Volume 14 | Issue 6 |

 Abstract

Rubber (Hevea brasiliensis) is a commercially important crop, yet foliar diseases such as Anthracnose, Corynespora Leaf Fall, and Phytophthora-induced Dry Leaf Syndrome significantly reduce plantation yield and tree longevity. Manual diagnosis by agricultural officers is time-consuming, subjective, and often inaccessible to smallholder farmers in remote regions. This paper presents an end-to-end AI-powered mobile application for real-time detection and classification of rubber leaf diseases using deep learning. The system employs a MobileNetV2 convolutional neural network trained via a two-stage transfer learning strategy: an initial warmup phase with a frozen ImageNet backbone followed by fine-tuning of the top 30 layers using cosine-decay learning rate scheduling. Data augmentation, L2 regularization, dropout, and class-weight balancing were applied to improve generalization on the Mendeley Rubber Leaf Dataset containing 1,741 images across four classes. The model achieved a validation accuracy of 99.7% with perfect precision and recall across all classes. The trained model was deployed through a dual-inference architecture: a Python Flask REST API for cloud-based predictions and a quantized TensorFlow Lite model embedded within a cross-platform Flutter mobile application for offline inference, ensuring uninterrupted functionality in rural areas with limited connectivity. The application further incorporates a 90% confidence-threshold gating mechanism to reject ambiguous inputs, multilingual support, an analytics dashboard for disease trend monitoring, and PDF report generation for agricultural record-keeping. The proposed system demonstrates that lightweight deep learning models, combined with intelligent mobile deployment strategies, can provide scalable, accurate, and accessible diagnostic tools for precision agriculture. Index Terms--Deep Learning, Transfer Learning, MobileNetV2, Rubber Leaf Disease, TensorFlow Lite, Flutter, Precision Agriculture, CNN, Image Classification

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 Keywords

, Convolutional Neural Network (CNN), Precision Agriculture, Plant Disease Classification, Artificial Intelligence in Agriculture, Image Classification, Mobile Application, Flask API, Offline Inference, Smart Farming, Agricultural Technology, Leaf Disease Prediction, Machine Learning, Computer Vision, Hevea brasiliensis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Agricultural development and rural development are closely interconnected processes that play a crucial role in improving the socio-economic conditions of rural communities. Agriculture serves as the backbone of rural economies by generating employment, enhancing incomes, and ensuring food security. Sustainable agricultural growth contributes significantly to poverty reduction, economic diversification, and overall rural transformation. In India, various government initiatives and development programmes support rural agricultural development through financial assistance, technological innovation, infrastructure creation, crop insurance, and market reforms. Effective rural development also requires improvements in education, healthcare, transportation, irrigation, and communication facilities to create an enabling environment for agricultural progress. The study highlights the complementary relationship between agricultural advancement and rural development, emphasizing the importance of integrated policies, institutional support, farmer empowerment, and sustainable practices. It concludes that coordinated efforts by governments, local institutions, and stakeholders are essential for achieving inclusive growth, strengthening rural livelihoods, and ensuring long-term agricultural sustainability and rural prosperity.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Agricultural Development, Rural Development, Rural Livelihoods, Sustainable Agriculture, Food Security, Government Schemes, Inclusive Growth, India.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Toni Morrisons's books reveal of complex web of themes, characters, and storylines when analysed through the lens of literary analysis and feminism. Toni Morrison, Maya Angelou, Paul Marshall, Alice Walker, and Gloria Naylor were among the American writers who saw writing as a way to break free, a strategy for rebellion, and a creative way to express oneself. She follows in Edward Said's footsteps by exploring how the dominant group manipulates black reality to serve its own agenda; Said revealed orientalism as a Western tactic for moulding and dominating the Orient. Her current projects include an Afro-centric perspective and an African-American poetics. While exploring the intricacies of black women's life in white America, she tries to comprehend the contradiction of her African-American identity. This presentation will examine Toni Morrison's works through the lens of literary criticism.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Rebellion, Novel, America, Afro-Centric, Poetics, contradiction, identity.

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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

 Keywords

Organometallic Catalysis, Ligand Design, Precision Catalysis, Catalytic Efficiency, Green Chemistry, Transition Metals, Computational Chemistry

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Regulatory affairs ensures the safety, quality, and efficacy of pharmaceutical products by managing regulatory submissions and compliance throughout drug development. It plays a vital role in obtaining approval for Investigational New Drug (IND) and New Drug Application (NDA) submissions before marketing. Regulatory professionals coordinate clinical and nonclinical studies while ensuring adherence to national and international guidelines. In India, the Central Drugs Standard Control Organization (CDSCO) is responsible for approving new drugs. This review outlines the regulatory process for new drug approval, required documentation, and the importance of post-marketing surveillance (Phase IV), while comparing regulatory frameworks with global authorities such as the FDA.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Regulatory Affairs, Investigational New Drug (IND), New Drug Application (NDA), Drug Approval, CDSCO, FDA, Clinical Trials, Post-Marketing Surveillance, Drug Development, Regulatory Compliance.

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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

 Keywords

Food Delivery Riders, Gig Economy, Dietary Intake, Perceived Stress Scale, Nutritional Status, Body Mass Index, Meal Pattern Questionnaire, General Nutrition Knowledge Questionnaire, Micronutrient Deficiency, Occupational Health

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nitrosamine impurities have emerged as a major concern in the pharmaceutical industry due to their genotoxic and carcinogenic properties and their potential impact on patient safety. Several incidents involving nitrosamine contamination in marketed medicinal products have prompted regulatory agencies worldwide to establish stringent guidelines for their assessment and control. This study aims to evaluate regulatory management strategies for nitrosamine risk assessment during post-approval changes in pharmaceutical products. The work reviews international regulatory frameworks established by the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), World Health Organization (WHO), and International Council for Harmonisation (ICH), with emphasis on risk-based approaches, lifecycle management, and quality risk management principles. The nitrosamine risk assessment process, including risk identification, evaluation, confirmatory analytical testing, risk control, and continuous monitoring, is discussed in detail. Advanced analytical techniques such as LC-MS/MS and GC-MS are highlighted for their role in detecting nitrosamines at trace levels and ensuring compliance with acceptable intake limits. The study further examines the influence of post-approval changes, including modifications in manufacturing processes, raw materials, solvents, packaging systems, and manufacturing sites, on nitrosamine formation. Findings indicate that effective management of nitrosamine risks requires proactive risk assessment, validated analytical methods, robust change control systems, and adherence to evolving regulatory requirements. A multidisciplinary and lifecycle-oriented approach is essential for maintaining pharmaceutical product quality, ensuring regulatory compliance, and protecting public health.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Nitrosamines, Risk Assessment, Post-Approval Changes, Regulatory Management, ICH Q9, LC-MS/MS, Pharmaceutical Quality System, Lifecycle Management.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Spinal cord injury (SCI) is a life-altering condition that often leads to long-term physical, psychological, and social challenges. Among the various secondary complications associated with SCI, fatigue is one of the most commonly reported yet under-recognized symptoms. Persistent fatigue may negatively influence an individual's ability to participate in daily activities and may significantly affect their overall quality of life. Aim and Objective: The present study aimed to evaluate the impact of fatigue on participation and quality of life in individuals with spinal cord injury living in Mumbai. Method: A cross-sectional observational study was conducted among 138 individuals diagnosed with spinal cord injury. Participants were recruited through convenience sampling. Fatigue was assessed using the Fatigue Severity Scale (FSS). Participation levels were evaluated using the Utrecht Scale for Evaluation of Rehabilitation-Participation (USER-P), and quality of life was assessed using the World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire. Functional independence was measured using the Spinal Cord Independence Measure (SCIM). Data were analysed using IBM SPSS software. Descriptive statistics were calculated, and correlation analysis was performed to determine the relationship between fatigue, participation, and quality of life. Results: The findings of the study indicated a high prevalence of fatigue among individuals with spinal cord injury. Higher fatigue levels were significantly associated with reduced participation and poorer quality of life across multiple domains. A moderate negative correlation was observed between fatigue severity and participation scores, as well as between fatigue and quality of life domains. Individuals reporting greater fatigue demonstrated lower functional independence and decreased engagement in social and daily activities. Conclusion: Fatigue has a significant negative impact on participation and quality of life in individuals with spinal cord injury. The findings highlight the importance of assessing fatigue as a routine component of rehabilitation and implementing targeted interventions to manage fatigue in order to improve participation and overall well-being in this population.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Spinal cord injury, fatigue, participation, quality of life, rehabilitation, physiotherapy.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid growth of digital payment systems and online financial transactions has increased the risk of fraudulent activities, resulting in significant financial losses for customers, businesses, and financial institutions. Detecting fraudulent transactions in real time has become a major challenge due to the large volume of online payments processed every day. This project presents an intelligent Fraud Detection in Online Payment System using Machine Learning techniques to identify and prevent fraudulent transactions effectively. The system utilizes historical transaction datasets containing attributes such as transaction ID, transaction time, transaction amount, account balance details, and other relevant features to analyze transaction behavior and identify suspicious patterns. Data preprocessing techniques including data cleaning, feature selection, normalization, and dataset transformation are applied to improve data quality and model performance. The Logistic Regression algorithm is employed as the core classification technique due to its simplicity, efficiency, and suitability for binary classification problems involving fraudulent and genuine transactions. The developed system is integrated with a web-based application that enables real-time fraud detection. Whenever a new transaction is initiated, the system analyzes the transaction details using the trained machine learning model and predicts whether the transaction is fraudulent or genuine based on learned patterns from historical data. The prediction result is instantly displayed through the web interface, allowing administrators and users to take immediate action when suspicious activities are detected. This approach improves fraud detection accuracy, reduces manual monitoring efforts, minimizes financial risks, and provides a scalable and cost-effective solution for enhancing the security of online payment systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fraud detection in online payment, scam online payment, fraud transaction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Gamification in education leverages the motivational dynamics of game design to transform traditional learning environments into engaging and interactive experiences which enhances learning motivation, boosts classroom engagement, and improves students' learning outcomes. However, using these game mechanics for all type of learner can't cater to all the needs of the learners. Use of one-size-fit-all approach for gamification in education will create challenges like, less scope for personalization in learning, failure in utilizing diverse learning style, inappropriate feedback mechanism, scalability problem, and more focus on extrinsic motivation among learners. To bridge the gap between learner's, need and use of game mechanism, Adaptive Gamification can become the mean where it incorporates gaming elements according to the nature and learning style of the learners. Adaptive gamification with its features like real-time feedback system, scaffolding learning, dynamic adjustment mechanism and learning analytics can bring personalization that needs to be incorporated in order to fulfill the need of the learners' by keeping in view their learning pace and progress. Adaptive leaderboards, branching narratives and virtual mentors which promote inclusivity and equity in education by meeting the diversity among learners. Further, adaptive game mechanism also helps in developing the 21st century skills like, problem-solving, collaboration and digital literacy. It also helps in developing the mindset for a life-long learning. With all the benefits that came with adaptive gamification comes some challenges that can't be ignored. Some of the challenges are adaptive gamification have limitation in term of usability for different educational context. Other major challenges include technical limitation and data privacy problems. Adaptive gamification is a transformative innovation in education that bring the engaging and motivational part of gamification and customization of personalized learning, that help in making learning experience an interesting, effective and inclusive for each learner.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gamification in Education, Adaptive Gamification, Personalizing Learning, Hexad's topology

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Creative Commons Attribution 4.0 and The Open Definition