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Real-time e-health framework for efficient AI-driven disability monitoring using secured Internet of Medical Things:Real-time e-health framework for efficient AI-driven..
No full textThe integration of Internet of Medical Things (IoMT) technology is revolutionizing patient monitoring by enabling real-time and remote assessment. It utilized various health sensors and wireless technologies to communicate with patients and transmit health records to cloud systems for analysis and disease identification. This study proposes an AI-driven framework for disability detection using secured IoMT, leveraging motion analysis, efficient data routing, and secure cloud storage. The framework captures motion data through simulated IoT-enabled wearable devices, represented by open-source datasets such as publicly available PAMAP2 and MHEALTH. To identify movement patterns connected to disability and train the model, the motion data is first preprocessed using noise reduction and normalization techniques. The proposed framework utilizes a Support Vector Machine to classify the patterns due to its lightweight features, ultimately providing a rapid, real-time analysis in crucial health circumstances. It processes the extracted features and predicts whether a movement pattern indicates normal or disability related human behavior. Moreover, health records are transmitted from IoMT devices to the cloud using network optimization by exploring LPWAN/LoRaWAN protocols, ensuring energy-efficient, low-latency communication. By combining intelligent learning with optimized network protocols and secure cloud integration, the proposed framework gives a practical approach to the healthcare domain to access timely insights into patient health. The proposed framework is simulated in NS3 for performance evaluation and provides significant outcomes as compared to existing approaches in terms of energy consumption by an average of 47%, attack detection rate by an average of 35%, packet drop ratio by an average of 48% and false positive rate by an average of 42%
Family Factors and Internet Gaming Disorder among Adolescents: A Systematic Review.
Get PDF©2025, Sage Publications. This is an author produced version of a paper published in International Journal of Developmental Science, uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it
Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches
No full textFake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding fake news in Urdu is difficult because there are not many effective systems for this. This study aims to solve this problem by creating a detailed process and training models using machine learning, deep learning, and large language models (LLMs). The research uses methods that look at the features of documents and classes to detect fake news in Urdu. Different models were tested, including machine learning models like Naïve Bayes and Support Vector Machine (SVM), as well as deep learning models like Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM), which used embedding techniques. The study also used advanced models like BERT and GPT to improve the detection process. These models were first evaluated on the Bend-the-Truth dataset, where CNN achieved an F1 score of 72%, Naïve Bayes scored 78%, and the BERT Transformer achieved the highest F1 score of 79% on Bend the Truth dataset. To further validate the approach, the models were tested on a more diverse dataset, Ax-to-Grind, where both SVM and LSTM achieved an F1 score of 89%, while BERT outperformed them with an F1 score of 93%
Ethnic differences in beta cell function and pancreatic fat in Black African and White European men across a spectrum of glucose tolerance
No full textPeople of Black African (BA) ancestry are disproportionately affected by type 2 diabetes when compared with people of White European (WE) descent, despite lower levels of ectopic fat. Impaired beta cell function is a key pathophysiological feature of type 2 diabetes. It remains to be determined whether an associative relationship exists between intrapancreatic lipid (IPL) accumulation and beta cell function, and whether this differs by ethnicity. Fifty-three BA (23 normal glucose tolerance, 11 impaired glucose tolerance and 19 type 2 diabetes) and 51 WE (23/13/15) men underwent a hyperglycaemic clamp and mixed-meal tolerance test to assess insulin secretion and beta cell function, a hyperinsulinaemic-euglycaemic clamp to measure insulin sensitivity and Dixon MRI to determine IPL. Associations between IPL and beta cell function were assessed using linear regression. IPL was lower in BA compared with WE men (mean ± SD; 7.6 ± 2.6% vs 8.8 ± 3.7%, p=0.038), but after adjustment for waist circumference this ethnic difference no longer occurred (p=0.278). BA men with type 2 diabetes had lower total insulin secretion response to the mixed-meal (p=0.001) and hyperglycaemic clamp (p=0.002), but no ethnic differences were observed in the disposition index within glucose tolerance groups. IPL was inversely associated with beta cell function in the WE but not the BA men, but after adjustment for confounders these associations were not significant. Ethnic differences were apparent as beta cell function was inversely associated with IPL in the WE, but not BA, men. However, in both ethnic groups, this relationship appears secondary to other factors, such as adiposity, in the pathogenesis of type 2 diabetes. [Abstract copyright: © 2025. The Author(s).
Ethnic differences in adipose tissue dysfunction and insulin resistance: a scoping review
No full textThe objective of this scoping review is to synthesize ethnic comparison studies focused on characteristics of adipose tissue dysfunction including ectopic fat, adipokines and insulin resistance in populations of south Asian (SA), black (BA) and white (WE) ethnicity. A search of the literature was conducted on MEDLINE using keywords for adipose tissue dysfunction and ethnicity. Studies were included if they compared ectopic fat in adults (>18-years) of SA, BA or WE ethnicity, with data on insulin sensitivity and adipokines extracted where present. Thirty-one studies were included in this review. Trends showed most studies were conducted in USA (n = 22); BA were the focus of most ethnic comparison studies (n = 28). Most studies focused on intrahepatic lipids (n = 26), with fewer investigating intrapancreatic lipids (n = 3) and intramyocellular lipids (n = 8). Only 2 studies investigated leptin and adiponectin alongside ectopic fat deposition by ethnicity. Current trends indicate intrahepatic lipid is lower in BA but greater in SA compared to WE populations, indicting possible ethnic disparities in the role ATD in the development of T2D. Few ethnicity studies have investigated multiple characteristics of ATD between BA and SA groups in a single study which may be needed to elucidate ethnic-specific pathophysiology of T2D. [Abstract copyright: Copyright © 2025 The Author(s). Published by Elsevier B.V. All rights reserved.
Sources of occupational stress in UK construction projects: an empirical investigation and agenda for future research
No full textPurpose While stress, anxiety and depression rank as the second leading cause of work-related ill health in the UK construction sector, there exists a scarcity of empirical studies explicitly focused on investigating the sources of occupational stress among construction workers and professionals at both the construction project and supply chain levels. This study seeks to identify and investigate the primary stressors (sources of stress) in UK construction projects and to propose effective strategies for preventing or reducing stress in this context. Design/methodology/approach The study adopted a qualitative multi-methods research approach, comprising the use of a comprehensive literature review, case study interviews and a focus group. It utilised an integrated deductive-inductive approach theory building using NVivo software. In total, 19 in-depth interviews were conducted as part of the case-study with a well-rounded sample of construction professionals and trade supervisors, followed by a focus group with 12 policy influencers and sector stakeholders to evaluate the quality and transferability of the findings of the study. Findings The results reveal seven main stressors and 35 influencing factors within these 7 areas of stress in a UK construction project, with “workflow interruptions” emerging as the predominant stressor. In addition, the results of the focus-group, which was conducted with a sample of 12 prominent industry experts and policy influencers, indicate that the findings of the case study are transferrable and could be applicable to other construction projects and contexts. It is, therefore, recommended that these potential stressors be addressed by the project team as early as possible in construction projects. Additionally, the study sheds empirical light on the limitations of the critical path method and identifies “inclusive and collaborative planning” as a proactive strategy for stress prevention and/or reduction in construction projects. Research limitations/implications The findings of this study are mainly based on the perspectives of construction professionals at managerial and supervisory levels. It is, therefore, suggested that future studies are designed to focus on capturing the experiences and opinions of construction workers/operatives on the site. Practical implications The findings from this study have the potential to assist decision-makers in the prevention of stress within construction projects, ultimately enhancing workforce performance. It is suggested that the findings could be adapted for use as Construction Supply Chain Management Standards to improve occupational stress management and productivity in construction projects. The study also provides decision-makers and practitioners with a conceptual framework that includes a list of effective strategies for stress prevention or reduction at both project and organisational levels. It also contributes to practice by offering novel ideas for incorporating occupational stress and mental health considerations into production planning and control processes in construction. Originality/value To the best of the authors’ knowledge, this is the first, or one of the very few studies, to explore the concept of occupational stress in construction at the project and supply chain levels. It is also the first study to reveal “workflow” as a predominant stressor in construction projects. It is, therefore, suggested that both academic and industry efforts should focus on finding innovative ways to enhance workflow and collaboration in construction projects, to improve the productivity, health and well-being of their workforce and supply chain. Further, it is suggested that policymakers should consider the potential for incorporating “workflow” into the HSE's Management Standards for stress prevention and management
A study on the effects of location, ethnicity and care approach on people with Endometriosis in the UK.
No full textAffect regulation, mentalization, and attachment in intimate partner violence survivor women:A quasi-experimental controlled trial
No full textOBJECTIVE: This quasi-experimental controlled trial investigates the role of attachment patterns and the quality of mentalization in women exposed to domestic violence, with the aim of identifying protective and risk factors related to coercive control in intimate relationships.METHOD: The Relationship Scale Questionnaire, the Reflective Functioning Questionnaire, and the Rorschach Inkblot Test were administered to 80 women divided into three groups: women victims of chronic domestic violence, women victims of a single episode of domestic violence (WVSEDV), and a control group of women who never experienced domestic violence. Sample comparisons and univariate descriptive analyses were conducted.RESULTS: Women victims of chronic domestic violence predominantly showed disorganized attachment styles ( p < .001) and hypomentalization (80%; p < .001). WVSEDV presented a higher proportion of secure attachment styles (48%; p < .001) alongside a notable proportion of avoidant attachment styles (36%) and hypermentalization profiles (52%). No significant differences were found between the WVSEDV and women who never experienced domestic violence groups regarding attachment and mentalization dimensions. CONCLUSIONS: These findings indicate that it could be valuable to explore, through targeted research, whether promoting attachment security and mentalization abilities within psychotherapy might enhance the effectiveness of support for victims. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p
