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Geopolitical Risk, Variability of Oil Price, and the Global Trade Uncertainty: An Economic Perspective
Oil prices are the outcome of a highly integrated, dynamic global system. With geopolitical risk and trade policy uncertainty contribute to the volatile world markets, the study analyses the impact of geopolitical risk, trade policy uncertainty on crude oil price globally. It considers data from 2000 to 2023 and finds out systematic link between the three variables. The data proved a long run impact of trade policy uncertainty and geopolitical risk on the crude oil. This enhances the influence of the variables and leads to implementation of policy measures in global markets. The data are tested through Auto Regressive Distributed Lag (ARDL) model and checked for long run cointegration and short run association. The policy, thus, has been suggested as to improve the transition towards sustainability globally. Though the impact of geopolitical risk and trade policy uncertainty is not strong on crude oil price in world market, it can affect the short run volatility. Thus, mitigation, diversification and transparency are the key factors to strengthen the existing situation in world. 2026, IGI Global Scientific Publishing. All rights reserved. -
Geopolitical shockwaves: the Russia-Ukraine wars impact on BRICS financial markets
The Russia-Ukraine War triggered global financial market turmoil and disrupted the global supply chain, including agriculture and energy. This study explores the impact of the Russia-Ukraine war on BRICS nations stock markets, highlighting varying degrees of volatility and contagion effects. It examines the extent of contagion in the BRICS stock markets and their financial linkages by employing the multivariate DCC-GARCH model. The study reveals sensitive turbulence in Russian markets post-crisis, influenced by its direct involvement in the conflict. Brazil and China experienced higher market volatility after the event, and Brazil shifted its financial linkages with the global market. Conversely, the Indian market experienced eased overall volatility, but its financial linkage with Russia has increased due to its trade partnership. In the post-event period, China and South African markets indicate structural market decoupling. The long-term volatility persists over the short-term volatility of BRICS market dynamics. This study underscores the implications for investors and policymakers, emphasising the need for adjustments in monetary and fiscal policies to stabilise financial markets amid geopolitical uncertainties. 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Geopolymer concrete paving blocks made with Recycled Asphalt Pavement (RAP) aggregates towards sustainable urban mobility development
Policy makers in India have realized the importance of facility for pedestrians and non- motorized vehicles in an urban infrastructure setup. This has resulted in increased utilization of construction materials like Portland cement and crushed stone, which are not environmentally friendly and sustainable. The current study presents the development of paver blocks for pedestrian facility using different wastes. Geopolymer concrete was synthesized by fly ash and recycled asphalt pavement aggregates for making of paver blocks. Paver blocks were produced in laboratory with recycled asphalt pavement aggregate replacement levels of 0%, 20%, 40%, 60% and 80% by weight of virgin coarse and fine aggregates. The developed paver blocks were tested for dimensions and tolerances, water absorption, compressive strength and abrasion resistance as per IS15658:2006 standard. The results of the laboratory study show that recycled asphalt pavement aggregates can be introduced into geopolymer matrix to produce paver blocks of desirable quality. Furthermore, its use in pedestrian facilities provides a new avenue for managing the excessive waste, which otherwise goes in landfills, incurring loss to the paving industry. Therefore, the proposed method can help decision makers to effectively utilize recycled asphalt pavement in paving industry with environment-friendly approach. 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Geospatial Analysis of Groundwater Recharge Zones in Bengaluru
Urban flooding in cities like Bengaluru results from excessive rainfall overwhelming drainage systems, worsened by rapid urbanisation and the expansion of impervious surfaces. This study investigates the causes and consequences of urban flooding in Bengaluru, highlighting the decline in natural drainage and the encroachment of water bodies. Using QGIS, a geographic information system tool, spatial data from sources like NRSCs Bhuvan portal and USGS were analysed to identify flood-prone areas, drainage networks, and land use changes. The analysis revealed critical flooding zones such as Bellandur, Bommanahalli, and Mahadevapura. The study also emphasises the importance of implementing Best Management Practices (BMPs) and Rainwater Harvesting (RWH) strategies. Land Use and Land Cover (LULC) mapping, soil infiltration data, and rainfall patterns were assessed to understand urban hydrology. The findings stress the need for climate-resilient infrastructure, lake rejuvenation, and improved public awareness to mitigate future urban flood risks in Bengaluru. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Geospatial crime analysis and forecasting with machine learning techniques
People use social media to engage, connect, and exchange ideas, for professional interests, and for sharing images, videos, and other contents. According to the investigation, social media allows researchers to examine individual behavior features and geographic and temporal interactions. According to studies, criminology has become a prominent subject of study globally, using data gathered from online social media sites such as Facebook, News feed articles, Twitter, and other sources. It is possible to obtain useful information for the analysis of criminal activity by using spatiotemporal linkages in user-generated content. The study refers to the application of text-based data science by gathering data from several news sources and visualizing it. This research is motivated by the abovementioned work from various social media crimes and government crime statistics. This chapter looks at 68 various crime keywords to help you figure out what kind of crime you are dealing with concerning geographical and temporal data. For categorizing crime into subgroups of categories with geographical and time aspects using news feeds, the Naive Bayes classification algorithm is used. For retrieving keywords from news feeds, the Mallet package is used. The hotspots in crime hotspots are identified using the K-means method. The KDE approach is utilized to address crime density and this methodology has solved the difficulties that the current KDE algorithm has. The study results demonstrated equivalence between the suggested crimes forecasting model as well as the ARIMA model. 2022 Elsevier Inc. All rights reserved. -
Geospatial crime analysis to determine crime density using kernel density estimation for the indian context
Crime is the most common social problem faced in a developing country. Crime affects the reputation of a nation and the quality of life of its citizens. Crime also affects the economy of the country, increasing the financial burden of the government due to the need for expenditure in the police force and judicial system. Various initiatives are taken by law enforcement to reduce the crime rate. One such initiative, real-time accurate crime predictions can help reduce the occurrence of crime. In this paper, a crime analytics platform is developed, which processes newsfeed data analysis for different types of crimes and identify crime hotspots using Kernel Density Estimation method. This system enables criminologists to understand the hidden relationships between crime and geographical locations. Interactive visualization features are available that enable law enforcement agencies to predict crime. 2020 American Scientific Publishers. -
Geraniol and Citral as potential therapeutic agents targeting the HSP90 activity: An in silico and experimental approach
Lemongrass essential oil has antifungal and anti-cancerous properties. Heat-shock protein (HSP90), an ATP-dependent molecular chaperone found in eukaryotes, is involved in protein folding, stability, and disease, making it a promising research topic. Both in silico and in vitro approaches were used to provide a clear insight into the HSP90-ATPase 3D structures, activity, and their interaction with the essential oil constituents among various species such as fungi (S. cerevisiae), parasites (P. falciparum), and humans. For in silico studies, sequence alignment, docking (AutoDock), and absorption, distribution, metabolism, and excretion (ADME) properties were evaluated to obtain hit compounds specifically against each HSP90-ATPase. The hit compounds obtained were evaluated for their efficacy in the in vitro studies of S. cerevisiae. In vitro studies were carried out targeting HSP90-ATPases via lemongrass essential oil components individually and in combination as a function of concentration and various salt concentrations. Results suggest that sequence alignment exists of over 75% among these three species. The best docking score was possessed by Geraniol and its constituent (geldanamycin ? ?4.93 kcal/mol) (a known antifungal and antitumor against HSP90) in all the above species. Lemongrass oil and the combination of Geraniol and Citral at concentrations of 80 ?g/mL showed the maximum inhibition of ATPase and HSP90-ATPase activity compared to their individual treatment. Therefore, both in silico and in vitro studies provide clear evidence of specific inhibitory action of lemongrass oil, Geraniol, and Citral against the ATPase and HSP90ATPase activities and might show potential as antifungal and antitumor drugs. 2021 -
Gestational diabetes prediction using hybrid probabilistic machine learning models
[No abstract available] -
Gesture based Real-Time Sign Language Recognition System
Real-Time Sign Language Recognition (RTSLG) can help people express clearer thoughts, speak in shorter sentences, and be more expressive to use declarative language. Hand gestures provide a wealth of information that persons with disabilities can use to communicate in a fundamental way and to complement communication for others. Since the hand gesture information is based on movement sequences, accurately detecting hand gestures in real-time is difficult. Hearing-impaired persons have difficulty interacting with others, resulting in a communication gap. The only way for them to communicate their ideas and feelings is to use hand signals, which are not understood by many people. As a result, in recent days, the hand gesture detection system has gained prominence. In this paper, the proposed design is of a deep learning model using Python, TensorFlow, OpenCV and Histogram Equalization that can be accessed from the web browser. The proposed RTSLG system uses image detection, computer vision, and neural network methodologies i.e. Convolution Neural Network to recognise the characteristics of the hand in video filmed by a web camera. To enhance the details of the images, an image processing technique called Histogram Equalization is performed. The accuracy obtained by the proposed system is 87.8%. Once the gesture is recognized and text output is displayed, the proposed RTSLG system makes use of gTTS (Google Text-to-Speech) library in order to convert the displayed text to audio for assisting the communication of speech and hearing-impaired person. 2022 IEEE. -
Getting Back to Work: Cognitive-Communicative Predictors for Work Re-entry Following Traumatic Brain Injury
Return to work following a Traumatic Brain Injury (TBI) is affected by deficits across the cognitive, psycho-social and physical domains. The specific role of cognitive -communicative abilities influencing work re-entry is understudied. This study aimed at identifying the cognitive-communicative predictors for work re-entry following TBI. Thirty patients with TBI employed pre morbidly were categorized into two groups- 14 employed and 16 unemployed post TBI. Those having sustained mild, moderate or severe head injury and in the post injury period of 648months were recruited and majority belonged to skilled/ professional type of premorbid occupational status. They underwent a detailed assessment of cognition, language and communication using NIMHANS Neuropsychology Battery, Indian adapted versions of Western Aphasia Battery and La Trobe Communication Questionnaire (LCQ) respectively. Patients employed post TBI had better Aphasia Quotient (AQ) and better performance on all the cognitive domains and few domains of LCQ than those who remained unemployed. On step-wise Discriminant Function Analysis (DFA), injury severity and AQ could significantly differentiate between the two groups with an overall accuracy of 80%. Severity of head injury is a significant predictor for employability post TBI and evaluation of language along with cognitive abilities is crucial for patients with TBI for work re-entry. The study highlights the importance of a multi-disciplinary team in the assessment and management of cognitive-communication impairments following a TBI. 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Getting Rid of Organizational Complacency in a Dynamic Environment
This case investigates the external consultants organizational diagnosis aimed at understanding the imperative for change within Infotics Solutions. It explores various concepts, including the nature of planned change and the resistance exhibited by employees. Emphasis is placed on the necessity of a comprehensive organizational diagnosis before embarking on the change process, highlighting the pitfalls of relying solely on a leaders intuition and experience to initiate change. Furthermore, the case underlines the implementation of human resource management interventions and their significance from both employee and organizational standpoints. It addresses the protagonists recognition of the need for external consultants expertise to grasp the problem and devise a strategic change process. The consultants methodical approach to planning change across different themes to achieve organizational objectives is elucidated, featuring the importance of employing the right diagnosis technique in situations where the problem is unclear. The case also showcases the consultants analytical approach to problem-solving, offering specific solutions tailored to the organizations needs. Ultimately, it illustrates the challenges faced by organizations that lean heavily on past successes and struggle to adapt to evolving environmental demands. Lastly, the case highlights the importance of analysing survey results and implementing theme-based interventions to address the issues confronting the organization and its employees at Infotics Solutions. 2024 Lahore University of Management Sciences. -
Ghost Kitchens Transforming the Culinary Landscape and Shaping the Future of Food Delivery
It presents an important shift in the food service industry, most of which was accelerated during the COVID-19 pandemic: ghost kitchens, or virtual or cloud kitchens. This research discusses the operational mechanisms, workforce consequences, and consumer attitudes toward ghost kitchens, which operate strictly for delivery purposes without having a traditional dining area, as well as the literature used between the years 2007 to 2024. The labor standards and compliance, as most ghost kitchens are built upon gig economy workers who toil in challenging circumstances. Additionally, the study examines consumer perception of this new phenomenon of dining and its potential for transforming culinary careers. Its findings indicate that while ghost kitchens open avenues for creativity in culinary arts and expansion of the marketplace, it simultaneously necessitates a readjustment in labor norms and consumer awareness. Given the anticipated high growth rate for the ghost kitchen market in the next years, it is significant that food service sector stakeholders grasp these dynamics. 2025 by IGI Global Scientific Publishing. All rights reserved. -
GLANCEGuided Language Through Autoregression Establishing Natural and Classifier-Free Editing
In this study, researchers aimed to simplify text conversion into images using the latest text-to-image generation methods. While these methods have improved the quality and relevance of generated images, certain crucial questions remained unanswered, limiting their practicality and overall quality. To address these issues, the researchers introduced a novel text-to-image method. This method allows for better control of the scene depicted in the image through text, enhances the tokenization process by incorporating specific knowledge about key image regions such as faces and important objects, and provides guidance to the transformer model without needing a classifier. The outcome of this work was a model that achieved state-of-the-art results in terms of image quality and human evaluation, enabling the generation of high-fidelity 512?512-pixel images. Moreover, this method introduced new capabilities, including scene editing, text editing with reference scenes, handling out-of-distribution text prompts, and generating story illustrations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Glancing angle sputter deposited tungsten trioxide (WO3) thin films for electrochromic applications
The columnar growth angle-dependent tungsten oxide (WO3) thin films were grown by using the Glancing angle sputter deposition (GLAD) technique with varying different substrate angles (00, 700, 750, and 800) on Fluorine-doped tin oxide (FTO) and Corning glass (CG) corning glass substrates at room temperature. The surface morphology, crystallographic structure, optical, and electrochemical properties were determined using X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), UltravioletVisible(UVVis) spectrometer, and electrochemical analyzer, respectively. The structural properties reveal that the films are amorphous in nature. FE-SEM studies observed the columnar growth of the nano-rods and surface porosity. The optical transmittance of the deposited films was decreased from 83 to 78%, and the optical bandgap decreased from 3.08 to 2.88eV with increasing GLAD angle. The electrochemical studies reveal that the GLAD angle influenced the coloration efficiency (CE). The highest CE of 32cm2/C at 600nm and highest Diffusion coefficient (DC) of 6.529 109 cm2s?1 of the films was observed for the films deposited at an angle of 750. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature. -
Global Analysis of Quantum Technology Discourse
he study provides a thorough exploration of the global quantum technology landscape, offering valuable insights for researchers, policymakers, and industry stakeholders. It employs advanced analytical methods such as Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF) for topic modeling. The research focuses on understanding discussion intensity, geographical distribution, co-mentioning patterns among countries, prevalent topics, and keyword-based trends. Utilizing diverse datasets, the study employs heatmaps, network analysis, and thematic analysis to categorize textual data. Evaluation metrics like Topic Coherence and Network Centrality Measures contribute to a robust methodology.Key findings include dominant discussions on quantum computing and investment strategies, with focused attention on governmental roles in R&D and specific quantum computer research. Notably, there is a niche focus on quantum algorithmic risks in Australia. Document characteristics vary, with some blending multiple themes and others centered around a single topic. LDA topic modeling and network analysis identify key countries, showcasing global hotspots and potential collaborations in quantum technology discussions. 2024 IEEE. -
Global and Indian Perspectives on Russia-Ukraine War using Sentiment Analysis
In today's world, social media has become a platform through which people express their opinions and thoughts regarding various topics. Twitter is one such platform wherein people resort to expressing their opinions or portraying sentiments to the world. Today it has become easier to analyze mass opinion by using sentiment analysis. This paper investigates the ongoing Russia-Ukraine war by analyzing opinionated tweets, and it seeks to understand the sentiments from a global and Indian perspective. Operation Ganga was carried out to evacuate Indian citizens from the war-hit region. Multinomial Naive Bayes classifier classified the tweets into positive, neutral, and negative categories. The paper employed NRCLex for emotion classification and aspect-based sentiment analysis to divide opinions into aspects and determine the sentiment associated with each element. For the study, 4,31,857 tweets were extracted, and the results of sentiment analysis depict that 44.09% users had negative sentiments followed by 33.378% users expressing positive sentiment and remaining 22.53% people were neutral in their tweets. Fear, anger and sadness were amongst the top emotions expressed in the negative tweets whereas the positive tweets expressed trust and anticipation that the war would end soon. Operation Ganga was carried out to evacuate Indian citizens from the war-hit region. An analysis was performed on 1542 tweets that were obtained for Operation Ganga. 74.5% of the users had positive sentiments about Operation Ganga, whereas 16.67% and 8.5% had negative and neutral sentiments respectively. The people trusted this evacuation process resulting in more positive sentiments. Fear of losing near and dear ones and fear of safety was the topmost concern for Indians and leadership was one of the topmost aspects tweeted in the positive sentiments. Thus, the overall results depict that the common man does not prefer war and is fearful of the outcomes. The government should hear the voice of the common man and plan strategies and decisions considering the common man's sentiments. 2022 ACM. -
Global Anti-Discrimination Law and AI Concerning Imposter Syndrome and Legal Frameworks: Gender, Diversity, and Intersectional Bias in Professional Advancement Technology
In the age of artificial intelligence, strong anti-discrimination laws are important for more than just following the rules. It includes social, ethical and economic issues of interest to technologists and non-technologists alike. The regulations would help reduce the chance that AI perpetuates stereotypes that limit women and other groups, based on preconceived ideas. Lost impostor syndrome, behind-thescenes and careers being ruined by AI-bias fuel psychological damage to self-esteem, job satisfaction, retention etc.AI bias If bias exits in neural networks that has emerged in the workforce, " then its best to circumvent such bias before problems arise. In that chapter, it examines how international antidiscrimination law links to AI, with examples of impostor syndrome. It also explores the intersection of this technology with global anti-discrimination laws, and in doing so, reveals significant legal and sociotechnical implications. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Global Applications of Indian Psychology: Therapeutic and Strategic Models
Global Applications of Indian Psychology: Therapeutic and Strategic Models addresses a pressing problem in the field of psychology: the need for a fresh perspective that can effectively tackle the complex challenges of our modern world. While traditional Western psychology has its merits, it often fails to consider crucial aspects of human experience and well-being, limiting our understanding and hindering our ability to meet diverse global needs. This book offers a solution by presenting an interdisciplinary exploration of Indian psychology and its practical applications. Edited by Anuradha Sathiyaseelan and Sathiyaseelan Balasundaram, this comprehensive guide caters to academic scholars seeking a unique approach to understanding human psychology. It delves into the historical roots and philosophical foundations of Indian psychology, providing readers with a profound understanding of its principles and theories. The book highlights the multidisciplinary applications of Indian psychology, ranging from management and health to clinical practices, highlighting the significance of ancient Indian texts, ayurveda, yoga, and mindfulness meditation. By facilitating cross-cultural dialogue and collaboration, Global Applications of Indian Psychology: Therapeutic and Strategic Models bridges the gap between Indian and Western psychology, offering researchers and practitioners insights from both traditions. This fosters a more comprehensive understanding of human psychology and equips individuals with effective strategies to enhance well-being and flourishing worldwide. This invaluable resource fills a crucial gap in the field, offering a unique perspective and practical insights for teaching professionals, students, healthcare professionals, policymakers, researchers, and scholars in their quest for understanding and improving human psychology. 2024 by IGI Global. All rights reserved. -
GLOBAL CLIMATE CHANGE GOVERNANCE: A RETHINKING
The decades of increased Green House Gas (GHG) emissions have increased global average temperature to 1.1 degrees over pre-industrial levels. In order to hold the global average temperature rise below 2 degrees Celsius and, if possible, 1.5 degree Celsius, the governments signed various treaties. However, countries? collective agreements to reduce their emissions were never kept. This study outlines why the method of mitigating global climate change has failed. The main problem was the inability to enforce goals and timelines. Ideas for even tighter emission limits will be ineffective unless they solve the enforcement gap. Trade restrictions are one method, but they introduce significant complications, particularly when used to enforce economy-wide carbon reduction agreements. The applied methodology is qualitative. This study proposes a novel strategy to unpack the climate challenge, targeting various gasses and industries with various instruments. It also illustrates how failing to address the climate problem fundamentally would generate incentives for various solutions, offering new problems for climate change governance. 2023, Institute for Research and European Studies. All rights reserved. -
Global Cultural Immersions in Learning for a Sustainable Future
Education is a critical driver for addressing global issues such as climate change, inequality, and environmental degradation. Cultural immersion programs that align with the Sustainable Development Goals (SDGs) help learners develop intercultural competence, global awareness, and a deep commitment to sustainability. These initiatives encourage practical decision-making rooted in diverse cultural, environmental, and social values. By engaging with indigenous knowledge, community-based practices, and scalable technologies, such programs foster inclusive, locally grounded solutions to global problems. Ultimately, they empower individuals and institutions to contribute meaningfully to a more just, resilient, and sustainable world. Global Cultural Immersions in Learning for a Sustainable Future highlights the transformative potential of experiential learning, demonstrating its ability to integrate cultural, environmental, and social values into practical decision-making. By presenting theoretical frameworks, case studies, and actionable strategies, it provides tools to design and implement impactful cultural immersion initiatives. Covering topics such as cross-cultural community development, global citizenship, and urban narratives, this book is an excellent resource for academicians, educators, policymakers, corporate leaders, students, researchers, and more. 2026 by IGI Global Scientific Publishing. All rights reserved.