The study investigates the combined influence of pedagogical adaptability, student engagement, quality management strategies, teacher support, technological integration, assessment and feedback, and parental involvement on students’ learning outcomes at the higher-secondary level. Using a quantitative, cross-sectional design and Structural Equation Modelling (SEM) with 290 respondents, the analysis revealed that student engagement, technological integration, quality management, and parental involvement significantly enhance learning outcomes, while teacher support, pedagogical adaptability, and assessment and feedback were not statistically significant. The model demonstrated good fit indices (χ²/df = 1.294, GFI = 0.900). Findings highlight the importance of engagement, technology, and parental collaboration in improving educational effectiveness..

This study investigates how adaptive teaching, technological integration, curriculum strategies, assessment and innovation, professional development, student engagement, and educational change influence teachers’ professional competencies in secondary schools. Using a quantitative survey design and structural equation modelling (SEM) on data from 260 teachers, the research identifies technological integration, curriculum strategies, student engagement, and educational change as significant predictors of professional competence. Findings highlight gaps in assessment practices and interdisciplinary approaches but underscore the need for modernized, engagement-driven pedagogy. Results provide actionable insights for policymakers and educators to enhance teacher effectiveness through targeted professional growth and systemic educational reforms..

This study examines how psychological, behavioural, and environmental factors shape students’ ability to manage time effectively in higher education. Using a quantitative design and Structural Equation Modelling (SEM) on responses from 255 students in Jharkhand and Bihar, the study tests the influence of self-motivation, academic stress, goal orientation, technological support, parental participation, student engagement, and personal skills on time management and study techniques. Results indicate that personal skills, parental participation, and goal orientation are strong positive predictors of effective planning, scheduling, and task completion. The findings provide an evidence base for interventions such as skills training, parental academic involvement, and goal-setting support to improve self-regulated learning..

This study presents the design, modeling, and experimental validation of novel hybrid cooling technologies for high-power electronic systems, integrating nanofluid-based forced convection with phase-change material (PCM) latent heat absorption. The research aims to overcome the limitations of conventional air and liquid cooling systems by improving heat dissipation, energy efficiency, and thermal stability under variable power loads. Experimental investigations, supported by MATLAB R2017b, ANSYS Fluent, and COMSOL Multiphysics simulations, were conducted for heat loads ranging from 50 W to 300 W. Results indicate that the hybrid nanofluid–PCM system achieved a minimum thermal resistance of 0.28 K/W, an average heat transfer coefficient of 550 W/m²·K, and a Coefficient of Performance (COP) between 5.8 and 8.8, significantly outperforming air and liquid cooling alternatives..

India is a country that possesses enormous resources, which has attracted a vast number of countries to put those riches to use and enrich their economies to the fullest extent possible. Customers' tastes and preferences are also subject to rapid change in today's environment, which is characterized by the rapid advancement of technology. For the sake of India's overall growth and for the purpose of achieving economic autonomy among its population, it is essential that rural areas experience rapid industrialization. The role of the small-scale industries is to assist in the expansion of the government's infrastructure and to reduce problems such as pollution, poverty, and slums..

Mathematical disciplines that study spaces where distances between points may be measured include metric space theory and metric geometry. These theories lay out a rigorous framework for studying the shapes, sizes, and relationships of things in real and virtual worlds. Geometric and analytical concepts may be applied to large regions by starting with the basic concept of a metric, which is a function that defines the distance between points. .

The exponential growth of online social networks (OSNs) has dramatically altered the ways in which people communicate, share information, and engage with one another. Concerns about data privacy, unauthorized access, and user monitoring have grown in tandem with the use of this link. This research introduces a new paradigm for community key management in online social networks (OSNs) that prioritizes privacy..

This study presents a sentiment analysis model for classifying user-generated drug reviews into positive, neutral, and negative categories using transformer-based embeddings and hybrid classifiers. A dataset of 5,170 drug reviews was collected from WebMD using the Beautiful Soup Python library and manually labeled for accuracy. After preprocessing and encoding, embeddings were generated using BERT, SciBERT, BioBERT, and SBERT models to capture contextual meaning. These embeddings were then used as input features for machine learning classifiers such as Decision Tree, Support Vector Machine (SVC), Random Forest, and Recurrent Neural Network (RNN). Experiments were conducted using Python (v3.9.11) and the SMOTE technique to address class imbalance. .

A fresh look at the geometric underpinnings of Einstein's Special and General Relativity has been driven by the ongoing conceptual difficulties with these theories, including simultaneity, curvature of spacetime, time dilation, and length contraction. For the purpose of addressing the Minkowskian model's inherent inconsistencies and interpretational challenges, this research suggests a Euclidean framework as an alternate formulation. This work shows that one need not invoke non-Euclidean spacetime curvature in order for relativistic effects to arise naturally from geometric relations by reinstating absolute Euclidean space and genuine temporal progression. .

This study examines IPO underpricing and long-term performance in the Indian capital market by analysing investor perceptions and key determinants influencing IPO pricing behaviour. Using primary data collected from 450 respondents and supported by structural equation modelling, the study finds that IPO underpricing is a widely perceived and systematic feature of the Indian market. Listing-day gains are viewed as clear evidence of underpricing and are found to benefit short-term investors more than long-term investors. Firm size, firm age, issue size, subscription rate, and market conditions significantly influence IPO pricing outcomes, while market volatility and underwriter reputation exert limited direct impact. The findings suggest that IPO underpricing in India is driven largely by investor psychology, demand management, and favourable market sentiment rather than pure pricing inefficiency. The study provides insights for investors, issuers, and regulators seeking to enhance IPO pricing efficiency and market transparency..

The term "decision support systems" (DSS) describes a type of computer-based system that gives information and resources to decision-makers. A more organised and evidence-based approach to decision-making is necessary to improve the efficacy of instruction in light of the growing complexity of educational administration. The Simple Additive Weighting (SAW) approach, a well-known Multi-Attribute Decision-Making (MADM) tool, is used to analyse the educational applications of Decision Support Systems (DSS). Ten strategic educational interventions are tested in this study using five main performance indicators for institutions. .

The purpose of the current research was to investigate the synergetic effect of adaptive training ecosystems and motivation-driven interventions while considering the moderating effect of behavioural analytics on organizational climate. According to the principles of DCT, a quantitative research approach was adopted for the current research by using a survey method with 312 participants from knowledge-intensive organizations. The proposed research model was tested using the SEM approach with a maximum likelihood method. .

This study created a neuropsychometric talent intelligence framework that combines psychological assessment and artificial intelligence (AI) into a single model for dynamic competency alignment and predictive retention analytics. The quantitative model-driven methodology utilized integrated datasets including neuropsychometric attributes (cognitive ability, emotional intelligence, behavioural traits) and HR metrics (performance, engagement, retention). Using machine learning techniques such as Random Forest, Support Vector Machines (SVM), and Neural Networks, the study analyzed the relationships between the two data sets in order to predict future outcomes. .

This paper investigates the complex negotiations of identity and resistance in Indian women autobiographers of the nationalist period through the intersecting discourses of caste, Christianity, and nationalism in Maharashtra. Focusing on low-caste and Christian-convert narratives by Savitribai Phule, Muktabai, Lakshmibai Tilak, Pandita Ramabai, and Krupabai Sattianadhan, it analyses how missionary evangelism provided new discursive tools while simultaneously imposing Victorian ideals of domesticity and Christian virtue. Postcolonial and comparative discourse analysis reveals strategies of co-option, resistance, and ambivalent selfhood that allowed these women to challenge Brahminical hegemony without fully abandoning indigenous cultural frameworks. The study highlights the “leavening” impact of Christianity on low-caste women’s consciousness, showing how missionary education, medical missions, and egalitarian rhetoric served as instruments for critiquing caste while creating hybrid identities at the crossroads of colonial modernity and indigenous reform. By examining the polyphonic voices and palimpsestic layers in these life writings, the paper demonstrates that women’s autobiographical self-narration was never a simple acceptance or rejection of missionary influence but a sophisticated site of ongoing negotiation. The findings contribute to postcolonial gender studies by illuminating how caste, gender, and religious hybridity shaped female subjectivity in colonial India and continue to inform contemporary understandings of identity formation under intersecting oppressions..

This study explores the interplay among destination image, attractions, and lifestyle factors in determining tourist satisfaction and loyalty intentions in Uttar Pradesh tourism. Utilizing data from 151 international and domestic visitors surveyed via Google Forms, the research applies exploratory factor analysis and structural equation modeling alongside demographic profiling and chi-square tests. Exploratory factor analysis extracted five constructs explaining 68.398 percent of variance, with destination image items scoring means of 3.72 to 4.08 and attractions and lifestyle measures also registering above-neutral ratings. SEM results identify attractions as the strongest predictor of satisfaction, followed by lifestyle and destination image. Logistic regression further links overall satisfaction, income, occupation, and cuisine appreciation to revisit intentions. Implications include strategic rebranding opportunities centered on cultural and culinary uniqueness to enhance loyalty and economic contributions..

This study explores the multifaceted role of the hospitality industry in driving tourism development in Uttar Pradesh, India. Utilizing secondary data from government reports, WTTC statistics, and primary insights from industry stakeholders, alongside a comprehensive review of policy frameworks and economic indicators, the research highlights hospitality's contributions to GDP, employment, foreign exchange earnings, and infrastructure growth. Key findings indicate that hospitality accounts for significant direct and indirect economic multipliers, supporting millions of jobs and enhancing destination competitiveness across major circuits like Agra-Braj, Buddhist, and Awadh-Ayodhya. Government measures, including star categorization, e-visa facilities, and dedicated tourism funds, have accelerated growth, yet challenges in service consistency, rural outreach, and post-pandemic recovery persist. Strategic rebranding as a cultural and culinary hub, coupled with public-private partnerships and sustainable practices, offers pathways for inclusive development. The analysis underscores hospitality's pivotal position in realizing Uttar Pradesh's tourism potential, contributing to sustainable economic growth and positioning the state as a global destination. Implications include targeted policy interventions for infrastructure, training, and marketing to maximize long-term benefits..