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This paper develops a simple model of the world supply chain to estimate the effects of sanctions that restrict the flow of inputs from one country to another. Such restrictions operate through changes in the weights of the global production network: the sanctioning country ceases supplying certain inputs to the target country and reallocates its production to other destinations. Using the OECD Inter-Country Input--Output tables, we calibrate the model to assess the vulnerability of the Indian economy. We consider two classes of counterfactuals: restrictions on a single sector of a foreign country supplying India, and restrictions on all sectors of a foreign country supplying India. We then rank foreign countries and foreign country-sectors by the risk that their supply restrictions pose to economic activity in India. Our results show that India's greatest country-level vulnerability is to China, followed by the United Arab Emirates, the United States, Saudi Arabi and Russia, with the vulnerability to China being twice as much that to the UAE.

Purpose: India has adopted a vertical, sector-led AI governance strategy. While promoting innovation, such a light-touch approach risks policy fragmentation. This paper aims to propose a cohesive "whole-of-government" architecture to mitigate these risks and connect policy goals with a practical implementation plan. Design/methodology/approach: The paper applies an established five-layer conceptual framework to the Indian context. First, it constructs a national architecture for overall governance. Second, it uses a detailed case study on AI incident management to validate and demonstrate the architecture's practical utility in designing a specific, operational system. Findings: The paper develops two actionable architectures. The primary model assigns clear governance roles to India's key institutions. The second is a detailed, federated architecture for national AI Incident Management. It addresses the data silo problem by using a common national standard that allows sector-specific data collection while facilitating cross-sectoral analysis. Practical implications: The proposed architectures offer a clear and predictable roadmap for India's policymakers, regulators and industry t

India's urbanization is often characterized as particularly challenging and very unequal but systematic empirical analyses, comparable to other nations, have largely been lacking. Here, we characterize India's economic and human development along with changes in its personal income distribution as a function of the nation's growing urbanization. On aggregate, we find that India outperforms most other nations in the growth of various indicators of development with urbanization, including income and human development. These results are due in part to India's present low levels of urbanization but also demonstrate the transformational role of its cities in driving multi-dimensional development. To test these changes at the more local level, we study the income distributions of large Indian cities to find evidence for high positive growth in the lowest decile (poorest) of the population, enabling sharp reductions in poverty over time. We also test the hypothesis that inequality-reducing cities are more attractive destinations for rural migrants. Finally, we use income distributions to characterize changes in poverty rates directly. This shows much lower levels of poverty in urban India

India's tea business has a long history and plays a significant role in the economics of the nation. India is the world's second-largest producer of tea, with Assam and Darjeeling being the most well-known tea-growing regions. Since the British introduced tea cultivation to India in the 1820s, the nation has produced tea. Millions of people are employed in the tea sector today, and it contributes significantly to the Indian economy in terms of revenue. The production of tea has changed significantly in India over the years, moving more and more towards organic and sustainable practices. The industry has also had to deal with difficulties like competition from other nations that produce tea, varying tea prices, and labor-related problems. Despite these obstacles, the Indian tea business is still growing and produces a wide variety of teas, such as black tea, green tea, and chai tea. Additionally, the sector encourages travel through "tea tourism," which allows tourists to see how tea is made and discover its origins in India. Overall, India's tea business continues to play a significant role in its history, culture, and economy.

Understanding how users authentically interact with Large Language Models (LLMs) remains a significant challenge in human-computer interaction research. Most existing studies rely on self-reported usage patterns or controlled experimental conditions, potentially missing genuine behavioral adaptations. This study presents a behavioral analysis of the use of English-speaking urban professional ChatGPT in India based on 238 authentic, unedited user prompts from 40 participants in 15+ Indian cities, collected using retrospective survey methodology in August 2025. Using authentic retrospective prompt collection via anonymous social media survey to minimize real-time observer effects, we analyzed genuine usage patterns. Key findings include: (1) 85\% daily usage rate (34/40 users) indicating mature adoption beyond experimental use, (2) evidence of cross-domain integration spanning professional, personal, health and creative contexts among the majority of users, (3) 42.5\% (17/40) primarily use ChatGPT for professional workflows with evidence of real-time problem solving integration, and (4) cultural context navigation strategies with users incorporating Indian cultural specifications in

As the two largest emerging emitters with the highest growth in operational carbon from residential buildings, the historical emission patterns and decarbonization efforts of China and India warrant further exploration. This study aims to be the first to present a carbon intensity model considering end-use performances, assessing the operational decarbonization progress of residential building in India and China over the past two decades using the improved decomposing structural decomposition approach. Results indicate (1) the overall operational carbon intensity increased by 1.4% and 2.5% in China and India, respectively, between 2000 and 2020. Household expenditure-related energy intensity and emission factors were crucial in decarbonizing residential buildings. (2) Building electrification played a significant role in decarbonizing space cooling (-87.7 in China and -130.2 kilograms of carbon dioxide (kgCO2) per household in India) and appliances (-169.7 in China and -43.4 kgCO2 per household in India). (3) China and India collectively decarbonized 1498.3 and 399.7 mega-tons of CO2 in residential building operations, respectively. In terms of decarbonization intensity, India (164

The integration of artificial intelligence (AI) into telecommunications infrastructure introduces novel risks, such as algorithmic bias and unpredictable system behavior, that fall outside the scope of traditional cybersecurity and data protection frameworks. This paper introduces a precise definition and a detailed typology of telecommunications AI incidents, establishing them as a distinct category of risk that extends beyond conventional cybersecurity and data protection breaches. It argues for their recognition as a distinct regulatory concern. Using India as a case study for jurisdictions that lack a horizontal AI law, the paper analyzes the country's key digital regulations. The analysis reveals that India's existing legal instruments, including the Telecommunications Act, 2023, the CERT-In Rules, and the Digital Personal Data Protection Act, 2023, focus on cybersecurity and data breaches, creating a significant regulatory gap for AI-specific operational incidents, such as performance degradation and algorithmic bias. The paper also examines structural barriers to disclosure and the limitations of existing AI incident repositories. Based on these findings, the paper proposes

India is the second-highest contributor to the post-2000 global greening. With satellite data, here we show that this 18.51% increase in Leaf Area Index (LAI) during 2001-2019 fails to translate into increased carbon uptake due to warming constraints. Our analysis further shows 6.19% decrease in Net Primary Productivity (NPP) during 2001-2019 over the temporally consistent forests in India despite 6.75% increase in LAI. We identify hotspots of statistically significant decreasing trends in NPP over the key forested regions of Northeast India, Peninsular India, and the Western Ghats. Together, these areas contribute to 31% of the NPP of India (1274.8 TgC.year -1). These regions are the warming hotspots in India. Decreasing photosynthesis and stable respiration, above a threshold temperature, are the key reasons behind the declining NPP. Warming has already started affecting carbon uptake in Indian forests and calls for improved climate resilient forest management practices in a warming world.

India is now among the major knowledge producers of the world, ranking among the top 5 countries in total research output, as per some recent reports. The institutional setup for Research & Development (R&D) in India comprises a diverse set of Institutions, including Universities, government departments, research laboratories, and private sector institutions etc. It may be noted that more than 45% share of India's Gross Expenditure on Research and Development (GERD) comes from the central government. In this context, this article attempts to explore the quantum of research contribution of centrally funded institutions and institution systems of India. The volume, proportionate share and growth patterns of research publications from the major centrally funded institutions, organised in 16 groups, is analysed. These institutions taken together account for 67.54% of Indian research output during 2001 to 2020. The research output of the centrally funded institutions in India has increased steadily since 2001 with a good value for CAGR. The paper presents noteworthy insights about scientific research production of India that may be useful to policymakers, researchers and science

We summarize the motivation for (as well as the presentations from) the April, 2024 workshop held in India and focused on radiowave techniques for cosmic ray and neutrino detection.

India is the largest democracy in the world and has recently surpassed China to be the highest-populated country, with an estimated 1.425 billion (approximately 18% of the world population). Moreover, India's elderly population is projected to increase to 138 million by 2035. Indian economy is already reeling under the pressure of exorbitant pension liabilities of the government for existing pensioners. As such, India has introduced a National Pension System (NPS), which is a Defined Contribution Scheme for employees joining government service on or after 1st January 2004, bidding adieu to the age-old, tried and tested Old Pension System (OPS) which is a Direct Benefit Scheme, in vogue in India since the British Raj. This is an epoch-making move by the government as it seeks to inculcate Disciplined Saving among the people while significantly reducing the government burden by reducing the Pension Liabilities of the Central and State Governments. This paper aims to analyse various features and intricacies of the NPS and address the claims of various stakeholders like the Central Government, State Government, Employees, Pensioners, etc. In light of the above, and taking cognisance of

In this report, we summarize the integrated multilingual audio processing pipeline developed by our team for the inaugural NCIIPC Startup India AI GRAND CHALLENGE, addressing Problem Statement 06: Language-Agnostic Speaker Identification and Diarisation, and subsequent Transcription and Translation System. Our primary focus was on advancing speaker diarization, a critical component for multilingual and code-mixed scenarios. The main intent of this work was to study the real-world applicability of our in-house speaker diarization (SD) systems. To this end, we investigated a robust voice activity detection (VAD) technique and fine-tuned speaker embedding models for improved speaker identification in low-resource settings. We leveraged our own recently proposed multi-kernel consensus spectral clustering framework, which substantially improved the diarization performance across all recordings in the training corpus provided by the organizers. Complementary modules for speaker and language identification, automatic speech recognition (ASR), and neural machine translation were integrated in the pipeline. Post-processing refinements further improved system robustness.

Recently, Indian Finance minister Nirmala Sitharaman announced in Union budget 2022-23 that Indian government will put 30% tax (the highest tax slab in India) on income generated from cryptocurrencies. Big financial institutions, experts and academicians have different opinions in this regard. They claim that it would be the end of cryptocurrency market in India or it would be possible that RBI (Reserve Bank of India) may launch its own crypto or digital currency. So in this context, in this article, the journey and future aspects of cryptocurrency in India are discussed and we hope that it will be a reference for further research and discussion in this area.

Initiatives by the IndIGO (Indian Initiative in Gravitational Wave Observations) Consortium during the past three years have materialized into concrete plans and project opportunities for instrumentation and research based on advanced interferometer detectors . With the LIGO-India opportunity, this initiative has a taken a promising path towards significant participation in gravitational wave (GW) astronomy and research, and in developing and nurturing precision fabrication and measurement technologies in India. The proposed LIGO-India detector will foster integrated development of frontier GW research in India and will provide opportunity for substantial contributions to global GW research and astronomy. Widespread interest and enthusiasm about these developments in premier research and educational institutions in India lead to the expectation that there will be a grand surge of activity in precision metrology, instrumentation, data handling and computation etc. in the context of LIGO-India. I discuss the scope of such research in the backdrop of the IndIGO action plan and the LIGO-India project.

Recent research has revealed undesirable biases in NLP data and models. However, these efforts focus on social disparities in West, and are not directly portable to other geo-cultural contexts. In this paper, we focus on NLP fair-ness in the context of India. We start with a brief account of the prominent axes of social disparities in India. We build resources for fairness evaluation in the Indian context and use them to demonstrate prediction biases along some of the axes. We then delve deeper into social stereotypes for Region andReligion, demonstrating its prevalence in corpora and models. Finally, we outline a holistic research agenda to re-contextualize NLP fairness research for the Indian context, ac-counting for Indian societal context, bridging technological gaps in NLP capabilities and re-sources, and adapting to Indian cultural values. While we focus on India, this framework can be generalized to other geo-cultural contexts.

Robotic technology has the potential to revolutionize the field of neurology by providing new methods for diagnosis, treatment, and rehabilitation of neurological disorders. In recent years, there has been an increasing interest in the development of robotics applications for neurology, driven by advances in sensing, actuation, and control systems. This review paper provides a comprehensive overview of the recent advancements in robotics technology for neurology, with a focus on three main areas: diagnosis, treatment, and rehabilitation. In the area of diagnosis, robotics has been used for developing new imaging techniques and tools for more accurate and non-invasive mapping of brain structures and functions. For treatment, robotics has been used for developing minimally invasive surgical procedures, including stereotactic and endoscopic approaches, as well as for the delivery of therapeutic agents to specific targets in the brain. In rehabilitation, robotics has been used for developing assistive devices and platforms for motor and cognitive training of patients with neurological disorders. The paper also discusses the challenges and limitations of current robotics technology for

Wind power generated by wind has non-schedule nature due to stochastic nature of meteorological variable. Hence energy business and control of wind power generation requires prediction of wind speed (WS) from few seconds to different time steps in advance. To deal with prediction shortcomings, various WS prediction methods have been used. Predictive data mining offers variety of methods for WS predictions where artificial neural network (ANN) is one of the reliable and accurate methods. It is observed from the result of this study that ANN gives better accuracy in comparison conventional model. The accuracy of WS prediction models is found to be dependent on input parameters and architecture type algorithms utilized. So the selection of most relevant input parameters is important research area in WS predicton field. The objective of the paper is twofold: first extensive review of ANN for wind power and WS prediction is carried out. Discussion and analysis of feature selection using Relief Algorithm (RA) in WS prediction are considered for different Indian sites. RA identify atmospheric pressure, solar radiation and relative humidity are relevant input variables. Based on relevant i

We have studied the context and development of the ideas of physical forces and differential calculus in ancient India by studying relevant literature related to both astrology and astronomy since pre-Greek periods. The concept of Naisargika Bala (natural force) discussed in Hora texts from India is defined to be proportional to planetary size and inversely related to planetary distance. This idea developed several centuries prior to Isaac Newton resembles fundamental physical forces in nature especially gravity. We show that the studies on retrograde motion and Chesta Bala of planets like Mars in the context of astrology lead to development of differential calculus and planetary dynamics in ancient India. The idea of instantaneous velocity was first developed during the 1st millennium BC and Indians could solve first order differential equations as early as 6th cent AD. Indian contributions to astrophysics and calculus during European dark ages can be considered as a land mark in the pre-renaissance history of physical sciences. Key words: physical forces, differential calculus, history of science, planetary dynamics, ancient India

Background: The ongoing COVID-19 epidemic dilated rapidly throughout India. To end the global COVID-19 pandemic major behavioral, social distancing, contact tracing, and state interventions has been undertaken to reduce the outbreak and avert the persistence of the coronavirus in humans in India and worldwide. In absence of any vaccine or therapeutics, forecasting is of utmost priority for health care planning and control the transmission of COVID-19. Methods: We have proposed a mathematical model that explain the transmission dynamics of COVID-19 in India. Based on the estimated data our model predicts the evolution of epidemics and the end of SARS-CoV-2 and aids to evaluate the influence of different policies to control the spread of the diseases. Findings: With the real data for infected individuals, we find the basic reproduction number $R_0$ for 17 states of India and overall India. A complete figure is given to demonstrate the estimated pandemic life cycle along with the real data or history to date. Our study reveals that the strict control measures implemented in India substantially mitigated the disseminate of SARS-CoV-2. Importantly, model simulations predict that 95% red