Volume 14 | Issue 7 |

 Abstract

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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 Keywords

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

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 Abstract

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

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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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 Keywords

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

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 Abstract

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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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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 Keywords

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

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Mobile banking has emerged as one of the most significant innovations in the modern banking sector, transforming the way customers access and utilize banking services. The increasing penetration of smartphones, internet connectivity, and digital payment systems has encouraged. customers to perform financial transactions through mobile applications without visiting physical bank branches. Mobile banking offers various facilities such as fund transfers, balance inquiries, bill payments, account monitoring, and other banking services, thereby enhancing convenience and accessibility for users. The present study examines the impact of mobile banking on customer satisfaction in public and private sector banks. The primary objective of the study is to analyse customer perceptions regarding mobile banking services and to compare satisfaction levels among users of public and private sector banking applications. The study also investigates the influence of factors such as ease of use, security, transaction speed, service quality, accessibility, reliability, and customer trust on overall satisfaction. The research is based on both primary and secondary data. Primary data were collected through a structured questionnaire administered to customers who regularly use mobile banking services, while secondary data were obtained from books, journals, research articles, banking reports, and online sources. The collected data were analysed using descriptive statistical techniques. The findings reveal that mobile banking has positively influenced customer satisfaction by making banking services faster, more convenient, and easily accessible. Customers of private sector banks generally reported higher satisfaction levels due to better application performance, faster transaction processing, and user-friendly interfaces. In contrast, customers of public sector banks expressed greater trust and confidence in the security and reliability of their banking institutions. Despite the overall positive perception, certain challenges such as technical issues, security concerns, and occasional service interruptions continue to affect customer experiences. The study concludes that mobile banking significantly contributes to customer satisfaction in both public and private sector banks. Banks should focus on improving digital infrastructure, strengthening cybersecurity measures, enhancing customer support, and increasing awareness regarding digital banking services. Continuous innovation and service improvement will be essential for sustaining customer satisfaction and ensuring the long term success of mobile banking platforms.

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Keywords: Mobile Banking, Customer Satisfaction, Public Sector Banks, Private Sector Banks, Digital Banking, Service Quality, Customer Trust, Banking Technology.

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Background Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases and remains one of the leading causes of cancer-related mortality worldwide. Recent advances in immune checkpoint inhibitor therapy targeting PD-1/PD-L1 pathways have improved survival outcomes; however, only a subset of patients demonstrates durable clinical responses. Emerging evidence indicates that lung microbiome dysbiosis plays an important role in tumor progression, immune regulation, inflammatory pathways, and response to immunotherapy. Aim To assess the role of lung microbiome dysbiosis in NSCLC progression and its association with immunotherapy response among patients receiving immune checkpoint inhibitor therapy. Methods A prospective observational study was conducted among 100 diagnosed NSCLC patients receiving immunotherapy. Bronchoalveolar lavage (BAL) samples were collected for microbial profiling using 16S rRNA sequencing. Clinical characteristics, tumor stage, PD-L1 expression, inflammatory biomarkers, and immunotherapy response were assessed. Treatment response was evaluated according to RECIST 1.1 criteria. Data were analyzed using SPSS version 26.0. Results Among 100 NSCLC patients, lung microbiome dysbiosis was identified in 62% of cases. Advanced tumor stage (III-IV) was significantly associated with reduced microbial diversity (p<0.01). Patients with balanced lung microbiota showed a higher immunotherapy response rate (63.2%) compared with dysbiosis patients (32.3%). Increased abundance of Proteobacteria and reduced Firmicutes were associated with poor progression-free survival and resistance to immune checkpoint inhibitors. Conclusion Lung microbiome dysbiosis significantly influences NSCLC progression and immunotherapy response. Microbial profiling may serve as a potential biomarker for predicting treatment outcomes and developing microbiome-targeted therapeutic approaches.

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 Keywords

Keywords: Non-small cell lung cancer, Lung microbiome, Dysbiosis, Immunotherapy, Immune checkpoint inhibitors, PD-1, PD-L1

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Creative Commons Attribution 4.0 and The Open Definition