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The broad-band spectral energy distribution of candidate neutrino blazars
Blazars, the jet-dominated class of active galactic nuclei comprising flat-spectrum radio quasars (FSRQs) and BL Lacertae objects (BL Lacs), are now increasingly identified as potential sources of high-energy neutrinos. Such neutrino blazars are ideal targets to investigate the high-energy emission processes and to understand their role as neutrino sources. We report results on four candidate neutrino blazars, PKS 0446+112, TXS 0506+056, PKS 1424(Formula presented) 418, and PKS 1502+106. We carried out (Formula presented) -ray spectral and timing analysis on three time periods that comprise a quiescent epoch, an epoch that corresponds to neutrino detection, and a flaring epoch. We also carried out modelling of the broad-band spectral energy distribution (SED) on those three epochs. We found that the (Formula presented) -ray spectra of the BL Lac TXS 0506+056 can be adequately described by a power law, while the spectra of the other three FSRQs require a log-parabola model. On shorter time-scales, we observed flux variability with doubling/halving time-scales of 4.70, 9.24, 30.76, and 15.42 h for PKS 0446+112, TXS 0506+056, PKS 1424(Formula presented) 418, and PKS 1502+106, respectively. The SEDs of most of the epochs for the sources are well explained by a leptonic scenario. However, the quiescent epoch of PKS 1502+106 and the neutrino-emission epoch of PKS 0446+112 required an additional hadronic component to reproduce the observed SEDs. Our analysis reveals a complex interplay of leptonic and hadronic processes. While certain neutrino-associated epochs align with a leptonic model, others necessitate a hadronic component to explain the emission features. The Author(s) 2026. Published by Oxford University Press on behalf of Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. -
Clues on the X-ray emission mechanism of blazars PKS 2155?304 and 3C 454.3 through polarization studies
X-ray polarization measurable with the imaging X-ray Polarimetry Explorer (IXPE) could constrain the long debated leptonic versus hadronic origin for the high energy component in the broad band spectral energy distribution (SED) of blazars. We report here the results from IXPE and SED modeling of PKS 2155?304 and 3C 454.3, a high and low synchrotron peaked blazar. For PKS 2155?304, from model-independent analysis, we found polarization angle ?X = (130 2.5) deg and polarization degree ?X = (20.9 1.8)% in the 2?8 keV band in agreement with spectro-polarimetric analysis. We found ?X to vary with time and indications of it to vary between energies, suggesting that the emission regions are stratified. For 3C 454.3, we did not detect X-ray polarization in the June 2023 observation, analyzed here for the first time. The detection of X-ray polarization in PKS 2155?304 and its non-detection in 3C 454.3 is in accordance with the X-ray emission from synchrotron and inverse Compton process, respectively, operating in these sources. Further, our division of the dataset into finer time bins allows a more granular view of polarization variability. Additionally, we modeled the broadband SEDs of both the sources using data acquired quasi-simultaneously with IXPE, in the optical, UV and X-rays from Swift, AstroSat and ?-rays from Fermi. In PKS 2155?304, the observed X-ray is found to lie in the high energy tail of the synchrotron component of the SED, while in 3C 454.3 the observed X-ray lies in the rising part of the inverse Compton component of the SED. Our SED modeling along with X-ray polarization observations favor a leptonic scenario for the observed X-ray emission in PKS 2155?304. The SED modeling for these specific IXPE epochs has not been presented before, allowing us to place additional constraints on the physical conditions in the jet. These results strengthen the case for a structured jet model where X-ray emission originates from a compact acceleration zone near the shock front, while lower-energy optical emission is produced in a broader, more turbulent region. 2025 Elsevier B.V. -
Real-time human action prediction using pose estimation with attention-based LSTM network
Human action prediction in a live-streaming videos is a popular task in computer vision and pattern recognition. This attempts to identify activities in an image or video performed by a human. Artificial intelligence(AI)-based technologies are now required for the security and human behaviour analysis. Intricate motion patterns are involved in these actions. For the visual representation of video frames, conventional action identification approaches mostly rely on pre-trained weights of various AI architectures. This paper proposes a deep neural network called Attention-based long short-term memory (LSTM) network for skeletal based activity prediction from a video. The proposed model has been evaluated on the BerkeleyMHAD dataset having 11 action classes. Our experimental results are compared against the performance of the LSTM and Attention-based LSTM network for 6 action classes such as Jumping, Clapping, Stand-up, Sit-down, Waving one hand (Right) and Waving two hands. Also, the proposed method has been tested in a real-time environment unaffected by the pose, camera facing, and apparel. The proposed system has attained an accuracy of 95.94% on BerkeleyMHAD dataset. Hence, the proposed method is useful in an intelligent vision computing system for automatically identifying human activity in unpremeditated behaviour. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. -
Investigating MnSe@Y2O3 nanocomposite as an electrode for asymmetric hybrid supercapacitor
In this research work, manganese selenide (MnSe) and yttrium oxide (Y2O3) nanoparticles have been synthesized by facile melt diffusion and hydrothermal technique which are then composited by ultrasonication. The composite MnSe@Y2O3 has been analyzed as a supercapacitor electrode. The growth structure of the composite was scrutinized systematically by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), high resolution transmission electron microscopy (HRTEM), and selected area diffraction pattern (SAED). The Trasatti and Dunn's plots have been also plotted to calculate the capacitive and diffusive contribution. The device is fabricated with PVA-KOH gel electrolyte. Also, the fabricated device MnSe@Y2O3||AC has exhibited a specific capacity of 48.39 C/g at 1 A/g through the potential window of 01.7 V. The wide potential window is evidence for high energy density. This also provides elevated energy density of 19 Wh/kg, at high power density of 1445 W/kg, and has shown brilliant cyclic stability of 70.16 % even after 5000 charge/discharge cycles. 2024 Elsevier B.V. -
Colouring of (P3? P2) -free graphs
The class of 2 K2-free graphs and its various subclasses have been studied in a variety of contexts. In this paper, we are concerned with the colouring of (P3? P2) -free graphs, a super class of 2 K2-free graphs. We derive a O(?3) upper bound for the chromatic number of (P3? P2) -free graphs, and sharper bounds for (P3? P2, diamond)-free graphs and for (2 K2, diamond)-free graphs, where ? denotes the clique number. The last two classes are perfect if ?? 5 and ? 4 respectively. 2017, Springer Japan KK, part of Springer Nature. -
Social media advertising: A dimensional change creator in consumer purchase intention
The chapter discusses the importance of social media platforms, especially Instagram and YouTube, in advertising for influencing the consumer purchase intention of Generation Z. Various methods of business expansion through social media advertising have been explored. The authors examine in detail several key characteristics of social media advertising that affect consumer purchase intentions, including emotional appeal, interactivity, trust, creativity, and the role of e-word of mouth. The impact of Web 2.0 technologies on the development and effectiveness of social media advertising is emphasized, highlighting the close relationship between the Web 2.0 systems to enable the delivery of advertisements based on usage and preferences to accurately target, increasing the efficiency and effectiveness of advertising campaigns mobile, Web 2.0. Implicit communication, mobile-related advertising, and mobile-specific content have become important parts of social media advertising. Researchers from various fields have drawn on rapidly evolving social media platforms, each with its own unique perspective. 2024, IGI Global. All rights reserved. -
Antecedents of visual merchandising decisions: An empirical evidence /
Researchers World, Vol.8, Issue 4, pp. 107-113, ISSN No. 2231-4172. -
Facile synthesis of Sb2Se3 anchored NiO nanocomposite as an efficient electrode for hybrid supercapacitors
In this study, we aimed to develop a novel electrode material for hybrid supercapacitors by synthesizing NiO@Sb2Se3 nanocomposites and evaluating their electrochemical performance. Antimony triselenide (Sb2Se3) nanoparticles were synthesized via a facile melt diffusion technique at 700C, while nickel oxide (NiO) nanoparticles were prepared by a hydrothermal method. Both nanomaterials were composited through ball milling and characterized using SEM, PXRD, SAED, HRTEM, and XPS. Electrochemical studies demonstrated that the composite delivered a specific capacity of 140.26 Fg?1 at 10?mVs?1 and 128.97 Fg?1 at 1 Ag?1 in a three-electrode configuration. A hybrid supercapacitor device assembled with PVAKOH gel electrolyte exhibited a wide potential window (02V), achieving 60.58 Cg?1 at 1 Ag?1, with an energy density of 33.65 Whkg?1 at 2000 Wkg?1, power density, and 82.3% capacity retention over 2000 cycles. These results demonstrate the potential of NiO@Sb?Se? nanocomposites as promising electrode materials for next-generation energy storage devices. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Reimagining Consumer Experience in the Digital Age: A Strategic and Technological Perspective
In the contemporary digital landscape, consumer experience has emerged as a strategic differentiator and a critical determinant of organizational success. This chapter is intended to elaborate the changing face of customer experience in the digital era, especially with emerging technologies, data- driven strategies, and changing consumer expectations, radically changing traditional business to consumer interactions. Advanced tools like artificial intelligence, machine learning, big data analytics, and augmented reality are changing methods of designing, delivering, and managing customer interactions across digital and physical environments is, therefore, pertinent. In emphasizing aspects of personalization, immediacy, and engagement in real time, all these have dramatically changed consumer expectations and call for a rethink for omnichannel consistency and seamless integration. This chapter presents a realistic and future oriented picture of how an organization can strategically reinvent consumer experience in the digital age. 2026 by IGI Global Scientific Publishing. All rights reserved.. -
A Legal Analysis of Cyber-Enabled Wildlife Offences in India: A Qualitative Case Study of Sea Fans (Gorgonia spp.) on YouTube
With the advent of the Internet, offences against threatened species have transitioned online. Such species are directly or indirectly traded on social media despite being protected under Indian wildlife law. A qualitative case study was undertaken to assess the preparedness of national law and policy in prohibiting such offences. Sixty-three YouTube links on sea fans in the Hindi language were accessed over 8 weeks, and the information generated by both content creators and audiences was gathered and categorized for analysis. The legal provisions were then interpreted and applied to assess the extent to which the parties involved could be held liable. Our investigation shows that of these video links, the content creators directly offered specimens for sale in 15.87% of instances, demonstrated physical possession of wild specimens in 23.81% of these posts, and were involved in both activities in 20.63% of the links, which in our analysis is explicitly prohibited under national law. The remaining 39.68% of video links merely disseminated information on the relevance or usage of species in occult or religious practices, for which no express legal provision currently exists. Certain indirect legal provisions were found to be relevant; however, there were challenges associated with their implementation. Even the liability of a social media company was found to be limited if it can be demonstrated that the company exercised due diligence. Therefore, there is a need to explicitly regulate online content that has the potential to drive an unlawful demand for protected species alongside the imposition of enhanced liability on social media companies. Such measures, coupled with community awareness, can reduce cyber-enabled wildlife offences committed through social media channels. 2024 Taylor & Francis Group, LLC. -
Integration of Intelligent System and Big Data Environment to Find the Energy Utilization in Smart Public Buildings
Buildings are the leading consumer of energy in the setting of smart cities, and public structures such as hospitals, schools, government offices, and additional institutions have high energy needs owing to their frequent use. However, there needs to be adequate use of the latest innovations in machine learning inside the big data context in this field. Controlling the energy efficiency of public subdivisions is a crucial aspect of the smart city concept. This chapter aims to address the challenge of integrating big data platforms and machine learning algorithms into an intelligent system for this purpose to forecast how much energy various Croatian government buildings will consume, prediction models were constructed using deep learning neural networks, Rpart regression tree models, and random forests using variable reduction techniques. The evaluation of all three techniques considered critical aspects, and the random forest methodology yielded the most precise model. The MERIDA intelligent system aims to enhance energy efficiency in public buildings by integrating big data and predictive algorithms. This research examines the technological requirements for a platform that facilitates public administration in planning public building reconstruction, reducing energy consumption and expenses, and connecting intelligent public buildings in smart cities. Digitizing energy management may improve public administration efficiency, service quality, and environmental health. 2025 Scrivener Publishing LLC. All rights reserved. -
Development and Validation of the Multidimensional Psychosocial Risk Screen (MPRS): An Approach towards Primary Prevention
Background: The prevalence of mental health problems in adolescents has been identified as a global concern. Early screening and identification can offer benefits in terms of primary prevention and reduced healthcare costs. This study aimed to develop a tool to assess the risk of developing mental health problems in adolescents. Methods: The study followed an exploratory sequential design and was divided into five phases. The Multidimensional Psychosocial Risk Screen (MPRS) is a newly developed self-report measure. The various steps in its development and validation have been elaborated. The MPRS was evaluated with a sample of 934 adolescents aged 12-18, spread across the 8th-12th grade. Results: Exploratory and confirmatory factor analyses revealed a robust factor structure. The extracted five factors were named as Parent-Child Relationship (PCR), Self-Concept (SC), Teacher-Student Dynamics (TSD), Social Media Use (SMU), and Peer Interaction (PI). The reliability of the subscales ranged from 0.60 to 0.80. The overall reliability of the scale was good (a = 0.87). Convergent validity of the scale was established using standard measures of risk factors and emotional and behavioural problems. Conclusions: The MPRS can be considered an effective tool with an adequate factor structure and good psychometric properties. It can be beneficial in the early detection of vulnerabilities to mental health problems in adolescents and, therefore, seen as a key element in primary prevention and fostering individualized interventions. 2023 The Author(s). -
Exploring perspectives on risks to mental health problems in adolescents: A dual method approach
This study explores different perspectives on the risk factors of mental health problems among adolescents using a dual method approach. 12 mental health professionals were interviewed using a semi-structured interview guide. Nine Focus Group Discussions were conducted with parents, teachers and school going adolescents (aged 12-18). Data were transcribed and analysed using content analysis. Common codes and categories were extracted from both the methodologies thus, representing triangulation and trustworthiness of findings. The results show seven major coding categories including self concept, coping mechanisms, parenting principles and family dynamics, teacher-student dynamics, peer interaction and media. Participants across the groups described the relevance of these categories in the mental health of adolescents. The findings were illustrated using Bronfenbrenners ecological systems theory framework. The findings have important implications in terms of identification and management of mental health difficulties in adolescents especially from a preventive perspective. The findings conclude that risk factors exist within the individual as well the contextual systems which make an adolescent vulnerable to a number of mental health problems. The findings can be included in the primary prevention framework by identifying and modifying these risk factors and therefore, delaying the progression of mental health difficulties into a major disorder. 2022 RESTORATIVE JUSTICE FOR ALL. -
Role of Technology in Achieving SDG Adoption in Emerging Economies
Technology has always changed the world for the better making processes efficient and effective, yet it is imperative to gain a comprehensive understanding and know-how of these technologies in order to utilize them for SDG adoption especially in emerging economies. The United Nations sustainable development goals (SGDs) provide us with a framework for creating a more sustainable, prosperous and equitable future by the year 2030 and modern technology has a vital role to play in actualizing these plans. However, utilizing technology for SDG adoption in emerging economies come with its own set of constraints and challenges. Emerging economies face unique challenges in their pursuit of the United Nations SDGs, including limited infrastructure, economic instability, and unequal access of resources. Nonetheless is proving to be a key enabler in overcoming such hurdles and accelerating the adoption of SDGs. This chapter explores how technology, including mobile connectivity, artificial intelligence (AI), blockchain, and the Internet of Things (IoT) are enabling smother and more streamlined adoption of SDGs and how emerging economies are the real beneficiaries. Mobile technology, for instance, has revolutionized the financial system making it inclusive, bring it within reach of the unbanked population of the world. Technology is also empowering small farmers with accurate weather forecast, real-time market data, and affordable crop management tools. This is a direct contribution to SDG 1 (No Poverty) and SDG 2 (Zero Hunger). In a similar manner, AI-powered app-based healthcare solutions are a massive leap within the sector and can help tackling disease outbreaks and enhancing the general health of the people, thus having a direct positive impact on SDG 3 (Good Health and Well-being). Furthermore, the applications of IoT are numerous and are proving to be rather beneficial for cities in emerging economies. It is being utilized to implement smart energy grids to water management systems directly contributing to SDG 6 (Clean Water and Sanitation) and SDG 7 (Affordable and Clean Energy). This chapter concludes by examining the need of inclusive policies and investment in digital infrastructure to ensure that emerging economies can reap maximum through the modern-day technologies. It also addresses the potential risks, such as digital inequality and data privacy concerns assessing how the contemporary technology be utilized in order to achieve sustainable development in emerging economies. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Ensuring Equity and Mitigating Harm in AI (Fairness and Bias)
The rapid spread of Artificial Intelligence (AI) across sectors like healthcare, finance, education, law enforcement, and public administration has dramatically changed how decisions are made, services are delivered, and organizations function. AI holds incredible potential to improve human well-being and drive societal progress. Yet, alongside these opportunities come serious ethical concernsparticularly around fairness, bias, and the risk of reinforcing existing social inequalities. This chapter explores these challenges in depth, offering an interdisciplinary perspective on how bias emerges in AI systems. 2026 by IGI Global Scientific Publishing. All rights reserved. -
BORCAE: Bayesian Optimized Residual Convolutional Autoencoder for Efficient Feedback Compression in RIS-Assisted Time-Varying IoT Networks
Reconfigurable Intelligent Surfaces (RIS) have strong potential to improve the performance of time-varying Internet of Things (IoT) networks. However, a major challenge in operating RIS effectively is the need for frequent Quantized Phase Configuration (QPC) feedback bits from the Base Station (BS) to the controller. This challenge becomes more serious asthe RIS size grows, since the feedback bandwidth is limited. As a result, efficient compression of control signals is crucial for the practical deployment of RIS. In this work, we propose Bayesian Optimized Residual Convolutional AutoEncoder (BORCAE), a lightweight and noise-resilient feedback compression framework based on a 1D Convolutional Autoencoder with residual connections. The model is designed to reduce QPC feedback size while preserving high reconstruction fidelity. To ensure adaptability across varying deployment conditions, we employ Bayesian hyperparameter optimization using Optuna, which enables automatic tuning of key architectural hyperparameters. This optimization ensures that the architecture generalizes effectively across a wide range of operating scenarios. Additionally, we integrate the Limited Memory Broyden Fletcher Goldfarb Shanno (LBFGS) optimizer during the final training epochs, which accelerates convergence and improves stability. For performance evaluation, we use Normalized Mean Squared Error (NMSE) as the reconstruction metric. Extensive testing across different Signal-to-Interference-plus-Noise Ratio (SINR) levels demonstrates that BORCAE consistently achieves lower NMSE compared to DL-CsiNet and CsiNet. The results highlight the practical viability of BORCAE for RIS-assisted communication, offering improved efficiency, and scalability for real-world IoT and Sixth-Generation (6G) applications. 2020 IEEE. -
PUNCHING UP IN STAND-UP COMEDY: Speaking Truth to Power
Punching Up in Stand-Up Comedy explores the new forms, voices and venues of stand-up comedy in different parts of the world and its potential role as a counterhegemonic tool for satire, commentary and expression of identity especially for the disempowered or marginalised. The title brings together essays and perspectives on stand-up and satire from different cultural and political contexts across the world which raise pertinent issues regarding its role in contemporary times, especially with the increased presence of OTT platforms and internet penetration that allows for easy access to this art form. It examines the theoretical understanding of the different aspects of the humour, aesthetics and politics of stand-up comedy, as well as the exploration of race, gender, politics and conflicts, urban culture and LGBTQ+ identities in countries such as Indonesia, Finland, France, Iran, Italy, Morocco, India and the USA. It also asks the question whether, along with contesting and destabilising existing discursive frameworks and identities, a stand-up comic can open up a space for envisaging a new social, cultural and political order? This book will appeal to people interested in performance studies, media, popular culture, digital culture, sociology, digital sociology and anthropology, and English literature. Chapter 9 of this book is freely available as a downloadable Open Access PDF at https://www.taylorfrancis.com under a Creative Commons (CC-BY) 4.0 license. Funded by the University of Helsinki. 2023 selection and editorial matter, Rashi Bhargava and Richa Chilana; individual chapters, the contributors. -
INTRODUCTION
[No abstract available]