Volume 12 | Issue 10

 Abstract

E-commerce or "electronic commerce" is the trading of goods and services online. An expanding number of tangible commodities, digital items, and services can be bought and sold electronically by individuals and companies thanks to the internet. Despite having an impressive growth rate, the Indian e-commerce sector has lagged behind that of many industrialized and developing nations, mostly as a result of a comparatively small number of internet users. The Indian E-exchange business has gone through a dramatic shift from merely being a showing platform to one-touch swapping. This study aims to discuss the opportunities and challenges associated with e-commerce. This analysis revealed that up until recently, the emphasis has been on the demand side of the E-Commerce region in order to generate interest.In addition to identifying numerous obstacles to future e-commerce growth and development, this study aims to investigate the evolution of e-commerce in India.

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 Keywords

E-Commerce, B2B, Opportunities and Challenges

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Emerging and developing quickly are cryptocurrencies, especially Bitcoin, and as a result, the world pays attention and worries about the negative effects of cryptocurrencies on the environment. Although these cryptocurrencies seek to put into place an efficient and centralized financial system, they have been found to cause pollution and mainly through processes such as PoW mining. This paper aims at assessing the environmental sustainability of the new generation of money to understand more about its carbon footprint and power consumption. Cryptocurrencies such as Bitcoin depend on computational muscle to solve those intricate puzzles and this process entails a lot of energy. Majority of this energy is generated from non-renewable sources, which worsens emission of green house gases globally. In this paper, an analysis of the power consumption of the most popular cryptocurrencies and their comparison with ordinary financial systems is presented. The implications include aspects of electrical power, carbon intensity, and spatial distribution of mining activities, with focuses on areas using coal and other fossil energy sources. Alongside estimating impacts of cryptocurrencies on the environment, this work also looks into new possibilities for sustainable solution. Some of the recommendations regarding Cryptocurrencies involve turning to PoS and other consensus mechanisms that allow for decreased energy consumption. Moreover, this paper also presents activities within the cryptosphere in relation to the utilization of renewable energy in mining and enhancement of energy usage in the process. The research shows that, though the environmental cost of cryptocurrencies is still high, constant development in consensus algorithms and the current use of renewables are prospects for change. In the final section, therefore, the author stresses the significance of combining the principles of environmental law and the concepts of adaptive control in optimizing a cryptocurrency's utilization of resources worldwide and of creating sustainable regulatory practices and elaborate cooperation between industries to eliminate the adverse environmental impacts of cryptocurrency mining.

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 Keywords

cryptocurrencies, carbon footprint, Bitcoin, Proof of Work, energy consumption, environmental sustainability, Proof of Stake, renewable energy

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 Abstract

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smart city, net zero, hydrogen economy, industry 4.0, green finance

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Data science, also identified as data-driven science, is an involving two or more academic, scientific, or artistic disciplines field about technical methods, processes, and systems to pull out information or insights from data in various forms, structured or unstructured, comparable to data mining. Data science is about trade with large excellence of data for the rationale of extracting meaningful and rational results/conclusions/patterns. It's a recently rising field that encompasses a number of actions, such as data mining and data analysis. It employs techniques ranging from mathematics, statistics, and information technology, computer programming, data engineering, pattern recognition and learning, visualization, and towering presentation computing. This paper gives a clear plan about the diverse data science technologies used in Big data Analytics. Data science is a "perception to unite statistics, data analysis and their connected methods" in order to "recognize and examine genuine phenomena" with data. It employs techniques and theories strained from many fields within the large areas of arithmetic, statistics, information science, and computer science, in particular from the sub domains of machine learning, classification, cluster analysis, data mining, databases, and visualization.

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Data science, data, analytics, information, unstructured data, extraction, preservation, data visualization

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The rise of digital payment systems is driving a global shift towards cashless societies, presenting both opportunities and challenges for economies. This research explores the emerging innovations in payment systems, such as digital wallets, cryptocurrencies, and biometric payments, and their role in shaping a cashless future. It also identifies key challenges, including cybersecurity risks and digital inequality, which could hinder widespread adoption. Using secondary data from research papers, industry reports, government publications, and case studies, the study examines the potential for economic growth and financial inclusion enabled by cashless systems, while also assessing regulatory and infrastructural challenges. The findings highlight that while cashless systems offer significant benefits in terms of transaction efficiency, financial inclusion, and transparency, there is a need for comprehensive strategies to address security concerns and ensure equal access to digital payment platforms.

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Cashless society, Digital payment systems, financial inclusion, Cybersecurity Digital wallets

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This paper is to study the significance of digital currency in the modern Era. Digital money is any means of payment that exists in a purely electronic form.. It is accounted for and transferred using online systems. Digital money streamlines financial infrastructure, making it cheaper and faster to conduct monetary transactions. Bitcoin is often considered as first cryptocurrency. Digital Wallet is an application on an electronic device that stores payment transaction and allows to securely make purchases without carrying cash or cards. It was of great usage during COVID times. India is prepared to face such challenges in future making a cash free economy.

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Digital Money, Digital wallet

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Digital currencies have become a hot topic among regulators, financial institutions, and economists in recent years, having previously been discussed only at the margins of the financial discourse. Debates over the potential of Cryptocurrencies like bitcoin and Ethereum, Stablecoins, and Central Bank Digital Currencies (CBDCS) to transform international financial systems have been triggered. Although conventional finance has operated within established structures, virtual currencies present new prospects, difficulties, and consequences. This article explores the complex role that digital currencies play in our financial system, examining both their short- and long-term effects and their transformative potential.

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Digital Currencies, Cryptocurrencies, Blockchain, Bitcoin, Cybersecurity

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 Abstract

Digital Money, also known as electronic money or e-money, refers to any form of currency or value that exists in digital or electronic form. It represents a digital representation of traditional fiat currency, such as the US dollar or the euro, or a digital representation of an asset, like gold or a specific commodity. Digital Currency is typically stored and transacted electronically, using digital devices such as computers, smartphones, or other electronic devices. It allows for quick and convenient transactions, as well as seamless online payments. Similar to physical banknotes, the Digital Rupee will have unique identification and will be regulated by the RBI. The liability for the currency will rest with the central bank. Digital Currency aims to be accessible both online and offline. The RBI plans to launch two versions of the Digital Rupee: Digital Rupee for Wholesale (eINR-W) catering to financial institutions for interbank settlements and Digital Rupee for Retail (eINR-R) for consumer and business transactions. The implementation of the Digital Rupee is expected to eliminate the costs associated with the security printing of physical currency, which is currently borne by the general public, businesses, banks, and the RBI. The transition to a digital currency has the potential to enhance efficiency, transparency, and accessibility in financial transactions within the Indian economy.

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 Keywords

E-Money, Digital Currency, Bitcoin, cryptocurrency. .Central Bank Digital Currencies CBDC, Virtual currency.

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Agriculture is the backbone of every country's economy and has the highest position in providing livelihood to people and ensuring and maintaining the sustainability of ecosystems, however, industrialization and its subsequent effects require modernization of the current agricultural system. In this regard, new information technologies and artificial intelligence provide the best ways to increase agricultural yield. The Internet of Things (IoT) is the use of information technology and wireless communicators and sensors mounted on various objects that have the ability to communicate in real time. The IoT field can control the environment for growing crops, predict the need for fertilizers in the soil, identify plant diseases, and help automate farm machinery to minimize labour-related issues. With this concept in mind, we present a detailed review on IoT in agricultural systems with special emphasis on smart agriculture and cloud computing, sensors and communication platforms, and deep and transfer learning in disease recognition. Prediction of soil temperature and moisture, meteorological events and the onset of pest attacks can solve crop loss problems by alerting the farming community before such unfortunate events begin and before an economic threshold level is reached.

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Cloud computing; Crop monitoring, Crop sensors, Internet of things, Smart agriculture

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Artificial intelligence, which seems like a remote dream, has now encouraged from science literature movies to reality, gaining thrust in the last few years and leading to many developments in almost every field. All industries will be impacted by AI, and AI is no exception. The impact of intellectual property on the field of intellectual property will be twofold. On the one hand, intellectual property will prove ownership of patents and patent search tools, will be researched and searched in a timely manner, and provide a system for installation. inventions and provides innovators with methods for existing patents similar to their own ideas and many other things, but on the other hand, intellectual property can also come Voluntary, it also proves to be a threat to innovation and creativity, knowledge of rights in the mind. The emergence of Generative Artificial Intelligence (AI) has ushered in a new era of innovation and revolutionized the intellectual property rights (IPR) landscape. This research paper aims to explore the balance between supporting AI-generated creativity and protecting personal AI. Generative AI is capable of producing a wide range of original content, from writing to scientific research, posing a serious challenge to the notions of human intelligence and intellectual property holders as a creative person. This article provides an in-depth look at existing legal frameworks regulating intellectual property rights and examines their relevance in overcoming the challenges presented by artificial intelligence. - create content. It raises questions about the writing and history of the digital age by showing important circumstances in which works independently created by artificial intelligence may qualify for copyright. Additionally, this article explores the ethical and economic implications of AI in the field of intellectual property, considering its potential to create content freedom and the risk of making humans creative. Using a multidisciplinary approach and drawing on knowledge from legal science, technology, and ethics, this study presents a revised legal model innovation that incorporates the unique features of artificial intelligence while protecting the rights and motivations of human creation.

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Artificial Intelligence, Intellectual Property Rights, Copyright Law, Patent Law, Machine Learning

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The amount of money needed to fund a day-to-day business operation is known as working capital. The objective of the study was to evaluate the working capital of select FMCG companies in india the duration of the study was 2019-2023. Six companies chosen for the study. The cash conversion cycle, payable days, inventory days, and receivable days are computed to evaluate the performance of the business. Descriptive statistics used for analysis. The study's findings demonstrated that HUL and Britannia were having negative working capital.

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WORKING CAPITAL ANALYSIS ON SELECT FMCG COMPANIES IN INDIA

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Role of ESG consideration in determining investment decision: An individual Investor perspective

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India is the second highest population in the world. India's construction industry is large as well as visible and providing employment to 3.2 crore workers nationally. The present study analyses the changing pattern of socio economic condition of construction workers in Sivagangi District of Tamil Nadu. Also, the researcher attempted to found the socioeconomic condition, identified the problems of construction workers and working condition and health awareness of construction workers in the study area. This study was entirely based on primary data which were collected from 100 respondents. The samples were selected purposively. The researcher found that three aspect such as the socio economic condition, working condition and health problems of construction workers in the study area. The researcher find out 50 percent of the samples respondents were earned income of between one lakh to two lakhs and 34 percent of the construction workers were earned income of between two lakhs to three lakhs. Remaining 8 percent of the workers were earned below one lakh as well as above three lakhs in the study area.

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construction work, population growth, socio economic condition, employment, health status, awareness

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ELECTRICAL CONDUCTION AND OPTICALPERFORMANCEOFRARE- EARTH (Er³⁺, Tb³⁺) DOPED CALCIUM SILICATE

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Calcium silicate1, rare-earth doping2, electrical conductivity3, photoluminescence4, erbium ions5.

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Recent advancements in deep learning for Natural Language Processing (NLP) have significantly accelerated research in Natural Language to SQL (NL2SQL) translation across both academia and industry [1]. Several architectures have been proposed to address this task, including approaches based on reinforcement learning, sequence-to-sequence (Seq2Seq), and sequence-to-set (Seq2Set) learning frameworks [2][3]. In this work, we propose a hybrid architecture that integrates TaBERT and SQLOVA for enhanced NL2SQL generation. TaBERT, which is pre-trained on structured tabular-text data, provides superior contextual understanding compared to conventional BERT representations [4], thereby improving the semantic encoding of natural language queries and table headers. The NL2SQL component of SQLOVA is stacked on top of the TaBERT encoder, enabling further contextual refinement and feature extraction from both query and schema representations. Additionally, the choice of optimization strategy plays a critical role in improving model convergence and prediction accuracy. Experimental results on the WikiSQL dataset demonstrate that the proposed architecture, when trained using the Lookahead optimizer [5], achieves performance improvements of 0.2%, 0.5%, and 0.4% in where-num, where-col, and where-cond accuracy metrics, respectively, compared to the baseline model.

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neural networks, NLP, nl2sql

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 Abstract

Rajasthani Lok Sahitya Me Rajputon Ki Virata Avam Shaurya

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Rajasthani Lok Sahitya Me Rajputon Ki Virata Avam Shaurya

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Persistent challenges in real-time character animation across heterogeneous metaverse platforms have motivated the development of architecturally sophisticated AI systems capable of unified motion synthesis and cross-device deployment. This paper presents MetaAnimNet, a transformer-based animation intelligence framework designed to address the longstanding disconnect between motion quality, computational efficiency, and platform interoperability in virtual environment applications. The proposed architecture integrates a temporal attention mechanism with a motion context fusion module, enabling the system to generate fluid, physically plausible character animations that adapt to varying skeletal rigs and rendering pipelines across Unity, Unreal Engine, and web-based environments. Unlike prior deep learning approaches that optimize for a single platform configuration, MetaAnimNet employs a cloud-edge synchronization strategy that balances inference load between edge devices and server-side computation, sustaining real-time frame rates even under constrained hardware conditions. Experimental evaluation across four benchmark datasets, including Human3.6M, CMU Motion Capture, Mixamo, and AMASS, demonstrates that MetaAnimNet achieves a mean per-joint position error reduction of 18.4% over the strongest baseline, while maintaining an average inference latency of 23.7 milliseconds per frame on standard consumer-grade GPUs. Motion smoothness scores and cross-platform consistency metrics further confirm the practical deployability of the proposed system. The framework is validated in a live metaverse testbed, where avatar synchronization accuracy and user immersion quality are measured against existing animation intelligence systems.

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transformer-based animation; metaverse character animation; cross-platform motion retargeting; temporal attention mechanism; avatar synchronization; real-time motion synthesis; animation intelligence; deep learning motion prediction

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Displacement from home causes a crisis of identity, but also creates opportunities for a new hybridized identity which often questions received notions of nationality and culture. In case of women, there is a further inflection of identity by gender. Diaspora helps Indian woman to come to terms with herself, a process which could not be affected within the Indian socio-cultural setting. In my paper focused on Arundhati Roy's The God of Small Things, Jhumpa Lahiri's The Namesake and Kiran Desai's The Inheritance of Loss, I wish to look at the implications of crossover by female protagonists and characters and how it impacts cultural identity. The women novelists have fashion female autonomy in their female characters by giving them a new vision of Indian women, pleasing to Western mind and feelings and yet reflecting their Indian-ness and have allowed each heroine to assume beyond the adequate performance of the Indian expected feminine roles. They fight against the role-model mind set and the cultural identity of the archetype of traditional Indian women. The paper will seek to study the tension and conflict between being rooted and being in perpetual motion in relation to the governing issue of being a woman caught between patriarchy and a liberalized world order and how they negotiate between the question of "home" and "world".

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(Diaspora, Identity, Gender, Belonging, Cultural Hybridity)

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Having reliable labor market statistics is essential for understanding employment dynamics and designing effective economic policies. In developing economies like India, where a significant portion of the workforce is engaged in informal and self-employment work, measuring employment and unemployment presents significant conceptual and methodological challenges. This study examines the main sources of employment and unemployment data in India and analyzes the methodologies used to measure labor market indicators. The paper compares key datasets, including the Periodic Labour Force Survey (PLFS), the Consumer Pyramid Household Survey conducted by the Centre for Monitoring the Indian Economy (CMIE), the Population Census, and international labor databases. Using a descriptive and comparative analytical approach, the study assesses differences in measurement methods, such as "usual status," "current weekly status," and "current daily status." The findings highlight that variations in survey methodologies, reference periods, and sampling designs often lead to significant differences in employment estimates. The study also identifies several challenges in labor market data, such as the underreporting of informal employment and female labor, limitations of high-frequency labor statistics, and comparability issues across datasets.

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Employment measurement, unemployment statistics, labour market data, PLFS, CMIE, India

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Abstract: Inflammation is a type of defense mechanism employed by the immune system that hinders infection advancement and supports the effective elimination of a variety of external invasions. Self-assembled nano structures, particularly chromosomes are gaining increased utility and popularity as a medication transport mechanism under circumstances like arthritis. These chromosomes serve as highly adaptable carriers with encouraging thermostatic capabilities and can be delivered through oral, topical, intravenous, ocular, and trans dermal routes. Recently valuable research has contributed to enhancing the effectiveness, analysis, target specificity, and regulation of drug release profiles for delivery of anti-inflammatory bio active. However, the clinical transition has been sluggish and also necessitates substantial display. This review highlights the late developments with challenges in the progress as well as appeal of chromosomes in case of different inflammatory pathways on rheumatoid arthritis while also addressing the obstacles encountered in transforming it into a viable nano technological solution.

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Keywords: Target specificity, Nanotechnology, Bio actives, Inflammatory pathways

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