ Linguistic Interdependence Hypothesis, the research aimed to determine how parents’ education level, employment status, and household income influence school participation; assess the effects of access to food, shelter, and financial stability on attendance; and identify the challenges posed by dialect differences in the medium of instruction. The respondents included 112 kindergarten IP learners enrolled in Licoan Integrated School, Kulasi Elementary School, Puntian Elementary School, Vista Villa Elementary School, and Ocasion Elementary School, together with their parents during School Year 2025–2026. Using total population sampling, data were gathered through a structured and validated survey questionnaire. Descriptive statistics such as frequencies, means, and percentages were employed to profile respondents and identify trends, while inferential statistics tested significant differences and relationships among variables. Findings revealed that parental education and employment status had a high influence on children’s attendance, particularly in motivating learners and ensuring provision for school needs, while household income showed a moderate influence. Survival needs, such as food and shelter, exerted moderate impacts, with school feeding programs identified as supportive interventions to encourage attendance. Financial struggles were noted as barriers but did not entirely prevent learners from attending classes, as many families sought external assistance. Dialect challenges were identified as moderate, with parents recognizing that language barriers affect learners’ confidence and comprehension but do not wholly hinder school participation. The study concludes that parental demographics, survival needs, and dialect differences collectively shape school attendance patterns among IP learners. Strengthening culturally responsive teaching, expanding feeding initiatives, and providing targeted financial support can reduce absenteeism and enhance retention. The results underscore the importance of addressing socio-economic and linguistic barriers to create equitable educational opportunities for Indigenous learners in Sumilao, Bukidnon.

This paper aims at determining non-zero distinct integer solutions to the non-homogeneous cubic equation with four unknowns x^2-y^2=z^3-w^3 by reducing it to the negative pellian equation through suitable transformations. A few relations among the solutions are presented.

This study critically examined the application of machine learning (ML) techniques for process control in automated manufacturing within the context of Industry 4.0. It adopted a systematic literature review and qualitative conceptual analysis to synthesize existing theoretical models, empirical studies, and industrial practices published from 2018 onward. The study classified supervised, unsupervised, and reinforcement learning paradigms according to their suitability for key process control tasks, including quality prediction, anomaly detection, adaptive optimization, and predictive maintenance. It identified that supervised learning techniques demonstrated high industrial viability for prediction-oriented tasks, while unsupervised learning proved valuable for early fault detection despite interpretability challenges. Reinforcement learning showed strong potential for adaptive control but faced significant barriers related to safety, data requirements, and deployment complexity. Major challenges hindering real-time industrial adoption were found to include data quality limitations, model opacity, integration with legacy control systems, and performance degradation due to process drift. Based on these findings, the study proposed a hybrid ML-based process control architecture that integrated interpretable models, deep learning, and digital twin technology within a unified framework. The architecture incorporated uncertainty quantification, human-in-the-loop oversight, and continuous learning mechanisms to enhance robustness, trust, and safety. Overall, the study provided a structured pathway for transitioning ML techniques from experimental applications to reliable, production-ready industrial control systems.

This study looks at how Solar-Powered Irrigation Systems (SPIS), which offer a dependable, affordable, and environmentally friendly substitute for diesel and grid- dependent pumps, are changing rural agriculture. Crop failure and financial instability for smallholder farmers are frequently caused by high fuel prices and power fluctuations in rural areas. The study assesses how photovoltaic (PV) arrays and water pumping technology can work together to offer a steady supply of water while lowering carbon footprints and long-term operating costs. Important conclusions indicate that although the initial expenditure is still a barrier, the payback period is much shorter than that of fossil fuel alternatives because there are no fuel costs and no maintenance. The study suggests that solar-powered solutions can double annual harvest cycles and guarantee long-term food security in off-grid agricultural areas when combined with drip irrigation and efficient government subsidies.

In order to achieve Sustainable Development Goal 4 (SDG 4), which guarantees inclusive and equitable quality education and encourages opportunities for lifelong learning for all, this conceptual and position paper examines the strategic positioning of competency-based learning (CBL) in higher education (HE). It focuses especially on encouraging creativity, workforce development, and entrepreneurial abilities. It examines the relationship between CBL and the SDG-4 tenets of equity, employability, and personalised learning pathways.The study integrates emerging conceptual frameworks and empirical evidence through an integrated review technique, global policy analysis, and educational thought leadership. How CBL structures might foster the flexible skill sets required for entrepreneurship and small business development in a developing global market is also covered. The manuscript's methodology is based on integrative devices, referencing reports on sustainable development, global education policy, and management literature. The primary findings demonstrate that CBL facilitates the creation of flexible, customised learning pathways that are relevant to labour market demands. In this approach, students get the creativity, leadership, and entrepreneurial abilities necessary for long-term economic growth.They also demonstrate how CBL promotes learner agency, flexible learning pathways, and mastery of pertinent competencies—all of which are important components of the global education agenda. By presenting CBL as a strategic lever and catalyst to bridge the gap between the HE and entrepreneurial ecosystems, promote inclusive education, and raise the calibre and applicability of HE, the paper advances educational and management study in this area. Policymakers, university administrators, and educators should use the study's observations as a guide to create CBL-compatible curriculum that support future entrepreneurs' and small company leaders' attitudes and behaviours in line with SDG-4 aims.The lack of a well examined empirical footprint of CBL and its long-term impact on entrepreneurial outcomes are among the study's limitations, as is the possibility that CBL may not be equally common everywhere at the regional and institutional level. The interdisciplinary and integrative strategy used in this research to demonstrate how CBL may be strategically used to forward the SDG-4 vision and agenda polemics in HE settings is its unique contribution. It supports the resilience and sustainability of SMEs and e-ventures by providing a foundation for additional empirical research, multi-sector collaboration, and the development of e-entrepreneurial competence.

This paper presents a comprehensive security analysis of data storage mechanisms within the Android operating system. It begins by establishing a multi-faceted definition of sensitive user data, drawing from prominent legal frameworks such as GDPR and CCPA. A detailed architectural review of Android's storage options—including internal storage, external storage, SharedPreferences, and SQLite databases—is conducted, followed by an in-depth vulnerability analysis of each. Common attack vectors, such as plaintext data exposure, SQL injection, and "Man-in-the-Disk" attacks, are dissected with reference to real-world case studies and vulnerability reports. The core of this paper is a prescriptive guide to best practices, focusing on a defense-in-depth strategy. This includes the correct implementation of modern cryptographic APIs, the foundational role of the hardware-backed Android Keystore system for secure key management, database encryption using SQLCipher, and the critical adoption of the Scoped Storage model. Finally, the paper looks toward the future, analyzing emerging threats and the applicability of advanced security paradigms like Zero Trust Architecture (ZTA) in the mobile context. The primary contribution of this work is a holistic, actionable framework for developers and security professionals to design, implement, and audit secure data storage in Android applications, thereby mitigating the risk of data breaches and ensuring user privacy.

Problem Statement Understanding
Generally the toilets/washrooms of public places Railways, Bus stand & Common Toilets are very Dirty, because the users don’t clean or flush it knowingly. So the next user faces very problem due to unhygienic, dirty and bad odour. To overcome from this situation I have an idea ..... Simply we can fit a low cost mechanical fittings in public toilets, this system automatically flush the toilet even the user don’t want to flush it and make it clean and hygienic for next users. It also reduce the water uses.

Chanakya Neeti Sutra, composed by the ancient Indian strategist and philosopher Acharya Chanakya (also known as Kautilya or Vishnugupta), represents one of the earliest and most comprehensive treatises on statecraft, governance, and administrative principles. This study examines the timeless principles of good governance embedded in Chanakya's teachings, which remain remarkably relevant to contemporary governance challenges. The research analyzes key governance concepts including ethical leadership, administrative efficiency, judicial fairness, economic management, and diplomatic relations as articulated in the Neeti Sutras. Through a systematic examination of these ancient principles, this study demonstrates how Chanakya's wisdom provides a robust framework for addressing modern governance issues such as corruption, accountability, transparency, and effective public administration. The findings suggest that integrating Chanakya's governance philosophy with contemporary democratic values can enhance administrative effectiveness and promote ethical leadership in modern political systems.

Word-of-mouth communication plays a crucial role in influencing consumer behaviour, particularly in tribal areas where interpersonal relationships and community ties are strong. The present study examines the impact of word-of-mouth communication on the buying behaviour of tribal consumers in Shirpur Taluka of Dhule District, Maharashtra. The research is based on primary data collected from 90 tribal consumers using a structured questionnaire comprising multiple-choice and Likert scale questions. The study analyses the sources of product information, level of trust in interpersonal communication, and the influence of positive and negative feedback on purchase decisions. Secondary data were collected from books, journals, government reports, and previous research studies to support the theoretical framework. Simple statistical tools such as percentages, tables, and charts were used for data analysis. The findings reveal that family members, neighbours, and shopkeepers are the most trusted sources of information, and word-of-mouth communication significantly affects the purchase decisions of tribal consumers. The study concludes that Word-Of-Mouth communication is more influential than formal advertising in tribal markets. The research provides valuable insights for marketers, policymakers, and researchers for designing effective communication strategies suitable for tribal areas.

Governance systems worldwide are facing unprecedented challenges arising from social inequality, administrative inefficiency, corruption, political polarization, and technological transformation. In response, legal and constitutional reforms have emerged as central instruments for ensuring equitable distribution of power and resources while enhancing the efficiency of governance mechanisms. This research paper undertakes an in-depth doctrinal and comparative analysis of legal and constitutional reforms as tools for achieving equitable and efficient governance. It examines the conceptual foundations of governance, traces the historical evolution of constitutional reform movements, analyses key reform domains such as electoral systems, judiciary, administrative law, decentralization, human rights, and anti-corruption mechanisms, and evaluates comparative constitutional experiences from different jurisdictions. The paper further identifies structural, political, and institutional challenges that impede reform implementation and offers policy-oriented recommendations to strengthen governance frameworks. The study concludes that sustained, inclusive, and context-sensitive legal and constitutional reforms are indispensable for democratic legitimacy, social justice, and effective public administration in contemporary societies.

The present study aimed to formulate and evaluate a polyherbal emulgel containing Centella asiatica extract and Azadirachta indica (neem) oil for the effective treatment of acne and reduction of acne scars. Centella asiatica was collected, authenticated, and subjected to methanolic extraction, followed by phytochemical screening to identify active constituents. Azadirachta indica oil was incorporated into an oil-in-water emulsion, which was then combined with a suitable gel base to prepare the final emulgel formulation. The developed emulgel was evaluated for various physicochemical properties, including appearance, pH, spreadability, homogeneity, viscosity, and stability. The formulation exhibited acceptable characteristics and good consistency, indicating suitability for topical application. The presence of bioactive compounds from both herbal ingredients suggests potential anti-inflammatory, antimicrobial, and wound-healing properties, making the developed emulgel a promising and safe herbal alternative for acne management and scar reduction.

In this work, we present a novel analytical approach that does not rely on predetermined neuroanatomical references for analysing and comparing brain MRI data from non-standard animal models, like sheep. The created pipeline overcomes the drawbacks of conventional neuroimaging approaches by combining automated MRI segmentation techniques with graph neural networks (GNNs). Traditional methods typically rely on set anatomical atlases, which frequently don't adjust to rare species or developing brains. The suggested approach reduces template-related bias and enhances generalisation by directly identifying regions of interest from MRI scans and modelling the brain as a graph structure. In experiments, the GNN-based model performs better than a traditional convolutional neural network (CNN) model in age prediction tasks, with an accuracy of 63.22% versus 59.77%. Additionally, the application of GNNs facilitates efficient learning of intricate interregional brain interactions and improves model transparency. Additionally, improved biological understanding of developmental patterns and structural connectivity is supported by the suggested method. Overall, these findings show that the framework provides a reliable, flexible, and understandable alternative for brain MRI analysis in studies using non-traditional animal models and developmental research.

For a bed rest patient proper an timely nursing medical support is very important. In medical or home the changing of diaper and empting/changing of Uro bag is a important as well as irritating job. For this purpose the attendant also suffer a lot with the patient. He/she has to alert all the time. But its is a common issues everywhere.

Urban air pollution remains one of the most pressing environmental and public health challenges of the 21st century. Rapid urbanization, industrial growth, and motorization have exacerbated the concentration of harmful atmospheric pollutants in cities worldwide. These elevated levels of pollutants are linked not only to environmental deterioration but also to increased morbidity and mortality among exposed populations. This review synthesizes current research on urban air pollution control strategies, monitoring technologies, predictive modeling, and policy interventions, drawing upon 20 high-quality journal articles and reports. Key themes include the integration of advanced sensor networks and machine learning for air quality monitoring, policy frameworks for pollution mitigation, and the role of smart-city technologies in adaptive control systems. The review identifies gaps in current research and highlights future directions, including the need for more granular data, real-time control mechanisms, and community-based participatory approaches.

Chronic spinal cord issues often manifest as complex, radiating symptoms that affect both upper and lower extremities. This paper explores the clinical presentation of right-sided limb pain, difficulty in prolonged standing, and walking limitations (claudication). By examining the intersection of spinal stenosis, disc herniation, and secondary conditions like adhesive capsulitis (frozen shoulder), we evaluate the efficacy of surgical versus physiotherapeutic interventions.

Type 2 Diabetes (T2D) represents a global health crisis of unparalleled scale, characterized by its rising prevalence, significant morbidity, and substantial economic burden. The inherent complexity of T2D management, which requires continuous monitoring and multifaceted intervention, often strains traditional healthcare models, leading to therapeutic inertia and suboptimal outcomes. Clinical Decision Support Systems (CDSS) have emerged as a promising tool to augment clinical practice, yet their early iterations were limited by static, rule-based architectures. The integration of Artificial Intelligence (AI) and predictive algorithms is catalyzing a paradigm shift, transforming CDSS from simple alerting mechanisms into dynamic, data-driven, and personalized intelligent assistants. This paper provides a comprehensive review of the application of AI-powered CDSS in T2D management. We begin by outlining the clinical and operational challenges of T2D that necessitate advanced decision support. We then trace the evolution of CDSS and delve into the technical foundations of relevant AI and machine learning (ML) methodologies, including supervised, unsupervised, and deep learning approaches. The core of the paper synthesizes current applications across four key domains: (1) predictive risk stratification for disease onset and complications; (2) personalized glycemic control and treatment optimization; (3) early and automated detection of diabetes-related complications; and (4) enhancement of patient engagement and self-management. A critical analysis of the significant challenges hindering widespread clinical adoption is presented, encompassing data quality issues, algorithmic bias, the "black box" problem of interpretability, workflow integration, and regulatory/ethical considerations. Finally, we explore promising future directions, including federated learning, causal AI, and the concept of digital twins, and conclude with recommendations for researchers, clinicians, and policymakers to responsibly translate this transformative technology into improved, equitable, and person-centered diabetes care.

Human resources will be forced to labour under more stressful situations unless and until the organization delivers the best HRMP to its employees, resulting in poor performance and job satisfaction. This research investigates the impact of human resource management practices on employee performance and job satisfaction. A standardized questionnaire was used to interview 229 volunteers from various organizations. The topic is investigated using chi square in this research. The results demonstrate that a variety of dependent factors, such as age, education, and current work experience, have a significant moderating effect on the relationship between HRM practices and employee performance. When mediation is employed, job satisfaction is unrelated to HR management practices.

Women constitute a significant proportion of India’s agricultural workforce, contributing approximately 80% of rural labour in farming-related activities. However, their contributions in promoting sustainable and eco-friendly agricultural practices remain underrecognized in mainstream discourse. This paper examines the pivotal role of women farmers in advancing ecological agriculture in Madhya Pradesh and Rajasthan, two agrarian states where women-led initiatives are transforming agricultural landscapes. Through a comprehensive analysis of current practices, case studies, government initiatives, and grassroots movements, this research demonstrates that women farmers are not merely participants in agriculture but are emerging as leaders and innovators in promoting organic farming, natural farming, water conservation, and biodiversity preservation. The paper explores the mechanisms through which women farmers adopt and promote eco-friendly practices, the socioeconomic benefits they derive, and the institutional and policy frameworks that support their endeavours. By examining both successes and challenges, this study highlights how empowering women farmers is essential for achieving sustainable agriculture and climate resilience in India.

Osteoarthritis (OA) remains the most prevalent degenerative joint disorder globally, characterized by the progressive breakdown of articular cartilage. This paper examines the multifaceted problems faced by patients, including chronic pain, limited mobility, and psychological distress. While conventional treatments (pharmacotherapy and physical therapy) and modern interventions (biologics and regenerative medicine) provide relief, early and accurate diagnosis remains a challenge. We propose a Deep Learning framework utilizing Convolutional Neural Networks (CNNs) to automate the grading of OA severity via the Kellgren-Lawrence (KL) scale. Utilizing a Kaggle-sourced dataset from the Osteoarthritis Initiative (OAI), the proposed model demonstrates superior accuracy in multi-class classification, offering a scalable tool for clinical decision support.

The integration of artificial intelligence in healthcare has demonstrated remarkable potential for improving diagnostic accuracy, treatment planning, and patient outcomes. However, the widespread adoption of AI-based decision support systems faces significant challenges related to trust, transparency, and accountability. This article explores the critical role of Explainable AI (XAI) in developing trustworthy healthcare decision support systems. We examine the fundamental principles of XAI, current methodologies for achieving explainability, regulatory and ethical considerations, implementation challenges, and future directions for creating AI systems that healthcare professionals can trust and patients can rely upon.

The homogeneous cubic equation with four unknowns represented by the Diophantine equation x^3+y^3+2(x+y)(x-y)^2=22zw^2 is analyzed for its patterns of non-zero distinct integral solutions.

This study examined the relationship between liquidity management and the financial performance of construction and real estate companies listed on the Nigerian Exchange. Adopting a correlational research design, the study focused on how liquidity management proxies working capital ratio, quick ratio, cash ratio, and operating cash flow ratio influence firm performance, measured by profit after tax. Secondary data were extracted from the published financial statements of five selected listed construction/real estate companies over the study period, yielding a total of 50 firm-year observations. Data were analyzed using descriptive statistics and multiple regression techniques with the aid of SPSS. Descriptive results showed that profit after tax (log-transformed) had a mean value of 6.31 with a standard deviation of 0.89, while the average working capital ratio and quick ratio were 2.25 and 2.12 respectively, indicating moderate liquidity levels among the firms. The regression results revealed that none of the individual liquidity proxies had a statistically significant effect on financial performance at the 5% level. Specifically, working capital ratio (t = 1.257, p > 0.05), quick ratio (t = −1.365, p > 0.05), cash ratio (t = 1.810, p > 0.05), and operating cash flow ratio showed insignificant relationships with profit after tax. However, the joint effect of the liquidity variables was statistically significant, as indicated by an F-statistic of 3.209 (p = 0.021). The model explained approximately 22% of the variation in financial performance (R² = 0.222). The findings suggest that while liquidity management practices jointly influence the performance of construction companies in Nigeria, individual liquidity indicators do not exert a significant standalone effect. The study concludes that effective liquidity management remains important but may not directly translate into improved profitability without complementary operational and strategic efficiencies. It recommends improved cash planning, budgetary control, and integrated financial management practices to enhance the performance of construction and real estate companies in Nigeria.

The convergence of big data, advanced analytics, and precision medicine is fundamentally transforming healthcare delivery from a one-size-fits-all approach to highly individualized patient care. This article examines how healthcare data analytics enables personalized medicine and enhances clinical decision support systems across the continuum of care. Through integration of genomic data, electronic health records, real-time monitoring, and machine learning algorithms, healthcare providers can now tailor treatments to individual patient characteristics, predict disease progression with unprecedented accuracy, and receive intelligent recommendations at the point of care. This comprehensive analysis explores the technological foundations, clinical applications, implementation challenges, and future directions of analytics-driven personalized medicine and decision support, demonstrating how data science is revolutionizing clinical practice to improve patient outcomes while advancing the efficiency and effectiveness of healthcare delivery.

This paper presents a structured framework for developing an AI-powered research assistant that operates on a cloud-based knowledge fusion model. The system aims to simplify academic research by integrating information from multiple digital sources, processing it through advanced Natural Language Processing (NLP), and generating intelligent, real-time responses. Organized into modular components such as data ingestion, knowledge fusion, semantic analysis, and query handling, the architecture ensures high scalability and reliability. By leveraging machine learning techniques, the platform can summarize content, extract insights, and support decision-making for students and researchers. Core features such as role-based access, secure cloud storage, and adaptive learning enhance usability and maintain data integrity. The solution promotes efficiency, accuracy, and accessibility, offering institutions a modern approach to managing research information and assisting users throughout their academic workflows.

The Euphorbiaceae represents1 almost all habits of growth, and exhibits a high degree of adaptability to varying environments. The species of this family are distributed all over the world, except in Arctic and Antarctic regions. About half of the species (4000) inhabit equatorial America; they are much rarer in temperature America. In the old world they are more abundant in the Mediterranean region and in temperate Asia then between the tropics. The members of the family2 secrete a very acrid milky juice, varying in strength with the species, the organ of the plant and the climate. The latex present in many of the species is of particular importance in the genus Hevea and a number of other rubber producing genera. In some, the milky juice is one of the most deleterious of poisons and in others its acridity is so far neutralized by mucilage and resins as to reduce it to a simple purgative and diuretic. Some species are slightly narcotic- acrid others aromatic. The Albumin usually contains fixed bland oil, without the acridity which is found in the embryo and the integuments of the seed. It is to a liquid resin and a volatile principle that all the properties of the spurgeworts are due. They are thus the strongest in alcoholic tinctures, but are dissipated by the application of heart. Manihot offers a remarkable example. There is scarcely a more poisonous juice than this yet the action of fire converts the plant into very wholesome food. A general survey of phytochemicals in Euphorbiaceae has been given in Table.1.

In an era of escalating healthcare costs and increasing pressure to deliver high-quality patient care, hospitals worldwide are turning to data analytics as a strategic tool for operational optimization. This article explores the transformative role of healthcare data analytics in enhancing hospital resource utilization and reducing operational costs. By examining key applications including predictive modeling, real-time resource tracking, patient flow optimization, and supply chain management, this analysis demonstrates how data-driven decision-making enables healthcare organizations to achieve significant cost savings while maintaining or improving clinical outcomes. The article also addresses implementation challenges, presents case studies of successful analytics deployments, and discusses future trends that will shape the evolution of healthcare analytics in resource management.

Nigeria faces a mounting plastic waste crisis, generating over 32 million tons of solid waste annually, with plastics comprising a growing proportion that overwhelms inadequate landfills, open dumps, and natural ecosystems. Conventional disposal methods like open burning release toxic dioxins and contribute to environmental degradation, while imported synthetic catalysts for advanced waste conversion remain prohibitively expensive. This comprehensive review explores Nigerian kaolin—an abundant, locally sourced clay mineral—as a cost-effective alternative for catalytic pyrolysis of polymer wastes, transforming non-recyclable plastics (HDPE, LDPE, PP, PS, PET) into valuable pyrolytic fuels. Derived primarily from kaolinite (Al₂Si₂O₅(OH)₄), Nigerian kaolin exhibits favorable physicochemical properties including 45-55% SiO₂, 25-35% Al₂O₃, moderate Brønsted/Lewis acidity, and layered structure that supports zeolite Y synthesis and direct catalytic applications. Major deposits span states like Abia, Anambra, Bauchi, Edo, Ekiti, and Katsina, offering vast reserves for industrial utilization. The review details kaolin's transformation into metakaolin via calcination (500-700°C), enhancing surface area (10-30 m²/g → higher) and catalytic activity for pyrolysis at reduced temperatures (350-500°C vs. 450-600°C thermal), achieving 60-75 wt% liquid yields with gasoline/diesel-range hydrocarbons (40-45 MJ/kg calorific value). Environmental benefits include landfill diversion, lower emissions than open burning, and char-based carbon sequestration, while economic advantages encompass 25% catalyst cost savings, job creation across waste-to-fuel value chains, and reduced fossil fuel imports. However, challenges persist: deposit variability requiring beneficiation, catalyst deactivation (coke deposition, pore blockage), scaling from bench to industrial reactors, feedstock contamination from real-world mixed plastics, and policy gaps hindering commercialization. Future research directions emphasize advanced catalyst modifications (metal doping, hierarchical porosity), process optimization (fluidized-bed reactors, kinetic modeling), feedstock flexibility (co-pyrolysis with biomass), product upgrading for fuel standards compliance, comprehensive life cycle assessments, and pilot demonstrations. Supportive policies—tax incentives, extended producer responsibility, and national standards—are essential. Nigerian kaolin-based pyrolysis represents a circular economy cornerstone, converting waste liabilities into sustainable energy assets while advancing environmental protection and energy security.