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Climate Risks in an Unequal Society: The Question of Climate Justice in India
Over the past few decades, India has witnessed the brunt of climate change impacts in multiple dimensions. Notably, recent years' experiences prove that there has been a substantial increase in the intensity, frequency, and duration of climate-related risks and extreme events, resulting in an acceleration of the nexus between climate change and inequities. Despite the growing advancements of socioeconomic research on current and future climate change risks in India, the explorations through the lens of legal perspectives are still limited and have not met the demands. This chapter argues for rethinking legal perspectives of climate justice in India by drawing insights from two recent climate extreme events. To begin with, this chapter briefly reviews the historical background of the global actions to combat climate inequities and injustices and identifies the ways in which climate injustices perpetuate. For this, it adopts three main principles of climate justice, consisting of equity, a rights-based approach, and sustainability. Following this, it discusses India's climate policy and the existing institutional framework and actions to respond to climate change at the national and state levels. Then, by focusing on the climate change impacts on India, it introduces two recent climate-related risk events in India, and it discusses the unequal structuration of climate risks and the resulting more vulnerable and precarious situation of the marginal sections of the society that already faces multiple social injustices of Indian society. At the end of the cases, it briefly offers a critique of the climate change action plans of the respective states. This chapter concludes by outlining a few strategies to create a more sustainable and equitable approach toward climate governance and justice by strengthening the legal and institutional dispensations of the climate regime in India. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Climate-Smart Livelihood - A Case Study of Dodaballapura Taluk of Bangalore Rural District
More than a billion farmers around the world are on the frontier of climate change. These farmers' livelihoods are directly and indirectly affected by the impact of climate change. Climate smart livelihood explains the practices in agriculture sector which sustainably contributes to productivity and income. This study tries to explore the adaptation of climate smart livelihood techniques by the farmers in the Doddaballapur taluk of Bangalore rural district. The data was collected primarily from the five villages and 50 households of Doddaballapur taluk. The survey revealed that 81.67% of the respondents faced problems during adaptation of climate smart agriculture was due to poor support of local and national authorities with climate related issues and ranked it one of the major constraints. This was followed by lack of financial constraints, lack of knowledge about adaptive practices (78.50%), non-availability of agriculture inputs in time (76.17%), lack of education about the adaptation strategies (75.33%), unavailability of new technologies (78.83%), higher cost of the agricultural inputs used for the practices (71.17%), lack of improved communication facility about the climate change (71 %), migration of youth due to urbanization and better employment (70.83%), lack of knowledge about post-harvest technology (68.83%), lack of awareness about climate change issues (59.83 %). The study reveals that as most farmers believe they have low capacity to adapt to climate-smart agriculture due to lack of availability of resources. Government can help farmers through National Agricultural Extension Project (NAEP), Krishi Prashasthi, etc. 2022 - Kalpana Corporation. -
Climate, agriculture, and farmer's mental health: Unravelling the nexus in Wayanad, Kerala
A sizable majority of the population works in the primary sector in Kerala's Wayanad district, where agriculture is the backbone of the local economy. However, dynamic issues including climate change, fluctuating soil quality, crop diseases, and related economic consequences pose difficulties for this industry. The complicated linkages between agricultural practices and climate change are discussed using qualitative data from in-depth interviews with 15 Wayanad farmers. Agricultural productivity and revenue are strongly impacted by unpredictable rainfall, which is exacerbated by strong winds, natural disasters, wildlife intrusions, and crop diseases. The failure of farmers to adjust to these climate changes is a remarkable finding, frequently brought on by fear and unstable financial situations. This resistance causes anxiety, a sense of powerlessness, and a sense of responsibility for circumstances that are out of their control. In order to help farmers manage the unforeseeable effects of climate change, the study emphasizes the urgent need for policy initiatives in areas like Wayanad. Cooperative farming and knowledge-sharing platforms are examples of strategies that could improve farmers' psychological resilience and general well-being. Given that agriculture accounts for a substantial portion of the region's income and that resources and knowledge are scarce, climate change has a considerable impact on agricultural outputs and farmers' psychological well-being. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Clinical hypnosis and Patanjali yoga sutras
The trance states in yoga and hypnosis are associated with similar phenomena like relaxation, disinclination to talk, unreality, misrepresentation, alterations in perception, increased concentration, suspension of normal reality testing, and the temporary nature of the phenomena. While some researchers consider yoga to be a form of hypnosis, others note that there are many similarities between the trance in yoga and the hypnotic trance. The present study aimed to find similarities between the trance states of hypnosis and Patanjali?s yoga sutras. The trance states were compared with the understanding of the phenomena of trance, and the therapeutic techniques and benefits of both. An understanding of the concept of trance in Patanjali?s yoga sutras was gained through a thematic analysis of the book Four Chapters on Freedom by Swami Satyananda Saraswati. This led to an understanding of the concept of trance in the yoga sutras. The obtained concepts were compared to the concepts of trance in hypnosis (obtained through the literature on hypnosis) to investigate whether or not there exist similarities. The findings of the study show that there are similarities between the trance in hypnosis and the trance in Patanjali?s yoga sutras in the induction and deepening of the trance states in hypnosis and that of Samadhi, the phenomena present in hypnosis and the kinds of siddhis that are obtained through Samadhi, and the therapeutic techniques and the therapeutic process in Patanjali?s yoga sutra and hypnosis. -
Clinical implications of chromosomal polymorphisms in congenital disorders
Alterations in the DNA sequence are generally seen in the general population at >1%, and these alterations can be deletions or insertions. Classically, chromosomal polymorphisms (CPMs) are alterations with no significant phenotypic distinctions. However, few studies have shown that the presence of CPM can lead to congenital disabilities, which can be fatal. These variants in the DNA can happen in the form of single nucleotide polymorphisms (SNPs). The human genome is considered full of SNPs, and they are responsible for causing pathological phenotypes and provide insight into pathogenesis, a therapeutic approach to the pathology. About 100 million SNPs are observed in humans for an average of 300 nucleotides. These polymorphisms are detected by using molecular techniques. These polymorphisms are not just restricted to the coding region. The CPMs are first recognized on the chromosomes through molecular techniques, followed by detection of the polymorphism. The CMPs are generally the SNPs, deletions/duplications, and presence of microsatellite DNAs. Here we have summarized the implications of CMPs in a few congenital disorders and the method of diagnosis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Clinical Intelligence: Deep Reinforcement Learning for Healthcare and Biomedical Advancements
Deep reinforcement learning (DRL) is showing a remarkable impact in the healthcare and biomedical domains, leveraging its ability to learn complex decision-making policies from raw data through trial-and-error interactions. DRL can effectively extract the characteristic information in the environment, propose effective behavior strategies, and correct errors that occurred during the training process. Targeted toward healthcare professionals, researchers, and technology enthusiasts, this chapter begins with notable applications of DRL in healthcare, including personalized treatment recommendations, clinical trial optimization, disease diagnosis, robotic surgery and assistance, mental health support systems, chronic disease management and scheduling, and a few more. It also delves on challenges such as data privacy, interpretability, regulatory compliance, validation, and the need for domain expertise to ensure safe and effective deployment. Next, the chapter seamlessly transitions into DRL algorithms contributing to the biomedical field which are gaining traction due to their potential to provide timely and personalized interventions. Over time, the research community has proposed several methods and algorithms within the field of deep reinforcement learning that help agents learn optimal policies from rich data. Healthcare data is often complex, high-dimensional, and unstructured, such as medical images, genomics data, and patient records. The healthcare-suitable DRL algorithms such as Q-learning, SARSA, Bayesian, actor-critic, reinforcement learning (RL), Deep-Q-Networks (DQN), and Monte Carlo Tree Search (MCTS) are highlighted. In addition, the section offers guidelines for the application of DRL to healthcare and biomedical problems, aiming at providing indications to the designer of new applications in order to choose among different RL methods. Furthermore, a case study is included to fully realize the revolutionary benefits of DRL in healthcare environments, aiming to bridge the gap between theory and practice. The case study presents a remarkable impact on categories such as precision medicine, dynamic treatment regime, medical imaging, diagnostic systems, control systems, chat-bots and advanced interfaces, and healthcare management systems. 2024 Scrivener Publishing LLC. -
Clinical Study Macular Oedema
Prior to the development of the ophthalmoscope, macular oedema remained mostly unknown. Macular oedema is caused by fluid buildup in the retinal layers around the fovea. It causes vision loss by changing the functional cell connection in the retina and stimulating an inflammatory reparative response. The clinical profile, aetiology, and varied types of Macular Oedema are hence the focus of research, and also to investigate the aetiology of macular oedema as well as the various forms of macular oedema in patients attending Krishna Hospital in Karad. The male to female ratio among the 60 participants was 2.53:1. Macular oedema is the major cause for loss in vision which is common vitreo retinal diseases, with diabetes being the most prevalent cause (35% of cases) in our study. Its early detection and treatment are critical for preventing blindness. It is consequently critical to understand the aetiology, pattern, and chronicity of macular oedema in order to customize treatment and monitor response to it. RJPT All right reserved. -
Clinical Text Classification of Medical Transcriptions Based on Different Diseases
Clinical text classification is the process of extracting the information from clinical narratives. Clinical narratives are the voice files, notes taken during a lecture, or other spoken material given by physicians. Because of the rapid rise in data in the healthcare sector, text mining and information extraction (IE) have acquired a few applications in the previous few years. This research attempts to use machine learning algorithms to diagnose diseases from the given medical transcriptions. Proposed clinical text classification models could decrease human efforts of labeled training data creation and feature engineering and for designing for applying machine learning models to clinical text classification by leveraging weak supervision. The main aim of this paper is to compare the multiclass logistic regression model and support vector classifier model which is implemented for performing clinical text classification on medical transcriptions. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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Clonning and Characterization of An Exported Protein Present in the RD7 Region of Clinical Isolates of Mycobacterium Tuberculosis
The bacterium Mycobacterium tuberculosis is responsible for causing the disease newlinetuberculosis in mammals, which is regarded as one of the oldest diseases haunting the human race. The only available tuberculosis vaccine Bacillus Calmette-Guerine (BCG), is effective against childhood tuberculosis but is regarded as having low efficacy in conferring protection in the case of tuberculosis in adults. A comparison of the M. tuberculosis H37Rv strain and clinical isolates from Kerala had earlier revealed that the clinical strains have a distinctive 4.5 kb genomic sequence that is lacking from the H37Rv strain in the RD7 region. The RD7 is a distinctive genomic region that is absent in M. tuberculosis H37Rv and Mycobacterium bovis BCG strain. The 4.5 kb genomic sequence is projected to include 6 potential ORFs by newlineNCBI ORF prediction tool, one of which Novel Hypothetical Protein (NHP2) is anticipated to encode an exported protein with a length of 268 amino acids. Studies demonstrate that Mycobacterium tuberculosis secretory proteins such as the Ag85 complex, the ESAT-6 family protein, and the PE-PPE family proteins were newlineeffective vaccine candidates because they trigger T cells. Here, we present an indepth analysis of the exported protein, which is 268 amino acids long. The putative exported protein with a gene 807 bp long was PCR amplified and cloned in the expression vector pET-32a for expression. The protein was over expressed using Isopropyl D-1-thiogalactopyranoside (IPTG) and was isolated and purified using column chromatography. Bioinformatics studies were conducted to study the characteristics of the expressed protein. A novel putative mycobacterial protein discovered by subtractive hybridization was studied for its potential as a vaccine candidate using cutting-edge computer technologies. -
Cloud and IOT based alcohol and health monitoring system /
Patent Number: 202141022529, Applicant: Dr.AR.Sivakumaran.
Wireless alcohol and health monitoring system that can monitor a human 24x7. Vehicle driving to manufacturing plants, Offices, Hospitals, Military, and other such ventures need to screen their staff/faculty follow all hard-working attitudes that incorporate, not coming to premises affected by liquor. This guarantees legitimate hard-working attitudes are followed. Our proposed framework takes into consideration liquor and wellbeing checking in addition to a detailing framework that screens this and reports it to concerned staff distantly over the web. -
Cloud and IOT based smart forest fire detection and warming system /
Patent Number: 202141048693, Applicant: Arumugam Ranjith.
The development of modern industrial civilizations has caused in the establishment of manufacturing plants, office buildings, and housing blocks throughout urban parts. Because of the combustible substances contained in these facilities, there are gas and oil tanks all over these areas. Because of the densely packed buildings, extreme heat and smoke, and the possibility of explosives, putting out a fire in one of these places is nearly impossible. -
Cloud based ERP Model using Optimized Load Balancer
Enterprise Resource Planning (ERP) and Cloud computing are turning out to be increasingly more significant in the field of Information Technology (IT) furthermore, Communication. These are two distinct segments of current data frameworks, and there are a few inside and out examinations about Enterprise Resource Planning on cloud computing framework. ERP frameworks are related with a few issues, for example, shared synchronization of multi-composed assets, constrained customization, massive overhauling cost, arrangement mix, industry usefulness, reinforcement support and innovation refreshes. These issues render ERP frameworks execution excruciating, complex and time-devouring and create the need for a huge change in ERP structure to upgrade ERP frameworks foundation and usefulness. Cloud Computing (CC) stages can defeat ERP frameworks inconsistencies with financially savvy, redid and profoundly accessible figuring assets. The objective of this examination is to blend ERP and CC benefits to lessen the factor of consumption cost and execution delays through a proposed system. For this reason, investigate the unmistakable issues in current ERP frameworks through a complete correlation between ERP when moving to CC condition. Also, a conventional structure is proposed for 'Cloud-based ERP frameworks'. 2020 IEEE. -
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Cloud Computing Application: Research Challenges and Opportunity
In a world with intensive computational services and require optimal solutions, cloud security is a critical concern. As a known fact, the cloud is a diverse field in which data is crucial, and as a result, it invites the dark world to enter and create a virtual menace to businesses, governments, and technology that is facilitated by the cloud. This article addresses the fundamentals of cloud computing, as well as security and threats in various applications. This research study will explore how security is remaining as a potential risk for cloud users across the globe by listing some of the cloud applications. Some viable solutions and security measures that could help us in analyzing cloud security threats are reviewed. The analyzed solutions include profound analytical thinking on how to render the solutions more impactful in each scenario. Several cloud security solutions are available to assist businesses in reducing costs and enhancing security. This study discover that if the risks are taken into consideration without any delay then the matter of solutions gets divided into four pillars, which will assist us in obtaining a more comprehensive knowledge. Visibility, compute-based security, network protection, and lastly identity security are referred as four pillars. 2022 IEEE. -
Cloud computing security for public cloud using ciphers and queueing petri nets
Cloud computing is the most used word in the domain of Information Technology, which is making colossal differentiations in the IT business. Nowadays, a massive proportion of data is being made, and the masters are discovering better approaches for managing this data. In a general sense, the word cloud implies a virtual database that stores immense data from various clients. There are three sorts of cloud public, private and hybrid. A public cloud is fundamental for general customers where customers can use cloud benefits free or by paying. Private cloud is for explicit associations, and hybrid one is in a broad sense a mix of both. Cloud offers diverse kind of administrations, for instance, IAAS, PAAS, SAAS where administrations like a stage for running any application, getting to the enormous information extra room, can use any application running under the cloud are given. The cloud similarly has a shortcoming concerning the security for the data warehouse. In a general sense, public cloud is inclined to data modification, data hacking and therefore, the integrity and privacy of the data are being undermined. Here in our work our motive is to verify the information that will be taken care of in the public cloud by using the multi-stage encryption. The estimation that we have proposed is a mix of Rail Fence cipher and Play Fair cipher. 2020, IJSTR. -
Cloud Computing with Machine Learning Could Help Us in the Early Diagnosis of Breast Cancer
The purpose of this study is to develop tools which could help the clinicians in the primary care hospitals with the early diagnosis of breast cancer diagnosis. Breast cancer is one of the leading forms of cancer in developing countries and often gets detected at the lateral stages. The detection of cancer at later stages results not only in pain and in agony to the patients but also puts lot of financial burden on the caregivers. In this work, we are presenting the preliminary results of the project code named BCDM (Breast Cancer Diagnosis using Machine Learning) developed using Mat lab. The algorithm developed in this research cancer work based on adaptive resonance theory. In this research work, we concluded how Art 1 network will help in classification of breast. The aim of the project is to eventually run the algorithm on a cloud computer and a clinician at a primary healthcare can use the system for the early diagnosis of the patients using web based interface from anywhere in the world. 2015 IEEE. -
Cloud Computing, Machine Learning, and Secure Data Sharing enabled through Blockchain
Blockchain technologies are sweeping the globe. Cloud computing & secure data sharing have emerged as new technologies, owing to current advances in machine learning. Conventional machine learning algorithms need the collection & processing of training information on centralized systems. With the introduction of new decentralized machine learning algorithms & cloud computing, ML on-device information learning is now a reality. IoT gadgets may outsource training duties to cloud computing services to enable AI at the network's perimeter. Furthermore, these dispersed edges intelligence architectures bring additional issues, also including consumer confidentiality & information safety. Blockchain has been proposed as a viable alternative to these issues. Blockchain, as a dispersed intelligent database, has evolved as a revolutionary innovation for the future phase of multiple industries' uses due to its decentralized, accessible, & safe structure. This system also includes trustworthy automatic scripting running & unchangeable information recordings. As quantum technologies have proven more viable in the latest days, blockchain has faced prospective challenges from quantum computations. In this paper, we summarize the existing material in the study fields of blockchain-based cloud computing, machine learning, and secure data sharing, as well as a basic orientation to post-quantum blockchain to offer a summary of the existing state-of-the-art in these cutting-edge innovations. 2022 IEEE. -
Cloud databases: A resilient and robust framework to dissolve vendor lock-in
Vendor lock-in has become a major concern in cloud computing. The term vendor lock-in describes situations where the subscriber cannot move data or services to another cloud vendor. This is due to heavy data volumes, high network bandwidth costs, dependencies, or unacceptable downtime. The proposed vendor lock-in dissolution practice migrates the database effectively in noticeably less time, regardless of database size and with a nominal network bandwidth requirement. Through this new practice, databases can be migrated to very remote regions, even across continents. A real-time implementation of the proposed method presented in this paper. 2024 The Author(s)