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34 pages, 930 KiB  
Review
The Quality of Greek Islands’ Seawaters: A Scoping Review
by Ioannis Mozakis, Panagiotis Kalaitzoglou, Emmanouela Skoulikari, Theodoros Tsigas, Anna Ofrydopoulou, Efstratios Davakis and Alexandros Tsoupras
Appl. Sci. 2025, 15(16), 9215; https://doi.org/10.3390/app15169215 (registering DOI) - 21 Aug 2025
Abstract
Background: Greek islands face mounting pressures on their marine water resources due to tourism growth, agricultural runoff, climate change, and emerging pollutants. Safeguarding seawater quality is critical for ecosystem integrity, public health, and the sustainability of tourism-based economies. Objectives: This scoping review synthesizes [...] Read more.
Background: Greek islands face mounting pressures on their marine water resources due to tourism growth, agricultural runoff, climate change, and emerging pollutants. Safeguarding seawater quality is critical for ecosystem integrity, public health, and the sustainability of tourism-based economies. Objectives: This scoping review synthesizes and evaluates the existing research on seawater quality in the Greek islands, with emphasis on pollution sources, monitoring methodologies, and socio-environmental impacts, while highlighting the gaps in addressing emerging contaminants and aligning with sustainable development goals. Methods: A systematic literature search was conducted in Scopus, Google Scholar, ResearchGate, Web of Science, and PubMed for English- and Greek-language studies published over the last two to three decades. The search terms covered physical, chemical, and biological aspects of seawater quality, as well as emerging pollutants. The PRISMA-ScR guidelines were followed, resulting in the inclusion of 178 studies. The data were categorized by pollutant type, location, water quality indicators, monitoring methods, and environmental, health, and tourism implications. Results: This review identifies agricultural runoff, untreated wastewater, maritime traffic emissions, and microplastics as key pollution sources. Emerging contaminants such as pharmaceuticals, PFASs, and nanomaterials have been insufficiently studied. While monitoring technologies such as remote sensing, fuzzy logic, and Artificial Neural Networks (ANNs) are increasingly applied, these efforts remain fragmented and geographically uneven. Notable gaps exist in the quantification of socio-economic impact, source apportionment, and epidemiological assessments. Conclusions: The current monitoring and management strategies in the Greek islands have produced high bathing water quality in many areas, as reflected in the Blue Flag program, yet they do not fully address the spatial, temporal, and technological challenges posed by climate change and emerging pollutants. Achieving long-term sustainability requires integrated, region-specific water governance linked to the UN SDGs, with stronger emphasis on preventive measures, advanced monitoring, and cross-sector collaboration. Full article
27 pages, 1502 KiB  
Review
Monitoring of Air Pollution from the Iron and Steel Industry: A Global Bibliometric Review
by Ekaterina Zolotova, Natalya Ivanova and Sezgin Ayan
Atmosphere 2025, 16(8), 992; https://doi.org/10.3390/atmos16080992 (registering DOI) - 21 Aug 2025
Abstract
The iron and steel industry is one of the main industrial contributors to air pollution. The aim of our study is to analyze modern studies on air pollution by the iron and steel industry, as a result of which the geography and research [...] Read more.
The iron and steel industry is one of the main industrial contributors to air pollution. The aim of our study is to analyze modern studies on air pollution by the iron and steel industry, as a result of which the geography and research directions and the degree of development of current issues will be assessed, and the most cited articles and journals will be identified. A review of contemporary research (2018–2024) was conducted on the basis of articles with a digital object identifier (DOI) using machine learning methodologies (VOSviewer software version 1.6.20). The number of articles selected was 80. The heat map of study density clearly showed that the geographic distribution of studies was extremely uneven. A total of 65% of the studies were conducted in China, 9% in Nigeria, 6% in Russia, 3% in Poland, and 3% in Turkey. The remaining 14% of articles represent a series of single studies conducted in 11 countries. The revealed geographical imbalance between countries with developed production and the number of studies conducted in them shows a significant shortcoming in monitoring research. Most of the studies (20%) were devoted to the assessment of multicomponent emissions. A special place among them was occupied by the inventory of emissions using various methods. The next main directions in terms of the number of articles were aimed at studying the toxic metal emissions (19%), at the analysis of organic emissions (19%), at the modeling and forecasting of emissions (18%), and at particulate matter studies (15%). The main features of the articles for each direction are briefly noted. Citation analysis made it possible to compile a rating of articles of greatest scientific interest and the most authoritative journals. Citation network analysis revealed important insights into the structure of scientific communication in the monitoring of atmospheric pollution from the iron and steel industry. The results of our review will contribute to the consolidation of scientists, the identification of gaps in scientific knowledge, and the improvement of environmental policy and technological solutions. Full article
(This article belongs to the Section Air Pollution Control)
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16 pages, 6454 KiB  
Article
Insights into the Genomic Architecture and Improvement of the Capabilities of Acinetobacter calcoaceticus for the Biodegradation of Petroleum Hydrocarbons
by Yaning Zeng, Mutian Wang, Xiaoyu Chang, Leilei Wang, Xiaowen Fu, Yujie Huang, Fanyong Song, Lei Ji and Jianing Wang
Microorganisms 2025, 13(8), 1953; https://doi.org/10.3390/microorganisms13081953 - 21 Aug 2025
Abstract
Petroleum-contaminated terrestrial ecosystems require effective bioremediation strategies. In this study, genomic analysis revealed key biodegradation genes on the Acinetobacter calcoaceticus 21# chromosome: alkane hydroxylases (alkB, almA, LadA) and aromatic ortho-cleavage pathway genes (catABC). Phylogenetic and multiple sequence [...] Read more.
Petroleum-contaminated terrestrial ecosystems require effective bioremediation strategies. In this study, genomic analysis revealed key biodegradation genes on the Acinetobacter calcoaceticus 21# chromosome: alkane hydroxylases (alkB, almA, LadA) and aromatic ortho-cleavage pathway genes (catABC). Phylogenetic and multiple sequence alignment analyses of the almA gene in strain 21# revealed the presence of signature motifs characteristic of Baeyer–Villiger monooxygenase. Functional annotation analysis demonstrated stronger phylogenetic affinity of this protein to previously characterized BVMOs than to hydroxylases. Therefore, it is suggested that the AlmA protein in 21# exhibits BVMO activity and participates in the subterminal oxidation pathway of alkane degradation. Wild-type 21# degraded both n-Octacosane (24.47%) and pyrene (34.03%). Engineered 21#-A3 showed significantly enhanced n-Octacosane degradation (28.68%). To validate AlmA function and assess impacts of exogenous gene integration, we expressed the almA gene from A. vivianii KJ-1 via pET-28a(+)-av-almA-BH vector. Enzymatic assays demonstrated no activity toward long-chain alkanes but high activity for 2-decanone (0.39 U/mg) and 2-dodecanone (0.37 U/mg). Metabolite analysis confirmed recombinant AlmA functions through subterminal oxidation. This study establishes a foundational framework for advancing the optimization of petroleum-degrading bacteria. To engineer more efficient hydrocarbon-degrading strains, future research should integrate meta-cleavage pathways to expand their substrate utilization range for polycyclic aromatic hydrocarbons. Full article
(This article belongs to the Section Environmental Microbiology)
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20 pages, 1733 KiB  
Article
Molecular Structure, Matrix-Isolation IR Spectrum and UV-Induced Transformations of 2-Amino-5-(4-Methoxyphenyl)-1,3,4-Oxadiazole
by İsa Sidir, Susy Lopes, Rui Fausto and A. J. Lopes Jesus
Molecules 2025, 30(16), 3444; https://doi.org/10.3390/molecules30163444 - 21 Aug 2025
Abstract
The photochemistry of 1,3,4-oxadiazoles remains poorly understood, despite their recognized importance in medicinal chemistry and materials science. In this work, we report a detailed matrix-isolation study of 2-amino-5-(4-methoxyphenyl)-1,3,4-oxadiazole, combining low-temperature infrared spectroscopy with broadband UV photolysis and quantum chemical calculations. Theoretical analysis predicts [...] Read more.
The photochemistry of 1,3,4-oxadiazoles remains poorly understood, despite their recognized importance in medicinal chemistry and materials science. In this work, we report a detailed matrix-isolation study of 2-amino-5-(4-methoxyphenyl)-1,3,4-oxadiazole, combining low-temperature infrared spectroscopy with broadband UV photolysis and quantum chemical calculations. Theoretical analysis predicts the gas-phase molecule to exist exclusively as the amino tautomer, populating two nearly isoenergetic conformers (anti and syn) defined by the relative orientation of the amino and methoxy groups. Experimental IR spectra of the compound isolated in Ar and Xe matrices at 15 K confirm sole trapping of the amino tautomer. Annealing of the Xe matrix to the highest achievable temperature induced no detectable spectral changes, consistent with the predicted isoenergetic character of the conformers. Upon broadband UV irradiation (λ > 200 nm), the compound undergoes ring opening through N−N and C−O bond cleavages, paralleling the behavior of unsubstituted 1,3,4-oxadiazole system. Isocyanates emerge as the predominant photoproducts from these photochemical pathways. Additionally, spectroscopic evidence supports an alternative reaction pathway involving early-stage amino−imino tautomerization, followed by ring-opening of the imino tautomer through isocyanic acid extrusion, leading to the formation of a nitrilimine intermediate. This reactive species subsequently photorearranges into a carbodiimide via a diazirine-mediated pathway. All photoproducts were unambiguously identified through their distinct IR signatures, supported by quantum chemical calculations and reference data from structurally related systems. These findings provide unprecedented insight into the photochemical behavior of substituted 1,3,4-oxadiazoles and unveil new reaction pathways modulated by substituent effects, expanding the understanding of their photoreactivity. Full article
(This article belongs to the Section Photochemistry)
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16 pages, 1750 KiB  
Article
An Intelligent Educational System: Analyzing Student Behavior and Academic Performance Using Multi-Source Data
by Haifang Li and Zhandong Liu
Electronics 2025, 14(16), 3328; https://doi.org/10.3390/electronics14163328 - 21 Aug 2025
Abstract
Student behavior analysis plays a critical role in enhancing educational quality and enabling personalized learning. While previous studies have utilized machine learning models to analyze campus card consumption data, few have integrated multi-source behavioral data with large language models (LLMs) to provide deeper [...] Read more.
Student behavior analysis plays a critical role in enhancing educational quality and enabling personalized learning. While previous studies have utilized machine learning models to analyze campus card consumption data, few have integrated multi-source behavioral data with large language models (LLMs) to provide deeper insights. This study proposes an intelligent educational system that examines the relationship between student consumption behavior and academic performance. The system is built upon a dataset collected from students of three majors at Xinjiang Normal University, containing exam scores and campus card transaction records. We designed an artificial intelligence (AI) agent that incorporates LLMs, SageGNN-based graph embeddings, and time-series regularity analysis to generate individualized behavior reports. Experimental evaluations demonstrate that the system effectively captures both temporal consumption patterns and academic fluctuations, offering interpretable and accurate outputs. Compared to baseline LLMs, our model achieves lower perplexity while maintaining high report consistency. The system supports early identification of potential learning risks and enables data-driven decision-making for educational interventions. Furthermore, the constructed multi-source dataset serves as a valuable resource for advancing research in educational data mining, behavioral analytics, and intelligent tutoring systems. Full article
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14 pages, 680 KiB  
Article
Adaptation of the Child Coeliac Disease Food Attitudes and Behaviours Scale (Child CD-FAB) into Brazilian Portuguese: Translation and Evaluation of Reproducibility and Internal Consistency
by Marina de Cesaro Schwantes, Heather Maddison-Roberts, Eduardo Yoshio Nakano, Raquel Braz Assunção Botelho and Renata Puppin Zandonadi
Nutrients 2025, 17(16), 2704; https://doi.org/10.3390/nu17162704 - 21 Aug 2025
Abstract
Background/Objectives: This study aimed to translate the Child Coeliac Disease Food Attitudes and Behaviours Scale (Child CD-FAB) into Brazilian Portuguese and to evaluate its reproducibility and internal consistency. Methods: Three steps were carried out: (i) translation and cultural adaptation of the [...] Read more.
Background/Objectives: This study aimed to translate the Child Coeliac Disease Food Attitudes and Behaviours Scale (Child CD-FAB) into Brazilian Portuguese and to evaluate its reproducibility and internal consistency. Methods: Three steps were carried out: (i) translation and cultural adaptation of the Child CD-FAB into Brazilian Portuguese; (ii) pre-test; and (iii) psychometric evaluation of the Child CD-FAB-BR. The Child CD-FAB was translated and back-translated, and then discussed with and approved by the author of the original instrument. The translated version was tested on five children and adolescents (aged 8 to 16 years) with coeliac disease to assess comprehension. Subsequently, psychometric evaluation used responses from 20 participants with the same characteristics, assessing reproducibility (test–retest reliability) via intraclass correlation coefficient (ICC) and internal consistency via Cronbach’s alpha. Results: The Child CD-FAB was successfully translated to Brazilian Portuguese (Child CD-FAB-BR), and it presented good internal consistency (α = 0.892) and an excellent intraclass correlation coefficient (ICC = 0.923). Conclusions: The Child CD-FAB-BR is the first instrument to evaluate food attitudes and behaviours in Brazilian children and adolescents with CD, showing good psychometric properties. This instrument will support future research and clinical practice by guiding behaviour-based strategies to enhance nutritional education and public policies for this group. Full article
(This article belongs to the Special Issue Gluten-Free Diet and Supportive Nutrition Care Plans)
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17 pages, 1626 KiB  
Article
Chemical Profiling and UPLC-qTOF-MS/MS-Based Metabolomics of Three Different Parts of Edgeworthia chrysantha and Identification of Glucose Uptake-Enhancing Compounds
by Jin-Pyo An, Sohee Han, Van-Hieu Mai, Jorge-Eduardo Ponce-Zea, Gi Hyeon Seong, Thi-Kim-Quy Ha and Won Keun Oh
Nutrients 2025, 17(16), 2684; https://doi.org/10.3390/nu17162684 - 19 Aug 2025
Abstract
Background/Objectives: Edgeworthia chrysantha is rich in coumarin and flavonoid dimers, which may exhibit diverse pharmacological activities. However, to date, no metabolomics studies have been conducted and its bioactive constituents related to glucose metabolism remain uncharacterized. This study aimed to conduct a comprehensive chemical [...] Read more.
Background/Objectives: Edgeworthia chrysantha is rich in coumarin and flavonoid dimers, which may exhibit diverse pharmacological activities. However, to date, no metabolomics studies have been conducted and its bioactive constituents related to glucose metabolism remain uncharacterized. This study aimed to conduct a comprehensive chemical analysis combined with bioactivity assays to evaluate its efficacy in promoting glucose uptake. Methods: Chemical profiling of three parts (leaf, stem, and root) of E. chrysantha was performed using UPLC-Q-TOF-MS/MS spectrometry, followed by metabolomics analysis. Based on the chemical profiles and glucose uptake activity, compounds were isolated from the root. Their structures were elucidated using spectroscopic techniques, including UV, NMR, and mass spectrometry. The glucose uptake activity of the isolated compounds was assessed using a 2-NBDG assay. Results: Metabolic analysis revealed distinct chemical compositions among the plant parts. Dimeric coumarins and biflavonoids were abundant in the root, whereas flavonoid monomers were predominant in the leaf. Bioactivity-guided isolation yielded nine compounds (19), among which compound 1, a newly identified coumarin glycoside, exhibited significant glucose uptake-enhancing activity. Molecular docking analysis further suggested that compound 1 activates AMPK through an allosteric site, thereby promoting glucose uptake. Conclusions: These findings provide a comprehensive chemical and metabolomic characterization of E. chrysantha and highlight its potential as a functional food ingredient for glucose-lowering effects. Full article
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33 pages, 32635 KiB  
Article
Fire Resilience Evaluation of a Historic University Building in China
by Bo Huang, Junwu Wang and Chunbao Yuan
Appl. Sci. 2025, 15(16), 9131; https://doi.org/10.3390/app15169131 - 19 Aug 2025
Abstract
In recent years, the preservation of historic university buildings has gained increasing attention, particularly in the context of fire safety, as building fires pose significant threats to these structures. In alignment with global initiatives on resilient cities and communities, a focus on enhancing [...] Read more.
In recent years, the preservation of historic university buildings has gained increasing attention, particularly in the context of fire safety, as building fires pose significant threats to these structures. In alignment with global initiatives on resilient cities and communities, a focus on enhancing fire resilience in historic university buildings has emerged. From the perspective of fire resilience in historic university buildings, this study constructs an IDIA model for evaluating fire resilience in historic university buildings based on the improved Delphi method(ID), the Interpretive Structure Model (ISM), and the Analytical Network Process (ANP). This model objectively identifies fire resilience indicators for historic university buildings, explores the interactions between influencing factors, and analyzes the priorities of factors influencing fire resilience in historic university buildings, thereby improving the overall fire resilience of the historic university building system. This research focused on the administrative and teaching buildings of the former Central South School of Architecture and Engineering on the Mafangshan Campus of Wuhan University of Technology. The results indicate that fire resistance levels, the fire water supply system and fire awareness are extremely important indicators of fire resilience in historic university buildings. This research framework contributes to understanding the fire resilience of historic university buildings and is of vital importance for building resilient communities. Full article
(This article belongs to the Special Issue Heritage Buildings: Latest Advances and Prospects)
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27 pages, 5105 KiB  
Article
Uncovering the Genetic Identity and Diversity of Grapevine (Vitis vinifera L.) in La Palma Island (Canary Archipelago, Spain) Through SSR-Based Varietal Profiling and Population Structure Analysis
by Qiying Lin-Yang, Leonor Deis, Joan Miquel Canals, Fernando Zamora and Francesca Fort
Horticulturae 2025, 11(8), 983; https://doi.org/10.3390/horticulturae11080983 - 19 Aug 2025
Abstract
The primary challenge facing modern agriculture, including viticulture, is the impact of climate change. The scientific community recommends exploring and utilizing both inter-varietal and intra-varietal variability of local grapevines within each region. The goal is to prioritize planting local varieties over international and [...] Read more.
The primary challenge facing modern agriculture, including viticulture, is the impact of climate change. The scientific community recommends exploring and utilizing both inter-varietal and intra-varietal variability of local grapevines within each region. The goal is to prioritize planting local varieties over international and imported ones to mitigate the effects of climate change. Within this context, La Palma Island has undertaken a comprehensive assessment evaluating its viticultural heritage. A total of 96 individuals were collected and subjected to genotyping utilizing 20 simple sequence repeats (SSRs). This analysis yielded 44 unique molecular profiles, of which 3 represent new varieties reported for the first time (Aromatica Eufrosina, Cagarruta de oveja, and Viñarda rosada). Additionally, fourteen previously unreported mutations were identified, of which two contain triallelic SSRs. Consequently, the present population of local grapevines on La Palma Island comprises seven varieties (Albillo criollo, Aromatica Eufrosina, Bienmesabe tinto, Cagarruta de oveja, Gual Mazo, Sabro, and Viñarda rosada). The Bienmesabe tinto variety is possibly an interspecific cross. The varieties Aromatica Eufrosina and Viñarda rosada also presented somewhat particular behavior. The distinctiveness of this grapevine population from La Palma Island reinforces the notion that the Canary Archipelago represents a significant center of grapevine biodiversity. The volcanic activity of Tajogaite (2021) did not have a significant impact on grapevine biodiversity on the island. Full article
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25 pages, 4032 KiB  
Article
New Logistic Family of Distributions: Applications to Reliability Engineering
by Laxmi Prasad Sapkota, Nirajan Bam, Pankaj Kumar and Vijay Kumar
Axioms 2025, 14(8), 643; https://doi.org/10.3390/axioms14080643 - 19 Aug 2025
Abstract
This study introduces a novel family of probability distributions, termed the Pi-Power Logistic-G family, constructed through the application of the Pi-power transformation technique. By employing the Weibull distribution as the baseline generator, a new and flexible model, the Pi-Power Logistic Weibull distribution, is [...] Read more.
This study introduces a novel family of probability distributions, termed the Pi-Power Logistic-G family, constructed through the application of the Pi-power transformation technique. By employing the Weibull distribution as the baseline generator, a new and flexible model, the Pi-Power Logistic Weibull distribution, is formulated. Particular emphasis is given to this specific member of the family, which demonstrates a rich variety of hazard rate shapes, including J-shaped, reverse J-shaped, and monotonic increasing patterns, thereby highlighting its adaptability in modeling diverse types of lifetime data. The paper examines the fundamental properties of this distribution and applies the method of maximum likelihood estimation (MLE) to determine its parameters. A Monte Carlo simulation was performed to assess the performance of the estimation method, demonstrating that both Bias and mean square error decline as the sample size increases. The utility of the proposed distribution is further highlighted through its application to real-world engineering datasets. Using model selection metrics and goodness-of-fit tests, the results demonstrate that the proposed model outperforms existing alternatives. In addition, a Bayesian approach was used to estimate the parameters of both datasets, further extending the model’s applicability. The findings of this study have significant implications for the fields of reliability modeling, survival analysis, and distribution theory, enhancing methodologies and offering valuable theoretical insights. Full article
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49 pages, 50264 KiB  
Article
Prediction and Optimization of the Restoration Quality of University Outdoor Spaces: A Data-Driven Study Using Image Semantic Segmentation and Explainable Machine Learning
by Xiaowen Zhuang, Zhenpeng Tang, Shuo Lin and Zheng Ding
Buildings 2025, 15(16), 2936; https://doi.org/10.3390/buildings15162936 - 19 Aug 2025
Abstract
Evaluating the restoration quality of university outdoor spaces is often constrained by subjective surveys and manual assessment, limiting scalability and objectivity. This study addresses this gap by applying explainable machine learning to predict restorative quality from campus imagery, enabling large-scale, data-driven evaluation and [...] Read more.
Evaluating the restoration quality of university outdoor spaces is often constrained by subjective surveys and manual assessment, limiting scalability and objectivity. This study addresses this gap by applying explainable machine learning to predict restorative quality from campus imagery, enabling large-scale, data-driven evaluation and capturing complex nonlinear relationships that traditional methods may overlook. Using Fujian Agriculture and Forestry University as a case study, this study extracted road network data, generated 297 coordinates at 50-m intervals, and collected 1197 images. Surveys were conducted to obtain restorative quality scores. The Mask2Former model was used to extract landscape features, and decision tree algorithms (RF, XGBoost, GBR) were selected based on MAE, MSE, and EVS metrics. The combination of optimal algorithms and SHAP was employed to predict restoration quality and identify key features. This research also used a multivariate linear regression model to identify features with significant statistical impact but lower features importance ranking. Finally, the study also analyzed heterogeneity in scores for three restoration indicators and five campus zones using k-means clustering. Empirical results show that natural elements like vegetation and water positively affect psychological perception, while structural components like walls and fences have negative or nonlinear effects. On this basis, this study proposes spatial optimization strategies for different campus areas, offering a foundation for creating high-quality outdoor environments with restorative and social functions. Full article
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22 pages, 3665 KiB  
Article
Comparative Study of Linear and Non-Linear ML Algorithms for Cement Mortar Strength Estimation
by Sebghatullah Jueyendah, Zeynep Yaman, Turgay Dere and Türker Fedai Çavuş
Buildings 2025, 15(16), 2932; https://doi.org/10.3390/buildings15162932 - 19 Aug 2025
Abstract
The compressive strength (Fc) of cement mortar (CM) is a key parameter in ensuring the mechanical reliability and durability of cement-based materials. Traditional testing methods are labor-intensive, time-consuming, and often lack predictive flexibility. With the increasing adoption of machine learning (ML) in civil [...] Read more.
The compressive strength (Fc) of cement mortar (CM) is a key parameter in ensuring the mechanical reliability and durability of cement-based materials. Traditional testing methods are labor-intensive, time-consuming, and often lack predictive flexibility. With the increasing adoption of machine learning (ML) in civil engineering, data-driven approaches offer a rapid, cost-effective alternative for forecasting material properties. This study investigates a wide range of supervised linear and nonlinear ML regression models to predict the Fc of CM. The evaluated models include linear regression, ridge regression, lasso regression, decision trees, random forests, gradient boosting, k-nearest neighbors (KNN), and twelve neural network (NN) architectures, developed by combining different optimizers (L-BFGS, Adam, and SGD) with activation functions (tanh, relu, logistic, and identity). Model performance was assessed using the root mean squared error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). Among all models, NN_tanh_lbfgs achieved the best results, with an almost perfect fit in training (R2 = 0.9999, RMSE = 0.0083, MAE = 0.0063) and excellent generalization in testing (R2 = 0.9946, RMSE = 1.5032, MAE = 1.2545). NN_logistic_lbfgs, gradient boosting, and NN_relu_lbfgs also exhibited high predictive accuracy and robustness. The SHAP analysis revealed that curing age and nano silica/cement ratio (NS/C) positively influence Fc, while porosity has the strongest negative impact. The main novelty of this study lies in the systematic tuning of neural networks via distinct optimizer–activation combinations, and the integration of SHAP for interpretability—bridging the gap between predictive performance and explainability in cementitious materials research. These results confirm the NN_tanh_lbfgs as a highly reliable model for estimating Fc in CM, offering a robust, interpretable, and scalable solution for data-driven strength prediction. Full article
(This article belongs to the Special Issue Advanced Research on Concrete Materials in Construction)
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42 pages, 2302 KiB  
Article
The Role of E-Waste in Sustainable Mineral Resource Management
by Dina Mohamed, Adham Fayad, Abdel-Mohsen O. Mohamed and Moza T. Al Nahyan
Waste 2025, 3(3), 27; https://doi.org/10.3390/waste3030027 - 19 Aug 2025
Abstract
This paper analyses the role of electronic waste (E-waste) as a secondary source of critical and precious minerals, addressing the challenges and opportunities in transitioning towards a circular economy (CE) for electronics. The surging global demand for these essential materials, driven by technological [...] Read more.
This paper analyses the role of electronic waste (E-waste) as a secondary source of critical and precious minerals, addressing the challenges and opportunities in transitioning towards a circular economy (CE) for electronics. The surging global demand for these essential materials, driven by technological advancements and renewable energy infrastructure, necessitates alternative supply strategies due to the depletion of natural reserves and the environmental degradation associated with primary mining. E-waste contains a rich concentration of valuable metals, such as gold, silver, and platinum, making its recovery a promising solution aligned with CE principles, which can mitigate environmental impacts and ensure long-term material availability. This paper examines the environmental, economic, and technological aspects of E-waste recovery, focusing on core processes such as physical and mechanical separation, pyrometallurgical, hydrometallurgical, bio-metallurgical, and electrochemical techniques. It explores innovative strategies to improve material recovery efficiency and sustainability, with consideration of evolving regulatory frameworks, technological advancements, and stakeholder engagement. The analysis highlights that e-waste, particularly printed circuit boards, can contain 40–800 times more gold than mined ore, with 1000–3000 g of gold per tonne compared to 5–10 g per tonne in traditional ores. Recovery costs using advanced E-waste recycling technologies range between $10,000–$20,000 USD per kilogram of gold, significantly lower than the $30,000–$50,000 USD per kilogram in primary mining. Globally, over 50 million tonnes of E-waste are generated annually, yet less than 20% is formally recycled. Efficient recycling methods can recover up to 95% of base and precious metals under optimized conditions. The paper argues that E-waste recycling presents a viable pathway to conserve critical raw materials, reduce environmental degradation, and enhance circular economic resilience. However, it also emphasizes persistent challenges—including high initial investment, technological limitations in developing regions, and regulatory fragmentation—that must be addressed for scalable adoption. Full article
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13 pages, 2819 KiB  
Article
Stormwater in the Desert: Unveiling Metal Pollutants in Climate-Intensified Flooding in the United Arab Emirates
by Lara Dronjak, Sofian Kanan, Tarig Ali, Md Maruf Mortula, Areej Mohammed, Jonathan Navarro Ramos, Diana S. Aga and Fatin Samara
Water 2025, 17(16), 2457; https://doi.org/10.3390/w17162457 - 19 Aug 2025
Abstract
This study investigated the concentrations of metals in stormwater runoff collected during two extreme flooding events on the American University of Sharjah (AUS) campus in the United Arab Emirates (UAE). Given the increasing frequency of intense rainfall in arid regions, stormwater contamination represents [...] Read more.
This study investigated the concentrations of metals in stormwater runoff collected during two extreme flooding events on the American University of Sharjah (AUS) campus in the United Arab Emirates (UAE). Given the increasing frequency of intense rainfall in arid regions, stormwater contamination represents a growing environmental and public health concern. Stormwater samples were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES) to quantify metal concentrations. The results showed that iron (0.049–2.080 mg/L), aluminum (0.097–2.020 mg/L), and potassium (0.614–3.860 mg/L) were the most abundant metals detected. Lower concentrations were observed for manganese (0.000–0.058 mg/L), barium (0.000–0.073 mg/L), chromium (0.000–0.013 mg/L), nickel (0.000–0.038 mg/L), and vanadium (0.000–0.004 mg/L). These findings underscore the critical need for effective stormwater management in arid regions, where climate change is expected to increase the frequency and intensity of extreme weather events. Improved drainage systems and long-term monitoring are essential to mitigate the environmental and public health risks posed by stormwater contamination in rapidly urbanizing areas. Full article
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17 pages, 2406 KiB  
Article
Microscopic and Crystallographic Analysis of Increased Acid Resistance of Melted Dental Enamel Using 445 nm Diode Laser: An Ex-Vivo Study
by Samir Nammour, Marwan El Mobadder, Aldo Brugnera, Praveen Arany, Mireille El Feghali, Paul Nahas and Alain Vanheusden
Dent. J. 2025, 13(8), 376; https://doi.org/10.3390/dj13080376 - 19 Aug 2025
Abstract
Background/Objectives: This study aimed to evaluate the efficacy of a 445 nm diode laser in enhancing enamel resistance to acid-induced demineralization and to investigate the associated compositional and structural modifications using scanning electron microscopy (SEM), electron spectroscopy for chemical analysis (ESCA), and [...] Read more.
Background/Objectives: This study aimed to evaluate the efficacy of a 445 nm diode laser in enhancing enamel resistance to acid-induced demineralization and to investigate the associated compositional and structural modifications using scanning electron microscopy (SEM), electron spectroscopy for chemical analysis (ESCA), and X-ray diffraction (XRD) crystallographic analysis. Methods: A total of 126 extracted human teeth were used. A total of 135 (n = 135) enamel discs (4 × 4 mm) from 90 teeth were assigned to either a laser-irradiated group or an untreated control group for SEM, ESCA, and XRD analyses. Additionally, 24 mono-rooted teeth were used to measure pulp temperature changes during laser application. Laser irradiation was performed using a 445 nm diode laser with a pulse width of 200 ms, a repetition rate of 1 Hz, power of 1.25 W, an energy density of 800 J/cm2, a power density of 3980 W/cm2, and a 200 µm activated fiber. Following acid etching, SEM was conducted to assess microstructural and ionic alterations. The ESCA was used to evaluate the Ca/P ratio, and XRD analyses were performed on enamel powders to determine changes in phase composition and crystal lattice parameters. Results: The laser protocol demonstrated thermal safety, with minimal pulp chamber temperature elevation (0.05667 ± 0.04131 °C). SEM showed that laser-treated enamel had a smoother surface morphology and reduced acid-induced erosion compared with controls. Results of the ESCA revealed no significant difference in the Ca/P ratio between groups. XRD confirmed the presence of hydroxyapatite structure in laser-treated enamel and detected an additional diffraction peak corresponding to a pyrophosphate phase, potentially enhancing acid resistance. Results of the spectral analysis showed the absence of α-TCP and β-TCP phases and a reduction in the carbonate content in the laser group. Furthermore, a significant decrease in the a-axis lattice parameter suggested lattice compaction in laser-treated enamel. Conclusions: Irradiation with a 445 nm diode laser effectively enhances enamel resistance to acid demineralization. This improvement may be attributed to chemical modifications, particularly pyrophosphate phase formation, and structural changes including prism-less enamel formation, surface fusion, and decreased permeability. These findings provide novel insights into the mechanisms of laser-induced enhancement of acid resistance in enamel. Full article
(This article belongs to the Special Issue Laser Dentistry: The Current Status and Developments)
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