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Reimagining Automotive Manufacturing with Generative AI: A Technolology-Organization-Environment Perspective
Generative AI (Gen-AI) is transforming industries, and the automotive sector is no exception. Auto Component Manufacturing (AutoCM) organizations face strong pressure to adopt Gen-AI for competitiveness, yet little research has examined adoption factors in this context. This study investigates the determinants of Gen-AI adoption in AutoCM firms using the Technology-Organization-Environment framework. A model was developed and tested through survey data from 490 managers, validated via PLS-SEM. The findings reveal key predictors of adoption: perceived intelligence, data quality, absorptive capacity, IT infrastructure, top management commitment, vendor support, competitive pressure, and government support. Results further show that adoption intention drives potential use of Gen-AI, but this relationship is weakened by concerns over Gen-AI hallucination. This research identifies crucial drivers of Gen-AI adoption in AutoCM, extends TOE framework literature, and provides actionable insights for practitioners to strategically harness Gen-AIs transformative potential in the sector. 2025 The Author(s). Published with license by Taylor & Francis Group, LLC. -
ChatGPT and Me: A Dual Factor Examination
ChatGPT advances human-like conversations based on prompts and has been popular among students. ChatGPT offers advantages, but students have also experienced disadvantages, which affect their intention to use it. Drawing on this concern, this research uses a mixed-method approach. For study 1, 45 semi-structured interviews were conducted. Based on these responses, 10 constructs were identified. Using a Dual-factor approach, we categorized convenience, perceived enjoyment, perceived interactivity, learner autonomy, personalization and AI quality as Enablers and technological insecurity, poor information quality, diminishing critical thinking, and plagiarism as Inhibitors. For Study 2, data was collected through a questionnaire from 525 respondents. Structural equation modeling was employed to find support for all the Enablers and Inhibitors except plagiarism. The study also tested the moderating role of FOMO between enablers and students ChatGPT usage intention. This study contributes to the theoretical underpinnings of ChatGPT usage and provides practical implications for educators, learners and developers. 2025 International Association for Computer Information Systems. -
Is ChatGPT Enhancing Youths Learning, Engagement and Satisfaction?
Integration of artificial intelligence (AI) in educational practices necessitates the understanding of the influence of tools such as ChatGPT. Self-determination Theory (SDT) has been used to examine the impact of ChatGPT usage by students for the improvement of perceived learning, engagement and satisfaction. The moderating role of students AI literacy between ChatGPT and the antecedents of intrinsic motivation, autonomy, competence and relatedness. The data was collected through questionnaire from 481 students and structural equation modeling was used to analyze the data. The findings of the study shows that ChatGPT usage impacts students perceived autonomy, competence, and relatedness, enhancing intrinsic motivation. Also, there is a moderation of AI literacy between ChatGPT usage and these psychological needs. This study extends SDT to student interactions with ChatGPT and underscores the pivotal role of AI literacy. The findings contribute to the discourse on AI and education, offering valuable perspectives on students use of ChatGPT and its effect on their academic experience. 2024 International Association for Computer Information Systems. -
A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system
Robotic systems have become popular across various industries, ranging from manufacturing and healthcare to logistics and space exploration. However, increasing the integration of robotic systems into critical infrastructures exposes devices to cybersecurity threats. The intrusion detection system (IDS) plays a vital role in safeguarding the systems from malicious activities and unauthorized access. This paper presents a novel, robotics-aware IDS framework incorporating hybrid feature selection and tailored classification strategies for robotic system. To evaluate the efficacy of the presented framework, an algorithm is also designed and tested using multiple machine-learning techniques. The NSL-KDD dataset is utilized for training and evaluating machine learning models due to the inclusion of a wide range of attack scenarios and normal instances. The results demonstrate that the proposed IDS effectively classifies cyberattacks relevant to robotic systems. The presented framework is also evaluated against existing IDS approaches in robotic systems. The results demonstrate that the proposed approach exhibits better results in terms of accuracy, robustness, and adaptability to emerging cyber threats. 2025 The Author(s). Published with license by Taylor & Francis Group, LLC. -
Exploring the potential of Andrographis paniculata for developing novel HDAC inhibitors: an in silico approach
Cancer is one of the dreaded diseases of the twentieth century, emerging the major global causes of human morbidity. Cancer research in the last 15 years has provided unprecedented information on the role of epigenetics in cancer initiation and progression. Histone deacetylases (HDACs) are recognized as important epigenetic markers in cancer, whose overexpression leads to increased metastasis and angiogenesis. In the current study, thirty-four (34) compounds from Andrographis paniculata were screened for the identification of potential candidate drugs, targeting three Class I HDACs (Histone deacetylases), namely HDAC1 (PDB id 5ICN), HDAC3 (PDB id 4A69) and HDAC8 (PDB id 5FCW) through computer-assisted drug discovery study. Results showed that some of the phytochemicals chosen for this study exhibited significant drug-like properties. In silico molecular docking study further revealed that out of 34 compounds, the flavonoid Andrographidine E had the highest binding affinities towards HDAC1 (?9.261 Kcal mol?1) and 3 (?9.554 Kcal mol?1) when compared with the control drug Givinostat (-8.789 and ?9.448 Kcal mol?1). The diterpenoid Andrographiside displayed the highest binding affinity (-9.588 Kcal mol?1) to HDAC8 compared to Givinostat (-8.947 Kcal mol?1). Statistical analysis using Principal Component Analysis tool revealed that all 34 phytocompounds could be clustered in four statistical groups. Most of them showed high or comparable inhibitory potentials towards HDAC target protein. Finally, the stability of top-ranked complexes (Andrographidine E-HDAC1 and HDAC3; Andrographiside-HDAC8) at the physiological condition was validated by Molecular Dynamic Simulation and MM-PBSA study. Communicated by Ramaswamy H. Sarma. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
You have to budget within the money you have: Intersections of immigration, health, and food insecurity in the South Bronx
This study explored food insecurity in the Bronx using a community-based participatory approach, including 38 interviews with food pantry users, four interviews with social service administrators, and two focus groups with 12 pantry staff and providers in New York City. Using a phenomenological framework, we identified three key themes: (1) negative impact of immigration status on food insecurity, (2) competing financial demands and limited access to social service assistance; and (3) adverse effects on physical and mental health. Findings highlight the relationships between food insecurity and immigration status. The costs of securing legal residency and sending remittances home contributes to the financial strain and poor health outcomes among immigrant communities in the South Bronx. Immigrants faced additional barriers that exacerbated these vulnerabilities, including language barriers and limited access to social services. With rising food costs due to inflation and uncertainties regarding potential cuts to federal food assistance programs, addressing food insecurity in the Bronx has never been more critical. Ensuring equitable food access for all Bronxites requires developing trusted relationships with immigrant communities and strong community partnerships with local social service organizations. 2025 Urban Affairs Association. -
The Role of Psychoactive Drugs in the Onset of Dissociative Identity Disorder: A Comparative Study of Alcohol and Drug Abusers
Psychoactive substances influence mood, cognition, and personality, with emerging synthetic drugs presenting new challenges. This study examines the impact of psychoactive drug use on the development of dissociative identity disorder (DID), comparing alcohol and drug abusers. A total of 120 participants (60 alcohol abusers, 60 drug abusers) from Suman Ellen Trust in Bangalore were assessed using standardized psychological instruments, including the Addiction Severity Index, Dissociative Disorders Interview Schedule, Drug Abuse Screening Test, and Dissociative Experiences Scale. A mixed-methods approach was employed, incorporating both quantitative (ANOVA, Pearson correlation) and qualitative (thematic analysis) methodologies to analyze dissociative symptoms and substance use patterns. Findings revealed a significant difference in DID prevalence between alcohol and drug abusers (F = 55.88, p <.01), with drug abuse showing a strong positive correlation with dissociative symptoms (r = 0.790, p <.01). The study highlights the need for integrated clinical approaches addressing both substance use disorders and dissociative pathology. Future research should focus on longitudinal studies to clarify causal mechanisms and develop targeted intervention strategies. 2026 Taylor & Francis Group, LLC. -
Modeling of non-Gaussian time series in the presence of measurement error
Measurement error in time series refers to inaccuracies or deviations in recorded data that can distort the true underlying patterns, potentially leading to biased estimates and misleading conclusions in statistical analysis. AR models with non-Gaussian errors are crucial for accurately capturing real-world time series data with skewness, heavy tails, or outliers, leading to better forecasts and more reliable statistical inferences. Our focus in this study is on an optimal estimating function (EF) method that accounts for measurement error while estimating the parameters of AR(1) with logistic innovation. The asymptotic properties of the obtained optimal EF are also proved. The simulation study shows that incorporating measurement error into the model yields better estimates compared to ignoring its presence when measurement error exists. This shows that ignoring the measurement error leads to biased estimates. 2026 Taylor & Francis Group, LLC. -
SwinTransConv and Tab-FCNN: a novel SwinTransConv neural network features and tab-fully connected neural network in pap smear images for cervical cancer classification
The primary objective of this paper is to delineate a Deep Learning (DL) methodology for cervical cancer from Pap smear imagery. In the interest of augmenting the quality and equilibrium of the dataset, the initial phase involved executing ROI detection on the Pap smear images. ROI detection is executed using YOLO V4 model in the input Pap smear images for detecting superficial, intermediate and parabasal layers. Then, the segmentation phase is performed to delinate cytoplasm and the nucleus, employing the YOLOv11 model. Subsequently, the feature extraction is executed by the proposed SwinTransConv, which integrates the Swin Transformer with a Convolutional Neural Network (CNN) to yield a robust and hierarchical representation of salient cellular features. The derived features act as input for the classification phase, for which a Tabular-Fully Convolutional Neural Network (Tab-FCNN) model is proposed by combining Tabular Network (TabNet) and Fully Convolutional Neural Networks (FCNN). TabNet identifies significant features from the input dataset utilizing attention-based mechanisms tailored for tabular data, whereas FCNN enhances the final decision-making process by assimilating complex feature interactions. Experimental findings state that the proposed approach reached an accuracy of 97.9%, a sensitivity of 95.4% and a specificity of 99.4%. 2026 Taylor & Francis Group, LLC. -
A study on comparisons of additive regression frailty models to counter heterogeneity: Bayesian strategies and case study
Historically, the primary goal of conventional survival study methods has been to reduce the frequency of failures over time. If the associated observed and unobserved variables are not known when studying such events, this can have detrimental effects. Frailty models offer a tempting solution for investigating the impact of unknown variables in such a case. In this article, we assume that frailty affects the hazard rate. We find that the weighted Lindley frailty models, which use general versions of the Weibull and log-logistic type II distributions as the baseline distributions, are a reliable method for ensuring the influence of endogenous variability. The parameters involved are estimated according to different loss functions using the Bayesian structure as the basis of Markov Chain Monte Carlo. Bayesian evaluation strategies are then implemented to evaluate the models. The results are demonstrated on known data of kidney infections. It is shown that the novel models outperform those based on the inverse Gaussian and gamma frailty distributions. 2024 Taylor & Francis Group, LLC. -
Telehealth Services for an Adolescent with Duchenne Muscular Dystrophy (DMD) During the COVID-19 Pandemic
The neuropalliative approach in a hospital setting for neuromuscular disorders is essentially multidisciplinary in focus and involves co-ordinated interventions. This case report describes an intensive case management approach through telehealth services provided from a hospital context in South India for psychosocial interventions for an adolescent with Duchenne Muscular Dystrophy. Case management interventions during the COVID-19 pandemic were provided through sixteen sessions over the telephone, focusing on need assessment, service plan development, implementation, co-ordination, and monitoring. Major strategies were crisis management, supportive psychotherapy, and cognitive-behavioural strategies. Adaptations made to meet the challenges of the COVID-19 pandemic using telehealth facilities can be incorporated into routine clinical practice in low-resource settings. IMPLICATIONS Telehealth, which emerged as a viable option for providing effective psychosocial care during the COVID 19 pandemic, could be adopted to complement routine clinical care in low-resource settings. 2024 Australian Association of Social Workers. -
I am lost in that reality, and I'm just playing the game: a qualitative study exploring gaming behaviour and its effect on young adults in India
The current study aims to explore gaming behaviour among young adults in India and its effects on their physical and emotional health, productivity, interactions, and social life. Data were collected from 12 avid gamers through in-depth semi-structured interviews. A thematic analysis was conducted to identify the global theme and organise themes from the data. The global theme was the exploration of contemporary gaming behaviour. The habit theme included the origin of the game, practice, and change over time, while the effects theme focused on the physical and emotional health, productivity, interactions, and social life of young adults who engaged in gaming. The findings suggest that gaming behaviour has become an established habit among young adults in India, significantly affecting various aspects of their lives. The study highlights the need for increased awareness of the potential negative consequences of excessive gaming and emphasises the importance of moderation in gaming. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Tele-law for legal education: exploring service learning in Indian law schools
The tele-law programme started in 2017 in India is an initiative to provide free online legal consultation to any citizen throughout India. The tele-law platform, and its mobile application, is accessible to any citizen in need of legal aid who can use it for getting consultation through empanelled lawyers. The application currently faces issues in accessibility due to illiteracy and the digital divide. This paper attempts the integration of the tele-law framework with legal aid clinics for achieving the two-fold objective of service learning for law students as well as ease of access to legal aid for beneficiaries. The paper analyses the barriers to legal aid highlighting the unmet legal aid needs in India and examines the tele-law schemes framework. After examining the legal framework, the responses from law school clinics in the National Capital Territory of Delhi, India, and the survey responses of law students on service learning, the paper proposes a framework for involving law students in tele-law for case registration, beneficiary assistance, and legal advice. The paper concludes by recommending a model for integrating tele-law to enhance service learning in legal education, which can be applied by legal aid clinics around the globe. 2025 The Association of Law Teachers. -
Fluorescent chiral nematogens derived from naturally occurring moieties
We discuss the synthesis and characterisation of new non-symmetric liquid crystal dimers of cholesteryl n-(4-formyl-2-methoxyphenoxy)alkanoates by tethering cholesterol and vanillin. Spectroscopic characterisation such as IR, 1H and 13C NMR used to confirm the molecular structures. Mesophase properties are assessed using polarising optical microscopy (POM) and differentially scanning calorimeter (DSC). All the dimers in the series display liquid crystalline phase particularly cholesteric and smectic A* phases. Additionally, a UV-Vis study showed that the molecules self-assemble into H-aggregates with strong fluorescence emission. DFT studies provide insights into molecular geometry, electronic structure, and energy states, enabling detailed estimations of chemical behaviour and interactions. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Indian perspectives on single-session therapy: an initial qualitative study with psychiatric social workers
Single-Session Therapy (SST) is an emerging approach to mental-health service delivery that maximises the value of a single clinical encounter. It is gaining traction globally for its brevity and potential to address mental health concerns. This study explores perspectives of five Psychiatric Social Workers (PSWs) at a premier Indian psychiatric institute regarding SSTs suitability for the Indian population. Hybrid thematic analysis of a focus group discussion reveals both promising potential and significant challenges for adapting SST to the Indian context. Although participants noted that intentional one-time visits are currently uncommon at their institution, they identified SST as a responsive intervention for addressing caregiver burden and preventing relapse, suggesting its value as a responsive and opportunity-based intervention. Participants raised practical concerns regarding session structure, time constraints, and unpredictability of client return. Despite these cautions, they recognised SSTs potential to widen access to care in India. The discussion emphasises on need for specialised training, supervision, regulatory frameworks, and broader mental health promotion efforts to incorporate SST as a viable therapeutic intervention delivery method. This preliminary investigation serves as a valuable springboard for further research on the potential of SST in a country like India. 2026 GAPS. -
The secret sauce: factors influencing the effectiveness of virtual influencer endorsements
Riding on the waves of growing popularity, virtual influencers (VIs) are reshaping the influencer marketing landscape. The proliferation of generative AI has further accelerated their commercial adoption, with global brands such as Chanel, Prada, and Balenciaga entering into endorsement deals with these artificial entities. Nevertheless, the extant literature remains fragmented and inconclusive in assessing the effectiveness of such endorsements, thereby necessitating a comprehensive inquiry into what makes VIs effective endorsers. To address this gap, the current study employs the Total Interpretive Structural Modelling (TISM) methodology and is the first to provide a comprehensive hierarchical framework that organises the disparate findings into a structured, multi-stage cascade of effects. In addition, a MICMAC analysis is conducted to determine the relative importance of each factor based on its driving and dependence power. The findings offer actionable implications for VI creators, advertisers, and brand managers, alongside expanding the current body of literature. 2025 Advertising Association. -
Efficacy of in-person versus digital mental health interventions for postpartum depression: meta-analysis of randomized controlled trials
Aim: This meta-analysis aimed to compare the efficacy of in-person and digital mental health interventions in addressing Postpartum Depression. Methods: Following PRISMA guidelines, the protocol for this meta-analysis was registered at the Open Science Framework (Retrieved from osf.io/wy3s4). This meta analysis included Randomized Controlled Trials (RCTs) conducted between 2013 and 2023. A comprehensive literature search identified 35 eligible RCTs from various electronic databases. Inclusion criteria focused on pregnant women over 18 years old, encompassing antenatal depression and up to two years postpartum. Diagnostic interviews or Edinburgh Postnatal Depression Scale (EPDS) were used to establish PPD. Digital interventions included telephonic, app-based, or internet-based approaches, while in-person interventions involved face-to-face sessions. Results: The meta-analysis revealed a moderate overall effect size of ?0.69, indicating that psychological interventions are effective for PPD. Digital interventions (g = ?0.86) exhibited a higher mean effect size than in-person interventions (g = ?0.55). Both types of interventions displayed substantial heterogeneity (digital: I2 = 99%, in-person: I2 = 92%), suggesting variability in intervention content, delivery methods, and participant characteristics. Conclusion: Digital mental health interventions show promise in addressing PPD symptoms, with a potentially greater effect size compared to in-person interventions. However, the high heterogeneity observed in both modalities underscores the need for further research to identify key drivers of success and tailor interventions to diverse populations. Additionally, the choice between digital and in-person interventions should consider individual needs and preferences. Ongoing research should further investigate and optimise intervention modalities to better serve pregnant women at risk of PPD. 2024 Society for Reproductive & Infant Psychology. -
New discrete trigonometric distributions: estimation with application to count data
In this research, we contribute to the development of original discrete distributions for count data analysis. We elaborate four new and different discrete trigonometric distributions with two parameters based on a discretization of the so-called sin-Weibull, cos-Weibull, tan-Weibull, and type II tan-Weibull distributions. We investigate the advantages of the proposed distributions and their trigonometric nature for capturing count data. In particular, some fundamental distributional properties of the discrete sin-Weibull distribution are derived. Subsequently, we turn it into a statistical model. Parameter estimation by the maximum likelihood and proportion of zeros and ones methods are then discussed. A simulation study is carried out to evaluate some frequentist properties of the developed methodology. As the study focuses mainly on the practical aspect, the applicability of the proposed models is evaluated using real-count datasets from various fields. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Analysis of a mathematical model of the aggregation process of cellular slime mold within the frame of fractional calculus
The pivotal aim of the present study is to find the solution for a nonlinear system describing the aggregation process of cellular slime mold by using (Formula presented.) -homotopy analysis transform method. The coupled system is considered within the frame of the Caputo fractional operator. We examine three different cases with distinct values of sensitivity function (Formula presented.), (Formula presented.) and (Formula presented.) to exemplify the efficiency and applicability of the considered scheme. We capture the nature of the obtained results with respect to the fractional order, with distinct initial conditions, and illustrate them using 2D and 3D plots for particular values of the parameters. The considered scheme offers parameters, which help to adjust the convergence region, and we plotted the ?-curves to dissipate the effect in the present framework. Moreover, some simulating and important behavior of the considered model using attained results shows the prominence of the hired operator while analyzing the coupled equations and confirms the competence of the projected scheme. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Numerical study on magnetohydrodynamics micropolar Carreau nanofluid with Brownian motion and thermophoresis effect
The current work explores the investigation of the influence of nonlinear thermal radiation on unsteady, magnetohydrodynamics boundary layer flow of micropolar Carreau nanofluid past a stretching sheet. Viscous dissipation, internal heating, Brownian motion, heat source/sink, thermophoresis, chemical reaction, and Joule heating effects are considered in the study. To analyze the model, the governing partial differential equations are rephrased and written in the non-dimensional form with the relevant dimensionless quantities. To obtain the solutions, the nonlinear non-dimensional governing equations are numerically solved using finite difference approximation. The impact of every significant flow parameter on fluid motion, micro-rotation, temperature, concentration, surface drag, heat, and mass transfer rates are presented through plotted graphs and tables. It is noted from the study that the fluid flow and angular motion increase, whereas the temperature declines with higher values of the micropolar constant. Further, it is noticed that thermal distribution is a rising function of radiation parameter, and due to the nonlinear thermal radiation effect, there is an increase of 4.903% in temperature distribution when compared to linear thermal radiation. To support the validity of the solutions, a comparison was made with notable results from the existing literature for the specific case of this study. 2023 Informa UK Limited, trading as Taylor & Francis Group.