Subsume Pediatric Headaches in Psychiatric Disorders? Critiques on Delphic Nosology, Diagnostic Conundrums, and Variability in the Interventions
Children and adolescents; Pediatric headaches; Primary headaches; Tension-type headache
Purpose of Review: Tension-type headache (TTH) continues to be the most prevalent type of headache across all age groups worldwide, and the global burden of migraine and TTH together account for 7% of all-cause years lived with disability (YLDs). TTH has been shown to have a prevalence of up to 80% in several studies and presents a wide range and high variability in clinical settings. The aim of this review is to identify gaps in diagnostics, nosology, and variability in the treatment of children and adolescents who present with headaches without an identifiable etiology. Recent Findings: Migraine and TTH have been debated to have more similarities than distinctions, increasing chances of misdiagnosis and leading to significant cases diagnosed as probable TTH or probable migraine. The lack of specificity and sensitivity for TTH classification often leads to the diagnosis being made by negating associated migraine symptoms. Although pathology is not well understood, some studies have suggested a neurological basis for TTH, in need of further validation. Some research indicates that nitric oxide signaling plays an integral part in the pain mechanisms related to TTH. Analgesics and non-steroidal anti-inflammatories are usually the first lines of treatment for children with recurring headaches, and additional treatment options include medication and behavioral therapies. Summary: With high prevalence and socioeconomic burden among children and adolescents, its essential to further study Tension-type headaches and secondary headaches without known cause and potential interventions. Treatment studies involving randomized controlled trials are also needed to test the efficacy of various treatments further. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Sharma A.; Khurana P.; Venkatraman A.; Gupta M.
Current Pain and Headache Reports, Vol-28, No. 7, pp. 651-662.
ISSN: 15313433; PubMed ID: 38367199; CODEN: CPHRG
Sharma A., Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States; Khurana P., Department of Psychology, Christ University, NCR, Delhi, India; Venkatraman A., Department of Pediatric Neurology, Geisinger Health System, Danville, PA, United States; Gupta M., Southwood Psychiatric Hospital, Pittsburgh, PA, United States
Strain-Induced Tribocatalytic Activity of 2D ZnO Quantum Dots
The use of low-frequency vibration or high-frequency ultrasound waves to create polarization and an inherent electric field in piezo-tribocatalysts has recently been shown to be a novel advanced oxidation process. In this study, we have demonstrated the synthesis of two-dimensional (2D) ZnO quantum dots (QDs) and their strain-induced tribocatalytic effect, where the triboelectric charges generated under the influence of friction and strain are used to facilitate the decomposition of organic dye molecules. The catalytic performance of 2D QD catalysts can be tuned by modulation of the strain-induced band-gap variation, which are typically regarded as the active sites. The underlying mechanism for the strain-induced catalytic performance is due to the presence of defective dipole moments. Detailed theoretical investigations reveal strain-induced charge-transfer-dependent catalytic properties of the 2D ZnO QD-polymer interface. We believe that the present work provides a fundamental understanding of the design of high-performance catalysis applications for water cleaning and emerging technologies. 2024 American Chemical Society.
Kumbhakar P.; Mishra S.; Kumbhakar P.; Barik R.K.; Tiwary C.S.; Singh A.K.
Journal of Physical Chemistry C, Vol-128, No. 25, pp. 10733-10741.
https://doi.org/10.1021/acs.jpcc.4c02798 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196007564&doi=10.1021%2facs.jpcc.4c02798&partnerID=40&md5=c7f9fdbba4bc095382fbed7a51334400
Kumbhakar P., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Mishra S., Materials Research Centre, Indian Institute of Science, Bangalore, 560012, India; Kumbhakar P., Nanoscience Laboratory, Department of Physics, National Institute of Technology, West Bengal, Durgapur, 713209, India; Barik R.K., Materials Research Centre, Indian Institute of Science, Bangalore, 560012, India; Tiwary C.S., Department of Metallurgical and Materials Engineering, Indian Institute of Technology, West Bengal, Kharagpur, 721302, India; Singh A.K., Materials Research Centre, Indian Institute of Science, Bangalore, 560012, India
Covid-19, macroeconomic policies, and analysis of the inflation-unemployment dynamics in india
COVID-19; Demand; Fiscal policy; India; Inflation; Monetary Policy; Shocks; Supply; Unemployment
Indian economy could largely withstand the adversities of 2008 recession, the signs of a downturn were clearer by 2017 following the arrival of twin policies, Demonetization as well as the Goods and Services Tax. The COVID-19 pandemic has deepened the crisis leading to a significant reduction in production and total expenditure. Although India has resorted to a combination of conventional policies monetary as well as fiscal injections to face the economic crisis, it has had serious negative consequences on production and employment. We investigate the nature of relationship between inflation and unemployment during the recession and the pandemic times using the non-linear regression analysis. The results reveal that the recessionary phase has given way to a stagflationary situation owing to inflation persistence in the short run. We suggest the usefulness of a more comprehensive term structure strat?gy to deal with the adverse supply shocks and policy failures. Indian Institute of Finance.
Karakunnel J.J.; Victor V.; Athan S.L.A.; Fekete-Farkas M.
Finance India, Vol-38, No. 2, pp. 339-356.
Karakunnel J.J., CHRIST (Deemed-to-be-University), The Department of Economics, Bhavani Nagar, SG Palya, Karnataka, Bangalore, 560029, India; Victor V., Indian Institute of Technology (IIT) Roorkee, Department of Humanities and Socieal Science, Roorkee, 247667, India; Athan S.L.A., CHRIST (Deemed-to-be-University), The Department of Economics, Bhavani Nagar, SG Palya, Karnataka, Bangalore, 560029, India; Fekete-Farkas M., Hungarian University of Agricultural and Life Sciences, Faculty of Economics and Social Science, Per Koly str. 1, Glo, 2100, Hungary
Shared Mobility and Indias Generation Z: Environmental Consciousness, Risks, and Attitudes
collaborative consumption; Generation Z; shared mobility; sharing economy; urban transport
Shared mobility platforms have built scalable digital marketplaces that facilitate the allocation and sharing of transportation and promote sustainable urban travel. Generation Zs attitude toward shared consumption is closely linked to their perceptions of the importance of sustainability. This study identifies Generation Zs awareness of shared mobility platforms in India and the factors that influence their use. Data were collected from 318 respondents from Generation Z in India and analyzed using partial least squares structural equation modeling. Findings indicate that Generation Zs intention to use shared mobility is influenced by environmental consciousness, social aspects, economic benefits, and perceived risks. Results also show that perceived risks have an indirect effect on intention, which is mediated by attitude. The novel conceptual model developed and tested in this research can be used to inform policies and business models for the adoption of shared mobility services for Generation Z, ultimately promoting more sustainable transportation systems and improved urban mobility. 2024 by the authors.
Sustainability (Switzerland), Vol-16, No. 12
Multidisciplinary Digital Publishing Institute (MDPI)
https://doi.org/10.3390/su16125258 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206111603&doi=10.3390%2fsu16125258&partnerID=40&md5=591db119fc1e2287850b74420ecbffc9
Palanichamy S., Department of Business and Management, Christ University, Bengaluru, 560076, India; Mohanty P., Department of Business and Management, Christ University, Bengaluru, 560076, India; Kennell J., School of Hospitality and Tourism Management, Faculty of Arts and Social Sciences, University of Surrey, GU2, Guildford, 7XH, United Kingdom
Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles
Coyote optimization algorithm Deep belief network Deep learning Fake profile detection Social network
Fake profile detection on social media is a critical task intended for detecting and alleviating the existence of deceptive or fraudulent user profiles. These fake profiles, frequently generated with malicious intent, could engage in different forms of spreading disinformation, online fraud, or spamming. A range of techniques is employed to solve these problems such as natural language processing (NLP), machine learning (ML), and behavioural analysis, to examine engagement patterns, user-generated content, and profile characteristics. This paper proposes an automated fake profile detection using the coyote optimization algorithm with deep learning (FPD-COADL) method on social media. This multifaceted approach scrutinizes user-generated content, engagement patterns, and profile attributes to differentiate genuine user accounts from deceptive ones, ultimately reinforcing the authenticity and trustworthiness of social networking platforms. The presented FPD-COADL method uses robust data pre-processing methods to enhance the uniformness and quality of data. Besides, the FPD-COADL method applies deep belief network (DBN) for the recognition and classification of fake accounts. Extensive experiments and evaluations on own collected social media datasets underscore the effectiveness of the approach, showcasing its potential to identify fake profiles with high scalability and precision. 2024 Institute of Advanced Engineering and Science. All rights reserved.
Unni M.V.; Jeevananda S.; Kalapurackal J.J.; Fatma S.
Indonesian Journal of Electrical Engineering and Computer Science, Vol-35, No. 1, pp. 292-300.
Institute of Advanced Engineering and Science
All Open Access; Hybrid Gold Open Access
https://doi.org/10.11591/ijeecs.v35.i1.pp292-300 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192075358&doi=10.11591%2fijeecs.v35.i1.pp292-300&partnerID=40&md5=3161f2ba8d3e01e7ef8251724ba5f268
Unni M.V., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Jeevananda S., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Kalapurackal J.J., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Fatma S., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India
Computational study of charge transfer iso-surface in first three excited states, electron-hole transition effects, chemical nature and bond order analysis investigations of chrysogine
ADMET; DFT; Docking; Lung cancer; Topology
This work presents the theoretical DFT (Density Functional Theory) studies and the biological application of chrysogine, a marine alkaloid. Energy minimisation and additional DFT evaluations were performed for vacuum and solvent media. It has been observed that solvation with polar solvents has resulted in a slight variation in the molecule's properties. The Multiwfn software was employed to carry out various topological analyses. Among these, the charge transfer studies show that the second and third excited states are the most significant. From the reactivity analysis, the least energy gap (4.9624 eV) is obtained in water, indicating that chrysogine is most reactive in aqueous media. Theoretical UV studies show that the trends in ?max values correspond to n >?* and n >?* electronic transitions within the molecule. An increase in medium polarity has demonstrated in the MEP (Molecular Electrostatic Potential) maps an increase in the potential range from ?6.619 10?2 a.u. to 6.619 10?2 a.u. in the gas phase, to a sharp rise to ?8.036 10?2 a.u. to 8.036 10?2 a.u. in ethanol, ?8.098 10?2 a.u. to 8.098 10?2 a.u. in methanol, ?8.130 10?2 a.u. to 8.130 10?2 a.u. in DMSO, and ?8.127 10-2 a.u. to 8.127 10?2 a.u. in water. The most significant transition contributing to molecular stability from NBO (Natural Bond Orbital) analysis is: (O2-C9) ?* ? ?* (C7-C8) with the energy of 258.13 kcal mol?1. The ADMET profile for the molecule was assimilated with the help of online servers. The molecule was docked against lung cancer target proteins (PDB ID: 1NTK, 3QFB) using software such as AutoDock Tools and PyMOL. The respective illustrations and data were visualised using Discovery Studio Visualizer. Good binding affinities (?5.69 kcal mol?1 for 1NTK and ?6.64 kcal mol?1 for 3QFB proteins) and interactions were achieved with the selected targets. 2024 Elsevier B.V.
Bhargiri J.J.; Parakkal S.C.; Datta R.; Alharbi N.S.; Kadaikunnan S.; Muthu S.
Computational and Theoretical Chemistry, Vol-1237
https://doi.org/10.1016/j.comptc.2024.114649 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193487312&doi=10.1016%2fj.comptc.2024.114649&partnerID=40&md5=aaaf9ab39fb482adfb5437b8b0eb6b6b
Bhargiri J.J., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Parakkal S.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Datta R., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Alharbi N.S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Kadaikunnan S., Department of Botany and Microbiology, College of Science, King Saud University, P.O Box 2455, Riyadh, 11451, Saudi Arabia; Muthu S., Department of Physics, Arignar Anna Govt. Arts College, Tamil Nadu, Cheyyar, 604407, India
Artificial intelligence talent acquisition in HEIs recruitments
Artificial intelligence; Higher educational institution and platforms; Recruitment; Talent acquisition
Purpose: The current research study aims to examine the application feasibility and impact of artificial intelligence (AI) among higher educational institutions (HEIs) in talent acquisitions (TA). Design/methodology/approach: A systematic sampling method was adopted to collect the responses from the 385 staff working across the various levels of management in HEIs in metropolitan cities in India. JAMOVI & SmartPLS 4 were applied to validate the hypothesis by performing the simple percentage analysis and structural equation modelling. The demographic and construct variables considered were adoption, actual usage, perceived usefulness, perceived ease of use and talent management. Findings: The key indicators of perceived usefulness are productivity, perceived ease of use, adaptability, candidate experience with the adoption of AI, frequency in decision-making in its actual usage and career path of development in the HEIs. These are the most influential items impacting the application of AI in TA. Originality/value: AI has the potential to revolutionize TA in HEIs in the form of enhanced efficiency, improved candidate experience, more objective hiring decisions, talent analytics and risk automation. However, they facilitate resume screening, candidate sourcing, applicant tracking, interviewing and predictive analytics for attrition. 2024, Emerald Publishing Limited.
International Journal of Information and Learning Technology, Vol-41, No. 3, pp. 230-243.
https://doi.org/10.1108/IJILT-09-2023-0176 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192928463&doi=10.1108%2fIJILT-09-2023-0176&partnerID=40&md5=a548d29c8527f1feb670239c74a77e2d
R V., School of Commerce, Mount Carmel College, Autonomous, Bangalore, India; R H., School of Business and Management, CHRIST (Deemed to be University) Yeshwanthpur Campus, Bangalore, India; E S., Department of Commerce, CHRIST (Deemed to be University) Yeshwanthpur Campus, Bangalore, India; V D., School of Business and Management, CHRIST (Deemed to be University) Yeshwanthpur Campus, Bangalore, India
Does risk management components influence on project success? Evidence from IT sector
Information Technology; Project Success; Risk Assessment; Risk Management; Risk Planning
All organizations and stakeholders would ideally like to see an information technology (IT) project managed successfully. Many researchers have strongly debated the importance of risk management in project management about the size of the project since it gives project managers a forward-looking view of risks and chances to increase the project's success. The main aim of the study is to determine how risk management parameters and their mediated effects impact the effectiveness of IT projects. Data was collected from 261 IT professionals involved in projects through a structured questionnaire and analyzed using regression and SEM to test their statistical significance and prove the hypothesis. The study arrived at some significant results which showed the relationship of Risk Identification and Risk Analysis on Risk Assessment, which impacts Project Success. It also showed that the success of the project depended on Stake-holders Tolerance and Risk Implementation. In addition to this, the study provides evidence that risk management does not influence the success of the project. The study's discovery of the intervening impact of risk management practices clarifies preconceived conceptions in the risk management sector. 2024 Growing Science Ltd. All rights reserved.
Selvakumar J.J.; Suganya G.; Arthi T.S.; Pachiyappan S.
Journal of Project Management (Canada), Vol-9, No. 3, pp. 269-276.
https://doi.org/10.5267/j.jpm.2024.4.001 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197311368&doi=10.5267%2fj.jpm.2024.4.001&partnerID=40&md5=c2d05e4bd2f377581784ff9a904288b1
Selvakumar J.J., CHRIST University, Karnataka, Bengaluru, India; Suganya G., Kumaraguru College of Liberal Arts and Science, Tamil Nadu, Coimbatore, India; Arthi T.S., Sri Ramakrishna Engineering College, Tamilnadu, Coimbatore, India; Pachiyappan S., CHRIST University, Karnataka, Bengaluru, India
Facile fabrication of 3D-?-Fe2O3@2D-g-C3N4 heterojunction composite materials: Effect of iron oxide loading on the electrochemical performance
Carbon materials; Cyclic voltammetry; Graphitic carbon nitride (g-C3N4); Hydrothermal synthesis method; Supercapacitor electrode devices; ?-Fe2O3 nanospheres
Designing heterojunction nanocomposites is crucial for optimizing supercapacitor electrodes. This study addresses the challenge by introducing a facile synthesis method for creating 3D-?-Fe2O3@2D-g-C3N4 heterojunctions through a bulk carbon nitride-assisted hydrothermal process. During this process, the growth of ferric oxide particles coincides with the exfoliation and deposition of carbon nitride, leading to simultaneous structural changes in both iron oxide and carbon nitride phases. The resulting composite's properties strongly correlate with the iron oxide loading. Comprehensive characterization using XRD, FTIR, SEM-EDAX, XPS and TEM identified three distinct structures for ?-Fe2O3/g-C3N4 composites based on iron oxide loading: low, medium, and high. The medium-loaded sample demonstrated superior electrochemical performance, attributed to better interfacial contact and the formation of 3D-Fe2O3@2D-g-C3N4 heterojunctions. This composite, with an optimized 22 wt% iron oxide loading, exhibited a maximum specific capacitance of 925.1 Fg?1 at 5 mVs?1 and 498.6 Fg?1 at 6 Ag?1 in charge-discharge analysis, with stable performance over 2000 cycles. Overall, this research presents an enhanced hydrothermal method for facile preparation of effective ?-Fe2O3/g-C3N4 heterojunction materials. 2024 Elsevier B.V.
Ranjithkumar R.; Lakshmanan P.; Palanisami N.; Devendran P.; Sudhahar S.; Nallamuthu N.; Thrimurthulu G.; Kim I.T.; Krishna Kumar M.
Inorganic Chemistry Communications, Vol-165
https://doi.org/10.1016/j.inoche.2024.112553 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192789068&doi=10.1016%2fj.inoche.2024.112553&partnerID=40&md5=ac4fd647ff93ff4d5424d3eca233b90a
Ranjithkumar R., Department of Physics, International Research Centre, Kalasalingam Academy of Research and Education, Tamil Nadu, Krishnankoil 626 126, India, Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon, 22212, South Korea, Department of Chemical and Biological Engineering, Gachon University, Gyeonggi-do, Seongnam-si, 13120, South Korea; Lakshmanan P., Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon, 22212, South Korea; Palanisami N., Centre for Functional Materials, Vellore Institute of Technology, Tamil Nadu, Vellore, 632 014, India; Devendran P., Department of Physics, International Research Centre, Kalasalingam Academy of Research and Education, Tamil Nadu, Krishnankoil 626 126, India; Sudhahar S., Department of Physics, Alagappa University, Tamil Nadu, Karaikudi, 630 003, India; Nallamuthu N., Dayananda Sagar Academy of Technology and Management, Bangalore, 560 082, India; Thrimurthulu G., Inorganic and Physical Chemistry Division, Indian Institute of Chemical Technology, Telangana, Hyderabad, 500007, India; Kim I.T., Department of Chemical and Biological Engineering, Gachon University, Gyeonggi-do, Seongnam-si, 13120, South Korea; Krishna Kumar M., Department of Physics and Electronics, CHRIST (Deemed to be University), Karnataka, Bengaluru 560 029, India
Psychological adjustment, choice of game genre and living arrangements among adolescents with and without IGD
Adolescents; Anxiety; Depression; Game genre; Gender differences; Internet gaming disorder; Living arrangements; Psychosocial functioning
In India, the prevalence of internet gaming disorders ranges from 8 to 9%. Adolescents are more likely to become addicted to online games. This study compares teenage gamers with and without Internet Gaming Disorder (IGD) in terms of game genre, psychosocial adjustment, and living conditions with a sample of 80 in each group. The results demonstrate that adolescents with this disorder had significantly higher scores for depression, anxiety, and psychosocial deterioration than adolescents without gaming disorder. Even though the prevalence of males is high, both genders do not significantly differ from one another in psychological adjustment. Another finding is that adolescents with gaming disorders play multiplayer online role-play games and Battle Royal games more frequently than average players. The prevalence of this disorder is also influenced by living conditions; teenagers who stay in hostels or pay guest rooms are more likely to develop a gaming addiction. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Current Psychology, Vol-43, No. 26, pp. 22542-22549.
PV S., CHRIST UNIVERSITY (Deemed to be), Christ University Bannerghatta Road Campus, Pai Layout, Hulimavu, Karnataka, Bengaluru, 560076, India, St Aloysius (Deemed to be University), Kodialbail, P B 720, Mangalore, 575 003, India; Kanwar P., CHRIST UNIVERSITY (Deemed to be), Christ University Bannerghatta Road Campus, Pai Layout, Hulimavu, Karnataka, Bengaluru, 560076, India
Machine Learning and Deep Learning Analysis of Vehicle Carbon Footprint
climate change; fuel efficiency; greenhouse gas emissions; machine learning
Clearly climate change is one of the most significant hazards to mankind nowadays. And daily the situation has become worse. No other way characterises climate change except through changes in the patterns of temperature and weather. Human activity generates the primary greenhouse gas emissions. Among these activities are burning coal, oil, natural gas, as well as other fuels; agricultural techniques, industrial operations, deforestation, burning coal, oil. Mostly resulting from human activities, the average temperature of the planet has significantly increased by almost 1.1 degrees Celsius since the late 1800s. One theory holds that internal combustion engines affect roughly thirteen percent. The objective of this work is to do an analysis of a complicated dataset involving fuel consumption in urban and highway environments as well as mixed combinations since the relevance of these variables in modelling attempts dictates. Reduced CO2 emissions emissions and environmental impact follow from reduced fuel use. The project used numerous machine learning and deep learning approaches to comprehend data analysis. Moreover, this work investigates the dataset to acquire knowledge and concurrently solves problems such overfitting and outliers. Control of complexity is achieved using several methods like VIF, PCA, and Cross-Validation. Models combining CNN and RNN performed really well with an accuracy of 0.99. The R-squared metrics are utilized in order to do the evaluation of the model. Apart from linear regression, support vector machines, Elastic Net with a rewardable accuracy, random forest was applied. It has rather good 0.98 accuracy. We can therefore state that our model analyzed the data properly and generated accurate output since the results we obtained during the assessment phase exactly the same ones we obtained during the training stage. Mass data cleansing is required as well as further study to increase machine learning model accuracy and performance. 2024 The authors.
Dhyan R.; Joy H.K.; Sridevi R.; Electa Alice J.A.; Vanusha D.
International Journal of Environmental Impacts, Vol-7, No. 2, pp. 287-292.
International Information and Engineering Technology Association
https://doi.org/10.18280/ijei.070213 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201631162&doi=10.18280%2fijei.070213&partnerID=40&md5=205c7868572c386ae4be4b41d8dbd976
Dhyan R., Department of Computer Science, Christ University, Bangalore, 560029, India; Joy H.K., Department of Computer Science, Christ University, Bangalore, 560029, India; Sridevi R., Department of Computer Science, Christ University, Bangalore, 560029, India; Electa Alice J.A., Department of Electronics and Communication Engineering, KS Institute of Technology, Bangalore, 560019, India; Vanusha D., Department of Computer Science and Engineering, SRM Institute of Technology, Chennai, 603203, India
Constraining the physical parameters of XTE J1701-462 through NuSTAR observations
accretion, accretion discs; stars: neutron; X-rays: binaries; X-rays: individual: XTE J1701-2
The spectral properties of the transient neutron star low-mass X-ray binary XTE J1701-462 were studied using the data obtained from FPMA/B detectors onboard NuSTAR during its second known outburst (2022 September). The physical parameters of the system were derived from the analysis of the data in the 3.0-30.0 keV energy range. The patterns displayed on the hardness-intensity diagram of the three observations closely resembled the banana branch/normal branch, a vertex of horizontal and normal branch of the Z-track and a transition from normal branch to flaring branch. Spectral analysis of the source revealed the presence of Fe K emission complex. The source spectra were fitted with a multitemperature blackbody () component in conjunction with the reflection model (). The values of temperature (kTin) and radius (Rin) of the inner accretion disc obtained from the spectral fitting with the model combination - + showed the source to be in its soft spectral state during the observations. The inclination angle (?) of the source was estimated to be between 19 and 33 and the inner disc radius (Rin) was found to be 17.4 km. Assuming the case of magnetic truncation of accretion disc, the upper limits for the magnetic dipole moment (?) and the magnetic field strength (B) at the poles of the neutron star in the system were found to be 5.78 1026 G cm3 and 8.23 108 G, respectively, for kA = 1. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society.
Thomas N.T.; Jirawala K.; Gudennavar S.B.; Bubbly S.G.
Monthly Notices of the Royal Astronomical Society, Vol-531, No. 2, pp. 2237-2244.
https://doi.org/10.1093/mnras/stae1299 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194908052&doi=10.1093%2fmnras%2fstae1299&partnerID=40&md5=f3f66ba3546ddce5057ba8a77dcfcf3a
Thomas N.T., Department of Physics and Electronics, CHRIST University, Karnataka, Bangalore, 560029, India; Jirawala K., Department of Physics and Electronics, CHRIST University, Karnataka, Bangalore, 560029, India; Gudennavar S.B., Department of Physics and Electronics, CHRIST University, Karnataka, Bangalore, 560029, India; Bubbly S.G., Department of Physics and Electronics, CHRIST University, Karnataka, Bangalore, 560029, India
Circular supply chains in manufacturingQuo vadis? Accomplishments, challenges and future opportunities
circular economy; circular theories, strategies, applications; descriptive content analysis; manufacturing supply chain operations; network analysis
Circular approach in manufacturing supply chain (SC) operations yields multiple benefits through optimal utilisation and consumption of resources. This study maps the scope and structure of circularity in the manufacturing SC discipline and explores the evolution of the domain over time. We review 946 journal articles published between 2013 and September 2023. Our study identifies key drivers and barriers to circular economy (CE) deployment in manufacturing SC operations, bibliometric parameters, emerging research themes, decision support tools, theories and applications. Using the theory extension approach, we propose a strategic framework to fortify the deployment of circularity in SCs. This comprehensive study renders a methodological contribution through combined descriptive content analysis and bibliometric and network analyses to evaluate the circular manufacturing SC operations concepts, theories and applications. We posit that manufacturing firms require to deploy innovation-led approaches to embed the CE strategies in their SC operations. We find that the studies investigating green skill development and circularity-culture adoption can facilitate manufacturers to understand the efficacy of circularity in their SC operations. The findings of this study can facilitate the practitioners to identify the links between the CE approaches and their strategic implications and examine CE implementation at the strategic level. 2024 The Authors. Business Strategy and The Environment published by ERP Environment and John Wiley & Sons Ltd.
Bhattacharya A.; Srivastava S.; Majumdar A.
Business Strategy and the Environment, Vol-33, No. 5, pp. 4397-4423.
https://doi.org/10.1002/bse.3702 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184466672&doi=10.1002%2fbse.3702&partnerID=40&md5=d6a11a90c5ca43a25e4bfef25b46dbf7
Bhattacharya A., Norwich Business School, University of East Anglia, Norwich, United Kingdom; Srivastava S., Operations and Decision Sciences, Christ University, Bangalore, India, Department of Textile & Fibre Engineering, Indian Institute of Technology Delhi, New Delhi, India; Majumdar A., Department of Textile & Fibre Engineering, Indian Institute of Technology Delhi, New Delhi, India
A novel chemical route for low-temperature curing of natural rubber using 2,4 dihydroxybenzaldehyde: improved thermal and tensile properties
Activation energy; Dihydroxybenzaldehyde; Latex; Low-temperature vulcanization; Natural rubber
A novel method for chemically curing natural rubber (NR) using 2,4-dihydroxybenzaldehyde (DHB) at low temperatures has been discovered. Adding varying amounts of DHB to NR increases the crosslinking between the NR molecular chains. The chemical reaction between NR molecular chains and DHB was confirmed through Fourier transform infrared (FTIR) and proton nuclear magnetic resonance (NMR) spectra. From the thermogravimetric analysis (TGA), the thermal stability and activation energy of degradation were determined. The variation in glass transition temperature (Tg), as an indication of increased crosslink density, reducing the mobility of rubber chains, has been confirmed through differential scanning calorimetry (DSC). The addition of DHB to latex significantly enhanced the thermal stability of the rubber. An increase in the activation energy of 5.52% was observed upon the addition of 80mL DHB into NRL when compared to the uncured one. Furthermore, the tensile properties, in terms of tensile strength and modulus of elasticity of rubber, were drastically increased through DHB crosslinking. Tensile strength values of rubber were found to increase by reducing its elongation at break due to the formation of crosslinks between the macromolecular chains. NR cured with 80mL DHB exhibited superior tensile and thermal properties among the series of cured samples. By adding 80mL of DHB, the tensile strength increased by 390% and the elongation at break decreased by 10%. The advantage of this curing method is that, it is an effective technique for crosslinking NR directly from NR latex at comparatively low temperature. Graphical abstract: (Figure presented.) Iran Polymer and Petrochemical Institute 2024.
Raosaheb B.V.; Adeppa A.; Aralihalli S.; Kalkornsurapranee E.; Tuljittraporn A.; Chuaybamrung A.; Vijayashankar A.V.; Johns J.
Iranian Polymer Journal (English Edition), Vol-33, No. 7, pp. 915-925.
Springer Science and Business Media Deutschland GmbH
Raosaheb B.V., Research Center, Department of Physics, Rajarajeswari College of Engineering, Bangalore, India; Adeppa A., Department of Aeronautical Engineering, ACS College of Engineering, Bangalore, India; Aralihalli S., Department of Chemistry, Rajarajeswari College of Engineering, Bangalore, India; Kalkornsurapranee E., Division of Physical Sciences, Faculty of Science, Prince of Songkla University, Hat-Yai, Thailand; Tuljittraporn A., Division of Physical Sciences, Faculty of Science, Prince of Songkla University, Hat-Yai, Thailand; Chuaybamrung A., Division of Physical Sciences, Faculty of Science, Prince of Songkla University, Hat-Yai, Thailand; Vijayashankar A.V., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST-Deemed to be University, Bangalore, 560074, India; Johns J., Research Center, Department of Physics, Rajarajeswari College of Engineering, Bangalore, India
A Bibliometric Analysis of Asset Allocation for Retirement
Allocation of investment assets is key in attaining a sustainable retirement portfolio. In this research article, the authors analyzed the most recent research publications in the area related to asset allocation for retirement and identified those which have the highest impact. The authors research was conducted using the bibliometric analysis technique of research articles collected from the Scopus database. Most of the research articles were published in reputed journals in the United States, United Kingdom, Australia, and Germany. It was also observed that most of the highly cited research articles in the research area of asset allocation for retirement are focused on financial literacy, increase in retirement age, aging, and pension reforms. The authors findings identified six research themes in asset allocation for retirement such as 1) asset allocation for retirement planning, 2) methods to increase efficiency, 3) investment preferences for retirement savings 4) financial literacy and retirement planning, 5) reforms on retirement savings, and 6) annuities for retirement income. Furthermore, nineteen future research directions are also provided. In conclusion, the authors aim to assist future researchers in identifying highly cited articles, key authors, contributing countries and research themes in asset allocation for retirement. Overall, the analysis provides comprehensive information in addressing research questions in the field of asset allocation for retirement. Copyright 2024 With Intelligence LLC.
Journal of Retirement, Vol-12, No. 1, pp. 61-83.
https://doi.org/10.3905/jor.2024.1.158 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201201677&doi=10.3905%2fjor.2024.1.158&partnerID=40&md5=32f93b8e1e6f6d3e9ba8259839e4deb3
Lyngdoh S.W., Department of Commerce at Christ University in NCR, Delhi, India; Das S., Department of Commerce at Christ University in NCR, Delhi, India; Das T., Department of Business and Management at Christ University in NCR, Delhi, India
Predicting Stock Market Movements Through Multisource Data Fusion Graphs: An Approach Employing Graph Convolutional Neural Network
Data fusion; Gated Recurrent Unit; Graph Convolution Neural Network; Multi-source data; Multi-source data fusion graphs; Stock market trends; Stock trend prediction
The stock market plays an important role in the capital market, and investigating price fluctuations in the stock market has consistently been a prominent subject for researchers. The application of soft computing techniques to predict and categorize stock market movements is a significant research challenge that has gathered considerable attention from researchers. Although several studies highlight the significance of incorporating information from two sources in stock movement prediction, the potential of advanced graphical techniques for modeling and analyzing multi-source data remains an unattended research area. This study aims to address this gap by introducing a novel model that utilizes multi-source data fusion graphs to predict future market movements. The primary challenge involves establishing a model that can effectively gather the relationships among various data sources and employ this understanding to improve prediction performance. Compared to several existing methods relying only on historical data or sentiment data, which show limited predictive power and lack generality, the proposed approach seeks to overcome these limitations. The proposed model integrates various information sources, including historical prices, news data, Twitter data, and technical indicators for predicting future stock market trends. This presented method involves constructing a subgraph map for each data type to capture events from both rising and falling markets. Then, a Gated Recurrent Unit (GRU) is employed to aggregate the subgraph nodes. These aggregated nodes are then integrated with a Graph Convolutional Neural Network (GCNN) to classify the multi-source graph, therefore achieving stock market trend prediction effectively. To further validate its effectiveness, the presented model is applied to Indian stock market data, demonstrating its feasibility in fusing multi-source stock data and establishing its suitability for effectively predicting stock market movements. 2024 Seventh Sense Research Group
International Journal of Engineering Trends and Technology, Vol-72, No. 6, pp. 8-18.
https://doi.org/10.14445/22315381/IJETT-V72I6P102 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197208553&doi=10.14445%2f22315381%2fIJETT-V72I6P102&partnerID=40&md5=d7dcd751e80fb1aabcd2c949abf825a9
Ranjith J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Chandar S.K., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Electrochemical performance of ZnxCo3-xO4/N-doped rGO nanocomposites for energy storage application
Co3O4; CV; GCD; Nanocomposites; rGO; ZnCo2O4
In this study, nanocomposites consisting of zinc-doped cobalt oxides with a spinel structure and nitrogen-doped reduced graphene oxide (ZnxCo3-xO4 (x = 0 and 1))/N-doped rGO) were synthesized using a solvothermal method. The synthesized materials were investigated using XRD, TEM, EDS, BET, Raman, and XPS for their phase formation, morphology, elemental composition, surface area, and chemical states. XRD analysis revealed that the metal oxides (Co3O4 and ZnCo2O4) present in the composites exhibited a single-phase cubic spinel structure, with a nanocrystalline nature and crystallite size ranging from 8 nm to 20 nm. Raman and TEM analyses revealed the co-existence of metal oxide nanoparticles and N-doped rGO phases in the composites. Electrodes were fabricated using the synthesized nanocomposite materials and subjected to electrochemical testing, including CV, GCD and EIS. The specific capacitiance (Cs) of samples determined to be 181 F/g and 234 F/g for CO/NrGO (Co3O4/N-doped rGO) and ZCO/NrGO (ZnCo2O4/N-doped rGO) nanocomposites, respectively, at lower current density (0.5 A/g). At all current densities, the CS of ZCO/NrGO nanocomposite electrode is observed to be higher than the CO/NrGO nanocomposite, probably due to structural defects and uniform anchoring of ZnCo2O4 particles over the layers of NrGO. The ZCO/NrGO composite electrode exhibits ?86 % capacitance retention after 3000 cycles. 2024 Elsevier B.V.
Kalpana S.; Bhat V.S.; Hegde G.; Anantharamaiah P.N.
Materials Chemistry and Physics, Vol-319
https://doi.org/10.1016/j.matchemphys.2024.129331 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190338794&doi=10.1016%2fj.matchemphys.2024.129331&partnerID=40&md5=517284b4ea1af312f14b8b5f0dc72c9d
Kalpana S., Department of Chemistry, Faculty of Mathematical and Physical Sciences, M. S. Ramaiah University of Applied Sciences, Bangalore, 560058, India; Bhat V.S., Centre for Nano-materials & Displays (CND), B. M. S. College of Engineering, Bull Temple Road, Bangalore, 560019, India; Hegde G., Department of Chemistry, CHRIST (Deemed to be University), Hosur RD, Bhavani Nagar, S. G. Palya, Bangalore, 560029, India; Anantharamaiah P.N., Department of Chemistry, Faculty of Mathematical and Physical Sciences, M. S. Ramaiah University of Applied Sciences, Bangalore, 560058, India
The development and validation of digital amnesia scale
Confirmatory factor analysis (CFA); Dependency; Detoxification; Digital Amnesia Scale (DAS); Distraction; Exploratory factor analysis (EFA)
The usage of digital devices has increased rapidly in recent times due to the expansion of online learning platforms, leading to greater reliance on them. As a result, people forget simple information, dates, and appointments that might lead to digital amnesia. Hence, we aimed to develop and validate a digital amnesia scale (DAS). The study was carried out in two studies. In the first study, we collected data from 616 college students to examine the factor structure of the model and its underlying dimensions for a large pool of items. These analyses showed that the scale formed a three-dimensional structure: digital distraction, digital dependency, and digital detox. In the second study, we collected data from 383 college students to confirm the three-factor structure of the DAS. A satisfactory level of reliability was demonstrated by McDonalds ? value for the dimensions. The testretest reliability was found to be 0.76. The DAS had satisfactory convergent and discriminant validity. This scale could be useful for both researchers and educators to assess digital amnesia among college students. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Current Psychology, Vol-43, No. 22, pp. 19594-19603.
Robert S.J., Department of Psychology, Christ University, Karnataka, Bangalore, 560060, India; Kadhiravan S., Department of Psychology, Periyar University, Salem, 636 011, India; McKay D., Department of Psychology, Fordham University, New York, NY, United States
Nondestructive and cost-effective silkworm, Bombyx mori (Lepidoptera: Bombycidae) cocoon sex classification using machine learning
Image Processing; Machine learning; Sericulture; Sex classification; Silkworm Cocoon
Sericulture is the process of cultivating silkworm cocoons for the production of silks. The quality silk production requires quality seed production which in turn requires accurate classification of male and female pupa in grainage centers. The challenges in the current methods of silkworm cocoon sex classification using manual observation lie in the time-consuming nature of the process, potential human error, and difficulties in accurately discerning subtle morphological differences between male and female cocoons. FC1 and FC2 single hybrid variety breed pupa are commonly used in south India for the production of high yielding double hybrid bivoltine silkworm seeds. In this study, 1579 FC1 and 1669 FC2 variety samples were used for the classification process. To overcome the challenges of present physical observation by expert employees, camera images of FC1 and FC2 cocoons were used in this study for sex classification. The proposed model used Histogram Oriented Gradient (HOG) feature descriptor of cocoon samples. Linear Discriminant Analysis (LDA) was applied on the feature vector to reduce the dimension and this feature matrix was given to the classical machine learning algorithms support vector machine (SVM), k-nearest neighbors (kNN), and gaussian nae bayes for classification with stratified 10-fold cross validation. The results showed that for FC1 data HOG + LDA + Nae Bayes performed better with a mean accuracy of 95.3% and for FC2 data HOG + LDA + KNN attained a mean accuracy of 96.2%. Our results suggest that this camera imaging method can be used efficiently in the classification based on the cocoon size and shape of different breeds. African Association of Insect Scientists 2024.
International Journal of Tropical Insect Science, Vol-44, No. 3, pp. 1125-1137.
Thomas S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Thomas J., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India
Nonlinear stability analysis of Rayleigh-Bard problem for a Navier-Stokes-Voigt fluid
Double diffusive convection; Ekman damping; Kelvin-Voigt; Navier-Stokes-Voigt fluid; Nonlinear stability analysis
The linear and nonlinear stability analyses of thermosolutal convection in a non-Newtonian Navier-Stokes-Voigt fluid, considering Soret and Ekman damping effects, are conducted analytically. Instability thresholds are determined for thermosolutal convection within a viscoelastic fluid of the Kelvin-Voigt type, wherein a dissolved salt field exists. Two scenarios are examined: one where the fluid layer is heated from the bottom and concurrently salted from the bottom, and the other where the fluid layer is heated from the bottom and concurrently salted from the top. The governing partial differential equations system includes conservation laws of mass, momentum, energy, and salt concentration. Using the energy method, the disturbances to the fluid system are shown to decay exponentially. Analytical expressions are developed for the eigenvalue as a function of Soret, Lewis, Prandtl, Kelvin-Voigt, and Rayleigh friction numbers. The study illustrates the shift from a stationary mode of convection to an oscillatory mode and provides thresholds that indicate these transitions. It is found that the viscoelastic property of the fluid acts as a stabilizing agent for oscillatory mode convection. Rayleigh friction substantially controls the convection threshold. Upon comparing threshold values between linear and nonlinear theories, a subcritical instability region is observed in the heating bottom-salting bottom case (case-1), whereas such a region is absent in the heating bottom-salting top case (case-2). 2024 Elsevier Ltd
International Journal of Non-Linear Mechanics, Vol-162
https://doi.org/10.1016/j.ijnonlinmec.2024.104712 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189108280&doi=10.1016%2fj.ijnonlinmec.2024.104712&partnerID=40&md5=bd4cd324bc17230a6a85bdb391fe300d
Basavarajappa M., School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, Edinburg, 78539, TX, United States, Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Banglore, 560029, India; Bhatta D., School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, Edinburg, 78539, TX, United States