Volume 14 | Issue 7 |

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Keywords: Protein-energy malnutrition, Essential minerals, Serum calcium, Zinc deficiency, Iron deficiency, Growth stunting, Transferrin, Hemoglobin, Metabolic biomarkers, Case-control study.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Maiya Samman Yojna, Financial Empowerment, Women, Direct Benefit Transfer, Ranchi, Jharkhand

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Creative Commons Attribution 4.0 and The Open Definition

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Football is a high-pressure team sport characterised by uncertainty, physical contact, public scrutiny, and frequent setbacks such as defeat, injury, and exclusion from selection. Psychological resilience, broadly defined as the capacity to adapt positively in the face of adversity, has been increasingly recognised as a core determinant of sustained competitive success in football. This paper presents a systematic review of twenty recent studies examining the relationship between psychological resilience and competitive outcomes among football players across age groups, performance levels, and cultural settings. The reviewed literature converges on several themes: resilience is built through the interaction of personal qualities (mental toughness, hardiness, grit, self-efficacy) and contextual resources (social support, coaching climate, team culture); resilience training and psychological skills interventions produce measurable gains in mental toughness, decision-making, and on-field performance; and resilience operates as a protective factor during injury recovery and high-stakes competitive moments such as penalty shootouts. Gaps remain in longitudinal and causal designs, in research on female and youth players, and in culturally diverse samples. The review concludes with practical implications for coaches, sport psychologists, and talent-development pathways.

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Creative Commons Attribution 4.0 and The Open Definition

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psychological resilience, mental toughness, football, soccer, competitive performance, hardiness, systematic review

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Stock price prediction; LSTM; Random Forest; attention mechanism; sentiment analysis; ensemble learning; hybrid machine learning; NSE NIFTY 50.

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Creative Commons Attribution 4.0 and The Open Definition

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Fraud remains one of the most significant challenges facing the banking industry worldwide. It undermines financial stability, reduces customer confidence, and results in substantial financial losses. As banking operations become increasingly digital and complex, fraud schemes have evolved, making effective internal control measures more important than ever. Internal controls are the policies, procedures, and systems established by banks to safeguard assets, ensure the accuracy of financial records, promote operational efficiency, and ensure compliance with laws and regulations. Strong internal control measures play a critical role in detecting fraudulent activities at an early stage and preventing fraud before it occurs.

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"The Impact of Internal Control Measures on the Detection and Prevention of Fraud in Banks"

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Biomedical waste management; Simulation-based training; Housekeeping staff; Knowledge; Practice; Compliance; Infection prevention; Hospital waste management; Quasi-experimental study.

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Creative Commons Attribution 4.0 and The Open Definition

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Child malnutrition remains a critical public health challenge in India, undermining human capital formation and long-term economic growth. Despite improvements in nutrition indicators over recent decades, acute malnutrition manifested as wasting continues to affect nearly one-fifth of children under five. This paper examines community-based management of acute malnutrition (CMAM) as a scalable, equity-oriented approach for addressing this burden. Drawing on state-level evidence compiled by NITI Aayog in collaboration with UNICEF, the study analyses institutional designs, service delivery mechanisms, and outcomes across Indian states. Using secondary empirical data from NFHS-5 and programme implementation records, the paper synthesizes best practices across thematic domains community mobilization, screening, medical and nutritional management, monitoring systems, and multisectoral convergence. The findings indicate that CMAM can successfully manage 80-90% of uncomplicated severe acute malnutrition cases at the community level, improve service coverage, and reduce health-system burden when embedded within existing ICDS and health infrastructure. The study concludes with policy recommendations for scaling, sustainability, and integration with preventive nutrition strategies under India's nutrition governance framework.

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Creative Commons Attribution 4.0 and The Open Definition

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Acute malnutrition, CMAM, child nutrition, community health, India, Poshan 2.0

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Creative Commons Attribution 4.0 and The Open Definition

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The water samples from Jangamhatti Dam and Tilari Dam in Chandgad Tehsil, Kolhapur (Maharashtra), were collected during the pre-monsoon (April 2025) and post-monsoon (November 2025) seasons. Physicochemical parameters such as pH, temperature, salinity, chlorides, total hardness, turbidity, electrical conductivity, calcium, magnesium, dissolved oxygen (DO), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) were analyzed and compared with the standard values recommended by the World Health Organization (WHO). The results indicated noticeable variations in these parameters between the two dams.

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Creative Commons Attribution 4.0 and The Open Definition

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Jangamhatti Dam, Tilari Dam, Physicochemical analysis

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Creative Commons Attribution 4.0 and The Open Definition

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There is an influx of digitally generated content and user opinions over several decades and has brought major changes to the information environment. Online platforms such as movie review sites, e-commerce portals, and social networking services produce a large amount of user-generated content every year. This includes customer feedback, reviews of products and services, and general social discussions. Together, this information forms an important source of sentiment data that supports business decisions, political communication, and social research. This paper proposes a model SentiBERT with sentiment intelligence framework that uses three transformer architectures--BERT, RoBERTa, and DistilBERT--against classical TF-IDF-based baselines on the IMDB Large Movie Review Dataset, while evaluating across Amazon product and Yelp restaurant review datasets considering cross-domain transfer protocol. SentiBERT generates three remarkable outputs which distinctively elevates this model from rest. First, we design a multi-method Explainable AI (XAI) pipeline that unifies Local Interpretable Model-agnostic Explanations (LIME), BertViz attention-weight visualization, and GPT-2-grounded for natural language explanations-- In this approach, the generated explanation is based on measurable evidence obtained from LIME rather than relying only on unrestricted language model outputs, which helps reduce the chances of imagined results. Second, we implement a hybrid aspect-based sentiment analysis (ABSA) module that integrates spaCy noun-phrase extraction with BERT context-window scoring across six film-specific aspect categories. Third, vocabulary overlap is examined to understand transfer difficulty. For this purpose, Jaccard similarity is used as a reference measure. Additionally, words associated with model failure are identified across target domains using LIME. The experimental results are validated against reproducible JSON metric files which demonstrates RoBERTa achieves the highest test-set accuracy of 91.70% and AUC-ROC of 0.972, representing a 32% reduction in error rate relative to the best classical baseline (Linear SVM: 87.62%). Interestingly, the accuracy drop for zero-shot cross-domain transfer is only 0.60% and 0.40% on Amazon and Yelp, respectively, and contradicts the notion of domain fragility for transformer-based sentiment classifiers. Under text-casing perturbation, BERT achieves 90.0% accuracy, whereas it drops to 70.0% when the test set is heavily corrupted with 20% of typing errors (typo injection). The biggest challenge BERT faces is the identification of subword tokenisation boundaries. The results shed light on the advantages and disadvantages of applying sentiment analysis based on transformers to real-world applications.

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Creative Commons Attribution 4.0 and The Open Definition

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Sentimental Analysis, DistilBERT, BERT, RoBERTa, LIME, GPT-2, Aspect-Based Sentiment Analysis (ABSA), Cross-Domain Transfer Learning, Explainable AI, Natural Language Processing

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Creative Commons Attribution 4.0 and The Open Definition

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This paper argues that shadow economies are not peripheral anomalies or symptoms of underdevelopment but adaptive institutions that emerge when formal economic systems externalise health risk onto workers without adequate protection. Drawing on nineteenth-century literary evidence from Dickens, Hugo, and Dostoevsky -- read through Elaine Freedgood's method of strong metonymic reading -- alongside Hernando de Soto's theory of informal capital, Rosenblat and Stark's empirical study of Uber drivers, the Fairwork 2021 global report on platform labour during COVID-19, and Mia Moore's legal critique of algorithmic governance, the paper identifies a four-stage recurring institutional mechanism: health risk privatisation, income volatility amplification, vulnerability accumulation, and adaptive informality emergence. It demonstrates that this mechanism operates similarly across industrial capitalism and contemporary platform labour, despite significant differences in technology and scale. The paper concludes by proposing three institutional design interventions -- (i) health-indexed algorithmic constraints, (ii) portable risk contributions, and (iii) mandatory health transparency audits -- that would interrupt the cycle by making health economically visible within platform governance. The contribution is both theoretical, in reframing shadow economies as predictable institutional responses to risk externalisation, and practical, in identifying actionable policy directions for platform labour reform.

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Creative Commons Attribution 4.0 and The Open Definition

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Shadow Economy, Risk Externalisation, Algorithmic Governance, Platform Labour, Health Invisibility, Institutional Economics, Behavioural Economics, Gig Economy, Informal Institutions.

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Creative Commons Attribution 4.0 and The Open Definition