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A hybrid CRITIC-MAIRCA framework for optimal phase change material selection in solar distillation systems

Gusztáv Fekete Vedant Singh Prabhakar Bhandari Meizi Wang Lalit Ranakoti Akashdeep Negi Tej Singh

Publication Name: International Journal of Thermofluids

Publication Date: 2025-05-01

Volume: 27

Issue: Unknown

Page Range: Unknown

Description:

Phase change materials (PCMs) serve as an efficient thermal energy storage mediums across a range of thermal systems, including solar distillations. The selection of an appropriate PCM candidate is a vital integration aspect that affects solar distillation performance. Therefore, the present research introduces a multi-criteria decision-making (MCDM) framework for identifying suitable PCM candidates for application in solar distillation systems. Evaluation indices include eighteen PCM alternatives and seven criteria, which were established from the literature. Criteria importance through intercriteria correlation (CRITIC) method was used to assign objective weights to the criteria, followed by the MAIRCA (multi-attributive ideal-real comparative analysis) approach to rank PCM alternatives. The proposed MCDM model suggests the suitability of paraffin wax followed by soy wax and beeswax PCMs for solar distillation applications, respectively. The comparative analysis, sensitivity analysis, and Kendall rank correlation effectively validated the rankings, demonstrating a robust positive correlation among the results. This study can serve as a preliminary step for experimental and simulation-based investigations aimed at optimizing the selection of PCM in the early stage, thereby reducing the time and costs associated with further analysis.

Open Access: Yes

DOI: 10.1016/j.ijft.2025.101167

Analysis and Prediction of Traffic Conditions Using Machine Learning Models on Ikorodu Road in Lagos State, Nigeria

Majid Movahedi Rad Udeme Udo Imoh

Publication Name: Infrastructures

Publication Date: 2025-05-01

Volume: 10

Issue: 5

Page Range: Unknown

Description:

Traffic counts are essential for assessing road capacity to provide efficient, effective, and safe mobility. However, current methods for generating models for traffic count studies are often limited in their accuracy and applicability, which can lead to incorrect or imprecise estimates of traffic volume. This study focused on analyzing and predicting traffic conditions on Ikorodu Road in Lagos State. The analysis involved an examination of historical traffic data, specifically focusing on daily and hourly traffic volumes. The prediction involved the use of machine learning models, including decision trees, gradient boosting, and random forest classifiers. The results of this study revealed significant variations in traffic volume across different days of the week and times of the day, indicating peak and off-peak periods. The study also highlighted the need for a more comprehensive approach that includes additional factors, such as weather conditions, road work, and special events, which could significantly impact traffic volume.

Open Access: Yes

DOI: 10.3390/infrastructures10050122

Corporate Social Responsibility from the Aspect of Sustainability—Evidence from the Hungarian HR Sector

Dóra Lakosy Julia Szoke

Publication Name: Administrative Sciences

Publication Date: 2025-05-01

Volume: 15

Issue: 5

Page Range: Unknown

Description:

Corporate social responsibility (CSR) has been long examined since every company affects its natural and social environments. This study presents research on CSR practices and their relationship with Sustainable Development Goals (SDGs) with the aim to find out about CSR from the aspect of sustainability in practice. The study reviews the theoretical framework for sustainability and CSR, and by conducting qualitative research focusing on the CSR activities of the Hungarian HR service industry, it presents the relation of these CSR practices to sustainability. This regional focus combined with the industry-specific focus provides the novelty of the study. Results show that the Hungarian HR sector has made a significant contribution to sustainable development in the areas of equality and inclusiveness in the responsible workplace and environmental/ecological responsibility. It was also found that the CSR practices of the examined HR companies greatly overlap, although differences were identified. It concludes that HR companies operating in Hungary can contribute to sustainable development and that the examined companies’ CSR practices are aligned with the SDGs, since sustainability is an integral part of their CSR strategy, though in various degrees.

Open Access: Yes

DOI: 10.3390/admsci15050159

Heritability and Trends in Selected Udder Traits and Their Relation to Milk Production in Holstein-Friesian Cows

Szabolcs Bene László Bognár Zsolt J. Kőrösi Ferenc Szabó

Publication Name: Animals

Publication Date: 2025-05-01

Volume: 15

Issue: 9

Page Range: Unknown

Description:

This study aimed to evaluate the heritability (h2) estimates of some important udder conformation traits, their relationship to each other and with production, and their phenotypic and genetic trends over a 10-year period in relatively high-yielding Holstein-Friesian cows. A total of 15,032 cows from six herds in Hungary were tested for milk (MY), butterfat (FY), and protein (PY) production yields over 305 days in first lactation. In addition, their udder conformation was scored for udder attachment (FU), rear udder height (RUH), central ligament (CL), udder depth (UD), front teat placement (FTP), and udder texture (UT) on a 1–9 linear udder score scale. REML and BLUP single-step animal model and linear regression model were used for data analysis and estimation. The production traits of the cows were quite reasonable, with 10,179.4 kg milk, 380.3 kg fat, and 333.1 kg protein in a standard lactation of 305 days. The scores of the udder conformation traits (5.4 to 6.1) were slightly above the mean of 5 on a linear scale of 1–9. The h2 for MY, FY, and PY were obtained from 0.30 to 0.35, while those for udder traits were from 0.22 to 0.41. Phenotypic (rp) and genetic (rg) correlations for the relationship between production and udder conformation were weak or negligible (ranged from −0.33 to +0.15). Most of the associations between different udder traits were generally weak, but moderate positive correlations were observed between FU and UD (rp = 0.42, rg = 0.50 or 0.57), and between FU and UT (rp = 0.36, rg = 0.33 or 0.35). There were increasing genetic trends in the milk production (b = 2.2 to 16.5), but the studied udder conformation traits did not change over time (b = 0.00 to 0.03). In our study, despite an increase in milk yield over the studied ten-year period, udder conformation traits did not change. Therefore, considering that udder conformation scores were slightly above average and that udder traits were included in the selection index, we believe that it may be necessary to reconsider the udder conformation scoring system and its inclusion in the selection index.

Open Access: Yes

DOI: 10.3390/ani15091276

Driver Distraction Detection in Extreme Conditions Using Kolmogorov–Arnold Networks

Szabolcs Fischer Janos Hollosi Mykola Sysyn Gabor Kovacs Dmytro Kurhan Viktor Nagy

Publication Name: Computers

Publication Date: 2025-05-01

Volume: 14

Issue: 5

Page Range: Unknown

Description:

Driver distraction can have severe safety consequences, particularly in public transportation. This paper presents a novel approach for detecting bus driver actions, such as mobile phone usage and interactions with passengers, using Kolmogorov–Arnold networks (KANs). The adversarial FGSM attack method was applied to assess the robustness of KANs in extreme driving conditions, like adverse weather, high-traffic situations, and bad visibility conditions. In this research, a custom dataset was used in collaboration with a partner company in the field of public transportation. This allows the efficiency of Kolmogorov–Arnold network solutions to be verified using real data. The results suggest that KANs can enhance driver distraction detection under challenging conditions, with improved resilience against adversarial attacks, particularly in low-complexity networks.

Open Access: Yes

DOI: 10.3390/computers14050184

How Weed Flora Evolves in Cereal Fields in Relation to the Agricultural Environment and Farming Practices in Different Sub-Regions of Eastern Hungary

Zita Dorner Mihály Zalai János György NAGY Erzsébet Tóth

Publication Name: Agronomy

Publication Date: 2025-05-01

Volume: 15

Issue: 5

Page Range: Unknown

Description:

This study explores the relationship between abiotic factors, farming practices, and weed growth in winter wheat fields in Eastern Hungary. It examines the order of weed dominance and the influence of soil, environmental, and agricultural variables on weed composition and diversity before herbicide application. The research was conducted across four sub-regions in the Great Hungarian Plain, each with distinct soil, hydrological, and geographical conditions. Between 2018 and 2021, 103 fields were surveyed and weed species cover was recorded using EPPO-based identification and quadrat sampling. Soil properties, environmental conditions, and farming practices were documented through soil analysis, geographical data, and farmer interviews. Statistical analyses were preformed including ANCOVA, redundancy analysis, and Shannon diversity index calculations. The results show that common weed species include Veronica hederifolia, Stellaria media, and Apera spica-venti, with winter annuals dominating. Soil compaction and salinity affected weed diversity, while increased copper and zinc concentrations had minor effects on weed coverage. Farming practices, particularly tillage systems and fertilizer use, had a significant effect on species richness and diversity. Different regional and annual weed distributions were observed, with correlation between certain tillage systems and specific weed species. The results emphasize the need for climate-conscious farming practices, and we recommend prioritising shallow cultivation and deep loosening over ploughing in order to manage weed populations effectively. These insights contribute to sustainable weed management strategies in cereal production.

Open Access: Yes

DOI: 10.3390/agronomy15051033

Key Drivers of Sustainable Marketing in the Chinese Hotel Industry: The Mediating Role of Big Data Applications and Marketing Innovation

Md Billal Hossain Yang Li Haolang Qin

Publication Name: Sustainability Switzerland

Publication Date: 2025-05-01

Volume: 17

Issue: 10

Page Range: Unknown

Description:

The service industry in China faces significant challenges in achieving environmental sustainability, with sustainable marketing emerging as a critical solution. This study aims to develop a comprehensive model combining the Stimulus–Organism–Response (SOR) theory and the Technology Acceptance Model (TAM) theory to analyze the mediating roles of big data applications and marketing innovation in fostering sustainable marketing practices. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on a sample of 319 service industry professionals in China, this study examines key factors such as environmental responsibility, consumer engagement, and organizational capabilities. The findings reveal that environmental responsibility and consumer engagement have a significant positive impact on sustainable marketing practices, with big data applications and marketing innovation serving as crucial mediators. This research provides valuable insights for service managers in China to align technological advancements and innovative approaches with sustainability objectives. Future research is encouraged to explore other industry-specific factors and extend the findings to different regions.

Open Access: Yes

DOI: 10.3390/su17104425

Optimizing Parameter Sets for Laser-Textured Piston Rings Using Design of Experiments and Multibody Dynamics Calculations

András Lajos Nagy Gabor Laki Dominika Pintér László Boros

Publication Name: Coatings

Publication Date: 2025-05-01

Volume: 15

Issue: 5

Page Range: Unknown

Description:

Friction and wear reduction in internal combustion engines are crucial for improving efficiency and durability. This study investigates the effect of microtextured surfaces on friction power loss in an engine’s piston ring-cylinder system. A numerical analysis was conducted on piston rings equipped with dimple-shaped microtextures using AVL Excite Piston & Rings, modelling a hard chromium-coated piston ring and a cast iron cylinder. The goal was to determine the optimal surface texture parameters that minimize friction power loss under typical urban driving conditions with SAE 0W-30 oil. A two-step Design of Experiments (DoE) approach was employed, where the first step involved mapping the effects of texture parameters, i.e., dimple depth (A = 0.5, 1, 1.5 µm), dimple distance (B = 120, 160, 240 µm), and dimple diameter (C = 50, 60, 70 µm), to identify influential factors. The second step aimed at locating a parameter configuration with minimal friction power loss. The results demonstrated that the optimized texture parameters can significantly reduce friction power loss. The lowest friction power loss of 8.96 W was achieved with a dimple depth of 2 µm, distance of 80 µm, and diameter of 60 µm, which contributed to an 8.3% improvement over the reference surface. The model built to describe the investigated texturing approach exhibited a strong correlation with an R2 value of 0.93, and the deviation between predicted and measured values was below 1%. Future work will involve tribometer tests to experimentally validate the optimized parameters and confirm the simulation results.

Open Access: Yes

DOI: 10.3390/coatings15050528

Laboratory Evaluation and Finite Element Modeling of SBS and Basalt Fiber Modified Mixtures

Mohammad Fahad Nagy Richard

Publication Name: Applied Sciences Switzerland

Publication Date: 2025-05-01

Volume: 15

Issue: 9

Page Range: Unknown

Description:

The incorporation of basalt fiber into asphalt mixtures offers potential improvements in their viscoelastic properties. This study explores the addition of basalt fiber to Styrene Butadiene Styrene (SBS)-modified asphalt mixtures with varying SBS contents. Specifically, 0.3% basalt fiber was added to an asphalt mixture containing 3% SBS, and its performance, measured in terms of dynamic stability and flexural strength, was compared with a mixture with 7% SBS content. Additionally, finite element analysis using the Modified Burger’s Logit model was conducted to assess rutting and fatigue behavior. Given the high cost associated with increasing the SBS content, basalt fiber presents a cost-effective alternative without sacrificing performance. Laboratory tests, including the Marshall stability test, dynamic stability, flexural strength, and fatigue tests, were conducted to evaluate both mixtures. Results indicate that the mixture with 0.3% basalt fiber and 3% SBS outperforms the 7% SBS mixture, showing a 47% improvement in dynamic stability and rutting resistance and a 16% increase in flexural strength.

Open Access: Yes

DOI: 10.3390/app15094965