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Lithium photodisintegration with linearly polarized photons at astrophysical energies
We present here a model-independent theoretical discussion of differential cross-sections in photodisintegration of lithium with unpolarized and linearly polarized photons. In recent years, experimental measurements are being carried out on the photodisintegration of lithium in the reaction channel 7Li(?, n)6Li to study the angular dependence of cross-section. In this regard, we have studied the spin structure of amplitudes in 7Li(?, n)6Li by expressing the differential cross-section in terms of Legendre polynomials. 2023 Oxford University Press. All rights reserved. -
Lithium photodisintegration with unpolarized photon beams at near threshold energies
The study of photonuclear reactions with lithium targets i.e. photodisintegration of lithium in addition to other photonuclear reactions is of considerable interest to the fields of nuclear physics, astrophysics, laser physics and several applications such as non - destructive testing of nuclear materials. We propose to study photodisintegration of lithium with unpolarized photon beams at near threshold energies. Our model independent theoretical approach, which makes use of irreducible tensor techniques, is well suited for making predictions on the spin observables as well as the differential cross section. In this paper we analyze the reaction channel 7Li + ? ? 6Li + n by using unpolarized photons. 2022 -
Litigating for Climate JusticeChasing a Chimera?
Across the world, in recent decades, climate litigations have been playing essential roles in shaping domestic policies and legal frameworks on climate change and also in rendering climate justice. There has also been a continuous rise in the development of climate actions, and climate claim litigations by individuals, civil society, and non-state actors. The Indian Supreme Court, High Courts, and the National Green Tribunal have played a significant role in environmental governance by interpreting constitutional and statutory rights to include a right to the environment over the past decades. Nevertheless, with the latest trends in climate litigations, climate challenges have grown across varied climate-related issues, requiring a new judicial approach. In its analysis of climate claims, the justice dispensation mechanism ought to comprehend the shortcomings and be able to generate solutions, similar to those adopted by the courts in the United States, the United Kingdom, and the Netherlands. An analyses of the approach taken by courts in developing nations namely in the Philippines, South Africa, and Pakistan that have compelled governments and corporates to meet their climate commitments are examined. Climate litigation in India has been emerging rapidly over the past decade. As the claims are increasing, the courts and the National Green Tribunal need enhanced capacity building to address climate litigations. This chapter seeks to address the feasibility and implication of equipping courts to address climate litigation. We review the scope of climate litigation and consider the challenges and opportunities to ensure climate justice. This chapter concludes by outlining possible opportunities and challenges in interlinking climate litigation and climate justice in India. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Lived experiences of urban working mothers during pandemic: A matricentric exploration in the Indian context
In India, entrenched patriarchal norms dictate gender roles, perpetuating men-headed families and patrilineal traditions deeply ingrained in its culture. Within this framework, working mothers daily confront gender biases despite society undervaluing their crucial roles in caregiving and the economy. The Covid-19 pandemic intensified these challenges, as working mothers faced heightened expectations to excel in both professional and maternal roles. With inadequate support and intensified caregiving demands, their physical and mental well-being significantly suffered. This article explores the complex realities experienced by Indian working mothers during the pandemic. Viewing motherhood through a matricentric lens underscores its importance to society while highlighting the need to redistribute caregiving responsibilities beyond mothers alone. The researchers conducted a qualitative study, interviewing 30 Indian working mothers from various professional backgrounds using semi-structured interviews. Thematic analysis revealed that despite seventy-seven years of independence, mothers in India continue to grapple with patriarchal oppression, inequality, and violence, underscoring the persistent challenges faced in navigating societal norms and expectations. By gaining insight into their experiences, policymakers can better grasp these burdens and implement measures to address associated physical and mental health concerns. 2025 Elsevier Ltd -
Lived Experiences, Challenges, and Coping Mechanisms of Undergraduate Students on Cybersecurity in Digital Environments
Higher education students use digital devices for learning, entertainment, and financial transactions. The present study examines undergraduate (UG) students challenges faced in cyber security space amid digital environments. The study employed a qualitative research design with a narrative inquiry method to capture the lived experiences, challenges, and coping mechanism of UG students through semi structured interviews. The researchers analyzed the qualitative data of ten UG students using the inductive thematic analysis method. UG students shared overall that they face varied experiences, multiple challenges, and cope with cyber security issues in multiple ways. Findings from the study led to recommendations for stakeholders, which includes designing higher education classes in a more secure way. This may offer students orientation on cybersecurity knowledge which keeps them safe and helps them understand the digital environment overall. 2024 Taylor & Francis Group, LLC. -
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Living Life Beyond Binaries- Bisexuality in Urban India
This qualitative study aimed to understand the lived realities of bisexual individuals in a society predominantly perceived through a binary lens. Describing the term bisexual by orientation as individuals who engage in same-sex and opposite-sex intimacies, taking into account several factors, that include but are not reducible to the sex and gender of the self and others. The research employed an ethnographic approach with a group of Indian adults. Interestingly, the study revealed that the participants did not consider bisexuality as a central component of their sexual behavior and identity, instead utilizing specific strategies to maintain a heterosexual facade while engaging in same-sex encounters. They regarded these encounters as part of their overall sexual experiences, distinct from a fixed sexual identity and relationships. Contrary to the prevailing notion that bisexuals must suppress their genders attraction to be in monogamous relationships, the participants affirmed being in monogamous relationships. They devised discreet methods to partake in same-sex encounters, safeguarding their monogamous relationships without feeling compelled to openly disclose their same-sex inclinations. 2025 Taylor & Francis Group, LLC. -
Living with Coronavirus outbreak in India
The present paper focuses on living with coronavirus outbreak in India. This piece emphasizes on various policies adopted by the government of India to face the coronavirus crisis. It brings into perspective what financial strides the economy is going through, the mental health of the citizens, and the current situation of health care in the country. The current commentary reflects the learnings from COVID-19, the role of defined governmental policies, and support in surviving such an unforeseen situation. 2020 American Psychological Association. -
Load Balancing Strategy for Large Scale Software Defined Networks
Programmability has left its mark on every facet of business, with technology playing newlinean integral role. Social networking industry trends underscore technology s ubiquity in newlinenearly every business transaction. Traditional networks grapple with numerous challenges, rendering them ill-equipped to process and handle the demands of the modern newlinelandscape effectively. The lack of programming in these networks leads to stagnation, newlineinhibiting their ability to evolve or enhance performance. The advent of Software Defined Networks (SDN) has introduced increased flexibility into conventional networks, newlineopening avenues for creating innovative services. newlineSDN technology addresses challenges in large-scale networks, offering solutions for newlinehigh throughput, virtualization, fault detection, and load balancing, providing effective network management. The rapid expansion of network services and applications newlinein SDN environments demands sophisticated load-balancing solutions that adapt to newlinedynamic traffic patterns and varying service requirements. This study presents a pioneering algorithm, the Dynamic Load Balancing Algorithm (DLBA), which utilizes the newlineProgramming Protocol-independent Packet Processors (P4) language. The algorithm is newlinespecifically crafted to tackle the issues associated with optimizing traffic distribution in newlinethe data plane of SDN. newlineP4 programming language, recognized as one of the most robust languages, addresses newlinethe limitations of traditional networking, enhancing programmability and agility by newlinedistributing the load across the network. The research implements a novel quotDynamic newlineLoad Balancing Algorithmquot using the P4 language to instill dynamism and achieve load newlinebalance in large-scale networks. The P4-based implementation showcases dynamicity, scalability, flexibility, and adaptability. This research commences with thoroughly newlineexamining existing load-balancing algorithms implemented using the P4 language, followed by a comparative analysis between these algorithms and DLBA. -
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Load balancing with availability checker and load reporters (LB-ACLRs) for improved performance in distributed systems
Distributed system has quite a lot of servers to attain increased availability of service and for fault tolerance. Balancing the load among these servers is an important task to achieve better performance. There are various hardware and software based load balancing solutions available. However there is always an overhead on Servers and the Load Balancer while communicating with each other and sharing their availability and the current load status information. Load balancer is always busy in listening to clients' request and redirecting them. It also needs to collect the servers' availability status frequently, to keep itself up-to-date. Servers are busy in not only providing service to clients but also sharing their current load information with load balancing algorithms. In this paper we have proposed and discussed the concept and system model for software based load balancer along with Availability-Checker and Load Reporters (LB-ACLRs) which reduces the overhead on server and the load balancer. We have also described the architectural components with their roles and responsibilities. We have presented a detailed analysis to show how our proposed Availability Checker significantly increases the performance of the system. 2014 IEEE. -
Load shedding using GA and ACO in smart gird environment
Increasing pressure on the utilities to accommodate energy efficiency, load management and progress in advanced technology has led to transformations for existing grid into a smarter grid. Creating awareness among the end-users to participate in load management programs instead of capacity addition is the best solution for maintaining the stability in the grid. Load shedding is a strategy under load management in which load connected to the smart grid is individually controlled via two- way communication. In this paper, a Smart Load shedding approach is developed based on load prioritization. The required amount of load to be shed under lack of sufficient generation level is optimized by Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithms. The proposed approach is implemented using a real time feeder data from the substation, India. The results reflect the effectiveness of proposed algorithms taken into practical applications. -
Loan Default Prediction Using Machine Learning Techniques and Deep Learning ANN Model
Loan default prediction is a critical task in the financial sector, aimed at assessing the creditworthiness of borrowers and minimizing potential losses for lending institutions. Online loans continue to reach the public spotlight as Internet technology develops, and this trend is expected to continue in the foreseeable future. In this paper, the authors proposed loan default loan prediction system based on ML and DL models. This work makes use of the information on loan defaults provided by Lending Club. The dataset is preprocessed by applying various data preprocessing techniques and preprocessed dataset is generated. Later, we proposed four ML algorithms decision tree, random forest, logistic regression, K-NN and Feed forward neural network. The experimental results shown that proposed feed forward neural network achieved good accuracy for loan default prediction with an accuracy of 99%. 2023 IEEE. -
Local community involvement in wildlife resorts: Issues and Challenges
The Global Code of Ethics for Tourism Article 5 states that tourism should be a beneficial activity for host countries and communities (UNWTO). The code also emphasises on equitable distribution (between host countries and communities) of the economic and sociocultural benefits generated by tourism activities. The tourism resorts and accommodation sector have to involve local communities in socio-economic activities and priority should be given to local manpower. A wildlife resort has vast opportunities to involve local communities in their day to day operation by purchasing local products, promoting local festivals, providing employment opportunities to locals, and involving local communities in decision-making. Wildlife resorts can also promote local culture, create environment awareness among local people, provide educational support to the local children, and support development of infrastructure and medical facilities for the locals. Though local communities can be involved in various activities of wildlife resorts, it is essential to address the issues and challenges that hinder wildlife resorts from doing so. This paper attempts to determine the issues and challenges faced by wildlife resorts in involving local communities in their day to day operations and suggests ways and means to overcome those challenges. The scope of the study covered selected wildlife resorts in Karnataka. The targeted respondents of the research survey were resort managers and data were collected using open-ended questions to understand real-time issues and challenges involving local communities in resort activities. The data were then analysed using thematic text analysis. The findings from the study will help explore means of providing a better framework which will help wildlife resorts overcome issues and challenges involving local communities. The Author(s) 2017. -
Local Hearts, Global Minds: Using SEL to Prevent Bullying in Resource- Constrained Establishments
This chapter explores the role of Socio- Emotional Learning in developing bullying prevention strategies in resource constrained educational establishments. By applying established theoretical frameworks such as the CASEL model, Bronfenbrenners ecological systems theory and Banduras social learning theory, SEL is established as a culturally adaptable approach to combat bullying in under- resourced settings. By drawing on case studies from developing and under- developed countries such as India, Zimbabwe, and Ghana, efficacy of simple interventions are highlighted. Techniques such as circle time, storytelling, peer mentoring, and theatre based interventions are proposed as tools to boost empathy, emotional regulation and prosocial behavior in accordance with SEL. Evidence based effectiveness of SEL in resource constrained environments allows for it to be proposed as a simple but efficient method ready to be integrated into programs as a cost effective approach against bullying. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Local post-hoc interpretable machine learning model for prediction of dementia in young adults
Dementia is still the prevailing brain disease with late diagnosis. There is a large increase in dementia disease among young adults. The major reason is over indulgence of young adults on social media resulting in denial of disease and delayed clinical diagnosis. Dementia is preventable and curable if diagnosed at an early stage, however, no attempts are being made to mitigate dementia in young adults. Today artificial intelligence (AI) based advanced technology with real-life consultations in clinical or remote setups are proved beneficial and is used to detect dementia. Most AI-based test is dependent on computer-aided diagnosis (CAD) tools and uses non-invasive imaging technology such as magnetic resonance imaging (MRI) data for disease diagnosis. In this paper, a local post-hoc interpretable machine learning (LPIML) model for prediction of dementia in young adults is proposed. The performance parameters are computed and compared based on accuracy, specificity, precision, F1 score and recall. The proposed work yields 98.87% training accuracy on original images and 99.31% training accuracy on morphologically enhanced images. The performance results are intrinsic and intuitive in learning the prediction results of individual case. The adoption of the proposed work will accelerate the diagnosis process in the era of digital healthcare. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Local self-government in India: A critical analysis through the lens of democratic decentralization
Local Self-Government (LSG) existed in a variety of forms throughout India. LSG was seen as an effective form of day-to-day management and administration in rural areas in India. This ensured a democratic form of administration even during the time of monarchs. Although it had a setback during the Muslim and British rulers period, it continued to exist. Gandhi raised his voice for increased decentralization and self-rule of the villages. Although the Constitution did not provide such an option, many committees opined that the local governance should be entrusted to the local people. Accordingly, LSG got constitutional recognition through the 73rd and 74th Amendments in 1992. It provided a three-tier system of governance at the regional level as well. Using analytical and critical lenses, this chapter examines the functioning of the constitutionally established LSG model through the lens of democratic decentralization to expose how far it has achieved its objective. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Localised actor roles in post-disaster housing recovery: A case study from Kerala
The effectiveness of post-disaster housing reconstruction (PDHR) is increasingly being challenged by the frequency and complexity of climate-induced disasters. In the Indian state of Kerala-particularly the highland regions of Kottayam and Idukki-landslides and floods have caused significant housing losses in recent years. While the government initiated housing recovery interventions after the 2021 landslide event, multiple civil society actors, including faith-based organisations, political parties, and professional groups, also participated in reconstruction efforts. This study examines the actor-specific approaches to community consultation in PDHR and their impact on beneficiary satisfaction. Using a qualitative case study design, the analysis identifies variations in participation across planning, design, and construction stages, and maps these to outcomes such as reconstruction speed, satisfaction levels, and community cohesion. While some actors offered comprehensive engagement strategies, others limited their consultation, resulting in mismatches between needs and outcomes. Findings suggest that community consultation remains uneven and often symbolic, with beneficiaries perceiving external aid as benevolence rather than entitlement. The study underscores the importance of meaningful participation in PDHR, especially in the context of localized climate events. These insights offer practical implications for designing inclusive recovery frameworks and enhancing community resilience in hazard-prone regions. The Authors, published by EDP Sciences, 2025. -
Localization Method for Camera Networks in Surveillance System
The significance of prevention and mitigation of critical issues especially in the homeland security has been increasing day by day. Emergence of autonomous video analytics tools greatly helped in the prevention of security threats. The recognition of video analytics for anomaly detection based on a set of unsupervised approaches has many fundamental technical challenges. This entails autonomous object localization and tracking technique especially in the presence of occlusion. This paper focuses on deriving a solution for the object detection and tracking in a heterogeneous camera network. The object tracking method is mainly based on Kalman filter whereas frame difference algorithm is used for object localization. This detection and tracking solution is expected to significantly reduce the effect of occlusion while tracking the anomaly. The organisation of the thesis is done into various chapters. The first chapter contains an introduction to the video surveillance system and the need for an unsupervised approach. This chapter also states the objective of the research. The solution overview gives high level solution architecture of the proposed system. The second chapter focus on the literature overview in which the citation from different papers in the field of video analytics, Kalman filter implementation and camera configuration has been referred. Chapter 3 provides the methodology in which a brief introduction to the basic algorithms used in the solution, the Kalman filter and the frame difference algorithm, are discussed. This is followed by the solution architecture of the proposed system. Chapter 4 shows the Matlab implementation of the mentioned algorithms. In Chapter 5, the results of the implementation are discussed. Chapter 6 talks about the summary of the work done and conclusion. This chapter also includes the future enhancements suggested. -
Localizing and Classifying Kannada Texts Using a YOLO-Based Approach
Extracting handwritten characters from the scanned documents is a critical step due to the inherent complexities of various writing styles, inconsistent alignments, multi-touch scenarios, and overwriting characters. Expanding upon the real-time object detection capabilities of YOLOv8 (You Only Look Once), the current paper presents an experiment utilizing a dataset of 2000 handwritten images. This dataset combines the standard dataset (Chars74K) with the custom dataset featuring multi-touch handwritten text, encompassing both individual characters and character combinations that form words. The annotations were created using the Roboflow application and exported to a yaml (yet another markup language) file. The hybrid dataset was split into training, validation, and testing sets. The evaluation process yielded an accuracy of 96.8% at a threshold of 0.5 for recognizing and classifying the characters. The result suggests a positive correlation between training dataset size and model accuracy. Further, fine-tuning the hyperparameters could increase the accuracy upto 98.4%. Additional experiments were conducted to compare YOLOv8 and Detectron2 with Faster R-CNN. The results demonstrated that YOLOv8 offers substantially faster inference times, while Detectron2 with Faster R-CNN exhibited marginally higher accuracy in few classes. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.