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Found 6374 publications
Estimation of Milk Casein Content Using Machine Learning Models and Feeding Simulations
Publication Name: Dairy
Publication Date: 2025-08-01
Volume: 6
Issue: 4
Page Range: Unknown
Description:
Milk quality has a growing importance for farmers as component-based pricing becomes more widespread. Food quality and precision manufacturing techniques demand consistent milk composition. Udder health, general cow condition, environmental factors, and especially feed composition all influence milk quality. The large volume of routinely collected milk data can be used to build prediction models that estimate valuable constituents from other measured parameters. In this study, casein was chosen as the target variable because of its high economic value. We developed a multiple linear-regression model and a feed-forward neural network model to estimate casein content from twelve commonly recorded milk traits. Evaluated on an independent test set, the regression model achieved R2 = 0.86 and RMSE = 0.018%, with mean bias = +0.003% and slope bias = −0.10, whereas the neural network improved performance to R2 = 0.924 and RMSE = 0.084%. In silico microgreen inclusion from 0% to 100% of dietary dry matter raised the predicted casein concentration from 2.662% to 3.398%, a relative increase of 27.6%. To extend practical applicability, a simulation module was created to explore how microgreen supplementation might modify milk casein levels, enabling virtual testing of dietary strategies before in vivo trials. Together, the predictive models and the microgreen simulation form a cost-effective, non-invasive decision-support tool that can accelerate diet optimization and improve casein management in precision dairy production.
Open Access: Yes
DOI: 10.3390/dairy6040035
Prediction model of performance–energy trade-off for CFD codes on AMD-based cluster
Publication Name: Future Generation Computer Systems
Publication Date: 2025-08-01
Volume: 169
Issue: Unknown
Page Range: Unknown
Description:
This work explores the importance of performance–energy correlation for CFD codes, highlighting the need for sustainable and efficient use of clusters. The prime goal includes the optimisation of selecting and predicting the optimal number of computational nodes to reduce energy consumption and/or improve calculation time. In this work, the utilisation cost of the cluster, measured in core-hours, is used as a crucial factor in energy consumption and selecting the optimal number of computational nodes. The work is conducted on the cluster with AMD EPYC Milan-based CPUs and OpenFOAM application using the Urban Air Pollution model. In order to investigate performance–energy correlation on the cluster, the CVOPTS (Core VOlume Points per TimeStep) metric is introduced, which allows a direct comparison of the parallel efficiency for applications in modern HPC architectures. This metric becomes essential for evaluating and balancing performance with energy consumption to achieve cost-effective hardware configuration. The results were confirmed by numerous tests on a 40-node cluster, considering representative grid sizes. Based on the empirical results, a prediction model was derived that takes into account both the computational and communication costs of the simulation. The research reveals the impact of the AMD EPYC architecture on superspeedup, where performance increases superlinearly with the addition of more computational resources. This phenomenon enables a priori the prediction of performance–energy trade-offs (computing-faster or energy-save setups) for a specific application scenario, through the utilisation of varying quantities of computing nodes.
Open Access: Yes
Water Insecurity and Development Cooperation: Hungary’s Engagement in Africa
Publication Name: Grassroots Journal of Natural Resources
Publication Date: 2025-08-01
Volume: 8
Issue: 2
Page Range: 1-27
Description:
The Sustainable Development Report 2023 showed that 2.2 billion people lacked access to safely managed drinking water in 2022, with 703 million unable to access even basic services. In addition to this, the Afrobarometer’s 2024 survey indicated that Sub-Saharan Africa water supply was ranked among the top governance challenges in 39 surveyed countries. This study explores regional and urban–rural disparities in access to drinking water, while also assessing the scope and geography of Hungary’s water-related development cooperation on the continent. The methodology combines quantitative indicators from the UNICEF–WHO Joint Monitoring Programme with geospatial visualization techniques. The analysis reveals substantial inequalities in rural Eastern Africa, over 97 million people rely on surface water or unimproved sources, while Middle Africa reports more than 55 million in the same categories. In contrast, urban areas in Northern Africa show significantly better outcomes, with over 111 million having access to safely managed drinking water. These figures highlight persistent spatial divides and the critical need for targeted investment in rural service provision. Hungarian development engagement was examined through project records from the Ministry of Foreign Affairs and Trade, alongside publicly available data from Hungarian NGOs and private sector actors. The study finds that Hungary has contributed to water-related initiatives in countries such as the Democratic Republic of the Congo, Ghana, and Uganda, but has had limited involvement in other severely affected countries, including Niger (31% unsafe access), Madagascar (42%), and the Central African Republic (37%). This study addresses a significant research gap since the intersection of Hungarian development cooperation and African water security has received minimal scholarly attention to date. By offering a comprehensive, data-driven analysis of both African water access and Hungary’s related foreign engagement, the research contributes to the understanding of potential synergies and future avenues for international collaboration in this field.
Open Access: Yes
Development Process of TGDI SI Engine Combustion Simulation Model Using Ethanol–Gasoline Blends as Fuel
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-08-01
Volume: 15
Issue: 15
Page Range: Unknown
Description:
The Fit for 55 package introduced by the European Union aims to achieve a 55% reduction in greenhouse gas emissions by 2030. In parallel, increasingly stringent exhaust gas regulations have intensified research into alternative fuels. Ethanol presents a promising option due to its compatibility with gasoline, higher octane rating, and lower exhaust emissions compared to conventional gasoline. Additionally, ethanol can be derived from agricultural waste, further enhancing its sustainability. This study examines the impact of two ethanol–gasoline blends (E10, E20) on emissions and performance in a turbocharged gasoline direct injection (TGDI) spark-ignition (SI) engine. The investigation is conducted using three-dimensional computational fluid dynamics (3D CFD) simulations to minimize development time and costs. This paper details the model development process and presents the initial results. The boundary conditions for the simulations are derived from one-dimensional (1D) simulations, which have been validated against experimental data. Subsequently, the simulated performance and emissions results are compared with experimental measurements. The E10 simulations correlated well with experimental measurements, with the largest deviation in cylinder pressure being an RMSE of 1.42. In terms of emissions, HC was underpredicted, while CO was overpredicted compared to the experimental data. For E20, the IMEP was slightly higher at some operating points; however, the deviations were negligible. Regarding emissions, HC and CO emissions were higher with E20, whereas NOx and CO2 emissions were lower.
Open Access: Yes
DOI: 10.3390/app15158677
Service Difficulties, Internal Resolution Mechanisms, and the Needs of Social Services in Hungary—The Baseline of a Development Problem Map
Publication Name: Social Sciences
Publication Date: 2025-08-01
Volume: 14
Issue: 8
Page Range: Unknown
Description:
This study focuses on the current service/care difficulties and challenges that social institutions in Hungary are facing during their daily operations; how they can react to them utilizing their internal resources, mechanisms, and capacities; and what concrete, tangible needs and demands are emerging in terms of methodological professional support, potential forms, interventions, and direction for professional development. A total of 24 general and 55 specific service and operational problems were identified and assessed in eight different service areas (family and child welfare services, family and child welfare centers, respite care for children, care for the homeless, addiction intervention, care for people with disabilities, care for psychiatric patients, specialized care for the elderly, and basic services for the elderly). The empirical base of the study uses a database of 201 online questionnaires completed by a professional target group working for social service providers in two counties (Győr-Moson-Sopron and Veszprém), representing 166 social service providers. The questionnaires were completed between November and December of 2022. The findings will be used to develop a professional support and development problem map. Social institutions face complex and serious service/care difficulties and challenges in their daily operations. Three distinctive basic problems clearly stand out in both severity and significance from the complex set of factors assessed. The biggest problem in the social care system is clearly the complex challenge of low wages, followed by the administrative burdens in the ranking of operational difficulties, and the third key factor was the psycho-mental workload of staff.
Open Access: Yes
Synergistic Effects of CuO and ZnO Nanoadditives on Friction and Wear in Automotive Base Oil †
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-08-01
Volume: 15
Issue: 15
Page Range: Unknown
Description:
Efficient lubrication lowers friction, wear, and energy losses in automotive drivetrain components. Advanced lubricants are key to sustainable transportation performance, durability, and efficiency. This study analyzes the tribological performance of Group III base oil with CuO and ZnO nanoadditive mixtures. These additives enhance the performance of Group III base oils, making them highly relevant for automotive lubricant applications. An Optimol SRV5 tribometer performed ball-on-disk sliding contact tests with 100Cr6 steel specimens subjected to a 50 N force and a temperature of 100 °C. The test settings are designed to mimic the boundary and mixed lubrication regimes commonly seen in the automobile industry. During the tests, the effect of nanoparticles on friction was measured. Microscopic wear analysis was performed on the worn specimens. The results demonstrate that adding 0.3 wt% CuO nanoparticles to Group III base oil achieves a 19% reduction in dynamic friction and a 47% decrease in disk wear volume compared to additive-free oil. Notably, a 2:1 CuO-to-ZnO mixture produced synergy, delivering up to a 27% friction reduction and a 54% decrease in disk wear. The results show the synergistic effect of CuO and ZnO in reducing friction and wear on specimens. This study highlights the potential of nanoparticles for lubricant development and automotive applications.
Open Access: Yes
DOI: 10.3390/app15158258
Optimizing mung bean and soybean hydrolysis for the generation of bioactive peptides of potential functional food applications
Publication Name: Food Chemistry X
Publication Date: 2025-08-01
Volume: 30
Issue: Unknown
Page Range: Unknown
Description:
This study investigates the enzymatic hydrolysis of soybean (Glycine max L.) and mung bean (Vigna radiata) proteins using bromelain, ficin, papain, and pepsin to improve digestibility and functional properties. We hypothesized that mung bean's less compact structure would yield higher degree of hydrolysis (DH) and bioactive peptides compared to soybean, enhancing antioxidant capacity for functional foods. Mung bean showed significantly higher proteolysis, with a maximum DH of 46.5 ± 2.1 % (p ≤ 0.05) using 10 % bromelain for 12 h, versus soybean's 26.9 ± 1.5 % (p ≤ 0.05). Bromelain and ficin outperformed papain and pepsin, producing up to 62.3 ± 3.2 % oligopeptides and 32.4 g/100 g free amino acids in mung bean. Mung bean hydrolysates exhibited superior antioxidant activity, reaching 78.4 ± 2.5 % DPPH scavenging (p ≤ 0.05), compared to soybean's 58.9 ± 2.0 % (p ≤ 0.05), due to increased 200–1000 Da peptides. Optimal conditions (10 % enzyme, 12 h) improved solubility and bioactivity, highlighting mung bean's potential and bromelain's efficacy for sustainable food applications, warranting further protease research.
Open Access: Yes
Regional Patterns in Weed Composition of Maize Fields in Eastern Hungary: The Balance of Environmental and Agricultural Factors
Publication Name: Agronomy
Publication Date: 2025-08-01
Volume: 15
Issue: 8
Page Range: Unknown
Description:
The primary aim of this study was to explore the influence of abiotic factors on weed development in maize fields, with the goal of informing more effective weed management practices. We focused on identifying key environmental, edaphic, and agricultural variables that contribute to weed infestations, particularly before the application of spring herbicide treatments. Field investigations were conducted from 2018 to 2021 across selected maize-growing regions in Hungary. Over the four-year period, a total of 51 weed species were recorded, with Echinochloa crus-galli, Chenopodium album, Portulaca oleracea, and Hibiscus trionum emerging as the most prevalent taxa. Collectively, these four species accounted for more than half (52%) of the total weed cover. Altogether, the 20 most dominant species contributed 95% of the overall weed coverage. The analysis revealed that weed cover, species richness, and weed diversity were significantly affected by soil properties, nutrient levels, geographic location, and tillage systems. The results confirm that the composition of weed species was influenced by several environmental and management-related factors, including soil parameters, geographical location, annual precipitation, tillage method, and fertilizer application. Environmental factors collectively explained a slightly higher proportion of the variance (13.37%) than farming factors (12.66%) at a 90% significance level. Seasonal dynamics and crop rotation history also played a notable role in species distribution. Nutrient inputs, particularly nitrogen, phosphorus, and potassium, influenced both species diversity and floristic composition. Deep tillage practices favored the proliferation of perennial species, whereas shallow cultivation tended to promote annual weeds. Overall, the composition of weed vegetation proved to be a valuable indicator of site-specific soil conditions and agricultural practices. These findings underscore the need to tailor weed management strategies to local environmental and soil contexts for sustainable crop production.
Open Access: Yes
Sudden deaths of barn swallows (Hirundo rustica) caused by an invading cold front in September 2024 in Hungary
Publication Name: Magyar Allatorvosok Lapja
Publication Date: 2025-08-01
Volume: 147
Issue: 8
Page Range: 493-498
Description:
Background: The barn swallow (Hirundo rustica) is a migratory bird with a characteristic color, shiny black on the back, dirty white feathers on the belly, rust-red throat, weighing 17–20 g. This species mainly hunts flying insects, catching them in flight and the swallows are constantly hunting in the air between sunrise and sunset. As the food-scarce autumn season approaches, swallows gather in large flocks and when the daytime temperature drops permanently below 15 ºC, they leave for their wintering grounds in Africa. The birds are preparing for the migration, replenishing their body's fat depots. By the time of leaving, thebirds reach a body weight of 22–25 g, which enables them to travel thousands of kilometers. The metabolism of birds is fast, which is especially noticeable in smaller species. Shortterm starvation is already associated with a significant deterioration in nutritional status. Objectives: The carcasses of the swallows that were still alive at the time of capture, but died during transport were examined to identify to cause of sudden death. Materials and Methods: On September 16, 2024, 34 immobile and flightless swallows were delivered to the Clinic of the Department of Exotic Animal and Wildlife Medicine from the beach in Csopak, Hungary (46° 58′ 10.4″ N, 17° 56′ 13.9″ E). Five randomly selected carcasses of swallows were examined according to the standard pathological methods (dissection, histopathology, special stainings, bacteriological examination, PCR). Results and Discussion: During the dissection the body weight of the swallows delivered to the clinic was 12.0–13.0 g (12.6 g on average) which is around half of the normal bodyweight of these birds before migration. The supplementary examinations were negative for known pathogens and histopathology showed extreme lack of glycogen. According to the weather data from 11th of September 2024, a cyclone with significant cooling and heavy rainfall hit Hungary. The reason behind the death of the swallows was starvation caused by the sudden disappearance of the population of flying insects that could be caught by swallows due to cold and rainy weather. This case draws attention to the dangers of sudden extreme effects of global climate change in the case of some sensitive animal populations.
Open Access: Yes
