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8 pages, 226 KB  
Brief Report
Influenza-Associated Benign Acute Childhood Myositis During the 2024–2025 Season: A Retrospective Multicenter Study
by Chrysoula Kosmeri, Margarita Efthalia Papasavva, Afroditi Kyrkou, Vasiliki Gketsi, Ekaterini Siomou, Fani Ladomenou and Alexandros Makis
Children 2025, 12(10), 1333; https://doi.org/10.3390/children12101333 (registering DOI) - 4 Oct 2025
Abstract
Background: The aim of this study was to describe the clinical and laboratory characteristics of hospitalized pediatric influenza cases during the 2024–2025 season in Northwestern Greece, with a focus on influenza-associated benign acute childhood myositis (BACM). Methods: We conducted a retrospective [...] Read more.
Background: The aim of this study was to describe the clinical and laboratory characteristics of hospitalized pediatric influenza cases during the 2024–2025 season in Northwestern Greece, with a focus on influenza-associated benign acute childhood myositis (BACM). Methods: We conducted a retrospective observational study of children aged 0–16 years hospitalized with laboratory-confirmed influenza between October 2024 and May 2025 at two pediatric departments. BACM was diagnosed based on calf pain, difficulty walking, elevated creatine kinase (CK), and symptom resolution without other causes. Results: A total of 113 children (mean age 7.0 ± 4.2 years; 50.4% male) were included; 61.1% had influenza A and 38.9% influenza B. None had received influenza vaccination. BACM was identified in 37 children (32.7%), who were significantly older than patients without myositis (9.3 ± 2.7 vs. 6.0 ± 4.5 years, p < 0.001). Influenza B was strongly associated with BACM (70.3% vs. 29.7%, χ2(1) = 22.7, p < 0.001, Cramer’s V = 0.448). Median CK in BACM cases was 2637 IU/L (range: 189–129,390 IU/L); all had preserved renal function. One patient with congenital myopathy developed rhabdomyolysis (peak CK 130,000 IU/L) but had a full recovery. All patients received oseltamivir and supportive care; no intensive care admissions or deaths occurred. Conclusions: In our hospitalized cohort, BACM was observed relatively frequently (32.7%), particularly in children with influenza B; however, this proportion reflects hospitalized cases and does not indicate the true incidence in the general pediatric population. Despite high CK levels, outcomes were favorable with supportive care. These findings underscore the importance of clinician awareness to avoid unnecessary investigations and hospitalizations. Full article
(This article belongs to the Section Global Pediatric Health)
13 pages, 1556 KB  
Article
Prediction of Plate End Debonding of FRP-Strengthened RC Beams Based on Explainable Machine Learning
by Sheng Zheng and Woubishet Zewdu Taffese
Buildings 2025, 15(19), 3576; https://doi.org/10.3390/buildings15193576 (registering DOI) - 4 Oct 2025
Abstract
This research explores the phenomenon of plate-end (PE) debonding in reinforced concrete (RC) beams strengthened with fiber-reinforced polymer (FRP) composites. This type of failure represents a key mechanism that undermines the structural performance and efficiency of FRP reinforcement systems. Despite the widespread use [...] Read more.
This research explores the phenomenon of plate-end (PE) debonding in reinforced concrete (RC) beams strengthened with fiber-reinforced polymer (FRP) composites. This type of failure represents a key mechanism that undermines the structural performance and efficiency of FRP reinforcement systems. Despite the widespread use of FRP in structural repair due to its high strength and corrosion resistance, PE debonding—often triggered by shear or inclined cracks—remains a major challenge. Traditional computational models for predicting PE debonding suffer from low accuracy due to the nonlinear relationship between influencing parameters. To address this, the research employs machine learning techniques and SHapley Additive exPlanations (SHAP), to develop more accurate and explainable predictive models. A comprehensive database is constructed using key parameters affecting PE debonding. Machine learning algorithms are trained and evaluated, and their performance is compared with existing normative models. The study also includes parameter importance and sensitivity analyses to enhance model interpretability and guide future design practices in FRP-based structural reinforcement. Full article
(This article belongs to the Special Issue AI-Powered Structural Health Monitoring: Innovations and Applications)
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19 pages, 8271 KB  
Article
Asymmetric Structural Response Characteristics of Transmission Tower-Line Systems Under Cross-Fault Ground Motions Revealed by Shaking Table Tests
by Yu Wang, Xiaojun Li, Xiaohui Wang and Mianshui Rong
Symmetry 2025, 17(10), 1646; https://doi.org/10.3390/sym17101646 (registering DOI) - 4 Oct 2025
Abstract
The long-distance high-voltage transmission tower-line system, frequently traversing active fault zones, is vulnerable to severe symmetry-breaking damage during earthquakes due to asymmetric permanent ground displacements. However, the seismic performance of such systems, particularly concerning symmetry-breaking effects caused by asymmetric fault displacements, remains inadequately [...] Read more.
The long-distance high-voltage transmission tower-line system, frequently traversing active fault zones, is vulnerable to severe symmetry-breaking damage during earthquakes due to asymmetric permanent ground displacements. However, the seismic performance of such systems, particularly concerning symmetry-breaking effects caused by asymmetric fault displacements, remains inadequately studied. This study investigates the symmetry degradation mechanisms in a 1:40 scaled 500 kV tower-line system subjected to cross-fault ground motions via shaking table tests. The testing protocol incorporates representative fault mechanisms—strike-slip and normal/reverse faults—to systematically evaluate their differential impacts on symmetry response. Measurements of acceleration, strain, and displacement reveal that while acceleration responses are spectrally controlled, structural damage is highly fault-type dependent and markedly asymmetric. The acceleration of towers without permanent displacement was 35–50% lower than that of towers with permanent displacement. Under identical permanent displacement conditions, peak displacements caused by normal/reverse motions exceeded those from strike-slip motions by 50–100%. Accordingly, a fault-type-specific amplification factor of 1.5 is proposed for the design of towers in dip-slip fault zones. These results offer novel experimental insights into symmetry violation under fault ruptures, including fault-specific correction factors and asymmetry-resistant design strategies. However, the conclusions are subject to limitations such as scale effects and the exclusion of vertical ground motion components. Full article
(This article belongs to the Section Engineering and Materials)
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23 pages, 548 KB  
Article
Symmetry- and Asymmetry-Aware Dual-Path Retrieval and In-Context Learning-Based LLM for Equipment Relation Extraction
by Mingfei Tang, Liang Zhang, Zhipeng Yu, Xiaolong Shi and Xiulei Liu
Symmetry 2025, 17(10), 1647; https://doi.org/10.3390/sym17101647 (registering DOI) - 4 Oct 2025
Abstract
Relation extraction in the equipment domain often exhibits asymmetric patterns, where entities participate in multiple overlapping relations that break the expected structural symmetry of semantic associations. Such asymmetry increases task complexity and reduces extraction accuracy in conventional approaches. To address this issue, we [...] Read more.
Relation extraction in the equipment domain often exhibits asymmetric patterns, where entities participate in multiple overlapping relations that break the expected structural symmetry of semantic associations. Such asymmetry increases task complexity and reduces extraction accuracy in conventional approaches. To address this issue, we propose a symmetry- and asymmetry-aware dual-path retrieval and in-context learning-based large language model. Specifically, the BGE-M3 embedding model is fine-tuned for domain-specific adaptation, and a multi-level retrieval database is constructed to capture both global semantic symmetry at the sentence level and local asymmetric interactions at the relation level. A dual-path retrieval strategy, combined with Reciprocal Rank Fusion, integrates these complementary perspectives, while task-specific prompt templates further enhance extraction accuracy. Experimental results demonstrate that our method not only mitigates the challenges posed by overlapping and asymmetric relations but also leverages the latent symmetry of semantic structures to improve performance. Experimental results show that our approach effectively mitigates challenges from overlapping and asymmetric relations while exploiting latent semantic symmetry, achieving an F1-score of 88.53%, a 1.86% improvement over the strongest baseline (GPT-RE). Full article
(This article belongs to the Special Issue Symmetry and Its Applications in Computer Vision)
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11 pages, 823 KB  
Article
Closed-Form Solution Lagrange Multipliers in Worst-Case Performance Optimization Beamforming
by Tengda Pei and Bingnan Pei
Signals 2025, 6(4), 55; https://doi.org/10.3390/signals6040055 (registering DOI) - 4 Oct 2025
Abstract
This study presents a method for deriving closed-form solutions for Lagrange multipliers in worst-case performance optimization (WCPO) beamforming. By approximating the array-received signal autocorrelation matrix as a rank-1 Hermitian matrix using the low-rank approximation theory, analytical expressions for the Lagrange multipliers are derived. [...] Read more.
This study presents a method for deriving closed-form solutions for Lagrange multipliers in worst-case performance optimization (WCPO) beamforming. By approximating the array-received signal autocorrelation matrix as a rank-1 Hermitian matrix using the low-rank approximation theory, analytical expressions for the Lagrange multipliers are derived. The method was first developed for a single plane wave scenario and then generalized to multiplane wave cases with an autocorrelation matrix rank of N. Simulations demonstrate that the proposed Lagrange multiplier formula exhibits a performance comparable to that of the second-order cone programming (SOCP) method in terms of signal-to-interference-plus-noise ratio (SINR) and direction-of-arrival (DOA) estimation accuracy, while offering a significant reduction in computational complexity. The proposed method requires three orders of magnitude less computation time than the SOCP and has a computational efficiency similar to that of the diagonal loading (DL) technique, outperforming DL in SINR and DOA estimations. Fourier amplitude spectrum analysis revealed that the beamforming filters obtained using the proposed method and the SOCP shared frequency distribution structures similar to the ideal optimal beamformer (MVDR), whereas the DL method exhibited distinct characteristics. The proposed analytical expressions for the Lagrange multipliers provide a valuable tool for implementing robust and real-time adaptive beamforming for practical applications. Full article
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13 pages, 1102 KB  
Article
Children with Genetically Confirmed Hereditary Spastic Paraplegia: A Single-Center Experience
by Seyda Besen, Yasemin Özkale, Murat Özkale, Sevcan Tuğ Bozdoğan, Özlem Alkan, Serdar Ceylaner and İlknur Erol
Children 2025, 12(10), 1332; https://doi.org/10.3390/children12101332 (registering DOI) - 4 Oct 2025
Abstract
Objective: The classification of hereditary spastic paraplegia (HSP) is based on genetics, and the number of genetic loci continues to increase with new genetic descriptions. Additionally, the number of new variants in known mutations continues to increase. In this paper, we aim to [...] Read more.
Objective: The classification of hereditary spastic paraplegia (HSP) is based on genetics, and the number of genetic loci continues to increase with new genetic descriptions. Additionally, the number of new variants in known mutations continues to increase. In this paper, we aim to report our experience with genetically confirmed HSPs. Methods: We retrospectively evaluated 10 consecutive children with genetically confirmed HSPs. Results: In this study, we identified six novel mutations, including spastic paraplegia 11 (SPG11), glucosylceramidase beta 2 (GBA2), chromosome 19 open reading frame 12 (C19orf12), 1 in each of the Cytochrome P450 family 7 subfamily B member 1 (CYP7B1) genes, and two different mutations in the intropomyosin-receptor kinase fused gene (TFG) gene. We also identified different clinical phenotypes associated with known mutations. Conclusions: Heterozygous mutations with GBA2 and SPG11 mutation-related HSP are reported for the first time, expanding the known inheritance patterns. We report a novel homozygous chromosome 19 open reading frame 12 (C19orf12) mutation resulting in iron accumulation in the brain, broadening the genetic variants and clinical findings. We determine the first Turkish patients with carnitine palmitoyltransferase IC (CPT1C) and TFG gene mutation-related pure HSP. A pure form of HSP with two novel TFG gene mutations is also identified for the first time. We report the first Turkish patient with kinase D-interacting substrate of 220 kDa (KIDINS220) gene, broadening the clinical spectrum of KIDINS220 variant-related disorders to encompass certain HSPs. Moreover, a novel variant in the oxysterol7-hydroxylase (CYP7B1) gene is reported, expanding the genetic variants and clinical findings relating to SPG5. Full article
(This article belongs to the Section Pediatric Neurology & Neurodevelopmental Disorders)
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15 pages, 518 KB  
Review
Inner Ear Dysfunction in Thyroid Disease: A Scoping Review
by Athena Eliana Arsie, Luca Sacchetto, Carlotta Muneretto, Matteo Seno, Enrico Apa, Elisabetta Genovese, Daniele Monzani and Silvia Palma
Medicina 2025, 61(10), 1793; https://doi.org/10.3390/medicina61101793 (registering DOI) - 4 Oct 2025
Abstract
Background and Objectives: Sensorineural hearing loss (SNHL) is influenced by various causes, including thyroid diseases. For example, hypothyroidism and thyroid autoimmunity can damage the inner ear through hormonal, immune, and vascular mechanisms. Vestibular disorders like Ménière’s disease (MD) and benign paroxysmal positional [...] Read more.
Background and Objectives: Sensorineural hearing loss (SNHL) is influenced by various causes, including thyroid diseases. For example, hypothyroidism and thyroid autoimmunity can damage the inner ear through hormonal, immune, and vascular mechanisms. Vestibular disorders like Ménière’s disease (MD) and benign paroxysmal positional vertigo (BPPV) also show possible associations with thyroid dysfunction. Materials and Methods: A review following PRISMA guidelines searched PubMed, Scopus, and Google Scholar for studies linking thyroid disorders with inner ear dysfunction. Results: Out of 985 screened records, 30 studies met inclusion criteria, involving various thyroid disorders, primarily hypothyroidism and autoimmune thyroiditis. Scientific evidence supports a correlation between hypothyroidism and hearing impairment. However, some studies also suggest a link between hyperthyroidism and inner ear disorders, particularly focusing on the role of autoimmunity in this context. Concerning vestibular dysfunction, the available studies are less abundant and support a significant association between thyroid disease and Meniere’s disease. Conclusions: There is a clear correlation between hypothyroidism and auditory function. A substantial body of literature also supports an association with vestibular disorders, although some discrepancies remain. Further research is needed to elucidate the underlying pathophysiological mechanisms (e.g., autoimmune, vascular, metabolic) involved with this correlation. Full article
(This article belongs to the Section Endocrinology)
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10 pages, 5358 KB  
Article
Microstructural Evolution of Cold-Rolled Type 347H Austenitic Heat-Resistant Steel
by Yanmo Li, Xiangqian Liu, Minghui Zhang, Qiulong Li, Long Niu, Zhihua Wang, Zhe Xu, Wei Wang, Peiyue Li, Bin Chen, Chenxi Liu and Zhihua Sun
Coatings 2025, 15(10), 1157; https://doi.org/10.3390/coatings15101157 (registering DOI) - 4 Oct 2025
Abstract
The influence of cold rolling deformation degree (15%, 30%, 45%, 60%, 75%, and 90%) on the microstructural evolution and the mechanical properties of type 347H austenitic heat-resistant steel was investigated using optical microscopy, X-ray diffraction, magnetic hysteresis loop measurement, transmission electron microscopy, and [...] Read more.
The influence of cold rolling deformation degree (15%, 30%, 45%, 60%, 75%, and 90%) on the microstructural evolution and the mechanical properties of type 347H austenitic heat-resistant steel was investigated using optical microscopy, X-ray diffraction, magnetic hysteresis loop measurement, transmission electron microscopy, and a hardness test. Two types of martensite formed in the deformed specimens, as thin ε-martensite in the cold-rolled steels when the deformation degree was less than 60%, and α′-martensite in the heavily cold-rolled steels when the deformation degree ranged from 60% to 90%. Furthermore, the amount of α′-martensite increases rapidly with the increase in the cold rolling deformation degree. Hence, 60% is considered as the critical point of cold rolling reduction for the formation of α′-martensite. If the specimen experienced a cold rolling reduction of 90%, ε-martensite was hardly observed, while the volume faction of the α′-martensite amounts to 25%. It is verified by the TEM observations that the α′-martensite is transformed from the austenitic matrix as well as the preformed ε-martensite. Full article
(This article belongs to the Section Surface Characterization, Deposition and Modification)
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16 pages, 2720 KB  
Article
Shale Oil T2 Spectrum Inversion Method Based on Autoencoder and Fourier Transform
by Jun Zhao, Shixiang Jiao, Li Bai, Bing Xie, Yan Chen, Zhenguan Wu and Shaomin Zhang
Geosciences 2025, 15(10), 387; https://doi.org/10.3390/geosciences15100387 (registering DOI) - 4 Oct 2025
Abstract
Accurate inversion of the T2 spectrum of shale oil reservoir fluids is crucial for reservoir evaluation. However, traditional nuclear magnetic resonance inversion methods face challenges in extracting features from multi-exponential decay signals. This study proposed an inversion method that combines autoencoder (AE) [...] Read more.
Accurate inversion of the T2 spectrum of shale oil reservoir fluids is crucial for reservoir evaluation. However, traditional nuclear magnetic resonance inversion methods face challenges in extracting features from multi-exponential decay signals. This study proposed an inversion method that combines autoencoder (AE) and Fourier transform, aiming to enhance the accuracy and stability of T2 spectrum estimation for shale oil reservoirs. The autoencoder is employed to automatically extract deep features from the echo train, while the Fourier transform is used to enhance frequency domain features of multi-exponential decay information. Furthermore, this paper designs a customized weighted loss function based on a self-attention mechanism to focus the model’s learning capability on peak regions, thereby mitigating the negative impact of zero-value regions on model training. Experimental results demonstrate significant improvements in inversion accuracy, noise resistance, and computational efficiency compared to traditional inversion methods. This research provides an efficient and reliable new approach for precise evaluation of the T2 spectrum in shale oil reservoirs. Full article
(This article belongs to the Section Geophysics)
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15 pages, 1917 KB  
Article
Test–Retest Reliability of Ankle Mobility, Balance, and Jump Tests in Amateur Trail Running Athletes
by Alberto Dominguez-Muñoz, José Carmelo Adsuar, Santos Villafaina, Juan Luis Leon-Llamas and Francisco Javier Dominguez-Muñoz
Sports 2025, 13(10), 352; https://doi.org/10.3390/sports13100352 (registering DOI) - 4 Oct 2025
Abstract
This study aimed to test the reliability of seven functional performance tests in amateur trail runners, including ankle mobility, balance, hopping, and countermovement jump (CMJ) tests. The sample consisted of 35 runners who were evaluated in two sessions separated by 7 to 14 [...] Read more.
This study aimed to test the reliability of seven functional performance tests in amateur trail runners, including ankle mobility, balance, hopping, and countermovement jump (CMJ) tests. The sample consisted of 35 runners who were evaluated in two sessions separated by 7 to 14 days, which varied due to participants’ scheduling constraints. Relative reliability was assessed using the Intraclass Correlation Coefficient (ICC, which indicates consistency between repeated measures), the Standard Error of Measurement (SEM, which reflects measurement precision), and the Minimal Detectable Change (MDC, which represents the smallest real change beyond measurement error). The results show high reliability in almost all tests. The Lunge Test obtained an ICC of 0.990 and 0.983 for distance, and 0.941 and 0.958 for angular measurements in both legs. The Hop Tests showed moderate reliability with ICC above 0.7 In contrast, the Y Balance Test demonstrated lower reliability, with ICC values ranging from 0.554 to 0.732. The CMJ test showed good reliability, with an ICC ranging from 0.753 to 0.894, an SEM between 5.79% and 11.3%, and an MDC ranging from 15.54% to 31.44%, making it useful for assessing lower limb explosive strength. Both tests presented comparatively higher error values, which should be considered when interpreting individual changes. These findings support the use of these tests as valid and reliable tools for evaluating ankle dorsiflexion, balance, functional symmetry, and lower limb explosive strength in amateur trail runners, prior to training programs or injury prevention strategies, provided that standardized protocols and validated measuring instruments are used. Full article
(This article belongs to the Special Issue Fostering Sport for a Healthy Life)
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17 pages, 2779 KB  
Article
Self-Reported Outcomes of Endocrine Therapy with or Without Ovarian Suppression in Premenopausal Breast Cancer Patients: A Brazilian Quality-of-Life Prospective Cohort
by Natália Nunes, Giselle Carvalho, Bernardo Ramos, Juliana Pecoraro, Lilian Lerner, Debora Azevedo, Thamirez Ferreira, Larissa Santiago de Moura, Carolina Galvão and Mariana Monteiro
Cancers 2025, 17(19), 3229; https://doi.org/10.3390/cancers17193229 (registering DOI) - 4 Oct 2025
Abstract
Background: Endocrine therapy (ET) with or without ovarian function suppression (OFS) is a cornerstone treatment for estrogen receptor-positive (ER+) breast cancer (BC) in premenopausal women, but its impact on quality of life (QoL) and sexual health remains a concern. Methods: We conducted a [...] Read more.
Background: Endocrine therapy (ET) with or without ovarian function suppression (OFS) is a cornerstone treatment for estrogen receptor-positive (ER+) breast cancer (BC) in premenopausal women, but its impact on quality of life (QoL) and sexual health remains a concern. Methods: We conducted a multicenter, prospective, observational study including premenopausal women (≤50 years) diagnosed with stage I–III ER+ BC and treated in private healthcare facilities in Brazil between 2013 and 2023. Patients received ET alone (ET-only) or combined with OFS (OFS-ET). QoL was assessed at baseline and 3, 6, 9, 12, and 24 months using the EORTC QLQ-BR23. Sexual functioning and sexual enjoyment were prespecified primary outcomes. Logistic regression identified factors associated with OFS use, and Fisher’s exact test was applied for categorical comparisons at 24 months. Results: Among 363 patients (80% ET-only, 20% ET + OFS), younger age, advanced stage, and chemotherapy were independently associated with OFS use. Both groups reported early declines in sexual functioning and enjoyment. By 24 months, ET-only patients had returned to baseline, whereas OFS patients remained below baseline. At the item level, no significant differences were observed in sexual desire (51.5% vs. 42.0%; p = 0.33) or enjoyment (26.0% vs. 13.5%; p = 0.20). Lack of sexual activity was more frequent in the OFS group (60.6% vs. 41.2%; p = 0.05). Body image was significantly more impaired with OFS, with a higher proportion of patients reporting feeling less attractive (38.2% vs. 19.9%; p = 0.04) and less feminine (26.5% vs. 11.7%; p = 0.05). Conclusions: ET impairs sexual health in young BC survivors, particularly when combined with OFS. These findings underscore the need for routine sexual health assessments and supportive interventions in survivorship care. Full article
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27 pages, 2297 KB  
Article
Artificial Intelligence Adoption in Non-Chemical Agriculture: An Integrated Mechanism for Sustainable Practices
by Arokiaraj A. Amalan and I. Arul Aram
Sustainability 2025, 17(19), 8865; https://doi.org/10.3390/su17198865 (registering DOI) - 4 Oct 2025
Abstract
Artificial Intelligence (AI) holds significant potential to enhance sustainable non-chemical agricultural methods (NCAM) by optimising resource management, automating precision farming practices, and strengthening climate resilience. However, its widespread adoption among farmers’ remains limited due to socio-economic, infrastructural, and justice-related challenges. This study investigates [...] Read more.
Artificial Intelligence (AI) holds significant potential to enhance sustainable non-chemical agricultural methods (NCAM) by optimising resource management, automating precision farming practices, and strengthening climate resilience. However, its widespread adoption among farmers’ remains limited due to socio-economic, infrastructural, and justice-related challenges. This study investigates AI adoption among NCAM farmers using an Integrated Mechanism for Sustainable Practices (IMSP) conceptual framework which combines the Technology Acceptance Model (TAM) with a justice-centred approach. A mixed-methods design was employed, incorporating Fuzzy-Set Qualitative Comparative Analysis (fsQCA) of AI adoption pathways based on survey data, alongside critical discourse analysis of thematic farmers narrative through a justice-centred lens. The study was conducted in Tamil Nadu between 30 September and 25 October 2024. Using purposive sampling, 57 NCAM farmers were organised into three focus groups: marginal farmers, active NCAM practitioners, and farmers from 18 districts interested in agricultural technologies and AI. This enabled an in-depth exploration of practices, adoption, and perceptions. The findings indicates that while factors such as labour shortages, mobile technology use, and cost efficiencies are necessary for AI adoption, they are insufficient without supportive extension services and inclusive communication strategies. The study refines the TAM framework by embedding economic, cultural, and political justice considerations, thereby offering a more holistic understanding of technology acceptance in sustainable agriculture. By bridging discourse analysis and fsQCA, this research underscores the need for justice-centred AI solutions tailored to diverse farming contexts. The study contributes to advancing sustainable agriculture, digital inclusion, and resilience, thereby supporting the United Nations’ Sustainable Development Goals (SDGs). Full article
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16 pages, 392 KB  
Article
Investigating the Etiology and Demographic Distribution of Enamel Hypoplasia
by Claudia Moro, Lucie Biehler-Gomez, Giuseppe Lanza Attisano, Daniele Maria Gibelli, Federica Boschi, Danilo De Angelis and Cristina Cattaneo
Heritage 2025, 8(10), 420; https://doi.org/10.3390/heritage8100420 - 3 Oct 2025
Abstract
Enamel hypoplasia (EH) is a stress marker commonly used in bioarcheological research to investigate health during growth. However, its analysis in contemporary samples allows for additional avenues of research, including comparison with medical records. The aim of the present research is to explore [...] Read more.
Enamel hypoplasia (EH) is a stress marker commonly used in bioarcheological research to investigate health during growth. However, its analysis in contemporary samples allows for additional avenues of research, including comparison with medical records. The aim of the present research is to explore the influence of biological sex and socioeconomic status on the distribution of EH and examine the factors that contribute to the development of this defect. In this perspective, analysis of dentition was conducted on 132 individuals, with known information about age, biological sex, nationality, medical records, and socioeconomic status. Statistical analysis was conducted using Fisher’s test and the chi-square test. As a result, EH was observed more frequently among individuals from disadvantaged backgrounds, while a significant association was observed with socioeconomic status, evidencing a strong association between EH presence and structural vulnerability (chi-square, p = 0.04). The frequency of EH between sexes was not significant; however, a higher frequency was observed among males (chi-square, p = 0.94). We hypothesize that the impact of female biological buffering might be reduced in the European sample, as this result aligns with background information of the context. These results align with the research hypotheses and reinforce the multifactorial etiology of EH. Full article
(This article belongs to the Special Issue Advanced Analysis of Bioarchaeology, Skeletal Biology and Evolution)
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23 pages, 5798 KB  
Article
Application of Generative AI in Financial Risk Prediction: Enhancing Model Accuracy and Interpretability
by Kai-Chao Yao, Hsiu-Chu Hung, Ching-Hsin Wang, Wei-Lun Huang, Hui-Ting Liang, Tzu-Hsin Chu, Bo-Siang Chen and Wei-Sho Ho
Information 2025, 16(10), 857; https://doi.org/10.3390/info16100857 - 3 Oct 2025
Abstract
This study explores the application of generative artificial intelligence (AI) in financial risk forecasting, aiming to assess its potential in enhancing both the accuracy and interpretability of predictive models. Traditional methods often struggle with the complexity and nonlinearity of financial data, whereas generative [...] Read more.
This study explores the application of generative artificial intelligence (AI) in financial risk forecasting, aiming to assess its potential in enhancing both the accuracy and interpretability of predictive models. Traditional methods often struggle with the complexity and nonlinearity of financial data, whereas generative AI—such as large language models and generative adversarial networks (GANs)—offers novel solutions to these challenges. The study begins with a comprehensive review of current research on generative AI in financial risk prediction, with a focus on its roles in data augmentation and feature extraction. It then investigates techniques such as Generative Adversarial Explanation (GAX) to evaluate their effectiveness in improving model interpretability. Case studies demonstrate the practical value of generative AI in real-world financial forecasting and quantify its contribution to predictive accuracy. Furthermore, the study identifies key challenges—including data quality, model training costs, and regulatory compliance—and proposes corresponding mitigation strategies. The findings suggest that generative AI can significantly improve the accuracy and interpretability of financial risk models, though its adoption must be carefully managed to address associated risks. This study offers insights and guidance for future research in applying generative AI to financial risk forecasting. Full article
(This article belongs to the Special Issue Modeling in the Era of Generative AI)
58 pages, 4299 KB  
Article
Optimisation of Cryptocurrency Trading Using the Fractal Market Hypothesis with Symbolic Regression
by Jonathan Blackledge and Anton Blackledge
Commodities 2025, 4(4), 22; https://doi.org/10.3390/commodities4040022 - 3 Oct 2025
Abstract
Cryptocurrencies such as Bitcoin can be classified as commodities under the Commodity Exchange Act (CEA), giving the Commodity Futures Trading Commission (CFTC) jurisdiction over those cryptocurrencies deemed commodities, particularly in the context of futures trading. This paper presents a method for predicting both [...] Read more.
Cryptocurrencies such as Bitcoin can be classified as commodities under the Commodity Exchange Act (CEA), giving the Commodity Futures Trading Commission (CFTC) jurisdiction over those cryptocurrencies deemed commodities, particularly in the context of futures trading. This paper presents a method for predicting both long- and short-term trends in selected cryptocurrencies based on the Fractal Market Hypothesis (FMH). The FMH applies the self-affine properties of fractal stochastic fields to model financial time series. After introducing the underlying theory and mathematical framework, a fundamental analysis of Bitcoin and Ethereum exchange rates against the U.S. dollar is conducted. The analysis focuses on changes in the polarity of the ‘Beta-to-Volatility’ and ‘Lyapunov-to-Volatility’ ratios as indicators of impending shifts in Bitcoin/Ethereum price trends. These signals are used to recommend long, short, or hold trading positions, with corresponding algorithms (implemented in Matlab R2023b) developed and back-tested. An optimisation of these algorithms identifies ideal parameter ranges that maximise both accuracy and profitability, thereby ensuring high confidence in the predictions. The resulting trading strategy provides actionable guidance for cryptocurrency investment and quantifies the likelihood of bull or bear market dominance. Under stable market conditions, machine learning (using the ‘TuringBot’ platform) is shown to produce reliable short-horizon estimates of future price movements and fluctuations. This reduces trading delays caused by data filtering and increases returns by identifying optimal positions within rapid ‘micro-trends’ that would otherwise remain undetected—yielding gains of up to approximately 10%. Empirical results confirm that Bitcoin and Ethereum exchanges behave as self-affine (fractal) stochastic fields with Lévy distributions, exhibiting a Hurst exponent of roughly 0.32, a fractal dimension of about 1.68, and a Lévy index near 1.22. These findings demonstrate that the Fractal Market Hypothesis and its associated indices provide a robust market model capable of generating investment returns that consistently outperform standard Buy-and-Hold strategies. Full article
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