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Found 6374 publications
Exploring the state-of-the-art of halal food research using latent Dirichlet allocation
Publication Name: Discover Food
Publication Date: 2025-12-01
Volume: 5
Issue: 1
Page Range: Unknown
Description:
The rapid growth of the halal food (HF) industry has created a pressing need for a comprehensive synthesis of the existing body of knowledge. However, there remains a significant gap in the literature regarding the key themes, patterns, and emerging areas in HF research. This study addresses this gap by systematically analyzing the HF literature to identify key themes, patterns, and emerging areas of interest in the HF field. The study employs latent Dirichlet allocation (LDA)-based topic modeling to uncover and map the underlying themes in the HF literature, analyzing 738 publications from Scopus to determine the main topics and trends in HF research. The analysis reveals six main topics in HF research: (1) HF quality, safety assessment, and production methods; (2) HF supply chain management; (3) HF detection and authentication methods; (4) HF and Islamic culture; (5) HF and consumer behavior; and (6) HF and tourism and hospitality. The study identifies an overall increasing trend in HF research over the years, with particular emphasis on HF supply chain management and consumer behavior, while HF and Islamic culture received comparatively lower levels of attention. This study offers a novel and comprehensive analysis of the HF literature using LDA-based topic modeling, highlighting the key themes and patterns in the field. The insights derived from this study hold significant theoretical and practical implications for researchers, policymakers, manufacturers, retailers, and consumers in the rapidly growing HF industry. By identifying the main areas of focus and research gaps, the study serves as a valuable foundation for further research and analysis in the field, ultimately contributing to the ongoing development and evolution of HF research.
Open Access: Yes
Integrated Rough AHP and Neural Network Model for Mobile Phone Selection with Big Data Under Uncertainty
Publication Name: Journal of Intelligent and Fuzzy Systems
Publication Date: 2025-12-01
Volume: 49
Issue: 6
Page Range: 1414-1427
Description:
This paper applied an integrated approach to Multi-Attribute Decision Making (MADM) by combining the Rough Analytic Hierarchy Process (RAHP) and Neural Network, specifically a Multi-Layer Perceptron (MLP) for a specific problem of smartphone selection. The Rough Analytic Hierarchy Process, grounded in rough set theory, proves adept at handling uncertainties in decision-making processes. Through the integration of RAHP and MLP, this study provides a comprehensive framework for ranking mobile phone criteria, focusing on camera quality, selfie capabilities, audio performance, display features, battery life, and pricing. The practical example employed demonstrates the applicability of the proposed methodology in real-world decision-making scenarios, the fusion of RAHP and MLP emerges as a potent solution for Multiple Attribute Decision Making (MADM) problems, offering decision-makers confidence in navigating intricate scenarios. This integrated approach signifies a new era of robust decision-making, enhancing outcomes across diverse domains by synergizing structured prioritization and uncertainty management. The paper proceeds with a literature review, outlining existing approaches in decision-making scenarios. The methods section details the operations with rough numbers, the Rough Analytic Hierarchy Process, and the Multi-Layer Perceptron. A numerical example of mobile phone selection is presented, illustrating the application of the integrated approach. In the presented numerical example, two scenarios are provided: one without a price criterion and another with a price criterion. In the price-less scenario, the Honor Magic5 Pro is chosen, while in the scenario considering price, the Oppo Find X6 Pro is selected as the best option.
Open Access: Yes
Eating disorders and disordered eating on wrestling sport: a systematic review
Publication Name: BMC Nutrition
Publication Date: 2025-12-01
Volume: 11
Issue: 1
Page Range: Unknown
Description:
Although there are studies on the effects of eating disorders (EDs) among athletes, a limited number of studies have been conducted in wrestling. This systematic review aims to identify the prevalence of eating disorders (ED) and disordered eating (DE) in wrestling, which is important for developing healthier weight control behaviours within the sport. A systematic review was conducted following the PRISMA protocol, focusing on publications from the last 10 years. PubMed, Scopus, PsycINFO, SPORTDiscus and Web of Science were used to identify eligible studies with the searching terms “Eating disorders” AND “wrestlers” OR “Eating disorders” AND “wrestling” OR “Disordered eating” AND “wrestlers” OR “Disordered eating” AND “wrestling” OR “Anorexia Nervosa” AND “wrestlers” OR “Anorexia Nervosa” AND “wrestling” OR “Bulimia Nervosa” AND “wrestlers” OR “Bulimia Nervosa” AND “wrestling” within the timeframe from 2014 to 2024. Eight articles met the inclusion criteria. When all studies were considered as a homogeneous group, the analysis revealed: (a) wrestlers are significantly more susceptible to Eds than other branches, (b) wrestlers have unhealthy weight control behaviors to control weight for optimum performance and to enhance their muscular appearance due to body image issues. It is recommended that future research address eating disorders, which have predominantly been studied in male wrestlers, within female wrestlers as well. Additionally, it is advised to identify potential causes contributing to the elevated risk of eating disorders among wrestlers and to develop targeted prevention strategies.
Open Access: Yes
Identifying Consumer Segments for Advanced Driver Assistance Systems (ADAS): A Cluster Analysis of Driver Behavior and Preferences
Publication Name: Future Transportation
Publication Date: 2025-12-01
Volume: 5
Issue: 4
Page Range: Unknown
Description:
The rapid advancement of Advanced Driver Assistance Systems (ADAS) is reshaping the future of mobility by offering potential improvements in safety, efficiency, and driving experience, yet consumer acceptance remains uneven across regions. This study addresses the gap in knowledge and trust by examining how Hungarian drivers, as part of the Central and Eastern European context, perceive and adopt ADAS technologies. To achieve this, we conducted two expert in-depth interviews to refine the research instrument, followed by an online survey of 179 drivers. Using k-means cluster analysis, we identified three distinct consumer segments: Conservative Controllers, who demonstrate low levels of trust and willingness to adopt ADAS; Cautious Adopters, who weigh costs and benefits carefully; and Pragmatic Innovators, who are open to experimentation and display the highest acceptance and willingness to pay. The results reveal that awareness and familiarity strongly influence acceptance, highlighting the role of consumer education and transparent communication in shaping adoption. The findings suggest that manufacturers, driving schools, and policymakers can accelerate the diffusion of ADAS by developing targeted strategies tailored to different consumer groups. Strengthening knowledge and trust in these systems will not only support their market success but also contribute to safer, more sustainable transportation.
Open Access: Yes
ESG disclosure topics and reporting frameworks: exploratory research across automotive, construction, and energy industries
Publication Name: Discover Sustainability
Publication Date: 2025-12-01
Volume: 6
Issue: 1
Page Range: Unknown
Description:
Environmental, Social, and Governance (ESG) reporting and proper measurement of greenhouse gas emissions are becoming increasingly important for industries with substantial environmental impact. This research aims to assess the current state of ESG reporting practices and highlight areas for improvement across the automotive, construction and energy industries operating in the Central Eastern European (CEE) region. To achieve this aim, a multi-industry sustainability disclosure database was created and analyzed through a Python-based text-mining methodology, using term frequency-inverse document frequency and keyword-in-context analysis. The process involved extracting and preprocessing text from 60 sustainability reports for the year 2021, followed by constructing a custom dictionary of key ESG terms aligned with the European Sustainability Reporting Standards. The findings reveal considerable variance in the focus of qualitative disclosures across industries, particularly regarding climate change and biodiversity. The investigation underscores the need for enhanced transparency, consistent metrics, and rigorous validation in ESG reporting. The study also provides new insights into the technical possibilities of automated text analysis for sustainability reporting in the CEE region, and highlights key areas where improvement appears necessary.
Open Access: Yes
Biological and therapeutic implications of sex hormone-related gene clustering in testicular cancer
Publication Name: Basic and Clinical Andrology
Publication Date: 2025-12-01
Volume: 35
Issue: 1
Page Range: Unknown
Description:
Background: Gonadotropin dysregulation seems to play a potential role in the carcinogenesis of testicular germ cell tumor (TGCT). The aim of this study was to explore the expression of specific genes related to sex hormone regulation, synthesis, and metabolism in TGCT and to define specific hormonal clusters. Two publicly available databases were used for this analysis (TCGA and GSE99420). By means of hard-threshold regularized KMEANS clustering, we assigned TGCT samples into four clusters defined in respect to different expression of the sex hormone-related genes. We analysed clinical data, protein and gene expression, signaling regarding hormonal clusters. Based on whole-transcriptome gene expression, prediction of anti-cancer drug response was made by RIDGE models. Results: Cluster #1 (12–16%) consisted primarily of non-seminomatous germ cell tumor (NSGCT), characterized by high expression of PRL, GNRH1, HSD17B2 and SRD5A1. Cluster #2 (42–50%) included predominantly seminomas with high expression of SRD5A3, being highly infiltrated by T and B cells. Cluster #3 (8.3–18%) comprised of NSGCT with high expression of CGA, CYP19A1, HSD17B12, HSD17B1, SHBG. Cluster #4 (23–30%), which consisted primarily of NSGCT with a small fraction of seminomas, was outlined by increased expression of STAR, POMC, CYP11A1, CYP17A1, HSD3B2 and HSD17B3. Elevated fibroblast levels and increased extracellular matrix- and growth factor signaling-related gene signature scores were described in cluster #1 and #3. In the combined model of progression-free survival, S2/S3 tumor marker status, hormonal cluster #1 or #3 and teratoma histology, were independently associated with 25–30% increase of progression risk. Based on the increased receptor tyrosine kinase and growth factor signaling, cluster #1, #3 and #4 were predicted to be sensitive to tyrosine kinase inhibitors, FGFR inhibitors or EGFR/ERBB inhibitors. Cluster #2 and #4 were responsive to compounds interfering with DNA synthesis, cytoskeleton, cell cycle and epigenetics. Response to apoptosis modulators was predicted only for cluster #2. Conclusions: Hormonal cluster #1 or #3 is an independent prognostic factor regarding poor progression-free survival. Hormonal cluster assignment also affects the predicted drug response with cluster-dependent susceptibility to specific novel therapeutic compounds.
Open Access: Yes
Knowledge or Confidence? Exploring the Interplay of Financial Literacy, Digital Financial Behavior, and Self-Assessment in the FinTech Era
Publication Name: Fintech
Publication Date: 2025-12-01
Volume: 4
Issue: 4
Page Range: Unknown
Description:
Purpose: The central research question of the study is how objective financial knowledge and subjective financial confidence interact and relate to digital financial behavior and the use of FinTech tools. By examining both objective knowledge refers to measured, test-based financial competence and subjective confidence denote self-assessed financial understanding, the research offers insight into the psychological and demographic drivers of FinTech use and perceived financial well-being. Design/methodology/approach: Based on the OECD’s 2023 international financial literacy survey, the study uses a nationally representative Hungarian sample. It employs non-parametric statistical methods, linear regression, and two-step cluster analysis. Three composite indicators, general digital activity, digital financial engagement frequency, perceived financial security were developed to measure general digital activity, frequency of digital financial engagement, and perceived financial security. Findings: Results reveal a moderate but significant correlation between actual and self-assessed financial knowledge. Men score higher on both measures, though self-assessment bias does not significantly differ by gender. Higher education and income levels are associated with stronger financial literacy and more frequent use of FinTech tools, while age correlates negatively. However, the accuracy of self-perception is not explained by these demographic factors. Cluster analysis identifies four distinct financial knowledge profiles and five consumer digital behavior types, revealing disparities in digital financial inclusion and confidence. Originality: This research contributes a multidimensional perspective on how consumer capabilities, attitudes, and digital behavior influence FinTech adoption. By integrating behavioral, demographic, and psychological factors, the study offers practical implications for targeted financial education and the design of inclusive, human-centered digital financial services—especially relevant for emerging European markets.
Open Access: Yes
Waste-Derived Composite Selection for Sustainable Automotive Brake Friction Materials Using Novel MEREC-RAM Decision Framework
Publication Name: Lubricants
Publication Date: 2025-12-01
Volume: 13
Issue: 12
Page Range: Unknown
Description:
This study aims to identify the most suitable slag waste-filled polymer composite for automotive braking applications. It employs a hybrid multi-criteria decision-making (MCDM) model that integrates the “method based on the removal effects of criteria” (MEREC) and the “root assessment method” (RAM) method. Eight slag waste-filled polymer composites, evaluated using seven performance-defining criteria, were considered in the MCDM analysis. The performance evaluation criteria included the friction coefficient, wear, friction fluctuations, friction stability, fade-recovery aspects, and rise in disk temperature. The criteria were weighted through the MEREC approach, which identified fade% (0.2890) and wear (0.2829) as the most important attributes in the assessment. The RAM was employed to rank the alternatives and suggested that the composite alternative with 60 wt.% slag waste and 5 wt.% coir fiber proved to be the best composition for automotive braking applications. The results were validated using nine MCDM models and Spearman correlation coefficients, which showed that the ranking of alternatives was consistent and stable even when the normalization steps of MEREC were swapped. Statistical validation demonstrated a strong predictive accuracy (p < 0.05) with a strong correlation coefficient (>0.8) alongside a minimal mean absolute error. Furthermore, sensitivity analysis was performed by examining several weight situations to determine whether the priority weights influenced the ranking of the composite alternatives. The findings from both the correlation and sensitivity analyses confirm the proposed hybrid MEREC-RAM model’s consistency and effectiveness.
Open Access: Yes
Metakaolin-Enhanced Laterite Rock Aggregate Concrete: Strength Optimization and Sustainable Cement Replacement
Publication Name: Buildings
Publication Date: 2025-12-01
Volume: 15
Issue: 24
Page Range: Unknown
Description:
The growing demand for concrete in tropical regions faces two unresolved challenges: the high carbon footprint of ordinary Portland cement (OPC) and limited understanding of how supplementary cementitious materials affect the mechanical performance of laterite rock aggregates concrete. Although metakaolin (MK) is a highly reactive pozzolan, its combined use with laterite rock aggregates concrete and its influence on strength development and microstructure have not been sufficiently clarified. This study investigates the mechanical behavior and sustainability potential of laterite rock aggregate concrete in which OPC is partially replaced by MK at 0%, 5%, 10%, 15%, and 20% by weight. All mixes were prepared at a constant water–binder ratio of 0.50 and tested for workability, compressive strength, split-tensile strength, and flexural strength at 7, 14, and 28 days, with and without a polycarboxylate-based superplasticizer. The results show that MK significantly enhances the mechanical performance of laterite rock concrete, with an optimum at 10% replacement: the 28-day compressive strength increased from 35.6 MPa (control) to 53.9 MPa in the superplasticized mix, accompanied by corresponding gains in tensile and flexural strengths. SEM–EDS analyses revealed microstructural densification, reduced portlandite, and a refined interfacial transition zone, explaining the improved strength and cracking resistance. From an environmental perspective, a 10% MK replacement corresponds to an approximate 10% reduction in clinker-related CO2 emissions, while the use of locally available laterite rock reduces the dependence on quarried granite and transportation impacts. The findings demonstrate that MK-modified laterite rock concrete is a viable and eco-efficient option for structural applications in tropical regions. The study concludes that MK-enhanced laterite rock aggregate concrete can deliver higher structural performance and improved sustainability without altering conventional mix design and curing practices.
Open Access: Yes
