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Found 6374 publications
Numerical algorithm of fourth-grade nanofluid flow with heat transfer consists of aluminum alloys over a riga plate
Publication Name: Journal of Thermal Analysis and Calorimetry
Publication Date: 2025-10-01
Volume: 150
Issue: 19
Page Range: 15723-15736
Description:
The MHD (magnetohydrodynamic) fourth-grade nanofluid flow consisting of aluminum alloys (Ti6 Al4 V) nanoparticles over a Riga plate is studied. The study of fourth-grade fluids (FGFs) improves the capacity to design systems and procedures for a variety of industries, ultimately promoting performance and the durability of the product. Ti6 Al4 V nanoparticles (NPs) are dissolved in water to prepare the nanofluid. The FGF flow has been analyzed under the impacts of Arrhenius activation energy, heat source/sink, and chemical reaction. The modeled equations (momentum, energy, and fluid concentration equations) are reformed into dimension-free form through similarity conversion. The transform set of ordinary differential equations (ODEs) is numerically solved by using the parametric continuation method (PCM). For accuracy of the results, the outcomes are compared to the published work. The error between the present results and the published study is -0.00028% at M = 5.0 (magnetic parameter), which ensures that the proposed methodology and model are accurate and reliable. From the graphic results, it has been noticed that the velocity field improves with the influence of fourth-grade fluid parameter, cross-viscous coefficient, and third-grade fluid parameter. The thermal profile of NF boosts with the variation in heat source parameters and the rising number of Ti6 Al4 V-NPs.
Open Access: Yes
Uncovering key factors in differentiating fermented milk by feeding type and probiotic potential with E-nose and NIRS techniques
Publication Name: Food Control
Publication Date: 2025-10-01
Volume: 176
Issue: Unknown
Page Range: Unknown
Description:
1: This study evaluates the capabilities of near-infrared spectroscopy (NIRS) and electronic nose (E-nose) in characterizing fermented milk, focusing on the impact of feeding type and probiotic potential. Three separate trials were conducted to compare the effects of Total Mixed Ration (TMR) cow feeds enriched with polyunsaturated fatty acids against control feeds. Milk samples, collected from the feeding trials, were fermented with three Lactobacillus strains categorized based on their probiotic potential: moderate (M), non-probiotic (N), and probiotic (P). The probiotic (P) strain exhibited distinct biochemical changes that were easily identifiable by both technologies. The NIRS and E-nose datasets were analysed separately to highlight the individual strengths and unique contributions of each technique in discriminating sample attributes. Specific NIRS wavelengths (1600–1800 nm), associated with unsaturated fatty acids like oleic and linoleic acids, acted as reliable markers for distinguishing milk samples based on the feeding type, while the 1300–1600 nm range helped differentiate strains. E-nose analysis identified volatile compounds such as hexanal and 1-hexen-3-one, formed from the oxidative degradation of unsaturated fatty acids, highlighting the impact of bacterial strains and milk composition on aroma and flavor. The fatty acid profile, particularly the unsaturated fatty acids and their derivatives, played a crucial role in strain and diet selection, offering valuable insights into the development of fermented milk products with specific probiotic characteristics.
Open Access: Yes
Effect of GNSS Spoofing on GNSS-IMU Data Fusion-based Vehicle Pose Estimation
Publication Name: IFAC Papersonline
Publication Date: 2025-10-01
Volume: 59
Issue: 30
Page Range: 150-155
Description:
This paper examines the effect of GNSS spoofing on GNSS-IMU fusion-based position, velocity and attitude estimates. First, it proposes and tunes an estimator considering also IMU sensor biases and real flight data of a multicopter. Then it feeds the estimator with IMU data from a fixed flight trajectory and GNSS data from different trajectories with increasing divergence from the fixed one simulating a perfect spoofing scenario. Detailed examination of the estimates shows that spoofing has non negligible effect on velocity and especially attitude estimates. Thus any spoofing detection algorithm can not be based on attitude estimates which utilize GNSS data.
Open Access: Yes
A bibliometric investigation of chatbot applications in business and management
Publication Name: Discover Applied Sciences
Publication Date: 2025-10-01
Volume: 7
Issue: 10
Page Range: Unknown
Description:
Chatbots have become a pivotal technology in business and management. Despite their growing adoption, existing research on chatbots is diverse and fragmented, lacking a cohesive overview of the field’s development and emerging trends. This study aims to answer the core research question: “What are the major research patterns, influential contributors, and emerging themes in chatbot-related literature within business and management between 2018 and 2024?” To address this, a structured four-step bibliometric methodology was applied to systematically collect, screen, and analyze relevant literature. A total of 331 peer-reviewed journal articles published between 2018 and 2024 were retrieved from the Web of Science database. Bibliometric and metadata analyses were conducted using CiteSpace software, including keyword co-occurrence, co-citation, and collaboration network visualizations. The findings show a steady rise in chatbot publications, with the highest output in 2023 (88 articles) and 2024 (85 articles). Prolific authors include Mou Jian, Lova Rajaobelina, and Xueming Luo, while top institutions are the University System of Ohio and the Indian Institute of Management. Core themes include AI, customer service, trust, and consumer experience, with emerging topics such as large language models and service quality. Influential cited works focus on anthropomorphism, technology acceptance, and generative AI. This study provides quantitative insights into the evolution of chatbot research, highlights key contributors and trends, and offers practical implications for improving chatbot design and adoption in business contexts.
Open Access: Yes
Examining the Determinants of Pedestrian Safety Risks in the Bangkok Metropolitan Region, Thailand
Publication Name: Sage Open
Publication Date: 2025-10-01
Volume: 15
Issue: 4
Page Range: Unknown
Description:
Transportation systems are complex and multimodal, comprising diverse travel modes that often compete for limited roadway space. However, the diversity of these modes also generates varying levels of exposure and vulnerability, particularly among pedestrians, who represent the most at-risk group of road users. This study investigates the determinants of Pedestrian Safety (PS) within the Bangkok Metropolitan Region (BMR), focusing on behavioral, and environmental risk factors. Data was collected through a structured questionnaire distributed to 1,120 participants who had encountered potentially hazardous situations while walking. Ordinal logistic regression was used to examine the multifaceted influences shaping pedestrian risk behaviors across three user groups: (1) the general pedestrian population, (2) predominant pedestrian mode users, and (3) individuals with prior pedestrian accident experiences. The findings reveal that physical environmental characteristics and perceived behavioral control, particularly the availability and condition of pedestrian-supportive facilities have significant effects on risk-related behaviors. These results highlight the need for a comprehensive and context-sensitive approach to understanding pedestrian risk and for developing targeted interventions and strategic plans aimed at preventing pedestrian-related crashes in rapidly urbanizing environments.
Open Access: Yes
The Circle Group Heuristic to Improve the Efficiency of the Discrete Bacterial Memetic Evolutionary Algorithm Applied for TSP, TRP, and TSPTW
Publication Name: Symmetry
Publication Date: 2025-10-01
Volume: 17
Issue: 10
Page Range: Unknown
Description:
The quality of the initial population is a critical factor in the convergence speed and overall performance of an optimization algorithm. A well-structured initial population can significantly enhance the exploration capabilities of the algorithm, allowing it to more efficiently traverse the solution space and converge more quickly and reliably towards optimal or near-optimal solutions. In this paper, we present the Circle Group Heuristic (CGH), a spatially structured initialization method, for generating high-quality initial populations to enhance the convergence speed of the Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA) in solving the Traveling Salesman Problem (TSP) and related combinatorial optimization problems. This work extends the CGH beyond the TSP to a broader class of routing problems. The results show that the integration of CGH into DBMEA demonstrated consistent performance improvements on the TSP, the Traveling Repairman Problem (TRP), and the Traveling Salesman Problem with Time Window (TSPTW) instances of varying sizes. In particular, CGH provided high-quality starting points that accelerated convergence and reduced computational cost. In all tested scenarios, DBMEA enhanced with CGH and consistently preserved the best-known solution quality while reducing execution time.
Open Access: Yes
DOI: 10.3390/sym17101683
Driving the Consumer Adoption of Halal Cosmetics: A Systematic Review Using PRISMA and TCCM Framework
Publication Name: Journal of Cosmetic Dermatology
Publication Date: 2025-10-01
Volume: 24
Issue: 10
Page Range: Unknown
Description:
Background: The COVID-19 epidemic has fuelled increasing anxiety regarding the environment and religiosity. Moreover, the worldwide halal cosmetics industry is expected to experience significant growth in the years ahead. Still, the reasons that drove people all across to choose halal cosmetics are unclear. Objectives: The study aims to find factors influencing halal cosmetics purchases. Based on the findings, the review proposes a conceptual framework and new directions for future research in the context of halal cosmetics. Method: The PRISMA & TCCM framework systematically evaluates 51 empirical articles on consumers' behaviors regarding the purchase of halal cosmetics from Scopus between 2014 and 2024 for the review. Results: The review suggests forthcoming investigations to utilize Consumer Culture theory, Social Practice theory, and the UTAUT model. By highlighting patterns in halal cosmetics literature, the paper helps to guide future research in underexplored domains such as artificial intelligence and e-commerce. Practical Implications: The review contributes to the existing corpus of knowledge regarding the theoretical perspective of contemporary halal marketing through its proposed conceptual framework. In particular, scholars, academicians, and practitioners may delve into the reliable body of literature on halal cosmetics. Originality/Value: This study examines consumer behavior regarding the consumption of halal cosmetics. It pinpoints research gaps and offers future avenues using the TCCM framework. In addition, it provides the conceptual framework for measuring the behavior of halal cosmetics.
Open Access: Yes
DOI: 10.1111/jocd.70479
Assessing the Chronic Environmental Risk of Graphene Oxide Using a Multimarker Approach Across Three Trophic Levels of the Aquatic Ecosystem
Publication Name: Nanomaterials
Publication Date: 2025-10-01
Volume: 15
Issue: 20
Page Range: Unknown
Description:
With the rapid increase in the synthesis and application of graphene oxide (GO), questions have emerged about its inadvertent entry into aquatic habitats and the ecological consequences associated with such exposure While several studies have addressed the acute effects of GO, knowledge on its chronic impacts across multiple trophic levels remains limited. In this study, we assessed the chronic toxicity of a well-characterized GO product using model organisms representing three trophic levels: the bioluminescent marine bacterium Aliivibrio fischeri, unicellular green algae (Chlamydomonas reinhardtii, Chlorella vulgaris, Desmodesmus subspicatus), the cyanobacterium Synechococcus elongatus, and the freshwater cladoceran Daphnia magna. Endpoints included bioluminescence inhibition in bacteria, growth inhibition in photosynthetic primary producers, and reproduction and refined physiological parameters (heart rate, feeding activity) in D. magna. Our results demonstrated clear concentration-dependent chronic effects of GO, with A. fischeri, the applied photosynthetic primary producers and D. magna exhibiting significant inhibition of bioluminescence, growth, delayed onset of reproduction, and reduced fitness parameters, respectively. Based on the collected data, a comprehensive ecotoxicological risk assessment was carried out, revealing that pristine GO may pose negligible hazard to aquatic ecosystems under environmentally relevant exposure scenarios. The outcomes clearly demonstrate the relevance of incorporating chronic and multi-trophic effects when evaluating the ecological risks of emerging nanomaterials such as GO.
Open Access: Yes
DOI: 10.3390/nano15201553
The Role of Automated Diagnostics in the Identification of Learning Disabilities: Bayesian Probability Models in the Diagnostic Assessment
Publication Name: Education Sciences
Publication Date: 2025-10-01
Volume: 15
Issue: 10
Page Range: Unknown
Description:
This study investigates the application of Bayesian probability models in the diagnostic assessment of learning disabilities. The objective of this study was to determine whether specific conditions identified in expert reports could predict subsequent diagnoses. The sample consisted of 201 expert reports on children diagnosed with learning disabilities, which were analysed using qualitative content analysis, fuzzy set qualitative comparative analysis (fsQCA), and Bayesian conditional probability models. Variables such as vocabulary, working memory index, processing speed, and visuomotor coordination were examined as potential predictors. The analysis demonstrated that Bayesian networks captured conditional links, such as the strong association between working memory and perceptual inference, as well as an unexpected negative link between vocabulary and verbal comprehension. The study concludes that Bayesian networks provide a transparent and data-driven framework for pre-screening and risk assessment in special education settings. The limitations of this study include the absence of a control group and exclusive reliance on SNI cases. Future research should explore the integration of abductive reasoning into automated diagnostic software to enhance inclusivity and support decision-making.
Open Access: Yes
