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Found 6383 publications
Determination of Natural Blood Plasma Melatonin Concentration of Tsigai Ewes Characteristic for Gestation and Early Postpartum Period Between Autumnal Equinox and Winter Solstice
Publication Name: Veterinary Sciences
Publication Date: 2025-04-01
Volume: 12
Issue: 4
Page Range: Unknown
Description:
Melatonin is a special hormone with many functions. Its production in human and animal organisms is particularly seasonal and related to physiological processes. This study monitors blood plasma melatonin concentration in sheep during the whole gestation and early post-partum period, taking into account the effect of the season that has been less studied so far and in certain details for the first time. It proves that nocturnal plasma melatonin concentration in pregnant ewes increases between the autumnal equinox and the winter solstice in Central Europe in the Northern Hemisphere. It observes that nocturnal plasma melatonin concentration (between 18:00 p.m. and 06:00 a.m.) in pregnant ewes follows a less pronounced variation. Furthermore, it provides proof that nocturnal plasma melatonin concentration in pregnant ewes does not change as pregnancy progresses. It is the first to report that nocturnal plasma melatonin concentration decreases to the same level in ewes and new-born lambs immediately after birth, without nighty fluctuations.
Open Access: Yes
Relationship between primitive reflexes, functional fitness, handgrip strength, and physical activity in older adults aged 65 and over
Publication Name: Physiological Reports
Publication Date: 2025-04-01
Volume: 13
Issue: 7
Page Range: Unknown
Description:
The reemergence of primitive reflexes (PRs) in older adults is associated with dementia and cognitive impairment. Recent experimental work suggests gentle sensorimotor exercises may halt or reverse PR's inverse development. These findings question whether physical activity (PA) is negatively related to PRs. This study aimed to test this relationship in 52 older adults aged 66 and over who were volunteers from seven Hungarian nursing homes. They were tested individually using the Senior Test, hand-grip strength, 13 PRs, and PA levels using the Global Physical Activity Questionnaire. Apart from upper and lower body flexibility, all functional fitness indices and PA were negatively related to the number of PRs. A bootstrapped multiple hierarchical linear regression revealed that only PA was a statistically significant predictor (p < 0.001) of the PRs, accounting for 41% of the variance. This study is the first to demonstrate a robust negative relationship between PA and PRs and a weak negative association with hand-grip strength and four elements of functionality in older adults. The implications of the results could be significant for developing interventions to prevent or delay PRs' inverse development, which is associated with adverse mental health in older adults.
Open Access: Yes
DOI: 10.14814/phy2.70229
Effects of Crumb Rubber-Modified Asphalt as a Pavement Layer in Railways: A Scoping Review
Publication Name: Infrastructures
Publication Date: 2025-04-01
Volume: 10
Issue: 4
Page Range: Unknown
Description:
Railway track performance and durability face growing challenges from higher speeds, heavier axle loads, and changing environmental conditions. Crumb rubber-modified asphalt (CRMA) offers a sustainable solution by repurposing waste tires into a durable material for railway trackbeds, improving both performance and environmental impact. Following PRISMA-ScR guidelines, this scoping review synthesizes an extensive body of global research on the structural, mechanical, and environmental benefits of CRMA in railway trackbeds. A systematic literature search was conducted across major academic databases, covering studies published over several decades. Selection criteria focused on CRMA applications in railway trackbeds, using keywords such as “crumb rubber-modified asphalt”, “railway track vibration”, and “sustainable railway materials.” After rigorous screening and eligibility assessment, the most relevant peer-reviewed studies were included, emphasizing mechanical performance, durability, and environmental impact. Key findings indicate that CRMA effectively reduces ground vibrations, enhances load distribution, and lowers long-term maintenance costs while promoting sustainable waste management through tire recycling. However, challenges such as optimal mix design, potential emissions, and long-term bonding stability require further investigation. Additionally, the review was limited to English-language studies, potentially omitting relevant non-English research, and some reports were inaccessible during retrieval. This review maps critical research gaps, identifies key areas for future optimization, and highlights CRMA’s potential to advance resilient and eco-friendly railway infrastructure.
Open Access: Yes
Brain Structural Abnormalities in Patients with Post-COVID-19 Headache
Publication Name: Neurology International
Publication Date: 2025-04-01
Volume: 17
Issue: 4
Page Range: Unknown
Description:
Background/Objectives: Headache is one of the most common neurological symptoms associated with COVID-19, affecting approximately 25% of patients. While most headaches resolve within weeks, some persist for months, suggesting underlying structural brain changes. This study aimed to identify brain MRI abnormalities associated with chronic headaches in patients with a history of COVID-19 infection. Methods: This retrospective study included 30 patients with post-COVID-19 headaches and 30 control patients with no history of COVID-19. Demographic characteristics were analyzed using t-tests and chi-square tests. MRI findings were categorized into six types: cortical atrophy, white matter lesions, vascular lesions, lacunar lesions, vascular encephalopathy, and sinusitis. Differences in MRI findings between the two groups were evaluated using chi-square tests. Secondary outcomes included the analysis of symptoms accompanying headaches, diagnoses following MRI, and treatments applied. Results: White matter lesions were significantly more frequent in the post-COVID-19 group (50%) compared to controls (20%) (p = 0.015). Conversely, sinusitis was more prevalent in the control group (36.7%) than in the post-COVID-19 group (6.7%) (p = 0.005). Other MRI abnormalities showed no significant differences. Cognitive dysfunction (30%) and dizziness (33.3%) were the most common associated symptoms. The most frequent diagnoses after MRI in the post-COVID-19 group were headaches/migraines (23.3%), post-COVID-19 headache (20%), and vestibular syndrome (13.3%). Conclusions: Persistent post-COVID-19 headaches may be linked to structural white matter changes observed in MRI. Further research, ideally including pre-infection imaging data, is needed to determine the causal relationship between these lesions and chronic headache symptoms. Trial Registration: This study was registered in ClinicalTrials with the trial registration number NCT06825741 on 13 February 2025.
Open Access: Yes
Enhancing Supply Chain Safety and Security: A Novel AI-Assisted Supplier Selection Method
Publication Name: Decision Making Applications in Management and Engineering
Publication Date: 2025-04-01
Volume: 8
Issue: 1
Page Range: 22-41
Description:
The "Make or Buy" decision and the supplier selection are critical steps for the efficient operation of companies' supply chains. Safety and security are paramount considerations, especially in industries like logistics, where supply chains are vulnerable to external threats and disruptions. In this scientific article, we present a novel Artificial Intelligence (AI)-assisted supplier selection method that significantly enhances the safety and security of suppliers. During our research project, we have created an expert system and a corresponding knowledge base with the relevant rules to support supply chain decision-makers in selecting logistics service providers for warehousing services. The foundation of the AI-assisted supplier selection method is advanced data analytics and the application of expert systems, enabling companies to evaluate potential suppliers in detail from a safety and security perspective. The applied expert systems can identify potential risks and make predictions about supplier performance in the future. In the turbulent environment of the global supply chain, selecting long-term partners like warehousing services providers is critical for the success of the organization. A wrong supplier selection can hardly be reversed in warehousing services, as the cost of change is usually high. The article demonstrates the practical application of the expert system-assisted supplier selection method in a real-world supply chain environment and thoroughly analyzes the achieved results and advantages. The results show that the expert system-assisted method not only increases supplier safety and security but also contributes to improving the efficiency and sustainability of the supply chain. This article provides valuable guidance and solutions for companies looking to enhance their supplier selection using expert system technologies, thereby increasing the safety and security of their supply chains.
Open Access: Yes
The Efficacy of the Sensorimotor Training Program on Sensorimotor Development, Auditory and Visual Skills of Schoolchildren Aged 5–8 Years
Publication Name: Child and Youth Care Forum
Publication Date: 2025-04-01
Volume: 54
Issue: 2
Page Range: 323-352
Description:
Background: Around 800 million young children worldwide have cognitive-developmental limitations due to issues related to biological, environmental, and psychosocial factors. These problems lead to educational challenges, limited skill development, and higher unemployment rates. Therefore, timely interventions addressing the underlying problems in institutional settings are critically important. Objective: The authors created the “Sensorimotor Training Program” (STP) as a critical intervention to develop skills essential for starting school. This experimental study aimed to investigate the impact of the STP in an institutional setting, targeting the specific auditory and visual skills crucial for kindergarten and primary school learning. Methods: The STP comprises 120 training sessions focused on sensorimotor maturation. Seven hundred and seventy-two children aged 5–8 participated in the study, with 704 in the experimental and 68 in the control group, each containing a relatively balanced ratio of boys to girls. The study spanned six to eight months, with three to five weekly sessions. Results: The intervention resulted in significant improvements in sensorimotor development in the experimental compared to the control group [p <.001, effect size (d) =.483; auditory skills r =.605 p <.001, d =.366; visual skills r =.542, p <.001, d =.294]. The intervention group also improved compared to its baseline measurements. Conclusion: These results show that implementing the STP in school settings can improve sensorimotor development, impacting auditory and visual skills in children aged 5–8. These intervention-based improvements are above and beyond biological maturation.
Open Access: Yes
Examining the Environmental Ramifications of Asbestos Fiber Movement Through the Water–Soil Continuum: A Review
Publication Name: International Journal of Environmental Research and Public Health
Publication Date: 2025-04-01
Volume: 22
Issue: 4
Page Range: Unknown
Description:
The environmental pollution potential of asbestos products is a worldwide health issue, but their dissemination through the water–soil continuum is often an overlooked aspect. Similarly, the behavior of asbestos fibers released from the products is still not fully understood, although our knowledge is based on studies concerning their mineralogical characteristics, health effects, and waste disposal. It has been claimed and contradicted that asbestos harm is only found in air and humans. Asbestos fibers are found not only in industrial settings but also through the industrial use of asbestos cement products, which has contributed to asbestos emissions and its movement in water and soil. Asbestos fibers are diverse in their physicochemical properties, and this diversity has a significant influence on their behavior in the environment. Recent research has confirmed that asbestos can be transported by water and spread to other parts of the environment. However, the mechanisms underlying this, such as the settling of fibers, their attachment to soil particles, or their movement in groundwater, as well as the environmental and health implications, require further investigation. This paper examines the process and impact of asbestos contamination in the interconnected water, soil, and plant environmental sectors, providing a systematic review of the latest literature.
Open Access: Yes
Data-Driven Pavement Performance: Machine Learning-Based Predictive Models
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-04-01
Volume: 15
Issue: 7
Page Range: Unknown
Description:
Featured Application: This research provides effective methodology for pavement performance predictions using the data obtained from finite element analysis and merging it with machine learning algorithms. Traditional methods for predicting pavement performance rely on complex finite element modelling and empirical equations, which are computationally expensive and time-consuming. However, machine learning models offer a time-efficient solution for predicting pavement performance. This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. The input variables include axle load, truck load, traffic speed, lateral wander modes, asphalt layer thickness, traffic lane width and tire types, while the output variables consist of number of passes to fatigue damage, number of passes to rutting damage, fatigue life reduction in number of years and rut depth at 1.3 million passes. A k-fold cross-validation technique was employed to optimize hyperparameters. Results indicate that LightGBM and CatBoost outperform other models, achieving the lowest mean squared error and highest R² values. In contrast, linear regression and KNN demonstrated the lowest performance, with MSE values up to 188% higher than CatBoost. This study concludes that integrating machine learning with finite element analysis provides further improvements in pavement performance predictions.
Open Access: Yes
DOI: 10.3390/app15073889
Analysis of the Correlation Between Electric Bus Charging Strategies and Carbon Emissions from Electricity Production
Publication Name: World Electric Vehicle Journal
Publication Date: 2025-04-01
Volume: 16
Issue: 4
Page Range: Unknown
Description:
Reducing carbon dioxide emissions in transportation has become a priority for achieving emission targets. Transitioning to electric vehicles significantly decreases global CO2 emissions and reduces urban noise and air pollution. The selection of efficient charging strategies for electric bus fleets substantially influences their environmental impact. This study analyzes the charging strategy for electric bus fleets based on real operational data from Győr, Hungary. It evaluates the impact of different charging times and strategies on CO2 emissions, considering the energy mixes of Hungary, Poland, Germany, and Sweden. A methodology has been developed for defining sustainable and environmentally friendly charging strategies by incorporating operational conditions as well as daily, monthly, and seasonal fluctuations in emission factors. Results indicate substantial potential for emission reduction through the recommended alternative charging strategies, although further studies regarding battery lifespan and economic feasibility of infrastructure investments are recommended. The novelty of this work lies in integrating real charging data with hourly country-specific emission intensity values to assess environmental impacts dynamically. A comparative framework of four charging strategies provides quantifiable insights into emission reduction potential under diverse national energy mixes.
Open Access: Yes
DOI: 10.3390/wevj16040240
