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Found 6374 publications
A hybrid five-way decision architecture integrating q-ROFS with outranking relations and Bayesian risk optimization
Publication Name: Results in Engineering
Publication Date: 2025-12-01
Volume: 28
Issue: Unknown
Page Range: Unknown
Description:
To address the complex challenges of green sustainable agriculture arising from regional economic growth, this study proposes a novel five-way decision (F-WD) architecture. The framework is evaluated using a Bayesian risk mechanism to minimize expected losses, leveraging the flexibility of q-rung orthopair fuzzy logic ( q ¨ ≥ 1 ) combined with outranking relations and decision-theoretic rough sets (DTRS). This approach defines alternatives across five semantically interpretable regions, extending the conventional three-way decision (T-WD) framework to provide a more granular and versatile classification system. Outranking relations enable partial preference modeling among alternatives by incorporating dominance and incomparability, offering nuanced judgments when criteria conflict or are incommensurable unlike traditional ranking methods. The study begins by formulating F-WD specific relative gain and loss functions, laying the groundwork for the five zone decision-making process. It further validates the reliability of threshold values, their properties, and their role in defining decision boundaries. Compared to conventional methods like TOPSIS, Fuzzy AHP, T-WD-DTRS, IVIFS-ELECTRE, and the proposed technique demonstrates superior decision granularity, interpretability, and classification accuracy. These results underscore the method's credibility, soundness, and practical effectiveness in handling uncertainty, hesitation, and compromise in risk-sensitive environments. The q-ROFS-based F-WD model not only outperforms existing approaches but also serves as a powerful, adaptive tool for sustainable development, strategic planning, and policymaking in complex scenarios.
Open Access: Yes
Seroprevalence of hepatitis B and hepatitis C viral infections among refugees in Muzaffarabad, Pakistan
Publication Name: BMC Infectious Diseases
Publication Date: 2025-12-01
Volume: 25
Issue: 1
Page Range: Unknown
Description:
Background: Hepatitis B (HB) and Hepatitis C (HC) viral infections, with 328 million cases globally, represent a significant disease burden. Currently, Pakistan has 3.88 million HB and 9.31 million HC cases. High-risk populations like refugees are disproportionately affected by these infections. The objectives of this study were to determine the seroprevalence of hepatitis B surface antigen (HBsAg) and hepatitis C virus antibody (anti-HCV) among Kashmiri refugees in Muzaffarabad, Pakistan, and to identify the key demographic and educational risk factors associated with the seroprevalence in this population. Methods: A cross-sectional study was conducted across eight refugee camps in the Muzaffarabad division, Pakistan. A six-membered team visited each camp to collect blood samples through venipuncture. The seroprevalence of HBsAg and anti-HCV was determined using rapid immunochromatographic test (ICT) kits. Results: A total of 550 sera samples were collected from the refugee population in Muzaffarabad. The overall seroprevalence was 5.82% (32/550) for HBsAg and 4.73% (26/550) for anti-HCV. A higher seroprevalence of HBsAg and anti-HCV was recorded among females 6.12% (15/245), and 6.53% (16/245), respectively, compared to males 5.75% (17/305), and 3.28% (10/305), respectively. A marked increase in seroprevalence of HBsAg and anti-HCV was noted with an increase in age: 1–10 (2.44%) and (2.44%), 41–50 (8.20%) and (6.56%), and 51–60 (8.93%) and (8.93%), respectively. Chi-square test revealed a statistically significant association between age and seroprevalence of HBsAg χ² (degrees of freedom (df):6, N = 550) = 27.22, p = 0.000, and HC χ² (df:6, N = 550) = 15.23, p = 0.019.The level of education impacted the seroprevalence of HBsAg and anti-HCV, resulting in a higher seroprevalence of HBsAg (6.9%) and anti-HCV (5.4%) among uneducated individuals compared to educated individuals (4.71%) and (3.99%), respectively. Conclusion: The seroprevalence of HBsAg and anti-HCV is high among the refugee population of Muzaffarabad, Pakistan. There is a need for the implementation of a robust vaccination program for HB as well as the establishing a hepatitis micro-elimination program among the Kashmiri refugee population of Muzaffarabad, Pakistan.
Open Access: Yes
Application of whey protein-based edible coatings containing lemon peel powder and extract to maintain the antioxidant properties of table grapes during ambient storage
Publication Name: Food and Humanity
Publication Date: 2025-12-01
Volume: 5
Issue: Unknown
Page Range: Unknown
Description:
Table grapes are among the most widely consumed fruits worldwide; however, their shelf life is limited by water loss, microbial spoilage, and degradation of antioxidants. This study examined the effects of whey protein-based edible coatings enriched with 1 % lemon peel powder (LP1), 2 % lemon peel powder (LP2), 1 % lemon peel extract (LE1), or 2 % lemon peel extract (LE2) on the quality of Red Globe table grapes during 14-day ambient storage. The highest weight loss (33.2 %) occurred in uncoated samples, while LP1 had the lowest (20.4 %), indicating improved moisture retention. The initial pH of uncoated table grapes (3.63) increased to 4.23 by the end of storage. All coatings slowed this increase, resulting in final pH values ranging from 4.03 to 4.10. Regarding antioxidant-related parameters, LP1 showed higher total polyphenol content (TPC), ascorbic acid content, antioxidant activity (DPPH assay), and total monomeric anthocyanin (TMA) by 43.7 %, 25.0 %, 24.1 %, and 10.1 %, respectively, compared to uncoated samples. Among extract-enriched coatings, only LE1 maintained significantly higher antioxidant activity (75.8 %), while TPC and ascorbic acid levels were comparable to those of the uncoated samples. TMA content in LE-treated table grapes (23.6–22.5 mg CGE/100 g) was lower than in uncoated samples (26.7 mg CGE/100 g). Multivariate analyses (PCA, HCA) revealed distinct clustering between coated and uncoated samples, with LP1 showing the most pronounced separation. These results indicate that LP1 treatment may help reduce weight loss and support antioxidant stability, offering a potentially sustainable postharvest strategy for table grapes.
Open Access: Yes
Value of Robotics: Comparison of Three Different High-Intensity Training Programs for Rehabilitation After Stroke
Publication Name: Sensors
Publication Date: 2025-12-01
Volume: 25
Issue: 24
Page Range: Unknown
Description:
Strokes are one of the leading causes of adult disability. There are a wide range of therapies available in stroke care for people with stroke, but there can be wide variations in the effectiveness of these therapies, so it is essential to review and compare them from time to time. In our study, we measured and compared the effectiveness of three high-intensity therapies: an agility training program without technological tools, a virtual reality exergaming training program with a low-cost device, and a high-cost robotic training program using augmented and virtual reality. All three therapies helped to improve the patients’ functional abilities, balance, and gait. On average, endurance increased by 104–177%, balance scores by 36–53%, and gait speed by 5–10% depending on the intervention. Robotic therapy and exergaming facilitate greater improvements in walking speed, step length, and balance-related gait metrics. These findings have profound implications for stroke rehabilitation, advocating for the prioritization of robotic and exergaming interventions over conventional functional therapies, like agility training. Given the limited sample size, the results should be interpreted as preliminary, highlighting the need for further studies with larger cohorts.
Open Access: Yes
DOI: 10.3390/s25247667
Chasing a Phantom Dysfunction: A Position Paper on Current Methods in Exercise Addiction Research
Publication Name: International Journal of Mental Health and Addiction
Publication Date: 2025-12-01
Volume: 23
Issue: 6
Page Range: 4600-4611
Description:
Exercise addiction has been investigated for almost half a decade in well over 1000 published papers. Studies adopt different terminologies like exercise addiction, overexercise, exercise dependence, compulsive exercise, obligatory exercise, and the like to refer to the same concept while creating conceptual confusion and rendering cross-study comparability challenging. The paradox is that fewer than ten research articles cover cases of clinical significance, yielding an extremely high ratio of publications to problematic cases. While there is evidence that significantly more clinically attention-meriting cases might exist, they surface in clinical practice rather than research settings. It is also peculiar that scholars search for a common path or shared etiology for exercise addiction, while each case, like those in substance use disorder, is unique, as also predicted by clinical models. Furthermore, the survey method uses scales yielding risk scores without diagnostic value. Most research in this direction, therefore, seems to be futile. Thus, it is not surprising that more than 10 years ago, the panel editing the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) found insufficient evidence for exercise addiction being a mental dysfunction. As a result, exercise addiction has no clinical diagnostic criteria. This position paper aims to identify conceptual and methodological research barriers that hinder progress in this field, ultimately calling for a paradigm shift toward more productive research. In conclusion, the position of this paper is that most currently used research methodologies on exercise addiction are unsatisfactory and, consequently, a paradigm shift is urgently needed.
Open Access: Yes
The impact of machine learning applications in agricultural supply chain: a topic modeling-based review
Publication Name: Discover Food
Publication Date: 2025-12-01
Volume: 5
Issue: 1
Page Range: Unknown
Description:
Machine learning (ML) has become a pivotal element in agriculture, providing groundbreaking solutions to tackle intricate issues related to productivity, sustainability, and resource management. A comprehensive examination of the current literature is crucial as the discipline evolves, allowing for the identification of significant themes, trends, and focal discussions. The current study employs latent Dirichlet allocation (LDA)-based topic modeling to examine 1114 publications regarding ML applications in agriculture, sourced from the Scopus database. The analysis indicates notable expansion in ML studies, featuring leading publications across various interdisciplinary fields. Six primary areas have been identified: precision agriculture and remote monitoring, molecular and food composition analysis, food systems and agricultural applications, quality assurance and adulteration detection, advanced financial and technological applications in ML, and predictive modeling for agricultural success and efficiency. Every topic is examined to highlight its contributions and possible avenues for further investigation. The analysis offers theoretical perspectives on the interdisciplinary aspects of ML in agriculture, along with practical applications for farmers, agribusiness experts, policymakers, and technologists. This study represents the first thorough review of ML applications in agriculture utilizing the LDA approach. It provides a current and comprehensive understanding of the field, while also uncovering emerging areas and opportunities for future exploration.
Open Access: Yes
A comprehensive narrative review on precision medicine approach to hypertension: exploring the role of genetics, epigenetics, microbiome, and artificial intelligence
Publication Name: Journal of Health Population and Nutrition
Publication Date: 2025-12-01
Volume: 44
Issue: 1
Page Range: Unknown
Description:
Background: Hypertension (HTN) impacts approximately 1.28 billion individuals globally and poses a great burden of disease. The objectives of this study are to explore the role of genetics, epigenetics, microbiome, and artificial intelligence (AI) in the management of HTN. A thorough literature search was conducted across various databases including PubMed, Google Scholar, Web of Science (WoS), and Medline to retrieve articles related to the role of genetics, epigenetics, microbiome, and AI in the precision medicine of HTN. Genes—including ACE, NOS3, ADD1, CYP11B2, NPPA, and NPPB—have a profound impact on blood pressure (BP) regulation in our body and polymorphism in these key genes can lead to HTN. Up or down-regulation of genes by epigenetic factors such as miRNA-155, miRNA-210, and miRNA-122 can significantly contribute to the development of HTN. These genetic and epigenetic factors can also be used as specific targets for gene editing and gene therapy for long-term management of HTN. However, the implementation of these techniques has not been possible in clinical settings due to lack of human studies and safety concerns related to unpredictable DNA alterations, nucleotide deletions, and loss of allele-specific chromosomes. Modulation of gut microbiome through oral supplements, fecal microbiota transplant (FMT), and dietary interventions has emerged as one the most effective and safe techniques for managing HTN in human models. AI-based cutting-edge models have helped curate personalized diet plans based on an individual’s unique microbiome, genomic information, and physiological conditions leading to a reduction in BMI, fat, BP, and heart rate while improving overall cardiac health and gut microbial diversity. Despite the significant advantages offered by AI-based medicine, ethical concerns—related to data privacy, bias, and discrimination—and ineffective models have led to limited integration of AI in precision medicine of HTN. The integration of genetics, epigenetics, microbiome, and AI-based models can play a key role in improving the current landscape of precision medicine of HTN. These cutting-edge techniques can lead to a shift from the current one-size-fits all approach to more personalized treatment plan however further research in human models is needed to determine the safety and true efficacy of these techniques. Additionally, new AI-models need to be developed that address ethical concerns and are effective in real-world clinical settings.
Open Access: Yes
Health and well-being surveys in higher education: a scoping review
Publication Name: International Journal of Educational Research Open
Publication Date: 2025-12-01
Volume: 9
Issue: Unknown
Page Range: Unknown
Description:
Objective: Higher education institutions increasingly recognize student and staff well-being as critical to institutional success. This scoping review examines existing university health and well-being surveys to support the development of a standardized assessment framework for informed decision-making. Methods: The review follows PRISMA-ScR guidelines. The protocol was registered in the Open Science Framework. A total of 237 full-text articles were systematically reviewed and analyzed using a predefined structured framework. Results: The review identified and detailed the key features of existing surveys, including the topics covered, the measurement instruments employed, and other methodological characteristics. A classification system was developed to categorize questionnaires, and a hierarchical model was established to link relevant surveys to corresponding themes. Conclusions: To the best of our knowledge, this is the first scoping review of health and well-being surveys conducted among university members. The findings provide valuable insights for improving future survey designs and advancing comprehensive well-being assessments in higher education.
Open Access: Yes
Analysis of Wireless Communications for Smart Grid: MABAC Model Based on Complex Propositional Picture Fuzzy Sugeno Weber Power Aggregation Information
Publication Name: Systems and Soft Computing
Publication Date: 2025-12-01
Volume: 7
Issue: Unknown
Page Range: Unknown
Description:
In this study, the shortcoming of the conventional procedure is demonstrated by proposing the novel technique of complex propositional picture fuzzy sets with some fundamental concepts based on algebraic and Sugeno Weber norms. In addition, the authors classified the different types of power operators based on Sugeno Weber norms for complex propositional picture fuzzy values, called the complex propositional picture fuzzy Sugeno Weber power averaging, complex propositional picture fuzzy Sugeno Weber weighted power averaging, complex propositional picture fuzzy Sugeno Weber power geometric, complex propositional picture fuzzy Sugeno Weber weighted power geometric operators and also designed their three different properties for each operator. As well, the authors designed the multi-attributive border approximation area comparison for the proposed operator. Further, wireless communication networks are playing a critical and vital role in the circumstance of development and operation of smart grids, which incorporate advanced technologies to enhance the capability, efficiency, and sustainability of electricity distribution. Finally, the designed techniques and models are applied to the wireless communications for smart grids in Taiwan. Sensitivity and comparative analysis are derived to obey the strength and competence of the developed model. This study gives an inventive decision analysis structure, which varieties a substantial contribution to wireless communication in smart grid assessment difficulties under the indeterminate situation.
Open Access: Yes
