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34 pages, 15138 KiB

Open AccessArticle

Equivalent Porous Medium (EPM) Modeling of Karst Features for Slope Stability Analysis in Karst-Prone Weak Rock Masses

by Joan Atieno Onyango, Takashi Sasaoka, Hideki Shimada, Akihiro Hamanaka and Dyson Moses

Modelling 2025, 6(3), 81; https://doi.org/10.3390/modelling6030081 (registering DOI) - 14 Aug 2025

In weak carbonate rock masses, small-sized karst features ranging from greater than 2 cm to over 1 m in diameter can significantly compromise slope stability, yet they are often overlooked in traditional geotechnical models. This study employs the equivalent porous medium (EPM) approach [...] Read more.

In weak carbonate rock masses, small-sized karst features ranging from greater than 2 cm to over 1 m in diameter can significantly compromise slope stability, yet they are often overlooked in traditional geotechnical models. This study employs the equivalent porous medium (EPM) approach to incorporate these small-sized voids into two-dimensional finite element slope stability analysis using RS2 software (Version 11.022). By treating the matrix of karst hollows as a porous continuum, we simulate the mechanical and hydraulic influence of their presence on pit slope performance. Results show that even small voids substantially reduce the factor of safety, with destabilization intensifying as void density and pore fluid infiltration increase. Distinct failure mechanisms—including circular sliding, localized subsidence due to cavity collapse, and rockfalls from intersecting shear planes—emerge from the simulations. The stress trajectories and yield elements highlight how minor voids influence the distribution and initiation of shear and tensile failures. These findings reveal that karst features previously considered negligible can be critical structural discontinuities that trigger failure. The EPM framework thus provides a computationally efficient and mechanistically sound means of modelling the cumulative impact of small-sized karst features, bridging a significant gap in geotechnical design for karst-prone weak rock slopes. Full article

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16 pages, 2190 KiB

Open AccessArticle

Potentially Toxic Element Migration Characteristics and Bioavailability in Soils of the Black Shale Region, Western Zhejiang Province, China

by Huanyuan Chen, Baoliang Chen, Chunlei Huang, Xinzhe Lu, Ruosong Zou and Yutong Wei

Toxics 2025, 13(8), 679; https://doi.org/10.3390/toxics13080679 - 14 Aug 2025

Abstract

Some soil heavy metal pollution, such as As (Arsenic) and Cd (cadmium), in the black shale areas of western Zhejiang, exhibits significant geological background characteristics, yet the migration patterns and bioavailability are unclear. This study systematically integrated geochemical investigations of the rock-weathered soil–water–soil [...] Read more.

Some soil heavy metal pollution, such as As (Arsenic) and Cd (cadmium), in the black shale areas of western Zhejiang, exhibits significant geological background characteristics, yet the migration patterns and bioavailability are unclear. This study systematically integrated geochemical investigations of the rock-weathered soil–water–soil system to reveal the migration mechanisms and the species of the potentially toxic elements (PTEs) in black shale regions. The results showed that strongly acidic drainage (pH = 3.9) released from black shale weathering led to significant enrichment of Cd and As in soils. The mean Cd concentration (0.84 mg/kg) was 3.3 times higher than the Zhejiang background value, with active speciation (exchangeable fraction and humic acid-bound fraction) dominating during migration. This research provides a scientific basis for PTE prevention and control in geologically high-background regions. Full article

(This article belongs to the Section Metals and Radioactive Substances)

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14 pages, 4807 KiB

Open AccessArticle

Identification of Candidate Genes Related to the Husk Papillae in Foxtail Millet (Setaria italica (L.) P. Beauv)

by Meixia Tan, Yang Yang, Zhe Chen, Xiangyuan Gong, Fangfang Ma, Ming Duan, Lidong Wang and Yuanhuai Han

Plants 2025, 14(16), 2535; https://doi.org/10.3390/plants14162535 (registering DOI) - 14 Aug 2025

Abstract

Efficient and fast water uptake by seeds, facilitated by optimal soil moisture, plays a critical role in timely germination and early seedling vigor for foxtail millet production in arid and semi-arid regions. The husk, as a unique structure through which the seed contacts [...] Read more.

Efficient and fast water uptake by seeds, facilitated by optimal soil moisture, plays a critical role in timely germination and early seedling vigor for foxtail millet production in arid and semi-arid regions. The husk, as a unique structure through which the seed contacts the soil, plays an important role in water uptake and germination. Many foxtail millet germplasm accessions have papillae on the epidermis of their husks, yet the role of this trait in water uptake and germination, as well as the genetic basis and regulatory mechanism related to this trait, remain unknown. In this study, we demonstrated that the water uptake by the seeds from accessions with papillae was significantly higher than that of accessions without papillae two hours and four hours after sowing during a 10 h experiment, resulting in faster germination. Analysis of segregating ratios from two F2 populations derived from crossing between accessions with and without papillae indicated that husk papilla density was of monogenic dominance. Bulked Segregant Analysis Sequencing (BSA-Seq) showed that candidate regions on chromosome 5 were significantly associated with husk papilla density. The mapped region overlapped by the two BSA populations for papilla density included 72 genes. In combination with the expression profiles of these genes, five candidate genes were identified, encoding aquaporins, fructose transporter, and glycoside hydrolase. This study elucidated the role of husk papillae in enhancing water uptake and germination in foxtail millet, provided genetic insights into the trait, and laid the foundation for further study on the mechanism of husk papilla differentiation. Full article

(This article belongs to the Section Plant Molecular Biology)

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30 pages, 5536 KiB

Open AccessArticle

Explainable Artificial Intelligence for the Rapid Identification and Characterization of Ocean Microplastics

by Dimitris Kalatzis, Angeliki I. Katsafadou, Eleni I. Katsarou, Dimitrios C. Chatzopoulos and Yiannis Kiouvrekis

Microplastics 2025, 4(3), 51; https://doi.org/10.3390/microplastics4030051 - 14 Aug 2025

Abstract

Accurate identification of microplastic polymers in marine environments is essential for tracing pollution sources, understanding ecological impacts, and guiding mitigation strategies. This study presents a comprehensive, explainable-AI framework that uses Raman spectroscopy to classify pristine and weathered microplastics versus biological materials. Using a [...] Read more.

Accurate identification of microplastic polymers in marine environments is essential for tracing pollution sources, understanding ecological impacts, and guiding mitigation strategies. This study presents a comprehensive, explainable-AI framework that uses Raman spectroscopy to classify pristine and weathered microplastics versus biological materials. Using a curated spectral library of 78 polymer specimens—including pristine, weathered, and biological materials—we benchmark seven supervised machine learning models (Decision Trees, Random Forest, k-Nearest Neighbours, Neural Networks, LightGBM, XGBoost and Support Vector Machines) without and with Principal Component Analysis for binary classification. Although k-Nearest Neighbours and Support Vector Machines achieved the highest single metric accuracy (82.5%), k NN also recorded the highest recall both with and without PCA, thereby offering the most balanced overall performance. To enhance interpretability, we employed SHapley Additive exPlanations, which revealed chemically meaningful spectral regions (notably near 700 cm⁻¹ and 1080 cm⁻¹) as critical to model predictions. Notably, models trained without Principal Component Analysis provided clearer feature attributions, suggesting improved interpretability in raw spectral space. This pipeline surpasses traditional spectral matching techniques and also delivers transparent insights into classification logic. Our findings can support scalable, real-time deployment of AI-based tools for oceanic microplastic monitoring and environmental policy development. Full article

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10 pages, 3568 KiB

Open AccessCommunication

CRISPR-Editing AsDREBL Improved Creeping Bentgrass Abiotic Stress Tolerance

by Rong Di, Sreshta Ravikumar, Ryan Daddio and Stacy Bonos

Int. J. Plant Biol. 2025, 16(3), 89; https://doi.org/10.3390/ijpb16030089 - 14 Aug 2025

Abstract

Cool-season creeping bentgrass (Agrostis stolonifera L., As) is extensively used on golf courses worldwide and is negatively affected by several fungal diseases and abiotic stresses including drought and salinity. CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated) gene editing technology was employed [...] Read more.

Cool-season creeping bentgrass (Agrostis stolonifera L., As) is extensively used on golf courses worldwide and is negatively affected by several fungal diseases and abiotic stresses including drought and salinity. CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated) gene editing technology was employed in this project to knock out the AsDREBL (dehydration responsive element binding-like factor) gene, a potential negative regulator in stress tolerance. With our established single guide RNA (sgRNA)-based CRISPR-editing vector and optimized creeping bentgrass tissue culture system using mature seed-derived embryogenic calli of cv. Crenshaw as explant, more than 20 transgenic plants were produced by gene gun bombardment. Fifteen confirmed AsDREBL mutant plants were tested for drought and salinity tolerance by withholding water and applying salt spray in greenhouse settings. Some of the mutants were shown to be more tolerant of drought and salinity stress compared to the non-edited, wild type Crenshaw plants. Our results demonstrate that CRISPR-gene editing technology can be successfully applied to improve the agronomical traits of turfgrass. Full article

(This article belongs to the Section Plant Response to Stresses)

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19 pages, 1906 KiB

Open AccessReview

The Duodenum-Centered Neurohormonal Hypothesis of Type 2 Diabetes: A Mechanistic Review and Therapeutic Perspective

by Athena N. Kapralou, Christos Yapijakis and George P. Chrousos

Curr. Issues Mol. Biol. 2025, 47(8), 657; https://doi.org/10.3390/cimb47080657 - 14 Aug 2025

Abstract

Type 2 diabetes mellitus (T2DM) is a multifactorial disorder defined by insulin resistance, β-cell dysfunction, and chronic hyperglycemia. Although peripheral mechanisms have been extensively studied, increasing evidence implicates the gastrointestinal tract in disease onset. Insights from bariatric surgery, gut hormone signaling, and incretin-based [...] Read more.

Type 2 diabetes mellitus (T2DM) is a multifactorial disorder defined by insulin resistance, β-cell dysfunction, and chronic hyperglycemia. Although peripheral mechanisms have been extensively studied, increasing evidence implicates the gastrointestinal tract in disease onset. Insights from bariatric surgery, gut hormone signaling, and incretin-based therapies suggest that the gut contributes actively beyond nutrient absorption. Yet, a cohesive framework integrating these observations remains absent, leaving a critical gap in our understanding of T2DM’s upstream pathophysiology. This work builds upon the anti-incretin theory, which posits that nutrient-stimulated neurohormonal signals—termed “anti-incretins”—arise from the proximal intestine to counteract incretin effects and regulate glycemic homeostasis. The excess of anti-incretin signals, perhaps stimulated by macronutrient composition or chemical additives of modern diets, disrupts this balance and may cause insulin resistance and β-cell depletion, leading to T2D. We hypothesize that the neuroendocrine signals produced by cholecystokinin (CCK)-I and secretin-S cells, both located in the proximal intestine, function as endogenous anti-incretins. In this context, we hypothesize a novel model centered on the chronic overstimulation of I and S cells by high-fat, high glycemic index modern diets. This drives what we term “amplified digestion”—a state marked by heightened vagal and hormonal stimulation of biliary and pancreatic secretions, increased enzymatic and bile acid activity, and alterations in bile acid composition. This condition leads to an extended breakdown of carbohydrates, lipids, and proteins into absorbable units, thereby promoting excessive nutrient absorption and ultimately contributing to insulin resistance and progressive β-cell failure. Multiple lines of clinical, surgical, and experimental evidence converge to support our model, rooted in the physiology of digestion and absorption. Western dietary patterns appear to induce an over-digestive adaptation—marked by excessive vagal and hormonal stimulation of biliary and pancreatic secretion—which amplifies digestive signaling. This heightened state correlates with increased nutrient absorption, insulin resistance, and β-cell dysfunction. Interventions that disrupt this maladaptive signaling—such as truncal vagotomy combined with duodenal bypass—may offer novel, physiology-based strategies for T2DM treatment. This hypothesis outlines a potential upstream contributor to insulin resistance and T2DM, grounded in digestive tract-derived neurohormonal dysregulation. This gut-centered model may provide insight into early, potentially reversible stages of the disease and identify a conceptual therapeutic target. Nonetheless, both the hypothesis and the accompanying surgical strategy—truncal vagotomy combined with proximal intestinal bypass—remain highly exploratory and require systematic validation through mechanistic and clinical studies. Further investigation is warranted to clarify the molecular regulation of I and S enteroendocrine cells, including the genetic and epigenetic factors that may drive hypersecretion. While speculative, interventions—surgical or pharmacologic—designed to modulate these digestive signals could represent a future avenue for research into T2DM prevention or remission, pending rigorous evidence. Full article

(This article belongs to the Special Issue Molecular Insights into Multifactorial Causes of Insulin Resistance in Obesity)

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10 pages, 1645 KiB

Open AccessArticle

Molecular Characterization of Citrus Accessions Grown for Pre-Breeding Purposes

by Israel Felipe Gonçalves Soares, Felipe Cruz Paula, Conceição de Maria Batista Oliveira, José Dias de Souza Neto, Talles de Oliveira Santos, Rafael Nunes de Almeida, Ana Paula Candido Gabriel Berilli, Sávio da Silva Berilli, Taís Cristina Bastos Soares, Jardel Oliveira Santos, Alexandre Cristiano Santos Júnior and Monique Moreira Moulin

Curr. Issues Mol. Biol. 2025, 47(8), 656; https://doi.org/10.3390/cimb47080656 - 14 Aug 2025

Abstract

The objective of this work was to analyse the genetic diversity of a population of Citrus spp. in the south of the State of Espírito Santo, Brazil, for pre-breeding studies. For that, a total of sixty genotypes were analysed, including ten citrus varieties [...] Read more.

The objective of this work was to analyse the genetic diversity of a population of Citrus spp. in the south of the State of Espírito Santo, Brazil, for pre-breeding studies. For that, a total of sixty genotypes were analysed, including ten citrus varieties from four species of the Citrus genus. The methodology involved DNA extraction, amplification via polymerase chain reaction, and the use of a set of 16 Simple Sequence Repeat markers. These markers identified 42 alleles, with a variation of one to four alleles per locus, an average heterozygosity value of 0.53, and an average polymorphic information content of up to 0.29 per species. After the analysis, a dissimilarity matrix was generated using Jaccard distance and a dendrogram, revealing the formation of two groups: Group I, comprising Citrus sinensis varieties, and Group II, comprising varieties of Citrus latifolia, Citrus aurantifolia, and Citrus reticulata. Our study demonstrated that the combination of these markers allowed for the differentiation of genotypes within the collection. The results obtained are valuable for the future management of the collection and the efficient use of genetic diversity estimation in Citrus spp. Full article

(This article belongs to the Special Issue Molecular Breeding and Genetics Research in Plants, 2nd Edition)

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35 pages, 2758 KiB

Open AccessReview

Redox Homeostasis in Red Blood Cells: From Molecular Mechanisms to Antioxidant Strategies

by Sara Spinelli, Angela Marino, Alessia Remigante and Rossana Morabito

Curr. Issues Mol. Biol. 2025, 47(8), 655; https://doi.org/10.3390/cimb47080655 - 14 Aug 2025

Abstract

Red blood cells (RBCs) are uniquely vulnerable to oxidative stress due to their role in O₂ transport and their high content of heme iron and polyunsaturated fatty acids (PUFAs). Despite lacking nuclei and organelles, RBC homeostasis relies on a finely tuned redox [...] Read more.

Red blood cells (RBCs) are uniquely vulnerable to oxidative stress due to their role in O₂ transport and their high content of heme iron and polyunsaturated fatty acids (PUFAs). Despite lacking nuclei and organelles, RBC homeostasis relies on a finely tuned redox system to preserve membrane integrity, cytoskeletal organization, and metabolic function. Impairment of this delicate balance results in a series of oxidative events that ultimately leads to the premature clearance of RBCs from the bloodstream. This review outlines the main oxidative mechanisms that affect RBC at different levels, such as membrane, cytoskeleton, and intracellular environment, with a focus on the molecular targets of reactive species. The role of major antioxidant systems in preventing or reversing redox damage will also be examined, revealing their multiple mechanisms of action ranging from direct ROS scavenging to the enhancement of endogenous antioxidant defense pathways. Redox regulatory mechanisms in RBCs are required to maintain membrane integrity, cytoskeletal organization, and metabolic function. Disruption of these processes causes several oxidative processes that trigger premature RBC removal. Cumulative evidence places oxidative stress at the core of RBC dysfunction in both physiological aging and pathological conditions, including diabetes, inflammatory conditions, and hemolytic disorders. Antioxidant-based strategies, rather than providing generalized protection, should aim to selectively target the specific molecular pathways affected in distinct clinical settings. Full article

(This article belongs to the Special Issue Therapeutic Effects of Natural Bioactive Compounds in the Management of Human Diseases)

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23 pages, 1140 KiB

Open AccessReview

Hypersensitivity to Folic Acid and/or Folinic Acid—A Review of Clinical Cases, Potential Mechanism, Possible Cross-Allergies and Current Diagnostic Options

by Kinga Lis

Curr. Issues Mol. Biol. 2025, 47(8), 654; https://doi.org/10.3390/cimb47080654 - 14 Aug 2025

Abstract

Folic acid and its derivatives (e.g., folinic acid) are a group of water-soluble compounds collectively known as vitamin B9. Synthetic folic acid is a component of dietary supplements, medications and other pharmaceuticals and fortified foods. Folinic acid (5-formyltetrahydrofolic acid) is the active metabolite [...] Read more.

Folic acid and its derivatives (e.g., folinic acid) are a group of water-soluble compounds collectively known as vitamin B9. Synthetic folic acid is a component of dietary supplements, medications and other pharmaceuticals and fortified foods. Folinic acid (5-formyltetrahydrofolic acid) is the active metabolite of folic acid. It is used to treat vitamin B9 deficiency and as an adjunct to various combination therapies. Hypersensitivity reactions to folic acid or folinic acid are rare and occur following exposure to synthetic folic acid or its derivatives but not on natural folates. In people allergic to folates, cross-reactions are possible following exposure to folic acid analogues (including antifolates, e.g., methotrexate). The mechanism of hypersensitivity to folic acid and/or folinic acid has not been clearly established. Both IgE-dependent and non-IgE-dependent hypersensitivity reactions are likely. It is possible that folic or folinic acid is either an immunogen or a hapten. Diagnosing hypersensitivity to folic/folinic acid is difficult. There are no validated in vitro or in vivo diagnostic tests. The basophil activation test (BAT) appears to be a promising tool for diagnosing folate allergy. The aims of the manuscript were to review published clinical cases of hypersensitivity reactions to folic or folinic acid, potential mechanisms of these reactions and possible cross-allergies, and current diagnostic possibilities of folate hypersensitivity. Full article

(This article belongs to the Special Issue Molecular Mechanisms and Regulation in Allergy and Immune Diseases, Immunodeficiencies, 2nd Edition)

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23 pages, 14755 KiB

Open AccessArticle

A Database for Second World War Military Landscapes in Sardinia: Toward an Integrative Strategy of Knowledge, Representation, and Adaptive Reuse

by Giancarlo Sanna, Andrés Martínez-Medina and Andrea Pirinu

Architecture 2025, 5(3), 60; https://doi.org/10.3390/architecture5030060 - 14 Aug 2025

Abstract

This paper presents the development and structure of a geospatial (work in progress), architectural heritage database designed to document, interpret, and valorize Second World War military fortifications in Sardinia. Currently hosting over 1800 georeferenced entries—including bunkers, artillery posts, underground shelters, and camouflage systems—the [...] Read more.

This paper presents the development and structure of a geospatial (work in progress), architectural heritage database designed to document, interpret, and valorize Second World War military fortifications in Sardinia. Currently hosting over 1800 georeferenced entries—including bunkers, artillery posts, underground shelters, and camouflage systems—the database constitutes the analytical core of an interdisciplinary research framework that interprets these remnants as a coherent wartime palimpsest embedded in the contemporary landscape. By integrating spatial data, archival sources, architectural features, conservation status, camouflage typologies, and both analog and digital graphic representations, the system operates as a central infrastructure for multiscale heritage analysis. It reveals the interconnections between dispersed military structures and the wider territorial fabric, thereby laying the groundwork for landscape-based interpretation and site-specific reactivation strategies. More than a cataloging tool, the database serves as an interpretive and decision-making interface—supporting the generation of cultural itineraries, the identification of critical clusters, and the design of adaptive reuse scenarios. While participatory tools and community engagement will be explored in a second phase, the current methodology emphasizes landscape-oriented reuse strategies based on the perception, spatial storytelling, and contextual reading of wartime heritage. The methodological synergy between GIS, 3D modeling, traditional drawing, and archival research (graphic and photographic documents) contributes to a holistic vision of Sardinia’s wartime heritage as both a system of knowledge and a spatial–cultural resource for future generations. Full article

(This article belongs to the Special Issue Strategies for Architectural Conservation and Adaptive Reuse)

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12 pages, 243 KiB

Open AccessReview

Lung Carcinoids in Adolescents and Young Adults (AYAs): A Still Overlooked Clinical Entity

by Alice Laffi, Laura Pala, Chiara Catania, Marzia Locatelli, Priscilla Cascetta, Emilia Cocorocchio, Giovanni Luca Ceresoli, Daniele Laszlo, Flaminia Facella, Emily Governini, Marzia Bendoni, Giuseppe Pelosi, Fabio Conforti and Tommaso Martino De Pas

Curr. Oncol. 2025, 32(8), 458; https://doi.org/10.3390/curroncol32080458 - 14 Aug 2025

Abstract

Pulmonary carcinoids (PCs) are rare neoplasms involving typical and atypical carcinoids (TCs and ACs), defined histologically by absent or focal necrosis and mitotic counts (<2/mm² vs. 2–10/mm²), respectively. Although uncommon overall, TCs and ACs represent the most frequent non-hematologic malignancies [...] Read more.

Pulmonary carcinoids (PCs) are rare neoplasms involving typical and atypical carcinoids (TCs and ACs), defined histologically by absent or focal necrosis and mitotic counts (<2/mm² vs. 2–10/mm²), respectively. Although uncommon overall, TCs and ACs represent the most frequent non-hematologic malignancies in the pediatric population. However, significantly less is known about PC in AYAs, a population often overlooked or analyzed within pediatric or adult cohorts. In this critical review, we analyzed existing literature on PCs in the AYA population using a question-and-answer format, emphasizing the substantial gap in current knowledge in this field and the urgent unmet clinical need for future scientific proposals. First, we analyzed epidemiology and the data availability about the association between PCs in AYA patients and genetic syndromes that typically reach the maximal diagnostic incidence within this age group. We then reviewed the available literature about the pathologic characteristics, clinical presentation, and treatment strategies for localized and metastatic disease in PC AYA patients. According to our findings, a significant lack of age-specific evidence and the need for international collaboration and prospective, AYA-focused clinical studies were underscored. Advancing research in this area is essential to improve understanding and develop tailored, evidence-based therapeutic approaches for this peculiar population. Full article

(This article belongs to the Special Issue Clinical Advances and Therapeutic Challenges in Small-Cell Lung Cancer and Rare Thoracic Cancers)

21 pages, 1608 KiB

Open AccessArticle

Predicting Efficiency and Capacity of Drag Embedment Anchors in Sand Seabed Using Tree Machine Learning Algorithms

by Mojtaba Olyasani, Hamed Azimi and Hodjat Shiri

Geotechnics 2025, 5(3), 56; https://doi.org/10.3390/geotechnics5030056 - 14 Aug 2025

Abstract

Drag embedment anchors (DEAs) play a vital role in maintaining the stability and safety of offshore structures, including floating wind turbines, oil rigs, and marine renewable energy systems. Accurate prediction of anchor performance is essential for optimizing mooring system designs, reducing costs, and [...] Read more.

Drag embedment anchors (DEAs) play a vital role in maintaining the stability and safety of offshore structures, including floating wind turbines, oil rigs, and marine renewable energy systems. Accurate prediction of anchor performance is essential for optimizing mooring system designs, reducing costs, and minimizing risks in challenging marine environments. By leveraging advanced machine learning techniques, this research provides innovative solutions to longstanding challenges in geotechnical engineering, paving the way for more efficient and reliable offshore operations. The findings contribute significantly to developing sustainable marine infrastructure while addressing the growing global demand for renewable energy solutions in coastal and deep-water environments. This current study evaluated tree-based machine learning algorithms, e.g., decision tree regression (DTR) and random forest regression (RFR), to predict the holding capacity and efficiency of DEAs in sand seabed. To train and validate the results of machine learning models, the K-fold cross-validation method, with K = 5, was utilized. Eleven geotechnical and geometric parameters, including sand friction angle (φ), fluke-shank angle (α), and anchor dimensions, were analyzed using 23 model configurations. Results demonstrated that RFR outperformed DTR, achieving the highest accuracy for capacity prediction (R = 0.985, RMSE = 344.577 KN) and for efficiency (R = 0.977, RMSE = 0.821 KN). Key findings revealed that soil strength dominated capacity, while fluke-shank angle critically influenced efficiency. Single-parameter models failed to capture complex soil-anchor interactions, underscoring the necessity of multivariate analysis. The ensemble approach of RFR provided superior generalization across diverse seabed conditions, maintaining errors within ±10% for capacity and ±5% for efficiency. Full article

(This article belongs to the Special Issue Recent Developments in the Machine Learning Modeling of Geotechnical Data)

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18 pages, 9548 KiB

Open AccessArticle

Time Series Transformer-Based Modeling of Pavement Skid and Texture Deterioration

by Lu Gao, Zia Ud Din, Kinam Kim and Ahmed Senouci

Constr. Mater. 2025, 5(3), 55; https://doi.org/10.3390/constrmater5030055 - 14 Aug 2025

Abstract

This study investigates the deterioration of skid resistance and surface macrotexture following preventive maintenance using micro-milling techniques. Field data were collected from 31 asphalt pavement sections located across four climatic zones in Texas. The data encompasses a variety of surface types, milling depths, [...] Read more.

This study investigates the deterioration of skid resistance and surface macrotexture following preventive maintenance using micro-milling techniques. Field data were collected from 31 asphalt pavement sections located across four climatic zones in Texas. The data encompasses a variety of surface types, milling depths, operational speeds, and drum configurations. A standardized data collection protocol was followed, with measurements taken before milling, immediately after treatment, and at 3, 6, 12, and 18 months post-treatment. Skid number and Mean Profile Depth (MPD) were used to evaluate surface friction and texture characteristics. The dataset was reformatted into a time-series structure with 930 observations, including contextual variables such as climatic zone, treatment parameters, and baseline surface condition. A comparative modeling framework was applied to predict the deterioration trends of both skid resistance and macrotexture over time. Eight regression models, including linear, tree-based, and ensemble methods, were evaluated alongside a time series Transformer model. The results show that the Transformer model achieved the highest prediction accuracy for skid resistance (

R^{2} = 0.981

), while Random Forest performed best for macrotexture prediction (

R^{2} = 0.838

). The findings indicate that the degradation of surface characteristics after preventive maintenance is non-linear and influenced by a combination of environmental and operational factors. This study demonstrates the effectiveness of data-driven modeling in supporting transportation agencies with pavement performance forecasting and maintenance planning. Full article

23 pages, 5951 KiB

Open AccessArticle

Study on the Application Potential and Environmental Impact of Fly Ash and Calcined Coal Gangue in Cementitious Materials

by Zhaochang Zhang, Yudong Luo, Yonghong Miao, Enquan Zhou, Zhiwei Yan and Guiyu Zhang

Constr. Mater. 2025, 5(3), 54; https://doi.org/10.3390/constrmater5030054 - 14 Aug 2025

Abstract

Coal is still China’s primary energy source, and the production process of coal produces industrial byproduct coal gangue. This study explores the possibility of using industrial byproducts of thermal power generation, fly ash (FA) and calcined coal gangue (CCG), as a partial (10% [...] Read more.

Coal is still China’s primary energy source, and the production process of coal produces industrial byproduct coal gangue. This study explores the possibility of using industrial byproducts of thermal power generation, fly ash (FA) and calcined coal gangue (CCG), as a partial (10% and 20%) substitute for cement in construction materials. Methodical research was conducted to determine how these two substances affect the microstructure and macroscopic characteristics of cement-based materials. Macroscopic performance test findings indicate that replacing 20% of cement with CCG had no discernible effect on the specimens’ performance. At the same time, adding FA required 28 days to be comparable to the control group. Mercury intrusion porosimetry (MIP) test results show that using CCG can refine microscopic pores. Additional hydration products could be produced by these materials, according to analyses using Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The production of hydration products by CCG to fill the microscopic pores was further demonstrated by scanning electron microscopy (SEM) pictures. After 28 days of hydration, a layer of hydration products developed on the surface of FA. When supplementary cementitious materials (SCMs) were added, calcium hydroxide (CH) was consumed by interacting with FA and CCG to form additional hydration products, according to thermogravimetric analysis (TG) data after 28 days. Furthermore, an evaluation of FA and CCG’s effects on the environment revealed that their use performed well in terms of sustainable development. Full article

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16 pages, 728 KiB

Open AccessArticle

Response of Sunflower Genotypes to Salinity Stress Under Laboratory Conditions

by Tatenda Ocean Chiradza, Charles Shelton Mutengwa and Nyasha Esnath Chiuta

Stresses 2025, 5(3), 50; https://doi.org/10.3390/stresses5030050 - 14 Aug 2025

Abstract

Sunflower (Helianthus annuus L.) is an essential oilseed crop known for its adaptability to harsh environments including drought. However, salinity stress, affecting over 20% of global agricultural land, poses a serious threat to its productivity. This study evaluated the response of 17 [...] Read more.

Sunflower (Helianthus annuus L.) is an essential oilseed crop known for its adaptability to harsh environments including drought. However, salinity stress, affecting over 20% of global agricultural land, poses a serious threat to its productivity. This study evaluated the response of 17 sunflower genotypes under salinity stress (200 mM NaCl) and optimum (0 mM NaCl) conditions in the laboratory. The experiment was arranged in a completely randomized design with three replications and was validated through a second experimental run. Measured parameters included germination percentage and speed, root and shoot length, biomass, and water content. Stress tolerance indices (STIs) for germination, seedling length, and biomass were calculated. Combined ANOVA showed that genotype and environment interactions significantly (p < 0.001) affected all measured traits. Salinity stress significantly reduced germination, seedling growth, and biomass across genotypes, with some experiencing complete germination inhibition. Genotypes 9, 14, 16, and 17 consistently maintained higher germination, seedling length, and biomass under stress, with high STIs, indicating tolerance to salinity stress during the early growth stages. These results identified genotypes 9, 14, 16, and 17 as promising candidates for breeding programs aimed at enhancing salinity tolerance, offering sustainable solutions for the utilization of saline soils and for enhancing food security. Future research should focus on the field-based validation of these genotypic responses. Full article

(This article belongs to the Collection Feature Papers in Plant and Photoautotrophic Stresses)

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7 pages, 10289 KiB

Open AccessCase Report

Brown Tumor in Jaw Associated with Hyperparathyroidism: A Case Report

by Verónica Montserrat Silva-Gutiérrez, Judith Berenice Macías-Jiménez, Adriana Molotla-Fragoso, Claudia Patricia Mejía-Velázquez, Gabriel Levi Estévez-González and Luis Fernando Jacinto-Alemán

Oral 2025, 5(3), 59; https://doi.org/10.3390/oral5030059 - 14 Aug 2025

Abstract

Background/Objectives: Brown tumors are bone manifestations of hyperparathyroidism, and they are characterized by histologic similarities with Central Giant Cell Granuloma (CGCG). Their diagnosis requires clinical, microscopic, macroscopic, and serologic correlation, as there is usually an elevation in parathormone levels due to the [...] Read more.

Background/Objectives: Brown tumors are bone manifestations of hyperparathyroidism, and they are characterized by histologic similarities with Central Giant Cell Granuloma (CGCG). Their diagnosis requires clinical, microscopic, macroscopic, and serologic correlation, as there is usually an elevation in parathormone levels due to the underlying metabolic disorder. Methods: This case describes a patient with a left mandibular lesion and a history of CGCG. Results: Through the joint analysis of clinical, histologic, and serologic findings, the diagnosis of a brown tumor associated with hyperparathyroidism was confirmed. Conclusions: This case highlights the importance of a comprehensive evaluation of oral and systemic features for accurate diagnoses and appropriate patient management. Full article

(This article belongs to the Collection Oral and Systemic Health: Border Dentistry and the Borders of Dental Practice)

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10 pages, 501 KiB

Open AccessBrief Report

ERBB2 Mutation Testing in NSCLC: A Pan-European Real-World Evaluation of the Oncomine Precision Assay

by Ilaria Alborelli, Melanie Demes, Peter Wild, Susana Hernandez, Fernando Lopez-Rios, Olivier Bordone, Christophe Bontoux, Paul Hofman, Caterina De Luca, Giancarlo Troncone, Luisella Righi, Umberto Malapelle, Ricella Souza da Silva, Luis Cirnes, Fernando Schmitt, Eveline Keller, Philip M. Jermann, John Longshore and Lukas Bubendorf

J. Mol. Pathol. 2025, 6(3), 19; https://doi.org/10.3390/jmp6030019 - 14 Aug 2025

Abstract

Background/Objectives: The non-small-cell lung cancer (NSCLC) therapeutic landscape has undergone a profound transformation with the introduction of multiple personalized treatment options. Mutations in ERBB2 (HER2) have recently emerged as promising novel targets for the treatment of non-squamous NSCLC (nsNSCLC). Accurate, rapid, [...] Read more.

Background/Objectives: The non-small-cell lung cancer (NSCLC) therapeutic landscape has undergone a profound transformation with the introduction of multiple personalized treatment options. Mutations in ERBB2 (HER2) have recently emerged as promising novel targets for the treatment of non-squamous NSCLC (nsNSCLC). Accurate, rapid, and efficient molecular profiling is crucial for identifying patients who may benefit from targeted therapies, including HER2-directed agents. Materials and Methods: Here, we aimed to retrospectively assess the performance of the Oncomine™ Precision Assay* (OPA) in combination with the Ion Torrent Genexus™ Integrated Sequencer* (Thermo Fisher Scientific. Waltham, MA, USA) for detecting ERBB2 mutations in nsNSCLC. A total of 108 archived nsNSCLC samples, consisting of biopsies, resections, and cytological specimens, were used to assess concordance with in-house-validated orthogonal tests. Results: The OPA showed high sensitivity and specificity with an overall accuracy of 100% for single-nucleotide variants (SNVs) and insertions and deletions (Indels). SNVs and Indels with allele frequencies as low as 5% were correctly identified across samples with a tumor cell content ranging from 5% to 95%. Additionally, the assay demonstrated high reproducibility across the six participating laboratories. The turnaround time of the OPA was notably shorter compared to traditional orthogonal methods, facilitating rapid molecular report generation. Conclusions: The OPA in combination with the Ion Torrent Genexus™ System allows for highly sensitive and specific detection of relevant ERBB2 mutations. The assay’s streamlined workflow, coupled with its automated data analysis pipeline, enables a fast turnaround time for testing across a range of sample types. This includes samples with reduced tumor cell content and limited available input. This study demonstrates the future potential of using this assay in a clinical setting. Full article

19 pages, 1610 KiB

Open AccessArticle

Utilization of Iron Foam as Structured Catalyst for Fischer–Tropsch Synthesis

by Yira Victoria Hurtado, Ghazal Azadi, Eduardo Lins de Barros Neto and Jean-Michel Lavoie

Fuels 2025, 6(3), 60; https://doi.org/10.3390/fuels6030060 - 14 Aug 2025

Abstract

This work focuses on the fabrication, characterization, and performance of a structured iron catalyst to produce hydrocarbons by the Fischer–Tropsch synthesis (FTS). The structured catalyst enhances the heat and mass transfer and provides a larger surface area and lower pressure drop. Iron-based structured [...] Read more.

This work focuses on the fabrication, characterization, and performance of a structured iron catalyst to produce hydrocarbons by the Fischer–Tropsch synthesis (FTS). The structured catalyst enhances the heat and mass transfer and provides a larger surface area and lower pressure drop. Iron-based structured catalysts indicate more activity in lower H₂/CO ratios and improve carbon conversion as compared to other metals. These catalysts were manufactured using the sponge replication method (powder metallurgy). The performance of the structured iron catalyst was assessed in a fixed-bed reactor under industrially relevant conditions (250 °C and 20 bar). The feed gas was a synthetic syngas with a H₂/CO ratio of 1.2, simulating a bio-syngas derived from lignocellulosic biomass gasification. Notably, the best result was reached under these conditions, obtaining a CO conversion of 84.8% and a CH₄ selectivity of 10.4%, where the catalyst exhibited a superior catalytic activity and selectivity toward desired hydrocarbon products, including light olefins and long-chain paraffins. The resulting structured catalyst reached a one-pass CO conversion of 84.8% with a 10.4% selectivity to CH₄ compared to a traditionally produced catalyst, for which the conversion was 18% and the selectivity was 19%, respectively. The results indicate that the developed structured iron catalyst holds considerable potential for efficient and sustainable hydrocarbon production, mainly C10–C20 (diesel-range hydrocarbons), via Fischer–Tropsch synthesis. The catalyst’s excellent performance and improved stability and selectivity offer promising prospects for its application in commercial-scale hydrocarbon synthesis processes. Full article

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23 pages, 771 KiB

Open AccessArticle

Research and Quantitative Analysis on Dynamic Risk Assessment of Intelligent Connected Vehicles

by Kailong Li, Feng Zhang, Min Li and Li Wang

World Electr. Veh. J. 2025, 16(8), 465; https://doi.org/10.3390/wevj16080465 - 14 Aug 2025

Abstract

Ensuring dynamic risk management for intelligent connected vehicles (ICVs) in complex urban environments is critical as autonomous driving technology advances. This study presents three key contributions: (1) a comprehensive risk indicator system, constructed using entropy-based weighting, extracts 13-dimensional data on abnormal behaviors (e.g., [...] Read more.

Ensuring dynamic risk management for intelligent connected vehicles (ICVs) in complex urban environments is critical as autonomous driving technology advances. This study presents three key contributions: (1) a comprehensive risk indicator system, constructed using entropy-based weighting, extracts 13-dimensional data on abnormal behaviors (e.g., speed, acceleration, position) to enhance safety and efficiency; (2) a multidimensional risk quantification method, simulated under single-vehicle and platooning modes on a CARLA-SUMO co-simulation platform, achieved >98% accuracy; (3) a cloud takeover strategy for high-level autonomous vehicles, directly linking risk assessment to real-time control. Analysis of 56,117 risk data points shows a 32% reduction in safety risks during simulations. These contributions provide methodological innovations and substantial data support for ICV field testing. Full article

23 pages, 2882 KiB

Open AccessArticle

Electrify the Field: Designing and Optimizing Electric Tractor Drivetrains with Real-World Cycles

by Korbinian Götz, Markus Pointner, Lukas Mayr, Simon Mailhammer and Markus Lienkamp

World Electr. Veh. J. 2025, 16(8), 463; https://doi.org/10.3390/wevj16080463 - 14 Aug 2025

Abstract

The electrification of tractors can increase the self-supply of renewable energy produced on the farm and reduce the operating costs of tractors. However, electric tractors face higher upfront costs than their diesel counterparts, as well as limited operating time. A drivetrain that is [...] Read more.

The electrification of tractors can increase the self-supply of renewable energy produced on the farm and reduce the operating costs of tractors. However, electric tractors face higher upfront costs than their diesel counterparts, as well as limited operating time. A drivetrain that is highly efficient in a wide range of agricultural applications reduces operating costs and enables long operating times. Thus, we propose a method to design electric tractor drivetrain configurations that incorporates longitudinal dynamic simulations to enable the development of such efficient drivetrains. To represent a diverse application profile, we include real-world load cycles recorded from a 104 kW diesel tractor. Our investigation focuses on the axle-individual drivetrain topology (eAxle) and the central motor topology as the configurations that offer the most promising trade-off between efficiency and complexity. The design method includes the top-down design of the topology including its individual components, such as the inverter, motor, and transmission, which are varied based on the load. Our method derives drivetrains with average efficiencies of 83% for an axle-individual topology with two gears. With a 100 kWh battery, such a drivetrain enables operating times of 7.5 h when fertilizing and 2.4 h when seeding. Full article

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18 pages, 3195 KiB

Open AccessArticle

Design and Investigation of Mechanical Properties of Additively Manufactured Novel Coil-Shaped Wave Springs

by Gul Jamil Shah, Muhammad Rizwan ul Haq and Jeng-Ywan Jeng

Appl. Mech. 2025, 6(3), 61; https://doi.org/10.3390/applmech6030061 - 14 Aug 2025

Abstract

Additive Manufacturing (AM) has revolutionized the production of intricate geometries tailored to customized functional mechanical properties, making it widely adopted across various industries, including aerospace, automotive, and biomedical sectors. However, the fabrication of mechanical springs has remained largely constrained by conventional manufacturing techniques, [...] Read more.

Additive Manufacturing (AM) has revolutionized the production of intricate geometries tailored to customized functional mechanical properties, making it widely adopted across various industries, including aerospace, automotive, and biomedical sectors. However, the fabrication of mechanical springs has remained largely constrained by conventional manufacturing techniques, which limit their cross-sectional geometries to regular shapes, thereby restricting their mechanical performance and energy absorption capabilities. This limitation poses a significant challenge in applications where enhanced load-bearing capacity, energy absorption, and tailored stiffness characteristics are required. To address this issue, this study investigates the influence of coil shape on the mechanical properties of wave springs, specifically focusing on load-bearing capacity, energy absorption, stiffness, and compression behavior during cyclic loading and unloading. Nine contact-type wave springs with distinct coil shapes—square, rectangular, pentagonal, hexagonal, heptagonal, octagonal, quadro, circular (4 waves per coil), and circular (6 waves per coil)—were designed and fabricated using MultiJet Fusion (MJF) technology. Uni-axial compression testing was conducted over ten loading–unloading cycles to evaluate their mechanical performance and deformation characteristics. The results indicate that wave springs with square and rectangular coil shapes exhibit the highest energy absorption while maintaining the lowest stiffness and minimal energy loss during the first ten loading–unloading cycles. Furthermore, experimental findings were validated using finite element analysis (FEA) under identical boundary conditions, demonstrating close agreement with a deviation of only 2.3% compared with the experimental results. These results highlight AM’s potential for customizing wave springs with optimized mechanical performance. Full article

22 pages, 1908 KiB

Open AccessArticle

AI-Blockchain Integration for Real-Time Cybersecurity: System Design and Evaluation

by Sam Goundar and Iqbal Gondal

J. Cybersecur. Priv. 2025, 5(3), 59; https://doi.org/10.3390/jcp5030059 - 14 Aug 2025

Abstract

This paper proposes and evaluates a novel real-time cybersecurity framework integrating artificial intelligence (AI) and blockchain technology to enhance the detection and auditability of cyber threats. Traditional cybersecurity approaches often lack transparency and robustness in logging and verifying AI-generated decisions, hindering forensic investigations [...] Read more.

This paper proposes and evaluates a novel real-time cybersecurity framework integrating artificial intelligence (AI) and blockchain technology to enhance the detection and auditability of cyber threats. Traditional cybersecurity approaches often lack transparency and robustness in logging and verifying AI-generated decisions, hindering forensic investigations and regulatory compliance. To address these challenges, we developed an integrated solution combining a convolutional neural network (CNN)-based anomaly detection module with a permissioned Ethereum blockchain to securely log and immutably store AI-generated alerts and relevant metadata. The proposed system employs smart contracts to automatically validate AI alerts and ensure data integrity and transparency, significantly enhancing auditability and forensic analysis capabilities. To rigorously test and validate our solution, we conducted comprehensive experiments using the CICIDS2017 dataset and evaluated the system’s detection accuracy, precision, recall, and real-time responsiveness. Additionally, we performed penetration testing and security assessments to verify system resilience against common cybersecurity threats. Results demonstrate that our AI-blockchain integrated solution achieves superior detection performance while ensuring real-time logging, transparency, and auditability. The integration significantly strengthens system robustness, reduces false positives, and provides clear benefits for cybersecurity management, especially in regulated environments. This paper concludes by outlining potential avenues for future research, particularly extending blockchain scalability, privacy enhancements, and optimizing performance for high-throughput cybersecurity applications. Full article

(This article belongs to the Section Security Engineering & Applications)

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30 pages, 1486 KiB

Open AccessArticle

A Comprehensive Analysis of Evolving Permission Usage in Android Apps: Trends, Threats, and Ecosystem Insights

by Ali Alkinoon, Trung Cuong Dang, Ahod Alghuried, Abdulaziz Alghamdi, Soohyeon Choi, Manar Mohaisen, An Wang, Saeed Salem and David Mohaisen

J. Cybersecur. Priv. 2025, 5(3), 58; https://doi.org/10.3390/jcp5030058 - 14 Aug 2025

Abstract

The proper use of Android app permissions is crucial to the success and security of these apps. Users must agree to permission requests when installing or running their apps. Despite official Android platform documentation on proper permission usage, there are still many cases [...] Read more.

The proper use of Android app permissions is crucial to the success and security of these apps. Users must agree to permission requests when installing or running their apps. Despite official Android platform documentation on proper permission usage, there are still many cases of permission abuse. This study provides a comprehensive analysis of the Android permission landscape, highlighting trends and patterns in permission requests across various applications from the Google Play Store. By distinguishing between benign and malicious applications, we uncover developers’ evolving strategies, with malicious apps increasingly requesting fewer permissions to evade detection, while benign apps request more to enhance functionality. In addition to examining permission trends across years and app features such as advertisements, in-app purchases, content ratings, and app sizes, we leverage association rule mining using the FP-Growth algorithm. This allows us to uncover frequent permission combinations across the entire dataset, specific years, and 16 app genres. The analysis reveals significant differences in permission usage patterns, providing a deeper understanding of co-occurring permissions and their implications for user privacy and app functionality. By categorizing permissions into high-level semantic groups and examining their application across distinct app categories, this study offers a structured approach to analyzing the dynamics within the Android ecosystem. The findings emphasize the importance of continuous monitoring, user education, and regulatory oversight to address permission misuse effectively. Full article

(This article belongs to the Section Security Engineering & Applications)

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11 pages, 1591 KiB

Open AccessFeature PaperArticle

Incomplete Wenzel State Induced by Dual-Critical Angles in Regular Square Pyramid Microstructures

by Yizhang Shao, Mengyu Zhu, Liyang Huang and Bo Zhang

Surfaces 2025, 8(3), 57; https://doi.org/10.3390/surfaces8030057 - 14 Aug 2025

Abstract

The array of regular square pyramid microstructures with zero-spacing features is an ideal structural topology for building superhydrophobic functional surfaces due to its excellent anti-wetting performance and low surface adhesion properties. In the framework of existing studies, this microstructured array is usually considered [...] Read more.

The array of regular square pyramid microstructures with zero-spacing features is an ideal structural topology for building superhydrophobic functional surfaces due to its excellent anti-wetting performance and low surface adhesion properties. In the framework of existing studies, this microstructured array is usually considered to exist only in two typical wetting states, the stable Cassie state and the Wenzel state. In this study, a third type of wetting state, the incomplete Wenzel state, was discovered for the first time using experimental characterization, and the evolution mechanism of this new wetting state was revealed based on critical contact angle theory and numerical simulation. It is revealed that the faces and edges of the square pyramid microstructures exhibit different tilting angles, and this unique geometrical design endows them with dual critical contact angles. When the intrinsic contact angle of the microstructure is between the critical contact angles for the edges and faces, the wetting behavior of the droplet contact line in the directions parallel to the edges and faces will generate spontaneous and non-spontaneous competition effects, which lead to the formation of the incomplete Wenzel state. The dual-critical-angle theoretical model constructed in this study provides a new perspective for improving the theoretical system of wetting dynamics on pyramid arrays. Full article

(This article belongs to the Collection Featured Articles for Surfaces)

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45 pages, 59922 KiB

Open AccessArticle

Machine Learning Applied to Professional Football: Performance Improvement and Results Prediction

by Diego Moya, Christian Tipantuña, Génesis Villa, Xavier Calderón-Hinojosa, Belén Rivadeneira and Robin Álvarez

Mach. Learn. Knowl. Extr. 2025, 7(3), 85; https://doi.org/10.3390/make7030085 - 14 Aug 2025

Abstract

This paper examines the integration of machine learning (ML) techniques in professional football, focusing on two key areas: (i) player and team performance, and (ii) match outcome prediction. Using a systematic methodology, this study reviews 172 papers from a five-year observation period (2019–2024) [...] Read more.

This paper examines the integration of machine learning (ML) techniques in professional football, focusing on two key areas: (i) player and team performance, and (ii) match outcome prediction. Using a systematic methodology, this study reviews 172 papers from a five-year observation period (2019–2024) to identify relevant applications, focusing on the analysis of game actions (free kicks, passes, and penalties), individual and collective performance, and player position. A predominance of supervised learning, deep learning, and hybrid models (which integrate several ML techniques) is observed in the ML categories. Among the most widely used algorithms are decision trees, extreme gradient boosting, and artificial neural networks, which focus on optimizing sports performance and predicting outcomes. This paper discusses challenges such as the limited availability of public datasets due to access and cost restrictions, the restricted use of advanced visualization tools, and the poor integration of data acquisition devices, such as sensors. However, it also highlights the role of ML in addressing these challenges, thereby representing future research opportunities. Furthermore, this paper includes two illustrative case studies: (i) predicting the date Cristiano Ronaldo will reach 1000 goals, and (ii) an example of predicting penalty shoots; these examples demonstrate the practical potential of ML for performance monitoring and tactical decision-making in real-world football environments. Full article

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22 pages, 4009 KiB

Open AccessArticle

A Multi-Dimensional Feature Extraction Model Fusing Fractional-Order Fourier Transform and Convolutional Information

by Haijing Sun, Wen Zhou, Jiapeng Yang, Yichuan Shao, Le Zhang and Zhiqiang Mao

Fractal Fract. 2025, 9(8), 533; https://doi.org/10.3390/fractalfract9080533 - 14 Aug 2025

Abstract

In the field of deep learning, the traditional Vision Transformer (ViT) model has some limitations when dealing with local details and long-range dependencies; especially in the absence of sufficient training data, it is prone to overfitting. Structures such as retinal blood vessels and [...] Read more.

In the field of deep learning, the traditional Vision Transformer (ViT) model has some limitations when dealing with local details and long-range dependencies; especially in the absence of sufficient training data, it is prone to overfitting. Structures such as retinal blood vessels and lesion boundaries have distinct fractal properties in medical images. The Fractional Convolution Vision Transformer (FCViT) model is proposed in this paper, which effectively compensates for the deficiency of ViT in local feature capture by fusing convolutional information. The ability to classify medical images is enhanced by analyzing frequency domain features using fractional-order Fourier transform and capturing global information through a self-attention mechanism. The three-branch architecture enables the model to fully understand the data from multiple perspectives, capturing both local details and global context, which in turn improves classification performance and generalization. The experimental results showed that the FCViT model achieved 93.52% accuracy, 93.32% precision, 92.79% recall, and a 93.04% F1-score on the standardized fundus glaucoma dataset. The accuracy on the Harvard Dataverse-V1 dataset reached 94.21%, with a precision of 93.73%, recall of 93.67%, and F1-score of 93.68%. The FCViT model achieves significant performance gains on a variety of neural network architectures and tasks with different source datasets, demonstrating its effectiveness and utility in the field of deep learning. Full article

(This article belongs to the Special Issue Recent Advances in Fractional Fourier Transforms and Applications, 2nd Edition)

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