Hybrid optimization for efficient 6G IoT traffic management and multi-routing strategy
subject: Air pollution monitoring; Deep reinforcement learning; Dynamic cluster head selection; IoT; Mobile ad-hoc networking; Quantum entanglement and mobility metric; Quantum genetic algorithm; Quantum-inspired clustering algorithm
description: Efficient traffic management solutions in 6G communication systems face challenges as the scale of the Internet of Things (IoT) grows. This paper aims to yield an all-inclusive framework ensuring reliable air pollution monitoring throughout smart cities, capitalizing on leading-edge techniques to encourage large coverage, high-accuracy data, and scalability. Dynamic sensors deployed to mobile ad-hoc pieces of fire networking sensors adapt to ambient changes. To address this issue, we proposed the Quantum-inspired Clustering Algorithm (QCA) and Quantum Entanglement and Mobility Metric (MoM) to enhance the efficiency and stability of clustering. Improved the sustainability and durability of the network by incorporating Dynamic CH selection employing Deep Reinforcement Learning (DRL). Data was successfully routed using a hybrid Quantum Genetic Algorithm and Ant Colony Optimization (QGA-ACO) approach. Simulation results were implemented using the ns-3 simulation tool, and the proposed model outperformed the traditional methods in deployment coverage (95%), cluster stability index (0.97), and CH selection efficiency (95%). This work is expected to study the 6G communication systems as a key enabler for IoT applications and as the title legible name explains, the solutions smartly done in a practical and scalable way gives a systematic approach towards solving the IoT traffic, and multi-routing challenges that are intended to be addressed in 6G era delivering a robust IoT ecosystem in securing the process. The Author(s) 2024.
creator: Logeshwaran J.; Patel S.K.; Kumar O.P.; Al-Zahrani F.A.
source: Scientific Reports, Vol-14, No. 1
publisher: Nature Research
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 20452322; PubMed ID: 39730656
format: Online
language: English
type: Article
coverage: Logeshwaran J., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Patel S.K., Department of Computer Engineering, Marwadi University, Rajkot, 360003, India; Kumar O.P., Department of Electronics and Communication Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India; Al-Zahrani F.A., Computer Engineering Department, Umm Al-Qura University, Mecca, 24381, Saudi Arabia

Wound Healing, Cell Viability and Antimicrobial Potency of Mucus from Pangasianodon hypophthalmus
subject: Cell Cytotoxicity; Cell Migration; Mucus Extracts; Pangasianodon hypophthalmus; Wound Healing
description: Acute and chronic wounds are the major cause of death according to World Health Organization (WHO), in which, antimicrobial resistance is considered to be a major plight. In this regard, our study is aimed at developing an antimicrobial agent using the mucus of Pangasianodon hypophthalmus against the clinically resistant microbial pathogens and to evaluate the cell cytotoxicity and cell viability followed by an in vitro wound healing analysis. The evaluation of antimicrobial activity was performed through well diffusion method and micro dilution method. The cell cytotoxicity and cell viability were assessed using MTT assay. The cell migration and in vitro wound healing was performed using scratch assay. The acidic extracts of mucus showed antimicrobial activity against the eight different selected bacterial strains while the organic extract showed against seven bacterial strains. L929 showed a cell viability of 102.96% at a concentration of 75 g/mL and did not show cell toxicity effect up to the concentration of 300 g/mL. In the in vitro wound healing analysis, the cell migration rate was 99.27% in the treated cells while, the untreated showed only 94.68%. The current research work clearly shows that the mucus of P. hypophthalmus possesses antimicrobial activity and wound healing potency. Furthermore, gene expression analysis and in vivo trials have to be performed for a thorough understanding of the actual cellular mechanism of wound healing. The Author(s) 2024.
creator: Gomathy M.; Pappuswamy M.
source: Journal of Pure and Applied Microbiology, Vol-18, No. 4, pp. 2411-2423.
publisher: Journal of Pure and Applied Microbiology
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 9737510
format: Online
language: English
type: Article
coverage: Gomathy M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Pappuswamy M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India

Predictors of compassion competence among nurses working in the non-profit healthcare sector in India
subject: compassion competence; engagement; nurse practice environment; the non-profit sector
description: Objectives: For many years, the non-profit healthcare sector in India has been able to instil a sense of goodwill in the society through the provision of healthcare services, which are not only affordable and accessible, but also deliver compassionate care. This study was an attempt to evaluate the compassionate care and competence of the nurses working in India's non-profit healthcare sector, and to identify the predictive factors associated with their work environment and engagement. Methods: A cross-sectional survey of nurses working in the medical college hospitals managed by private trusts in the non-profit sector in India was conducted using an online questionnaire. The study was conducted in April 2021 after the second wave of the Covid-19 pandemic. Socio-demographic factors, compassion competence, nurse practice environment, and nurse engagement were assessed. Linear regression analysis was conducted to identify the variance and the predictors of compassion competence among Indian nurses. Results: We found that nurses practice environment (?=0.982, p=< .001) and engagement (?=0.842, p=< .001) predicted compassion competence during the Covid-19 pandemic. Moreover, nurse practice environment and engagement positively influenced compassion competence. Conclusion: There was a considerably high level of compassion competence among nurses working in the non-profit healthcare sector during the Covid-19 pandemic. The compassion phenomenon was statistically significantly impacted by the nurses practice environment and their level of engagement. Consequently, not only does competent compassion behaviour require positive work environments and engaged nurses, but also nurses compassion competence and its relationship with practice environment factors and engagement are critical in the non-profit healthcare sector in India. These findings support previous reviews that a high degree of compassion competence increases healthcare quality. 2024 Jismon, M. G., Rofin T. M., Th…
creator: George J.M.; Rofin T.M.; Thekkekkara J.V.; Asha K.C.; Vijesh P.V.
source: International Journal of Practice-Based Learning in Health and Social Care, Vol-12, No. 2, pp. 34-48.
publisher: Coventry University
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 20516223
format: Online
language: English
type: Article
coverage: George J.M., Christ University, NCR, Delhi, India; Rofin T.M., Indian Institute of Management, Mumbai, India; Thekkekkara J.V., St. Johns Medical College, Bangalore, India; Asha K.C., St. Thomas Hospital, Kerala, Chethipuzha, India; Vijesh P.V., Rajagiri College of Social Sciences, Kerala, Kalamassery, India

Polyaniline/Reduced Graphene Oxide/Zinc Oxide Hybrid Electrodes Fabricate by Combining Electrospinning/Electrospray Technique for Supercapacitors
subject: electrospinning/spraying; polyaniline; reduced graphene oxide; supercapacitor
description: This study presents the successful synthesis and characterization of polyaniline (PANI), PANI/reduced graphene oxide PANI/rGO (PR), and PANI/rGO/ZnO (PRZ) nanocomposites as electrode materials for supercapacitors. Employing electrospinning and electrospraying techniques, we developed nanofibrous composites with enhanced structural and electrochemical properties. The addition of rGO and ZnO in the PRZ composite significantly improved specific capacitance, stability, and charge-transfer efficiency. Electrochemical analyses, including cyclic voltammetry (CV), galvanostatic chargedischarge (GCD), and electrochemical impedance spectroscopy (EIS), revealed a peak specific capacitance of 845 F g?1 at 0.5 A g?1 for PRZ, outperforming PR (395 F g?1), and PANI (140 F g?1). These enhancements are attributed to the synergistic effects of carbon-based and pseudocapacitive components, resulting in higher conductivity, improved redox activity, and reduced internal resistance. Additionally, the PRZ composite exhibited excellent cyclic stability, retaining 89% of its capacitance over 5000 cycles, underscoring its durability and suitability for long-term energy storage applications. 2024 John Wiley & Sons Ltd.
creator: Simon S.; Sreeja P.B.
source: Energy Storage, Vol-6, No. 8
publisher: John Wiley and Sons Inc
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 25784862
format: Online
language: English
type: Article
coverage: Simon S., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, India; Sreeja P.B., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, India

Development of ?-carrageenan-based transparent and absorbent biodegradable films for wound dressing applications
subject: Absorbent wound dressings; Biodegradable wound dressing; Carrageenan wound dressing; Lyophilization; Solvent casting; Transparent wound dressing
description: Wound healing remains a critical challenge in healthcare, requiring advanced wound dressings with superior properties like transparency, absorbency, and biocompatibility. However, gaps exist in the use of marine-derived biopolymers for sustainable dressings. This study addresses this gap by combining ?-carrageenan (KC) with polyvinyl pyrrolidone (PVP) to develop transparent and absorbent biodegradable films through solvent casting and lyophilization techniques. Lyophilized films exhibited superior absorbency (9.17 g/cm2) and moisture management, with a water vapour transmission rate of 3990.67 g/m2/24 h, while solvent-cast films showed 78 % transmittance, enabling wound visualization. Mechanical testing revealed high tensile strength (31.5 MPa) and folding endurance (410 folds), ensuring durability. In vitro bactericidal assays confirmed efficacy against MRSA and E. coli, and in vivo tests on Wistar rats showed complete wound healing within 16 days with 91.1 % closure, outperforming untreated controls (76.7 %). This is the first study to explore lyophilized KC-PVP films for wound dressing applications, demonstrating potential for drug release, absorbency, and biodegradability. The innovative combination of biopolymers and fabrication techniques offers a sustainable, high-performance solution for wound care. 2024 Elsevier B.V.
creator: P A.; M R.J.; Joy J.M.; Visnuvinayagam S.; Remya S.; Mathew S.
source: International Journal of Biological Macromolecules, Vol-282
publisher: Elsevier B.V.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 1418130; PubMed ID: 39500428; CODEN: IJBMD
format: Online
language: English
type: Article
coverage: P A., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India, Department of Life Sciences, Christ University, Hosur Main Road, Bhavani Nagar, Karnataka, Bangalore, 560029, India; M R.J., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India; Joy J.M., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India, Department of Zoology, St. Teresa's College (Autonomous), Kerala, Ernakulam, 682011, India; Visnuvinayagam S., Microbiology, Fermentation and Biotechnology Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India; Remya S., Fish Processing Technology, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India; Mathew S., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India

Interplay between personality and attitude towards emotions with creative self concept among young adults
subject: Attitude towards emotions; Creative self concept; Creativity; Personality
description: Creative self-concept, intimately intertwined with the personality traits and plays a pivotal role in shaping individuals behavioral tendencies. Personality traits are largely responsible to influence how people perceive and navigate their creative abilities and self-expression. Moreover, attitudes towards emotions are another key facet of ones psychological landscape, impacting their inclination to perceive, process, and manage emotional experiences. Keeping this view, the present research attempts to explore the interconnectedness of creative self-concept, personality traits, and attitudes towards emotions among young adults, as well as focuses on exploring the predictors of creative self concept. For this purpose participants consisted of 200 young adults with a mean age of 21.20 years. Statistical outcomes revealed that creative self concept is a significant positive correlate of openness, conscientiousness, extraversion, agreeableness, attitude towards sadness, and attitude towards fear. Additionally, stepwise multiple regression analysis confirmed that openness (R2 = 27%), neuroticism (R2 = 2%) and attitude towards sadness (R2 = 2%) emerged as the significant predictors of creative self concept. Findings from the current research concludes that for young adults to have self-perception in the realm of creativity, personality traits and attitude towards emotions are significant contributing factors. By recognizing and employing these connections, individuals, educators, counselors, and practitioners can contribute to the cultivation of creativity and personal development. The Author(s) 2024.
creator: Gupta A.; Pathak S.; Panwar N.
source: BMC Psychology, Vol-12, No. 1
publisher: BioMed Central Ltd
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 20507283; PubMed ID: 39609701
format: Online
language: English
type: Article
coverage: Gupta A., Department of Psychology, Christ University, Delhi, NCR, India; Pathak S., Department of Psychology, Christ University, Delhi, NCR, India; Panwar N., Department of Psychology, Christ University, Delhi, NCR, India

Future of knowledge management in investment banking: Role of personal intelligent assistants
subject: investment banking; knowledge management; machine learning and industrial revolution; Personal intelligent assistants; structural equation modelling
description: Purpose: The studys objective focuses on investigating the involvement of Personal Intelligent Assistants (PIAs) in the Knowledge Management Process (KMP) in Investment Banking Companies leading to Industrial Revolution 5.0 leading to effective Organizational Knowledge Management. Design/Methodology: A Self-administered Survey Questionnaire was circulated to 695 employees of Investment Banking Companies operating in Bangalore, Mumbai, Delhi, Hyderabad, Chennai, and Pune using the Cluster Sampling method. The Covariance-based Structural Equation Modelling (CB-SEM) and Gradient Boosting Regression technique of Machine Learning were used to validate the hypothesis through JASP V.18 Software. Knowledge Creation, Knowledge Sharing, Knowledge Retrieval, Knowledge Application, and Organizational Knowledge Management are the crucial constructs considered in the study. Findings: The results revealed that Knowledge Application is the most influencing factor in effective organizational Knowledge management among the Investment Banks followed by Knowledge Sharing. It also emphasizes that they have a weak Knowledge retrieval process and minimal efforts taken to create knowledge within these banks. Implications: The PIAs can facilitate effective Data Analysis and research in managing vast data eliminating the repeated tasks in portfolio reconciliation and offering personalized recommendations to manage portfolios. It enables in compliance, risk management, client relationship management, real-time monitoring and leveraged decision-making through predictive analysis. The Author(s) 2024.
creator: Radhakrishna V.; Ravi H.; Elango S.; Divyashree V.; Jaganathan A.; Ponnusamy M.
source: Methodological Innovations, Vol-17, No. 4, pp. 229-247.
publisher: SAGE Publications Inc.
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 20597991
format: Online
language: English
type: Article
coverage: Radhakrishna V., Mount Carmel College, School of Commerce, Bangalore, India; Ravi H.; Elango S., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Divyashree V., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Jaganathan A., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Ponnusamy M., Sona College of Technology, Tamil Nadu, Salem, India

Understanding Labor Market Dynamics in Urban India Amidst the Pandemic: A Study Employing Supervised Learning Methods
subject: COVID-19; Employment; KNN algorithm; Labor market transition; Multinomial logistic regression; Urban India
description: This study provides insights into the dynamic job ladder and challenges in the Indian labor market, particularly when facing external shock. It examines the fluidity of job transitions among the employed, unemployed, and those not in the laborforce, focusing on the urban labor market of India during the COVID-19 pandemic. Using data from the 2020-21 Periodic Labour Force Survey, a longitudinal panel dataset was created to track individuals across four quarters, enabling the monitoring of their activity status. Employing K-Nearest Neighbour classification, the study identifies vulnerabilities in labor market engagement. It further explores factors driving transitions among the three states of labor market involvement, using a multinomial logistic model adjusted for selection bias. The research reveals significant movement within the labor force, with notable shifts between employment statuses. Even those currently employed are often vulnerable, at risk of detachment from the labor force at any time. Women were disproportionately affected, with evidence of discouraged worker effect, as many ceased jobs search duo to perceived job scarcity or unavailability of decent jobs. The study raised concerns about the sustainability of self-employment and the security of regular jobs. These findings expose enduring structural challenges exacerbated by the pandemic, calling for urgent action to address widespread unemployment, low female participation, and prevailing inequalities in the labor market. The Author(s), under exclusive licence to The Indian Econometric Society 2024.
creator: Singha Roy N.; Ghosh N.
source: Journal of Quantitative Economics, Vol-22, No. 4, pp. 883-909.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 9711554
format: Online
language: English
type: Article
coverage: Singha Roy N., Department of Economics, Christ University, Hosur Road, Bengaluru, 560029, India; Ghosh N., Bengaluru, India

Kannada translation and validation of Wellman and Liu's theory of mind scale and children's social understanding scale in preschoolers
subject: Children's Social Understanding Scale (CSUS); preschoolers; reliability; translation; validity; Wellman and Liu's Theory of Mind (ToM) scale
description: Background: Assessing theory of mind (ToM) in children is crucial for understanding social cognition. Wellman and Liu's ToM scale and the Children's Social Understanding Scale (CSUS) have been used to study ToM in children but are not available in the local language. Aim: This study aims to translate both scales into Kannada and validate them in preschool children. Methods: Following the rigorous WHO protocol, we meticulously translated and back-translated Wellman and Liu's ToM and CSUS into Kannada with the help of bilingual experts. Validation involved administering both scales to 118 preschool children aged 3 to 6 years from diverse urban and rural backgrounds in a cross-sectional study, ensuring the scales' applicability across different settings. Results: The Cronbach's alpha values for Wellman and Liu's ToM and the CSUS were 0.769 (95% CI 0.698 to 0.828) and 0.983 (95% CI 0.978 to 0.987), respectively, indicating high internal consistency. The test-retest reliability for Wellman and Liu's ToM scale domains ranged from 0.74 to 0.95, and for the CSUS, it was 0.99, demonstrating good reliability. Pearson's correlation between the domains of two scales ranged from 0.32 to 0.69, suggesting a moderate relationship. Conclusion: Our study findings demonstrate that Kannada translations of Wellman and Liu's ToM and CSUS have good internal consistency, test-retest reliability, and construct validity. These tools will be valuable for understanding social cognition in preschool children. 2024 Indian Journal of Psychiatry.
creator: Vishwanath R.; Kamath A.G.; Thomas N.; Praharaj S.K.
source: Indian Journal of Psychiatry, Vol-66, No. 12, pp. 1139-1144.
publisher: Wolters Kluwer Medknow Publications
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 195545; CODEN: IJRPA
format: Online
language: English
type: Article
coverage: Vishwanath R., Department Of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy Of Higher Education, Karnataka, Manipal, India; Kamath A.G., Department Of Psychiatry, Manipal Hospital, Karnataka, Mangalore, India; Thomas N., Consultant Clinical Psychologist, Karnataka, Mangalore, India, Department Of Psychology, Christ University, Karnataka, Bengaluru, India; Praharaj S.K., Department Of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy Of Higher Education, Karnataka, Manipal, India

Assessing Housing Preferences and Living Conditions of Migrant Workers in the Fringe Areas of Bengaluru City, India
subject: fringe areas; housing preferences; living conditions; migrant workers
description: This study investigates the housing preferences and its impact on living conditions of migrant industrial workers in the fringe areas of Bengaluru, India, where rapid urbanization and economic expansion have led to a significant demand for affordable housing. Using the Analytic Hierarchy Process (AHP), a multi-criteria decision-making framework, this study analyzed key factors influencing housing choices, such as proximity to the workplace, affordability, and access to essential amenities. Data were collected from 400 respondents through a combination of surveys, complimented by field observations and expert consultations. The findings indicate a strong preference for affordable housing close to employment hubs, with proximity to workplace emerging as the most critical criterion with a priority weight of 43.36%, followed by affordability with a priority weight of 12.47%. However, field insights reveal a trade-off with housing quality and living conditions. Many migrant workers are confined to overcrowded and poorly ventilated rental units, often provided by employers, which compromises their health and well-being. Our results contribute to the understanding of urban housing challenges in rapidly growing economies and emphasize the importance of sustainable, health-oriented housing policies that can mitigate environmental impacts and improve the quality of life for low-income migrant populations. 2024 by the authors.
creator: Chadchan J.; Hossiney N.; Tamil Selvan P.K.; Vijayan A.
source: Societies, Vol-14, No. 12
publisher: Multidisciplinary Digital Publishing Institute (MDPI)
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 20754698
format: Online
language: English
type: Article
coverage: Chadchan J., School of Architecture, Christ University, Bangalore, 560074, India; Hossiney N., Department of Civil Engineering, Christ University, Bangalore, 560074, India; Tamil Selvan P.K., School of Business and Management, Christ University, Bangalore, 560074, India; Vijayan A., School of Architecture, Christ University, Bangalore, 560074, India

HunterPrey Optimization Algorithm for Optimal Allocation of PV, DSTATCOM, and EVCS in Radial Distribution Systems
subject: intelligent algorithm; optimal allocation; radial distribution systems; voltage stability
description: This research article instigates a seminal approach for optimizing reactive power in renewable energy sources (RES) and electric vehicles (EVs) coalescing distribution systems, using the innovative HunterPrey Optimization (HPO) algorithm in conjunction with DSTATCOM as a reactive power compensator. The proposed methodology aims to minimize losses, enhance voltage stability, and improve overall system performance by simultaneously optimizing reactive power flows in photovoltaic RES (PV_DG), EV charging stations (EVCS), and DSTATCOMs within the distribution system. Simulations carried on IEEE-33, IEEE-69, and IEEE-118 test bus systems in MATLAB environment demonstrate that the HPO-based approach achieves a 91.47% and 96.61% reduction in real power losses and an improvement in voltage profile with a minimum voltage value of 0.991 and 0.994 p.u. (respectively for IEEE-33 and 69 bus systems), compared to traditional algorithms. These results highlight the lofty performance of the HPO method, effectively addressing the challenges posed by the integration of RES and EVs along with DSTATCOM. 2024 John Wiley & Sons Ltd.
creator: Pappu S.L.; Janamala V.; Veerendra A.S.
source: Advanced Control for Applications: Engineering and Industrial Systems, Vol-6, No. 4
publisher: John Wiley and Sons Inc
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 25780727
format: Online
language: English
type: Article
coverage: Pappu S.L., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Bangalore, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Bangalore, India; Veerendra A.S., Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

Efficient hydrogen evolution reaction performance of Ni substituted WS2 nanoflakes
subject: Hydrogen evolution reaction; Transition metal dichalcogenides; Two dimensional materials; WS2
description: We have investigated the structural, optical and electrocatalytic hydrogen evolution reaction (HER) performance of pristine, Co and Ni substituted WS2 nanoflakes synthesised by facile hydrothermal method. The XRD pattern confirms the formation of hexagonal WS2 for both pristine and substituted WS2 nanoflakes. The FESEM images validate the flake-like structure for both pristine and substituted WS2. In addition, we have also analysed the Raman and UV-Vis absorbance spectra of the samples. The electrocatalytic studies reveal that the nickel-substituted WS2 (Ni-WS2) nanoflakes show superior hydrogen evolution (HER) performance compared to cobalt-substituted WS2 (Co-WS2) nanoflakes. Hence, we have varied the Ni concentration and investigated the dependence of Ni content on the electrocatalytic performance. It is found that the electrocatalytic performance of the Ni-WS2 nanoflakes increases with an increase in Ni content owing to the modified edge structures. Thus, our studies suggest Ni substitution in WS2 nanostructures can boost electrocatalytic HER performance. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
creator: Joseph A.; Chacko L.; Sanal K.C.; Pineda-Aguilar N.; Jasna M.; Antony A.; Aneesh P.M.
source: Applied Physics A: Materials Science and Processing, Vol-130, No. 12
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 9478396; CODEN: APAMF
format: Online
language: English
type: Article
coverage: Joseph A., Department of Physics, Central University of Kerala, Tejaswini Hills, Kerala, Periye, Kasaragod, 671320, India; Chacko L., Department of Physics and Electronics, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India; Sanal K.C., Facultad de Ciencias Quicas, Universidad Automa de Nuevo Leon, San Nicolas de los Garza, Mexico; Pineda-Aguilar N., Centro de Investigaci en Materiales Avanzados, S.C. (CIMAV), Subsede Monterrey, Parque de Investigaci e Innovaci on Tecnolica, Apodaca, Mexico; Jasna M., Department of Physics, Cochin University of Science and Technology, Kerala, Kochi, 682022, India, Microelectronics Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, FI-90014, Oulu, Finland; Antony A., Department of Physics, Cochin University of Science and Technology, Kerala, Kochi, 682022, India; Aneesh P.M., Department of Physics, Central University of Kerala, Tejaswini Hills, Kerala, Periye, Kasaragod, 671320, India

Web-based single session therapy training for mental health support providers: a mixed-methods evaluation study protocol
subject: Evaluation study design; Mixed method; Randomized control design; Single session therapy; Training
description: The growing mental health needs and constrained resources in low- and middle-income countries necessitate scalable solutions. Single Session Therapy (SST) is a global trend in brief and cost-effective options for mental health interventions. It involves a single planned session between mental health service provider and client. This study aims to present a protocol to develop and evaluate a culture specific web-based training program to equip mental health support providers with the skills and confidence to deliver SST. The study protocol uses a mixed-methods evaluation design through three phasesneed assessment where psychologists and social workers collaborate to identify training needs and co-create the program; development and expert validation of the web-based training program; and randomized control trial to evaluate the training, followed by in-depth discussions with participants. This study breaks new ground by empirically designing and evaluating a training program for SST. It uniquely co-designs and validates a culturally sensitive SST training program, leveraging the expertise of a renowned international panel. This protocol goes beyond a blueprint for replicating this study, it serves as a foundational guide for nations seeking to implement effective SST training for their mental health professionals, preventing duplication of efforts. The Author(s) 2024.
creator: Joseph J.; Rajan S.K.; Sudhesh N.T.; Krishnan U.
source: Discover Mental Health, Vol-4, No. 1
publisher: Springer Nature
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 27314383
format: Online
language: English
type: Article
coverage: Joseph J., School of Psychological Sciences, Christ University, Bangalore, 560029, India; Rajan S.K., School of Psychological Sciences, Christ University, Bangalore, 560029, India; Sudhesh N.T., School of Psychological Sciences, Christ University, Bangalore, 560029, India; Krishnan U., School of Psychological Sciences, Christ University, Bangalore, 560029, India

Bio-Inspired Energy Storage Electrode: Utilizing Co3O4 Hollow Spheres Derived from Sugarcane Bagasse Extract Synthesis Via Hydrothermal Route
subject: ASC device; Co3O4-hollow spheres; Energy storage; Sugarcane bagasse
description: Recent research has explored the utilization of sugarcane bagasse, a bio-industrial waste, to fabricate energy storage devices due to ecofriendly nature, low cost with industrial scale production. In this investigation, cobalt oxide hollow spheres (Co3O4 HSs) were synthesized from waste sugarcane bagasse extract with the carbon spheres (CSs) act as template. The main component of sucrose (C12H22O11) linked with cellulose fibers and other oxygenic functional groups were used to prepare CSs. Previously, a metal precursor (Co(NO3)2.6H2O) was mixed with sugarcane bagasse extract and subjected to a hydrothermal process, resulting in uniform-sized metal CSs. The uniform sized Co3O4 HSs were formed by calcined metal CSs. The calcination temperature plays a crucial role to eliminating implanted carbon material on inter surface area of the metal oxide, shaping the Co3O4 HSs. Structural, vibrational, morphology and elemental analyses were confirmed by X-ray diffraction (XRD), Fourier transformed infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), respectively. Electrochemical tests show improved ion transport and low resistance, leading to high capacitance in asymmetric supercapacitor (ASC) devices. Subsequently, for asymmetric supercapacitor (ASC) devices, using with Co3O4 HSs has function of cathode and activated carbon (AC) as anode, the devices demonstrated impressive results of 33.1 Fg? 1 at 1 Ag? 1, 86.8% retention after 4,000 cycles, as well as the energy density and power density of 5.9W h kg? 1 at 1500W kg? 1. The Co3O4 HSs||AC device exhibits promising energy storage properties for future applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
creator: Nagavenkatesh K.R.; Murugesan M.; Sambathkumar C.; Devendran P.; Nallamuthu N.; Krishna Kumar M.
source: Journal of Inorganic and Organometallic Polymers and Materials, Vol-34, No. 12, pp. 6088-6101.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 15741443
format: Online
language: English
type: Article
coverage: Nagavenkatesh K.R., Department of Physics, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, Virudhunagar, 626 126, India; Murugesan M., Department of Physics, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, Virudhunagar, 626 126, India; Sambathkumar C., Department of Physics, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, Virudhunagar, 626 126, India; Devendran P., Department of Physics, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, Virudhunagar, 626 126, India; Nallamuthu N., Department of Physics, Dayananda Sagar Academy of Technology and Management, Udayapura, Karnataka, Bangalore, 560 082, India; Krishna Kumar M., Department of Physics and Electronics, CHRIST (Deemed to be University, Karnataka, Bangalore, 560 029, India

EDSSR: a secure and power-aware opportunistic routing scheme for WSNs
description: Motivated by the pivotal role of routing in Wireless Sensor Networks (WSNs) and the prevalent security vulnerabilities arising from existing protocols, this research tackles the inherent challenges of securing WSNs. Many current WSN routing protocols prioritize computational efficiency but lack robust security measures, making them susceptible to exploitation by malicious actors. The prevalence of reactive protocols, chosen for their lower bandwidth consumption, exacerbates security concerns, as proactive alternatives require more resources for maintaining network routes. Additionally, the ad hoc nature and energy constraints of WSNs render conventional security models designed for wired and wireless networks unsuitable. In response to these limitations, this paper introduces the Secured Energy-Efficient Opportunistic Routing Scheme for Sustainable WSNs (EDSSR). EDSSR is designed to enhance security in WSNs by continuously updating neighbor information and validating the legitimacy of standard routing parameters. Critically, the protocol is power-aware, recognizing the vital importance of energy considerations in the constrained environment of WSNs. To assess the efficacy of EDSSR in mitigating WSN vulnerabilities, simulation experiments were conducted, evaluating the protocols performance on key metrics such as throughput, average End-to-End delay (delay), energy consumption (EC), network lifetime (alive nodes), and malware detection rate. The results demonstrate that the EDSSR protocol significantly improves performance. It shows substantial gains in sum goodput relative to throughput, average delay, EC, and alive nodes. Specifically, the EDSSR protocol is 23% faster than DLAMD and 1013% faster than EEFCR. Additionally, the malware detection rate increases by 23%. The Author(s) 2024.
creator: Yang R.; Patil M.A.; Narayana P.; Jayaram D.; Keerthi K.; SudhakarYadav N.; Chithaluru P.; Kumar S.; Elminaam D.S.A.; Alsekait D.M.
source: Scientific Reports, Vol-14, No. 1
publisher: Nature Research
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 20452322; PubMed ID: 39562589
format: Online
language: English
type: Article
coverage: Yang R., FESCO Adecco, Shanghai, 200000, China; Patil M.A., Department of Computer Science and Engineering, Christ (Deemed to be University) School of Engineering and Technology, Kengeri, Karnataka, Bengaluru, 560074, India, Department of Computer Science and Engineering, G. Narayanamma Institute of Technology and Science, Shaikpet, Telangana, Hyderabad, 500104, India; Narayana P., Stanley College of Engineering and Technology for Women, Hyderabad, Abids, India; Jayaram D., Department of Information Technology, Chaitanya Bharathi Institute of Technology (A), Hyderabad, Gandipet, 500075, India; Keerthi K., Methodist College of Engineering and Technology, Hyderabad, Abids, India; SudhakarYadav N., Department of Information Technology, Chaitanya Bharathi Institute of Technology (A), Hyderabad, Gandipet, 500075, India; Chithaluru P., Department of Information Technology, Mahatma Gandhi Institute of Technology, Telangana, 500075, India; Kumar S., Department of Computer Engineering and Applications, GLA University, Mathura, India, Department of Computer Science, Graphic Era Hill University, Dehradun, 248001, India; Elminaam D.S.A., Faculty of Computers and Artificial Intelligence, Benha University, Banha, Egypt, Jadara Research Center, Jadara University, Irbid, 21110, Jordan; Alsekait D.M., Department of Computer Science, Applied College, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia

Detection and identification of un-uniformed shape text from blurred video frames
subject: Deep neural networks; Optical character recognition; Region convolution neural networks; Region of interest; Text detection; Text recognition
description: The identification and recognition of text from video frames have received a lot of attention recently, that makes many computer vision-based applications conceivable. In this study, we modify the picture mask and the original identification of the mask region convolution neural network and permit detection in three levels, including holistic, sequence, and at the level of pixels. To identify the texts and determine the text forms, semantics at the pixel and holistic levels can be used. With masking and detection, existences of the character and the word are separated and recognised. In addition, text detection using the results of 2-D feature space instance segmentation is done. Moreover, we explore text recognition using an attention-based optical character recognition (OCR) method with mask region convolution neural networks (R-CNN) to address and detect the problem of smaller and blurrier texts at the sequential level. Using attribute maps of the word occurrences in sequence to seq, the OCR method calculates the character sequence. At last, a fine-grained learning strategy is proposed to constructs models at word level using the annotated datasets, resulting in the training of a more precise and reliable model. The well-known benchmark datasets ICDAR 2013 and ICDAR 2015 are used to test our suggested methodology. 2024, Institute of Advanced Engineering and Science. All rights reserved.
creator: Channegowda R.H.; Srinivasaiah R.; Jankatti S.K.; Meenakshi; Jinachandra N.S.; Hombegowda R.K.T.
source: IAES International Journal of Artificial Intelligence, Vol-13, No. 4, pp. 4795-4805.
publisher: Institute of Advanced Engineering and Science
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 20894872
format: Online
language: English
type: Article
coverage: Channegowda R.H., Department of Electronics and Communication Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India; Srinivasaiah R., Department of Computer Science and Engineering, CHRIST Deemed to be University, Bengaluru, India; Jankatti S.K., Department of Computer Science and Technology, Dayananda Sagar University, Bengaluru, India; Meenakshi, Department of Computer Science and Engineering, RNS Institute of Technology, Bengaluru, India; Jinachandra N.S., Department of Mechanical Engineering, CHRIST Deemed to be University, Bengaluru, India; Hombegowda R.K.T., Department of Electronics and Communication Engineering, Ghousia College of Engineering, Ramanagara, India

Multi-Model Traffic Forecasting in Smart Cities using Graph Neural Networks and Transformer-based Multi-Source Visual Fusion for Intelligent Transportation Management
subject: Congestion forecasting; Graph neural networks; Multi-modal traffic forecasting; Recursive feature elimination; Smart cities; Transformer-based multi-source visual fusion
description: In the intelligent transportation management of smart cities, traffic forecasting is crucial. The optimization of traffic flow, reduction of congestion, and improvement of theoverall transportation systemefficiency all depend on accurate traffic pattern projections. In order to overcome the difficulties causedby the complexity and diversity of urban traffic dynamics, this research suggests a unique method for multi-modal traffic forecasting combining Graph Neural Networks (GNNs) and Transformer-based multi-source visual fusion. GNNs are employed in this method to capture the spatial connections betweenvarious road segments and to properly reflect the basic structure of the road network. The model's ability to effectively analyse traffic dynamics and relationships between nearby locations is enhanced by graphsrepresenting the road layout, which also increases theoutcome of traffic predictions. Recursive Feature Elimination (RFE) is employed to improve the model's feature selection process and choose the most pertinent features for traffic prediction, producing forecasts that are more effective and precise. Utilizing real-time data, the performance of the suggested strategywasassessed, enabling it to adjust to shifting traffic patterns and deliver precise projections for intelligent transportation management. The empirical outcomes show exceptional results ofperformance metrics for the proposed approach, achieving anamazing accuracy of 99%. The resultsshow that the suggested techniques findings have the ability to anticipate traffic and exhibit a superior level of reliability whichsupports efficient transportation management in smart cities. The Author(s), under exclusive licence to Intelligent Transportation Systems Japan 2024.
creator: Dhanasekaran S.; Gopal D.; Logeshwaran J.; Ramya N.; Salau A.O.
source: International Journal of Intelligent Transportation Systems Research, Vol-22, No. 3, pp. 518-541.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 13488503
format: Online
language: English
type: Article
coverage: Dhanasekaran S., Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Tamil Nadu, Coimbatore, 641202, India; Gopal D., Department of Electronics and Communication Engineering, AVN Institute of Engineering and Technology, Hyderabad, India; Logeshwaran J., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Ramya N., Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, India; Salau A.O., Department of Electrical/Electronics and Computer Engineering, Afe Babalola University, Ado-Ekiti, Nigeria, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Tamil Nadu, Chennai, India

Deciphering the non-linear nexus between government size and inflation in MENA countries: an application of dynamic-panel threshold model
subject: Dynamic panel threshold; Government size; Inflation rate; MENA; Nonlinear relationship
description: Contradictory to conventional economic theory, which foresees any increase in the size of government as inflationary, this article provides evidence that the reaction of price levels to changes in the size of government is nonlinear. The price levels do not necessarily increase in response to a rise in the size of the government but only up to a certain threshold or optimal level. Accordingly, this paper utilizes the dynamic panel threshold model to examine the threshold effects of government size (measured as government final consumption expenditure as a proportion of GDP) on inflation using a sample of 10 selected MENA countries from 1980 to 2019. The findings of this study stand out in several ways. First, the results support the nonlinear relationship between government size and inflation in the study area. Second, the government sizes estimated threshold level is equivalent to 12.46%. Third, government size negatively impacts inflation in the regime of small governments up to the threshold level. The impact turns positive once the government size goes beyond the threshold level in a regime of large size of government. These findings have ramifications for the conduct of fiscal policy. Policymakers in the MENA region can increase the size of government till it reaches the threshold level without exerting any upward pressure on price levels. The Author(s) 2024.
creator: Tariq A.; Amin A.; Ahmad M.
source: Journal of Economic Structures, Vol-13, No. 1
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 21932409
format: Online
language: English
type: Article
coverage: Tariq A., Department of Economics, Central University of Kashmir, Ganderbal, 191201, India, Department of Data Science, Christ University, Bengaluru, India; Amin A., Department of Economics, Central University of Kashmir, Ganderbal, 191201, India; Ahmad M., Department of Economics, Central University of Kashmir, Ganderbal, 191201, India

Unveiling the Dual Potential of the MoS2@VS2 Nanocomposite as an Efficient Electrocatalyst for Hydrogen and Oxygen Evolution Reactions
subject: 2D materials; density functional theory; electrocatalysts; hydrogen evolution reaction; oxygen evolution reaction
description: Clean and reliable energy sources are essential amidst growing environmental concerns and impending energy shortages. Creating efficient and affordable catalysts for water splitting is a challenging yet viable option for renewable energy storage. Traditional platinum-based catalysts, while highly active, are quite expensive. Our study introduces two-dimensional (2D) MoS2@VS2 nanocomposites, developed using hydrothermal technique, as a bifunctional catalyst for the electrolysis of water into valuable products. Structural studies revealed the formation of MoS2@VS2 nanocomposites with a nanoflake-like structure, where MoS2 nanosheets grow on the VS2 surface. This 2D-based electrocatalyst demonstrated exceptional reaction kinetics, with low overpotentials of 265 mV for the hydrogen evolution reaction (HER) and 300 mV for the oxygen evolution reaction (OER) at 10 mA/cm2. Furthermore, the electrocatalyst displayed small Tafel slopes of 65 mV/dec and 103 mV/dec for HER and OER, respectively, along with excellent stability. The unprecedented catalytic activity stems from the synergistic effect between semiconducting MoS2 and metallic VS2. Density functional theory calculations confirmed that this synergy enhances the electrical conductivity, facilitating efficient electron transfer during the reaction and providing an abundance of exposed active sites. These results mold MoS2@VS2 nanocomposites as promising electrocatalysts for overall water splitting, paving the way for sustainable energy future. 2024 American Chemical Society.
creator: Anju J.S.; Chacko L.; Sruthi T.; Gopika P.; Mathew V.; Aneesh P.M.
source: ACS Applied Energy Materials, Vol-7, No. 23, pp. 11184-11194.
publisher: American Chemical Society
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 25740962
format: Online
language: English
type: Article
coverage: Anju J.S., Department of Physics, Central University of Kerala, Kasaragod, Kerala, Periye, 671320, India; Chacko L., Department of Physics and Electronics, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Sruthi T., Department of Physics, Central University of Kerala, Kasaragod, Kerala, Periye, 671320, India; Gopika P., Department of Physics, Central University of Kerala, Kasaragod, Kerala, Periye, 671320, India; Mathew V., Department of Physics, Central University of Kerala, Kasaragod, Kerala, Periye, 671320, India; Aneesh P.M., Department of Physics, Central University of Kerala, Kasaragod, Kerala, Periye, 671320, India

A framework for natural resource management with geospatial machine learning: a case study of the 2021 Almora forest fires
subject: Aerosol; Biomass burning; Climate change; Natural hazards; Wildfires
description: Background: Wildfires have a substantial impact on air quality and ecosystems by releasing greenhouse gases (GHGs), trace gases, and aerosols into the atmosphere. These wildfires produce both light-absorbing and merely scattering aerosols that can act as cloud condensation nuclei, altering cloud reflectivity, cloud lifetime, and precipitation frequency. Uttarakhand province in India experiences frequent wildfires that affect its protected ecosystems. Thus, a natural resource management system is needed in this region to assess the impact of wildfire hazards on land and atmosphere. We conducted an analysis of a severe fire event that occurred between January and April 2021 in the Kumaun region of Uttarakhand, by utilizing open-source geospatial data. Near-real-time satellite observations of pre- and post-fire conditions within the study area were used to detect changes in land and atmosphere. Supervised machine learning algorithm was also implemented to estimate burned above ground biomass (AGB) to monitor biomass stock. Results: The study found that 21.75% of the total burned area burned with moderate to high severity, resulting in a decreased Soil Adjusted Vegetation Index value (> 0.3), a reduced Normalized Differential Moisture Index value (> 0.4), and a lowered Normalized Differential Vegetation Index (> 0.5). The AGB estimate demonstrated a significant simple determination (r2 = 0.001702) and probability (P < 2.2 10?16), along with a positive correlation (r ? 0.24) with vegetation and soil indices. The algorithm predicted that 17.56 tonnes of biomass per hectare burned in the Kumaun forests. This fire incident resulted in increased emissions of carbon dioxide (CO2; ~ 0.8 10?4kgcarbonh?1), methane (CH4; ~ 200 10?9mol fraction in dry air), carbon monoxide (CO; 2000 1015moleculescm?2 total column), and formaldehyde (HCHO; 3500 1013moleculescm?2 total column), along with increased aerosol optical thickness (varying from 0.2 to 0.5). Conclusions: We believe that our…
creator: Tiwari A.; Nanjundan P.; Kumar R.R.; Soni V.K.
source: Fire Ecology, Vol-20, No. 1
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 19339747
format: Online
language: English
type: Article
coverage: Tiwari A., Christ University, Lavasa, Pune, 412112, India, India Meteorological Department, Shimla Office, Shivajinagar, Pune, 411005, India; Nanjundan P., Christ University, Lavasa, Pune, 412112, India; Kumar R.R., India Meteorological Department, Shimla Office, Shivajinagar, Pune, 411005, India; Soni V.K., India Meteorological Department, Mausam Bhawan, Lodhi Road, New Delhi, 110003, India