Volume 13 | Issue 2 |

 Abstract

Artificial intelligence (AI) has rapidly become a game-changing technology in the banking industry. It is transforming the way banks operate and interact with their customers. AI-driven predictive models also play a crucial role in fraud detection, enabling banks to identify and prevent fraudulent activities in real time. By analyzing customer behavior, AI can flag unusual transactions or suspicious activity, allowing banks to respond swiftly and minimize potential losses. From automating tedious tasks to providing personalized services, AI is revolutionizing the banking sector in numerous ways. In this blog post, we will explore ways in which AI is being used in banks to enhance efficiency, improve customer experience, and make better-informed decisions. So, let's dive into the world of AI and discover how it is shaping the future of banking.

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 Keywords

Decision Making, Customer Behavior, Fraud Detection, Robo-Advisors, Risk Assessment, Personalized Marketing.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The current paper tries to locate the areas where the New Education Policy 2020 in India reflects the hidden issue of inequality and disparity in Higher Education. This is significant because the policy makers have intended to make education a tool to level the different social inequalities in our country. A sociological reading into and an analysis of the NEP 2020 shows the possibility of disparities hidden in the policy initiatives not only among the students but also in the institutional frameworks. An understanding of the same would help not only in overcoming the same but also create a just and equal society which the policy makers have as one of their stated objectives.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

NNEP 2020, higher education, social inequalities, social disparities, caste, class, gender, capitalist market.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Birds are excellent indicators of the health of an ecosystem in a landscape and perform vital ecological roles such pollination, seed dispersal, pest control, and nutrient dynamics. In order to guarantee ecological functionality and ecosystem stability, biodiversity inventory and conservation, including landscape-level ecosystem restoration, have recently become top priorities worldwide. The purpose of this project is to establish a baseline database of avifaunal assemblages in the Kalimpong District of West Bengal at the lower altitudinal level. A total of 56 bird species, representing 29 families, were documented. In terms of family diversity, Muscicapidae was the most prominent in the study area, with 9 species, followed by Picidae with 5 species. This study contributes valuable insights into the avian diversity of the region.

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 Keywords

Avian Fauna, species richness, Kalimpong, RDi

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

When we encounter difficult or taxing circumstances, or stressors, our bodies and minds go into a hyperarousal state, commonly known as stress. Chronic illnesses including anxiety, depression, and cardiovascular disease can develop in people who are exposed to various stressors for an extended period of time, particularly when these stressors happen at the same time. In order to avoid these long-term impacts, it is essential to recognise stress early on, and continuous monitoring provides a viable option. One possibility for personal stress monitoring is the use of wearable devices that can gather data continuously and in real-time, allowing users to keep tabs on their stress levels as the day progresses. This study provides an extensive analysis of several approaches to stress detection that make use of wearable sensors in conjunction with machine learning methodologies. Wearable sensors including electrocardiograms (ECGs), electroencephalograms (EEGs), and photoplethysmography (PPGs) are reviewed, along with the many settings when stress is tracked, such as while driving, learning, or working. Various stress detection approaches were examined in this review, with an emphasis on the stressors, procedures, outcomes, benefits, drawbacks, and difficulties encountered by each research. The area of stress monitoring is anticipated to benefit from these findings in the future. In addition, the study suggests a multimodal stress detection system that combines various kinds of wearable sensors with deep learning algorithms. This could be a great step towards better real-time stress detection that is both accurate and adaptive, which would be great for mental health management and healthcare prevention.

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 Keywords

Stress Detection, Wearable Sensors, Machine Learning, Electrocardiogram (ECG), Electroencephalography (EEG), Photoplethysmography (PPG), Real-time Monitoring, Mental Health, Psycho- physiological State, Continuous Monitoring, Deep Learning, Multimodal System, Stressors, Personalized Stress Management, Health Monitoring

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In the Vedic Period (1500-1000 BC), women were venerate as mother goddesses (Shakti). They represent life and were believed to hold huge tolerance and sacrifice abilities. As a result, women held respectable position in society during Vedic era. In this period; women had equal status and position as their male counterparts. They were allowed to actively participate in rituals with their husbands and attend the Sabha political institution to share their opinions. Women like Virangana, Bipla, and Mrigalina were mentioned as gone to war. Despite the priority for the birth of a son in society, daughters were not neglected. Women can get higher education during this time and can learnt Vedic hymns, such as Apala, Ghosha, Lopamudra, Vishwabara, Gargi, and Maitri. They were also able to hold the upavit, a sacred thread wear by Hindu. Women were wealthy and can beautify themselves with expensive jewellery, cosmetics, and various hair buns. They could wear many costumes and participated in festivals and dances. Women during Vedic period were skilled in various handicrafts and were praised for their beauty. The main aim of this paper is to attain an understanding of gender role and women equality in Vedic language. The article "Gender Role and Women Equality in Vedic Literature" can give an overview of the position of women and gender role in ancient Indian society, as reflected in Vedic texts.

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 Keywords

Women equality, Women status, Vedic period, Ancient India.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract Chinua Achebe's Things Fall Apart is a landmark in African literature, offering a profound exploration of the effects of colonialism on indigenous African societies. This paper examines how Achebe portrays the clash of cultures and the ensuing struggle for personal and communal identity in Igbo society. Through the experiences of Okonkwo and the transformations in the fictional village of Umuofia, Achebe critiques the destructive forces of colonialism and examines the deep-seated tensions between tradition and change, ultimately presenting a nuanced understanding of African identity in the face of European imperialism.

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Key word: Colonialism, Clash of cultures, Struggle for identity, Personal identity, Communal identity, Igbo society, Okonkwo, Umuofia, Cultural transformation, Tradition vs. change, European imperialism

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Creative Commons Attribution 4.0 and The Open Definition

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Efficient inventory management is crucial for businesses to maintain optimal stock levels, reduce costs, and improve operational efficiency. This research presents an Inventory Management System (IMS) developed using Python and PyQt5, providing a user-friendly graphical interface for inventory tracking. The system enables businesses to monitor stock levels, manage product details, generate reports, and automate restocking alerts. By leveraging PyQt5 for the GUI and Python for backend processing, the system ensures seamless interaction and data management. The proposed IMS enhances accuracy, reduces manual errors, and improves decision-making by offering real-time inventory insights. This research highlights the system's architecture, features, and the benefits of integrating technology into inventory management.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Inventory Management, Stock Tracking, Inventory System, PyQt5, Python, Database Management, Automation, GUI Application, Inventory Control, Real-time Monitoring, Data Accuracy, Retail Management, Supply Chain, Inventory Optimization, Software Development.

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Creative Commons Attribution 4.0 and The Open Definition

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The fluvio-coastal Khejuri Blocks of Purba Medinipur district in West Bengal is a dynamic landscapes shaped by riverine and marine interactions. Having the influences from river Hooghly, river Rasulpur, Talpati channel and Bay of Bengal, the region is highly vulnerable to fluvio-coastal erosion, tidal surges, sea cyclones, saline intrusion, and socio-economic stressors, necessitating comprehensive research for sustainable management. This study aims to systematically review existing literatures on the geomorphological, hydrological, ecological, and socio-economic aspects of the region to identify knowledge gaps and refine potential research directions. A critical analysis of past studies reveals gaps in long-term morphodynamic assessments, the socio-ecological impacts of climate change, and the effectiveness of existing coastal management strategies. Additionally, inconsistencies in data availability and methodological approaches limit a holistic understanding of the region's evolving dynamics. By synthesizing insights from interdisciplinary research, this study seeks to highlight underexplored areas such as community resilience, nature-based adaptation strategies, and the integration of remote sensing and GIS for spatiotemporal analysis. Addressing these research gaps is crucial for developing evidence-based policies and sustainable management strategies for the Khejuri Blocks. This review will contribute to a more focused and impactful research agenda, ensuring a scientific foundation for mitigating the environmental and socio-economic challenges of this vulnerable coastal region.

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 Keywords

Fluvio-coastal dynamics, Khejuri Blocks, literature review, knowledge gaps, potential research focus, coastal management, climate resilience

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Creative Commons Attribution 4.0 and The Open Definition

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The asset management industry is undergoing a transformative shift driven by advancements in big data analytics and machine learning (ML). This paper explores the integration of these technologies into portfolio optimization, highlighting their potential to enhance decision-making, risk management, and returns. By leveraging vast datasets--ranging from market data to alternative data sources like social media sentiment and satellite imagery--machine learning algorithms can uncover hidden patterns and generate predictive insights. This study examines the application of ML techniques such as reinforcement learning, neural networks, and natural language processing (NLP) in asset allocation, risk assessment, and performance prediction. Through a combination of theoretical analysis and empirical data, the paper demonstrates how these technologies are reshaping traditional financial models and creating new opportunities for investors. The findings suggest that the future of asset management lies in the seamless integration of human expertise and machine intelligence, paving the way for more adaptive and resilient investment strategies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Asset Management Industry, Big Data Analytics, Machine Learning (ML), Portfolio Optimization, Decision-Making, Risk Management, Investment Returns, Market Data, Alternative Data Sources, Social Media Sentiment, Satellite Imagery, Predictive Insights, Machine Learning Algorithms, Hidden Patterns, Reinforcement Learning, Neural Networks, Natural Language Processing (NLP), Asset Allocation, Risk Assessment, Performance Prediction, Financial Models, Empirical Data, Human Expertise, Machine Intellige

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This review manuscript examines the protective effects of corn silk extract (Zea mays) against lithium carbonate-induced renal toxicity in rats. Lithium carbonate, widely utilized as a mood stabilizer for bipolar disorder, has been associated with significant renal damage, manifesting as lithium-induced nephropathy. The review highlights the complex mechanisms underlying lithium nephrotoxicity, including oxidative stress, inflammation, and alterations in renal fluid balance, leading to chronic kidney disease. Given the potential adverse effects of long-term lithium use, there is an increasing interest in natural compounds that can mitigate these renal injuries. Corn silk, known for its diuretic, anti-inflammatory, and antioxidant properties, has shown promise in reducing kidney damage caused by nephrotoxic agents. The manuscript synthesizes existing research on the biochemical, histopathological, and molecular effects of corn silk extract, emphasizing its potential as a renoprotective agent. The findings suggest that corn silk extract could serve as a complementary treatment to reduce the risk of renal damage in patients undergoing prolonged lithium therapy. However, further clinical studies are required to validate its efficacy and safety in humans, as well as to explore optimal dosages and interactions with other nephrotoxic drugs. This review underscores the importance of investigating natural remedies in the context of pharmaceutical treatments, especially for vulnerable populations reliant on long-term medication.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Corn Silk Extract ,Lithium Carbonate ,Nephrotoxicity , Oxidative Stress ,Renal Protection

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Creative Commons Attribution 4.0 and The Open Definition