This article explores the increasing concern about romantic boundary violations between educators and learners in both high schools and higher education settings. The aim is to develop a conceptual and analytical understanding of how power asymmetry, organisational culture, and social normalisation contribute to these relationships. The study is based solely on a qualitative document review of existing academic literature, policy reports, and legal frameworks. This approach provides a rigorous and ethically non-intrusive analysis that does not involve human participants. The article finds that educator–learner relationships remain a persistent problem because institutional cultures often blur boundaries, normalise inappropriate behaviour, and fail to enforce safeguarding policies consistently. Recent research also highlights that institutional silence, fear of reporting, and patriarchal norms often reproduce vulnerabilities that learners experience. The analysis in this article shows that the normalisation of boundary violations is not merely an individual behavioural issue but a systemic problem linked to organisational culture and weak accountability structures. The findings contribute to a deeper theoretical understanding of educator misconduct and point to the need for more robust oversight, safeguarding mechanisms, and professional ethics training in schools and universities. The article concludes that addressing these violations requires sustained institutional reform, a culture of accountability, and stronger preventative frameworks grounded in student protection and public trust.

In recent years, universities across both developed and developing contexts have observed a notable decline in the number of graduates progressing directly into postgraduate academic studies. Instead, a growing proportion of graduates are opting for professional qualifications in fields such as teaching, law, accounting, and other practice-oriented professions. This shift raises important questions about the changing value of academic postgraduate education in contemporary labour markets. The purpose of this study is to explore the factors influencing graduates’ decisions to favour professional qualifications over postgraduate academic studies. Using a descriptive qualitative research design based on secondary data analysis, the study synthesizes recent policy reports, graduate employment statistics, and peer-reviewed literature published within the last five years. The findings indicate that employment uncertainty, rising costs of postgraduate education, delayed economic returns, and the perceived labour market relevance of professional credentials are central drivers of this trend. The study also finds that professional qualifications are increasingly viewed as clearer pathways to employability, occupational licensing, and income stability. These preferences are reinforced by employer signalling practices and broader shifts toward skills-based hiring. The study contributes to higher education and labour market literature by highlighting how structural economic pressures and changing conceptions of career security are reshaping postgraduate participation patterns. The paper concludes by arguing that universities must rethink the positioning, design, and labour market articulation of postgraduate academic programmes if they are to remain relevant in an increasingly professionalised and credential-driven economy.

The Indian Grain Logistics Emergency Support Base Project is located within the Lahuradewa Lake flood detention areas of the Ganges River Basin, it is necessary to assess its flood impact and mitigate flood disaster losses. Taking the Indian Grain Logistics Emergency Support Base Project as a case, this research employed a two-dimensional planar mathematical model and a three-dimensional seepage model to analyze and demonstrate the bidirectional influence between the Ganges River floods and the support base project, as well as the corresponding measures. The results indicate that, on one hand, the project occupies 0.0005 % of the effective flood storage capacity of the detention area. The impact of the construction project is minimal on the flow rate, duration, water level, and flow field processes during flood diversion and retreat. However, project construction has a certain effect on the seepage stability of flood control structures. On the other hand, the impact of the Ganges River floods is relatively small on the project in terms of scouring and sedimentation. Nevertheless, during flood diversion operations, the project area submerges, with water depths ranging from 2.55 m to 3.11 m. Based on these findings, the formulation of flood emergency response plans should be considered during both construction and operational periods. It can provide decision-making support, engineering planning, construction, and management references for grain storage projects and other infrastructures within flood detention areas to address natural disasters induced by floods.

This study characterizes the technical specifications and operational variability of large pelagic purse seine components used at the Archipelago Fishing Port (PPN) Pekalongan, Central Java. Eight purse seine units were analyzed through direct measurement, observation, and in-depth interviews. Results indicate that nets are constructed from polyamide (PA) with mesh sizes ranging from 2 inches (50.8 mm) in the bunt to 4 inches (101.6 mm) in the wings and body, and denier sizes from d12 to d30, corresponding to sinking forces of 2.69–8.14 kgf per 100 m. All ropes are polyethylene (PE) with diameters from 10–60 mm, with the ground rope consistently 10% longer than the head rope. Two float types were used: DS2 (1.163 kgf buoyancy) on wings/body and YQE-20 (1.760 kgf) on the bunt, contributing total buoyancy between 2,868.68–3,530.19 kgf. Sinkers were made of lead, with two weight classes (0.211 kg and 0.243 kg), and total sinking forces ranged from 1,008.35–1,327.66 kgf. Rings were stainless steel, providing additional sinking force of 0.366–0.537 kgf each. Significant inter-vessel variations were observed in component dimensions and quantities, reflecting adaptive, experience-based designs. The findings provide a technical baseline for optimizing gear efficiency, improving catch performance, and supporting sustainable purse seine fisheries management in Indonesian waters.

Human–wildlife conflict (HWC) continues to undermine biodiversity conservation and rural livelihoods in developing countries, particularly in communities bordering protected areas. This study evaluates the effectiveness, adoption, and perceived performance of community-based human–wildlife conflict mitigation strategies in Msaranga and Mahorosha villages, located along the eastern boundary of Kilimanjaro National Park (KINAPA), Tanzania. A mixed-methods research design was employed, integrating household surveys (n = 60), key informant interviews, focus group discussions, direct observation, and physical site visits. The findings indicate that local communities employ a range of mitigation measures, including physical barriers (trenches, stone walls, thorn hedges), chilli pepper fences and guiding fields, scaring and chasing, visual deterrents, and guard dogs. Physical barriers were perceived as the most effective intervention (41.7%), followed by Mauritius thorn hedges (37.9%), scaring and chasing (21.7%), chilli-based deterrents (15.3%), visual deterrents (5%), and electric or natural fences (4.3%). Although electric fencing was widely perceived as effective, it was rarely adopted due to high installation and maintenance costs. The study concludes that while local communities demonstrate substantial adaptive capacity in mitigating HWC, the effectiveness and sustainability of these measures are constrained by financial limitations, labour intensity, ecological pressures, and weak institutional support. Strengthened collaboration between conservation authorities and local communities, enhanced conservation education, and targeted technical and financial assistance are essential for promoting sustainable human–wildlife coexistence in the eastern Kilimanjaro landscape.

Liver abscess (LA) remains a significant clinical challenge characterized by a purulent collection in the liver parenchyma. Historically associated with high mortality, advances in imaging and minimally invasive procedures have significantly improved patient outcomes. This paper examines the primary classifications—pyogenic and amebic—and discusses their etiology, ranging from biliary tract infections to parasitic invasions. We explore early clinical indicators, the "gold standard" of modern treatment involving percutaneous drainage, and the emerging integration of Artificial Intelligence (AI). AI models, particularly deep learning and radiomics, are proving pivotal in automating detection and differentiating between abscess types, thereby optimizing the clinical decision-making path.

This study investigates how artificial intelligence (AI) can accelerate the transition toward a circular economy by optimizing resource use, enhancing supply chain transparency, and promoting innovative, sustainable business models. Through concrete applications such as intelligent waste sorting and reverse logistics, AI contributes to reducing losses, improving traceability, and supporting innovative circular practices. A survey conducted with 65 Tunisian SMEs confirms that, when adoption is supported by organizational and institutional factors, AI improves environmental performance and helps achieve sustainable development goals.

Background: Sexually transmitted infections (STIs) remain a major public health concern, particularly among young adults in tertiary institutions. Adequate knowledge and positive attitudes toward STI prevention among health sciences students are essential, as they are future healthcare providers and key agents of health promotion. Objective: This study assessed the knowledge and attitude to sexually transmitted infections among students in a College of Health Sciences in a tertiary institution in Nigeria. Methods: A cross-sectional descriptive study was carried out using a semi-structured, self-administered questionnaire among 394 undergraduate students in a College of Health Sciences selected through a multistage sampling technique. Data were analyzed using SPSS version 25. Statistical significance was set at p < 0.05. Results: The mean age of respondents was 21.07 ± 2.46 years, with most aged 16–25 years. More than half of the respondents (55.8%) were female. Overall, 55% of the respondents had good knowledge of STIs, 42% had fair knowledge, and 3% had poor knowledge. HIV (93.9%), gonorrhea (91.4%), and syphilis (87.1%) were the most commonly identified STIs. Most respondents correctly identified unprotected sexual intercourse (94.4%) and multiple sexual partners (85.0%) as major routes of transmission. A large proportion (86.0%) knew that STIs can be asymptomatic, and 76.1% believed that STIs are preventable. Attitudes toward STI prevention were largely positive, with all the respondents demonstrating an overall positive attitude. No significant association was found between socio-demographic characteristics and level of knowledge of STIs (p > 0.05). Conclusion: Health sciences students demonstrated generally good knowledge and positive attitudes toward STIs however, misconceptions regarding prevention and transmission persist. Continuous, evidence-based sexual health education and stigma-reduction strategies are therefore recommended to strengthen STI prevention efforts in tertiary institutions.

The high rate at which renewable energy systems are developed has escalated the necessity of comprehension of integrated planning frameworks clearly factoring in on climate variability and physical climate processes. Conventional energy planning models tend to adopt climate factors as exogenous or independent variables, which restrict such models to be able to adopt the long-term sustainability amid altering climatic conditions. The research will hypothesize a proposal of an integrated climate physics modelling to conduct sustainable renewable energy planning by integrating climate sensitive indicators and use of qualitative primary data, supportive of a statistical analysis. The study aims at capturing the impact of the dynamics of climate on renewable energy performance, planning decision and sustainability outcomes. Primary qualitative information is gathered due to the structured interviews with energy planners, climate analysts, and policy experts using elicitation of experts. These observations are coded and then statistically and decision-support analyzed to establish prevailing climate-energy interaction patterns. The suggested framework will connect climate physics variables and renewable energy planning indicators and will make a more resilient and adaptive decision-making process. The findings indicate that climate-physics consideration can be integrated with renewable energy planning to increase the resilience of the system, improve its sustainability objectives, and mitigate the risk of long-term planning. The study is a new interdisciplinary solution which helps in the gap between climate science and energy system planning and the practical advice to policymakers and planners who want to create climate-resilient renewable energy solutions in the era of uncertainty.

This study looked at how quality assurance practices (QAP) and information and communication technology (ICT) use can help predict self-directed learning (SDL) skills among distance learners in Southwest Nigeria. The study used a correlational survey approach based on Garrison's Community of Inquiry framework and Knowles' theory of andragogy. A total of 420 undergraduate students from certain National Open University of Nigeria (NOUN) study centres took part. We used a systematic, validated questionnaire including scales on QAP, ICT use, and SDL abilities to gather data. We employed descriptive statistics, Pearson correlation, and multiple regression analysis to look at the data. The results showed that there was a strong positive link between QAP and SDL skills (r = .52, p < .001) and between using ICT and SDL skills (r = .56, p < .001). Also, QAP and ICT use together predicted SDL skills, explaining 46% of the difference (R² = .46, F(2,417) = 88.92, p < .001). ICT use (β = .42, p < .001) was a little better at predicting than QAP use (β = .37, p < .001). These results show how important it is for institutions and technology to help remote learners develop SDL skills. The study finds that improving quality assurance systems and encouraging the use of ICT in a smart way are both very important for developing independent learning skills in open and distance education. Suggestions are offered for changing institutional policies, improving digital infrastructure, and starting professional development programs that will help SDL outcomes. The results add to the body of research on learner support and digital transformation in ODL systems.

Oil exploration and exploitation in Nigeria have a long history, yet they have left significant environmental footprints, impacting ecosystems and human health in affected regions. This study investigated the effects of petroleum exploration and production activities on the physicochemical and microbiological quality of the River Ethiope, Niger Delta, with the aim of characterizing its geochemistry and assessing water quality for human use. Thirteen water samples were collected from seven communities along the river (Sapele, Okpara, Igun, Abraka, Obiaruku, Ebedei, and Umutu/Umuaja) and analyzed for key parameters, including pH, conductivity, total dissolved solids (TDS), total hardness, turbidity, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), sulphate, phosphate, nitrate, oil and grease, and coliform count. The results were compared with World Health Organization (WHO, 1993/1996) standards for drinking water. Most physicochemical parameters, including conductivity, TDS, hardness, salinity, calcium, magnesium, nitrate, phosphate, and BOD/COD values, fell within WHO permissible limits. However, deviations were observed in pH, turbidity, DO, oil and grease, and coliform counts, indicating contamination from oil spillage, gas flaring, and anthropogenic activities. Notably, the communities of Umutu/Umuaja, Obiaruku, and Sapele were more severely impacted. The study highlights that while portions of the River Ethiope remain suitable for irrigation and domestic use, the water is unsafe for direct consumption without treatment. It underscores the urgent need for effective environmental management, continuous monitoring, and public awareness campaigns targeting oil operators, transporters, and local communities. Regulatory enforcement, pollution mitigation, and reduced reliance on crude oil as a primary energy source are recommended to safeguard water quality and protect aquatic ecosystems.

Climate-induced migration represents one of the most pressing yet underappreciated global crises of the twenty-first century. As climate change accelerates, millions of people worldwide are being forcibly displaced due to rising sea levels, extreme weather events, droughts, and environmental degradation. This comprehensive review paper synthesizes current knowledge on climate-induced population displacement, examining the social, economic, and political consequences for both migrants and receiving communities. Drawing on 30+ contemporary academic sources and empirical studies from 2017-2025, this paper explores the multifaceted dimensions of climate migration, including the push- pull dynamics of environmental stressors, the gendered vulnerabilities of displaced populations, livelihood adaptation strategies, and the critical governance gaps in international and national policy frameworks. The review identifies that while climate migration is increasingly recognized as an adaptation strategy, displaced populations remain largely excluded from formal decision-making processes, left vulnerable to exploitation, trafficking, and resource scarcity. The paper argues that addressing climate migration requires integrated, transnational governance mechanisms that recognize the intersecting vulnerabilities of women, marginalized communities, and least-developed countries. Research gaps identified include the need for comprehensive longitudinal studies on livelihood outcomes of climate migrants, nuanced understanding of the climate-conflict nexus in migration decision-making, and policy frameworks that center the agency and rights of displaced populations.

Composite materials are widely used now a days due to their superior strength, hardness, and light weight nature compared to conventional materials. This study focuses on the development of a hybrid composite using carbon fiber reinforced polymer and jute fiber, fabricated through the hand layup technique. Carbon fiber provides exceptional tensile strength and stiffness, while jute fiber a natural and cost-effective reinforcement, enhances the composite sustainability. The fabrication involves layering four jute and three carbon fiber plies with its corresponding hardening polyester resin in 10:1 ratio, ensuring proper adhesion and minimizing defects such as air bubbles. The mechanical properties of the hybrid composite are assessed through tensile and flexural tests to evaluate its strength and durability. Furthermore numerical simulations using ANSYS Software are conducted, and the results are compared with theoretical calculations to validate the composite structural performance. This research aims to explore the potential of CRFP-Jute hybrid composites for aerospace, automotive, and structural applications, where a balance between strength, weight reduction, and sustainability is essential.

Career-based entrepreneurship has emerged as a significant alternative for Indian youth, primarily driven by the lack of formal employment prospects and the dynamic economic scenario. However, the motivation for entrepreneurship is not solely dependent on economic aspects, such as the need for income and job scarcity, but is also profoundly influenced by socio-cultural factors like family background, social norms, and educational environment. This paper adopts an interdisciplinary approach, drawing on insights from economics, psychology, and cultural studies, to investigate the development of entrepreneurial desires in Indian youth, mediated by both economic motivation and cultural discourses. By synthesizing evidence from Global Entrepreneurship Monitor (GEM) reports and reputable research studies, the paper elucidates the interplay between material conditions and social meanings in shaping youth entrepreneurial intentions. Finally, it discusses policy implications aimed at encouraging inclusive and sustainable youth entrepreneurship in India.

Background: Uterine leiomyoma is the most prevalent benign tumour of the female reproductive tract and a major contributor to gynaecological morbidity, with potential adverse effects on fertility. Although many women remain asymptomatic and are diagnosed incidentally during clinical examination or ultrasonography, a significant proportion develop symptoms that necessitate intervention. Management options may be medical or surgical and are influenced by factors such as age, parity, reproductive intentions, fibroid characteristics, and the impact of symptoms on quality of life. Objective: To determine the prevalence, sociodemographic characteristics, clinical presentation, and surgical outcomes of women managed surgically for uterine leiomyoma. Methods: This was a retrospective descriptive study of women who underwent surgical management for uterine leiomyoma at the Federal Medical Centre, Yenagoa, Bayelsa State, between 1 January 2018 and 31 December 2020. Relevant data were extracted from hospital records and analyzed using descriptive statistics.
Results: Out of 1,373 gynaecological admissions during the study period, 160 cases were due to uterine leiomyoma, yielding a prevalence of 11.7%. A total of 380 gynaecological surgeries were performed, of which 98 (25.8%) were for uterine leiomyoma. The condition was most frequently observed among women aged 30–39 years (46.9%) and nulliparous women (37.7%). The mean age of the patients was 38 years, with a mean parity of 1. Heavy menstrual bleeding (40.1%) and abdominal swelling (35.2%) were the predominant presenting symptoms. Abdominal myomectomy was the most commonly performed procedure (74.5%), including 5.5% repeat myomectomies, followed by total abdominal hysterectomy (20.4%). Postoperative wound complications occurred in 5.1% of patients, and no mortality was recorded. Conclusion: Uterine leiomyoma occurs mainly among women in their third decade of life and those with low parity. Menorrhagia and abdominal swelling are the most common presenting symptoms, with abdominal myomectomy being the predominant surgical treatment. Overall surgical outcomes are favourable, with no recorded mortality.

This study examines the relationship between job loss expectations and household financial distress using microdata from the Federal Reserve Bank of New York’s Survey of Consumer Expectations (SCE). Using a nationally representative sample of working-age individuals observed monthly between 2020 and early 2025, the analysis investigates whether households’ subjective perceptions of labor market risk are economically consequential for financial vulnerability, independent of realized job loss. Financial distress is measured using a composite binary indicator based on respondents’ reported difficulty meeting financial obligations, deterioration in financial conditions, and limited ability to absorb unexpected expenses. The results show a strong and robust association between perceived job loss risk and financial distress. A 10 percentage-point increase in the subjective probability of job loss is associated with a 4.2 percentage-point increase in the likelihood of financial distress, even after controlling for income, education, employment status, demographic characteristics, and financial buffers. The effect remains stable across alternative model specifications, lagged expectations, and robustness checks. Heterogeneity analysis reveals that the relationship is substantially stronger among low-income and less-educated households, consistent with greater vulnerability to labor market uncertainty. These findings provide new evidence that subjective expectations about employment stability are a key determinant of household financial vulnerability, extending the expectations literature beyond consumption and saving behavior. The results suggest that expectation-based measures can serve as early indicators of financial distress and highlight the potential value of policies aimed at stabilizing household expectations and strengthening financial resilience.

In the modern era of rapid technological advancement, child safety has become a growing concern, particularly in public spaces such as shopping malls, parks, schools, and recreational areas, where numerous cases of children getting lost or temporarily separated from their parents or guardians have been reported. These incidents highlight the limitations of conventional supervision methods and expose children to potential safety risks if immediate action is not taken. This paper presents the development of a Wearable Child Tracker with GPS and Messaging Integration, an Internet of Things (IoT)-based safety device designed to enhance child security and parental awareness. The proposed system integrates a Global Positioning System (GPS) module with an ESP32 microcontroller to acquire accurate real-time location data, which is transmitted wirelessly to parents or guardians through the Telegram messaging application using a bot-based communication approach. This architecture eliminates the need for a dedicated backend server, thereby reducing system complexity, operational cost, and maintenance requirements. The wearable device is compact, lightweight, and energy-efficient, making it suitable for continuous daily use by children. Functional testing indicates that the system is capable of providing real-time location updates with acceptable accuracy and response time under normal network conditions. Overall, the proposed solution demonstrates the feasibility of integrating wearable technology, GPS tracking, and instant messaging platforms to improve child safety and provide peace of mind to parents and guardians.

This study investigates the complex relationship between public perception of the Oodua People's Congress (OPC) and its impact on security dynamics in Nigeria. Employing a mixed-methods approach, data was collected from 500 survey respondents and 100 in-depth interviews across various regions. The findings reveal a stark perceptual divide: within its South-West ethnic base, the OPC is viewed favorably as an effective security provider (Mean=4.1) and cultural defender (Mean=4.3). Conversely, in other regions, it is perceived as a violent (Mean=4.5) and destabilizing force (Mean=4.6). Regression analysis identified ethnic affiliation (β=.40, p<.001) and personal experience with OPC security (β=.35, p<.001) as the strongest positive predictors of favorable perception, while trust in state security and negative media exposure were significant negative predictors. Qualitative data contextualizes this divide, highlighting themes of "Functional Illegitimacy" and "Methodological Contradiction." The study concludes that the OPC's contested legitimacy, derived from filling a security vacuum for one segment of the population while posing a national threat to another, represents a core challenge to security. Policy interventions must therefore navigate this duality, addressing the root causes of state security failure while managing the risks of ethnic militia violence.

The effectiveness of language instruction at the higher secondary level is closely linked to teachers’ perceptions of content difficulty and their instructional competence. Tamil, as a classical and contemporary language, comprises diverse content areas such as poetry, prose, supplementary lessons, and grammar each posing unique pedagogical challenges. The present study examines teachers’ perceptions of difficulty across these four Tamil content areas using item-wise analysis. Data were collected from higher secondary Tamil teachers and analyzed using descriptive statistics. The findings reveal that grammar is perceived as the most difficult component, followed by poetry and supplementary lessons, while prose is considered relatively less difficult. The study highlights critical areas requiring pedagogical support and curriculum-level interventions to enhance Tamil language teaching effectiveness.

The rapid increase in incidents related to women harassment, stalking, and unsafe public environments has intensified concerns regarding personal safety, particularly during travel or late hours. Traditional women safety solutions often rely on manual phone calls, mobile applications, or wearable devices, which may fail during panic situations due to delayed response, limited accessibility, or dependency on user interaction and hardware constraints.

The purpose of the present study was to investigate the effects of strength and conditioning training on speed and power among track athletes and football players in Tirupati district. A total of 120 male participants (60 track athletes and 60 football players) aged between 17 and 25 years were selected using purposive sampling from various sports clubs and educational institutions in Tirupati. The experimental group underwent a 12-week structured strength and conditioning training program, which included resistance training, plyometric drills, sprint workouts, and functional core exercises, administered five days per week. Pre- and post-training assessments were conducted using standardized tests: the 40-meter sprint test for speed, the vertical jump test, and the standing broad jump for power. Statistical analysis was performed using paired and independent t-tests to compare within-group and between-group differences at a 0.05 level of significance. The results indicated that both track athletes and football players showed significant improvements (p < 0.05) in speed and power following the strength and conditioning program. However, the magnitude of improvement in sprint speed was greater among track athletes, while football players demonstrated comparatively higher gains in lower-body power measures. The findings suggest that a programmed strength and conditioning regimen positively influences key performance indicators in both sports groups, with training adaptations tailored to sport-specific demands. It is concluded that integrating strength and conditioning training into regular practice schedules can enhance athletic performance in terms of speed and power in both track athletes and football players in the Tirupati district. Recommendations for future research include examining gender differences and long-term performance retention.

The present study was aimed at the synthesis of silver nanoparticles using Irvingia gabonensis peel extracts and investigation of the antimicrobial effects of these nanoparticles against Pseudomonas aeruginosa and Staphylococcus aureus microorganisms. The fruits were harvested, washed, peeled and dried for 12 weeks. Aqueous extracts of the fruit peel samples were thereafter obtained and the synthesis of the silver nanoparticles was carried out by mixing 30 ml of aqueous extract with 70 ml of 4mM and 8mM concentrations respectively, of the silver trioxonitrate salt. The synthesized silver nanoparticles were characterized using UV-Visible spectroscopy. The Irvingia gabonensis peel extracts-synthesized silver nanoparticles exhibited potent antibacterial activity against Pseudomonas aeruginosa and Staphylococcus aureus microorganisms Results from the UV-Visible spectroscopy characterization confirmed the synthesis of silver nanoparticles with spectral peaks obtained (between 200 and 429 nm) within the range expected for silver nanoparticles (between 380-480 nm). The silver nanoparticles synthesized using 4mM silver trioxonitrate salt was found to exhibit potent antibacterial activity with IC50 values of 38.05 μg/ml and 75.42 μg/ml for inhibition of total dehdrogenase activity of Staphylococcus aureus and Pseudomonas aeruginosa microorganisms respectively. IC50 values for the Inhibition of total dehydrogenase activity by the silver nanoparticles synthesized using 8mM silver trioxonitrate salt was not determinable. The results of this study thus have shown that silver nanoparticles can be synthesized using Irvingia gabonensis peel extracts and the silver nanoparticles possess significant antibacterial properties against Staphylococcus aureus and Pseudomonas aeruginosa.

This study investigates the effects of demographic characteristics on consumer responses to neuromarketing stimuli among 228 respondents in Sagar District. Using a cross-sectional survey design, the research examines how age, gender, income, and education influence consumer responsiveness to neuromarketing techniques. Data were analyzed using SPSS with chi-square tests, ANOVA, and regression analysis. Results indicate that demographic factors significantly influence consumer responses to neuromarketing stimuli, with age and education emerging as the strongest predictors. Younger consumers demonstrated higher engagement with visual and emotional marketing stimuli compared to older age groups. Gender differences were observed in attention allocation patterns, with males showing greater responsiveness to rational appeals and females to emotional content. Education level significantly predicted overall neuromarketing responsiveness, while income showed moderate effects. These findings have important implications for marketers developing targeted campaigns in emerging markets and contribute to the growing literature on consumer neuroscience in non-Western contexts.

This study sought to find and evaluate variables influencing employee happiness. In the healthcare industry, through literature review and expert consultations, including input on staff coordination, the latest technology, and previous reference studies. The objective of this study is to examine parameters associated to employee happiness, job load, work fulfillment, and emotional tiredness and characterize their impact on nurses and physicians in the central Catalonia health region during(37) (Spain) 2025(15) (12)(26). Techniques are employed A questionnaire was used to collect data for a multicenter cross-sectional investigation at Central Catalonia's territorial management (14)(26). The SPSS software was used for the analysis, and the job satisfaction survey (JSS) and questionnaire were used to gather the data. The study discovered favorable correlations between user happiness and worker productivity as well as between managerial impact and workforce contentment. The relationship between employee contentment and organizational offerings, as well as the need of emphasizing employee satisfaction for increased productivity (22) (25). Organizational procedures must be modified to increase employee involvement and job satisfaction while reducing emotional stress and tiredness (20)(34). This may involve limiting unpaid overtime and encouraging more consistent working hours. This study helps to comprehend the complicated links between organizational characteristics, employee happiness, and service quality in the healthcare sectore.

Serverless computing – a cloud-native model where infrastructure is abstracted away – is redefining the way modern applications are built and deployed. In this paradigm, developers write stateless functions that are triggered by events, while cloud providers handle provisioning, scaling, and fault tolerance. Unlike traditional server-based or containerized approaches, serverless emphasizes event-driven execution and a pay-as-you-go billing model, making it highly cost-efficient for unpredictable workloads. Leading platforms such as AWS Lambda, Azure Functions, and Google Cloud Functions support diverse triggers and integrations, enabling real-time processing, web backends, IoT pipelines, and automation tasks. Performance challenges, however, persist: cold start latency introduces delays in function execution, vendor lock-in limits portability, and monitoring distributed stateless services remains complex. Recent advancements show promise in mitigating these issues, including cold start optimizations (e.g. AWS SnapStart), serverless containers (Knative, AWS Fargate), and hybrid models that blend serverless with virtual machines. Industry reports forecast rapid adoption, with the global market projected to grow from USD 24.51 billion in 2024 to over USD 52 billion by 2030, reflecting a CAGR above 14%. Research is also exploring integration of serverless with AI/ML workloads and multi-cloud strategies to overcome vendor dependency. This paper reviews the evolution of serverless computing, outlines its architecture, highlights benefits and limitations, and examines empirical studies on performance and cost-effectiveness. Finally, open challenges such as debugging complexity, execution limits, and enterprise-scale adoption are discussed, along with future trends shaping this new era of cloud-native deployment.

Background: Worm infestation (Helminthiasis) remains a significant public health challenge in developing nations, particularly in urban slums characterized by poor sanitation. Chronic infestation often leads to a vicious cycle of malabsorption and nutritional deficiency, manifesting as stunted growth and wasting. While conventional anthelmintics are standard, recurring infections and drug resistance necessitate exploring holistic alternatives like homeopathy. Objective: To evaluate the efficacy of individualized homeopathic treatment in managing worm infestations and its subsequent impact on the nutritional status (weight/height) of children aged 2–5 years residing in slum areas. Methods: This prospective clinical trial will involve 100 children selected through systematic sampling from urban slums. Participants will be screened for worm infestation via stool examination or history of pica and anal itching.
• Intervention: Subjects will receive individualized homeopathic remedies (e.g., Cina, Santoninum, Teucrium, or Calcarea Carb) based on their physical and behavioural symptoms.
• Assessment: Primary outcomes include the reduction of parasite load (stool repeat test) and anthropometric gains (weight and height) monitored monthly over 6–12 months.
Results (Anticipated for 2026): Based on previous pilot data, it is expected that homeopathic intervention will not only reduce the frequency of worm expulsion and associated symptoms like teeth grinding and irritability but also lead to a significant weight gain of approximately 100–200g per month as digestive assimilation improves.

The unequal distribution of essential medicines and the significant wastage of surplus drugs remain critical challenges in healthcare systems, particularly in low-resource communities. Digital medicine donation platforms aim to bridge this gap by connecting donors with recipients; however, manual allocation processes often lead to inefficiencies, delays, and inequitable distribution. This paper proposes an AI-based optimization framework for donor-recipient allocation in surplus medicine platforms to ensure timely, fair, and need-based medicine redistribution.The proposed system leverages machine learning and optimization techniques to analyze donor availability, medicine attributes (type, quantity, expiry date, and storage requirements), recipient demand, geographic proximity, and urgency levels. A hybrid model combining predictive analytics and constraint-based optimization is employed to prioritize high-need recipients while minimizing wastage and logistics cost. Natural Language Processing (NLP) is utilized to classify medicine descriptions and validate donation details, while geospatial analytics supports efficient routing and matching.Experimental evaluation using simulated and real-world donation datasets demonstrates improved allocation accuracy, reduced medicine expiry loss, and faster fulfillment times compared to rule-based allocation approaches. The results highlight the potential of AI-driven allocation systems to enhance transparency, scalability, and social impact in surplus medicine redistribution. This research contributes a practical and scalable solution for intelligent healthcare donation platforms supporting sustainable and equitable access to essential medicines.

Plastic pollution constitutes a critical environmental challenge due to the extensive production, widespread use, and environmental persistence of polyethylene-based materials, particularly single-use packaging such as sachet water pouches and polythene bags. These materials are extensively consumed in developing regions, where inadequate waste management infrastructure exacerbates their accumulation in terrestrial and aquatic ecosystems. Owing to their stable hydrocarbon polymer structure, polyethylene plastics resist natural degradation, fragmenting over time into microplastics that pose serious ecological, public health, and economic risks. This study explores microbial biodegradation as a sustainable alternative to conventional plastic waste management approaches, with specific emphasis on the role of thermal pretreatment in enhancing polymer susceptibility to microbial attack. Heat treatment was applied to polyethylene materials to induce structural and surface modifications that improve microbial colonization and enzymatic accessibility. The biodegradation potential of selected microorganisms was subsequently evaluated under controlled conditions, considering key environmental parameters influencing degradation efficiency. Findings from this study demonstrate that thermal pretreatment significantly improves the biodegradability of polyethylene by promoting polymer chain scission and increasing surface reactivity, thereby accelerating microbial degradation processes. Despite inherent challenges such as slow degradation rates and variability in plastic composition, the results underscore the promise of integrating heat-assisted microbial biodegradation into sustainable plastic waste management strategies. This approach offers a viable, environmentally compatible pathway for reducing polyethylene waste accumulation and mitigating its long-term environmental impacts, particularly in regions heavily burdened by single-use plastic pollution.

Indiscriminate siting of boreholes is on the increase in most cities in Nigeria Owerri Urban is not an exception. The essence of this study is to assess the risk of sewage contamination in Boreholes in Owerri. 10 boreholes were randomly selected from different locations within the study area. Samples were collected and analyzed under physical, chemical, and bacteriological parameters. Analytical Hierarchy Process (AHP) was applied to select six (6) sewage indicator parameters, then weighted rates of: 0.28, 0.24, 0.24, 0.03, 0.10, and 0.10, were respectively. These weighted rates show the level of specific contribution of the parameters to sewage contamination and were applied to generate the groundwater contamination index (GWCI) for the ten (10) locations. The results of the GWCI showed that W10 with a horizontal separation (distance) of 27 m from the soak-away (septic system) gave a Contamination Index (CI) of 2.15972 which represent the best quality when compared with the other nine locations. The risk percentage is 53.7% which can be considered as medium risk. Other locations W1, W2, W3, W4, W5, W6, W7, W8, and W9 have GWCI of 1003.135, 203.5999, 203.6943, 106.1377, 102.5303, 402.1481, 103.2407,103.3082, and 402.7103, respectively with W1 having a horizontal separation of 6 m from the septic system as the worst GWCI. The study revealed that there are possibilities of sewage contamination and as such the WHO standard for sitting Septic systems and boreholes which is 30 m should be adhered to strictly. Also, for urban settlements like Owerri, Central water treatment and distribution should be made functional to meet the population demands so as to reduce mindless drilling by individuals as there is huge competition for space.

Nigeria’s Technical and Vocational Education and Training (TVET) system holds considerable potential to drive sustainable economic growth, yet its impact is diminished by persistent gaps between academic instruction and evolving industry demands. This study examines the effectiveness of curriculum delivery in relation to industrial engagement among TVET lecturers in Nigeria. Using a sample of 69 lecturers, two key indicators of industrial interaction were measured: B1, a binary variable indicating direct industrial engagement, and B3, a scale assessing the frequency of engagement with industry partners. The outcome variable, C1, reflects the frequency with which lecturers incorporate industry-relevant case studies into their teaching, measured on an ordinal scale. Ordered logistic regression (OLR) was employed to analyze the ordinal outcome, and odds ratios were computed to interpret the effects of the predictors. The findings reveal that lecturers with direct industrial engagement (B1) are significantly more likely to enrich their curriculum with practical industry examples (Odds Ratio = 2.83, p < 0.05). In contrast, the frequency of industry engagements (B3) did not significantly affect curriculum delivery. These results underscore that it is not merely the frequency but the quality of industrial involvement that enhances the relevance of TVET curricula. This study provides empirical evidence that reinforces calls for robust industry- academia partnerships and curriculum reform in TVET. The implications of these findings are far-reaching; policymakers and educators are encouraged to promote direct industrial collaboration and invest in professional development. Such initiatives are essential for aligning TVET outputs with real-world industrial needs, thereby improving workforce readiness and contributing to national economic development.

The paper outlines a robust, three-legged approach to transforming traditional financial Business Intelligence (BI) dashboards into predictive decision-support systems through Data Science (DS) and Artificial Intelligence (AI). For modern corporate finance, traditional static reporting methods no longer suffice; it requires real-time insights and sophisticated risk forecasting. This research maintains that advanced predictive modelling integration (forecasting, risk detection) into the visualization layer categorically necessitates structured, robust data architecture and comprehensive regulatory compliance protocols. The focus then shifts to implementing the Medallion Data Lakehouse Architecture for ensuring data integrity, lineage, and auditability. Subsequently, a detailed discussion of model selection is performed, governed by a critical accuracy-explainability trade-off. The resultant findings underpin the desirability of integrating explainable AI techniques, specifically SHAP and LIME, along with formalized model risk management protocols, especially those presented through the supervisory guidance of the Office of the Comptroller of the Currency (OCC) SR 11-7, as non-negotiable components of the predictive pipeline. Finally, the paper concludes by defining best practices in data governance and algorithmic fairness, assessing future directions, and, among these, the transformative role of generative AI in self-service financial analytics.

Direct Current (DC) motors are used in industries because they are less expensive, offer reduced complexity in control structure, and provide wide speed and torque performance. The speed control was achieved for separately excited DC motor by varying the armature voltage and by varying field flux. speed control method by varying armature voltage using chopper. The firing circuit of chopper receives signal from controller and variable voltage is given to the armature of DC motor according to the desired speed. Different firing angles were considered. As the triggering angle increases, the load voltage and load current decrease. At a trigger angle of 0º, the load voltage and load current was 345.8V and 328.1A respectively and this highest magnitude of load voltage and load current. Furthermore, the simulation results showed that the highest speed was obtained when the trigger angle was 0º. This can be attributed to the fact that as the load current increases the speed of the DC motor rises. Therefore, since the lowest value of load voltage and load current were obtained at a trigger angle of 90º, the lowest speed of the DC motor was achieved in this case.

Heart disease remains one of the leading causes of mortality worldwide, emphasizing the need for early and accurate diagnostic systems. Recent advancements in machine learning have shown significant potential in assisting clinical decision-making through data-driven prediction models. This paper presents an ensemble-based machine learning approach for accurate heart disease prediction by integrating multiple supervised learning algorithms to improve diagnostic performance. The proposed framework combines individual classifiers such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbors using ensemble techniques including voting and stacking. Comprehensive data preprocessing steps, including missing value handling, feature normalization, and feature selection, are employed to enhance model robustness. The ensemble model is evaluated on a benchmark heart disease dataset using standard performance metrics such as accuracy, precision, recall, F1-score, and ROC–AUC. Experimental results demonstrate that the ensemble approach outperforms individual classifiers by achieving higher prediction accuracy and improved generalization capability. The findings indicate that ensemble learning provides a reliable and efficient solution for early heart disease detection, supporting its potential application in intelligent healthcare and clinical decision support systems.

Maternal and child health continues to be a critical global public health challenge, particularly in developing countries where malnutrition, micronutrient deficiencies, and inappropriate dietary practices are widespread. Nutrition education is widely acknowledged as a cost-effective, sustainable, and preventive strategy for improving health outcomes among mothers and children. This paper provides a comprehensive review and analytical assessment of the impact of nutrition education on maternal and child health outcomes. It examines key theoretical frameworks, behavior-change mechanisms, and essential maternal and child nutrition indicators, supported by evidence from both national and international studies. The review findings demonstrate that nutrition education significantly enhances maternal knowledge, attitudes, and dietary practices, resulting in improved pregnancy outcomes, better infant and young child feeding practices, reduced prevalence of malnutrition, and improved child growth and development. The paper underscores the importance of systematically integrating nutrition education into maternal and child health programs to achieve sustainable improvements in health, nutrition, and overall human development.

Background: Scarlet fever, caused by Group A Streptococcus (GAS), has shown a global resurgence in recent years following the COVID-19 pandemic. In India, this re-emergence presents significant public health challenges due to the country’s large pediatric population and healthcare access disparities. Objective: This study aims to analyze the re-emergence patterns, clinical profile, and public health implications of scarlet fever in India, with emphasis on changing epidemiology, antimicrobial resistance, and prevention strategies. Methods: A comprehensive review of literature on GAS infections and scarlet fever was conducted, focusing on epidemiological data from India and comparable regions. WHO guidelines, national protocols, and recent studies on GAS infections published between 2015- 2025 were analyzed. Results: Recent data indicates a significant increase in scarlet fever cases in India following the COVID-19 pandemic, mirroring global trends. The clinical profile shows the classic triad of fever, pharyngitis, and sandpaper rash, with complications including rheumatic heart disease disproportionately affecting lower socioeconomic populations. Antimicrobial resistance patterns show concerning trends with increasing macrolide resistance. Conclusion: The re-emergence of scarlet fever in India necessitates enhanced surveillance, antimicrobial stewardship, and public health interventions. Vaccine development efforts represent a promising avenue for future control strategies.

Background: Diphtheria is a vaccine-preventable disease caused by Corynebacterium diphtheriae and continues to be a public health problem in India, despite the availability of effective immunization programmes. Periodic outbreaks and sporadic cases indicate persistent gaps in vaccination coverage and disease surveillance. Objective: This review aims to identify and analyze barriers to diphtheria prevention in India by examining immunization strategies, outbreak patterns, and programmatic challenges during 2015-2023. Methods: The literature review was conducted using PubMed, WHO databases, and Indian government health reports. Studies, outbreak reports, and immunization data from 2015 through 2023 were reviewed. Inclusion was based on all peer-reviewed articles, epidemiology reports, and official health statistics on the prevention of diphtheria and its outbreaks in India. Results: Immunization gaps in various major states varied from 62% to 91%, with marked disparities in urban and rural areas. Significant barriers included insufficient cold chain infrastructure; vaccine hesitancy; missed opportunities for vaccination related to migration; and weak surveillance systems. From 2015 to 2023, India reported several outbreaks with case fatality rates ranging from 5% to 16%. Conclusion: Despite the availability of effective vaccines, diphtheria prevention in India faces systemic barriers. Strengthening of immunization infrastructure, improvement in surveillance, and addressing socio-behavioral factors are crucial components for disease elimination.

Arterial narrowing, or stenosis, disrupts normal blood flow and elevates the risk of cardiovascular complications. Traditional hemodynamic models often assume a no-slip condition at the vessel wall, but emerging evidence suggests wall slip can influence flow characteristics, particularly in regions of narrowing. This study investigates the biomechanical effects of wall slip on blood flow through stenotic arteries, focusing on velocity profiles, wall shear stress, and flow disturbances. Using computational fluid dynamics (CFD) and a Navier slip boundary approach, we examine the impact of varying stenosis severity and slip lengths. Results indicate that wall slip significantly alters flow patterns, reducing peak shear stress while increasing localized velocity near the wall, which may affect endothelial function and disease progression. These insights improve the understanding of stenotic hemodynamics and have implications for clinical assessment and device design.

Speech-to-text (STT) conversion is a cornerstone of modern human-computer interaction, enabling machines to transcribe spoken language into text with increasing accuracy. With the rapid advancement in Artificial Intelligence and Natural Language Processing (NLP), speech recognition systems have transitioned from rule-based and statistical methods to highly sophisticated deep learning and transformer-based architectures. This evolution has opened up new possibilities in accessibility technologies, automated transcription services, virtual assistants, and real-time language translation, while also presenting unique technical challenges related to accuracy, latency, and adaptability across languages and dialects. This research paper aims to present a comprehensive comparative analysis of the diverse NLP-based techniques employed for STT conversion. We explore the progression of this field by first examining traditional approaches such as Hidden Markov Models (HMMs) and Gaussian Mixture Models (GMMs), whichrecognition systems. These conventional models were dependent on hand- engineered features and statistical representations, providing limited flexibility in handling complex acoustic variations, speaker accents, or noise in real-world environments. The paper then shifts focus to the emergence of end-to-end deep learning methods, particularly those employing Connectionist Temporal Classification (CTC) and Recurrent Neural Networks (RNNs). CTC-based models offered a significant improvement over traditional architectures by eliminating the need for pre-aligned input-output sequences.

Small and medium-sized enterprises (SMEs) contribute meaningfully to local employment and income generation, yet many operate with limited planning capability and face weak performance in competitive urban markets. This study examined the prevalence of strategic planning and its effects on business growth among selected SMEs in Makeni, Lusaka. A quantitative, cross-sectional survey design was adopted, using structured questionnaires administered to 100 SME owners and managers. Data were analysed in SPSS using descriptive statistics, paired-sample t-tests and repeated measures ANOVA at a 1% significance level. Only 17% of SMEs reported formal strategic planning, 49% relied on informal planning, and 34% reported no planning. Paired comparisons indicated statistically significant improvements after adopting strategic planning: mean sales growth rose from 5.47% to 7.84%, customer retention increased from 71.34% to 79.41%, and profit margin improved from 9.81% to 13.17% (all p < .001). Repeated measures ANOVA further confirmed significant effects of time, performance metric and their interaction (p < .001). The findings imply that even basic strategic planning practices can yield measurable performance gains for SMEs, suggesting the value of targeted capacity-building and simple monitoring tools that help owners translate plans into execution.

The present study investigates the impact of study habits on academic performance among higher secondary school students, with special reference to gender differences. A quantitative research approach using the descriptive survey method was adopted. The sample consisted of 200 higher secondary students (100 boys and 100 girls) selected through simple random sampling from four schools under the West Bengal Board of Higher Secondary Education in the North 24 Parganas district. Study habits were assessed using the standardized Study Habits Inventory developed by C. Gilbert Wrenn and adapted by Nurmala Jamaludin, while academic performance was measured through students’ examination scores. The findings revealed a significant positive relationship between study habits and academic performance (r = 0.15, p < 0.05), indicating that students with better study habits tend to achieve higher academic outcomes. No significant difference was found between boys and girls in academic performance, suggesting comparable achievement levels across genders. However, a significant gender difference was observed in study habits, with girls demonstrating significantly better study habits than boys at the 0.01 level. The study concludes that effective study habits play a crucial role in enhancing academic performance at the higher secondary level. The findings highlight the need for educators and policymakers to promote structured and gender-sensitive study habit interventions to improve students’ academic success and overall learning outcomes.

Background: Historically, scarlet fever is a significant cause of morbidity among children; however, fluctuating incidences are being observed across the world. Recently, the possibility of a resurgence has raised concerns, though reports from India are very limited. Understanding its re-emergence, clinical features, and epidemiological pattern is essential for guiding diagnosis and public health strategies. The objective is to study the pattern of re-emergence of scarlet fever in India, its clinical profile, demographic distribution, and therefore its implications on public health. Methods: A descriptive review of retrospectively collated published surveillance reports, hospital records, and case series during 2010–2025 across selected tertiary care centers in India was carried out. The incidence trend data, age distribution, clinical manifestation, diagnostic criteria, treatment practices, and outbreak reports were analyzed. Public health guidelines related to the control of Group A Streptococcus infection were reviewed for contextual interpretation. Results: Many regions reported a trending increase in scarlet fever cases starting after 2018, notably in the urban pediatric population. Commonly recognized clinical features included fever, sore throat, sandpaper-like rash, strawberry tongue, and Pastia lines. Primary care settings commonly reported delayed notifications and misdiagnosis. Macrolide resistance among Group A Streptococcus strains was found to be on the rise in some centers. Public health surveillance mechanisms were very different across states, with underreporting attributed mostly to this fact. Conclusion: There is a possibility of re-emergence of scarlet fever infection in parts of India with classical clinical manifestations along with emerging antimicrobial resistance patterns. Strengthening of surveillance, early diagnosis, clinician awareness, and unified reporting systems are necessary to avert outbreaks and disease burden.

Unit conversion occurs on daily basis in different fields of human endeavour, ranging from science, engineering, social sciences, medicine, business, building technology, education and daily tasks. The imperial system uses old-fashioned units like Inch, Yard, Foot, Mile, Pound, Ounce, Gallon, etc. to measure quantities. International System of units (SI) established a decimal system on which metric system is anchored. Conversion charts are usually consulted to manually convert from one unit of measurement to the other. These charts contain lists of equivalent measures which the user needs to memorise or keep handy. The manual unit conversion method is prone to errors, tasking and does not produce timely results. This paper aims to create a versatile and user-friendly software solution that facilitates seamless unit conversions across a spectrum of measurement domains. The system is designed to address the challenges posed by diverse unit systems, enabling users to effortlessly convert units of quantities like length, mass, volume, temperature, time data size. Object-Oriented System Analysis and Design methodology was adopted and the system was implemented using Visual Basic.net. The system’s interface features input fields, dropdown menus, and buttons that simplify the user experience, making the conversion process accessible to users of all levels of expertise. The layout is designed to ensure ease of navigation and a visually pleasing experience.

With the rising complexity and frequency of cyber threats, traditional perimeter- based security models are no longer sufficient. Zero-Trust Architecture (ZTA) has emerged as a paradigm shift in cybersecurity, emphasizing "never trust, always verify" principles. This research paper explores the foundational concepts of ZTA, the limitations of conventional network models, and the implementation of zero-trust frameworks in real-world environments. It proposes a multi-layered model combining identity-based access control, micro-segmentation, and continuous monitoring. The study also discusses future implications for enterprise security, IoT, and cloud computing. We conclude that ZTA is not just a trend but a fundamental necessity for modern cyberdefense.

Cybersecurity has become an essential requirement in modern digital infrastructures due to the rapid growth of internet-based services, cloud computing, and network-enabled devices. As cyber-attacks continue to evolve in complexity and frequency, traditional Intrusion Detection Systems (IDS) based on static rules or predefined attack signatures are no longer sufficient to identify sophisticated or previously unseen attacks. This project focuses on the development of an Improvised Reinforcement Learning-Based Intrusion Detection System that enhances intelligent threat detection through adaptive learning. The proposed system integrates feature extraction, preprocessing, Deep Q-Learning-based policy optimization, and intelligent classification to identify malicious and normal network activities. Standard benchmark datasets such as NSL-KDD and CIC-IDS-2017 are used to train and evaluate the model. Pre-processing techniques are applied to improve robustness and computational efficiency.

Housing insecurity in Abuja is shaped not only by shortages of dwellings but also by the tenure systems through which low-income households access housing. This study examined dominant tenure pathways among low-income earners in the Federal Capital Territory and assessed how tenure relates to key housing security outcomes, including affordability stress, perceived eviction risk, forced moves, and housing satisfaction. Using a cross-sectional household dataset (n = 900), the analysis applied descriptive statistics, cross tabulations, and logistic regression to test associations between tenure pathways and housing security outcomes. Informal rental emerged as the most common pathway and was associated with the highest levels of perceived eviction risk. Affordability stress was widespread, with rental pathways showing the greatest cost burden, and affordability stress strongly increased the likelihood of high perceived eviction risk. Owner or incremental build arrangements also showed elevated insecurity relative to more stable arrangements, highlighting that ownership like pathways do not automatically guarantee protection under contested or weakly documented conditions. Overall, the findings indicate that housing security improvements in Abuja require policies that jointly address rental affordability, enforceable tenure protections, and clearer documentation and regularisation pathways for vulnerable households.

Muscle oxygen availability is a key factor influencing exercise performance yet traditional markers such as heart rate and VO₂max do not fully capture localized oxygen dynamics. Near-infrared spectroscopy (NIRS) offers a non-invasive approach to continuously monitor muscle oxygen saturation (SmO₂) during exercise and recovery. This study examined the patterns of SmO₂ and heart rate (HR) responses in young athletes during incremental cycling exercise and post-exercise recovery. Twenty Indian athletes (10 male, 10 female; mean age 18.1 ± 15.2 years) completed a graded cycling test with increments until exhaustion, followed by a 5-minute passive recovery. SmO₂ was measured using a portable NIRS device on the vastus lateralis, while HR and respiratory gases were continuously recorded. Results revealed a progressive decline in SmO₂ from ~74% at rest to ~48% at peak workload, indicating increasing oxygen extraction by the working muscles. In parallel, HR rose steadily from ~68 bpm at rest to ~190 bpm at exhaustion, reflecting heightened cardiovascular demand. During recovery, HR decreased rapidly, falling to ~118 bpm at 2 minutes and ~88 bpm at 5 minutes, while SmO₂ rebounded from ~48% at peak to ~73% by 5 minutes, demonstrating efficient re-oxygenation. These findings highlight a characteristic inverse relationship between HR and SmO₂ during incremental exercise and a rapid resaturation pattern during recovery in young, trained individuals. NIRS-derived SmO₂ tracking may serve as a valuable tool for coaches and practitioners to optimize training loads, monitor fatigue, and enhance recovery strategies in developing athletes.

Population ageing poses significant health challenges in rural India, particularly due to the rising burden of multimorbidity among older adults. The present cross-sectional descriptive study examines the distribution of health problems and their association with selected socio-demographic factors among the rural elderly in Kurnool District, Andhra Pradesh. A total of 382 elderly persons aged 60 years and above were selected using proportionate random sampling based on the 2011 Census. Data were collected through a structured interview schedule and analyzed using descriptive statistics and chi-square tests. The findings reveal that a majority of respondents reported two or more health problems, indicating a high prevalence of multimorbidity. Housing condition and working status showed statistically significant associations with the number of health problems, while age, sex, caste, and religion did not exhibit significant relationships. The study highlights the importance of living conditions and economic engagement in shaping elderly health outcomes and underscores the need for integrated geriatric healthcare services and active ageing–oriented policies to promote healthy and dignified ageing in rural settings.

This study explored the perceived influence of training, injury recovery, and mental toughness on the performance of university-level volleyball athletes. A quantitative research design was employed, utilizing the survey method to gather data from 23 varsity volleyball athletes. The instrument assessed the athletes’ perceptions across three key areas: the effectiveness of their training programs, their experiences with injuries and recovery, and the influence of mental toughness on their performance. Findings revealed that athletes perceived their training as having a moderate influential on performance. While they showed strong confidence in the training’s ability to prepare them for competition, they expressed a need for more high-intensity, performance-specific coaching strategies. Injuries and recovery also received a moderate influential rating, with athletes demonstrating good awareness of injury prevention practices, but voicing concerns regarding the frequency of injuries and the lack of sufficient medical support. Mental toughness was rated as moderately influential with high recognition of mental preparation strategies, though athletes identified difficulty in recovering emotionally from losses or setbacks. Based on the results, the study concludes that although current training, injury management, and mental conditioning practices are effective to a degree, they fall short of fully maximizing athletic potential. The study recommends that training programs be revised to incorporate more high-intensity, skill-specific drills, medical support systems be improved, and mental resilience strategies be formally integrated into athlete development programs to optimize volleyball performance outcomes.

Financial inclusion is widely recognized as a critical mechanism for poverty alleviation, particularly in developing economies. This study examines its specific role in the context of rural Nigeria, where poverty and financial exclusion remain persistently high. The research aims to assess the impact of access to financial services including microcredit, mobile banking, and financial literacy on poverty reduction outcomes. Conducted in selected rural areas across five states in South-West Nigeria, the study employed a mixed-methods approach. Quantitative data were collected through structured questionnaires administered to 750 household heads, while qualitative insights were gathered via interviews with financial institutions, government officials, and NGO representatives. The results paint a stark picture of financial exclusion, with 54% of respondents completely outside the formal financial system. Among those with access, mobile money wallets (60.9%) are the most common entry point. However, infrastructural and educational barriers are significant; 70% of mobile money users cited poor network connectivity as a major challenge. The impact of microcredit was found to be positive but nuanced; while 77.5% of borrowers reported increased household income, 56% saw no change in employment, suggesting loans are used for capital intensification rather than job creation. A logistic regression model revealed that financial inclusion variables are significant positive predictors of a household&#39;s likelihood of being above the poverty line. Holding a formal account and using mobile money more than doubled the odds, but the most powerful predictor was financial literacy, which tripled the odds (Odds Ratio=3.06). The study identifies key barriers as a lack of money (69.3%), distance to facilities (64%), and high costs (52%). It concludes that while financial inclusion is a potent tool for poverty alleviation, its success hinges on an integrated strategy. Merely providing access is insufficient. Effective intervention must pair the expansion of digital financial services with targeted financial literacy programs and robust policies that address underlying infrastructural deficits and economic vulnerabilities.

This paper explores recent advancements in text classification and spam detection using Natural Language Processing (NLP). A comparative analysis is conducted between traditional machine learning algorithms and contemporary deep learning methods, emphasizing their performance, scalability, and practical applications. This document also incorporates notable references, flowcharts, and visualizations to elucidate the methodologies and outcomes.

As urban centers face escalating waste management challenges due to increased population density and consumption, traditional waste collection methods prove increasingly inefficient. The emergence of Smart Waste Management Systems (SWMS) offers a transformative approach for addressing these challenges through the integration of cutting-edge technologies. This abstract presents an overview of SWMS, which harnesses Internet of Things (IoT) sensors, data analytics, and machine learning algorithms to enhance waste management processes. By equipping waste bins with IoT sensors, SWMS provides real-time data on fill levels and waste types, enabling optimized collection routes and schedules. Machine learning models predict waste generation patterns and optimize resource allocation, reducing operational costs and minimizing environmental impact. Additionally, SWMS promotes greater transparency and efficiency by facilitating better monitoring and management of waste disposal practices. The abstract highlights the potential of SWMS to improve urban sanitation, lower carbon footprints, and contribute to sustainable city development. The Smart Waste Management System using Arduino and Load Cell presents an innovative approach to addressing the inefficiencies of traditional waste collection methods. This system is designed to monitor the fill levels of waste bins in real-time, leveraging Arduino microcontrollers and load cells for precise weight measurement. By continuously tracking the weight of the waste accumulated in bins, the system can provide accurate data on when bins are full, thereby optimizing the scheduling of waste collection services. This not only reduces unnecessary collection trips, saving time and resources, but also prevents overflow, maintaining cleanliness in public and private spaces. This smart waste management system exemplifies how IoT technologies can be harnessed to create more sustainable and efficient urban infrastructure, contributing to cleaner cities and a reduction in the environmental impact of waste management practices.

Air pollution has emerged as a critical environmental and public health concern, particularly in rapidly urbanizing regions. Conventional air quality monitoring systems are often expensive, sparsely deployed, and lack real-time accessibility, limiting their effectiveness in proactive pollution management. This paper presents the design and development of an IoT-based Air Quality Monitoring System that enables continuous, real-time monitoring of ambient air quality parameters.The proposed system integrates low-cost gas and particulate sensors with a microcontroller-based embedded platform to measure key air quality indicators such as particulate matter (PM₂.₅/PM₁₀), carbon monoxide (CO), nitrogen dioxide (NO₂), and volatile organic compounds (VOCs). Sensor data are transmitted wirelessly to a cloud server using IoT communication protocols, where the data are stored, processed, and visualized through a web and mobile-based dashboard. Threshold-based alerts are generated to notify users and authorities when pollutant levels exceed permissible limits.The system offers a scalable, cost-effective, and energy-efficient solution for urban air quality monitoring, enabling data-driven decision-making and public awareness. Experimental results demonstrate reliable real-time data acquisition, improved spatial coverage, and effective remote monitoring capabilities. The proposed system supports smart city initiatives and contributes to sustainable environmental monitoring and management.

This study investigates the effect of selected macroeconomic variables on economic growth in Nigeria. The study was motivated by persistent instability in key macroeconomic indicators and their implications for economic performance. Annual time-series data were used to examine the relationship between economic growth and selected macroeconomic variables, including interest rate, inflation rate, exchange rate, and foreign direct investment. Real Gross Domestic Product (RGDP) was adopted as a proxy for economic growth. The Autoregressive Distributed Lag (ARDL) bounds testing approach and the Error Correction Model (ECM) were employed for data analysis. The results indicate a long-run relationship among the variables. Exchange rate and inflation rates were found to have adverse and significant effects on economic growth, whereas foreign direct investment had a positive and significant effect. Interest rate showed a positive but statistically insignificant relationship with economic growth. The study concludes that macroeconomic stability is essential for sustainable economic growth in Nigeria.

The rapid expansion of the gig economy, freelancing, and crowd work has redefined employment landscapes worldwide, raising significant academic interest in recent years. This study presents a longitudinal bibliometric analysis of 1,529 scholarly publications from Dimensions.ai (2007– 2025) on gig economy, freelancing, and crowd work, focusing on their role in employment. It examines the growth and distribution of research across time, countries, and disciplines, while mapping the intellectual and collaborative structure using co-citation, co-authorship, and keyword analysis. Findings reveal significant growth in publications, diverse geographic contributions, and evolving research themes. The study highlights key knowledge clusters and collaboration patterns, offering insights into emerging trends. It concludes by emphasizing the need for future research on leveraging gig and platform work to promote sustainable and inclusive employment.

This study assessed the interaction between strategic foresight and the performance of SMEs in Rivers State. What informed the investigation was the reluctance of SMEs in Rivers State to develop the ability that will carefully enable them to foresee the future development, explore new trends and take action against impending disruptions, weak signals and convert the weaknesses into strengths that will enable the development of effective strategies to meet their financial and non financial goals. In solving this problem through this research, four research questions and four hypotheses were asked and formulated. Strategic foresight was operationalised using environmental scanning and scenario planning, while firm performance was measured with operational performance and quality. The research adopted the cross-sectional survey, and the study’s accessible population comprised of 445 owners and managers of the SMEs in Rivers State. A sample of 210 respondents was derived. The primary data was obtained using a well-structured questionnaire. Spearman's rank order correlation coefficient was used for the analysis. The findings revealed that both environmental scanning and scenario planning relate to firms' performance. The study concluded that strategic foresight correlates with the firm's performance of SMEs in Rivers State. The study therefore, recommends that management of SMEs in Rivers State should enhance environmental scanning and scenario planning in their organisations for the achievement of effective financial and non financial goals such as return on investment, growing revenue, market share and customer satisfaction.

Despite the widespread availability of technology and its benefits, its adoption among school (primary and secondary) teachers especially in the developing world remains inconsistent. This study investigates the barriers to effective technology adoption among primary and secondary school teachers in South-Western Nigeria. Data were collected through surveys administered to 600 teachers and semi-structured interviews with 60 educators across six states. Quantitative results revealed significant infrastructural deficits, with unreliable electricity (M = 4.5, SD = 0.7) and limited internet access (34% availability) identified as primary obstacles. Although 73% of teachers affirmed technology’s pedagogical value, only 45% felt confident using it in the classroom, highlighting a critical training–confidence gap. Regression analysis indicated that infrastructure, administrative support, access to resources, and teacher training collectively explained 58% of the variance in technology integration (R² = .58), rejecting the null hypothesis that these factors are unrelated. Qualitative themes underscored systemic issues: infrastructural instability, inadequate and theoretical training, lack of administrative support, and psychological resistance rooted in exam-centric curricula. The findings suggest that barriers are interdependent, necessitating holistic, system-wide interventions rather than isolated solutions. Recommendations include investing in sustainable infrastructure, implementing continuous practice-based professional development, strengthening school leadership, and aligning curriculum with digital competencies. This study contributes to the discourse on educational technology in low-resource contexts by emphasizing the need for integrated policy and practice reforms to enable meaningful technology integration.

This paper investigates how emerging digital work environments, together with reasonable accommodation practices, shape the workplace inclusion of employees with disabilities. Using a qualitative-descriptive approach based on secondary literature and empirical studies published between 2022 and 2025, the review highlights both the opportunities and challenges created by digital transformation. Evidence shows that accessible digital infrastructure, user-friendly platforms, and appropriately deployed assistive technologies can substantially reduce participation barriers for employees with diverse impairments. These tools enhance communication, promote flexible task execution, strengthen autonomy, and support greater productivity and job satisfaction. In many organisations, digitalisation has opened space for hybrid and remote work models that allow employees with mobility, sensory, or chronic conditions to engage fully without facing the constraints of traditional office environments. Despite these benefits, the findings also underscore persistent inequities associated with the digital divide. Differences in access to reliable connectivity, appropriate devices, and ongoing digital-skills training continue to disadvantage employees with disabilities, particularly those in resource-constrained settings. Moreover, inaccessible software interfaces, poorly designed online communication systems, and insufficient organisational support can reinforce exclusion if accommodation policies do not explicitly address digital requirements. The study contends that reasonable accommodation must evolve beyond conventional physical adjustments to include digital, procedural, and organisational elements. This involves investing in inclusive digital design, establishing clear accessibility standards, and building institutional capacity for the adoption and maintenance of assistive technologies. The paper concludes that employers and policymakers have a critical role in strengthening digital inclusion frameworks that support equitable participation. It calls for context-sensitive policies that align with national disability legislation, targeted digital-skills development programmes, and more comprehensive empirical research, especially in regions where digital accessibility remains understudied. By broadening the scope of reasonable accommodation to fully integrate digital considerations, organisations can advance meaningful inclusion and create more resilient and equitable workplaces.

The rapid expansion of digital technologies has reshaped professional environments across the world, including public sector institutions. This article examines how digital device dependency influences workplace culture in the public sector. The study investigates how constant connectivity, multitasking, and device-mediated communication affect organisational behaviour, productivity, and interpersonal relations. A qualitative document analysis was conducted using policy papers, peer-reviewed journal articles, and government reports published in the last five years. Findings show that digital devices have become central to administrative work, with many routine functions now mediated through smartphones, laptops, and communication platforms. These tools improve access to real-time information, simplify reporting processes, and enable quicker communication across units. Despite these advantages, the analysis also highlights several concerns that directly influence workplace culture. One recurring issue is cognitive overload, which arises when employees navigate multiple platforms, notifications, and tasks simultaneously. This pressure contributes to reduced concentration, slower decision making, and higher levels of work fatigue. The review further indicates that constant connectivity has blurred traditional boundaries between work and personal life. Employees often feel compelled to remain reachable after hours, which affects their sense of autonomy and overall well-being. In addition, increased reliance on digital communication has reduced opportunities for direct interpersonal engagement. Colleagues increasingly substitute face-to-face interaction with messages and virtual exchanges, which can weaken trust, collegiality, and shared organisational identity. The analysis reveals that many public institutions lack clear policies regulating digital device use and instead depend on informal norms shaped by managerial expectations and workplace culture. Without deliberate strategies to manage device dependency, public sector environments risk shifting toward fragmented attention, reactive communication patterns, and diminished collaborative practices. To address these emerging challenges, the article recommends strengthening digital literacy, developing guidelines for appropriate device use, and promoting healthier digital habits that support both productivity and meaningful professional relationships.

Digital transformation has become a pivotal instrument for enhancing efficiency, transparency, and accountability in public administration. In post-colonial contexts such as South Africa, however, its adoption intersects with entrenched bureaucratic norms, organisational inertia, and socio-cultural legacies. This study investigates the interplay between digital transformation initiatives, employee behaviour, and governance outcomes in South African public institutions. Drawing on a qualitative desk-based approach and secondary data analysis, the research examines patterns of technology adoption, employee attitudes, and informal practices that shape institutional performance. The results show that digital tools have increased information storage, service tracking, and workflow efficiency, which has helped some departments become more responsive. However, progress is not uniform. The potential benefits of technological investments are still being diluted by informal practices like selective use of digital systems, reliance on parallel manual processes, and preference for face-to-face communication. Lack of incentives for compliance, poor change management, and low levels of digital literacy are all associated with resistance to system protocols. Employee willingness to embrace and maintain digital practices was also found to be significantly influenced by organizational culture and leadership engagement. This research contributes to public administration scholarship by bridging the gap between technology adoption and human behaviour in post-colonial bureaucracies, offering both theoretical insights and practical guidance for enhancing governance outcomes in South Africa’s evolving digital landscape.

This paper examines the shaping of algorithmic accountability within local government service delivery in South Africa, emphasizing the institutional and ethical dimensions that influence responsible AI implementation. A qualitative document-analysis approach was employed, scrutinizing policy frameworks, local government strategy documents, and relevant secondary literature. Findings indicate that although South African local authorities are beginning to integrate artificial intelligence (AI) systems to enhance service delivery, significant constraints persist. These include weak institutional capacity, fragmented governance mechanisms, limited transparency, and the potential to reinforce existing inequalities. Emerging enablers include national policy instruments, opportunities for multi-stakeholder engagement, and the application of algorithmic impact assessments (AIAs) to structure accountability. The discussion underscores the potential of institutional reforms, ethical frameworks, and capacity-building initiatives to strengthen algorithmic accountability within local government contexts. The study contributes to public administration scholarship by extending knowledge on digital discretion and algorithmic governance in the Global South. Practical implications involve actionable recommendations for local governments to operationalize accountability in AI-assisted service delivery. Future research should focus on empirical case studies of individual municipalities to evaluate the performance of accountability mechanisms in practice.

This paper addresses the growing and often unmet mental health needs of the aging population and the pervasive issue of caregiver burnout. It is proposed a novel, multi-tiered AI-powered mental wellness application designed specifically for seniors, their caregivers, and their extended families. The application integrates advanced Natural Language Processing (NLP) for an empathetic conversational AI, Machine Learning (ML) for personalized content and predictive analytics, and a secure, collaborative platform for family care coordination. By providing seniors with accessible, stigma-free emotional support and cognitive stimulation while simultaneously offering caregivers proactive burnout detection and essential organizational tools, this solution aims to bridge critical gaps in geriatric care. The proposed method follows a Human-Centered AI (HCAI) and co-production framework, ensuring the app is not only technologically sound but also usable and trustworthy for its target audience. It presents a hypothetical user journey to illustrate the app's functionality and discuss a robust evaluation methodology alongside key ethical considerations, including data privacy, transparency, and the crucial role of human-AI complementarity.

Gallbladder stones, or cholelithiasis, are a prevalent gastrointestinal disorder posing a significant health risk. Early and accurate detection is crucial for effective patient management and preventing complications like cholecystitis or pancreatitis. Traditional diagnostic methods, primarily ultrasound and CT scans, rely heavily on operator expertise and subjective interpretation. This paper proposes an automated and highly accurate diagnostic framework utilizing an Ensemble Deep Learning approach. It leverages a fusion of pre-trained Convolutional Neural Network (CNN) architectures (e.g., ResNet, VGG, Inception) trained on a publicly available dataset from Kaggle containing medical images (e.g., ultrasound or CT images) of normal and abnormal gallbladders. The ensemble model aggregates the predictions of individual models to enhance robustness, generalization, and diagnostic precision compared to any single model. The proposed system is validated through extensive experimentation, demonstrating superior performance metrics—specifically, high accuracy, sensitivity, and specificity—outperforming state-of-the-art methods in gallstone detection. This research contributes a reliable, objective, and scalable tool for clinical decision support.

This paper presents a novel, multimodal, and explainable artificial intelligence (AI) framework designed to enhance the accuracy and efficiency of respiratory disease diagnosis. By addressing the limitations of traditional diagnostic methods, particularly in complex cases involving older adults with comorbidities, the proposed model synthesizes heterogeneous data sources, including radiological imaging and unstructured clinical text from electronic health records (EHRs). A hybrid deep learning architecture is proposed that leverages a Convolutional Neural Network (CNN) for image feature extraction and a Transformer-based mechanism for multimodal data fusion. The framework is designed with a strong emphasis on interpretability, incorporating Explainable AI (XAI) techniques such as Layer-wise Relevance Propagation (LRP) and Class Activation Maps (CAMs) to provide clinicians with transparent, human-understandable insights into the model's decision-making process. The model's hypothetical performance is benchmarked against existing unimodal and multimodal systems, demonstrating superior accuracy and F1-scores. The paper discusses the critical role of data quality, model generalizability, and the broader socio-technical and ethical considerations necessary for successful clinical adoption. It also discussed case study for a patient.

This paper explores the integration of Artificial Intelligence (AI) into smart classroom environments to enhance the learning experience. It is proposed a novel framework that leverages AI to personalize education, automate administrative tasks, and provide real-time performance analytics. The proposed method utilizes machine learning algorithms to adapt content delivery, identify learning gaps, and offer individualized support. Through this approach, we aim to create a more efficient, engaging, and equitable educational ecosystem. Our analysis demonstrates that an AI-driven smart classroom can significantly improve student engagement, academic outcomes, and teacher efficiency.

Human life expectancy has increased globally, making the understanding of brain aging and associated problems a critical public health priority. This paper examines the multifaceted problems related to human brain aging in later life, focusing on structural, biochemical, and cognitive changes, and their transition from normal aging to pathological conditions like dementia. We review the hallmarks of normal aging, including brain atrophy, white matter changes, and neurotransmitter decline, which contribute to common cognitive deficits such as impaired episodic memory and processing speed. The paper then discusses the major challenge of distinguishing normal age-related decline from the early stages of neurodegenerative diseases. A case study illustrates the clinical presentation of vascular cognitive impairment superimposed on early Alzheimer’s disease. Finally, we explore current research efforts, including lifestyle interventions and advanced neuroimaging and computational techniques like the "brain age gap," as avenues for early detection, intervention, and the promotion of successful cognitive aging. The global demographic shift toward an aging population has intensified the need to understand the biological and clinical complexities of the human brain in its later stages. This paper investigates the multifaceted problem of brain aging, characterized by a transition from physiological decline to pathological neurodegeneration. It is analysed the structural hallmarks, such as cortical atrophy and white matter degradation, alongside the underlying biochemical and cellular drivers, including mitochondrial dysfunction, proteostatic failure, and the "inflammaging" phenomenon. Through a comprehensive review of current research and a clinical case study, we examine the synergy between vascular and neurodegenerative pathologies. Furthermore, we evaluate the efficacy of multi-domain lifestyle interventions—encompassing physical exercise, the MIND diet, and glymphatic clearance—as primary mechanisms for bolstering cognitive reserve. The paper concludes that while aging is a biological certainty, the rate of cognitive decay is highly modifiable, necessitating a proactive, precision-medicine approach to geriatric neurology.

The researchers in this study set out to determine whether there was a connection between the entrepreneurial spirit and output at manufacturing SMEs in Rivers State, Nigeria. The study's primary focus was on how creativity and risk-taking relate to satisfied customers and financial outcomes. Based on the Enterprise Growth Theory, the study employed a survey research design. Its intended recipients were 450 workers from fifteen separate SMEs that produced paint and bottled water. A variety of statistical methods, including multiple linear regression, were applied to the data collected via structured questionnaires by SPSS. Though it cost consumers some pleasure in the near term, the results revealed that taking risks paid out in the end, and being creative paid pay in the ebb and flow of earnings. The study concludes that dimensions of entrepreneurial culture, particularly risk-taking and innovativeness, are critical drivers of organizational performance, and manufacturing SMEs must strategically balance these dimensions to optimize both customer satisfaction and profitability. It was recommended among other things that entrepreneurs and owners in SMEs should take positive risk that will discover modern and better was of satisfying their customers.

This study examines the paradox of Nigeria’s oil wealth and its limited contribution to sustainable development between 2004 and 2024. Despite vast oil revenues, the country continues to experience high poverty, weak institutions, and environmental degradation. Using econometric models such as Cointegration, ARDL, VECM, and panel data regression, the research analyzes the relationship between oil revenue, corruption, and development outcomes. Results show that while oil income positively affects GDP growth, its impact on poverty reduction and environmental quality is negative, largely due to corruption and poor governance. Regional disparities reveal that oil-producing states face worse socio-economic and environmental conditions despite higher revenues. The findings confirm the “resource curse” and underscore the moderating role of corruption in weakening the benefits of oil wealth. The study recommends stronger institutional frameworks, transparent resource management, and strict enforcement of the Petroleum Industry Act (2021) to ensure that oil revenues promote inclusive and sustainable development in Nigeria.

This paper examines the impact of standard costing to the earnings per share (EPS) in the manufacturing industry in Nigeria, by focusing on inventory, labour, and sales associated costs. Its research design corresponds with ex-post facto, where secondary data consist of the annual financial statements of twenty manufacturing enterprises over the eleven years (2013 to 2023). The data is analyzed using panel-data regression, unit-root testing, descriptive statistics and hypothesis testing. These findings show that the expenditures of labour and sales are respectively EPS-positive, but inventory expenditures are EPS-negative. Therefore standard-costing techniques are revealed to enhance the financial performance by streamlining the resources use and directing the companies to the dynamic pricing relationships that are based on the company specific activities.

The abstract of this research paper presents a comprehensive assessment of the physiological workload experienced by ten young women who regularly engage in gym-based physical activities. The study focuses on the evaluation of cardiac responses by analyzing resting, working, and incremental heart rates, which serve as key indicators of exercise intensity and workload. Utilizing standardized formulas, the Cardiac Cost of Work (CCW), Cardiac Cost of Recovery (CCR), and Total Cardiac Cost of Work (TCCW) were calculated to quantify the physiological demands placed on the cardiovascular system during typical gym routines. The results demonstrate that the majority of participants experience moderate to heavy physiological workload, indicating that their exercise sessions are physically demanding and may significantly impact cardiovascular health. This finding emphasizes the importance of monitoring cardiac responses to ensure safe and effective exercise practices. The study provides a practical framework for workload classification, enabling trainers and individuals to tailor gym routines for optimal health benefits while minimizing risks associated with excessive intensity. By integrating objective cardiac measures into exercise prescription, this research contributes to the development of evidence-based strategies for enhancing fitness and safeguarding cardiovascular well-being in young, physically active women.

The present study aimed to investigate the impact of an integrated training programme on ball control and tactical skill performance among high school boys in field hockey. A total of sixty (N = 60) high school boys were selected as subjects and randomly assigned into two groups: an experimental group (n = 30) and a control group (n = 30). The experimental group participated in an integrated training programme comprising technical skill drills, tactical training activities, and basic physical conditioning for a duration of eight weeks, while the control group followed their regular physical education and sports training routine. Ball control and tactical skill performance were assessed using standardized field hockey skill and game-based performance tests before and after the training intervention. Paired t-tests and independent t-tests were employed to analyze within-group and between-group differences. The results indicated a statistically significant improvement in ball control and tactical skill performance in the experimental group compared to the control group. The control group did not show significant changes. The findings suggest that integrated training is an effective method for enhancing technical and tactical abilities among high school boys in field hockey and can be effectively implemented within school-level training programmes.

This study analyzes a compiled dataset of political killings in Malabar and adjoining districts of Kerala between 1978 and 2018. The dataset summarizes victims (&#39;killed&#39;) and accused persons by political affiliation, religion, and (where recorded) caste/community. We present descriptive patterns and explicitly document missingness in caste identification, emphasizing that caste breakdowns apply only to the recorded subset. To contextualize the observed patterns, we append a demographic overview of northern and mid-Kerala panchayath using district-level religion shares, official SC/ST shares, and published community-composition estimates for major Hindu groups (including Thiyya and Nair).

The growing environmental concerns associated with single-use plastic packaging have intensified the search for sustainable and biodegradable alternatives derived from renewable resources. In this study, a green composite material was developed using recycled paper waste and coconut fibre as reinforcement, bonded with a starch-based adhesive matrix, for potential application in lightweight packaging. Composite sheets of nominal thicknesses 1.5 mm, 3 mm, and 5 mm were fabricated through pulping, fibre blending, slurry casting, moulding, and ambient drying. The physical performance of the composites was evaluated through water absorption testing in accordance with ASTM D570, thickness uniformity measurements, and qualitative solubility assessment. The results revealed a strong dependence of water absorption on composite thickness, with maximum water uptake values of 252.63%, 246.19%, and 185.32% for 5 mm, 3 mm, and 1.5 mm specimens, respectively. The high moisture sensitivity was attributed to the hydrophilic nature of lingo cellulosic fibres and the porous structure formed during manual fabrication. Surface-coated specimens exhibited reduced water absorption, demonstrating the effectiveness of barrier layers in improving moisture resistance. Solubility tests confirmed rapid disintegration in aqueous media, indicating high biodegradability of the developed composite. Thickness variation was found to be within acceptable limits for manually produced sheets. Overall, the study demonstrates the feasibility of utilizing paper waste and coconut fibre to produce an environmentally benign packaging material suitable for dry and lightweight applications. The findings highlight both the potential and limitations of starch-bonded natural fibre composites, particularly with respect to moisture resistance.

This study assessed the barriers to the adoption and sustainability of technology integration in teaching and learning processes in secondary schools within Abuja Municipal Area Council (AMAC), Abuja. A mixed-methods research design was employed, combining quantitative and qualitative approaches to provide a comprehensive understanding of the research problem. Data were collected from 440 respondents, comprising 400 students who completed structured questionnaires and 40 teachers who participated in semi-structured interviews. Quantitative data were analysed using descriptive statistics, while qualitative data were analysed thematically. The findings revealed that although most schools have introduced basic digital tools such as computers and projectors, the frequency of classroom technology use remains low, limiting sustained integration. Students reported increased interest, participation, and improved understanding when technology was used; however, these benefits were unevenly experienced across schools. Significant barriers identified include inadequate access to digital devices, poor internet connectivity, insufficient teacher training, lack of technical support, and disparities between public and private schools. The study concludes that while technology integration holds significant potential to enhance teaching and learning, its effectiveness and sustainability depend on addressing systemic, infrastructural, and human-capacity constraints. The study recommends sustained investment in ICT infrastructure, continuous teacher professional development, and supportive institutional policies to promote equitable and long-term technology integration in secondary schools within AMAC, Abuja.

The increasing prevalence of herbicide-resistant weeds, environmental contamination, and declining agroecosystem biodiversity highlights the urgent need for safer and more sustainable weed management strategies. This study reports the development of a cell-free mycoherbicidal broth derived from Fusarium sp. FGCCW#16, designed to overcome the biosafety concerns and field-performance variability associated with live fungal inoculants. The fungus was cultivated in a 10 L stirred-tank bioreactor under controlled pH, dissolved oxygen, agitation, and antifoam conditions to optimize extracellular phytotoxic metabolite production. Post-fermentation, a multi-step clarification process comprising centrifugation and sterile membrane filtration yielded a propagule-free, metabolite-rich broth. Stabilization via pH adjustment and 5% (v/v) glycerol supplementation effectively preserved herbicidal activity during storage. Greenhouse bioassays demonstrated rapid and selective suppression of seven target weed species?Lantana camara, Parthenium hysterophorus, Hyptis spp., Xanthium spp., Sida acuta, Cassia tora, and Antigonon leptopus?inducing chlorosis and necrosis within 72 h, while non-target crops remained unaffected. High-performance liquid chromatography (HPLC) analysis confirmed consistent metabolite profiles across independent batches, highlighting process reproducibility and formulation robustness. By eliminating viable fungal propagules while retaining herbicidal activity, this cell-free formulation reduces ecological risk and enhances predictability of application. Collectively, these findings establish a scalable, safe, and reproducible platform for fungal metabolite-based mycoherbicides, bridging bioreactor-level production with practical applications in sustainable weed management.

This study examines the impact of government taxation policies on the performance and sustainability of Small and Medium-Sized Enterprises (SMEs) in the Abuja Municipal Area Council (AMAC), Abuja. Recognising SMEs as critical drivers of economic growth, job creation, and poverty alleviation, the research investigates how tax compliance, multiple taxation, tax rates, and access to tax incentives influence business profitability and operational sustainability. A descriptive survey design was employed, targeting 180 registered SMEs across key commercial areas of AMAC. Data were collected using structured questionnaires and analysed through descriptive statistics and chi-square tests to test the research hypotheses. Findings reveal that tax payment significantly affects SME profitability, with high tax rates and multiple levies posing substantial financial and administrative burdens. Additionally, limited accessibility to tax incentives was found to negatively impact SMEs sustainability, while inadequate tax education and low adoption of digital tax systems hinder compliance. The study concludes that current taxation policies, though intended to generate revenue, often constrain SME growth and formalisation. It recommends harmonised tax structures, progressive and capacity-based tax assessments, improved access to incentives, and targeted education and digital support programs to enhance SMEs&#39; compliance, profitability, and sustainability in AMAC. Implementing these measures will strengthen SMEs? contributions to local economic development.

There is still need to improve the tracking error and robustness of the control system in the presence of disturbance because the existing systems or technique doesn?t meet the performance criteria for the system with regards to settling time and overshoot as high-precision satellite attitude control system (SACS) is critically demanded. In order to achieve this, the transfer function models of amplifier, actuator, and satellite structure for determining the transfer function a LEO satellite yaw-axis attitude were obtained. This work presented a yaw-axis ACS for LEO satellite using Proportional Integral and Derivative Tuned Compensator (PID-TC). The compensator was designed using the control system toolbox of MATLAB/Simulink based on PID Tuning design method using response time tuning technique with interactive (adjustable performance and robustness) design mode at a bandwidth of 44.5 rad/s. The compensator was added to position control loop of yaw-axis. Simulations were carried out in MATLAB environment for four separate cases (uncontrolled, PID-D, PID-TC-D, and LQR-D) by applying unit forced input to examine the various step responses. Initial simulation without the inclusion of the compensator (PID-TC) in the control loop resulting in rise time of 2.16 s, settling time of 22.14 s and 38.63% overshoot. Thus, in terms of the performance criteria defined for the system, all conditions were not met specifically the settling time and the overshoot. Hence, a PID-TC controller was designed and introduced into the system, which resulted in transient and steady-state performances of the system being characterized by rise time of 3.82, settling time of 7.30 s, overshoot of 3.88%, and steady-state error (0). The robustness of the designed PID-TC was examined by introducing a unit disturbance load torque and the step response simulation plot indicated that the achieved reduced rise time (1.82 s) and settling time (6.90 s) but with slight deterioration in smoothness and stability (as the overshoot was increased to 4.14%).

In this paper we discussed some parameters by which satisfaction level of Tourists may be increase then it will increase the footfall of Tourists and then it will impact to increase the economy as well as the image of the state in the Country and world. For the Study we have taken the data of Rajesthan State, which involve the variation of Profession, Age, Education, Gender, Marital status, living status etc. We have used Chi Square test for the analysis of data. It may be beneficial for the society as an example of maintaining service facility for Tourists at any tourism place for the buildup good image and better economy with the development of market as the need of peoples from various places and different community. In order to identify important tourist service facilities that determine the overall tourist satisfaction or one may say that the factors or facilities that attract more number of tourist and to get an idea which facility have to be improved to attract the inflow of tourist.

The integration of renewable energy sources with conventional power generation has fundamentally transformed modern power systems, creating complex mixed generation environments. This paper presents a comprehensive analysis of power system stability challenges in hybrid power networks incorporating conventional synchronous generators, wind turbines, solar photovoltaic systems, and energy storage systems. We examine frequency stability, voltage stability, rotor angle stability, and small-signal stability in the context of high renewable penetration. Advanced control strategies including virtual synchronous generator technology, coordinated damping controllers, and predictive stability enhancement techniques are evaluated. Case studies demonstrate that properly coordinated control systems can maintain stability even with renewable penetration levels exceeding 60%. The findings provide critical insights for power system operators and planners navigating the energy transition.

The COVID-19 pandemic exposed major gaps in healthcare systems, such as the shortage of doctors, nurses, medical equipment, and essential medicines. Because of these limitations, many people started taking medicines on their own without proper medical advice, which often made their health conditions worse. With the growth of technology and data-driven solutions, there is a growing need for systems that can assist both patients and healthcare professionals in making better treatment decisions. This work focuses on building a drug recommendation system that can help reduce the workload of medical specialists by suggesting appropriate medicines based on patient feedback. Using sentiment analysis, the system examines user reviews of various drugs to understand public opinion about their effectiveness. Machine learning algorithms are then applied to predict the overall sentiment and recommend the most suitable drug for a specific disease or condition.

Ensuring the safe storage, accurate tracking, and timely availability of blood remains a major challenge in healthcare systems, particularly during medical emergencies where real-time information is critical. This research addresses the question of how Internet of Things (IoT) technologies can be effectively utilized to improve blood bank management by enabling continuous monitoring, automated identification, and efficient communication between blood banks and hospitals. Blood units must be stored within strict temperature limits to preserve their quality, and manual monitoring methods are often unreliable and prone to human error. Additionally, traditional inventory systems lack real-time visibility and accurate traceability of blood units. To overcome these challenges, this study proposes an IoT-based blood bank management system using an ESP32 microcontroller integrated with a temperature sensor and RFID technology. The system continuously monitors storage temperature, uniquely identifies blood bags using RFID tags, and transmits real-time data to a centralized web server via Wi-Fi. A web-based application displays sensor data, blood inventory status, and enables hospitals to place blood orders online.

Accurate weather forecasting and climate analysis are essential for effective planning in agriculture, disaster management, and environmental sustainability. This paper presents a Python-based framework for weather forecasting and climate analysis using machine learning techniques. The proposed system utilizes historical meteorological data, including temperature, humidity, rainfall, wind speed, and atmospheric pressure, to train predictive models. Various machine learning algorithms are implemented and evaluated to forecast weather conditions and identify climate trends. Python libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib are used for data preprocessing, model development, and visualization. The framework enables efficient handling of large datasets, improves prediction accuracy, and supports comparative analysis of different models. Experimental results demonstrate that machine learning-based approaches outperform traditional statistical methods in capturing complex weather patterns. The proposed system provides a scalable and flexible solution for weather forecasting and climate analysis, supporting data-driven decision-making for environmental monitoring and climate research.

The greatest challenge in blood health is distinguishing between conditions defined by uncontrolled, dangerous bleeding (like inherited coagulopathies, exemplified by Hemophilia A and B, or HA/HB) and those marked by chronic cell destruction and dangerous clotting (such as Sickle Cell Disease, or SCA). However, the most life-threatening scenarios involve acquired syndromes that manifest a disturbing overlap, where patients suffer both massive bleeding and widespread clotting, including Disseminated Intravascular Coagulation (DIC), Thrombotic Microangiopathies (TTP/HUS), and Paroxysmal Nocturnal Hemoglobinuria (PNH). Accurate and immediate diagnosis demands the use of highly specific tools?from Factor Assays for congenital defects to measuring ADAMTS13 activity for TMA, and advanced flow cytometry for PNH clones. Getting the diagnosis right is the absolute foundation for effective, life-saving management, which ranges from simple Factor replacement to urgent plasma exchange (PEX) and targeted complement inhibition.

The definitive diagnosis and grading of brain tumours rely on the meticulous examination of histopathology whole-slide images (WSIs) by pathologists. This manual process is highly skilled, time-consuming, and suffers from inherent inter-observer variability, which can delay treatment initiation. This paper addresses these limitations by proposing a novel, robust Deep Learning (DL) framework for the automated classification and grading of primary brain tumours from digitized histopathology images. Our method utilizes a multi-scale attention-based Convolutional Neural Network (CNN) architecture to effectively handle the vast size and intricate cellular heterogeneity characteristic of WSIs. The proposed framework integrates a patch-level classification system with a WSI-level decision aggregation mechanism enhanced by a spatial attention module, allowing the model to focus on diagnostically significant regions (e.g., areas exhibiting high cellular atypia or mitotic activity). We detail the architecture, training methodology, and evaluation metrics. The results demonstrate that the proposed model achieves superior classification accuracy compared to standard transfer learning approaches, positioning it as a powerful and objective tool to assist pathologists in rapid, accurate, and consistent clinical diagnosis.

Uncontrolled driving behaviors, characterized by speeding, red-light running, and distracted operation, represent a major contributor to the escalating global crisis in pedestrian fatalities, particularly at urban intersections. Traditional fixed-time and purely vehicle-centric adaptive traffic control systems lack the necessary responsiveness and predictive capability to mitigate the high-risk conflicts arising from these unsafe driving practices. This paper proposes a novel Deep Reinforcement Learning (DRL) framework for dynamic traffic signal control, specifically optimized to prioritize pedestrian safety over mere vehicular throughput. The proposed method utilizes multi-sensor data fusion (LIDAR, video feeds, and connected vehicle data) to construct a comprehensive state representation that includes real-time risk factors, such as the probability of a driver running a red light or a pedestrian crossing illegally. The DRL agent learns an optimal policy by maximizing a reward function that heavily penalizes potential pedestrian-vehicle conflicts and minimizes pedestrian wait times, thereby reducing the impetus for rule violation. We present the DRL architecture, state-action space, and a simulated case study demonstrating that this predictive, safety-aware control paradigm significantly reduces conflict incidents and enhances overall safety metrics compared to conventional and vehicle-only adaptive systems.

This paper provides an exhaustive analysis of the application of fractional calculus in mathematical economics, arguing for its necessity in modelling real-world economic phenomena characterized by long-term memory and non-local interactions. Classical economic models, largely built upon integer-order differential equations, suffer from a fundamental limitation often termed "amnesia," as they assume instantaneous, local dependencies and disregard the influence of historical states on current behaviour. Drawing from a comprehensive literature review, the analysis establishes fractional calculus as the mathematical framework for a new "Memory Revolution" in economics. A rigorous conceptual foundation is provided, differentiating between key fractional operators like the Riemann-Liouville and Caputo derivatives and offering a compelling economic interpretation of the fractional order as a measure of fading memory. To demonstrate its utility, a fractional-order extension of the canonical Solow-Swan growth model is formulated. Through analytical and numerical methods, the analysis shows that the fractional model significantly affects the trajectory and long-term stability of capital accumulation, providing a more flexible and realistic representation of economic dynamics. The empirical evidence, including superior data-fitting performance in GDP modelling, validates the approach. The paper concludes by addressing the challenges of this nascent field and outlining future research directions, positioning fractional mathematical economics as a vital and emerging discipline.

The load speed control of the heavy duty has turbine is the focus of this research work. The method employed in work is load-frequency control of the heavy-duty gas turbine using PID control, fuzzy logic control and the Fuzzy-PD+I control techniques through their designed controllers. This study investigates the performance of different controllers for load control of heavy-duty gas turbines. A simulation study was conducted using MATLAB/Simulink to evaluate the performance of the controllers. The gas turbine model used was a single-shaft heavy-duty gas turbine with a rated power of 33.4 MW. The controllers were designed and tuned to achieve optimal performance. The controllers used are PID, Fuzzy, and Fuzzy-PD+I. The results show that the FUZZY PD+I controller performs better than the PID and Fuzzy controllers in terms of load management and stability. The study concludes that the Fuzzy-PD+I controller is a suitable choice for load control of heavy-duty gas turbines due to its improved load control and stability. with rise time of 2.6660s, settling time of 5.5726s and overshoot of 2.3082% at 50% load torque, and rise time of 2.6517s, settling time of 7.3710s and overshoot of 3.1252% at 100% load torque. It recommended the use of Fuzzy-PD+I controllers for load control of heavy-duty gas turbines, it also optimize the controller gains using simulation studies, and implement the controller in a real-time environment.

Plant diseases are one of the major threats to global food production. If these diseases are not identified at an early stage, farmers may suffer heavy crop losses, which can affect food supply and farmers? income. At present, disease detection is mostly done through manual observation of plant leaves, which is time-consuming, labor-intensive, and often inaccurate.
To overcome this problem, we developed an intelligent system using Deep Learning, specifically Convolutional Neural Networks (CNNs), to automatically detect plant diseases. The system is trained using thousands of images of both healthy and infected plant leaves. By learning patterns such as color changes, spots, and texture variations, the model is able to identify different plant diseases accurately, similar to how an expert examines crops. The results show that the proposed system is highly accurate and much faster than traditional manual inspection. It can successfully identify multiple plant diseases across different crops. This approach provides farmers with a quick and reliable way to detect diseases at an early stage, allowing timely treatment. As a result, it helps reduce crop loss, minimize the use of harmful chemicals, and supports sustainable and efficient agricultural practices.

Rajasthan is witnessing a silent revolution in higher education. According to the 2024?25 Annual Report of the Department of Higher Education, 7.25 lakh girls enrolled in colleges across the state compared to 5.86 lakh boys. For every 100 boys, 124 girls are now pursuing higher education - a remarkable leap from 2015, when the ratio was 97 to 100.This demonstrates that Rajasthan has emerged as a leader in gender-equitable higher education through integrated policy innervations combining institutional expansion, financial support system and targeted scholarship schemes.. The GER according to AISHE survey report of 2021-22 says that Male GER is 26.1 and Female GER is 26.0.which indicates that girls in Rajasthan have made significant progress in gross enrolment ratio (GER) in higher education drawing almost an equivalent with boys, thus attaining almost 100% gender neutrality in Higher education The achievement is attributed to a number of positive steps taken by the state government by introducing several schemes favoring girl?s education. KB KHOTRI an Educationist said ?certainly it is the result of positive efforts made by the government at all level of education the state is implementing multiple schemes that aim to further the education of girls and women special schools, colleges for girls, financial aid, free bicycles and the travel vouchers, no tuition fee for the girls studying in the colleges with the growing awareness among parents have contributed in attaining the success.. It is evident that young people, especially women, are ready to drive the state?s future.The Present paper is an Exploratory qualitative study to gain a contextual understanding of the Rajasthan?s government?s Synergistic impact which is a combination of mobility, infrastructure and financial support. initiatives like opening new girls colleges in the state demonstrates the infrastructure and kalibai Bheel Madhavi Scooty Yojana represents mobility and CM scholarship represents financial assistance by the state government for women empowerment in HEIs. The study will employ a case study design, focusing on the specific context For Scholarship like Madhvi Scooty Youjna. A micro level study has been conducted in the government girls college, Rajgarh. Data used for this study is from 2019-2025(Five Years ). of government gills college Rajgarh churu. Study highlights that from 2019 onwards government has taken the girl education seriously and higher education department has initiated some targeted programme for the upliftment of the status of women in society. New Words ? Higher Education, Initiative ,Scholarship (Kalibai Madhavi Scooty Yojna -KMCSY)

South Africa continues to experience persistently high unemployment despite decades of policy reform and economic restructuring. Public discourse increasingly frames this crisis as self-created, often attributing joblessness to labour migration, skills mismatch, or the alleged unwillingness of citizens to accept certain forms of work. This article reassesses unemployment in South Africa by situating it within a segmented labour market shaped by historical inequalities, contemporary migration dynamics, and a political economy that produces exclusion rather than absorption. Using a qualitative secondary data analysis of national labour force surveys, policy documents, and recent empirical studies, the paper interrogates the structural drivers of unemployment and the differentiated allocation of work across sectors. The findings demonstrate that migrant labour, both documented and undocumented, occupies specific labour market segments characterised by precarity, low wages, and weak regulation, rather than displacing South African workers in a uniform manner. Unemployment among citizens is shown to be more closely linked to deindustrialisation, spatial inequality, educational stratification, and employer preferences for flexible labour. The study further reveals how political narratives around migration obscure deeper governance and policy failures while reinforcing social fragmentation. The article contributes to debates on unemployment by moving beyond binary explanations of choice versus exclusion and by highlighting the need for labour market reform that addresses structural segmentation rather than scapegoating vulnerable groups. Policy implications include the strengthening of labour inspection regimes, targeted skills development linked to sectoral demand, and a more coherent migration governance framework that aligns with employment policy.

This article investigates the ongoing phenomenon of political defections and the rise of breakaway parties in South Africa, emphasising how these patterns have weakened democratic accountability over time. While party switching once operated within a formal legal framework under the country?s floor-crossing provisions, its legacy continues to shape political behaviour long after its abolition. By drawing together historical developments, legislative reforms, and recent scholarly debates, the paper examines how mid-term defections and splinter-party formation disrupt the relationship between voters and the representatives elected to speak on their behalf. The study adopts a qualitative design grounded in document analysis, focusing on constitutional amendments, parliamentary reports, and contemporary academic literature. This approach enables a detailed exploration of how defection patterns emerged, who benefitted from them, and how they have shifted the balance of political power. The findings show that defections tended to advantage dominant parties while weakening smaller political formations, often precipitating their decline or disappearance. At the same time, the practice fostered a culture of political mobility linked more to career preservation than to principled ideological shifts, contributing to declining public trust in democratic institutions. The article argues that South Africa?s closed-list proportional representation system, especially when paired with permissive defection rules, creates structural incentives that disconnect politicians from direct voter accountability. The study concludes by underscoring the need for electoral reforms aimed at restoring this accountability and calls for further empirical research into patterns of political mobility in the post-2009 era.

Youth constitute a demographic majority in South Africa, yet their representation in parliamentary decision making remains persistently low. This disconnect raises serious concerns for intergenerational justice and the long-term sustainability of democratic governance. The purpose of this article is to examine the extent and implications of youth under-representation in South Africa?s Parliament and to assess how this imbalance affects democratic legitimacy, policy responsiveness, and future-oriented governance. The study adopts a qualitative desktop research design, drawing on secondary data from parliamentary records, electoral statistics, and recent peer-reviewed literature on political representation, intergenerational justice, and democratic sustainability. The analysis reveals a significant age asymmetry in parliamentary leadership, with legislative authority concentrated among older cohorts whose policy priorities may not adequately reflect the lived realities of younger citizens. This pattern weakens substantive representation, undermines youth political trust, and constrains the state?s capacity to address long-term challenges such as unemployment, education reform, and climate vulnerability. The article argues that youth exclusion is not merely a representational deficit but a structural democratic risk that compromises intergenerational equity. The findings contribute to debates on democratic renewal by demonstrating that inclusive age representation is central to sustaining democratic legitimacy in ageing political institutions governing youthful societies. The study concludes by proposing institutional and party-level reforms aimed at strengthening youth representation as a democratic imperative rather than a symbolic gesture.

This study proposes the design and development of an Internet of Things (IoT)-enabled smart e-mirror that integrates a traditional mirror function with Artificial Intelligence (AI) and real-time data display. In today?s fast-paced lifestyle, people often lack time to stay updated with real-time information such as weather forecasts, news updates, schedules, and reminders while managing their daily routines. Existing smart devices require separate attention, making multitasking inconvenient. The proposed system utilizes a Raspberry Pi 3 as the core processor, a two-way mirror, an HDMI monitor, and the Google Assistant SDK for hands-free voice interaction. The solution incorporates OpenCV for handling the display interface and connects to APIs (OpenWeatherMap, NewsAPI) to fetch real-time updates. The system is designed to provide a personalized, interactive interface that saves time, assists in multitasking, and is scalable for future HealthTech applications, such as health monitoring and medicine reminders. This project aims to integrate multiple utilities into one physical object, differentiating it from traditional mirrors and separate smart devices.

Maintaining maternal safety during pregnancy re quires uninterrupted observation of physiological conditions and immediate support during critical events. This work proposes a wearable prenatal safety band capable of continuously tracking essential health indicators while providing instant emergency notification. The system is implemented using an ESP32 microcontroller connected to sensors that monitor heart rate and body temperature. To support emergency response, a GPS unit is incorporated for real-time location identification, and a dedicated SOS switch enables user- initiated alerts. When sensor values exceed defined safety limits or when the SOS switch is activated, the device automatically transmits health information and current location details to registered contacts via the Telegram communication platform. Real-time system status and health data are displayed using an OLED screen. The developed wearable emphasizes simplicity, affordability, and mobility, making it suitable for deployment in rural and resource constrained environments and contributing to faster medical response and improved prenatal care delivery.

Distance Learning is considered effective tool for gender equality and empowerments for balancing burden of assigned gender roles in particular for female students. The paper set out to examine the role of distance learning as a platform of promoting gender equality and women empowerment focusing TICD blended Model. Questionnaire survey and documentary review methods were employed in data collection. A quantitative data were analysed using Statistical Package for Social Sciences (SPSS 16th version). While qualitative information was analysed using content analysis. The study observed that majority of the respondents (96.6%) recognized the benefits of blended model in their economic, political and social wellbeing. Mostly TICD blended model was attributed to the expected positive outcome such as expanding the level of education, increase income and leadership after completing the course. The study concludes that studying through Distance Learning provides student with flexibility of studying while working and handling family related matters. Thus, awareness about uses the enhancing model should be provided regularly so as to attract a good number of Tanzanian to pursue their study at the TICD.

Digital life preservation uses AI to convert personal memories into interactive, searchable life narratives that can be passed to future generations. Although existing lifelogging and digital archiving systems capture daily activities, they often lack narrative structure, semantic organization, and long-term legacy value. With advances in semantic indexing, vector databases, multimodal processing, and generative AI, it is now possible to retrieve and present personal experiences in richer, more meaningful ways. This project proposes an AI-driven system that ingests text, audio, and images, automatically summarizes significant events, embeds them for semantic search, and securely stores metadata for long-term access. User queries retrieve relevant memories and generate coherent narratives, creating a dynamic and enduring digital archive. The approach supports intergenerational storytelling and preserves human experiences in accessible, contextually meaningful forms.

This paper presents a theoretical review.Presenting references such as the Basel problem, addressing how to apply the Schr?dinger equation to a wave function. The intention is to reference the geometric construction that Euler used to build his solution to the Basel problem. Likewise, a brief reference to Trigonometric Transformations, such as Integration by Parts in Differential Calculus and Integral Calculus, is also included. With this, one has the condition... In order to create epistemological and didactic conditions for solving exercises with the Wave Function in the Schr?dinger Equation, it is known in University Education that the Wave Function is calculated in the Schr?dinger Equation; however, the necessary epistemological analysis is not given, such as the Analysis of the Wave Function, that is, What is it? Or What is the Meaning of this Wave Function? With a Mathematical and Conceptually Epistemological approach in Physics. This article is a starting point as a reference for conceptual approach and analysis with various mathematical tools.

Communication barriers faced by hearing- and speech-impaired individuals significantly limit their interaction with the hearing population. Sign language serves as a primary medium of communication; however, the lack of widespread understanding creates challenges in real-time conversations. This paper presents a vision-based real-time assistive framework for sign language understanding using deep learning techniques. The proposed system employs computer vision to capture hand and body movements through a camera and utilizes MediaPipe for accurate landmark extraction. Temporal gesture patterns are modeled using a Long Short-Term Memory (LSTM)?based deep learning network, enabling effective recognition of dynamic sign sequences. The recognized signs are translated into corresponding text outputs in real time, facilitating seamless communication. Experimental results demonstrate that the system achieves high recognition accuracy with low latency under varying lighting and background conditions. The proposed framework is cost-effective, scalable, and suitable for real-world deployment, making it a practical assistive solution to bridge the communication gap between sign language users and the general population.

This paper presents, an integrated software platform designed to provide comprehensive interview preparation through the convergence of resume analysis, behavioral assessment, and adaptive question generation. The system employs machine learning techniques for gesture recognition and emotional analysis during mock interviews while leveraging natural language processing for skill gap identification and job-market analysis. The architecture utilizes a microservices-based approach with a React-based frontend, FastAPI backend, and PostgreSQL database via Supabase for scalability and real- time data persistence. By incorporating multiple analytical dimensions?technical competency, non- verbal communication patterns, and skill-market alignment?InterviewEase aims to bridge the gap between candidate preparation and employer expectations.

The fast and nonlinear dynamics associated with these converters; various difficulties have to be dealt with while controlling them. Thus, designing a controller with high response speed and robust capability is critical to guarantee efficient operation for power electronic converter. In this work, performance response improvement of power electronic converter using cascade controllers has been presented. The transient response characteristics of the system in the open-loop showed that it has a rise time of 0.000405 s, settling time of 0.00443 s, and overshoot of 42.3%. The high overshoot can be associated with the inability of the buck converter to handle nonlinearity in system dynamic process hence the outrageous oscillation and extremely peaking in output voltage. Therefore, a cascade control system based on combined Fuzzy-PID and PID controllers was designed and applied into the buck converter. The simulation results showed that the cascade control scheme offered enhanced rise time of 1.88e-05 s, settling time of 3.02e-05 s, and overshoot of 1.36%. Further analysis of the design controller to test for robustness proved that it was capable of handling change in operational parameters with fast tracking, stable and smooth response. When compared to the open-loop and PID controller, the cascade controller largely improved the overall system performance. With this outstanding performance, practical application of the designed control will be worthwhile to further ascertain its effectiveness.

Low tax revenue performance remains a major fiscal challenge in Nigeria, largely due to inadequate tax literacy, which weakens voluntary compliance and limits effective revenue mobilisation. While previous studies have focused mainly on enforcement and administrative control, limited attention has been given to the combined effect of different dimensions of tax literacy, especially at the sub-national level. This study examines how taxpayers’ knowledge of tax obligations, understanding of filing procedures, ability to compute tax liabilities, awareness of incentives and reliefs, and knowledge of penalties and sanctions influence tax revenue performance in Nigeria. The study adopts a survey research design and covers taxpayers and tax administrators in the state capitals of South-West Nigeria, including Abeokuta, Akure, Ado-Ekiti, Ibadan, Lagos, and Osogbo. Participants include registered small and medium-sized enterprises, self-employed individuals, corporate tax officers, tax officials, and certified tax consultants. A sample size of 180 respondents is selected using Yamane’s formula at a 95 per cent confidence level through stratified random sampling. Primary data are collected with a structured questionnaire and analysed using descriptive statistics, correlation analysis, and ordinary least squares regression. The findings show that all dimensions of tax literacy examined in the study have positive and statistically significant effects on tax revenue yield. This suggests that improved tax knowledge and skills encourage voluntary compliance and enhance revenue performance. Based on these results, the study concludes that strengthening tax literacy is essential for effective revenue mobilisation. It recommends sustained taxpayer education, simplified filing and computation processes, clear communication of incentives and sanctions, and continuous stakeholder engagement as practical strategies for improving tax revenue performance in Nigeria.

The journey towards Mauritian independence, formally achieved on 12 March 1968, is often narrated through the frameworks of constitutional conferences, the rise of political parties, and the pivotal role of visionary leaders like Sir Seewoosagur Ramgoolam. However, beneath this political superstructure lay a profound socio-cultural foundation that sustained, inspired, and directed the struggle: the culture of the Girmitiyas. The term Girmitiya, derived from the Hindi word ‘girmit’ (an indigenised corruption of the English ‘agreement’), refers specifically to the indentured labourers who embarked from British India to far-flung colonies under a system of fixed-term contracts after the abolition of slavery. Between 1834 and the early 20th century, nearly half a million of these labourers arrived in Mauritius, the first and a major recipient of this diaspora. Theirs was a culture forged in the crucible of trauma uprooted from homeland, subjected to the kala pani (black waters) voyage, and thrust into a brutal plantation regime. Yet, from this experience, they created a resilient, syncretic, and assertive cultural world. This article argues that Girmitiya culture was not a mere backdrop to the freedom struggle but its essential substratum, providing the tools for community preservation, fostering a collective consciousness that transcended narrow identities, and evolving into explicit platforms for political mobilisation and anti-colonial resistance. The struggle for freedom in Mauritius was, in a fundamental sense, a struggle for the recognition and rightful place of the Girmitiya legacy.

The National Education Policy (NEP) 2020 aims to transform teacher education in India by introducing a structured and multidisciplinary approach. A key feature is the introduction of a four-year integrated B.Ed. program to enhance pedagogical training and subject competency. The policy also emphasizes continuous professional development (CPD), the integration of digital learning tools, and the establishment of National Professional Standards for Teachers (NPST) to ensure uniform quality in teacher education. NEP 2020 presents numerous opportunities, such as improved teacher quality, increased collaboration with higher education institutions, and greater use of technology in teacher training. However, several challenges hinder its effective implementation, including infrastructure deficits, faculty shortages, resistance to change, and the digital divide. To address these issues, the study recommends increasing resource allocation, bridging the digital gap, strengthening policy implementation frameworks, and enhancing CPD opportunities for educators. Investing in ICT infrastructure, adopting competency-based teacher education, and ensuring effective monitoring mechanisms are crucial steps in overcoming barriers. Public-private partnerships and government initiatives must work in tandem to facilitate successful implementation. By addressing these challenges through strategic planning and continuous assessment, NEP 2020 has the potential to transform teacher education, ensuring a well-trained and competent teaching workforce that meets 21st-century educational demands. The success of NEP 2020 will largely depend on the collaborative efforts of policymakers, educators, and institutions in fostering a robust, inclusive, and technology-driven teacher education system.

The present research study aims to analyze the impact of sports activities on the emotional stability of students. In the contemporary educational environment, students are exposed to various psychological, emotional, and social pressures, which significantly affect their emotional stability. Emotional stability is an essential component of students’ personality development, mental health, and academic success. In this context, sports activities can serve as an effective means for promoting emotional balance and psychological empowerment among students. In the present study, the survey method was adopted, and school-level students were selected as the sample. Sports participation was considered as the independent variable, while emotional stability was taken as the dependent variable. For data collection, an Emotional Stability Scale and a Sports Participation Questionnaire were used. The collected data were analyzed using statistical techniques such as Mean, Standard Deviation, t-test, and Pearson’s Correlation. The findings of the study revealed that students who regularly participated in sports activities exhibited higher levels of emotional stability compared to those who did not participate in sports. Moreover, a positive and significant correlation was found between sports participation and emotional stability. The study concludes that sports activities play a crucial role in enhancing students’ emotional development and mental balance. Therefore, sports activities should be an integral part of school education to ensure the holistic development of students.

This study investigates the awareness, adoption, and implementation challenges and opportunities of Artificial Intelligence (AI) in teaching practices among instructors in Tanzanian public and private higher learning institutions (HLIs). Using a mixed-methods approach, the study examined differences in AI awareness levels, the extent of AI adoption, and institutional readiness. Results revealed no significant differences in most awareness indicators between public and private HLIs, except for foundational knowledge, which was higher in public HLIs. The extent of AI adoption was generally low across both sectors, with weak predictive influence from institutional support and personal willingness. Significant differences were observed in implementation challenges and opportunities public HLIs faced greater infrastructural and policy constraints, while private HLIs demonstrated slightly higher readiness and optimism toward AI. These findings highlight the need for targeted interventions, including investment in infrastructure, AI-focused professional development, and policy support. Strengthening institutional capacity and fostering a culture of innovation are critical to enhancing AI integration and maximizing its potential in Tanzanian HLIs.

Standard methods of extraction, separation and chemical characterization of flavonoid compounds are described by Tracey1 as well as Harborne2. Systematic procedure for the flavonoid identification employing chromatographic methods of analysis and chemical and spectral methods of identification have been explained by Geissman3, Harborne4, Mabry5 et al, Jay6 et al, Markhand7 and Linskens and Jackson8. The conventional chromatographic methods like column, paper and thin layer are still in use for separation and purification of the flavonoid compounds Increase in speed and efficiency in the separation of mixtures had been achieved by high pressure liquid chromatography (HPLC). Among the separation techniques applied to flavonoids HPLC has the advantage over to other techniques9 in regard to sensitivity, rapidity and easy quantification. Hosttettman and Hosttetman10 reviewed the relevant literature on HPLC upto 1980. A few other publications in this field include Rf values by Daigle and Conkeston11, use of Bondpak C18 with MeOH-HOAC-H2O as developing system with two pumps by casteele12 et al, analytical problems in HPLC by Bankova13 et al, Tamma14 et al and Barberan15 et al. The application of HPLC combined with FABMS in the structural elucidation of anthocyanin pigments was explained by J.B.Harborne and R.J. Grayer16. On line HPLC-UV, flash chromatography17,18, centrifugal TLC19-21 using chromatogram are also applied in the isolation of flavonoids. For difficult separations requiring very high resolution semi preparatory HPLC with automatic fraction collector is an ideal method. Reverse phase chromatography22-25, HPLC-DAD and HPLC-MS26 on chemically bonded phases gives better results of separation of plant phenolics.

Influencer marketing has become one of the major forms of digital advertising due to the rapid growth of social media platforms. This conceptual paper examines disclosure practices and ethical responsibility in influencer marketing communication by using secondary data, existing academic literature and regulatory guidelines and it mainly focus on how the mixing of personal content with promotional messages often make paid relationships unclear to the audiences. This situation creates ethical concerns related to transparency, possible consumer deception and trust issues among users. Previous studies show that clear and visible disclosures help consumers to recognise advertising contents and improve long-term trust towards influencers and brands, even though the immediate persuasive effect may get reduced to some extent. The paper review important regulatory frameworks, including guidelines issued by advertising authorities and discuss the continuing problems in compliance among influencers across different platforms and regions. Ethical issues such as hidden or unclear disclosures, pressure created by platform algorithms and low level of consumer awareness are critically discussed and the paper also explain the implications of these issues for brands, influencers and consumers, highlighting the need for more transparent and responsible influencer marketing practices for sustainability. Finally, the study identifies key research gaps and suggest future research directions for strengthening ethical standards and improving disclosure practices in emerging digital marketing environments, global markets and changing policy frameworks.

All over the world, people move to new countries for many reasons, such as studying, working, or migrating. Although their motivations differ, they often choose a particular place because of its safety, cultural appeal, traditions, food, language, or simply because they feel connected to it. Whatever the reason, thousands of people each year make their dream of living in a new country come true. Adapting to a new environment, however, can be challenging, especially with the administrative tasks people must handle upon arrival. To avoid becoming isolated in the “expat bubble,” individuals need to learn how to adjust to life in a foreign country or a new work environment (Sian 2018). Studying culturally appropriate behaviors and developing effective problem-solving strategies are essential foundations for successful adaptation. Many previous studies indicate that the process of adjusting to a new country and culture is known as culture shock. Culture shock develops gradually and requires time, effort, and personal reflection to overcome. While some people view living and working abroad as an exciting adventure, others argue that it presents a wide range of challenges. Therefore, the adjustment process varies from person to person and depends on individual circumstances, resources, and goals (Winkelman, 1994). The aim of this study is to investigate participants’ experiences of living in a new country and adapting to a new work environment. The findings highlight the diverse ways in which individuals navigate unfamiliar cultural contexts, manage culture shock, and develop strategies for effective adaptation. This research contributes to a deeper understanding of intercultural experiences and offers insights that may support individuals, organizations, and policymakers in facilitating smoother transitions for people entering new national and workplace environments.

The use of media in pulic relations is paramount and unavoidable.But while practicing public relations, the PR managers should always considier their audience as well as their preferred medium of engagement.This paper therefore,examined,explored and interogated the audience preferred meida and medium in public relations engagement of Coca-Cola PLC and Nigeria Breweries PLC, both located at Ikeja, Lagos state.The theories used were Media Dependecy Theory and Technological Determinism Theory.The survey method was adopted because of its efficency and accurency, using quantitative and qualitative approach.The design helped to extract primary data.The population of Ikeja residence was put at estimated 3,106.281 within the age of 18 to 40 years, while the sample size of 400 respodents was arrived at using Taro Yamane formula.This study established that despite the fact that social media and other new media were the audience preference of PR engagement of both organizations, traditional media like television, radio and news prints are still relevant in PR practice and should be modified to harmonize with the digital media. At the end, the researcher recommended that public relations managers or consultants should always watch and monitor the trend and always try to carry their audience along as regards to their choice of media in its public relations practice.

The work focuses on the formulation of polyherbal hydrogel incorporating liquorice (Glycyrrhiza glabra) and neem (Azadirachta indica) for effective de tanning and skin brightening. Hydrogels known for their high-water holding capacity, were selected to provide deep hydration and enhanced skin repair following UV exposure. Liquorice extract, a proven pigment lightening and antioxidant agent and neem extract, recognized for sun protective, antioxidant and skin brightening properties, were incorporated using Carbopol 940 as gelling polymer. The prepared hydrogel evaluated for appearance, pH, viscosity, spreadability, washability, stability studies, anti-microbial studies, invitro antioxidant activity, invitro anti thyrosinase activity and invitro SPF determination. Developing herbal hydrogel for de tan using liquorice and neem is safe, stable and effective altermative to commercial de tan products.

Cellular differentiation is a fundamental biological process through which multipotent stem cells acquire specialized functions and morphologies, ultimately giving rise to the diverse cell types that constitute complex organisms. While protein-coding genes have traditionally been the focus of gene regulation studies, the discovery and characterization of non-coding RNAs (ncRNAs) have revolutionized our understanding of the molecular mechanisms underlying cellular differentiation. Non-coding RNAs, which do not encode proteins but perform crucial regulatory functions, have emerged as master regulators of gene expression during development and differentiation. This comprehensive review examines the diverse classes of ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and other regulatory RNA species, and their intricate roles in orchestrating gene expression programs during cellular differentiation. We explore the molecular mechanisms by which ncRNAs regulate transcriptional and post-transcriptional processes, their involvement in chromatin remodeling, epigenetic modifications, and their interactions with transcription factors and signaling pathways. Furthermore, we discuss the implications of ncRNA dysregulation in developmental disorders and diseases, highlighting their potential as therapeutic targets and biomarkers. This review synthesizes current knowledge on ncRNA-mediated regulation of cellular differentiation and identifies key areas for future research in this rapidly evolving field.

Live-in relationship which is considered a modern or western concept has deep socio-historical roots in the Indian subcontinent. This research paper undertakes legal, historical, constitutional and socio-legal analysis of legal relationship in India which challenges the dominant narrative which views cohabitation as an alien concept to Indian culture. When we trace the evolution of intimate relationships from ancient Hindu texts such as Manusmriti which deal with eight types of marriages, Gandharva marriage is understood in the context of Kalidasa's Abhijanamshakuntalam. This study establishes that non-formal unions and consensual cohabitation were socially acknowledged in various forms during the Vedic and post-Vedic periods. This paper further explores parallels between the concept of Niyoga and contemporary live-in arrangements highlighting continuity rather than rupture in social practices. This study extends its analysis to medieval India, examining Islamic matrimonial concepts such as nikah, muta marriage, harem culture, and the interaction between Hindu and Muslim matrimonial traditions. It also examines tribal customary unions and non-ritualistic practices which reveal the pluralistic nature of Indian family structures. Its impact can be examined with reference to census practices, social reforms and legal codifications that lead to reshaping the institution of marriage and family structures. In the contemporary context, the research focuses on the provisions related to constitution under article 14, 15, 19, and 21 which are the relevant statutory laws and the judicial pronouncements recognizing live-in relationship and the presumption of marriage. The study also explores the social, economic, psychological and feminist dimensions of live-in relationship and addresses the issues on whether such relationships are a western import. It concludes with critical observations and recommendations that advocate the balanced legal framework that respects individual independence and ensures protection against exploitation, thereby aligning law with constitutional moral principles and social evolution.

The main objective of the study was to determine the influence of parental socioeconomic and demographic factors on school absences and dropouts among Indigenous Peoples (IP) elementary learners. Specifically, it described the parental profile in terms of age, family size, cultural obligations, and income level; measured the level of influence of these factors on school absences and dropouts; and tested for significant differences in influence when grouped according to the said characteristics. The respondents were 176 Grade 1 learners from Panganan, Digongan, and Kiulom Elementary Schools in Kitaotao District I together with their parents during SY 2024–2025. Total population sampling was employed. Data were gathered through a structured, expert-validated, and pilot-tested questionnaire. A descriptive–comparative design was used. Descriptive statistics summarized the parental profiles and the perceived influence levels. Inferential analysis tested group differences using One-Way ANOVA with post hoc procedures and independent samples t-tests, where appropriate. Results showed that parental age had a low overall influence; family size exerted a high influence; cultural obligations had a moderate influence; and income level showed a high influence on school absences and dropouts. Tests of significant difference further indicated that age, family size, and income level each produced statistically significant differences in influence; thus, the null hypothesis was rejected. It is essential to note that, despite constraints, most parents reported prioritizing schooling and encouraging regular attendance. However, financial limitations and larger household sizes posed substantial barriers, while cultural obligations moderately affected attendance without wholly disrupting schooling. The findings underscore the need for targeted financial assistance, support mechanisms for large households, and culturally responsive school practices to improve attendance and minimize dropouts among IP learners.

Globalisation has been one of the most defining drivers reconfiguring economies and labour markets globally. In India, the period of post-1991 liberalisation was a transformation that ushered in new opportunities and daunting challenges for labour. Although globalisation has boosted economic growth, its gains have disproportionately accrued to favour capital-intensive industries and skilled labour at the expense of the unorganised and agricultural economy that constitutes the bulk of labour. This current research discusses the extent and nature of labour utilization in India during globalisation. Using secondary data from government reports, the National Sample Survey Organisation (NSSO) and academic studies, it explores employment growth and elasticity, trends in unemployment, sectoral changes, casualization, feminization, wage differences and labour migration. It also delves into the government labour welfare policies, their shortcomings and the imperative of perspective planning for reconciling growth with fair labour rights and social security. The research points out that though globalisation offers scope for India's skilled labour force, structural rigidities, informalisation and weak welfare systems remain major challenges to inclusive development. Policy changes toward higher skill development, rigorous labour laws and social safety nets are required for sustainable labor utilization in the global economy.

Deep learning, a prominent subfield of machine learning, leverages multilayered neural networks to automatically learn intricate hierarchical representations from raw data. This paper provides a comprehensive review of foundational deep learning architectures, including Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, Transformer neural networks, Generative Adversarial Networks (GANs), and Autoencoders (AEs). For each method, core principles, distinct advantages, and inherent disadvantages are detailed. The discussion highlights how architectural innovations address specific data challenges and how the practical viability of these methods has been shaped by the interplay of algorithmic advancements and hardware capabilities. Furthermore, the paper briefly explores the widespread application of deep learning across diverse domains such as computer vision, natural language processing, speech recognition, healthcare, and finance, underscoring its transformative impact and the persistent challenges that continue to drive research.

Public awareness and accessibility are central to effective household engagement with emergency response systems. This study examines public awareness, knowledge, and accessibility of Emergency Communication Centres (ECCs) for household emergency response in Abuja Municipal Area Council, Nigeria. A quantitative cross-sectional survey was conducted among 384 households using structured questionnaires administered through face-to-face interviews. Descriptive statistics were used to assess levels of awareness, knowledge of the toll-free emergency number, confidence in contacting ECCs, and utilisation patterns, while chi-square tests and binary logistic regression examined factors influencing utilisation. Findings show that although general awareness of ECCs was moderate, actionable knowledge and confidence in using the service were limited. Utilisation of ECC services during emergencies was low, with households often relying on alternative or informal channels. Geographic location and prior awareness significantly influenced ECC utilisation, with lower usage observed in peri-urban and semi-rural areas. The study concludes that sustained public sensitisation and improved accessibility are essential to strengthen household utilisation of ECC services and enhance emergency response effectiveness.

This work examines the quest motifs in Ifeoma Okoye’s Chimere, Onyekachi Peter Onuoha’s Moonlight Lady, and O.O. Sangoyomi’s the Masquerade. The subordination and humiliation of women in most African society has led the woman to the quest for self-realization, self-rebuilding. Self-actualization, freedom, and independence. This study explores the motivation that triggers these quests and also demonstrates the impulse behind the motifs. The theory that informs this study is the African feminism. This is qualitative research as information are gathered from the internet, unpublished works, text books and other sources. Findings shows that patriarchy and African society are the biggest challenge women face. This work recommends that societal expectations and stereotypes that limit women’s choices should be challenged. This work concludes that, women despite their limitations, challenges and yearnings, still fight for self-actualization and a better livelihood. This study contributes to knowledge, that irrespective of the circumstances surrounding women, they still fly high to make their dreams a reality.

This research examines the representation of women in selected works of Mariama Ba's So Long A Letter, Akachi Adimora's The Last of the Strong Ones and Onyekachi Peter Onuoha's Moonlight Lady. African literature was in the past seen as men's preserve. The purpose of this study is to critical look at how African women reject patriarchal and traditional norms which they are confined to and take charge of their lives. This is a qualitative research as information are gathered from unpublished works, text books, internet, and other sources. The theory that informs this study is the African feminist theory known as womanism, an offshoot of feminism. Finding shows that patriarchy, obnoxious cultural norms and traditions are the major setbacks that mount restrictions on the personality of women in African society. This study recommends that the female gender should be schooled and educated on the importance of self-development and self worth. This study concludes that African writers have taken it upon themselves, through their efforts and struggles to projects a new realism and vision for Africa, while redressing the presentation of the Africa woman. This paper contributes to knowledge as it has exposed to readers that Women are beginning to emerge from behind, the veil of male-based culture to voice their needs.

This study examined influence of environmental adult education programmes on the restoration of aquatic resources among the Wakirika people of rivers state. four research objectives, four research questions, and four null hypotheses were used for the study. descriptive survey research design was adopted for the study. the population for the study comprised 168 community inhabitants, including 58 female and 110 male beneficiaries in the registered adult education centres in the study area. due to the relatively small and manageable population size, a census approach was used, eliminating the need for sampling and ensuring that the entire population was represented in the study. The instrument for data collection was a structured questionnaire titled “Influence of Environmental Adult Education Programmes on Restoration of Aquatic Resources Questionnaire”. the face and content validity of the instrument was determined by two experts in the field of environmental adult education. the reliability of the instrument was determined through a pilot study while Cronbach Alpha method was used to establish the reliability coefficient (r) value 0.69,. the responses from the four research questions were analysed with mean and standard deviation statistic. The findings from the study revealed that environmental literacy, conservation education, agricultural extension education, and waste management education programmes influence the restoration of aquatic resources among the Wakirika people of Rivers State to a high extent. The study recommended among others that Rivers State Government through Agency for Adult and Non-Formal Education should integrate environmental literacy education into existing adult education programmes in Rivers State to educate more community inhabitants on the needs for environmental activities that sustains aquatic lives.

The effective utilisation of community-based resources is critical to achieving sustainable development and improving the well-being of the Wakirika people in Rivers State, Nigeria. The paper highlighted the potential of community-based resources, including mangrove forests, creeks, cultural festivals, and traditional artifacts, to drive economic development, social empowerment, and environmental sustainability. However, the paper also identified several challenges that hinder the effective utilisation of these resources, including lack of access to information and technology, inadequate capacity and skills, inequitable distribution of resources, environmental degradation and climate change, lack of effective governance and institutions, and conflicting interests and power dynamics. To address these challenges, the paper recommended a range of strategies, including capacity building and training, establishment of community-based institutions, promotion of community participation and engagement, support for sustainable livelihoods, addressing conflicting interests and power dynamics, and improving access to information and technology. By adopting a holistic and participatory approach to development, the Wakirika people can harness their community-based resources to achieve sustainable development and improve their overall well-being.

Organotin(IV) complexes represent an important class of organometallic compounds due to their rich coordination chemistry and wide-ranging functional applications. The introduction of multidentate ligands has significantly expanded the structural diversity and stability of these complexes while enhancing their performance in biological, catalytic, and material-related domains. This review critically examines recent progress in the synthesis, structural dynamics, and functional performance of novel organotin(IV) complexes incorporating multidentate ligands. Particular emphasis is placed on synthetic methodologies, coordination behavior, structure–property relationships, and emerging application trends. The review also highlights existing challenges and outlines future research directions for the rational design of advanced organotin-based systems.

Digital content marketing has emerged as a critical strategic tool for organizations operating in technology-enabled market environments. With rapid digitalization and increasing consumer interaction through online platforms, firms are increasingly relying on content-driven approaches to enhance consumer engagement. This study empirically examines the influence of digital content marketing practices on consumer engagement in technology-enabled markets. The research focuses on key content marketing dimensions such as content quality, relevance, interactivity, consistency, and personalization, and evaluates their impact on cognitive, emotional, and behavioral engagement of consumers. Primary data were collected from consumers actively using digital platforms related to technology-based products and services. Statistical tools were employed to analyze relationships between content marketing practices and engagement outcomes. The findings reveal that high-quality, interactive, and personalized digital content significantly enhances consumer engagement, leading to improved brand connection and participation. The study contributes to marketing literature by providing empirical evidence on the effectiveness of digital content strategies in technology-driven contexts. The results offer valuable insights for marketers and organizations seeking to optimize digital content strategies to strengthen consumer engagement and competitive advantage.

Almost Distributive Lattices (ADLs) represent a significant generalization of Boolean algebras and distributive lattices, emerging as crucial algebraic structures in modern lattice theory. This comprehensive review examines the mathematical foundations, structural properties, and applications of ADLs, synthesizing key developments from their introduction by Swamy and Rao in 1981 to contemporary research. We explore the axiomatic foundations, characterization theorems, homomorphism theory, and various classes of ADLs including modular, sectionally semi-complemented, and Stone ADLs. The paper discusses topological considerations, congruence relations, and connections to related algebraic structures. We also highlight open problems and future research directions in this evolving field.

Thin Layer Chromatography (TLC) is a popular analytical method for separation and identification of components in mixture. This review provides a wide overview by covering the basic principles, methodology, retention factor calculations, and their applications in various scientific fields. Its simplicity, low cost, and versatility have made this technique a necessary instrument in pharmaceutical analysis, natural product chemistry, forensic science, and quality control laboratories. The review paper discusses the importance of TLC in modern analytical chemistry as well as its advantages and limitations.

A common gastrointestinal condition known as gastric ulcers causes mucosal damage to the stomach lining. Proton pump inhibitors, histamine-2 receptor antagonists, and antibiotics are currently the primary treatments for stomach ulcers. The extended use of these conventional treatments, however, could result in negative side effects and drug resistance. To control stomach ulcers, there has been an increase in interest in researching alternative and complementary therapies, such as nutraceuticals. The term "nutraceuticals" refers to a broad category of bioactive substances derived from natural sources, such as polyphenols, flavonoids, antioxidants, and dietary fibres. These substances have been shown to have a variety of pharmacological properties, such as anti inflammatory, antioxidant, antiulcerogenic, and cytoprotective effects. The review also examines the mechanisms underlying the antiulcerogenic effects of nutraceuticals, such as the modulation of pro-inflammatory cytokines, improvement of antioxidant defences, reduction of gastric acid secretion, stimulation of mucin production, and promotion of mucosal blood flow. Although nutraceutical approaches to treating stomach ulcers appear promising, it is important to consider their drawbacks, such as bioavailability, dose optimisation, and potential herb-drug interactions. Standardised formulations, ideal dosing schedules, and long-term safety profiles of these nutraceutical therapies must all be determined through more research. Finally, nutraceutical methods present a potentially effective route for the treatment of stomach ulcers.

This study provides an evaluative analysis of the obstacles to doing business in Sub- Saharan Africa and contributes to the existing literature by addressing two central research quest- ions: (1) what is the relationship between the ease of doing business and economic development, and (2) what are the principal obstacles to doing business in the region? To address these questions, the study examines the nexus between the ease of doing business and economic development across six key dimensions: wealth creation and distribution, employment generation, balanced regional and economic development, gross domestic product (GDP) and GDP per capita, living standards, and export performance. In addition, the study identifies and discusses major challenges to business activity in Sub-Saharan Africa, including the high costs associated with starting and operating a business, inadequate access to energy and electricity, limited access to finance, high taxation, and constraints on cross-border trade. The findings underscore the critical role of an enabling business environment in fostering sustainable economic development and highlight the structural and institu- tional barriers that continue to impede business growth in the region.

This study examined the influence of strategic capabilities on competitive advantage among microfinance banks in Nairobi City County, Kenya. Specifically, it investigated how managerial, marketing, technological, and networking capabilities contribute to competitive positioning in an increasingly dynamic and competitive financial services environment. The research adopted a descriptive research design and employed a census approach targeting all 156 employees from four key departments—operations, marketing, finance, and information technology—across thirteen licensed deposit-taking microfinance banks in Nairobi. Data was collected using structured questionnaires and analyzed through both descriptive and inferential statistical techniques, including correlation and multiple regression analysis using SPSS version 20.0. The study achieved a response rate of 75%, with 117 completed questionnaires. Reliability analysis confirmed excellent internal consistency (α = .959). Correlation analysis revealed strong positive relationships between all strategic capabilities and competitive advantage: marketing capabilities (r = .690, p < .01), managerial capabilities (r = .688, p < .01), networking capabilities (r = .660, p < .01), and technological capabilities (r = .610, p < .01). Multiple regression analysis indicated that the four predictors collectively explained substantial variance in competitive advantage (R² = .550, F(4, 112) = 34.212, p < .001). Marketing capabilities emerged as the strongest significant predictor (β = .337, t = 2.996, p = .003), followed closely by managerial capabilities (β = .325, t = 2.849, p = .005). These findings support Market-Based Theory and Dynamic Capability Theory, demonstrating that market-facing competencies and leadership effectiveness are primary drivers of competitive positioning. Interestingly, while technological capabilities (β = .012, t = .103, p = .918) and networking capabilities (β = .131, t = 1.068, p = .288) showed strong bivariate correlations with competitive advantage, they did not demonstrate significant independent effects in multivariate analysis, suggesting these capabilities function as enablers that enhance marketing and managerial effectiveness rather than serving as direct sources of competitive advantage. This pattern likely reflects technology commoditization within financial services and the indirect nature of networking benefits. The study recommends that microfinance institutions prioritize investments in marketing and managerial capability development as primary pathways to competitive advantage while ensuring technological and networking capabilities are effectively integrated to support these core competencies. Future research should employ longitudinal designs to examine temporal dynamics and explore mediating mechanisms through which technological and networking capabilities influence competitive outcomes across diverse geographical contexts.

Influencer marketing has become one of the major forms of digital advertising due to the rapid growth of social media platforms. This conceptual paper examines disclosure practices and ethical responsibility in influencer marketing communication by using secondary data, existing academic literature and regulatory guidelines and it mainly focus on how the mixing of personal content with promotional messages often make paid relationships unclear to the audiences. This situation creates ethical concerns related to transparency, possible consumer deception and trust issues among users. Previous studies show that clear and visible disclosures help consumers to recognise advertising contents and improve long-term trust towards influencers and brands, even though the immediate persuasive effect may get reduced to some extent. The paper review important regulatory frameworks, including guidelines issued by advertising authorities and discuss the continuing problems in compliance among influencers across different platforms and regions. Ethical issues such as hidden or unclear disclosures, pressure created by platform algorithms and low level of consumer awareness are critically discussed and the paper also explain the implications of these issues for brands, influencers and consumers, highlighting the need for more transparent and responsible influencer marketing practices for sustainability. Finally, the study identifies key research gaps and suggest future research directions for strengthening ethical standards and improving disclosure practices in emerging digital marketing environments, global markets and changing policy frameworks.

The review essay examines Shiv Khera’s - You Can Win (1998) mainly focuses on themes of positive attitude, motivation, ethics and self-belief from Human Resource Management perspective. Even though the book is internationally known as motivational guide, where this paper connects its ideas with students, working professionals and entrepreneurs in the context of motivation, Integrity and ethical behaviour in their personal as well as professional lives. This essay covers all the chapters and gives an overview of how the positive attitude, motivational strategies, ethical decision making and vision which supports in both personal and professional success.

Artificial Intelligence (AI) has evolved from rule-based expert systems to intelligent agents capable of autonomous perception, reasoning, learning, and decision-making. AI agents and autonomous decision systems represent a paradigm shift in computational intelligence, enabling machines to operate independently in dynamic and uncertain environments. These systems integrate perception modules, knowledge representation, decision-making algorithms, and learning mechanisms to achieve goal-directed behavior without continuous human intervention. Applications range from robotics, autonomous vehicles, and smart healthcare to finance, cybersecurity, and large-scale industrial automation. Despite their advantages, autonomous systems raise critical challenges related to safety, explainability, ethical decision-making, and accountability. This paper presents a comprehensive review of AI agents and autonomous decision systems, discussing their evolution, architectural models, decision-making techniques, learning mechanisms, applications, advantages, challenges, and future research directions. The study highlights how advancements in reinforcement learning, multi-agent systems, and large language models are accelerating the adoption of autonomous intelligence while emphasizing the need for robust governance and human-centric design.

Tribal peoples form a major segment of the world population. They are found all over the world. They are called by different names such as primitive, 'tribal,' 'indigenous,' 'aboriginal,' 'native,' and so on. India has a large number of tribal people. According to R. C, Verma they "constitute about 8.08% of the total population. They would be about 6.78 crores out of the total population of 83.86 crores according to [the] 1991 census" (I). The major tribes in India are the Gonds, the Bhils, the Sanlals, the Oraons and the Minas. They live in different regions in the forest as well as in urban areas, and mostly speak their own languages. The states of Madhya Pradesh, Orissa, Bihar, Maharashtra, Gujarat, Andhra Pradesh. West Bengal and the North eastern Region have a larger concentration of tribal population. The Andaman and Nicobar Islands are also inhabited by several tribes such as the Great Andamanese, Sentenelese, Onges, Jarwas, Sompens, and so on.

The primary argument of this discussion is that, despite the acceptance of implementing a gender mainstreaming approach in developing countries to promote gender equality, African countries, including Tanzania, still have action plans, such as projects, laws, policies, regulations, and programs, that scarcely address gender issues compared to developed countries. Gender issues encompass limited decision-making power, participation, and division of labour, control and ownership of resources, gender needs, and gender roles. This discussion is not concerned with political dynamics, economic issues, or cultural factors; instead, it aims to introduce the 7 approaches of the gender mainstreaming model and enhance understanding of how to conduct gender mainstreaming in development plans, particularly community development projects. Gender mainstreaming is essential for enhancing the well-being of community members, including boys, girls, men, and women from diverse backgrounds. The process of gender mainstreaming in community development projects should integrate the 7 approaches model, which involves gender analysis that organises data into gender-disaggregated categories, and the setting of gender-sensitive indicators that reflect whether development goals for achieving gender equality are met or not within the development plan, based on evidence collected through various data collection tools in the particular field. Also, the process of gender mainstreaming in community development projects closely resembles other development plans, such as policies, laws, regulations, and programmes. The only distinction is in the depth of analysis and the need for gender analysis to achieve gender equality. For African countries to effectively promote gender equality, they must strengthen their policies and strategies by incorporating 7 approaches such as Gender Mainstreaming (GM), Gender Analysis (GA), Gender Disaggregated Data (GDD), Development Plan (DP), Development Goals (DGs), Achieve Gender Equality (AGE), Sensitive Indicator (GSI) as outlined in the 7 approaches gender mainstreaming model.

Organizational culture plays a critical role in shaping employee behavior, creativity, and innovation within modern workplaces. The present study examines the effect of organizational culture on employee creativity and innovation in selected organizations. A total of 120 employees from various industries were surveyed using structured questionnaires measuring organizational culture dimensions, creativity levels, and innovation outcomes. The study employed descriptive statistics, correlation analysis, and regression analysis to assess the relationships between variables. The findings revealed that a supportive and collaborative organizational culture positively influences employee creativity and fosters innovative behaviors. Specifically, dimensions such as open communication, participative decision-making, and recognition of ideas were found to enhance creative problem-solving and innovative output significantly. Conversely, rigid hierarchical structures and punitive cultures were associated with lower levels of creativity and innovation. The study highlights the importance of fostering an adaptive and employee-centric culture to stimulate creative thinking and ongoing innovation within organizations. The results have practical implications for HR managers, leaders, and policymakers, highlighting the need for culture-driven strategies to enhance organizational performance in a competitive business environment.

Background: Uterine fibroids are benign tumours frequently associated with heavy bleeding, pelvic pain, and functional impairment. Many patients decline surgery due to morbidity, seeking individualized, low-risk alternatives. Case History: A 46-year-old woman with a bulky uterus and intramural fibroid presented with menorrhagia, pelvic pain, constipation, fatigue, and emotional disturbance. She had inadequate response to prior conventional treatment and was advised hysterectomy. Homoeopathic management with Phosphorus 1M and intercurrent Thuja occidentalis 1M was prescribed based on individualisation and repertorial analysis. Results: Progressive clinical improvement was observed with normalization of menses and radiological reduction of Uterine Size. Modified Naranjo score was 11, indicating a highly probable causal association with homoeopathic treatment. Conclusion: Individualized homoeopathy may offer a safe, effective complementary approach for symptomatic uterine fibroids, warranting further research.

Fake medicines have become an increasing global health problem, affecting confidence in the public, patient safety, and medical systems.These counterfeit medications are often hazardous or ineffective as they consist of wrong, spurious,or missing active therapeutic agents. financial incentives, regulatory errors, advanced developing techniques, And an increase in online transactions are the main causes of the rise in counterfeit drugs. Different instrumental techniques have been developed to adress this problem. Chromatography techniques, mainly High Performance Liquid Chromatography (HPLC), are used for identification, ingredient separation and accurate detection of any differences from documented formulations. Spectroscopic methods such as Raman, Fourier-transform Infrared (FTIR), and Near Infrared (NIR) Spectroscopy provide fast, harmless analyses of chemical and physical characteristics, providing unique fingerprints for medication testing.FTIR spectroscopy is used for rapid detection of chemical and physical properties which give unique molecular fingerprints for drug authentication. Several advanced techniques, such as microtomography and Raman microscopy,provide detailed surface and internal examinations, revealing structural and compositional irregularities. Additionally general methods such as visual inspection, physical testing, and thorough documentation verification help these techniques. Despite developments in technology, problems arise. Bcause of counterfeiters' shifting methods, inflated costs, and the world's limited authority to regulate. Therefore, ongoing development, validation, and use of affordable, portable analytical tools are crucial, as are increased enforcement and international collaboration. In order to effectively detect, prevent, and regulate counterfeit pharmaceuticals and ultimately protect public health and sustain pharmaceutical quality worldwide, an integrated multi-technique strategy is essential.

Food adulteration has become an increasingly common problem across the globe, threatening the safety, health, and consumer confidence in the whole process. This can happen deliberately as a means to earn profits or can happen unknowingly due to the inefficiencies caused by the environment. This review briefly describes the sources, risks, and current technological solutions for detection. Chromatographic and analytical methods like HPLC, GC-MS, and LCMS are highly sensitive and quantitative regarding the detection and identification of known sources, whereas spectroscopy and chemometric characterization are highly rapid and less destructive. The use of modern sensor-based technologies and E-nose systems facilitate the process of on-site testing, whereas untargeted approaches like metabolomics and stable isotope analysis improve authenticity testing. The role and sources are further briefly explained in the following sections.

Artificial intelligence (AI) and machine learning (ML) have transitioned from experimental computational tools to realistic clinical adjuncts across surgical specialties. Within oral and maxillofacial surgery (OMFS), AI has found particular relevance due to the specialty’s heavy reliance on advanced imaging, virtual surgical planning, complex three-dimensional anatomy, oncology diagnostics, and outcome prediction. Over the past decade, deep learning–based architectures such as convolutional neural networks (CNNs), U-Net derivatives, and transformer-based models have demonstrated significant potential in automating cone-beam computed tomography (CBCT) segmentation, craniofacial landmarking, implant planning, soft-tissue simulation, and multimodal prognostication in oral squamous cell carcinoma (OSCC). Despite promising accuracy metrics in research environments, barriers remain regarding dataset heterogeneity, generalizability, bias, explainability, medico-legal responsibility, and regulatory approval. This review synthesizes contemporary evidence on AI in OMFS, critically examines methodological strengths and weaknesses, and outlines a translational roadmap to enable responsible and clinically meaningful integration of AI systems into surgical practice. [1–5]

Graph Neural Networks (GNNs) have been widely adopted for learning from non-Euclidean data structures, particularly graphs. Numerous studies have sought to enhance training efficiency and reduce computational complexity when dealing with large-scale graph datasets. This paper surveys convolution-based GNN approaches developed for graph classification and prediction tasks on large graphs. Each method is critically examined with respect to its claimed efficiency gains and complexity reductions, and their limitations are systematically discussed. In addition, the reviewed techniques are evaluated from the perspective of graph dataset characteristics, providing insights into their practical applicability and constraints.

Sustainable education in the twenty-first century is increasingly dependent on access to reliable, affordable, and environmentally responsible energy systems. In Nigeria, persistent electricity shortages, high dependence on fossil-fuel generators, and rising energy costs continue to undermine effective teaching, learning, research, and institutional management across all levels of education. These challenges not only disrupt academic activities but also widen educational inequalities, limit digital learning opportunities, and strain already constrained institutional budgets. This article examines the role of renewable energy technologies in enhancing sustainable education in Nigeria, focusing on how clean and decentralized energy solutions can address systemic energy-related barriers to educational development. Drawing on recent scholarly literature, policy documents, and empirical evidence, the paper explores the relevance of key renewable energy technologies, such as solar, wind, biomass, small hydropower, and hybrid systems, to Nigeria’s education sector. The analysis highlights how renewable energy contributes to learning continuity, improved instructional quality, digital education support, financial sustainability, environmental protection, and skills development for green jobs. The article further argues that renewable energy adoption transforms educational institutions into resilient, future-ready spaces that align with global sustainability agendas, including the United Nations Sustainable Development Goals, particularly SDG 4 (Quality Education) and SDG 7 (Affordable and Clean Energy). Despite these benefits, the study identifies major constraints to widespread adoption, including high initial capital costs, weak policy coordination between the energy and education sectors, limited technical capacity, inadequate maintenance culture, security concerns, and unequal access between urban and rural institutions. The paper concludes that renewable energy technologies are not optional add-ons but strategic enablers of sustainable education in Nigeria. It recommends integrated policy frameworks, dedicated financing mechanisms, capacity building, curriculum integration, stakeholder engagement, and equity-focused implementation as critical pathways for embedding renewable energy into Nigeria’s education system and achieving long-term educational sustainability.

The present study aimed to examine the impact of Long-Term Athlete Development (LTAD) models on the performance of young athletes and football players in Tirupati district. A total of 80 young athletes (40 athletes and 40 football players) aged between 12 and 16 years were selected from schools and sports academies using a purposive sampling method. The participants underwent a 24-week LTAD-based training intervention emphasizing fundamental movement skills, progressive physical conditioning, sport-specific skill development, and psychological readiness, conducted four days per week. Performance variables such as speed, agility, endurance, coordination, and sport-specific skill proficiency were assessed using standardized field tests before and after the intervention. Statistical analysis was carried out using paired t-tests and analysis of covariance (ANCOVA) at a 0.05 level of significance to determine within-group and between-group differences. The findings revealed statistically significant improvements (p < 0.05) in all selected performance variables among both athletics and football players following the LTAD-based training program. Athletics players demonstrated greater gains in speed and endurance, whereas football players showed higher improvements in agility and skill-related performance. The results highlight the effectiveness of structured long-term development models in enhancing holistic athletic performance during early developmental stages. The study concludes that the adoption of LTAD frameworks in school and academy training programs can foster sustainable performance development and reduce the risk of early specialization and injury among young athletes in the Tirupati district. Future research is recommended to explore longitudinal outcomes across different age categories and gender groups.

Herbal nootropics, which are plant-based substances that enhance cognitive functions such as memory, learning, and focus, trace their roots to ancient civilizations. In Ayurveda, herbs such as Bacopa monnieri (Brahmi), Ashwagandha, and Gotu Kola are believed to sharpen intelligence and reduce stress. Traditional Chinese Medicine favored Ginkgo biloba, Panax ginseng, and Schisandra chinensis for concentration and vitality, whereas Egyptian and Greek traditions used rosemary and sage for alertness. The modern concept of "nootropics" emerged in 1972, coined by Dr. Corneliu E. Giurgea from Greek words noos (mind) and tropein (to guide), initially for synthetic compounds like piracetam but soon extending to natural plants. These herbs work through multiple mechanisms: boosting brain oxygen and glucose supply, offering neuroprotection via antioxidants, improving blood flow by enhancing red blood cell flexibility, and supporting cell membrane function and waste removal. Unlike instant-acting drugs, they require prolonged use and effectively cross the blood brain barrier. Key examples include Brahmi for memory, Ashwagandha for stress reduction, Ginkgo for circulation, turmeric for anti-inflammation affects and green tea for alertness. Scientific interest has surged in alternatives to synthetic drugs with fewer side effects, as validated by studies on neuroprotection, neurotransmitter enhancement, and inflammation reduction. Complementary lifestyle strategies, such as exercise, nutrient-rich diets (omega-3s, berries), mental stimulation, sleep, stress management, and hydration amplify these benefits. The future shines with consumer demand, tech integrations such as AI and nanotechnology for precision delivery, and validation of Ayurveda TCM. Challenges include standardization, regulation, and rigorous trials for personalized and safe therapies. This review synthesizes historical, mechanistic, and modern evidence on herbal nootropics, excluding synthetic and non-cognitive agents.

Oral dysbiosis, defined as an imbalance in the composition and function of the oral microbiota, is a central driver in the pathogenesis of periodontitis, a chronic inflammatory disease of the tooth-supporting structures. In health, commensal microorganisms maintain host-microbe homeostasis, but ecological shifts favor pathogenic species such as Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola, which disrupt immune regulation and trigger persistent inflammation. This dysregulated host response leads to connective tissue breakdown and alveolar bone resorption, while microbial by-products and systemic inflammatory mediators extend the impact of periodontitis beyond the oral cavity, linking it to conditions such as cardiovascular disease and diabetes. Conventional therapies reduce microbial load but often fail to restore ecological balance, highlighting the need for emerging strategies such as probiotics, host-modulation, and microbiome-targeted interventions aimed at re-establishing symbiosis. Thus, oral dysbiosis represents both a local and systemic challenge, underscoring the importance of precision approaches that integrate microbial profiling and immune modulation for effective periodontal care.

This paper discusses the student-teacher’s experiences during teaching practice using Activity-Based Learning (ABL). ABL states that learners actively construct knowledge through direct experiences and subsequent reflection, moving beyond passive information reception (Baserer, 2020). Throughout the teaching practice sessions, three main classroom tools were regularly used: flashcards to encourage active recall, chronology strips to support sequential understanding, and exit tickets to invite immediate reflection and feedback. Classroom observations focused on how students interacted with these tools, their level of participation, and the nature of their engagement. The use of flashcards encouraged recall and attention, chronology strips supported better understanding of sequences, and exit tickets gave insight into students’ learning and self-assessment. Overall, these observations showed that ABL tools helped improve student engagement, motivation, and active participation, making the learning experience more interactive and meaningful

India has a very rich and versatile knowledge system and cultural heritage. It has a long-standing tradition of knowledge and education, dating back to ancient universities like Nalanda and Takshashila. These institutions were renowned for their diverse curriculum, attracting scholars from across the globe. Indian civilization has always attached great value to knowledge — witness its amazingly large body of intellectual texts, the world&#39;s largest collection of manuscripts, its attested tradition of texts, thinkers and schools in so many domains of knowledge.

The history education in Thailand has evolved from ancient times to the present, which is related to Buddhism. The relationship between temple education and Thai society is organic and adaptive, creatively responding to changing political environments (David Wyatt, 1969). Education has been an important component of the vital, ongoing relationship between Thai people and the monastic institution within Thailand. Buddhism and education were intimately linked through monastic schools for novice monks. The school for teaching Buddhism in the past was a monastery because of the stipulation ‘all Thai men must be ordained to study the Dhamma and various teachings in Buddhism as a basis for their further life’. Buddhist Studies curriculum has been a compulsory subject everyone must study because the teachings in Buddhism are fundamental principles which most people use in their daily lives (Scotton, 1998).

Healthcare is evolving with a fresh focus on putting patients first. Central to this shift is the growing acknowledgement of patients' contributions in healthcare delivery and planning. Medical appointment scheduling serves as the primary gateway for most non-emergency healthcare services, and it is experiencing significant changes to encourage active patient participation. This project introduces a method for creating an intelligent appointment booking system that offers patients and users a simple approach to scheduling doctor visits online. Through internet connectivity, patients gain greater autonomy in making decisions about their appointment preferences, leading to enhanced accessibility. The project presents an approach to designing a smart appointment booking system that provides patients or any user with an easy way of booking a doctor’s appointment online. By using the Internet as a medium, more freedom is given to the patients in decision-making about their preferences for appointments, and it has improved access.10-point.

The design and development of a contemporary e- commerce retail system utilizing the newest trends and technologies is examined in this report. We suggest a headless, microservices-based architecture that is hosted on AWS cloud infrastructure and consists of a React front end, a Node.js back end, and MongoDB data stores. The system incorporates AR/VR features (e.g., virtual try-on, 3D product visualization) to improve user experience and integrates AI/ML for real-time personalization (recommendations, search, chatbots). Other essential elements include mobile/omnichannel commerce (PWA, mobile apps, and social commerce) and secure payment processing (e.g., virtual Stripe/PayPal with 3D Secure and fraud detection). The architecture decouples the front and back ends for scalability and agility using an API- driven methodology (GraphQL/REST). Findings show that a platform like omnichannel can increase conversion and retention. For instance, omnichannel shoppers increase lifetime value by about 30%, and AI personalization "delights shoppers" while increasing sales conversions. We wrap up by outlining the advantages (personalization, flexibility, worldwide reach) and drawbacks (data complexity, cost, privacy/compliance).

Artificial Intelligence (AI) has emerged as one of the most important technological forces reshaping human resource management (HRM). Recruitment and selection, which form the foundation of talent acquisition, have undergone major transformation with the integration of AI tools such as automated resume screening, predictive analytics, natural language processing, chatbots, and digital interview evaluation systems. This research paper presents an extensive examination of the role of AI in recruitment and selection with particular emphasis on its benefits, limitations, ethical implications, and future potential. The study is conceptual in nature and is based on a synthesis of existing literature from leading journals, academic research, and industry reports. The findings shows that AI can streamline hiring processes, reduce time-to-hire, increase the accuracy of candidate-job fit, and improve candidate experience. However, the adoption of AI also raises concerns such as algorithmic bias, lack of transparency, biasness, data privacy challenges, skill gaps among HR professionals, and overreliance on automation. The study results with recommendations for responsible AI implementation, highlighting the need for human–AI collaboration, ethical auditing mechanisms, training of HR professionals, and robust governance frameworks. The paper contributes to the existing body of knowledge by providing a holistic understanding of AI-driven recruitment and offering insights for practitioners, policymakers, HR professionals and researchers.

Background: The COVID-19 pandemic resulted in repeated revisions to Indian and global guidelines for surveillance, case definition, testing strategy, and clinical management. This, in turn, has great implications on the rapid identification of cases and the uniformity of management provided at different levels of care. Objective: To review how updated methodological guidelines for COVID-19 in India have impacted case detection and clinical management and to outline key learning points for undergraduate medical training. Methods: This narrative review used national documents from the Indian Council of Medical Research (ICMR) and Ministry of Health and Family Welfare (MoHFW), including testing strategy advisories, surveillance guidelines, and clinical management protocols, as well as World Health Organization (WHO) surveillance and case definition guidance and recent peer‑reviewed literature from 2015–2025. Documents were selected if they described COVID‑19 case definitions, testing strategies, surveillance approaches, or treatment protocols relevant to India, with emphasis on updates issued between 2020 and 2023. Results: Updated Indian guidelines progressively shifted from broad community testing and hospitalization to purposive testing focused on high‑risk groups and structured home/institutional care pathways, while surveillance moved toward integrated, variant‑sensitive systems aligned with WHO case definitions. This approach has evolved from empiric repurposed drugs to evidence-based oxygen therapy, steroids for hypoxic patients, thromboprophylaxis, and rational use of antivirals and immunomodulators.

The rapid integration of artificial intelligence into financial market is transforming traditional approaches to investment decision making. This study explores the impact of AI on the investment behaviour of academics in the Delhi ncr region. Academics, being relatively well informed and technologically adaptive, represent a unique investor group whose choices are shaped by both financial knowledge and professional exposure to analytical tools. The finding shows that AI applications such as robo advisors, algorithmic screeners and predictive analytics are increasingly used by academics to identify investment opportunities, assess risk and monitor portfolio. While AI has enhanced efficiency, reduced information overload and improved data driven decision making, academics remain cautious about fully relying on automated system, largely due to trust issues and the need for transparency in model output. The study further highlights that personal financial goals, risk tolerance and regulatory safeguard continue to moderate the extent of AI adoption.

भारत युगों से अपनी सांस्कृतिक संतृप्ता के लिए सम्पूर्ण विश्व में प्रसिद्ध है। विभिन्न संस्कृतियों और विचारधाराओं में विविधता होने के बावजूद भी उसकी अखंडता और एकनिष्ठा ज्यों की त्यों बनी हुई है। समय के साथ जैसे आधुनिकता की होड़ बढ़ती गई इसमें भी कुछ विकृतियों ने जन्म ले लिया हम अपनी मूल संस्कृति और परंपरा से दूर हो गए इस कारण देश की युवा पीढ़ी में अनुशासनहीनता, सतही मानसिकता और आत्मबल की शून्यता देखने को मिल रही है। भारत सरकार द्वारा प्रस्तावित इस राष्ट्रीय शिक्षा नीति की परिकल्पना है कि वो देश के युवाओं में अपनी संस्कृति, सभ्यता तथा आध्यात्मिक दर्शन के प्रति उत्सुकता जागरूक करें और उन्हें इस बात का विश्वास दिलाएं की एक व्यक्ति तभी एक परिपूर्ण नागरिक बन सकता है जब वह अपने देश की संस्कृति और परंपरा को समझे तथा उसे अपनी विचारधारा में समाहित कर देश की उन्नति के लिए सदैव तत्पर रहे। शोधपत्र में NEP 2022 द्वारा सांस्कृतिक अवधारणा को विश्लेषित किया गया है कि हम किस प्रकार अपनी मूल संस्कृति को शिक्षा का अभिन्न अंग बनाए ताकि युवाओं में इसका ज्ञान इस प्रकार समाहित हो की वो इससे कभी विलग न हो पाएं। राष्ट्रीय शिक्षा नीति 2020 इस तथ्य पर भी बल देती है की शिक्षा केवल किताबी ज्ञान तक सीमित न रहकर कला, भाषा और लोक-परंपराओं के एकीकरण के माध्यम से समग्र शिक्षा के लक्ष्य को प्राप्त कर सकें। इसमें भारतीय ज्ञान प्रणालियों के पुनरुद्धार की चर्चा की गई है, जिससे विद्यार्थी अपनी भाषाई अस्मिता और क्षेत्रीय विरासत पर गर्व करना सीख सकें। राष्ट्रीय शिक्षा नीति में वर्णित सांस्कृतिक अवधारणा के विश्लेषण से यह स्पष्ट है कि सांस्कृतिक बोध किस प्रकार विद्यार्थियों में सहिष्णुता और &#39;वसुधैव कुटुम्बकम्&#39; जैसे भारतीय मूल्यों को जागृत करता है।

Sir Syed Ahmad Khan is among the foremost educational reformers of nineteenth-century India who sought to reconstruct Muslim society through modern, rational, and morally grounded education. Modern education has been shaped by globalization, technological advancement, and market demands, prioritizes skill development and innovation. 19th century Indian educationists established the intellectual and institutional foundations for the cause of modern education in India while experiencing the cultural upheaval and colonial disturbance. Sir Syed Ahmad Khan played his part in transforming Indian educational landscape by his multidisciplinary and holistic educational model. Sir Syed Ahmad Khan championed western styled education system by integrating the religious identity of Indian Muslims with scientific temperament. This research paper presents an in-depth analysis of multidisciplinary and holistic educational model proposed and implemented by Sir Syed Ahmad Khan in context to modern education signifying his concord and conflict in ideological, cultural, and religious standpoints. This study is a qualitative content analysis-based literature review that examines his respective educational model aimed at tracing his long term impact on Muslim community in particular and Indian society in general. This paper undertakes a comparative analysis of Sir Syed Ahmad Khan’s educational model and modern education, highlighting areas of convergence and divergence in philosophy, curriculum, pedagogy, and social orientation. It argues that while modern education excels in technological and interdisciplinary advancement, Sir Syed’s model offers a value-centric framework that remains relevant for addressing contemporary ethical and identity challenges.

Shampoo is one of the cosmetic items that use surfactants as its principal ingredient. When used as directed, the shampoo will clean the hair of surface grease, filth, and skin debris without having an unfavorable effect on the user. A more radical approach in popularizing herbal shampoo would be to change the consumer expectations from a shampoo, with emphasis on safety and efficacy. Suitable for all hair types, our shampoo helps reduce frizz, adds shine, and protects against damage. Experience healthier, more vibrant hair with every wash.".This review focuses on the advantages, disadvantages, ideal properties, preparation method, evaluation techniques of shampoo formulation.

This review paper critically examines how media representations of religious conflicts shape public perception, influence social cohesion, and impact conflict dynamics in Nigeria. By analyzing studies on framing, language use, ownership biases, and the role of both traditional and social media, the review explores how various reporting approaches contribute to either escalation or de-escalation of tensions. It also highlights the potential for media to act as a peace building tool when ethical, conflict-sensitive reporting practices are employed. This review thus emphasizes the need for balanced, context-sensitive media portrayals to foster informed public discourse and social harmony.

Zirconia-based crowns have emerged as one of the most widely used all-ceramic restorative options in modern dentistry due to their superior mechanical strength, favorable biological response, and continuous improvements in esthetic properties. Initially introduced as a framework material for porcelain-veneered restorations, zirconia has undergone significant evolution through advancements in material engineering and digital manufacturing technologies. This review article provides an in-depth analysis of zirconia crown materials, including their crystallographic structure, classification based on yttria content and translucency, clinical performance, and recent innovations such as multilayer zirconia, ultra-translucent formulations, CAD/CAM workflows, and additive manufacturing. Current limitations and future research directions are also discussed to guide clinicians in evidence-based material selection.

The controversy between fair value accounting and historical cost accounting has become more heated since the financial crisis in 2008, especially in regard to which accounting standard is more useful in providing reliable financial reports in times of turmoil in economies. The following review aims at synthesizing existing bodies of knowledge in research studies focusing on these two models, outlining in depth their theoretical bases, applications, and conditions under which they would be more useful for specific stakeholders. Fair value accounting is relevant and up-to-date but can be subject to speculation and turbulence in markets, and historical cost is stable but may not reflect actual economic data in times of turmoil. Based on eighteen research studies and theoretical frameworks, this paper will explore the application and functionality of these two models in diverse economic conditions, especially in times of turbulence and uncertainty. The conclusion of this paper is showing that neither of these models can provide a general solution and that context-dependent applications and combinations may provide a solution for increasing and specific needs in financial accounting in these new technological and highly unstable economic times.

Ensuring examination integrity in Nigerian higher institutions remains a persistent challenge, particularly in environments with unreliable internet connectivity. While our earlier work (Dimoji et al., 2025) introduced a cost-effective, QR code–based system to combat student impersonation, its reliance on real-time online database queries rendered it vulnerable to network outages, a common constraint in many examination settings. To address this critical limitation, we present an enhanced, offline-first verification system that operates independently of network availability at the point of use. The proposed architecture leverages securely encrypted, pre-downloaded examination rosters containing only essential data: student registration numbers mapped to official photographs. This minimalist approach enables rapid, secure, and reliable verification using standard low-cost mobile devices, without requiring biometric hardware or continuous connectivity. By shifting from dynamic online queries to static, pre-provisioned data packets, our solution retains the original system’s speed and affordability while significantly improving robustness, privacy, and operational predictability. This offline-first model, designed specifically for resource-constrained contexts, offers a practical and scalable pathway to safeguard examination integrity where it is needed most.

Everyone prefers to obtain a gold loan in today's modernized world since it can be obtained quickly from banking institutions and non-banking financing institutions, where preference for other credit was comparably less because it takes time. This article examines the availability of gold loans in State bank of India (SBI) and ICICI Banks and the preference of the borrowers in obtaining the borrowers' level of familiarity with lending guidelines, and compared the trends of NPA of both the banks over the last five years. Ascertain yearly fluctuations in terms of profitability, liquidity and efficiency of SBI and ICICI banks. Five years of financial data were gathered in different secondary sources. By analyzing the net profit growth and comparing of liquidity ratios in SBI bank and ICICI Bank. The bank gold loan interest rates for SBI compared to ICICI Bank. The processing fees collected by SBI are 10.55% for 36 months and ICICI Bank will be charged 10.50% for an year as per the amount pledged. The SBI Bank is performing very well in terms of earning net profit over the last five years as compared to ICICI. The ICICI Bank current ratio is high when compared to SBI. Net profit growth of SBI is 492.26 in 2020-21 that is very high when compared to ICICI which is 97.31. Earnings per share are very high in ICICI Bank when compared to SBI during the year 2020-2024. It is find that return on equity of ICICI Bank is high from 2018-2022. P/E ratio of SBI is very high in 2017-2018 than ICICI Bank.

Web development has evolved significantly with cross-platform frameworks that promise unified development experiences across multiple platforms. Flutter, Google's UI toolkit, has emerged as a revolutionary framework extending beyond mobile applications to comprehensive web development. This research presents a systematic analysis of Flutter's web development capabilities, performance characteristics, and comparative evaluation against traditional web frameworks including React, Angular, and Vue.js. The study employs mixed-method research combining quantitative performance analysis, real-world case studies, and comparative benchmarking to evaluate Flutter web applications. Performance analysis was conducted using Chrome DevTools, Lighthouse metrics, and Flutter DevTools across multiple test scenarios including rendering performance, bundle size optimization, and user interaction responsiveness. With the introduction of WebAssembly (WASM) support in Flutter 3.22+, web applications demonstrate 42% faster rendering performance and 37% improvement in startup times compared to traditional CanvasKit rendering. Through examination of enterprise implementations including Google Ads (100M+ users), BMW My BMW App (47 countries), and eBay Motors (98.3% code sharing), this research demonstrates Flutter web's viability for interactive applications. The analysis reveals Flutter's strength in cross-platform development, with recent surveys indicating 68% of developers building for web, desktop, and mobile from a single codebase. However, challenges persist in search engine optimization (SEO), initial bundle sizes (2.5-3MB for WASM builds), and limited compatibility with older browser versions. Key findings indicate Flutter web achieves optimal performance for Progressive Web Apps (PWAs), interactive dashboards, real-time data visualization, and enterprise applications requiring consistent user experiences across platforms. Conversely, Flutter web demonstrates limitations for content-heavy websites, blogs, and SEO-critical applications where search visibility is paramount. The research concludes with practical recommendations for developers and organizations considering Flutter for web development projects, including decision frameworks, optimization strategies, and implementation best practices for 2025.

The paradigm of protein nutrition has undergone substantial transformation with growing evidence supporting plant-based macromolecules as viable alternatives to animal-derived proteins for skeletal muscle anabolism. This comprehensive review examines the biochemical properties, amino acid profiles, and physiological mechanisms through which botanical biopolymers influence myofibrillar protein synthesis and regulate muscle protein breakdown. Contemporary research demonstrates that strategic combinations of legume, cereal, and oilseed proteins can provide complete essential amino acid profiles necessary for optimal muscle protein accretion. This review synthesizes current understanding of leonine thresholds, digestive kinetics, and anabolic signalling pathways activated by plant proteins, while addressing considerations of bioavailability, anti-nutritional factors, and practical applications for athletic performance and clinical populations.

The empowerment of women, probably is one of the most oft-repeated statements that we come across in our society quite frequently. The fact that we in India repeatedly, have to use it, itself is suggestive that we actually are far off from a stage where women in our country could really be classified as empowered. Since they are yet to be so, we keep talking, discussing, putting up ideas, discussing in seminars/webinars and honestly, very few genuinely working towards achieving that goal.

Community Medicine traditionally emphasizes population-level strategies such as disease prevention, health promotion, and control of communicable and non-communicable diseases. Homoeopathy, in contrast, is fundamentally individualized, with Materia Medica forming the cornerstone of therapeutic decision-making based on the principle of similimum. At first glance, these approaches appear conceptually divergent. However, both systems share a common objective: the restoration and preservation of health. This review explores the conceptual and practical integration of Homoeopathic Materia Medica principles into the framework of Community Medicine. Through an analysis of classical homoeopathic literature, public health models, and integrative healthcare perspectives, the paper examines how individualised remedy knowledge can inform preventive, promotive, and community-level interventions. The review argues that Materia Medica, when applied beyond the clinic, can contribute meaningfully to community health initiatives by addressing susceptibility, resilience, and early functional disturbances at the population level. Such integration offers a complementary paradigm for strengthening holistic and person-centred approaches in Community Medicine.

This review examines the recent literature on Arabic education in Nigeria, synthesizing historical trends, prevailing challenges, and emerging prospects. Major trends include the persistence of Arabic across formal and informal educational settings, continued delivery through NCE and university programmes, and increasing attention to ICT integration. Key challenges identified in the literature are shortages of qualified teachers, inadequate instructional materials and curricula misalignment, low student motivation, infrastructural deficits, and uneven adoption of technology. Promising prospects include curriculum review (NCE minimum standards), teacher professional development, the growth of e-learning and digital resources, and policy interventions that integrate Arabic education into mainstream teacher education. The review concludes with recommendations for curriculum reform, investment in teacher training and ICT infrastructure, and targeted empirical studies to fill persistent knowledge gaps.

This paper presents the development of a kinematic identification framework for the directional motion of a fixed-wing aircraft based on the ARMAX (Auto-Regressive Moving Average with eXogenous inputs) model. The proposed approach aims to accurately identify the dynamic relationship between control inputs and the aircraft’s directional motion variables by utilizing measured flight data. First, the kinematic equations governing the directional motion of the fixed-wing aircraft are established. Subsequently, an ARMAX model structure is constructed to represent the system dynamics, in which appropriate model orders are selected to balance accuracy and computational efficiency. The model parameters are identified using input–output data obtained from simulation or experimental flight tests. The effectiveness of the proposed identification framework is evaluated through numerical simulations, where the identified model demonstrates good agreement with the reference data in both transient and steady-state responses. The results confirm that the ARMAX-based kinematic identification framework is capable of capturing the essential characteristics of the aircraft’s directional motion and can serve as a reliable basis for further control system design and performance analysis.

Sunscreens have evolved significantly over the past few decades, transitioning from simple UV-blocking creams to advanced multifunctional formulations that provide broad-spectrum protection, photostability, enhanced cosmetic appeal, and additional skin benefits. This review paper explores recent innovations in sunscreen technology, including nano-based delivery systems, hybrid filters, encapsulation techniques, antioxidant-fortified sunscreens, water-resistant formulations, and environment-friendly alternatives. Modern sunscreens aim to overcome major limitations found in traditional formulations, such as photodegradation, white cast formation, poor spreadability, and inadequate UVA protection. The review further highlights regulatory considerations, challenges in formulating safe filters, and future directions such as DNA-repair enzymes and wearable UV-monitoring systems. This comprehensive overview aims to help researchers and formulators understand current advancements and potential developments in sunscreen science.

Herbal hair shampoo is gaining significant attention as a natural and safer alternative to synthetic shampoos that often contain harmful chemicals like sulfates, parabens, silicones, and artificial fragrances. With increasing awareness about hair health and the side effects caused by chemical-based products, consumers are now shifting towards herbal formulations that use botanical extracts to cleanse, nourish, and strengthen hair. This review paper explores the concept, formulation, ingredients, mechanism of action, market trends, advantages, limitations, and future scope of herbal hair shampoos. Herbal shampoos are formulated using plant-based extracts such as shikakai, reetha, amla, hibiscus, neem, bhringraj, fenugreek, aloe vera, and tea tree oil. These herbs possess cleansing, conditioning, antibacterial, antifungal, antioxidant, and hair-strengthening properties. Bioactive compounds like saponins (natural cleansers), flavonoids, tannins, alkaloids, phenols, and vitamins contribute to scalp nourishment and hair growth. Studies highlight that natural saponins from reetha and shikakai provide a gentle cleansing effect without disturbing the scalp's natural pH. Amla and bhringraj extracts help reduce hair fall, increase hair density, and strengthen hair follicles. Neem and tea tree oil exhibit strong antimicrobial activity useful in treating dandruff and scalp infections. Aloe vera hydrates and soothes the scalp, reducing irritation.

This theoretical review examines the application of deep learning algorithms in automated code review and bug detection, highlighting their potential to improve software quality and development efficiency. Traditional static and dynamic analysis tools often struggle with complex code patterns and require extensive manual tuning. Deep learning models, particularly recurrent neural networks, convolutional architectures, and transformer-based language models, provide data-driven approaches capable of learning semantic and syntactic relationships directly from source code. These models enable automated identification of bugs, code smells, security vulnerabilities, and stylistic inconsistencies with higher accuracy and adaptability. The review also discusses key challenges, including the need for large, high-quality labeled datasets, handling diverse programming languages, and ensuring model interpretability for developers, emphasized by many scholars in this domain. Despite these limitations, deep learning continues to advance automated code analysis, offering promising directions for intelligent development environments and continuous integration pipelines. Overall, the theoretical foundations suggest substantial benefits for future software engineering practices.

Bone marrow cancers involve a mixed group of tumors that are mainly a hematopoietic system problem leading to blood cells production, differentiation, and functioning in a way that is not normal. These cancers consist of leukemia, lymphoma, multiple myeloma, myelodysplastic syndromes, and myeloproliferative disorders, and they are all characterized by the same bad effects on health and life expectancy. Among the different therapeutic approaches to treating these malignancies, the infusion of healthy hematopoietic stem cells known as Hematopoietic Stem Cell Transplantation (HSCT) is considered to be one of the most effective and possibly curative methods. The purpose of this review paper is to present the role of HSCT in bone marrow cancer in a very detailed manner, discussing the classification and pathophysiology of bone marrow tumours, the biological properties of stem cells, and the various methods of transplantation, autologous, allogeneic, and syngeneic HSCT being the main ones. Also, the different types of stem cell sources are explained so that readers can know the characteristics of bone marrow, peripheral blood, and umbilical cord blood as well as their pros and cons. Furthermore, the indications for HSCT, the selection of patients, the conditioning regimens, the transplantation procedures, and post-transplant care are described in detail. Hematopoietic stem cell transplantation (HSCT) is a powerful but complicated treatment option for such patients with significant issues like graft-versus-host disease, severe infections, toxicity to organs, relapse, and long-lasting quality-of-life problems. These issues put a spotlight on the importance of performing thorough patient evaluation, selecting the right donor, and then providing the best supportive care available. The recent developments in the field of transplantation, such as better HLA matching, reduced-intensity conditioning regimens, mobilization of peripheral blood stem cells using granulocyte colony-stimulating factor, ex vivo stem cell expansion, and using umbilical cord blood as an alternative stem cell source, have all made a huge difference in the outcome of transplants. In addition, emerging molecular and cellular techniques that target tumor cells through purging and immunomodulation make it safer and more effective to use HSCT for patients. In conclusion, HSCT still is a fundamental treatment for bone marrow cancers, as it offers not only a higher chance of survival but also disease control in the long run for selected patients. Research that is continuous and the development of technologies that are advanced are still at refining the methods of transplantation, reducing the complications, and increasing the use of HSCT, which is why it is still a vital part of modern hematologic oncology.

The study investigated the prospect of eco-friendly dyes extracted from L. perenne, M. maximus and S. officinarum. The aim was to extract and characterise the natural dyes. The extraction process involved Soxhlet techniques of the plants. The dye extracts were purified using chromatographic techniques. Fourier transform infrared spectroscopy techniques were used to characterise the isolates. Extraction was carried out at different temperatures. At a temperature of 80°C, ethanol was more efficient for extracting natural dye from the plants, with absorbance values of (1.4), (1.604) and (1.46) with a 29.88, 30.4 and 29.93 percentage recovery for L. perenne, M. maximus and S. officinarum within the wavelength of 200-800 nm. The dye extracts were subjected to thin-layer chromatography to separate the crude extracts on the basis of polarity and purify the extracts using column chromatography. The purified dye extracts were characterised using FT-IR. The FTIR study suggested the absorption band frequencies 3287.5-2937. 1 cm⁻¹ is assigned to N-H stretching, 3362. 1 cm⁻¹ to O-H stretching, 2927.7 cm⁻¹, 2881.2 and 937.1 cm⁻¹ to symmetric C-H stretching, 1651.2 cm⁻¹ and 1047.4 cm⁻¹ to C=C stretching, 1461. 1 cm⁻¹ vibration to –CH₂, 2937. 1 cm⁻¹ to C-H stretching, 1640 cm⁻¹ to C=O and 1461 cm⁻¹ are assigned to C=C stretching in the dye structure. Thus, the findings can inspire further research and development in utilising the plants for natural dye production.

Cybersecurity has become a major concern in modern digital environments due to the widespread use of internet services, cloud computing, and interconnected network devices. As cyber-attacks grow in frequency and complexity, traditional Intrusion Detection Systems that rely on fixed rules or known attack signatures struggle to identify new and evolving threats. This project focuses on developing a Time Series–based Intrusion Detection System that analyzes network traffic patterns over time to detect abnormal behavior. By studying temporal trends and deviations in network data, the proposed system improves the identification of suspicious activities without depending solely on predefined attack signatures. The proposed system combines data preprocessing, feature extraction, and time series–based analysis to distinguish between normal and malicious network activities. Standard benchmark datasets such as NSL-KDD and CIC-IDS-2017 are used for training and evaluation. Preprocessing steps including data cleaning, normalization, feature selection, and dimensionality reduction are applied to enhance detection performance and reduce computational overhead. By analyzing temporal patterns and variations in network traffic over time, the system effectively identifies anomalies while minimizing false alarms and improving overall detection accuracy.

Continuous Integration and Continuous Deployment (CI/CD) pipelines are central to modern DevOps practices, enabling rapid and reliable software delivery. However, speed-focused pipelines often compromise software quality. This paper proposes a structured software engineering process framework that integrates quality assurance, automated testing, security validation, and continuous monitoring into CI/CD pipelines to ensure consistent delivery of high-quality software systems.

Crop yield and efficiency in farming are significantly dependent on the early identification and prediction of plant leaf diseases. In Many Times machine learning algorithms have surfaced as potent instruments for mechanizing this procedure, offering farmers a precise and effective way to recognize and handle leaf illnesses. With a focus on early disease prediction before the formation of observable symptoms. In the field of agriculture, sustaining high yields and guaranteeing food security depends on the early diagnosis of diseases in crops like tomato plants.which have demonstrated promise in automating disease diagnosis procedures.

Sari-sari stores are a vital component of the Philippine grassroots economy, serving as the most accessible source of daily necessities for many communities. In recent years, the rapid expansion of financial technology (fintech), particularly digital payment platforms and e-wallet systems, has reshaped retail transactions and business operations among micro, small, and medium enterprises (MSMEs). This study examines the role of financial technology adoption in enhancing the operational effectiveness of sari-sari stores, with particular attention to transaction efficiency, cash flow management, customer responsiveness, and financial inclusion. Using a thematic literature analysis of studies published between 2022 and 2025, the research synthesizes empirical findings from national and regional contexts, including evidence from the Cordillera Administrative Region (CAR). The analysis reveals that fintech adoption contributes positively to faster transaction processing, improved financial awareness, enhanced customer convenience, and expanded access to formal financial services. However, the findings also highlight persistent barriers that limit the full realization of these benefits, such as unstable internet connectivity, limited digital literacy, cost sensitivity, and perceived transaction and cybersecurity risks. These constraints result in uneven adoption outcomes across urban and rural settings. The study concludes that while financial technology offers significant potential to strengthen the operational effectiveness and resilience of sari-sari stores, its impact is highly dependent on enabling infrastructure, affordable fintech solutions, and targeted capacity-building interventions. The findings provide valuable insights for policymakers, financial institutions, and development agencies seeking to promote inclusive digital transformation and sustainable growth among grassroots micro-enterprises in the Philippines.

The paper summarizes the company's problem (significant financial losses), the proposed solution (a strategic recovery plan), and the expected outcome (sustainable profitability). It will Key mention the root cause analysis, the core strategies (e.g., cost optimization, revenue generation), the timeline for recovery, and the expected final impact on stakeholders. NovaTech Solutions Ltd., once a leader in the Smart Home IoT sector, faced a "perfect storm" of unforeseen external shocks and internal mismanagement, resulting in a $15 million annual net loss. This paper analyses the root causes of this decline, specifically focusing on supply chain volatility and technical debt. It proposes a three-phased recovery plan—Stabilization, Restructuring, and Strategic Growth—to restore the company to a $5 million annual profit within 36 months. It also analyses the case study between two companies regarding the structure of falling and recovering of company in terms of recovery to growing aspects. The modern corporate landscape is defined by extreme volatility, where the transition from sustainable growth to systemic loss can occur with startling velocity. This abstract delineates a comprehensive Strategic Road Map designed to navigate organizations through the critical phases of financial distress toward a state of robust profitability. The roadmap serves as both a diagnostic tool for identifying the root causes of fiscal haemorrhaging—such as operational inefficiency, market misalignment, and excessive leverage—and a prescriptive framework for structural renewal [1-2]. At the core of this strategic intervention is the Dual-Track Recovery Model, which balances immediate tactical retrenchment with long-term strategic investment. The process begins with Phase I: Radical Stabilization, focusing on the preservation of liquidity through zero-based budgeting, the liquidation of non-core assets, and the immediate suspension of non-essential capital expenditures. This phase is designed to "stop the bleed" by lowering the company’s break-even point (BEP), ensuring that the organization can survive the short-term volatility required for deeper restructuring.

In the immediate aftermath of India’s independence in 1947, the seeds of the India–China border dispute were already present, rooted in colonial-era boundary arrangements that China never accepted. The eastern sector was defined by the McMahon Line, drawn during the 1914 Simla Convention between British India and Tibet, but rejected by China. In the west, the accession of Jammu & Kashmir to India in October 1947 introduced complexities over Aksai Chin. Thus, when India became independent, it inherited ambiguous frontiers: China did not recognize the McMahon Line, and the western boundary was unsettled. These unresolved issues hardened after the establishment of the People’s Republic of China in 1949, setting the stage for decades of contestation that escalated into the 1962 war.

Rubiaceae, the coffee family1 is considered to be one of the largest families of Angiosperms comprising 606 genera and about 10,000 species of trees, shrubs, lianas and herbs, sometimes anti inhabited, epiphytic or aquatic. The leaves are simple and usually entire and flowers are typically regular and bisexual with 4-5 fused petals. Members of Rubiaceae are distributed more widely all parts of the earth. All the genus of the family are economically important. The most economically important genus of the family is Coffea, the source of coffee; other members are important medicinally or as ornamentals. Some are used as a source of dye. A detailed general survey of the chemical constituents of the species of Rubiaceae family and the pharmacological activity of the members of Rubiaceae is presented in Table-1 and Table-2 respectively.

This academic essay examines the quite quitting in Philippine education as a systemic symptom of eroded psychological contracts. Analyzing the macro, meso, and micro levels, it argues that chronic disengagement stems from policy failures, poor leadership, and unsustainable workloads, which collectively deplete teachers’ vocational passion. Drawing on international literature and local studies, the analysis frames this withdrawal as a rational, self-preserving protest against conditions that hinder institutional mission. It concludes that reversing this trend requires integrated reforms –humane policies, transformational leadership, and cultural shifts to realign organizational systems with teacher well-being and restore the sector’s relational core.

The contemporary pharmacist has evolved from a medication dispenser to a critical healthcare professional positioned at the intersection of medication safety, public health, and substance misuse prevention. This review examines the expanding scope of pharmacy practice in addressing two interconnected challenges: the mitigation of substance misuse and the monitoring of complex medication side effect profiles. Through integration of prescription drug monitoring programs, medication therapy management services, harm reduction initiatives, and advanced clinical surveillance systems, pharmacists serve as essential gatekeepers and patient advocates. This article synthesizes current evidence on pharmacist-led interventions, evaluates their effectiveness in reducing substance misuse, and explores innovative approaches to side effect monitoring in an era of polypharmacy and complex therapeutic regimens. The analysis reveals that pharmacists possess unique positioning, accessibility, and clinical expertise that enable transformative contributions to these pressing healthcare challenges, yet systemic barriers continue to limit their full potential.

Cybersecurity management in critical infrastructure has emerged as a paramount concern in contemporary society, given the increasing digitalization and interconnectedness of essential services including energy, water, transportation, healthcare, and telecommunications. Critical infrastructure systems are fundamental to national security, economic stability, and public welfare, making them attractive targets for cyberattacks from state-sponsored actors, terrorist organizations, and criminal entities. The vulnerabilities inherent in these systems pose significant risks not only to operational continuity but also to social stability, public safety, and citizen trust in governmental institutions. This study examines the multifaceted dimensions of cybersecurity management within critical infrastructure sectors, analyzing the technical, organizational, and policy frameworks employed to mitigate cyber threats. Furthermore, it explores the profound social consequences that emerge from both successful cyberattacks and the implementation of cybersecurity measures themselves, including issues of privacy, civil liberties, digital equity, and social resilience. The research synthesizes existing literature, identifies gaps in current approaches, and proposes comprehensive strategies for enhancing cybersecurity posture while balancing societal values and individual rights. Through examining case studies of critical infrastructure incidents and their cascading social impacts, this study contributes to understanding the complex relationship between technological security measures and broader social implications in an increasingly digitally dependent world.

Banking and financial literacy have become essential in today’s rapidly growing economy. This study focuses on understanding the level of banking and financial awareness among college students in Chh. Sambhajinagar city. Both primary and secondary data were used, with a sample of 100 students from Arts, Commerce, and Science streams. The study examined students’ knowledge about various banking services, such as debit and credit cards, cheques, cancelled cheques, mobile banking (UPI), RTGS/NEFT, ATM limits, bad banks, loans, and banking complaints. The findings indicate that while some students have awareness of basic banking services, many lack detailed knowledge, especially regarding modern digital banking and financial protections like deposit insurance. Commerce students generally showed slightly higher awareness compared to Arts and Science students, but overall literacy is moderate. The study also highlights the need for workshops, guides, public awareness campaigns, and creative use of media to improve both banking and financial literacy. This research emphasizes that educated and informed customers are essential not only for individual financial security but also for the overall development of the economy. Strengthening financial literacy can help prevent fraud, improve money management, and make banking services more effective for everyone.

The AI-Driven Career Intelligence and Job Recommendation Platform is a mobile-first, cloud-enabled system that transforms how job seekers discover opportunities and close skill gaps through personalized, AI-powered guidance. Traditional job search tools surface generic listings and provide limited insight into how a candidate’s background aligns with role requirements. This platform addresses those limitations by combining sophisticated AI search, natural language understanding, and resume analysis to deliver contextualized job matches and actionable career advice. Job opportunities are discovered and indexed using an AI search layer that normalizes and enriches listings with semantic metadata—skills, experience levels, salary bands, and role specializations—enabling accurate matching against user profiles. Users create rich profiles and upload resumes (PDF/DOCX); an LLM-driven resume analyzer extracts skills, projects, education, and experience, storing structured representations for fast comparison. Bookmarked jobs act as a curated portfolio: the system performs a multi-job skill-gap analysis to compute match scores, prioritize missing competencies, and generate targeted learning recommendations with estimated effort, resources, and project ideas. Architecturally, the platform follows modular service principles: a Node.js/Express backend exposes RESTful APIs for profile management, job indexing, bookmarking, and AI analysis; Supabase/Postgres provides persistent storage (including JSONB fields for flexible resume analysis), while the React Native frontend (Expo) delivers a responsive, offline-friendly UX using AsyncStorage and intelligent caching. Security and reliability are enforced via authenticated endpoints, input validation, rate limiting for AI calls, and resilient error handling. By integrating AI-driven discovery with personalized, resume-aware guidance, the platform moves beyond passive job listings to a proactive career development tool—helping candidates discover relevant roles, understand precise gaps, and follow prioritized learning paths that improve employability and accelerate career progression.

FishVision is an intelligent, AI-driven mobile platform developed to automate the identification and classification of fish species in real time. Traditional methods of fish recognition in fisheries research and aquatic biodiversity studies are often manual, time-intensive, and prone to human error. FishVision bridges this gap by leveraging computer vision and deep learning technologies to deliver an accurate, efficient, and user-friendly solution for fishermen, marine biologists, researchers, and conservationists.The platform employs an integrated artificial intelligence pipeline combining YOLOv8 (You Only Look Once) for object detection and a TensorFlow/Keras-based Convolutional Neural Network (MOBILE NET) for fine-grained species classification. The system is capable of detecting multiple fish species within a single image, assigning each a confidence score to indicate prediction reliability. The underlying machine learning models are trained on a curated dataset of regionally significant species, covering more than 700 varieties, including freshwater and marine taxa. The use of OpenCV for preprocessing and image enhancement ensures robustness across varying lighting and environmental conditions,the mobile application offers a seamless cross-platform experience across Android, iOS, and web interfaces. It integrates an offline-first fish database, enabling continuous accessibility in remote fishing regions with limited connectivity. The backend, developed with Node.js and Express.js, incorporates a lightweight SQLite database and implements secure JWT-based authentication for user management and data protection.Beyond simple classification, FishVision functions as an educational and research tool, offering detailed biological, ecological, and taxonomic information for each species. Its modular architecture allows future integration of location-based features, AR-based species visualization, and real-time community reporting. By uniting modern AI, mobile computing, and marine science, FishVision transforms species identification into a smart, accessible, and scalable ecosystem that supports sustainable fisheries management and biodiversity conservation.

Hackathon success critically depends on balanced, interdisciplinary teams. Traditional methods (self-selection or random grouping) often produce skill imbalances and poor collaboration. Team Sangam AI addresses this by using AI to form teams based on participants’ technical skills, interests, and soft‐skill profiles. Resumes and profiles are parsed via NLP to extract expertise, then participants are clustered (e.g., K-Means) into heterogeneous teams covering complementary skills. Optionally, an LLM (such as the OpenAI API) analyzes text responses or psychometric inputs to infer personality traits, ensuring interpersonal compatibility. Early results suggest that this data-driven approach yields more equitable, well-rounded teams and improves outcomes (since balanced teams outperform random onesjournals.mriindia.com). The platform also records historical team performance to continually refine its matching models. This paper presents the architecture of Team Sangam AI, a proposed tech stack, potential training datasets, and a step-by-step workflow. The system aims to enhance hackathon experiences by promoting diversity, fairness, and collaboration, thereby advancing team formation beyond static manual methods.

The digital transformation of human resource management has fundamentally reshaped organizational practices through the implementation of Electronic Human Resource Management (E-HRM) systems. This empirical study examines the adoption, implementation, and impact of E-HRM systems across multiple organizations to understand how digital technologies are revolutionizing traditional HR functions. The research investigates the extent to which E-HRM systems enhance operational efficiency, improve employee satisfaction, and contribute to strategic decision-making processes. Through a comprehensive analysis of data collected from HR professionals and employees across various industries, this study reveals significant correlations between E-HRM adoption and organizational performance metrics. The findings indicate that organizations implementing comprehensive E-HRM systems experience reduced administrative costs, improved data accuracy, enhanced employee engagement, and better alignment between HR strategies and business objectives. However, the study also identifies critical challenges including technological resistance, implementation costs, data security concerns, and the need for continuous training. The research contributes to existing literature by providing empirical evidence on the transformative potential of E-HRM systems while offering practical recommendations for organizations navigating digital HR transformation. The study emphasizes that successful E-HRM implementation requires strategic planning, stakeholder engagement, and organizational readiness to embrace technological change.

The increasing demand for safe, effective, and natural skincare products has led to significant interest in polyherbal formulations for dermatological applications. Polyherbal creams incorporating medicinal plants such as Neem (Azadirachta indica), Turmeric (Curcuma longa), Aloe vera (Aloe barbadensis), Tulsi (Ocimum sanctum), and Manjistha (Rubia cordifolia) have gained attention due to their synergistic therapeutic properties, including antimicrobial, anti-inflammatory, antioxidant, wound-healing, and skin-rejuvenating effects. This comprehensive review focuses on the formulation strategies, excipient selection, and evaluation parameters involved in the development of polyherbal creams intended for skin protection and rejuvenation. Various formulation techniques, types of bases, and stability considerations are discussed in detail. Additionally, critical evaluation methods such as physicochemical characterization, microbial testing, skin irritation studies, Spreadability, viscosity, pH, stability, and in vitro efficacy assessments are systematically reviewed. The therapeutic relevance and safety profile of each herbal ingredient are also highlighted. Overall, this review emphasizes the potential of polyherbal cream formulations as effective, safer alternatives to synthetic dermatological products and provides a scientific framework for future research and development in herbal skincare formulations.

This paper investigates the evolution of theoretical approaches to sculpture, tracing its intellectual journey from the principles of formalism through the innovations of modernism and into the complexities of postmodernist thought. It emphasizes how these shifting frameworks have profoundly shaped the creation, interpretation, and critique of sculptural works across different historical moments. Formalism, with its focus on the intrinsic qualities of form, material, and visual arrangement, established a foundation for evaluating sculpture based on aesthetic purity and compositional balance. Modernism, by contrast, introduced a radical emphasis on originality, experimentation, and the breaking of traditional boundaries, positioning sculpture as a medium of innovation and self-expression that reflected broader cultural and technological changes. Postmodernism then challenged these earlier certainties, questioning the very idea of fixed meaning and embracing multiplicity, irony, and contextual interpretation, thereby redefining sculpture as a site of dialogue between diverse perspectives and cultural narratives. By examining these transitions, the paper highlights how artistic priorities and philosophical underpinnings have shifted over time, offering valuable insights into the changing role of sculpture within the broader art context, where it is no longer confined to formal aesthetics but is instead understood as a dynamic and contested field of meaning.

The growing convergence of environmental challenges and rapid digital transformation has intensified calls for education systems to cultivate sustainable, future-ready skills. In response, green technology has emerged as a critical catalyst for skills sustainability in 21st-century education. This article examines how sustainability-oriented technologies can enhance the relevance, adaptability, and longevity of learners’ competencies in an era of ecological uncertainty and economic transition. Anchored in Education for Sustainable Development, human capital theory, and constructivist learning perspectives, the study adopts a conceptual and analytical approach informed by recent empirical research and international policy frameworks. The article explores how green technologies, such as renewable energy systems, digital simulations, environmental data platforms, and low-carbon digital infrastructure, reshape curricula and pedagogy by fostering experiential, interdisciplinary, and problem-based learning. These approaches support the development of transferable competencies, including critical thinking, systems analysis, digital and environmental literacy, collaboration, and ethical reasoning. The discussion further highlights the importance of coherent policy alignment, institutional leadership, teacher professional development, and equitable infrastructure investment in enabling effective implementation, particularly in developing contexts. The article concludes that integrating green technology into education represents a transformative strategy for advancing skills sustainability, strengthening learners’ adaptability, and positioning education as a central driver of sustainable development in a rapidly changing world.

भारत में सामाजिक एवं आर्थिक न्याय की अवधारणा संविधान में निहित उस आदर्श व्यवस्था को प्रतिबिंबित करती है जिसका उद्देश्य समाज के सभी वर्गों को समान अवसर, गरिमा, सुरक्षा और संसाधनों तक न्यायसंगत पहुँच प्रदान करना है। यह शोध–लेख सामाजिक व आर्थिक न्याय के सैद्धांतिक एवं संवैधानिक आधारों का विश्लेषण करता है तथा सरकारी वित्त–प्रायोजित योजनाओं की भूमिका एवं प्रभाव को समकालीन संदर्भ में विवेचित करता है। विभिन्न कल्याणकारी कार्यक्रमों—जैसे मनरेगा, प्रधानमंत्री आवास योजना, जन–धन योजना, खाद्य सुरक्षा अधिनियम, उज्ज्वला योजना, आयुष्मान भारत, सामाजिक सुरक्षा पेंशन, छात्रवृत्ति एवं कौशल विकास योजनाओं—का तुलनात्मक अध्ययन यह दर्शाता है कि राज्य इन योजनाओं के माध्यम से वंचित समूहों को मुख्यधारा विकास से जोड़ने का प्रयास कर रहा है। लेख का निष्कर्ष यह बताता है कि यद्यपि इन योजनाओं ने सामाजिक–आर्थिक न्याय की दिशा में उल्लेखनीय प्रगति की है, लेकिन पारदर्शिता, वित्तीय दक्षता, लैंगिक संवेदनशीलता, सहभागी शासन और स्थानीय अनुकूलन अभी भी महत्वपूर्ण चुनौतियाँ बनी हुई हैं।

Pharmaceutical creams are the topically applied pharmaceutical products, either as medicated or non-medicated. This review focuses on the advantages, disadvantages, types, applications, classification, preparation methods, evaluation and formulation of cream. Not only cleansing, beautifying, and moisturizing, it also serves for medicinal purpose such as wound healing, protecting the skin against harshness from the environment help to relieve dryness, maintaining skin softness and also maintain the hydration of skin. Creams are mostly used as cosmetic products for texture against fungal and bacterial infection treating burns etc. Creams are evaluated for pH, viscosity, spreadability, appearance, acid value, etc.

This study adopted a quantitative, spatially-based research design leveraging Geographic Information System (GIS) and Remote Sensing (RS) technologies. The aim was to analyze, visualize, and predict flood vulnerability zones in Anambra West, Nigeria, using geospatial techniques. The design included systematic data acquisition, processing, integration, classification, and multi-criteria weighted overlay analysis. The work produced a multi-temporal flood vulnerability map spanning the years 2019 to 2023. The flood susceptibility map were classified into three flood risk levels: Low Risk, Moderate Risk and High Risk. The geospatial multi-criteria decision analysis (MCDA) approach was adopted, combining environmental and anthropogenic variables such as rainfall intensity, slope, elevation, distance to river, distance to road, drainage density, and land use/land cover (LULC). These parameters were reclassified into standardized classes and assigned weights based on their relative contribution to flood risks in the area. The research was structured into four phases: Data acquisition, Data pre-processing (projection, clipping, and raster alignment), Spatial and statistical analysis and Visualization and interpretation (map production and analysis).

Gamete donation has emerged to be a major aspect of Assisted Reproductive Technologies (ART), imparting new desire for individuals and couples not able to have a child in the ordinary way. The trouble of gamete exploitation, whether sperm or oocytes, is a very complicated and ethical trouble that crosses limitations and requires cautious interest. This paper explores ethics and guiding standards that entails: informed consent practices, elevating consciousness, anonymity of donor, access and fairness and infectious disease checking out. It’s far vital that the prevailing unique social and cultural scenario be maintained in view, democratic standards reputable, and to find out a way of making use of these technologies judiciously in view that they affect gift and future generations.

Chalcopyrite hydrometallurgy has been extensively examined, with particular focus on improving dissolution kinetics across a range of acidic environments, including chloride, aqueous sulphate and ammonia systems. In current copper-production practices, increasing priority is on establishing procedures that of treating low-grade sulphide ores that fall outside the applicability of conventional beneficiation routes such as crushing, grinding, and flotation. Furthermore, increasing research efforts are directed toward recuperation of copper from complex sulphide concentrates that are not amenable to pyrometallurgical routes. In most cases, extraction of copper from these materials is accomplished through leaching processes. As chalcopyrite (CuFeS₂) represents the most abundant copper sulphide mineral, substantial attention has been devoted to elucidating its leaching characteristics, as such insights are necessary for developing efficient extraction strategies for progressively lower-grade and more complex raw material. Moreover, overarching objective of these investigations is to elucidate kinetic parameters and underlying oxidation mechanisms of chalcopyrite when there are diverse oxidants (O₂, Fe³⁺, H₂O₂, chloride ions, silver ions, pyrite, and others), while concurrently generating the fundamental data required for advancing copper extraction technologies that comply with increasingly rigorous technological, economic, and environmental constraints. This paper provides a comprehensive synthesis of the current state of knowledge on chalcopyrite leaching, with particular emphasis on the oxidation processes occurring in acidic sulphate and chloride systems.

Myopia, commonly known as near sightedness, has emerged as a significant global public health concern, with prevalence rates projected to affect 50% of the world's population by 2050. This review paper provides an extensive analysis of the disease, moving from its initial pathogenesis and symptomatology to advanced diagnostic techniques. A significant portion of this review is dedicated to modern refractive interventions, specifically laser vision correction (LASIK, PRK, SMILE), detailing procedural durations, recovery timelines, and post-operative protocols. Furthermore, the paper examines the necessity of spectacle prescription updates, nutritional influences on ocular health, and preventative strategies. This review aims to synthesize current literature to provide a holistic understanding of Myopia management in the 21st century.

Rachana Sharir deals with the systematic study of human body structures through their morphological and functional attributes. The organization and actions of the body are governed by structures formed from the Saptdhatu, which together maintain physiological integrity.1Among the classical Ayurvedic texts, Sushruta Samhita holds a distinct position due to its detailed anatomical descriptions based on direct observation and dissection of the human body.2 Hence, it is considered a primary reference for understanding and interpreting complex and ambiguous anatomical structures. Snayu is one of the most significant structural entities described in Ayurvedic anatomy and is mentioned extensively in various contexts such as Marma, Agnikarma, Shastra Karma, Bandhana Karma, Sivana Karma, Siravedha, and Vatavikara. Despite its repeated references, the exact anatomical identity of Snayu has remained a subject of scholarly discussion. 2 Classical texts describe Snayu as strong, fibrous structures responsible for binding, stability, weight bearing, and maintenance of joint integrity. The present review aims to systematically compile and analyze the literary references of Snayu from Sushruta Samhitaand other Ayurvedic texts, and to correlate these descriptions with modern anatomical structures. Based on structural and functional similarities, Snayu can be conceptually correlated with fibrous connective tissues such as ligaments, tendons, and fascia described in contemporary anatomy. This integrative understanding is expected to provide clarity regarding the anatomical basis of Snayu Sharir and facilitate appropriate clinical application of therapeutic principles described in Sushruta Samhita for the management of Snayu-related disorders.

The growing use of GPS and navigation systems has significantly changed the driving experience in India. These systems help drivers find routes easily, avoid traffic congestion, save time, and reduce the stress of reaching unfamiliar destinations. At the same time, excessive dependence on GPS may reduce spatial awareness and create safety concerns when drivers follow directions without judgment. This study examines the impact of GPS navigation systems on drivers’ stress levels by analysing secondary data from transport reports, surveys, and existing studies. The findings indicate that GPS usage generally reduces driving stress and improves confidence, efficiency, and fuel savings. However, issues such as incorrect routes, network failures, and unsafe shortcuts highlight the need for cautious and informed use. The study concludes that GPS navigation systems are beneficial when used responsibly and recommends balanced usage to enhance driving comfort, safety, and sustainability.

The Zambian Constitutional Court’s recent judgment that fixed-term contract employees are not entitled to be retained on payroll until pension benefits are paid has sparked controversy. This paper examines the implication of this decision, scrutinizing article 189(2) and 266 of the constitution as well as section 73(1) (2) and, section 66(4), as the main provisions highlighting potential contradictions made by the court in the interpretation of pension rights which the constitution as granted to employees. In discussing this subject, the desk review of the superior courts judgments and legislations on employment law has been used. The judgement’s effect on worker’s rights and possible ways forward has also been discussed. In summary, the court did not holistically look at the danger of substituting the category of long-term contract employees from being retained on payroll if they are not paid at separation as by law requires. This has led to exploitation of employees’ rights in that category at separation as they endure economic hardship before they can jump on another job, as employers have intentionally continued to avoid paying employees in time but use the very judgment as a scapegoat.

In recent years, higher education has witnessed a growing shift from traditional teaching methods toward innovative, student-centred pedagogies that promote active engagement and holistic development. Among these approaches, game-based learning (GBL) and fitness-based learning (FBL) have gained considerable attention. Game-based learning emphasizes the use of structured games and gamified activities to enhance motivation, problem-solving skills, and academic engagement, while fitness-based learning integrates physical activities and exercise into the learning process to improve physical well-being, cognitive functioning, and overall learning outcomes. Despite extensive research on each approach individually, comparative studies examining their relative effectiveness among undergraduate students remain limited. The purpose of the present study was to conduct a comparative analysis of game-based learning and fitness-based learning in terms of their impact on undergraduate students’ learning engagement, motivation, and academic performance. The key variables of the study included the type of learning approach (game-based learning and fitness-based learning) as independent variables, and student engagement, motivation, and academic achievement as dependent variables. The study adopted a comparative quantitative research design, with elements of a mixed-method approach to enrich interpretation. A sample of 120 undergraduate students (aged 18–22 years) drawn from arts, science, and physical education disciplines of a university was selected using random sampling techniques. The participants were divided into two equal groups: one exposed to game-based learning activities and the other to fitness-based learning activities over a period of eight weeks. Data were collected using standardized questionnaires and achievement tests, and analysed using descriptive statistics and t-tests. The major findings revealed that game-based learning was more effective in enhancing student engagement and academic motivation, whereas fitness-based learning showed a stronger influence on physical well-being, concentration, and positive learning attitudes. However, both approaches contributed significantly to academic achievement. The implications of the study suggest that higher education institutions should adopt an integrated or hybrid instructional model combining game-based and fitness-based learning strategies to promote both cognitive and physical development of undergraduate students, thereby supporting holistic and sustainable learning outcomes.

Economic sanctions have become a central tool in contemporary international relations, operating at the intersection of political power, economic leverage, and strategic diplomacy. Traditionally designed to coerce target states into policy compliance without military intervention, sanctions have evolved into instruments of systemic influence, shaping global economic structures and political alignments. This paper examines the political economy of sanctions, analyzing how economic coercion affects trade, finance, and strategic partnerships in a multipolar world. Drawing on case studies of Russia, Iran, and China, the study highlights both the intended and unintended consequences of sanctions. While sanctions can disrupt financial systems, depress economic activity, and constrain policy options, they often induce adaptive strategies, including alternative trade networks, regional financial mechanisms, and technological self-reliance. These adaptations not only mitigate the immediate impact of coercion but also foster long-term realignments, such as the deepening of BRICS+ cooperation, de-dollarization efforts, and the creation of sanction-resilient economies. The paper integrates theoretical perspectives from realism, liberalism, dependency theory, and constructivism to explain the effectiveness, limitations, and broader implications of sanctions in shaping global interdependence. The analysis underscores that sanctions are more than punitive tools; they act as catalysts for structural shifts in international economic and political systems. Policymakers must, therefore, consider both the short-term objectives and the long-term systemic consequences of sanctions, balancing coercion with multilateral engagement and targeted strategies. The study contributes to the understanding of how economic coercion shapes international alignments in an increasingly complex and multipolar global order.

हिंदी साहित्य के इतिहास में प्रेमचंद वह महत्वपूर्ण कथाकार हैं, जिन्होंने अपनी कहानियों और उपन्यासों के माध्यम से भारतीय समाज के विविध आयामों का सूक्ष्म एवं व्यापक चित्रण किया। यह शोध-लेख प्रेमचंद के कथा-साहित्य में आदर्श और यथार्थ के पारस्परिक संबंध, ग्रामीण एवं दलित जीवन के यथार्थ चित्रण, गांधीवादी प्रभाव, सामाजिक संदर्भों और मानवीय मूल्यों की पुनर्स्थापना की प्रक्रिया का विश्लेषण करता है। लेख से स्पष्ट होता है कि प्रेमचंद का यथार्थवाद मात्र वस्तु-चित्रण नहीं, बल्कि मानवीय संवेदना और सामाजिक न्याय की आकांक्षा से संपृक्त आदर्शोन्मुख यथार्थवाद है।

Ointments are semisolid preparations designed for external application, where the drug is uniformly dispersed in a suitable base, often incorporating emulsions for better drug delivery and skin absorption. They typically include active medicinal substances and are meant for external use on the body to achieve a therapeutic outcome. Numerous medications intended for topical use on healthy or damaged skin and mucosa are formulated as semisolid preparations like ointments. As a result, ointment formulations have become a significant focus in modern pharmaceutical research due to their ease of application, physical stability, favorable dissolution characteristics, and overall therapeutic effectiveness. The ointment was formulated by blending active ingredients into the prepared base using trituration in an optimized ratio, and its quality was evaluated based on parameters like non-irritancy, ease of spreading, drug diffusion, and overall stability.

This is a phenomenological nature of study of the situation overshadowed by a society where assumption is that classroom is always under control of a teacher. It is a teacher that causes everything to happen. But really could be much further than the assumption. This is a study about psychological violence experienced by teachers in a Nepalese context. It has tried to shed light on what happens to a teacher's mental health being when bullied, tortured and disturbed by his/her own students. Obviously, the impact of students' undesirable behavior nurture by himself or in visibly other now students. Obviously, the impact teachers is daily focused in this study against teachers is daily focused in this study. This study is a mixed method study with the net data obtained from a minimal participant set. Though there exist variables in the study, they have not been quantified. The interpretation is solely based on the data collected from the questionnaire and the interview. And the conclusion is drawn in line with the purpose of the study and research questions.

Assisted Reproductive Technology (ART) has revolutionized infertility management, providing medical solutions such as surrogacy, gamete donation, pre-implantation genetic testing (PGT), and cryopreservation. While these innovations have offered new pathways to parenthood, they simultaneously raise profound ethical, social, and legal dilemmas. This paper examines key ethical concerns in ART, focusing on surrogacy, donor gametes, PGT, cryopreservation, and embryo rights. The discussion integrates bioethical principles of autonomy, beneficence, non-maleficence, and justice to evaluate practices that balance technological progress with moral responsibility. Surrogacy highlights issues of exploitation and commodification; gamete donation raises questions of anonymity and identity; PGT provokes debate over genetic selection and disability ethics; and cryopreservation introduces complex issues regarding embryo ownership and moral status. Comparative analysis of regulatory frameworks across India, the United States, and the European Union reveals varying cultural and legal approaches to ART governance. The study emphasizes the necessity for robust, ethically grounded policies that safeguard participants? rights, ensure equitable access, and prioritize the welfare of the resulting child. Ultimately, the ethical management of ART requires continuous reflection to harmonize reproductive autonomy with respect for human dignity.

Microfluidics has emerged as a transformative technology in analytical chemistry by enabling precise manipulation of fluids at the micrometer scale, thereby revolutionizing pharmaceutical and biomedical analysis. This review provides a comprehensive overview of microfluidics-based analytical methods with emphasis on their principles, fabrication strategies, detection techniques, and pharmaceutical applications. Fundamental aspects such as laminar flow behavior, low Reynolds number dynamics, and the dominance of surface forces at the microscale are discussed to explain the operational advantages of microfluidic systems. Commonly used materials including polydimethylsiloxane, glass, thermoplastics, and paper substrates are examined alongside fabrication approaches such as soft lithography, photolithography, three-dimensional printing, and paper-based patterning. The integration of microfluidics with analytical techniques including chromatography, capillary electrophoresis, immunoassays, droplet-based analysis, and biosensors is highlighted, demonstrating enhanced sensitivity, reduced analysis time, and minimal reagent consumption. Advanced detection methods such as optical, electrochemical, and mass spectrometric coupling further expand the analytical capability of lab-on-a-chip platforms. Applications spanning drug discovery, quality control, nanomedicine formulation, and point-of-care diagnostics are critically reviewed. Despite notable advantages, challenges related to fabrication complexity, material limitations, and system integration persist. Recent innovations incorporating artificial intelligence, organ-on-chip models, and scalable manufacturing approaches indicate a promising future for microfluidics as a core technology in modern pharmaceutical analysis.

The global transition toward sustainable agriculture has intensified interest in microbial biologicals?including biopesticides, biofertilizers, and biostimulants?as viable alternatives to synthetic agrochemicals. Although substantial progress has been achieved in microbial strain discovery and laboratory-scale efficacy, large-scale adoption remains constrained by formulation instability, limited shelf life, inconsistent field performance, manufacturing bottlenecks, and fragmented regulatory frameworks. These challenges have slowed the translation of promising microbial innovations into reliable, commercially scalable agricultural inputs. This review provides a critical and integrative analysis of recent advances in formulation science, industrial-scale fermentation, quality control systems, and regulatory pathways governing microbial biologicals. Particular emphasis is placed on formulation technologies?ranging from conventional wettable powders and granules to oil-based systems, microencapsulation, and emerging nano-enabled delivery platforms?and their role in enhancing microbial viability, environmental resilience, and field persistence. Key manufacturing considerations, including fermentation optimization, pilot-scale validation, downstream processing, and batch-to-batch consistency, are examined to bridge laboratory research with industrial production realities. Comparative evaluation of regulatory frameworks across major markets, including the European Union, United Kingdom, and India, highlights persistent challenges related to data requirements, approval timelines, and global harmonization. Emerging trends such as microbial consortia, artificial intelligence?assisted formulation and process optimization, and precision delivery systems are discussed as transformative strategies to improve efficacy, scalability, and commercial reliability. By synthesizing scientific, industrial, and regulatory perspectives, this review identifies critical gaps and proposes a practical framework to accelerate the development of robust, scalable, and field-effective microbial biologicals. The insights presented aim to support researchers, manufacturers, and policymakers in advancing microbial technologies as integral components of sustainable and resilient agricultural systems.

The continued issue of infectious diseases, particularly those caused by new and reemerging viruses, has highlighted the need for novel approaches to studying viral pathogenesis, immune responses and the development of effective vaccines and treatments. Immunoinformatics, a multidisciplinary area that combines bioinformatics, immunology and computational biology, is critical for tackling these difficulties. Immunoinformatics uses computational methods and large-scale datasets to predict immune responses, identify new vaccine candidates and propose therapeutic targets for viral illnesses. This strategy is especially important in the context of fast evolving viruses like SARS-CoV-2, Zika, Ebola and HIV which all represent serious hazards to world health. Immunoinformatics provides a variety of approaches, including epitope prediction, MHC (Major Histocompatibility Complex) binding analysis and immune response modeling which enable researchers to create and optimize vaccines with greater specificity and efficacy. These computational tools have transformed vaccine production by allowing the discovery of viral epitopes capable of inducing a strong immune response. Furthermore, immunoinformatics aids in understanding immune escape mechanisms and forecasting viral alterations which are critical for adjusting to the changing nature of viral infections. This review will investigate the use of immunoinformatics in the study of emerging and reemerging viruses, with an emphasis on its contributions to vaccine design, medication discovery and diagnostic development. By evaluating case studies and emphasizing successful immunoinformatics applications in controlling viral outbreaks, the research underlines the importance of accelerating the development of effective therapies. The research does, however, address the field's problems, such as restricted data availability, immune response complexity and the necessity for experimental confirmation of computational predictions. Finally, the study covers immunoinformatics' future directions, including the use of machine learning, artificial intelligence and next-generation sequencing technologies to improve the accuracy and efficiency of immunoinformatic procedures. Continued research, collaboration and innovation in computational biology are critical for strengthening global preparedness against infectious illnesses and responding quickly to future viral threats.

The idea of democracy in India came from Greece. Democracy means ensuring governance by the people so that every citizen participates in the decision-making process directly or indirectly through elected representatives. India is the largest democracy in the world. Democracy has many features (rule of law, equality, justice, transparency, accountability, promoting individual rights and liberties, etc.). Democracy is slowly changing its nature day by day. Democracy in the present era is not the same as it was before. Our country is the greatest democratic country but still, millions of people are struggling for their daily basic needs. In modern India, democracy has faced many challenges. Thus, it can be said that democracy is in trouble in some of the most mature democracies of the world. Presently Indian democracy has lost its form. The undemocratic rulers and dictators are trying to interpret the concept of democracy in their own words. They made it the most confusing theory in India. This paper attempts to examine and analyze the existing democratic system in India and its impact on the democratic system of the world. In this paper, I would like to discuss mainly the issues and challenges facing Indian democracy with some examples. In addition, I would suggest certain possible measures to ensure a healthy and sustainable democracy for India.

This paper examines how economic pressure serves as a regulatory force that shapes masculine identity in D. H. Lawrence's short stories, "The Rocking-Horse Winner" and "The Horse-Dealer's Daughter," in conjunction with Judith Butler's concept of gender performativity. The paper argues that the masculinity in Lawrence's narratives constitutes no natural or stable identity but rather one that is a socially compelled performance structured by financial anxiety, emotional repression, and cultural expectation. Lawrence exposes masculinity as a fragile and exhausting repetition of control that ultimately produces breakdown rather than coherence through Paul's obsessive pursuit of money and Jack Ferguson's faltering performance of authority. Lawrence links money, love, power, and gender in such a way as to make masculinity consist of a regulatory fiction inbred through repetition and liable to collapse once economic or emotional conditions change.

In Sudha Murthy?s Gently Falls the Bakula, the Bakula tree emerges as a central symbol that reflects the emotional and psychological journey of the protagonist, Shrimati, and her complex relationship with her husband, Shrikant. This paper explores the multi-layered symbolism of the Bakula tree, analyzing its role as a metaphor for love, sacrifice, and personal transformation. Initially, the tree symbolizes youthful love and innocence, embodying the early, idealistic stages of Shalini and Shrikant?s relationship. As the narrative progresses, the tree's decline mirrors the emotional distancing and sacrifice that characterize Shalini?s life. Ultimately, the renewal of the Bakula tree parallels Shalini's personal growth, suggesting the possibility of resilience and self-realization after emotional turmoil. Through an exploration of the tree's symbolic evolution, this paper examines how Sudha Murthy uses the Bakula tree to underscore themes of emotional decay, societal expectations, and renewal, offering a nuanced commentary on the dynamics of love and self-discovery. By focusing on the Bakula tree?s transformation, the paper highlights the novel's deeper reflections on the cycles of life, growth, and the potential for emotional and spiritual rebirth.

The Information Technology (IT) industry in India has been a cornerstone of economic growth and global integration. However, despite its progressive image, the sector exhibits significant gender disparity, particularly in retention and advancement to leadership roles. The National Capital Region (NCR), encompassing Delhi and its satellite cities of Gurugram, Noida, and Faridabad, is a major IT hub, making it a critical site for examining these dynamics. This paper evaluates the effectiveness of policy interventions?encompassing government initiatives, corporate policies, and civil society programs?aimed at enhancing women's participation in the NCR's IT sector. Employing a mixed-methods approach, including a review of secondary data, policy document analysis, and semi-structured interviews with women professionals, HR managers, and policymakers, the research assesses interventions across a lifecycle framework: Pipeline (Education & Recruitment), Retention (Workplace Environment), and Advancement (Leadership & Entrepreneurship). Findings indicate that while policies like STEM education pushes, maternity benefits amendments, and corporate Diversity & Inclusion (D&I) drives have improved entry-level recruitment, their effectiveness wanes in mid-career stages. Key barriers persist, including pervasive unconscious bias, inadequate support for post-maternity reintegration, lack of flexible work models rooted in trust, and weak implementation of anti-sexual harassment laws. The paper concludes that current interventions are often fragmented, compliance-oriented, and fail to address deep-seated socio-cultural norms that shape workplace culture. It recommends an integrated policy framework emphasizing measurable outcomes, shared accountability between government and industry, strengthening of the PoSH Act's implementation, promotion of women-led tech entrepreneurship in NCR, and the fostering of male allyship programs. This research contributes to the discourse on gender-inclusive economic growth by providing a region-specific, evidence-based analysis for designing more robust and impactful policies.

The age at which children enter formal schooling has traditionally been determined by developmental and psychological norms established during the mid-twentieth century. Between 1960 and 1980, the globally accepted minimum age for school entry was approximately six years, reflecting the cognitive, emotional, and environmental conditions of that period. However, rapid technological advancement, digital exposure, and changing patterns of early childhood stimulation in the twenty-first century have significantly altered children?s cognitive development and intellectual readiness. This paper presents a comparative psychological and IQ-based analysis of schooling readiness across three generations, spanning from 1960 to 2025, with a particular focus on the Indian educational context. The study adopts a conceptual and analytical approach, integrating classical developmental psychology theories with contemporary cognitive and educational engineering perspectives. It examines how early exposure to technology, interactive media, and enriched learning environments has accelerated cognitive functions such as language acquisition, visual-spatial reasoning, memory retention, and information processing in modern children. While these changes suggest that children aged three to five demonstrate increased intellectual readiness for structured learning, the paper also highlights a growing disparity between cognitive intelligence (IQ) and emotional intelligence (EQ), raising critical psychological concerns. To address this imbalance, the paper introduces the concept of educational engineering?an interdisciplinary framework that designs schooling systems aligned with both cognitive acceleration and emotional development. The study argues that early schooling can be psychologically beneficial only when curricula, pedagogy, and teacher preparedness are developmentally engineered rather than rigidly accelerated. By comparing generational learning environments, parental practices, and educational structures, the paper challenges the continued relevance of traditional school entry norms and calls for a re-evaluation of early education policies under India?s evolving educational landscape.

Edentulism remains a significant clinical problem affecting function, aesthetics, and quality of life, especially in elderly populations. Conventional complete dentures often suffer from poor retention and stability, particularly in the atrophic mandible, leading to compromised masticatory efficiency and patient satisfaction. Implant-supported overdentures (ISODs) have become a widely accepted treatment option that significantly enhances retention, stability, and overall prosthetic performance compared to conventional dentures. Successful overdenture therapy relies heavily on the attachment system used to connect the overdenture to dental implants, as different attachments influence clinical outcomes, prosthetic maintenance, patient satisfaction, and peri-implant tissue health.

Leadership in Indian schools is undergoing significant transformation due to NEP 2020 reforms, rising accountability expectations, and increasing classroom complexities. However, a persistent gap exists between teachers and administrators, often resulting in communication barriers, limited collaboration, and inconsistent instructional support. This study proposes the Teacher?Administrator Continuum (TAC) Model, a structural leadership framework designed to bridge these gaps by promoting transparency, pedagogical empowerment, shared decision-making, systematic communication, resource responsiveness, and balanced accountability. Using a qualitative design, data were collected from 20 participants (15 teachers and 5 administrators) across Indian schools through semi-structured interviews and one focus group discussion. Thematic analysis revealed six dominant themes validating the TAC framework: (1) Leadership Transparency, (2) Pedagogical Support, (3) Collaborative Decision-Making, (4) Communication Flow, (5) Resource Facilitation, and (6) Academic Accountability. Findings indicate that effective leadership is relational, collaborative, and instructionally guided rather than administrative and hierarchical. The TAC Model offers a practical and context-sensitive leadership framework aligned with global research and Indian school realities. The study?s implications highlight the need for leadership training, distributed responsibility, and NEP-aligned instructional reforms. It concludes that collaborative leadership is essential for sustainable school excellence in India.

Rapid transformations in twenty-first-century education demand teaching models that are holistic, structured, learner-centred, and operationally simple for teachers. Many traditional pedagogical frameworks address isolated dimensions such as learning theories, motivation, reading skills, or administrative planning, but they fail to integrate these elements into a unified system that functions effectively within real classroom conditions, particularly in the Indian context. The Omniframe Educational Model presents a comprehensive, classroom-tested solution by integrating conceptual clarity, structured pedagogy, leadership development, motivation, systematic reading practices, classroom governance, and reflective improvement into a single operational framework. Developed through long-term classroom observation, micro-level experimentation, and action research, the model provides educators with a practical and scalable blueprint to enhance student understanding, retention, discipline, and academic performance. Aligned closely with the National Education Policy (NEP) 2020, the Omniframe Educational Model supports multidisciplinary learning, strengthens teacher efficiency, and promotes a positive academic culture within schools. This paper presents the conceptual foundation, structural components, operational cycle, research methodology, findings, and classroom implications of the Omniframe Educational Model.

Student dropout at the secondary school level represents a critical educational and socioeconomic challenge, particularly acute in rural areas where access to quality education remains constrained by multiple intersecting factors. This analytical study examines the multifaceted determinants contributing to secondary school dropout rates with specific focus on rural contexts, where educational disadvantage is most pronounced. Through comprehensive review of empirical literature and theoretical frameworks, the research investigates how socioeconomic factors, parental education levels, family characteristics, school infrastructure, distance to educational institutions, teacher quality, peer influences, academic performance, and cultural attitudes collectively influence students' decisions to leave school prematurely. The findings reveal that rural dropout rates significantly exceed urban rates, with poverty emerging as the strongest predictor, followed by parental illiteracy, inadequate school infrastructure, long travel distances, and low perceived returns to education. Gender disparities persist, with girls in rural areas facing additional barriers including early marriage expectations and domestic responsibilities. The study identifies that dropout is not a sudden event but a gradual disengagement process beginning in primary years and culminating in secondary school exit. Family socioeconomic status, quality of teacher-student relationships, peer support networks, and parental involvement emerge as critical mediating factors. The research develops an integrated conceptual framework combining ecological systems theory, human capital theory, and social capital theory to explain dropout phenomena. Practical recommendations emphasize comprehensive interventions addressing poverty through conditional cash transfers, improving school infrastructure and teacher training, reducing opportunity costs, enhancing parental engagement, and creating supportive school climates that address rural students' unique challenges and promote educational retention and success.

Corporate governance has emerged as a critical determinant of organizational success and financial sustainability in contemporary business environments. This study examines the relationship between corporate governance practices and financial performance across diverse organizational contexts. Through comprehensive analysis of theoretical frameworks and empirical evidence, the research investigates how governance mechanisms including board composition, board size, board independence, ownership structure, and audit committee effectiveness influence financial outcomes measured through return on equity, return on assets, and market-based performance indicators. The findings reveal that effective corporate governance practices significantly enhance financial performance through improved monitoring, strategic decision-making, and resource allocation. Board independence emerges as a particularly influential governance mechanism, though its impact varies across different institutional and sectoral contexts. Ownership concentration demonstrates complex relationships with performance, yielding both positive monitoring effects and potential agency problems. The study synthesizes agency theory, stakeholder theory, stewardship theory, and resource dependence theory to explain governance-performance linkages. Practical implications emphasize the importance of balanced board composition, appropriate board size optimization, transparent disclosure practices, and alignment of managerial incentives with shareholder interests. The research contributes to corporate governance literature by integrating multiple theoretical perspectives and highlighting contextual factors that moderate governance effectiveness. Organizations seeking to enhance financial performance should prioritize implementation of comprehensive governance frameworks that address both monitoring and resource provision functions while remaining sensitive to industry-specific and institutional characteristics.

Green advertising has emerged as a critical marketing strategy in response to growing environmental consciousness among consumers worldwide. This study examines the influence of green advertising on brand trust and loyalty in contemporary markets. The research explores how environmental claims in advertising affect consumer perceptions, trust formation, and subsequent loyalty behaviors. Through comprehensive literature review and analysis, the study reveals that authentic green advertising significantly enhances brand trust, which serves as a crucial mediator between environmental marketing communications and brand loyalty. However, the relationship is moderated by factors including perceived greenwashing, consumer skepticism, and the credibility of environmental claims. The findings indicate that transparency, third-party certifications, and consistent environmental actions strengthen the positive impact of green advertising on trust and loyalty. Conversely, misleading or exaggerated environmental claims severely damage brand reputation and consumer relationships. The study contributes to understanding the complex dynamics between sustainability marketing, consumer psychology, and brand performance. Practical implications suggest that organizations must adopt genuine environmental commitments and communicate them authentically to build lasting consumer trust and loyalty in an increasingly eco-conscious marketplace.

Microfinance has emerged as an important developmental tool in rural India, enabling low-income households to access credit, build assets, and enhance livelihood opportunities. In Tamil Nadu, particularly in Tirupattur district, microfinance institutions (MFIs) and Self-Help Groups (SHGs) play a significant role in supporting vulnerable households. This study examines the influence of microfinance on rural household resilience through three dimensions?income improvement, debt management, and food security. Primary data collected from 180 SHG and MFI borrowers across five blocks of Tirupattur district forms the empirical basis of the study. The results reveal that microfinance participation has a positive association with income stabilization and food security, though issues such as multiple borrowings and rising indebtedness persist. The study concludes by highlighting the need for interest regulation, credit counselling, livelihood diversification, and enhanced government?MFI coordination to strengthen household resilience.

The escalating crisis of environmental pollution poses a significant and multifaceted challenge that transcends national borders, demanding universally applicable technological solutions. This research explores the critical role of Artificial Intelligence (AI) and Emerging Technologies, including the Internet of Things (IoT) and satellite remote sensing, in revolutionizing global pollution monitoring and driving sustainable environmental outcomes. Conventional monitoring approaches often suffer from poor data granularity and lack the predictive capacity necessary for proactive governance worldwide. To address this, we conduct a comparative analysis of AI deployment models for environmental applications across diverse global settings, contrasting the high-resource and regulated contexts of developed economies with the resource-constrained and rapidly industrializing environments of developing economies. Key findings indicate that the universal adoption challenge lies less in technological capability and more in overcoming issues of interoperability, data governance fragmentation, and regulatory standardization across international boundaries. The research synthesizes these findings to propose a conceptual model that facilitates the seamless flow of data from sensor to actionable policy. This integrated technological approach provides globally relevant guidelines for policymakers, institutions, and industry stakeholders. Ultimately, the successful deployment of these technologies is critical for transitioning from reactive mitigation to predictive environmental management, thereby achieving global sustainable development goals.

Community-Driven Development (CDD) has been a proven approach to rural development, poverty reduction, and the well-being of people in poor communities. The CDD approach has been applied in several regions worldwide. In principle, the CDD approach is used to address poverty dimensions in correspondence with the local context and societal behavior. In Laos, the central government has approved various community development approaches to eradicate poverty, with distinct processes across communities. Hence, it is necessary for a study to explore further the relationship between the level of participation and the physical environmental impacts after CDD project implementation. To obtain more accurate findings, samples from three Saemaul Undong Movement (SUM) villages in Toulakhom District, Vientiane Province, were randomly collected using questionnaires as survey instruments for both qualitative and quantitative data collection. The SUM in Laos has demonstrated substantial progress and practice in the agricultural sector, including changes in mindset, leadership approaches, and ownership among villagers during implementation and management. The key findings from the SUM pilot villages are positive improvements in income generation, whereas the drawbacks concern sustainable growth due to inadequate social cohesion and appropriate land-use planning.

Marmesin, a naturally derived furanocoumarin, has attracted considerable scientific interest due to its extensive pharmacological potential. Isolated from various medicinal plants including Aegle marmelos, Broussonetia kazinoki, and Feronia limonia, this bioactive molecule demonstrates a wide range of therapeutic effects encompassing anticancer, anti-inflammatory, antidiabetic, hepatoprotective, antimicrobial, and photobiological activities. Mechanistic studies indicate that marmesin exerts its pharmacological actions by modulating several key molecular targets such as PI3K/Akt and VEGF-A pathways, and by inhibiting enzymes like COX-2, 5-LOX, and aldose reductase. It also enhances insulin secretion by regulating ?-cell signaling and exhibits inhibitory activity against human heparan sulfatase-2 (HSULF-2), a known cancer-related enzyme. The broad therapeutic profile of marmesin highlights its potential as a natural lead molecule for drug discovery. This review consolidates existing literature on its structural characteristics, sources, biological activities, and mechanisms of action, emphasizing its emerging importance in modern pharmacological research.

The main purpose of the initiative is to set up a new, safe cloud-based system for medical data. The suggested structure changes cloud infrastructures to offer low costs, quick discovery, scalability, security, and the ability to adapt to changing workloads. It also makes me worry about the privacy and safety of patient info. A lot of study has been done on cloud data security, but there are still some problems that could leave data open to theft, changes, and unauthorized access. Using authentication and access control, this study shows a safe way to store healthcare data in cloud-based systems. So, only people who are allowed to can see the info, and it stays the same after being stored. This study suggests a three-step process that puts user ID verification, data privacy, and data accuracy at the top of the list. Putting these protections in place lets healthcare organizations use cloud storage while lowering risks like unauthorized access, data breaches, and abuse. Using the OPTIMI_RSA algorithm to confirm user identities is what this study on protecting cloud-based healthcare systems is all about. Only authorized users will be able to receive healthcare services, which protects the system and patient privacy.

Monetary policy serves as a critical instrument for macroeconomic stabilization in India, wielded primarily by the Reserve Bank of India (RBI) through interest rate adjustments, reserve requirements, and open market operations. This study examines the intricate relationship between monetary policy interventions and their dual impact on inflation control and economic growth promotion in the Indian context. The research explores how the RBI's policy rate decisions, liquidity management measures, and inflation targeting framework influence price stability and GDP growth trajectories. Through an analysis of monetary transmission mechanisms, the study investigates the channels through which policy changes affect real economic variables, including consumption, investment, and employment. The tension between maintaining price stability and fostering economic growth presents ongoing challenges for policymakers, particularly in a developing economy characterized by structural rigidities, supply-side constraints, and external vulnerabilities. The findings reveal that while contractionary monetary policy effectively curbs inflationary pressures, it may temporarily dampen economic growth, necessitating a delicate balancing act. Conversely, accommodative policies stimulate growth but risk inflation acceleration if maintained excessively. The study underscores the importance of credible monetary policy frameworks, forward guidance, and coordination with fiscal policy in achieving sustainable macroeconomic outcomes in India's dynamic economic landscape.

Heavy metal contamination in water bodies represents a critical environmental and public health challenge requiring cost-effective and sustainable remediation strategies. This research investigates the utilization of cocoa pod husk, an abundant agricultural waste material, as a low-cost bio-sorbent for removing heavy metals from aqueous solutions. The study focuses on optimizing adsorption parameters for lead(II), cadmium(II), and chromium(VI) removal using both raw and chemically modified cocoa pod husk. Response surface methodology was employed to optimize critical parameters including pH, bio-sorbent dosage, initial metal concentration, contact time, and temperature. Characterization techniques including FTIR, SEM, XRD, and point of zero charge determination revealed the presence of hydroxyl, carboxyl, and amino functional groups responsible for metal binding. Results demonstrate that acid-treated cocoa pod husk exhibits superior adsorption capacity compared to raw material, achieving maximum removal capacities of 89.7 mg/g for Pb(II), 62.4 mg/g for Cd(II), and 54.8 mg/g for Cr(VI) under optimal conditions. Adsorption kinetics followed pseudo-second-order model, while equilibrium data fitted well to Langmuir isotherm, indicating monolayer chemisorption mechanisms. Thermodynamic studies revealed that adsorption processes are spontaneous, endothermic, and favorable at elevated temperatures. Regeneration studies showed that the bio-sorbent maintains 78% efficiency after five consecutive cycles using dilute acid desorption. The extremely low production cost of $0.15-0.25 per kilogram compared to commercial adsorbents ($15-50 per kilogram) positions cocoa pod husk as an economically viable solution for heavy metal removal, particularly beneficial for developing regions where cocoa processing generates substantial waste volumes.

Deep learning-driven intelligent decision support systems (DL-IDSS) have emerged as transformative tools for addressing complex real-world problems across diverse domains including healthcare, finance, manufacturing, and urban planning. These systems leverage advanced neural network architectures to process vast amounts of structured and unstructured data, extracting meaningful patterns and generating actionable insights that enhance decision-making processes. Unlike traditional decision support systems, DL-IDSS demonstrates remarkable capabilities in handling non-linear relationships, adapting to dynamic environments, and learning from experience without explicit programming. The integration of convolutional neural networks, recurrent neural networks, and transformer architectures enables these systems to process multimodal data including images, text, time-series, and sensor information with unprecedented accuracy. However, challenges persist in areas of interpretability, computational requirements, data quality dependencies, and ethical considerations. This paper comprehensively examines the architecture, applications, challenges, and future directions of deep learning-driven intelligent decision support systems. Through systematic literature review and analysis of contemporary implementations, we identify critical success factors and propose a conceptual framework for designing effective DL-IDSS. The findings reveal that while these systems demonstrate superior performance in pattern recognition and prediction tasks, successful deployment requires careful consideration of domain-specific requirements, stakeholder engagement, and continuous model refinement to ensure sustainable value creation in organizational contexts.

The production of activated carbon from agricultural waste biomass represents a sustainable approach to waste management while generating high-value adsorbent materials for environmental and industrial applications. This research investigates the optimization of physical activation conditions for producing activated carbon from cocoa pod husk, an abundant agricultural residue from cocoa processing industries. The study employs response surface methodology using Box-Behnken design to optimize critical activation parameters including activation temperature (700-900?C), activation time (30-120 minutes), and CO? flow rate (50-200 mL/min). Characterization of the produced activated carbon through BET surface area analysis, scanning electron microscopy, Fourier transform infrared spectroscopy, and proximate analysis reveals the influence of activation conditions on structural and chemical properties. Results indicate that optimal activation conditions of 850?C temperature, 90 minutes activation time, and 150 mL/min CO? flow rate produce activated carbon with exceptional surface area (1247 m?/g), high porosity (0.68 cm?/g), and superior iodine number (1089 mg/g). The optimized activated carbon demonstrates excellent adsorption capacity for methylene blue (285 mg/g) and heavy metal ions, validating its effectiveness for water treatment applications. This research contributes to sustainable waste valorization strategies and provides practical guidelines for industrial-scale production of high-quality activated carbon from cocoa pod husk biomass.

The growing awareness of environmental degradation and social responsibility has transformed consumer behavior and marketing strategies worldwide. This study examines the relationship between sustainable marketing practices and consumer purchase intentions, exploring how eco-friendly branding, green product positioning, and corporate social responsibility initiatives influence buying decisions. Through a comprehensive literature review and conceptual framework development, this research identifies key factors that mediate the relationship between sustainability communication and consumer response. The study reveals that transparency, authenticity, and consistent green messaging significantly enhance consumer trust and purchase likelihood. Environmental concern, perceived consumer effectiveness, and social influence emerge as critical moderating variables. Additionally, the research highlights the importance of green brand image and perceived quality in converting environmental attitudes into actual purchase behavior. The findings suggest that companies must integrate sustainability deeply into their value propositions rather than treating it as a peripheral marketing tactic. This research contributes to understanding how businesses can leverage sustainable marketing practices to create competitive advantage while meeting evolving consumer expectations for environmental and social accountability.

The gig economy has fundamentally transformed traditional employment structures, creating new opportunities while simultaneously exposing workers to unprecedented financial vulnerabilities. This study examines the financial stability, savings behaviors, and risk exposure of gig economy workers across various platforms and sectors. Drawing from contemporary literature and empirical evidence, the research investigates how income volatility, lack of employment benefits, and irregular work patterns affect workers' ability to build financial resilience. The study reveals that gig workers face significant challenges including insufficient savings, limited access to credit, inadequate insurance coverage, and heightened vulnerability to economic shocks. Despite the flexibility advantages often cited, many gig workers struggle with financial planning due to unpredictable earnings and absence of employer-provided safety nets. The research employs a comprehensive framework analyzing income patterns, savings accumulation, and various dimensions of financial risk including health, retirement, and unemployment security. Findings indicate that while some highly skilled gig workers achieve financial stability, the majority experience precarious financial conditions requiring urgent policy interventions. The study concludes with recommendations for platform accountability, social protection mechanisms, and financial literacy programs tailored to gig workers' unique circumstances.

Hospital administrative practices play a critical role in determining the quality of healthcare services delivered to patients. Efficient administration influences resource utilization, staff performance, patient satisfaction, and overall service outcomes. This study examines the relationship between hospital administrative practices and service quality, focusing on key administrative dimensions such as leadership effectiveness, human resource management, financial planning, information systems, and patient-centered policies. Using an empirical approach, the study assesses how administrative efficiency contributes to improved responsiveness, reliability, assurance, empathy, and tangibility of hospital services. Data collected from healthcare professionals and patients highlight that hospitals with structured administrative systems demonstrate higher service quality and patient satisfaction levels. The findings reveal that administrative transparency, staff training, and technology-driven management significantly enhance operational efficiency and patient experiences. Conversely, poor coordination, inadequate staffing, and weak leadership negatively affect service delivery. The study contributes to healthcare management literature by establishing a clear linkage between administrative practices and service quality outcomes. It offers practical insights for hospital administrators and policymakers to strengthen governance frameworks and improve healthcare delivery standards. The study concludes that strengthening hospital administrative practices is essential for achieving sustainable service quality improvements in an increasingly complex healthcare environment.

The vice on teenage bullyism has grown to higher proportions of late in the country. There is both physical and cyber bullying aspects to it. This has been reported in different Machakos high schools. The problem has even escalated to teen gangs within Machakos area leaving the police with no clues how to curb it. The research will be based on the menace.

In India, political influence, economic pressure, cultural hierarchy, and quickly developing digital technology all impact the complicated framework in which journalism operates. Together, these factors result in a variety of censoring tactics, some overt and authorized by law, others covert, internalized, and ingrained in regular journalistic operations. The manifestation of censorship in modern Indian journalism is examined in this essay, along with the ways in which journalists negotiate, oppose, and reinterpret these limitations. The study contends that journalism in India is not just a profession but a dynamic space of conflict where meaning, identity, and power constantly intersect by fusing Humanities perspectives on discourse, identity, and representation with Social Sciences approaches to political economy, institutional power, and sociology of professions. Indian journalists continue to use acts of bravery, creative storytelling, group unity, and alternative media techniques to make their voices heard despite systemic obstacles. In the end, Indian journalism is characterized by a persistent conflict between vulnerability and agency, quiet and expression, and suppression and resistance.

This paper explores the intricate, bidirectional relationship between psychological stress and the development and exacerbation of peptic ulcers (specifically Gastric and Duodenal ulcers) in the human body. While the primary most peptic ulcers are linked to Helicobacter pylori infection and chronic Non-Steroidal Anti-Inflammatory Drug (NSAID) use, mounting clinical and epidemiological evidence suggests that chronic mental and emotional stress acts as a significant cofactor, modulating the body's protective mechanisms. The paper first reviews the physiological mechanisms by which stress hormones (e.g., cortisol, catecholamines) impair gastric mucosal integrity. It then presents case study examples of different ulcer types and their common psychological profiles. Finally, it hypothesizes a correlation between measured stress levels (via validated psychological scales) and ulcer incidence/severity, illustrating this with a conceptual Stress vs. Ulcer Incidence graph. The conclusion emphasizes the need for holistic treatment integrating both pharmacological and psychological interventions.

Operating systems serve as an interface between users and hardware, providing essential services such as process management, disk management, and memory management. This paper explores the functionality of memory management within operating systems, emphasizing the tracking and deallocation of memory allocated to processes. Understanding memory management is crucial for optimizing system performance and resource utilization.

Textbooks are foundational to the educational experience, serving as primary resources for students and teachers alike. In India, the National Curriculum Framework for School Education 2023 (NCF-SE 2023) outlines key principles and processes for the design and development of effective textbooks. This research paper provides an overview of these principles and processes, highlighting their significance in improving educational quality and relevance. The NCF-SE 2023 emphasizes a shift from textbook-centric approaches to using textbooks as tools to achieve specific learning outcomes. The Curriculum Principle mandates that textbooks align with the competencies for the stage and learning outcomes for the grade, ensuring comprehensive coverage and age-appropriate content. The Values Principle advocates for reflecting desirable values and dispositions in textbook content, fostering responsible and empathetic citizens. The Discipline Principle ensures subject-specific accuracy and coherence, maintaining alignment with core disciplinary principles. The Pedagogy Principle promotes active learning and critical thinking through appropriate teaching methods, integrating multimedia resources and interactive activities to engage students effectively. The Context Principle emphasizes the importance of incorporating local and regional contexts, making learning more relatable and meaningful for diverse student populations. The textbook development process begins with creating a syllabus document that guides content creation based on curricular goals, competencies, and learning outcomes. Peer and panel reviews refine content, while a pilot run in selected schools gathers feedback from teachers, students, and parents to further enhance textbooks. In brief, the NCF-SE 2023 provides a comprehensive framework for designing textbooks that support the achievement of learning standards. This research paper explores key principles and processes, demonstrating their role in creating inclusive, engaging, and impactful educational experiences across India.

Sodium Lauryl Sulfate (SLS), a potent synthetic surfactant derived from coconut and palm oil, plays a significant role in various consumer products, including soaps, shampoos, toothpaste, and household detergents. Its effectiveness in generating a rich lather and superior cleaning ability has made it a staple in the personal care and cleaning industries. However, the use of SLS presents notable challenges due to its potential to irritate the skin, particularly at elevated concentrations, prompting many manufacturers to opt for the milder Sodium Laureth Sulfate (SLES). SLS is also recognized as an approved food additive, evidencing its diverse applications beyond cosmetics. This abstract explores the chemical formulation, physiochemical properties, advantages and disadvantages, and broader applications of SLS. Additionally, it addresses its toxicological profile, pertinent side effects, and relevant case studies that highlight its impact on skin health. This comprehensive analysis aims to inform and guide formulators and consumers toward safer and more effective alternatives in personal care products.

The Indian Knowledge System (IKS) encompasses a vast repository of indigenous wisdom, including philosophy, science, mathematics, medicine, and arts, developed over millennia. Despite its richness, mainstream education in India has largely overlooked IKS in favor of Western pedagogical models. This paper explores the significance of integrating IKS into contemporary education, focusing on its potential to foster holistic learning, cultural preservation, and sustainable development. The study examines key domains of IKS?such as Vedas, Upanishads, Ayurveda, Yoga, traditional mathematics, and tribal knowledge systems?and proposes strategies for their inclusion in formal curricula. Challenges such as institutional resistance, lack of documentation, and modernization biases are also discussed. The findings suggest that a balanced integration of IKS with modern education can enhance critical thinking, ethical values, and national identity among learners.

Teacher education systems across the globe are experiencing increasing demands to prepare educators who are both technologically adept and pedagogically sound. However, these systems are often constrained by outdated administrative policies that hinder innovation and responsiveness. This paper critically explores how reforming administrative policies at the institutional, regional, and national levels can contribute to the development of effective teacher education programs. Drawing on international practices and recent empirical findings, it identifies key policy interventions and structural reforms that can empower teacher preparation programs to meet the challenges of 21st-century classrooms. The discussion emphasises decentralisation, stakeholder inclusion, and evidence-informed practices. Recommendations are provided to align administrative strategies with evolving educational needs and ensure long-term sustainability in educational governance.

The paper focuses on the cultural journey of the leg-work dance in Nigeria from the days of the Highlife kicks to the present Amapiano footwork and the cultural and entrepreneurial significance of the leg-work to youth. A qualitative-exploratory research design was employed in the study and data were gathered using semi structured interviews with dancers, music producers, and young entrepreneurs, other than participant observation and archival data. The findings from the interviews using thematic analysis brought to the fore that the evolution of the dance accompanied the changes in the music of the time and the growing urban culture among the youth, the influences from other parts of the world and the digital platforms that host the dances. The study demonstrates the leg-work dance as a valuable cultural and entrepreneurial tool and the youth as the performers and promoters of the dance from Nigeria. The leg-work and the footwork Amapiano can allow young people to participate in the growing global creative sector and sustainable economic development.

The rapid integration of artificial intelligence into financial market is transforming traditional approaches to investment decision making. This study explores the impact of AI on the investment behaviour of academics in the Delhi ncr region. Academics, being relatively well informed and technologically adaptive, represent a unique investor group whose choices are shaped by both financial knowledge and professional exposure to analytical tools. The finding shows that AI applications such as robo advisors, algorithmic screeners and redictive analytics are increasingly used by academics to identify investment opportunities, assess risk and monitor portfolio. While AI has enhanced efficiency, reduced information overload and improved data driven decision making, academics remain cautious about fully relying on automated system, largely due to trust issues and the need for transparency in model output. The study further highlights that personal financial goals, risk tolerance and regulatory safeguard continue to moderate the extent of AI adoption.