Volume 13 | Issue 11 |

 Abstract

Padmapurane tripurasurasamharakatha ekamadhyayanam

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Padmapurane tripurasurasamharakatha ekamadhyayanam

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From a theoretical perspective, AI has emerged in just a few short years from a seemingly abstract concept to an agent of change that seriously redefine global labor markets and the nature of work. This theoretical paper reviews the complex threat that AI poses to future generations of job opportunities, as well as adaptive strategies to mitigate the negative impacts of such a process. Based on recent studies, policy reports, and theoretical approaches, it will be underscored how automation and machine learning currently displace not only manual and routine jobs but also cognitive and professional jobs from industries. It emphasizes the risk of deepening social and economic inequalities, especially in developing countries with low readiness for digitalization. At the same time, this research recognizes the potential of AI to open up new avenues for job creation, on the proviso that education systems, policy frameworks, and corporate ethics advance to meet the demands ushered in. The discussion underlines the urgency of an approach that integrate AI literacy, critical thinking, and ethical decision-making into mainstream education and employee training programs. It further calls for international collaboration to define regulatory and ethical barriers that would secure the alignment of AI deployment with human-centered values of fairness, transparency, and inclusiveness. In conclusion, this study finds that the impact of AI on employment will not depend merely on technological developments but on how societies cope collectively with its integration, balancing innovation with empathy and; efficiency with equity, in order to secure a sustainable future for future generations.

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Artificial intelligence, automation, employment, workforce transformation, education, ethical AI, digital economy.

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Brain-computer interface (BCI) technology offers a promising innovation in post-stroke rehabilitation by providing real-time neural feedback and motor imagery training to enhance neuroplasticity and motor recovery. This narrative review synthesizes evidence from randomized controlled trials evaluating BCI-based interventions for stroke survivors at acute, subacute, and chronic phases. Key findings reveal that BCI interventions, especially when combined with conventional therapy modalities such as functional electrical stimulation and visual feedback, result in significantly greater improvements in upper and lower limb motor function versus standard care. BCI approaches also show additional benefits in enhancing attention, cognitive performance, and daily activity independence. Mechanistically, BCI systems strengthen neural connectivity and modulate cortical activation through closed-loop feedback, supporting both local and network-level brain reorganization. Despite promising results, further research is required to standardize protocols, identify ideal patient profiles, and assess long-term outcomes. Overall, BCI is an effective adjunct for neurorehabilitation, particularly for patients with severe motor deficits or limited voluntary movement, with potential to transform stroke recovery paradigms

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ANT: Attention Network Test; ARAT: Action Research Arm Test; BBS: Berg Balance Scale; BCI: Brain-Computer Interface; cFMA: combined Fugl-Meyer Assessment; EMG: Electromyography; FES: Functional Electrical Stimulation; FMA-LE: Fugl-Meyer Assessment Lower Extremity; FMA-UE: Fugl-Meyer Assessment Upper Extremity; fMRI: functional Magnetic Resonance Imaging; GAS: Goal Attainment Scale; HAM-D: Hamilton Depression Scale; LC: Laterality Coefficient; LI: Laterality Index; MAAS: Mindful Attention Awarene

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Web-Based No-Code Website Builder (NCWB) platforms aim to democratize web development by enabling users with minimal or no programming experience to design and deploy responsive websites. Leveraging intuitive drag-and-drop interfaces, these platforms integrate pre-built modular components--such as text fields, images, navigation bars, and multimedia elements--to streamline the design process and eliminate the need for manual coding. The review paper emphasizes accessibility, usability, and flexibility, providing real-time visual customization and responsive design capabilities. By adopting a no-code approach, the framework significantly reduces development time and cost while enhancing creative freedom for individuals, startups, and small enterprises. The study highlights the potential of no-code platforms in fostering digital inclusivity, empowering non-technical users to establish an effective online presence, and promoting innovation in modern web development practices.

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No-Code Development, Drag-and-Drop Interface, Website Builder, Web Design Automation.

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The Surrogacy (Regulation) Act, 2021 and associated regulations have closely regulated surrogacy in India, which has undergone a swift and controversial transformation from an emerging sector meeting domestic and international demand. Critics contend that although the law protects vulnerable women and children, it may be overcorrected by restricting reproductive autonomy and driving practices underground . Policymakers primarily justified the legislative change as a response to exploitation, the commodification of reproductive labour, and unethical practices at clinics. In order to balance the protection of vulnerable populations with reproductive autonomy and the best interests of children, this paper traces the historical development of surrogacy in India, examines the current legislative framework and implementation mechanisms, assesses significant ethical, social, and human rights concerns, reviews judicial responses, and suggests workable reforms. In order to create an integrated legal-ethical assessment with policy recommendations, the study draws on legislative texts, governmental regulations and announcements, significant court rulings, academic criticisms, and current reporting.

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surrogacy, Surrogacy (Regulation) Act 2021, altruistic surrogacy, reproductive rights, commodification, exploitation, child's rights, surrogate mother, assisted reproductive technology.

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The advent of generative Artificial Intelligence (AI) has initiated a profound paradigm shift in higher education. This study investigates student perspectives on these transformative tools, analyzing their adoption, application, and perceived impact on traditional learning processes. This research employed a quantitative, cross-sectional survey design, collecting 56 responses from students at Mumbai University to capture their perceptions and self-reported behaviors. The methodology involved descriptive statistical analysis and an inferential Chi-square test to explore associations between academic disciplines and AI usage frequency. Key findings indicate a high rate of AI adoption, with 62.5% of students using these tools at least "several times a week." Students primarily use AI for cognitive augmentation, such as 'Explaining complex concepts' (60.7%), rather than simple task automation. The data reveals a significant "Efficiency-Integrity Paradox": while students overwhelmingly agree that AI enhances learning efficiency ($M = 4.30$ on a 5-point scale), they simultaneously express high agreement with 'worry' that over-reliance 'might weaken critical thinking skills' ($M = 3.95$). Furthermore, the adoption of AI is measurably altering traditional study habits, with 30.4% of students reporting a decrease in consultations with professors. This trend is occurring within a significant "guidance vacuum," as 55.4% of students report their university has provided "No, there are no guidelines" for AI use. These findings culminate in an urgent call for Mumbai University to develop clear, co-designed AI policies and integrate mandatory ethical AI literacy into the curriculum to navigate the complex challenges and opportunities of this new academic era.

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Generative AI, Higher Education, Student Perspectives, Academic Integrity, Pedagogy , Artificial Intelligence, Educational Technology , ChatGPT , AI Literacy ,Student Ethics

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The global issue of Carbon dioxide emission has become a headache for the whole world, and therefore techniques like Carbon Capture Utilization and Sequestration (CCUS), Carbon Capture Utilization (CCU), and Carbon Capture Sequestration (CCS) are getting high attention. This paper deals with the Utilization of CO2 to produce methanol in electro-catalytic ways due to the high availability of methanol in the field of chemicals & fuels. A process flow sheet regarding the process of converting Carbon dioxide to methanol has been mentioned. Today, methanol is predominantly produced from natural gas by reforming the gas with steam and then converting and distilling the resulting synthesized gas mixture to create pure methanol instead if we produce methanol from CO2 this process is economically feasible and detailed economics regarding the production of methanol from CO2 has been mentioned.

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Carbon Capture Utilization (CCU),Carbon Capture Utilization and Sequestration (CCUS),

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The frequency and severity of climate-related disasters like wildfires and floods are rising, endangering infrastructure, the environment, and human lives. Conventional emergency response and forecasting systems frequently lack flexibility, real-time intelligence, and the capacity to pick up on changing environmental patterns. The Cognitive Artificial Intelligence (AI) Framework presented in this research is intended to improve emergency response operations coordination and hazard forecasting accuracy. The suggested framework uses a hybrid architecture that combines deep learning and cognitive reasoning to integrate diverse data sources, such as satellite images, meteorological datasets, geographical information systems (GIS), and historical disaster records. The cognitive layer improves prediction accuracy and facilitates independent decision-making in catastrophe management by utilising contextual comprehension, pattern recognition, and reinforcement learning. When compared to traditional AI-based hazard models, experimental evaluations show that the suggested method greatly increases prediction accuracy and reaction efficiency. Additionally, explainable AI is supported by an adaptive knowledge graph, which guarantees the system's decision-making processes are transparent and dependable. The study demonstrates how cognitive AI's self-learning, adaptable, and intelligent reaction mechanisms have the potential to completely transform disaster predictions and management.

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Cognitive AI, Flood Forecasting, Fire Hazard Prediction, Disaster Response, Deep Learning, IoT, Knowledge Graph, Climate Resilience.

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In any democratic country, voting is a fundamental right of any citizen that enables them to Choose the leaders of tomorrow. The trend of electronic voting has risen in recent years as an alternative to paper ballot elections, bringing meaningful benefits in terms of efficiency and error proneness. However, real-world applications have demonstrated significant vulnerabilities and susceptibility to software errors that could be exploited by malicious entities. In fact, the difficult challenge of electronic voting lies in the need to incorporate multiple, often contradictory, properties into the system design. As a digital platform, they eliminate the need to cast your votes using paper or having to gather in person. They also protect the integrity of your vote by preventing voters from being able to vote multiple times. Electronic voting, or e-voting, has fundamental benefits over paper-based systems, such as increased efficiency and reduced errors. The electronic voting system tends to maximize user participation by allowing them to vote from anywhere and from any device that has an internet connection. The blockchain is an emerging, decentralized, and distributed technology with strong cryptographic foundations that promises to improve different aspects of many industries. Expanding e-voting into blockchain technology could be the solution to alleviate the present concerns in e-voting. Here we propose a blockchain-based voting system that will limit the voting fraud and make the voting process simple, secure, and efficient.

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Blockchain, E-voting, Electronic Voting, Security Attacks, Cryptographic Vulnerabilities, Smart Contracts, Voter Privacy.

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This study examines the comparative preferences of investors towards Gold Exchange Traded Funds (ETFs) and physical gold in the Thrissur District. With the advent of digitization and financial innovations, gold ETFs have emerged as an attractive investment option, offering liquidity, transparency, and cost-efficiency. However, cultural and emotional values continue to influence the preference for physical gold. Using a structured questionnaire, data were collected from 100 investors. Descriptive statistics and the Chi-square test were applied to analyze the relationship between demographic variables and investment preferences. The results show a significant relationship between age, income, education, and the form of gold investment preferred. Younger investors tend to favor gold ETFs, while older investors remain inclined towards physical gold. The findings suggest a gradual shift in gold investment behavior among Indian investors.

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Gold ETF, Physical Gold, Investment Behaviour, Chi-square Analysis, Investor Preference

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