Volume 13 | Issue 6 |

 Abstract

Green finance plays an important role in promoting sustainability by diverting resources into ecologically friendly enterprises. This article emphasizes its expanding role in India's transition to a low-carbon economy, particularly in light of global climate commitments. The study uses a descriptive methodology and is based on secondary sources such as official statistics, reports, and scholarly literature. According to the findings, green finance has a favorable impact on India's growth in renewable energy, carbon reduction, climate resilience, and sustainable urban development. Key motivators include increased public awareness, international funding, and policy support. These findings imply that green finance not only promotes environmental objectives but also improves investor confidence and economic stability. In the future, its influence might be increased by incorporating fintech, increasing the number of green financial products, and clarifying regulations. According to the study, green finance is more than a trend; it is a fundamental pillar of sustainable development in India.

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 Keywords

Green Finance, Emergence of Green Finance, Drivers , Green Bonds

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract Purpose: - The purpose of the research is to analyse the factors influencing purchase decisions of millennial and gen z in online shopping environments. The researcher aim to find the influence of e-retailers image, social factors, situational and trust factors for preferring the online shopping over traditional shopping on Millennial and Gen Z. Motivation for the study: Younger age groups, including Millennial and Gen Z, exhibit higher frequencies of online shopping. They also demonstrate a stronger inclination towards using mobile devices for shopping and are more receptive to digital marketing strategies. In contrast, older consumers may have less familiarity with online shopping platforms and be more cautious about sharing personal information online. Research approach: This study examines consumer preferences in Lucknow, specifically their inclination towards online shopping versus traditional methods. It investigates how of e-retailers image, social factors, situational and trust factors impact their purchase decisions. Data was gathered from 178 consumers in Lucknow district and analyzed for this research. Finding: The research revealed that the majority of Millennial and Gen Z individuals opt to buy products through e-retail websites, as these platforms have successfully established trust among shoppers. Given the busy lifestyles of consumers, online shopping is considered more convenient. Contribution: This paper aims to assist e-retailers in comprehending the purchasing preferences of young adult consumers from the Lucknow district.

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Key words: Online shopping, factors influencing of online consumer, online shopping behaviour of Millennial and Gen Z, online buying behaviour.

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Genetic testing is a vital tool in assessing breast cancer risk, guiding treatment decisions, and improving early detection and personalized treatment. However, in India, limited genetic literacy--defined as the ability to understand and apply genetic information in healthcare decisions--combined with financial, infrastructural, and policy-related barriers, significantly restricts access to these life-saving services. Our findings show that only 10-15% of eligible patients undergo testing, and fewer than 30% of hospitals offer genetic counseling. Despite 22.5% of patients having a family history of breast cancer, awareness of BRCA mutations remains low. To improve access, we recommend integrating genetic counseling, expanding literacy programs, and implementing cost-reduction policies, ensuring early detection and personalized treatment for better patient outcomes. Such efforts will facilitate early diagnosis, improve treatment personalization, and ultimately enhance patient outcomes. Addressing these systemic issues is critical to ensuring equitable access to genetic services in India and fostering a more informed, proactive approach to breast cancer prevention and care.

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 Keywords

Genetic Testing, Genetic Literacy, Breast Cancer, BRCA Mutations, Genetic Counseling, Healthcare Access, Personalized Medicine, India, Early Detection, Precision Oncology.

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Creative Commons Attribution 4.0 and The Open Definition

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In the digital age, memes have emerged as a dominant form of communication, entertainment, and commentary. More than mere humor, memes serve as tools of satire, critiquing societal norms, politics, and culture with remarkable speed and reach. This paper explores how internet memes function as modern literary satire, analyzing their rhetorical strategies, intertextual nature, and participatory elements. Drawing from literary theory and media studies, the research argues that memes are a new form of digital literature that mirror and evolve traditional satirical functions, embodying the voice of the contemporary collective consciousness.

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Creative Commons Attribution 4.0 and The Open Definition

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Internet Memes, Digital Satire, Meme Theory, Intertextuality, Irony and Parody, Multimodal Texts

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Creative Commons Attribution 4.0 and The Open Definition

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Indian cinema has always been more than just a form of entertainment; it's the heartbeat of our collective story, telling us who we are and who we aspire to be. In the early days before independence, filmmakers quietly but powerfully wove anti-colonial messages into their stories, quietly kindling cultural pride and unity. After 1947, the silver screen became a mirror to our nation's hopes and hardships, boldly addressing the struggles of poverty, social injustice, and the fragile dreams of freedom. The 1970s and 1980s marked a turning point: heroes with a fire in their hearts, the iconic "angry young men", stood up against corruption and inequality, giving voice to the frustrations of everyday people. Fast-forward to the present, and Indian films have embraced globalisation without losing their soul. Movies like Lagaan and Uri: The Surgical Strike captivate us not only with epic storytelling but also with themes of resilience, self-reliance, and patriotic pride. Through a thoughtful mix of content analysis, literature insights, and historical perspective, this study dives into the symbols, narrative techniques, and cinematic moments that have continuously inspired a shared sense of national identity.

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 Keywords

nationalism, cultural identity, cinematic symbolism, public sentiment, patriotic cinema, social justice

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The rapid and accurate detection of COVID-19 has been crucial in mitigating the spread of the virus and ensuring timely medical intervention. This study presents a deep learning-based approach utilizing neural networks for the early detection of COVID-19 from clinical and radiological data. By leveraging convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the proposed model achieves high sensitivity and specificity in distinguishing COVID-19 cases from other respiratory conditions. The framework incorporates data preprocessing, feature extraction, and model optimization techniques to enhance diagnostic performance. Experimental results demonstrate the model's effectiveness in providing rapid, reliable screening, offering a promising tool for frontline healthcare systems, especially in resource-constrained environments. This research highlights the potential of deep learning as a transformative solution in pandemic response strategies, emphasizing the importance of AI-driven healthcare innovations.

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 Keywords

COVID-19 Detection, Neural Networks, Deep Learning, Rapid Screening, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Medical Imaging, Artificial Intelligence in Healthcare

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Sugarcane (Saccharum officinarum) is a vital commercial crop that significantly impacts the global economy, particularly in sugar and ethanol production. Proper management of sugarcane cultivation and its byproducts is crucial to enhancing productivity, reducing waste, and promoting sustainability. This review examines key aspects of sugarcane management, including optimal cultivation techniques, pest and nutrient control strategies, and harvesting methods. Additionally, it explores the effective utilization of byproducts such as bagasse, molasses, and press mud in biofertilizer production, energy generation, and other industrial applications. Furthermore, the study highlights emerging technologies and sustainable waste management strategies within the sugarcane industry. By implementing efficient farming and processing techniques, it is possible to increase yield while minimizing environmental impact, ensuring the long-term sustainability of the sugarcane sector.

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MANAGEMENT OF SUGARCANE AND ITS BY PRODUCTS

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Soil fertility constitutes a key factor in influencing the precise prediction of soil fertility classes, as well as agricultural productivity is important to optimizing agriculture practices. Classical soil fertility assessment methods are often labor intensive and costly. Machine learning based approaches are therefore an attractive alternative for improving efficiency. In this research, a novel method is introduced as a stacking ensemble method for soil fertility classification, which combines models. Each individual model is trained separately and their forecasts are combined through a meta-model in order to improve categorization ability.Unlike traditional single-model approaches the ensemble method effectiveness compared to individual models is assessed using classification metrics like F-1 measure, accuracy, sensitivity.The ensemble outperforms the the individual models demonstrating improved robustness and predictive reliability over existing techniques highlighting its potential for providing more robust and reliable soil fertility predictions.compared to previous approach this method provides more stable performance across fluctuations in nutrient levels and PH.This approach shows promising applications in precision agriculture, offering improved decision-making for soil management. Future studies aimed at improving performance could integrate data input such as sensor data.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Decision Tree,Gaussian NB,KNN,Logistic Regression,Machine Learning,stacking ensemble

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Creative Commons Attribution 4.0 and The Open Definition

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The widespread availability of nucleotide and amino acid sequence data has enabled the development of advanced methods for identifying biologically and clinically significant information. Online platforms such as GeneCards offer accessible repositories for extended research and academic exploration. Additional protein-related data can be retrieved from databases like UniProt and SwissProt. Tools such as FASTA and Clustal_X are commonly used to calculate sequence similarity, aiding in the selection of target genes. In addition, text mining serves as a valuable technique for extracting relevant knowledge from scientific literature.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

FASTA, Clustal_X, Genomic Data, Genetic Sequences, Bioinformatics

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Creative Commons Attribution 4.0 and The Open Definition

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This paper uses machine learning models to detect lung cancer early using patient data. Random Forest showed the best accuracy, offering a low-cost and effective diagnostic tool for early detection.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Lung Cancer, Early Detection, Machine Learning, Patient Records, Clinical Symptoms, Predictive Modelling, Medical Diagnosis, Structured Data, Support Vector Machine (SVM), Random Forest, Logistic Regression, Cancer Risk Prediction, Artificial Intelligence in Healthcare, Health Informatics, Non-Invasive Diagnosis

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