Volume 13 | Issue 8 |

 Abstract

This study investigates investor behavior towards bond market investments in India, focusing on the influence of fintech platforms, ESG-oriented green bonds, and investor financial literacy in enhancing retail participation. Using a sample of 200 respondents across Karnataka, the study applies descriptive statistics, ANOVA, and regression analysis to examine the impact of demographic, behavioral, and technological factors on investor preferences and repeated investment decisions. Findings reveal that factors such as age, income, digital readiness, and investor awareness significantly affect bond investment choices, while fintech tools and ESG-focused green bonds foster confidence and participation. The study highlights gaps in financial literacy and digital infrastructure in smaller cities, underscoring the need for targeted digital education, regulatory streamlining, and accessible fintech platforms to expand inclusive and sustainable bond market participation in India.

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 Keywords

Bond Market, Retail Investors, Fintech, Green Bonds, ESG, Investor Awareness, Financial Literacy, India.

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The prompt accurate identification of leaf diseases are crucial for enhancing agricultural productivity and mitigating crop losses. This study introduces a model based on Convolutional Neural Networks (CNN) that utilizes transfer learning through EfficientNet-B0 for the intelligent detection of plant leaf diseases. The model was trained and validated using a carefully curated dataset comprising over 10,000 images across various disease categories. We conducted a comparative analysis with three advanced models: Vision Transformer (ViT), ResNet-50. The experimental findings indicate that our proposed model achieved a remarkable classification accuracy of 97.8%, surpassing ViT's 94.2%, ResNet-50's 92.6%. The system's precision, recall, and F1-score were recorded at 98.1%, 97.5%, and 97.8%, respectively. Additionally, the model demonstrates quicker inference times and lower computational requirements. This research presents an effective and scalable solution for real-time implementation in smart agriculture applications, suitable for mobile or embedded systems.

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Convolutional Neural Networks (CNN), Leaf Disease Detection, EfficientNet-B0, Transfer Learning, Smart Agriculture, Deep Learning.

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 Abstract

Health issues like non-communicable diseases (NCDs), obesity, mental health problems and sedentary livelihood of a majority of population in the world often pose a massive threat to the global health and economy. In order to address this emerging issue, G20 nations have been found to encourage the inclusion of cost-friendly approaches like physical activities and sports in the daily lives of people to foster the economy and well-being of their population. This study primarily focuses on comparison of health issues of different types and strategies or health policies undertaken by G20 nations in order to incorporate physical activity and sports in educational institutions and public health sectors. Several barriers pertaining to the promotion of physical health like rapid urbanization, limited accessibility of people to sports facilities alongside cultural and socio-economic issues have been discussed in great detail with emphasis on certain health policies that have been successfully implemented. However, there are still a few challenges faced during policy administration in the nations which have been brought to attention simultaneously and specific recommendations are suggested to overcome them. This paper strongly supports the preparation of proper health policy frameworks for effective global health outcome. Promotion of healthy living standard in people is facilitated by the inclusion of physical activity and sports in school curriculum and at workplace with development and easy accessibility of public infrastructure and sports facilities alongside raising public awareness through discussions in G20 forums with an aim to provide a sustainable solution to emerging health issues.

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 Keywords

Healthy lifestyle, economy, well-being, policies, sustainability

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 Abstract

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5F's, knowledge, children, effectiveness, VATP.

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In recent years, there has been a notable increase in the interest surrounding machine learning techniques within the healthcare sector, particularly for their capacity to forecast diseases using patient data. This paper introduces a symptom-based disease prediction system that employs three machine learning algorithms--Support Vector Classifier (SVC), Gaussian Naive Bayes, and Random Forest Classifier. The model is trained on a carefully curated dataset comprising 4920 patient records linked to 41 distinct diseases and 132 symptoms utilized as predictive features. Users must provide at least three symptoms, as depending on a single symptom does not produce reliable or accurate predictions. Utilizing the chosen symptoms, the system forecasts the most likely disease, serving as a valuable preliminary screening tool. This framework offers a practical, cost-effective, and accessible approach for early-stage disease prediction and bolsters ongoing initiatives to incorporate machine learning into healthcare support systems.

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 Keywords

Disease prediction, Machine learning, Random Forest, Support Vector Classifier, Gaussian Naive Bayes, Symptom-based diagnosis, Healthcare, Gradio interface

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Tribal athletes, though often naturally active and physically resilient, face significant nutritional disadvantages rooted in socio-economic and cultural disruptions. These deficiencies, particularly in key nutrients like iron, calcium, protein, and B vitamins, undermine their athletic development and competitive performance. This study synthesizes findings from tribal regions in India, including dietary intake, anthropometric measurements, and observed performance metrics, to examine how undernutrition among tribal athletes impairs endurance, muscle strength, injury recovery, and overall physiological function. It also recommends culturally relevant interventions such as the reintroduction of traditional diets, nutrition education, and structural food policy reforms. Addressing these challenges is essential not just for sports equity but for the holistic well-being and empowerment of tribal youth in India.

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Tribal athletes, performance metrics, nutrition deficiency, indigenous health, traditional diets

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This research paper deals with the unconventional practice of Parag Tandal, an Indian artist belonging to the Koli community of Maharashtra. He uses ceramic as a critical and conceptual material which is rooted in socio political narratives. Instead of adhering to the traditional techniques of utility, finish and permanence he uses a post ceramic aesthetic in his works and liberates the medium from disciplinary constraints by using other mediums with ceramics. This paper deals with how his practice is unconventional and is shaping the contemporary Indian ceramic discourse.

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Parag Tandal, Contemporary Indian Ceramics, Indian Contemporary Art, Koli community, Dhokra casting, Archival Art, socially engaged Art.

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Clear Aligners, Orthodontics, Patient Compliance, Malocclusion, Treatment Outcomes

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The AIDA model (Attention, Interest, Desire, Action) has been one of the earliest building blocks of marketing communication and sales strategies. The purpose of this review paper is provide an overview of the conceptual and empirical use of the AIDA model for stimulating sales performance in various industries. AIDA is grounded in psychological and behavioral theories of consumer decision-making, organized in a step-by-step progression that leads potential customers through the steps of a purchasing funnel. The AIDA model has developed from a simple hierarchy to be a strategically nimble, multi-channel approach to marketing as the traditional marketing promotion landscape continues to evolve to digital and consumer-oriented environments. This paper concludes that a synthesis of over five decades of academic research highlights the progression of the AIDA model. The review organizes findings into two primary streams: (1) Theoretical CLoud Developments of AIDA - criticisms of, and applications of, and (2) Empirical Applications of AIDA using Traditional and Digital Media. There is a special emphasis on how the AIDA model is relevant in online marketing, social media advertising, and integrated marketing communication (IMC). In order to determine effectiveness of each stage in the AIDA model we use the important metrics of customer engagement, conversion rates, and return on investment (ROI). The other important aspects are the new permutations of the model, such as AIDAS (including satisfaction), as well as CAB (Cognitive-Affect-Behavioral), based on evolving behavioral analytics. The review highlights that while AIDA is still an essential construct in marketing practice today, one must recognize that it is a static implicit model that must be adapted and framed in energy and vibrancy through modern data-driven and customer-centric models to add maximum value. Consideration should also be given to future directions of research to align AIDA with AI-enhanced personalization and omnichannel marketing environments.

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AIDA Model, Sales Stimulation, Marketing Communication, Consumer Behavior, Digital Advertising, Attention-Interest-Desire-Action, Purchase Funnel.

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 Abstract

In the present study stress of secondary school students. The data gathered from 200 secondary school students with random sample in Guntur district. The tool adopted for the study was stress scale was prepared by Student's Stress Scale developed by Dr. Zaki Akhtar (2011) was modified, standardized and adopted. Reliability is 0.71. The study also revealed that gender was significantly influenced the stress Implications of the perhaps these were influenced by the characteristics of the subjects were categorized early teens with unstable emotional state

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Stress, Secondary School and Students.

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Creative Commons Attribution 4.0 and The Open Definition