Evidence-Based Interventions for Improved Psychosocial Outcomes in Harmful Alcohol Use: A Scoping Review
EEG neurofeedback; harmful alcohol use; psychosocial intervention; psychosocial outcomes; quality of life (QoL)
Background. Harmful alcohol use is defined as a drinking pattern that lasts at least one month or has occurred often during the preceding 12 months and that negatively impacts multiple facets of life. It has a high recurrence rate and a poor prognosis, despite the availability of cognitive-behavioral and psychosocial therapy. Emerging neuromodulation techniques for treating harmful alcohol use are gaining traction in the field of psychotherapy, but knowing their efficacy in terms of psychosocial outcomes necessitates an adjuvant approach. This scoping review aims to investigate the existing evidence on the effectiveness of various psychosocial interventions that improve quality of life (QoL) dimensions in conjunction with neurotherapies for individuals with harmful alcohol use. Methods. The review utilized a five-stage technique to search for research papers from 2000 to 2022. After screening and reviewing 41 full-text papers, 29 were found to meet the inclusion criteria. Conclusion. The articles highlighted the advantages of integrated therapeutic interventions such as motivation enhancement therapy, cognitive behavior therapy, neurotherapy, multimodal therapy, supportive therapy, and 12-step facilitation programs. However, limited studies have explored the effectiveness of combining neurotherapy with psychosocial interventions. Implications. Future research should focus on the efficacy of combining neurofeedback with psychosocial therapies to improve QoL for individuals with harmful alcohol use. 2024. Thakuria and Bennett.
NeuroRegulation, Vol-11, No. 2, pp. 172-183.
International Society for Neurofeedback and Research
https://doi.org/10.15540/nr.11.2.172 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199350917&doi=10.15540%2fnr.11.2.172&partnerID=40&md5=820454a9df5fd6e33839a53395789dbf
Thakuria K., Christ University, Department of Psychology, Bangalore, India, Department of Psychology, CHRIST (Deemed to be University, Hosur Road, Bangalore, India; Bennett C.N., Christ University, Department of Psychology, Bangalore, India
Food Additives and Evolved Methods of Detection: A Review
Analysis of food additives; colorants; detection; food additives; food preservation
Food additives are essential constituents of food products in the modern world. The necessity of food processing went up rapidly as to meet requirements including, imparting desirable properties like preservation, enhancement and regulation of color and taste. The methods of identification and analysis of such substances are crucial. With the advancement of technology, a variety of techniques are emerging for this purpose which have many advantages over the existing conventional ways. This review is on different kinds of additives used in the food industry and few prominent methods for their determination ranging from conventional chromatographic techniques to the recently evolved nano-sensor techniques. 2024 Taylor & Francis Group, LLC.
Aiswarya P.S.; Thadathil D.A.; George L.; Varghese A.
Critical Reviews in Analytical Chemistry
Aiswarya P.S., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Thadathil D.A., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; George L., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India; Varghese A., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India
A Thorough Review of Deep Learning in Autism Spectrum Disorder Detection: From Data to Diagnosis
ABIDE dataset; ASGCN (adaptive spatiotemporal; atlases; autism spectrum disorder (ASD); comprehensive review; Deep learning; electroencephalography (EEG); graph convolution network); LeNet; neuroimaging modalities; preprocessing tools; resting-state functional magnetic resonance imaging (rsfMRI); structural MRI (sMRI); task-based fMRI (tfMRI)
Background: Autism Spectrum Disorder (ASD) is a multifaceted neurodevelop-mental condition with significant heterogeneity in its clinical presentation. Timely and precise identification of ASD is crucial for effective intervention and assistance. Recent advances in deep learning techniques have shown promise in enhancing the accuracy of ASD detection. Objective: This comprehensive review aims to provide an overview of various deep learning methods employed in detecting ASD, utilizing diverse neuroimaging modalities. We analyze a range of studies that use resting-state functional Magnetic Resonance Imaging (rsfMRI), structural MRI (sMRI), task-based fMRI (tfMRI), and electroencephalography (EEG). This paper aims to assess the effectiveness of these techniques based on criteria such as accuracy, sensitiv-ity, specificity, and computational efficiency. Methods: We systematically review studies investigating ASD detection using deep learning across different neuroimaging modalities. These studies utilize various preprocessing tools, at-lases, feature extraction techniques, and classification algorithms. The performance metrics of interest include accuracy, sensitivity, specificity, precision, F1-score, recall, and area under the curve (AUC). Results: The review covers a wide range of studies, each with its own dataset and methodolo-gy. Notable findings include a study employing rsfMRI data from ABIDE that achieved an accuracy of 80% using LeNet. Another study using rsfMRI data from ABIDE-II achieved an im-pressive accuracy of 95.4% with the ASGCN deep learning model. Studies utilizing different modalities, such as EEG and sMRI, also reported high accuracies ranging from 74% to 95%. Conclusion: Deep learning-based approaches for ASD detection have demonstrated significant potential across multiple neuroimaging modalities. These methods offer a more objective and data-driven approach to diagnosis, potentially reducing the subjectivity associated with clinical evaluations. However, challenges remain, including the need for larger and more diverse da-tasets, model interpretability, and clinical validation. The field of deep learning in ASD diagnosis continues to evolve, holding promise for early and accurate identification of individuals with ASD, which is crucial for timely intervention and support. 2024 Bentham Science Publishers.
Recent Advances in Computer Science and Communications, Vol-17, No. 8, pp. 73-91.
Lamani M.R., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India; Pernabas J.B., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India
Can financial markets help attain carbon goals? Evidence from systematic literature review, bibliometric analysis and topic modelling
Bibliometric analysis; Carbon emission; Carbon performance; Finance; Financial market; PRISMA; Systematic literature review; Topic modelling
Purpose: This paper presents a conceptual framework based on an extensive literature review. The aim of this study is to deepen understanding of the relationship between carbon performance and the financial market by applying qualitative research approaches. Design/methodology/approach: The investigation has identified 372 articles sourced from Scopus databases, subjecting the bibliographic data to a comprehensive qualitativequantitative analysis. The research uses established protocols for a structured literature review, adhering to PRISMA guidelines, machine learning-based structural topic modelling using Python and bibliometric citation analysis. Findings: The results identified the leading academic authors, institutions and countries concerning carbon performance and financial markets literature. Quantitative studies dominate this research theme. The study has identified six knowledge clusters using topic modelling related to environmental reporting; price drivers of carbon markets; environmental policy and capital markets; financial development and carbon emissions; carbon risk and financial markets; and environmental performance and firm value. The results of the study also present the opportunities associated with carbon performance and the financial market and propose future research agendas on research through theory, characteristics, context and methodology. Practical implications: The results of the study offer insights to practitioners, researchers and academicians regarding scientific development, intricate relationships and the complexities involved in the intersection of carbon performance and financial markets. For policymakers, a better understanding of carbon performance and financial markets will contribute to designing policies to set up priorities for countering carbon emissions. Social implications: The study highlights the critical areas that require attention to limit greenhouse gas emissions and promote decarbonisation effectively. Policymakers can leverage these insights to develop targeted and evidence-based policies that facilitate the transition to a more sustainable and low-carbon economy. Originality/value: The study initially attempts to discuss the research stream on carbon performance and financial markets literature from a systematic literature review. 2024, Emerald Publishing Limited.
Dawar G.; Nagariya R.; Bhatia S.; Dhingra D.; Agrawal M.; Dhaundiyal P.
Sustainability Accounting, Management and Policy Journal
https://doi.org/10.1108/SAMPJ-05-2023-0319 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198852133&doi=10.1108%2fSAMPJ-05-2023-0319&partnerID=40&md5=9b48bc5dc7a712163aa2cb8364a3d335
Dawar G., School of Business and Management, Christ University, Bengaluru, India, Apeejay School of Management, Delhi, India; Nagariya R., School of Business and Management, Christ University, Bengaluru, India; Bhatia S., Department of Humanities, Delhi Technological University, Delhi, India; Dhingra D., Department of Management, Bennett University, Greater Noida, India, School of Management, BML Munjal University, Gurugram, India; Agrawal M., Jaipuria Institute of Management, Indore Campus, Indore, India; Dhaundiyal P., School of Business and Management, Christ University, Bengaluru, India
Parental Perspectives on Stress and Challenges in Raising Autistic Children: A Meta-Synthesis
Autism; Caregiver; Meta-synthesis; Parental perspectives; Parental stress
Raising autistic children can be challenging, and the current meta-synthesis explores the stress and challenges the parents encounter across life domains. Database searches (JSTOR, ProQuest, EBSCO, PsycINFO, and Google Scholar) were done using the SPIDER method, and 463 articles published between 2011 and 2021 were reviewed. The meta-synthesis adhered to the PRISMA guidelines and included 28 eligible studies centered on stress in parents of children up to the age of 12 years diagnosed with autism. This comprehensive analysis encompassed a collective participant pool of n-505 individuals. Eight stressors were derived using the line of argument synthesis method, which include parental stress due to emotional impact, diagnosis process, social stigma, financial aspects, work-life balance, lack of resources and social support, marital life, and academic setting. Multiple stressors exert a combined effect of individual and systemic factors across domains of life, leading to parental stress. Interventions must be designed considering the complex nature of the parental stress and its interaction with the environment. Psycho-education for awareness and empowerment contribute to parental well-being. The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.
Journal of Psychosocial Rehabilitation and Mental Health
https://doi.org/10.1007/s40737-024-00420-4 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201238651&doi=10.1007%2fs40737-024-00420-4&partnerID=40&md5=eabe24b38090c6dea8ef9df4357cdcd0
Dharanidharan D., Department of Psychology, Christ University, Bangalore, 560029, India; Kuruveettissery S., Department of Psychology, Christ University, Bangalore, 560029, India
Advancements in Sustainable Techniques for Dried Meat Production: an Updated Review
Antimicrobial; Dry meat; Health hazard; Non-thermal; Texture; Thermal
Dried meat is one of the ethnic and aesthetic food products popular among global civilizations and communities. The background of the production is associated with several methods practiced conventionally in the olden days. This review focused on investigating the advantages, challenges, research gaps, and technological intervention in dried meat production in the modern era. Moreover, it presented a gestalt of cutting-edge thermal and non-thermal food processing technologies and their effectiveness in extending shelf life. It delved into the specific characteristics of dried meat, including biochemical, sensory, and microbiological properties and processing techniques, and addressed the contamination sources. The pros and cons of various drying methods like hot-air drying, vacuum pulsed electric field, microwave-assisted techniques, and non-thermal drying processes are comprehended. The impact on meat's structural properties, nutritional value, shelf-life, quality control, and food safety are thoroughly presented. Moreover, the review explored the biochemical dynamics of the drying process and underscored the health risks associated with mycotoxin contamination in dried meat products. Furthermore, the study also presented the avenues of AI-based platforms and non-destructive technology for validating the quality of dried meat products. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Pushparaj K.; Balasubramanian B.; Meyyazhagan A.; Park S.; Arumugam V.A.; Pappuswamy M.; Bhotla H.K.; Liu W.-C.; Mousavi Khaneghah A.
Pushparaj K., Department of Zoology, School of Biosciences, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, Coimbatore, 641 043, India; Balasubramanian B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, 05006, South Korea; Meyyazhagan A., Department of Life Science, CHRIST University, Karnataka, Bengaluru, 560076, India; Park S., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, 05006, South Korea; Arumugam V.A., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, 641 046, India; Pappuswamy M., Department of Life Science, CHRIST University, Karnataka, Bengaluru, 560076, India; Bhotla H.K., Department of Zoology, School of Biosciences, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, Coimbatore, 641 043, India; Liu W.-C., Department of Animal Science, College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, 524088, China; Mousavi Khaneghah A., Faculty of Biotechnologies (BioTech), ITMO University, 191002, 9 Lomonosova Street, Saint Petersburg, Russian Federation, Halal Research Center of IRI, Iran Food and Drug Administration, Ministry of Health and Medical Education, Tehran, Iran
Deciphering the global research trends and significance of moral intelligence via bibliometric analysis
bibliometric and network analysis; biblioshiny analysis; moral injuries; moral intelligence; moral measurement; moral psychology; VOS view analysis
Introduction: Moral Intelligence (MI) as a concept has gained importance in recent years due to its wide applicability in individual, organizational, and clinical settings or even policy making. The present study employed Bibliometric analysis to understand the emerging topics associated with MI and its global research trend. This papers primary aim was (i) to explore the temporal and geographic growth trends of the research publication on MI. (ii) to identify the most prolific countries, institutions, and authors, working on MI, (iii) to identify the most frequent terminologies, (iv) to explore research topics and to provide insight into potential collaborations and future directions, and (v) to explore the significance of the concept of moral intelligence. Method: Bibliometric analysis was used to understand the emerging topics associated with MI and its global research trend using the SCOPUS database. VOS viewer and R were employed to analyze the result. Through the analysis conducted, the development of the construct over time was analyzed. Results: Results have shown that Iran and the United States and these two combined account for 53.16% of the total country-wise publications. Switzerland has the highest number of Multi-county publications. Authors from Iran and Switzerland have the most number of publications. Emerging topics like decision-making, machine ethics, moral agents, artificial ethics, co-evolution of human and artificial moral agents, green purchase intention etc were identified. Discussion: The application of MI in organisational decision-making, education policy, artificial intelligence and measurement of moral intelligence are important areas of application as per the results. Research interest in MI is projected to increase according to the results delineated in this article. Copyright 2024 Bagchi, Srivastava and Tushir.
https://doi.org/10.3389/fpsyg.2024.1425341 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204033212&doi=10.3389%2ffpsyg.2024.1425341&partnerID=40&md5=3c88adf5a747a16cb7ce25f414cbe5dd
Bagchi D., Department of Psychology, CHRIST (Deemed to be University) Delhi NCR, Delhi, India; Srivastava A., Jindal School of Psychology and Counselling, O.P. Jindal Global University, Haryana, Sonipat, India; Tushir B., Department of Psychology, CHRIST (Deemed to be University) Delhi NCR, Delhi, India
Women and Fairness: Navigating an Unfair World
Haque M.Z., Christ University, Bangalore, India; Taslim F., University of Dhaka, Dhaka, Bangladesh
A Comprehensive Review on Heart Disease Risk Prediction using Machine Learning and Deep Learning Algorithms
Cardiovascular diseases claim approximately 17.9 million lives annually, with heart attacks and strokes accounting for over 80% of these deaths. Key risk factors, including hypertension, hyperglycemia, dyslipidemia, and obesity, are identifiable, offering opportunities for timely intervention and reduced mortality. Early detection of heart disease enables individuals to adopt lifestyle changes or seek medical treatment. However, conventional diagnostic methods, such as electrocardiogramscommonly used in clinics and hospitals to detect abnormal heart rhythmsare not effective in identifying actual heart attacks. Additionally, angiography, while more precise, is an invasive method, financial strain on patients, and high chances of incorrect diagnosis, highlighting the need for alternative approaches. The main goal of this study was to assess the accuracy of machine learning techniques, including both individual and combined classifiers, in early detection of heart diseases. Furthermore, the study aims to highlight areas where additional research is necessary. Our investigation covers a decade period from 2014 to 2024, including a thorough review of pertinent literature from international conferences and top journals from the databases like Springer, ScienceDirect, IEEEXplore, Web of Science, PubMed, MDPI, Hindawi and so on. The following keywords were used to search the articles: heart disease risk, heart disease prediction, data mining, data preprocessing, machine learning algorithms, ensemble classifiers, deep learning algorithms, feature selection, hyperparameter optimization techniques. We examine the methodologies used and evaluate their effectiveness in predicting cardiovascular conditions. Our findings reveal notable progress in applying machine learning and deep learning in cardiology. The study concludes by proposing a framework that incorporates current machine learning techniques to enhance heart disease prediction. The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2024.
Karna V.V.R.; Karna V.R.; Janamala V.; Devana V.N.K.R.; Ch V.R.S.; Tummala A.B.
Archives of Computational Methods in Engineering
Springer Science and Business Media B.V.
https://doi.org/10.1007/s11831-024-10194-4 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207264313&doi=10.1007%2fs11831-024-10194-4&partnerID=40&md5=97deb939e860f00bbeb2adcb3f36a3ca
Karna V.V.R., Department of Electronics and Communication Engineering, Aditya University, Surampalem, 533437, India; Karna V.R., Department of Artificial Intelligence and Machine Learning, R V College of Engineering, Bengaluru, 560059, India; Janamala V., Department of Electrical and Electronics Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Devana V.N.K.R., Department of Electronics and Communication Engineering, Aditya University, Surampalem, 533437, India; Ch V.R.S., Department of Electronics and Communication Engineering, Aditya University, Surampalem, 533437, India; Tummala A.B., Department of Electronics and Communication Engineering, Chaitanya Bharati Institute of Technology, Hyderabad, 500075, India
A review on the efficacy of artificial intelligence for managing anxiety disorders
anxiety; artificial intelligence; GAD therapy; mental health disorder; natural language proceeding (NLP)
Anxiety disorders are psychiatric conditions characterized by prolonged and generalized anxiety experienced by individuals in response to various events or situations. At present, anxiety disorders are regarded as the most widespread psychiatric disorders globally. Medication and different types of psychotherapies are employed as the primary therapeutic modalities in clinical practice for the treatment of anxiety disorders. However, combining these two approaches is known to yield more significant benefits than medication alone. Nevertheless, there is a lack of resources and a limited availability of psychotherapy options in underdeveloped areas. Psychotherapy methods encompass relaxation techniques, controlled breathing exercises, visualization exercises, controlled exposure exercises, and cognitive interventions such as challenging negative thoughts. These methods are vital in the treatment of anxiety disorders, but executing them proficiently can be demanding. Moreover, individuals with distinct anxiety disorders are prescribed medications that may cause withdrawal symptoms in some instances. Additionally, there is inadequate availability of face-to-face psychotherapy and a restricted capacity to predict and monitor the health, behavioral, and environmental aspects of individuals with anxiety disorders during the initial phases. In recent years, there has been notable progress in developing and utilizing artificial intelligence (AI) based applications and environments to improve the precision and sensitivity of diagnosing and treating various categories of anxiety disorders. As a result, this study aims to establish the efficacy of AI-enabled environments in addressing the existing challenges in managing anxiety disorders, reducing reliance on medication, and investigating the potential advantages, issues, and opportunities of integrating AI-assisted healthcare for anxiety disorders and enabling personalized therapy. Copyright 2024 Das and Gavade.
Frontiers in Artificial Intelligence, Vol-7
https://doi.org/10.3389/frai.2024.1435895 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208569734&doi=10.3389%2ffrai.2024.1435895&partnerID=40&md5=7d38ccbcdead052165ae6f6a912f1e74
Das K.P., Department of Computer Science, Christ University, Bengaluru, India; Gavade P., Independent Practitioner, San Francisco, CA, United States
Impact of nanoparticles on immune cells and their potential applications in cancer immunotherapy
Antigen presentation; Dendritic cells; Macrophages; Nanotechnology; T lymphocytes
Nanoparticles represent a heterogeneous collection of materials, whether natural or synthetic, with dimensions aligning in the nanoscale. Because of their intense manifestation with the immune system, they can be harvested for numerous bio-medical and biotechnological advancements mainly in cancer treatment. This review article aims to scrutinize various types of nanoparticles that interact differently with immune cells like macrophages, dendritic cells, T lymphocytes, and natural killer (NK) cells. It also underscores the importance of knowing how nanoparticles influence immune cell functions, such as the production of cytokines and the presentation of antigens which are crucial for effective cancer immunotherapy. Hence overviews of bio-molecular mechanisms are provided. Nanoparticles can improve antigen presentation, boost T-cell responses, and overcome the immunosuppressive tumor environment. The regulatory mechanisms, signaling pathways, and nanoparticle characteristics are also presented for a comprehensive understanding. We review the nanotechnology platform options and challenges in nanoparticles-based immunotherapy, from an immunotherapy perspective including precise targeting, immune modulation, and potential toxicity, as well as personalized approaches based on individual patient and tumor characteristics. The development of emerging multifunctional nanoparticles and theranostic nanoparticles will provide new solutions for the precision and efficiency of cancer therapies in next-generation practice. Copyright 2024 The Authors.
Nair J.B.; Joseph A.M.; Sanoop P.; Joseph M.M.
https://doi.org/10.32604/biocell.2024.054879 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209541724&doi=10.32604%2fbiocell.2024.054879&partnerID=40&md5=d6d23215f101b56023d1218d51faf92b
Nair J.B., Leibniz Institute of Photonic Technology, Albert-Einstein-Stra 9, Jena, 07745, Germany, Serah Zines LLP, Sreeragam, Naduvannor P.O., Kerala, Kozhikkode, 673614, India; Joseph A.M., Department of Chemistry, Newman College, Kerala, Thodupuzha, 685585, India; Sanoop P., Department of Chemistry, Madanapalle Institute of Technology & Science (MITS), Madanapalle, Andhra Pradesh, Chittoor, 517325, India; Joseph M.M., Department of Life Sciences, CHRIST University, Karnataka, Bengaluru, 560029, India
Calcium Sulfide Based NanophosphorsA Review on Synthesis Techniques, Characterization and Applications
Biomedicine; Nanophosphors; Optoelectronics; Photoluminescence
Calcium sulfide (CaS) is a widely investigated alkaline earth sulfide nanophosphor with promising applications in optoelectronics and biomedical fields due to its excellent photoluminescence properties. The selection of the synthesis method is a crucial factor in determining the efficacy of nanophosphors for various applications. This review provides a comprehensive overview of the various synthesis techniques employed to develop CaS nanophosphors, including solvothermal, alkoxide, sol-gel, microwave, wet chemical co-precipitation, solid-state diffusion, and single-source precursor methods. The structural and optical properties of CaS nanophosphors are discussed in detail, highlighting the influence of different dopants on the emission color, which can be tuned from blue to red. The review also explores the potential applications of CaS nanophosphors in optoelectronics and biomedicine. This review serves as a valuable resource for researchers interested in developing CaS nanophosphors for various optoelectronic and biomedical applications, providing insights into the latest advancements and future prospects in this field. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Rekha S., Department of Physics, Maharajas College, Kerala, Ernakulam, 682011, India; Anila E.I., CHRIST (Deemed to be University), Bengaluru, 560029, India, Optoelectronic and Nanomaterials Research Laboratory, Department of Physics, Union Christian College, Kerala, Aluva, 683102, Philippines
Job Satisfaction Among Health-Care Practitioners: A Bibliometric Analysis
Bibliometric analysis; Burnout; Health Care; Job satisfaction; Turnover intention
Purpose: The study aims to throw light on job satisfaction among health-care practitioners based on the metadata of published literature from Scopus database with the help of bibliometric analysis. Design/methodology/approach: Metadata of 6,998 publications from the Scopus database were extracted. Bibliometric analysis was done with country-based co-authorship analysis, all keywords-based co-occurrence analysis, sources-based citation analysis, cited authors-based co-citation analysis, and term co-occurrence based on text data. Findings: It was found that United States had the highest number of publications at 2,037. The Journal Of Nursing Management had the highest number of publications (332). Term co-occurrence based on text data reveals that job satisfaction, turnover intention, work engagement, compassion fatigue, job stress, organizational commitment, job demand, job performance, workplace violence, job burnout, career satisfaction, safety climate, organizational support, transformational leadership, leadership style, discrimination, workplace bullying, and job strain are the most prominent terms. The paper also highlights the factors affecting job satisfaction of employees in the health-care sector. Conclusion: The paper tries to highlight the publication trends on the job satisfaction among health-care practitioners. Since health care is a primary sector, prosperity of other sectors in the society depends on the job satisfaction level of employees in this sector. 2024 Association for Radiologic & Imaging Nursing
https://doi.org/10.1016/j.jradnu.2024.10.009 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210055331&doi=10.1016%2fj.jradnu.2024.10.009&partnerID=40&md5=cde8d16b10d47ecb10fc9144fbab8206
Saha S., Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, Majitar, India; Saha S.K., School of Business and Management, CHRIST University, Bangalore, India; Jha A., Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, Majitar, India; Kumar S., Department of Management, Sikkim University, Sikkim, Gangtok, India
Advances in detecting non-steroidal anti-inflammatory drugs (NSAIDs) using molecular receptors and nanostructured assemblies
The detection and quantification of non-steroidal anti-inflammatory drugs (NSAIDs) are crucial due to their widespread use and potential impact on human health and the environment. This review provides a comprehensive survey of the recent advancements in sensing technologies for NSAIDs, focusing on molecular receptors and nanostructured assemblies. Molecular receptors based on different fluorescent molecules such as anthracene, naphthalimide, squaraine, quinoline, BINOL, etc. offer high selectivity and sensitivity for NSAID detection. In parallel, nanostructured assemblies including CdSe/ZnS, Cd/S quantum dots (QDs), carbon dot-containing imprinted polymers, Ag and Au nanoparticles (NPs), hydrogel-embedded chemosensors, etc. were utilized for NSAID detection. This review highlights the different binding pathways with the change of various photophysical properties combining molecular recognition elements with nanomaterials to develop innovative sensors that achieve rapid, sensitive, and selective detection of NSAIDs. The review also discusses current challenges and future prospects in the field and based on reported designed receptors and nanostructured assemblies. To the best of our knowledge, no reviews have been reported on this topic so far. Thus, this review will fruitfully guide researchers to design various new molecular receptors and nanostructured materials to detect NSAIDs. 2024 RSC.
https://doi.org/10.1039/d4md00661e https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210915254&doi=10.1039%2fd4md00661e&partnerID=40&md5=435c554310d50212810a3f7b7b76e10f
Das A.K., Department of Chemistry, Christ University, Hosur Road, Karnataka, Bangalore, 560029, India
Advances in suicide prevention: Critical overview of the gaps in suicide risk assessments, multimodal strategies, medicolegal risks, and the emerging evidence
evidence-based strategies; suicide; suicide prevention; suicide research; suicide risk assessment
The CDC reports that the United States has the highest suicide rates in over 80 years. Numerous public policies aimed at reducing the rising suicide rates, such as Aetna's partnership with the American Foundation for Suicide Prevention (AFSP) and the zero-suicide initiative, continue to challenge these attempts. It, therefore, remains imperative to explore the shortcomings of these efforts that hamper their efficiency in reducing suicide rates. Advancements in research over time have sparked scientific skepticism, encouraging re-evaluation of established concepts. The current paper tests prevalent assumptions and arguments to uncover a scientifically informed approach to addressing rising suicide rates in clinical settings. The Author(s), 2024.
Gupta M., Southwood Psychiatric Hospital, Pittsburgh, PA, United States; Khurana P., Department of Psychology, Christ University, Delhi NCR, India; Gupta N., Department of Psychiatry, Dayton's Children Hospital, Dayton, OH, United States
Breaking the Taboo: Addressing Menstrual Health Challenges in India
Menstrual Health; Menstrual Health Management; Menstruation; Sexually Transmitted Diseases
Although, menstrual hygiene is a topic as ancient as mankind, it has recently garnered attention because society is more willing to face its difficulties. Adolescents seldom talk about issues related to menstruation, menstruation disorders, menstrual cleanliness, and customs of their culture. There is little data on the hardships that teenage females bear from menstruation and their social norms. Adolescent health education must include information about menstruation. Menstrual behaviors are often greatly influenced by culture, awareness, and social condition. However, periods, behaviors, and problems are seldom included in health education programs for the younger girls in impoverished nations. International health organizations such as WHO and UNICEF have advised developing culturally responsive menstrual health management (MHM) as well as water, sanitation and hygiene (WASH) programs for the adolescent girls. Without an awareness of the preconceived notions and prejudices that teenage girls in poor nations currently have about menstruation, these programs cannot be implemented. The goal of this review from India was to record the myths that are currently in circulation concerning menstruation, menarche, and other understudied menstrual constraints. Our goal in conducting this review was to characterize and assess the effectiveness of menstruation education programs designed to provide early teenage girls the information and abilities they need to support menstrual health. RJPT All right reserved.
Jadhav P.; Hajare A.; Vatsa M.; Sebastian S.; Unnisa S.; Paliwal M.
Research Journal of Pharmacy and Technology, Vol-17, No. 11, pp. 5653-5659.
Research Journal of Pharmacy and Technology
Jadhav P., Krishna institute of pharmacy, Krishna Vishwa Vidyapeeth, Maharashtra, Karad, India; Hajare A., Bharati Vidyapeeth College of Pharmacy, Maharashtra, Palus, 416310, India; Vatsa M., Akhildev IPR and Research Services, UP, Greater Noida, India; Sebastian S., School of Business and Management, Christ University, India; Unnisa S., Department of Environmental Science, Osmania University, Telangana, Hyderabad, India; Paliwal M., Sri Balaji University, Maharashtra, Pune, India
Nanocarbon assisted green hydrogen production: Development and recent trends
Biohydrogen production; Electrochemical hydrogen production; Hydrogen; Photo-driven hydrogen production; Renewable and sustainable energy
The increasing consumption of energy and consequent fast depletion of fossil fuels and associated environmental challenges necessitate transformative innovations in the field of energy conversion. Owing to its exceptional energy density and zero emissions during combustion, Hydrogen is hailed as a promising source of clean and renewable energy that can replace fossil fuels in future energy conversion systems. Since Hydrogen is not readily available in the atmosphere, a variety of pathways have been followed for the evolution of Hydrogen from water and organic materials, which requires the involvement of catalysts to accelerate the reactions. Currently, noble metals and their alloys represent state-of-the-art materials for HER (Hydrogen Evolution Reaction), and the scarcity and high expense of such materials impose significant constraints on their widespread implementation in hydrogen production. In this context, nanocarbons and their composites for HER are worth exploring owing to their abundance, cost-effectiveness, eco-friendliness, exceptionally large surface-to-volume ratio, and excellent electrical and charge transfer properties. Here, three leading hydrogen production methods - biological, electrochemical, and photo-driven- are analyzed based on their characteristics, effectiveness, and limitations w.r.t. different nanocarbon materials. 2023 Hydrogen Energy Publications LLC
Kumar D.; Abraham J.E.; Varghese M.; George J.; Balachandran M.; Cherusseri J.
International Journal of Hydrogen Energy, Vol-50, pp. 118-141.
https://doi.org/10.1016/j.ijhydene.2023.07.257 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171159429&doi=10.1016%2fj.ijhydene.2023.07.257&partnerID=40&md5=98aa0948fe5525622323ea403a6c446b
Kumar D., Department of Physics, School of Sciences, JAIN (Deemed to be University), Karnataka, Bangalore, India; Abraham J.E., Department of Physics & Electronics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Varghese M., Department of Physics & Electronics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; George J., Department of Physics & Electronics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Balachandran M., Department of Physics & Electronics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Cherusseri J., Graphene and Advanced 2D Materials Research Group (GAMRG), School of Engineering and Technology, Sunway University, No.5 Jalan University, Bandar Sunway, Petaling Jaya, 47500, Malaysia
Growth of Indian cement industry, its environment impact and emerging alternatives
Cement; Concrete; Environment impact; Greenhouse gases; Gross domestic product (GDP0
The present study provides a detailed review on growth of Indian cement industry, its environmental implications of cement production and its significant influence on the future trajectory of the Indian concrete industry. The Indian cement sector, a vital contributor to the nation's economy, faces a dual challenge of meeting the growing demand for construction materials while mitigating its environmental footprint. The study delves into the industry's current status as the world's second-largest cement producer and its impact on various sectors, including employment, GDP contribution, and dependence on real estate and infrastructure. The paper identifies key obstacles hindering the Indian concrete industry's full potential, such as a slowdown in real estate development, low industrial investment, regulatory changes, and constraints on resource extraction. Despite the industry's promising growth, the looming threats from emerging technologies and increasing environmental concerns, particularly related to greenhouse gas emissions, necessitate a strategic shift towards sustainability. A central focus of the research is the urgent need for the Indian concrete industry to address its environmental impact, specifically the 7% contribution to global greenhouse gas emissions. The study explores the industry's role in creating carbon-neutral concrete by 2050 and emphasizes the importance of collaboration with policymakers, financial institutions like the International Finance Corporation (IFC), and end users in achieving this ambitious goal. The study reveals the comprehensive resource for industry stakeholders, and researchers interested in understanding the environmental implications of cement production and charting a sustainable course for the future of the Indian concrete industry and emerging alternatives. 2024, National Institute of Science Communication and Policy Research. All rights reserved.
Indian Journal of Engineering and Materials Sciences, Vol-31, No. 1, pp. 38-50.
National Institute of Science Communication and Policy Research
https://doi.org/10.56042/ijems.v31i1.7145 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190801816&doi=10.56042%2fijems.v31i1.7145&partnerID=40&md5=e6ba40d67d66fff7fea6148a41dd66f4
Mudgal V., Department of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560 076, India; Chellasamy A., Department of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560 076, India
Cassava (Manihot esculenta Crantz)A potential source of phytochemicals, food, and nutrition-An updated review
cassava; detoxification; fermentation; flour; polyphenols; starch
Cassava (Manihot esculenta Crantz) is believed to be an important staple food crop providing potential valuable food source as well as variety of phytoconstituents. Its starchy tubers provide a significant source of energy for around 500 million individuals. Among staple crops, it is regarded to be one of the top suppliers of carbohydrates. Its physicochemical qualities, as well as its availability, have made it a captivating food component. Cassava starch is a valuable raw material used to make a variety of both native and modified starch for cooking purposes. They have also been used for a variety of industrial uses. Cassava starch and flour have the potential to be valuable alternatives to rice, maize, and wheat crops. The advantages included being a staple diet for humans, a component of animal feeds, a raw ingredient for food processing, edible coatings, locally produced alcoholic beverages, and ethanol manufacturing. The roots consist of cyanogenic glycosides, which can lead to lethal cyanide poisoning if tubers arse not properly detoxified using different processing methods include washing, fermentation, boiling, peeling and chemical processing to escape toxin content. The current review summarizes cassava's bioactive components which could be a potential source of various pharmaceutical drugs as well as a source of traditional and modern food applications. 2024 The Authors. eFood published by John Wiley & Sons Australia, Ltd on behalf of International Association of Dietetic Nutrition and Safety.
Scaria S.S.; Balasubramanian B.; Meyyazhagan A.; Gangwar J.; Jaison J.P.; Kurian J.T.; Pushparaj K.; Pappuswamy M.; Park S.; Joseph K.S.
https://doi.org/10.1002/efd2.127 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183595988&doi=10.1002%2fefd2.127&partnerID=40&md5=a47ea108bb416b8b26671e898337bc27
Scaria S.S., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Balasubramanian B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Meyyazhagan A., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Gangwar J., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Jaison J.P., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Kurian J.T., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Pushparaj K., Department of Zoology, School of Biosciences, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, Coimbatore, India; Pappuswamy M., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Park S., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Joseph K.S., Department of Life Sciences, Christ University, Karnataka, Bangalore, India
Hardware in loop network simulators - An insight overview
Hardware-in-loop; network simulators; system-in-loop
Network simulation is a method of using software or a tool which can be used to mimic the network conditions that exist in pre-defined places. This kind of simulation allows the developers, designers, researchers and the network planners to intelligently plan, design, develop and test their applications or research work in changing network conditions. With varying network conditions either because of wireless nature or because of user mobility, it is very difficult to simulate the exact network conditions with the existing network simulators. These network simulators are flexible, re-usable and reliable. But they have a limitation of not being able to replicate the actual network conditions in the laboratories. This calls for a system in the loop or hardware in the loop concept to be extended to the network simulators. The idea of system in the loop is not new. In this paper, an overview with the fundamental understanding of the hardware-in-loop concept for network simulators, their applications and a review of the existing hardware-in-loop network simulators with their advantages and disadvantages is presented. 2024 World Scientific Publishing Company.
International Journal of Modeling, Simulation, and Scientific Computing, Vol-15, No. 1
Sushanth G., Department of Electronics and Communication Engineering, R. V. College of Engineering, Affiliated to Vtu, Belagavi, Karnataka, Bengaluru, India, Department of Electronics and Communication Engineering, Christ University, Karnataka, Bengaluru, India; Ravish Aradhya H.V., Department of Electronics and Communication Engineering, R. V. College of Engineering, Affiliated to Vtu, Belagavi, Karnataka, Bengaluru, India