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12 pages, 1956 KB

Open AccessArticle

Effects on Condylar Position of Head Flexion Typically Induced by the Use of Portable Electronic Devices: An Observational Study

by Marian Turbatu, Laura Pittari, Francesco Ferrini, Teresa Laborante, Alessandro Nota and Simona Tecco

Appl. Sci. 2025, 15(24), 13245; https://doi.org/10.3390/app152413245 (registering DOI) - 17 Dec 2025

Abstract

The widespread use of portable electronic devices has increasingly promoted the prolonged maintenance of non-physiological postures, particularly anterior and downward head flexion. Therefore, this study aimed to analyze the condylar and incisor relationship displacement induced by this improper posture. A total of 20 [...] Read more.

The widespread use of portable electronic devices has increasingly promoted the prolonged maintenance of non-physiological postures, particularly anterior and downward head flexion. Therefore, this study aimed to analyze the condylar and incisor relationship displacement induced by this improper posture. A total of 20 adult subjects (9 F, 11 M; mean age 27 ± 5) were recruited at the Department of Dentistry, Vita-Salute San Raffaele University, Milan, Italy. Mandibular kinematics was recorded using JMA-Optic AG (Zebris Medical GmbH, Isny, Germany). The protocol adopted consisted of three phases: (1) Habitual occlusion with light clenching, (2) Neuromuscular rest position (RP) verified by surface electromyography (sEMG), (3) Anterior head flexion (40–60°) (HF), simulating the posture typically observed during portable digital device use. Millimetric measurements of condylar displacement from RP to HF and incisal plane changes were collected. Data were analyzed descriptively with Microsoft Excel, and inferentially with StatPlus Pro (AnalystSoft, StatPlus: mac Pro, version 8). The right condyle exhibited a mean displacement of 1.9 mm in the downward direction (p < 0.001), while the left condyle showed a downward displacement of 1.5 mm (p < 0.001). No significant difference was observed between the two sides. At the dental level, the lower incisor revealed a mean shift of 1.0 mm superiorly (p < 0.001) and 0.7 mm anteriorly (p < 0.001). The HF determines a significant condylar and incisal plane displacement, and may predispose individuals to TMJ disorders, supporting the hypothesis of an emerging cranio-cervico-mandibular condition linked to prolonged use of high-tech display terminals, here proposed as ED-TMD (Electronic Device-Induced Temporomandibular Disorder). Full article

(This article belongs to the Special Issue Innovative Materials and Technologies in Orthodontics)

20 pages, 1180 KB

Open AccessArticle

Associations of Breast Cancer Treatments with One-Year Changes in Health-Related Fitness

by Fernanda Z. Arthuso, Ki-Yong An, Qinggang Wang, Renée L. Kokts-Porietis, Andria R. Morielli, Margaret L. McNeely, Jeff K. Vallance, S. Nicole Culos-Reed, Gordon J. Bell, Leanne Dickau, Myriam Filion, Stephanie M. Ntoukas, Jessica McNeil, Lin Yang, Charles E. Matthews, Christine M. Friedenreich and Kerry S. Courneya

Cancers 2025, 17(24), 4026; https://doi.org/10.3390/cancers17244026 (registering DOI) - 17 Dec 2025

Abstract

Background/Objectives: Early-stage breast cancer treatments adversely affect components of health-related fitness (HRF) important for treatment tolerability, recovery, and long-term outcomes. Few studies have examined cancer treatment modality-specific effects on HRF. We examined associations of breast cancer treatment modalities, regimens, and combinations with one-year [...] Read more.

Background/Objectives: Early-stage breast cancer treatments adversely affect components of health-related fitness (HRF) important for treatment tolerability, recovery, and long-term outcomes. Few studies have examined cancer treatment modality-specific effects on HRF. We examined associations of breast cancer treatment modalities, regimens, and combinations with one-year changes in HRF. Methods: Newly diagnosed early-stage breast cancer patients were recruited between 2012 and 2019 for the Alberta Moving Beyond Breast Cancer (AMBER) cohort study. HRF assessments were completed within 90 days of diagnosis and at one year, including cardiorespiratory fitness, muscle strength and endurance, and body composition. Analysis of covariance was used to test whether HRF changes differed between treatment modalities, regimens, and combinations. All tests were 2-sided. Results: A total of 1350 participants (mean [SD] age, 55.6 [10.7] years) were included. Women who received chemotherapy (n = 797; 59%) experienced statistically significant smaller increases in upper body strength (−1.7 kg, 95% confidence interval [CI]: −3.0 to −0.5), greater declines in lower body endurance (−118.0 kg, 95%CI: −216.6 to −19.3), and greater declines in total lean mass (−0.7 kg, 95%CI: −1.1 to −0.3), bone mineral density (−0.01 g/cm², 95%CI: −0.02 to 0.00), and bone mineral content (0.04 kg, 95%CI: −0.06 to −0.02). Other treatment modalities were modestly and inconsistently associated with HRF changes. Treatment combinations that included chemotherapy had the most negative impact on cardiorespiratory fitness and body composition. Conclusions: Chemotherapy—either alone or in combination with other treatments—had the largest and broadest negative impact on HRF recovery in early-stage breast cancer at one-year follow-up. Full article

(This article belongs to the Special Issue Exercise and Cancer Treatment: The Clinical Application of Exercise Oncology)

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14 pages, 3847 KB

Open AccessArticle

Secondary Genetic Events and Their Relationship to TP53 Mutation in Mantle Cell Lymphoma: A Sub-Study from the FIL_MANTLE-FIRST BIO on Behalf of Fondazione Italiana Linfomi (FIL)

by Maria Elena Carazzolo, Francesca Maria Quaglia, Antonino Aparo, Alessia Moioli, Alice Parisi, Riccardo Moia, Francesco Piazza, Alessandro Re, Maria Chiara Tisi, Luca Nassi, Pietro Bulian, Alessia Castellino, Vittorio Ruggero Zilioli, Piero Maria Stefani, Alberto Fabbri, Elisa Lucchini, Annalisa Arcari, Luisa Lorenzi, Barbara Famengo, Maurilio Ponzoni, Angela Ferrari, Simone Ragaini, Jacopo Olivieri, Vittoria Salaorni, Simona Gambino, Marilisa Galasso, Maria Teresa Scupoli and Carlo Visco Show full author list Hide full author list

Cancers 2025, 17(24), 4027; https://doi.org/10.3390/cancers17244027 (registering DOI) - 17 Dec 2025

Abstract

Background: Mantle Cell Lymphoma (MCL) is an aggressive malignancy with variable clinical behavior, largely reflecting the underlying molecular heterogeneity. The genomic landscape of MCL encompasses gene mutations with strong prognostic implications and secondary genetic events, which are also implicated in the pathogenesis [...] Read more.

Background: Mantle Cell Lymphoma (MCL) is an aggressive malignancy with variable clinical behavior, largely reflecting the underlying molecular heterogeneity. The genomic landscape of MCL encompasses gene mutations with strong prognostic implications and secondary genetic events, which are also implicated in the pathogenesis and prognosis of the disease. Methods: We evaluated the diagnostic samples of 73 patients with relapsed/refractory MCL that were enrolled in the Fondazione Italiana Linfomi Mantle First-BIO study. All patients had available data for correlating CNVs with the presence of TP53 mutation. Time to first relapse or progression of disease (POD) was used as the primary outcome measure. Results: We identified CNVs associated with MCL, with Del 9p21.3 (CDKN2A) being the strongest predictor of shorter time to POD (p = 0.01), independently of TP53 mutation in multivariable analysis. Unsupervised clustering identified molecularly defined clusters that were associated with significantly different times to POD (p = 0.01). Pairwise log-rank tests confirmed TP53 mutated vs. wild-type (WT) as the strongest prognostic factor, with cluster assessment improving the prognostic predictivity among patients: clusters TP53-mut vs. TP53-WT, p = 0.001, HR = 3.92; and p = 0.014, HR = 2.23, respectively. In conclusion, CNV-based molecular clusters might represent a novel approach to identify patients at higher risk of treatment failure, further contributing to the prognostic predictivity of TP53 mutation. Full article

(This article belongs to the Section Molecular Cancer Biology)

22 pages, 4620 KB

Open AccessArticle

Molecular Mechanisms and Antidiabetic Effects of Mango (Mangifera indica) Leaf Extract as a GLP-1 Analogue in Type 2 Diabetic Rats

by Amporn Jariyapongskul, Pornthip Boonsri, Itthipol Sungwienwong, Kulvadee Dolsophon, Nuttapon Apiratikul, Piyada Jittangprasert, Pornnapa Sitthisuk, Ruttachuk Rungsiwiwut, Siritron Samosorn, Sunit Suksamrarn and Ramida Watanapokasin

Int. J. Mol. Sci. 2025, 26(24), 12149; https://doi.org/10.3390/ijms262412149 (registering DOI) - 17 Dec 2025

Abstract

This study investigated the potential of scale-up mango leaf extract (MLE) as a treatment for diabetes, a global public health concern. MLE was prepared by boiling in water, yielding 12.07% (w/w), with a bioactive mangiferin content of 165.67 ± [...] Read more.

This study investigated the potential of scale-up mango leaf extract (MLE) as a treatment for diabetes, a global public health concern. MLE was prepared by boiling in water, yielding 12.07% (w/w), with a bioactive mangiferin content of 165.67 ± 10.88 μg/g in the crude powder. Mechanistically, MLE demonstrated a hypoglycemic effect by stimulating glucagon-like peptide-1 (GLP-1) secretion in NCI-H716 L-cells. This occurred through activation of the MAPK signaling pathway, evidenced by increased p-ERK1/2, p-p38, and p-c-Jun expression, and the Wnt signaling pathway, shown by increased β-catenin and decreased GSK-3β and Axin1 expression, consistent with molecular docking. In a type 2 diabetic rat model, MLE administration (40 mg/kg) significantly reduced metabolic parameters, including fasting blood glucose (FBG), body weight, cholesterol (CHOL), triglycerides (TGs), and HbA1c. Notably, MLE lowered serum insulin and the HOMA-IR index, and reduced serum dipeptidyl peptidase-IV (DPP-IV) levels, resulting in increased serum GLP-1, comparable to the drug sitagliptin. These findings suggest that MLE has great potential to lower blood glucose by inducing GLP-1 secretion via MAPKs and Wnt signaling pathways, positioning it as a promising candidate for alternative diabetes treatment or development as a dietary supplement. Full article

(This article belongs to the Section Bioactives and Nutraceuticals)

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26 pages, 4268 KB

Open AccessArticle

Combined Effect of Recycled Tire Steel Fiber and Blast Furnace Slag on the Mechanical Performance of 3D Printable Concrete

by Fatih Eren Akgümüş, Hatice Gizem Şahin, Tuğçe İsafça Kaya and Ali Mardani

Buildings 2025, 15(24), 4564; https://doi.org/10.3390/buildings15244564 (registering DOI) - 17 Dec 2025

Abstract

This study investigated the effects of waste steel fiber and high-volume blast furnace slag (BFS) substitution on the mechanical and physical properties of three-dimensional printable concrete (3DPC) to improve its environmental performance. BFS was substituted for cement at 0%, 25%, 50%, and 75% [...] Read more.

This study investigated the effects of waste steel fiber and high-volume blast furnace slag (BFS) substitution on the mechanical and physical properties of three-dimensional printable concrete (3DPC) to improve its environmental performance. BFS was substituted for cement at 0%, 25%, 50%, and 75% by volume. Waste steel fibers were added to the mixtures at three lengths (5, 10, and 15 mm) and two volumetric ratios (0.5% and 1.0%). Twenty-eight mixtures were optimized based on extrudability, buildability, and shape stability criteria. Parameters such as compressive and flexural strength, surface moisture content, and drying shrinkage were evaluated. The results showed that using up to 0.5% waste steel fibers increased compressive strength by up to 23%, but decreased it to a level of 1%. Fiber reinforcement improved the flexural strength of all blends by up to 53% at both ages, regardless of fiber ratio or length. Increasing the BFS substitution rate generally increased surface moisture however, this value decreased in mixtures containing 75% BFS and silica fume. Furthermore, using steel fibers and in-creasing fiber length significantly improved the drying shrinkage performance of the mixtures. Full article

(This article belongs to the Special Issue 3D-Printed Technology in Buildings)

25 pages, 2185 KB

Open AccessReview

Clinical Insights into Mesenchymal Stem Cell Applications for Spinal Cord Injury

by Matthew Shkap, Daria Namestnikova, Elvira Cherkashova, Daria Chudakova, Arthur Biktimirov, Konstantin Yarygin and Vladimir Baklaushev

Int. J. Mol. Sci. 2025, 26(24), 12139; https://doi.org/10.3390/ijms262412139 (registering DOI) - 17 Dec 2025

Abstract

This review examines the safety and clinical efficacy of mesenchymal stem/stromal cells (MSCs)-based therapies in patients with spinal cord injury (SCI). The analysis covers 26 clinical studies conducted on patients with varying degrees of the post-SCI neurological deficit. The review highlights the methodology [...] Read more.

This review examines the safety and clinical efficacy of mesenchymal stem/stromal cells (MSCs)-based therapies in patients with spinal cord injury (SCI). The analysis covers 26 clinical studies conducted on patients with varying degrees of the post-SCI neurological deficit. The review highlights the methodology of trials, the source of MSCs, the dosage of cells administered, transplantation methods, patient inclusion criteria, and the methods of evaluating the effectiveness of the therapy. MSC transplantation in SCI was safe and feasible in all the studies summarized in our review. All studies conducted have demonstrated varying degrees of patient improvement and reduction in the severity of neurological deficits. However, further controlled randomized studies on larger numbers of patients are needed to better evaluate the therapeutic efficacy of MS transplantation. The prospects of the enhancement of the efficacy of the SCI cell therapy with MSCs, including their transplantation with other types of stem cells, administration of MSC-derived exosomes, genetic modification of MSCs, use of the MSC- and other-stem-cell-based tissue-engineered scaffolds, and combination of cell therapy with neuromodulation, are discussed. Full article

(This article belongs to the Special Issue Mesenchymal Stem/Stromal Cells: Mechanisms and Applications in Tissue Regeneration)

17 pages, 4549 KB

Open AccessArticle

Simultaneous Determination and Dietary Risk Assessment of 26 Pesticide Residues in Wheat Grain and Bran Using QuEChERS-UHPLC-MS/MS

by Hongwei Zhang, Quan Liu, Xinhui Dong, Xueyang Qiao, Chunyong Li, Junli Cao, Pengcheng Ren, Jindong Li and Shu Qin

Foods 2025, 14(24), 4351; https://doi.org/10.3390/foods14244351 (registering DOI) - 17 Dec 2025

Abstract

Evaluating the potential chronic health risks posed by pesticides to consumers is essential for ensuring food safety and protecting public health. An ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) method coupled with modified QuEChERS extraction was developed to simultaneously determine 26 pesticide residues in [...] Read more.

Evaluating the potential chronic health risks posed by pesticides to consumers is essential for ensuring food safety and protecting public health. An ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) method coupled with modified QuEChERS extraction was developed to simultaneously determine 26 pesticide residues in wheat grain and bran. Samples were extracted with acetonitrile with 2% (v/v) acetic acid and cleaned up using C₁₈ sorbent. Method validation demonstrated excellent linearity, accuracy, and precision. When applied to 48 wheat grain and 24 bran samples collected from major wheat-growing regions in China, 12 and 21 pesticides were detected at concentrations ranging from <0.005 to 1.785 mg kg⁻¹ and <0.01 to 2.188 mg kg⁻¹, respectively. Chronic hazard quotients (HQc) and acute hazard quotients (HQa) for all pesticides for grain and bran were far below the safety threshold of 100%. These results indicate that pesticide residues in wheat grain and bran present negligible chronic dietary risks to consumers across all age groups. Full article

(This article belongs to the Special Issue Next-Generation Chemometric and Spectroscopic Strategies for Food Safety and Authenticity: Toward Faster and More Reliable Detection)

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26 pages, 1224 KB

Open AccessArticle

SPR-RAG: Semantic Parsing Retriever-Enhanced Question Answering for Power Policy

by Yufang Wang, Tongtong Xu and Yihui Zhu

Algorithms 2025, 18(12), 802; https://doi.org/10.3390/a18120802 (registering DOI) - 17 Dec 2025

Abstract

To address the limitations of Retrieval-Augmented Generation (RAG) systems in handling long policy documents, mitigating information dilution, and reducing hallucinations in engineering-oriented applications, this paper proposes SPR-RAG, a retrieval-augmented framework designed for knowledge-intensive vertical domains such as electric power policy analysis. With practicality [...] Read more.

To address the limitations of Retrieval-Augmented Generation (RAG) systems in handling long policy documents, mitigating information dilution, and reducing hallucinations in engineering-oriented applications, this paper proposes SPR-RAG, a retrieval-augmented framework designed for knowledge-intensive vertical domains such as electric power policy analysis. With practicality and interpretability as core design goals, SPR-RAG introduces a Semantic Parsing Retriever (SPR), which integrates community detection–based entity disambiguation and transforms natural language queries into logical forms for structured querying over a domain knowledge graph, thereby retrieving verifiable triple-based evidence. To further resolve retrieval bias arising from diverse policy writing styles and inconsistencies between user queries and policy text expressions, a question-repository–based indirect retrieval mechanism is developed. By generating and matching latent questions, this module enables more robust retrieval of non-structured contextual evidence. The system then fuses structured and unstructured evidence into a unified dual-source context, providing the generator with an interpretable and reliable grounding signal. Experiments conducted on real electric power policy corpora demonstrate that SPR-RAG achieves 90.01% faithfulness—representing a 5.26% improvement over traditional RAG—and 76.77% context relevance, with a 5.96% gain. These results show that SPR-RAG effectively mitigates hallucinations caused by ambiguous entity names, textual redundancy, and irrelevant retrieved content, thereby improving the verifiability and factual grounding of generated answers. Overall, SPR-RAG demonstrates strong deployability and cross-domain transfer potential through its “Text → Knowledge Graph → RAG” engineering paradigm. The framework provides a practical and generalizable technical blueprint for building high-trust, industry-grade question–answering systems, offering substantial engineering value and real-world applicability. Full article

(This article belongs to the Section Algorithms for Multidisciplinary Applications)

16 pages, 673 KB

Open AccessArticle

Associations Between the Food Environment and Food Insecurity on Fruit, Vegetable, and Nutrient Intake, and Body Mass Index, Among Urban-Dwelling Latina Breast Cancer Survivors Participating in the ¡Mi Vida Saludable! Trial

by Zachary O. Kadro, Eileen Rillamas-Sun, Blake O. Langley, Allison Meisner, Isobel Contento, Pamela A. Koch, Ann Ogden Gaffney, Dawn L. Hershman and Heather Greenlee

Nutrients 2025, 17(24), 3950; https://doi.org/10.3390/nu17243950 (registering DOI) - 17 Dec 2025

Abstract

Background: Socioeconomic disparities may drive cancer inequities in Hispanic/Latino populations. We examined associations of perceived access to healthy foods (AHF) and food insecurity (FI) with diet and body mass index (BMI) changes in Latina breast cancer (BC) survivors. Methods: Latina BC [...] Read more.

Background: Socioeconomic disparities may drive cancer inequities in Hispanic/Latino populations. We examined associations of perceived access to healthy foods (AHF) and food insecurity (FI) with diet and body mass index (BMI) changes in Latina breast cancer (BC) survivors. Methods: Latina BC survivors in a 12-month intervention trial aiming to increase fruit/vegetable intake and physical activity were analyzed. AHF was from a modified, validated neighborhood environment scale and dichotomized (low–medium vs. high). FI was defined as eating less and/or going hungry due to a lack of money. AHF and FI surveys were self-reported. Outcomes included dietary intake, diet quality, and BMI. Fruit/vegetable intake was log-transformed. Relationships between AHF and FI and changes in diet and BMI were evaluated using generalized estimating equations. Results: Of women with AHF data (n = 86), 58% reported low–medium access and 42% reported high access. Fruit/vegetable (FV) intake declined overall from baseline to 12 months, with greater reductions among low–medium AHF women (−32%, 95% CI: −51%, −7%) compared with high AHF women (−17%, CI: −40%, +13%). Statistically significant 12-month decreases in total calories, carbohydrates, sugars, and fat occurred in low–medium AHF women but not high AHF women, and changes in total energy density, carbohydrates, sugars, and BMI at 12 months were statistically significantly different between women with low–medium AHF and women with high AHF, p ≤ 0.05. Among 157 women, 23% reported FI. Reductions in fruit/vegetable intake were larger in women with FI (−39%, CI: −57%, −14%) than in women without FI (−10% reductions, CI: −25%, +8%) and between-group differences were significant at both 6 and 12 months, p ≤ 0.05. Most diet measures decreased for both FI and non-FI women, with greater decreases among those with FI. Conclusions: Latina BC survivors with FI or perceived limited AHF experienced greater declines in indicators of healthy diets including FV intake. Future interventions should integrate strategies to measure AHF and FI to address disparate access to healthy food options. Full article

(This article belongs to the Special Issue Food Security, Food Insecurity, and Nutritional Health)

16 pages, 3474 KB

Open AccessArticle

Study on Battery-Supercapacitor Hybrid Energy Storage System for Metros

by Jiayu Han, Boyang Shen, Yu Chen, Yuanxin Zhang, Minxing Li, Wenjing Mo and Lin Fu

Appl. Sci. 2025, 15(24), 13243; https://doi.org/10.3390/app152413243 (registering DOI) - 17 Dec 2025

Abstract

In the metro traction power supply system, the metro acceleration and braking may cause fluctuations of bus voltage, and it is difficult for a single energy storage device to achieve both the proper response speed and energy density. In this article, a novel [...] Read more.

In the metro traction power supply system, the metro acceleration and braking may cause fluctuations of bus voltage, and it is difficult for a single energy storage device to achieve both the proper response speed and energy density. In this article, a novel battery-supercapacitor hybrid energy storage system (HESS) was proposed to realise energy compensation and regulation under complex operating conditions of metros, in order to maintain a stable bus voltage. Using the short station distance working condition of Guangzhou Metro Line 4 as an example, four types of scenarios were designed for acceleration, braking, frequent acceleration-braking and two-metro simultaneous operation. The simulation results show that a single-mode energy storage could not effectively stabilise the bus voltage, while battery-supercapacitor HESS could control bus voltage fluctuation within 2 V. A comparative study on the proposed battery-supercapacitor HESS using a typical Buck-Boost DC/DC converter topology and a different Cuk DC/DC converter topology was carried out. Overall, this article provides a novel battery-supercapacitor HESS to stabilise the metro power system under complex acceleration and braking conditions, and lays the technical foundation for a hybrid energy storage system to be used in actual urban rail transit. Full article

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26 pages, 4837 KB

Open AccessArticle

Evaluation of Jute–Glass Ratio Effects on the Mechanical, Thermal, and Morphological Properties of PP Hybrid Composites for Sustainable Automotive Applications

by Tunahan Özyer and Emre Demirci

Polymers 2025, 17(24), 3335; https://doi.org/10.3390/polym17243335 (registering DOI) - 17 Dec 2025

Abstract

This study investigates polypropylene (PP)–based biocomposites reinforced with systematically varied jute and glass fiber ratios as sustainable, lightweight alternatives for semi-structural automotive parts. Four formulations (J20/G0, J15/G5, J10/G10, J5/G15) with a constant 20 wt% total fiber were produced by injection molding and characterized [...] Read more.

This study investigates polypropylene (PP)–based biocomposites reinforced with systematically varied jute and glass fiber ratios as sustainable, lightweight alternatives for semi-structural automotive parts. Four formulations (J20/G0, J15/G5, J10/G10, J5/G15) with a constant 20 wt% total fiber were produced by injection molding and characterized through mechanical, thermal, and morphological analyses. Tensile, flexural, and Charpy impact tests showed progressive improvements in strength, stiffness, and energy absorption with increasing glass fiber content, while ductility was maintained or slightly enhanced. SEM revealed a transition from fiber pull-out in jute-rich systems to fiber rupture and stronger matrix adhesion in glass-rich hybrids. Thermal analyses confirmed the benefits of hybridization: heat deflection temperature increased from 75 °C (J20/G0) to 103 °C (J5/G15), and thermogravimetry indicated improved stability and higher char residue. DSC showed negligible changes in crystallization and melting, confirming that fiber partitioning does not significantly affect PP crystallinity. Benchmarking demonstrated mechanical and thermal performance comparable to acrylonitrile–butadiene–styrene (ABS) and acrylonitrile–styrene–acrylate (ASA), widely used in automotive components. Finally, successful molding of a prototype exterior mirror cap from J20/G0 validated industrial processability. These findings highlight jute–glass hybrid PP composites as promising, sustainable alternatives to conventional engineering plastics for automotive engineering applications. Full article

(This article belongs to the Special Issue Advances in Composite Materials: Polymers and Fibers Inclusion)

52 pages, 23254 KB

Open AccessSystematic Review

Biochemical Reduction of Metal Salts as a Prominent Approach for Biohybrid Nanomaterials Production: A Review

by Daniil A. Bogachikhin, Marina A. Abramkina, Anastasia K. Dzuba, Bogdan Ya. Karlinskii and Vyacheslav A. Arlyapov

Nanomaterials 2025, 15(24), 1899; https://doi.org/10.3390/nano15241899 (registering DOI) - 17 Dec 2025

Abstract

Metal nanoparticles are unique materials with diverse properties and a wide range of paramount applications in various scientific fields, from catalysis and electrochemistry to pharmaceuticals and high-tech composite materials. Among the many methods for producing nanoparticles, those that use renewable plant biomass or [...] Read more.

Metal nanoparticles are unique materials with diverse properties and a wide range of paramount applications in various scientific fields, from catalysis and electrochemistry to pharmaceuticals and high-tech composite materials. Among the many methods for producing nanoparticles, those that use renewable plant biomass or its extracts, as well as biogenic approaches for synthesizing nanoparticles within living cells, are particularly promising from the viewpoint of Green Chemistry and sustainable development. These techniques, which are part of the rapidly growing field of Nanobiotechnology, can help solve problems associated with the use of toxic or expensive chemicals and increase the sustainability and affordability of the production of nanoparticles and biohybrid materials based on them. This review explores various methods for creating nanoparticles from both precious and base metals, using a variety of reducing agents and enzymes found in plants and bacteria, as well as promising biochemical approaches involving the reduction of metal salts inside living cells. Full article

(This article belongs to the Special Issue Eco-Friendly Nanomaterials: Innovations in Sustainable Applications)

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16 pages, 2841 KB

Open AccessArticle

Effect of Solidification Conditions on High-Cycle Fatigue Behavior in DD6 Single-Crystal Superalloy

by Hongji Xie, Yushi Luo, Yunsong Zhao and Zhenyu Yang

Metals 2025, 15(12), 1385; https://doi.org/10.3390/met15121385 (registering DOI) - 17 Dec 2025

Abstract

This study investigates the influence of solidification conditions on the high-cycle fatigue (HCF) behavior of a second-generation DD6 single-crystal superalloy. Single-crystal bars with a [⁰⁰¹] orientation were prepared using the high-rate solidification (HRS) and liquid-metal cooling (LMC) techniques under various pouring [...] Read more.

This study investigates the influence of solidification conditions on the high-cycle fatigue (HCF) behavior of a second-generation DD6 single-crystal superalloy. Single-crystal bars with a [⁰⁰¹] orientation were prepared using the high-rate solidification (HRS) and liquid-metal cooling (LMC) techniques under various pouring temperatures. The HCF performance of the heat-treated alloy was subsequently evaluated at 800 °C using rotary bending fatigue tests. The results demonstrate that increasing the pouring temperature effectively reduced the content and size of microporosity in the HRS alloys. At an identical pouring temperature, the LMC alloy exhibited a significant reduction in microporosity, with its content and maximum pore size being only 44.4% and 45.8% of those in the HRS alloy, respectively. Consequently, the HCF performance was enhanced with increasing pouring temperature for the HRS alloys. The LMC alloy outperformed its HRS counterpart processed at the same temperature, showing a 9.4% increase in the conditional fatigue limit (at 10⁷ cycles). Microporosity was identified as the dominant site for HCF crack initiation at 800 °C. The role of γ/γ′ eutectic in crack initiation diminished or even vanished as the solidification conditions were optimized. Fractographic analysis revealed that the HCF fracture mechanism was quasi-cleavage, independent of the solidification conditions. Under a typical stress amplitude of 550 MPa, the deformation mechanism was characterized by the slip of a/2<011> dislocations within the γ matrix channels, which was also unaffected by the solidification conditions. In conclusion, optimizing solidification conditions, such as by increasing the pouring temperature or employing the LMC process, enhances the HCF performance of the DD6 alloy primarily by refining microporosity, which in turn prolongs the fatigue crack initiation life. Full article

(This article belongs to the Section Metal Failure Analysis)

22 pages, 613 KB

Open AccessArticle

The Living Water of Policies: How Can Water Rights Trading Pilots Promote the Net Carbon Sink Intensity of the Planting Industry

by Yuan Zhao, Shaobo Cui, Lin Ji and Yunfeng Xing

Sustainability 2025, 17(24), 11343; https://doi.org/10.3390/su172411343 (registering DOI) - 17 Dec 2025

Abstract

Water rights trading policies play a crucial role in optimizing water resource allocation, improving agricultural water use efficiency, and promoting the sustainability of both agriculture and the environment, while also providing strong support for achieving the ‘dual-carbon’ goals. Utilizing data from 291 prefecture-level [...] Read more.

Water rights trading policies play a crucial role in optimizing water resource allocation, improving agricultural water use efficiency, and promoting the sustainability of both agriculture and the environment, while also providing strong support for achieving the ‘dual-carbon’ goals. Utilizing data from 291 prefecture-level cities between 2009 and 2023, this research applies the PSM-DID model to examine how the water rights trading policy affects the net carbon sink intensity in the planting sector. The findings are as follows: First, the water rights trading policy can significantly enhance the net carbon sink intensity of the planting industry, with an average increase of 1.110 tons per hectare. Second, the mediating effect model is employed to test the underlying mechanism. The results show that the water rights trading policy can play a role through two paths: reducing the proportion of food crop planting and reducing the use of fertilizer. Third, heterogeneity analysis is conducted using subgroup regression. The heterogeneity analysis reveals that the policy’s impact is more pronounced in cities characterized by abundant water resources, higher farmer incomes, and those situated in Eastern China. Fourth, a spatial-effect analysis is performed with the spatial Durbin model. The results further reveal that the policy not only directly enhances the net carbon sink intensity in the planting industry but also generates significant spatial spillover effects. In the future, efforts should focus on enhancing the market structure for water rights trading and reinforcing region-specific implementation strategies, guiding the green optimization of the planting structure, preventing the rebound effect of water conservation, and emphasizing the role of spatial linkage to create a new model of regionally coordinated low-carbon development in agriculture. Full article

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18 pages, 2806 KB

Open AccessArticle

Development of an Innovative Mechanical–Aeraulic Device for Sustainable Vector Control of Nymphs of Philaenus spumarius

by Francesco Paciolla, Alessia Farella, Gerardo Betrò, Annalisa Milella and Simone Pascuzzi

Agriculture 2025, 15(24), 2609; https://doi.org/10.3390/agriculture15242609 (registering DOI) - 17 Dec 2025

Abstract

Several management strategies based on different approaches have been proposed to contain the spread of the pest Xylella fastidiosa, but novel, effective, and sustainable physical methods are still needed. The present study is focused on the design, construction, and testing of an [...] Read more.

Several management strategies based on different approaches have been proposed to contain the spread of the pest Xylella fastidiosa, but novel, effective, and sustainable physical methods are still needed. The present study is focused on the design, construction, and testing of an innovative mechanical–aeraulic device which implements a physical vector control strategy against the nymphs of Philaenus spumarius. The developed machine generates an airstream with proper temperature, shape, and velocity to impact the nymphs sheltered in the protective white “spittle” and cause their impairment or death. The machine generates a hot airflow with a temperature of 71.9 °C at 10 cm and 65.4 °C at 30 cm and a speed of 8.6 m s⁻¹ at 10 cm to 6.2 m s⁻¹ at 30 cm from the central axis of the outlet section. The area affected by the hot airflow was 2.65 m², and the recorded mean temperature of the vegetation in this area was 60.2 ± 2 °C. The mean mortality rate of nymphs of Philaenus spumarius reached by using the developed machine was 84.3%. Full article

(This article belongs to the Section Agricultural Technology)

44 pages, 5889 KB

Open AccessArticle

A Multi-Stage Hybrid Learning Model with Advanced Feature Fusion for Enhanced Prostate Cancer Classification

by Sameh Abd El-Ghany and A. A. Abd El-Aziz

Diagnostics 2025, 15(24), 3235; https://doi.org/10.3390/diagnostics15243235 (registering DOI) - 17 Dec 2025

Abstract

Background: Cancer poses a significant health risk to humans, with prostate cancer (PCa) being the second most common and deadly form among men, following lung cancer. Each year, it affects over a million individuals and presents substantial diagnostic challenges due to variations [...] Read more.

Background: Cancer poses a significant health risk to humans, with prostate cancer (PCa) being the second most common and deadly form among men, following lung cancer. Each year, it affects over a million individuals and presents substantial diagnostic challenges due to variations in tissue appearance and imaging quality. In recent decades, various techniques utilizing Magnetic Resonance Imaging (MRI) have been developed for identifying and classifying PCa. Accurate classification in MRI typically requires the integration of complementary feature types, such as deep semantic representations from Convolutional Neural Networks (CNNs) and handcrafted descriptors like Histogram of Oriented Gradients (HOG). Therefore, a more robust and discriminative feature integration strategy is crucial for enhancing computer-aided diagnosis performance. Objectives: This study aims to develop a multi-stage hybrid learning model that combines deep and handcrafted features, investigates various feature reduction and classification techniques, and improves diagnostic accuracy for prostate cancer using magnetic resonance imaging. Methods: The proposed framework integrates deep features extracted from convolutional architectures with handcrafted texture descriptors to capture both semantic and structural information. Multiple dimensionality reduction methods, including singular value decomposition (SVD), were evaluated to optimize the fused feature space. Several machine learning (ML) classifiers were benchmarked to identify the most effective diagnostic configuration. The overall framework was validated using k-fold cross-validation to ensure reliability and minimize evaluation bias. Results: Experimental results on the Transverse Plane Prostate (TPP) dataset for binary classification tasks showed that the hybrid model significantly outperformed individual deep or handcrafted approaches, achieving superior accuracy of 99.74%, specificity of 99.87%, precision of 99.87%, sensitivity of 99.61%, and F1-score of 99.74%. Conclusions: By combining complementary feature extraction, dimensionality reduction, and optimized classification, the proposed model offers a reliable and generalizable solution for prostate cancer diagnosis and demonstrates strong potential for integration into intelligent clinical decision-support systems. Full article

(This article belongs to the Special Issue Advances in Machine Learning for Computer-Aided Diagnosis in Biomedical Imaging—2nd Edition)

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15 pages, 1237 KB

Open AccessArticle

Epigenome-Wide Search for Distinctive Methylation Biomarkers of Endothelial and Leukocyte DNA

by Valeria A. Korolenya, Maxim L. Filipenko and Mariya A. Smetanina

Epigenomes 2025, 9(4), 53; https://doi.org/10.3390/epigenomes9040053 (registering DOI) - 17 Dec 2025

Abstract

The endothelium, as the inner layer of the vascular wall, is in constant contact with blood components, so that leukocytes have the ability to adhere to endotheliocytes and penetrate to the subendothelial space. When studying heterogenic vascular samples containing endothelial cells or pathological [...] Read more.

The endothelium, as the inner layer of the vascular wall, is in constant contact with blood components, so that leukocytes have the ability to adhere to endotheliocytes and penetrate to the subendothelial space. When studying heterogenic vascular samples containing endothelial cells or pathological processes related to inflammation within the endothelium, it may be necessary to distinguish DNA by endothelial and leukocyte origin, which is possible due to its specific epigenetic modifications. To identify CpG loci that could serve as markers for endothelial cells, we searched for their distinctive stable methylated or demethylated states by applying marginal filtering (selecting CpG loci with methylation Beta values closer to 0 and 1) to the microarray data and identified 47 CpG loci with relatively stable methylation/demethylation status that differentiate endothelial (HUVEC, HCMEC, HPAEC, HPMEC, and LSEC) DNA from leukocyte (granulocytes, monocytes, and lymphocytes) DNA. In addition, we compared CpG loci with high and low levels of DNA methylation between different types of endothelial cells and leukocytes. We believe that the obtained data will hopefully facilitate further studies on endothelial dysfunction. Full article

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18 pages, 2426 KB

Open AccessArticle

Enhanced YOLOv8n-Based Three-Module Lightweight Helmet Detection System

by Xinyu Zuo, Yiqing Dai, Chao Yu and Wang Gang

Sensors 2025, 25(24), 7664; https://doi.org/10.3390/s25247664 (registering DOI) - 17 Dec 2025

Abstract

Maintaining a safe working environment for construction workers is critical to the improvement of urban areas. Several issues plague the present safety helmet detection technologies utilized on construction sites. Some of these issues include low accuracy, expensive deployment of edge devices, and complex [...] Read more.

Maintaining a safe working environment for construction workers is critical to the improvement of urban areas. Several issues plague the present safety helmet detection technologies utilized on construction sites. Some of these issues include low accuracy, expensive deployment of edge devices, and complex backgrounds. To overcome these obstacles, this paper introduces a detection method that is both efficient and based on an improved version of YOLOv8n. Three components make up the superior algorithm: the C2f-SCConv architecture, the Partial Convolutional Detector (PCD), and Coordinate Attention (CA). Detection, redundancy reduction, and feature localization accuracy are all improved with coordinate attention. To further enhance feature quality, decrease computing cost, and make corrections more effective, a Partial Convolution detector is subsequently constructed. Feature refinement and feature representation are made more effective by using C2f-SCConv instead of the bottleneck C2f module. In comparison to its predecessor, the upgraded YOLOv8n is superior in every respect. It reduced model size by 2.21 MB, increased frame rate by 12.6 percent, decreased FLOPs by 49.9 percent, and had an average accuracy of 94.4 percent. This method is more efficient, quicker, and cheaper to set up on-site than conventional helmet-detection algorithms. Full article

(This article belongs to the Special Issue Intelligent Sensors and Artificial Intelligence in Building)

11 pages, 924 KB

Open AccessArticle

Study of Reaction Parameters for the Precise Synthesis of Low-Molecular-Weight Oligosiloxanes

by Satoru Saotome, Jiaorong Kuang, Yujia Liu, Takayuki Iijima and Masafumi Unno

Materials 2025, 18(24), 5677; https://doi.org/10.3390/ma18245677 (registering DOI) - 17 Dec 2025

Abstract

This study investigates the influence of various parameters on the synthesis of oligosiloxanes with degrees of polymerization below 15. The work provides insights into methods for synthesizing oligosiloxanes with precisely controlled molecular weight and degrees of polymerization. Low-molecular-weight polysiloxanes with well-defined molecular characteristics [...] Read more.

This study investigates the influence of various parameters on the synthesis of oligosiloxanes with degrees of polymerization below 15. The work provides insights into methods for synthesizing oligosiloxanes with precisely controlled molecular weight and degrees of polymerization. Low-molecular-weight polysiloxanes with well-defined molecular characteristics have attracted attention due to their versatile functional properties and potential applications. Although some studies have explored the control of polysiloxane molecular weights, precise regulation of oligosiloxane molecular weight has been rarely investigated. This study aims to establish optimized reaction conditions for the synthesis of oligosiloxanes with precisely controlled molecular weights. The results reveal that the molecular weight of oligosiloxanes can be effectively tuned by adjusting the molar ratio between the promoter and initiator, the initiator and cyclotrisiloxane (D₃), as well as by varying the lithium type and solvent composition in the ring-opening polymerization of D₃. These findings provide valuable guidance for tailoring oligosiloxane properties and expanding their potential applications in advanced materials. Full article

(This article belongs to the Special Issue Functional Polymers for Energy, Biomedical and Electrical Applications)

14 pages, 3031 KB

Open AccessArticle

Identification of Mechanical Parameters of the Silicon Structure of a Capacitive MEMS Accelerometer

by Kamil Kurpanik, Klaudiusz Gołombek, Edyta Krzystała, Jonasz Hartwich and Sławomir Kciuk

Materials 2025, 18(24), 5676; https://doi.org/10.3390/ma18245676 (registering DOI) - 17 Dec 2025

Abstract

The aim of this study was to conduct an advanced analysis of the MEMS sensor, including both experimental tests and numerical simulations, in order to determine its mechanical properties and operational dynamics in detail. It is challenging to find publications in the literature [...] Read more.

The aim of this study was to conduct an advanced analysis of the MEMS sensor, including both experimental tests and numerical simulations, in order to determine its mechanical properties and operational dynamics in detail. It is challenging to find publications in the literature that are not based on theoretical assumptions or general manufacturer data, which do not reflect the actual microstructural characteristics of the sensor. This study uses a numerical model developed in MATLAB/Simulink, which allows the experimentally determined material characteristics to be combined with predictive dynamic modelling. The model takes into account key mechanical parameters such as stiffness, damping and response to dynamic loads, and the built-in optimisation algorithm allows the structural parameters of the MEMS accelerometer to be estimated directly from experimental data. In addition, SEM microscopic studies and EDS chemical composition analysis provided detailed information on the sensor’s microstructure, allowing its impact on mechanical properties and dynamic parameters to be assessed. The integration of advanced experimental methods with numerical modelling has resulted in a model whose response closely matches the measurement results, which is an important step towards further research on design optimisation and improving the reliability of MEMS sensors in diverse operating conditions. Full article

(This article belongs to the Special Issue Multiscale Mechanical Behaviors of Advanced Materials and Structures)

28 pages, 2484 KB

Open AccessReview

Research Progress on Application of Machine Learning in Continuous Casting

by Zhaofeng Wang, Jinghao Shao, Shuai Zhang, Jiahui Zhang and Yuqi Pang

Metals 2025, 15(12), 1383; https://doi.org/10.3390/met15121383 (registering DOI) - 17 Dec 2025

Abstract

Continuous casting is a key core link in steel production with characteristics of strong nonlinearity, multi-parameter coupling and dynamic fluctuations under working conditions. Traditional experience-dependent or mechanism-driven models are no longer suitable for the high-quality and high-efficiency production demands of modern steel industries. [...] Read more.

Continuous casting is a key core link in steel production with characteristics of strong nonlinearity, multi-parameter coupling and dynamic fluctuations under working conditions. Traditional experience-dependent or mechanism-driven models are no longer suitable for the high-quality and high-efficiency production demands of modern steel industries. Machine learning provides an effective technical path for solving the complex control problems in the continuous casting process through its powerful data mining and pattern recognition capabilities. This paper systematically reviews the research progress of machine learning applications in the field of continuous casting, focusing on three core scenarios: abnormal prediction, quality defect detection and process parameter optimization. It sorts out the evolution from single models to feature optimization and integration, deep learning hybrid models, and mechanism-data dual-driven models. It summarizes the significant achievements of this technology in reducing production risks and improving the stability of cast billet quality, and it analyzes the prominent challenges currently faced such as data distortion and distribution imbalance, insufficient model interpretability and limited cross-scenario generalization ability. Finally, it looks forward to future technological innovation and application expansion directions, providing theoretical support and technical references for the digital and intelligent transformation of the steel industry. Full article

26 pages, 2757 KB

Open AccessArticle

Novel Synthetic Steroid Derivatives: Target Prediction and Biological Evaluation of Antiandrogenic Activity

by David Calderón Guzmán, Norma Osnaya Brizuela, Hugo Juárez Olguín, Maribel Ortiz Herrera, Armando Valenzuela Peraza, Ernestina Hernández Garcia, Alejandra Chávez Riveros, Sarai Calderón Morales, Alberto Rojas Ochoa, Aylin Silva Ortiz, Rebeca Santes Palacios, Víctor Manuel Dorado Gonzalez and Diego García Ortega

Curr. Issues Mol. Biol. 2025, 47(12), 1059; https://doi.org/10.3390/cimb47121059 (registering DOI) - 17 Dec 2025

Abstract

Background: Two natural steroids derived from cholesterol pathways are testosterone and progesterone, androgen and antiandrogen receptor binding. Steroid androgen antagonists can be prescribed to treat an array of diseases and disorders such as gender dysphoria. In men, androgen antagonists are frequently used to [...] Read more.

Background: Two natural steroids derived from cholesterol pathways are testosterone and progesterone, androgen and antiandrogen receptor binding. Steroid androgen antagonists can be prescribed to treat an array of diseases and disorders such as gender dysphoria. In men, androgen antagonists are frequently used to treat prostate cancer and hyperplasia. Sex hormones regulate the expression of the viral receptors in COVID-19 progression, and these hormones may act as a metabolic signal-mediating response to changes in glucose and Reactive Oxygen Species (ROS). The objective of the present study is to use artificial intelligence (AI) applications in healthcare to predict the targets and to assess biological assays of novel steroid derivatives prepared in house from the commercially available 16-dehydropregnenolone acetate (DPA^®) aimed at achieving the metabolic stability of glucose and steroid brain homeostasis. This suggests the introduction of aromatic or aliphatic structures in the steroid B-ring and D-ring. This is important since the roles of 5α-reductase and ROS in brain control of glucose and novel steroids homeostasis remain unclear. Methods: A tool prediction was used as a tuned algorithm, with the novel steroid derivatives data in web interface to carry out their pharmacological evaluation. The new steroidal derivatives were determined with neuroprotection effect using the select biomarkers of oxidative stress on induced hypoglycemic male rat brain and liver. The enzyme kinetics was established by the inhibition of the 5α-reductase enzyme on the brain myelin. Results: We used novel chemical structures to order the information of a Swiss data bank that allow target predictions. Biological assays suggest that steroid derivatives with an electrophilic center can interact more efficiently with the 5α-reductase enzyme, and by this way, induce neuroprotection in hypoglycemia model. All compounds were synthesized with a yield of 30–80% and evaluated with tool target prediction to understand the molecular mechanisms underlying a given phenotype or bioactivity and to rationalize possible favorable or unfavorable side effects, as well as to predict off-targets of known molecules and to clear the way for drug repurposing. Apart, they turned out to be good inhibitors for the 5α-reductase enzyme. Conclusions: The probed efficacy of these novel steroids with respect to spironolactone control appears to be a promising compound for future hormonal therapy with neuroprotection activity in glucose disorder status. However, further research with clinically meaningful endpoints is needed to optimize the use of androgen antagonists in these hormonal therapies in COVID-19 progression. Full article

(This article belongs to the Special Issue Novel Pharmacological Strategies and Molecular Mechanisms in Nonclinical Research)

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22 pages, 3521 KB

Open AccessArticle

Energy-Model-Based Global Path Planning for Pure Electric Commercial Vehicles Toward 3D Environments

by Kexue Lai, Dongye Sun, Binhao Xu, Feiya Li, Yunfei Liu, Guangliang Liao and Junhang Jian

Machines 2025, 13(12), 1151; https://doi.org/10.3390/machines13121151 (registering DOI) - 17 Dec 2025

Abstract

Traditional path planning methods primarily optimize distance or time, without fully considering the impact of slope gradients in park road networks, variations in vehicle load capacity, and braking energy recovery characteristics on the energy consumption of pure electric commercial vehicles. To address these [...] Read more.

Traditional path planning methods primarily optimize distance or time, without fully considering the impact of slope gradients in park road networks, variations in vehicle load capacity, and braking energy recovery characteristics on the energy consumption of pure electric commercial vehicles. To address these issues, this paper proposes a globally optimized path planning method based on energy consumption minimization. The proposed method introduces a multi-factor coupled energy consumption model for pure electric commercial vehicles, integrating slope gradients, load capacity, motor efficiency, and energy recovery. Using this vehicle energy consumption model and the park road network topology map, an energy consumption topology map representing energy consumption between any two nodes is constructed. An energy-optimized improved ant colony optimization algorithm (E-IACO) is proposed. By introducing an exponential energy consumption heuristic factor and an enhanced pheromone update mechanism, it prioritizes energy-saving path exploration, thereby effectively identifying the optimal energy consumption path within the constructed energy consumption topology map. Simulation results demonstrate that in typical three-dimensional industrial park scenarios, the proposed energy-optimized path planning method achieves maximum reductions of 10.57% and 4.90% compared to the A* algorithm and ant colony optimization (ACO), respectively, with average reductions of 5.14% and 1.97%. It exhibits excellent stability and effectiveness across varying load capacities. This research provides a reliable theoretical framework and technical support for reducing logistics operational costs in industrial parks and enhancing the economic efficiency of pure electric commercial vehicles. Full article

(This article belongs to the Section Vehicle Engineering)

19 pages, 529 KB

Open AccessArticle

Fostering Action Competence Through Emancipatory, School-Based Environmental Projects: A Bildung Perspective

by Suchawadee Ketchanok and Jeerawan Ketsing

Educ. Sci. 2025, 15(12), 1706; https://doi.org/10.3390/educsci15121706 (registering DOI) - 17 Dec 2025

Abstract

Although much research in environmental and sustainability education has focused on knowledge and awareness, fewer studies have examined how school-based projects can foster young learners’ capacity for action. This study investigates how emancipatory, school-based environmental projects can foster young learners’ foundational capacities for [...] Read more.

Although much research in environmental and sustainability education has focused on knowledge and awareness, fewer studies have examined how school-based projects can foster young learners’ capacity for action. This study investigates how emancipatory, school-based environmental projects can foster young learners’ foundational capacities for contributing to a more sustainable and caring future. Grounded in the Bildung perspective and the action competence framework, a 16-week intervention was implemented with Grade 8 students who collaboratively identified and addressed authentic environmental issues—such as waste mismanagement, sanitation concerns, and safety risks—within their school community. Using a concurrent mixed-methods design, quantitative data from the Student Action Competence Questionnaire were integrated with qualitative evidence from worksheets and reflective journals. Results show consistent improvement across all dimensions of action competence, particularly in democratic collaboration and students’ willingness to take shared responsibility for environmental well-being. Qualitative findings reveal the development of critical reflection, co-creation with school stakeholders, and a growing sense of social responsibility, as students engaged in activities ranging from redesigning waste systems to proposing improvements through official communication channels. Rather than focusing on large-scale environmental outcomes, the projects cultivated everyday practices of care, participation, and ethical awareness—key dispositions for inspiring long-term change toward a greener and more sustainable future. The study highlights how context-based, dialogic learning can empower students as emerging environmental citizens within their immediate communities. Full article

(This article belongs to the Special Issue Education for a Sustainable Future: Inspiring Change for a Greener Planet)

27 pages, 3584 KB

Open AccessArticle

Divergence Shepherd Feature Optimization-Based Stochastic-Tuned Deep Multilayer Perceptron for Emotional Footprint Identification

by Karthikeyan Jagadeesan and Annapurani Kumarappan

Algorithms 2025, 18(12), 801; https://doi.org/10.3390/a18120801 (registering DOI) - 17 Dec 2025

Abstract

Emotional Footprint Identification refers to the process of recognizing or understanding the emotional impact that a person, experience, or interaction leaves on others. Emotion Recognition plays an important role in human–computer interaction for identifying emotions such as fear, sadness, anger, happiness, and surprise [...] Read more.

Emotional Footprint Identification refers to the process of recognizing or understanding the emotional impact that a person, experience, or interaction leaves on others. Emotion Recognition plays an important role in human–computer interaction for identifying emotions such as fear, sadness, anger, happiness, and surprise on the human face during the conversation. However, accurate emotional footprint identification plays a crucial role due to the dynamic changes. Conventional deep learning techniques integrate advanced technologies for emotional footprint identification, but challenges in accurately detecting emotions in minimal time. To address these challenges, a novel Divergence Shepherd Feature Optimization-based Stochastic-Tuned Deep Multilayer Perceptron (DSFO-STDMP) is proposed. The proposed DSFO-STDMP model consists of three distinct processes namely data acquisition, feature selection or reduction, and classification. First, the data acquisition phase collects a number of conversation data samples from a dataset to train the model. These conversation samples are given to the Sokal–Sneath Divergence shuffling shepherd optimization to select more important features and remove the others. This optimization process accurately performs the feature reduction process to minimize the emotional footprint identification time. Once the features are selected, classification is carried out using the Rosenthal correlative stochastic-tuned deep multilayer perceptron classifier, which analyzes the correlation score between data samples. Based on this analysis, the system successfully classifies different emotions footprints during the conversations. In the fine-tuning phase, the stochastic gradient method is applied to adjust the weights between layers of deep learning architecture for minimizing errors and improving the model’s accuracy. Experimental evaluations are conducted using various performance metrics, including accuracy, precision, recall, F1 score, and emotional footprint identification time. The quantitative results reveal enhancement in the 95% accuracy, 93% precision, 97% recall and 97% F1 score. Additionally, the DSFO-STDMP minimized the in training time by 35% when compared to traditional techniques. Full article

20 pages, 7209 KB

Open AccessArticle

A Novel Standalone TRNSYS Type for a Patented Shallow Ground Heat Exchanger: Development and Implementation in a DSHP System

by Silvia Cesari, Yujie Su and Michele Bottarelli

Energies 2025, 18(24), 6605; https://doi.org/10.3390/en18246605 (registering DOI) - 17 Dec 2025

Abstract

Decarbonizing building energy use requires efficient heat pumps and low-impact geothermal exchangers. A novel standalone TRNSYS Type was developed for a patented shallow horizontal ground heat exchanger (HGHE), called flat-panel (FP), designed at the University of Ferrara. Beyond simulating the FP in isolation, [...] Read more.

Decarbonizing building energy use requires efficient heat pumps and low-impact geothermal exchangers. A novel standalone TRNSYS Type was developed for a patented shallow horizontal ground heat exchanger (HGHE), called flat-panel (FP), designed at the University of Ferrara. Beyond simulating the FP in isolation, the Type enables coupling with other components within heat-pump configurations, allowing performance assessments that reflect realistic operating conditions. The Type was implemented in TRNSYS models of a ground-source heat pump (GSHP) and of a dual air and ground source heat pump (DSHP) to verify Type reliability and evaluate potential DSHP advantages over GSHP in terms of efficiency and ground-loop downsizing. The performance of the system was analyzed under varying HGHE lengths and DSHP control strategies, which were based on onset temperature differential DT. The results highlighted that shorter HGHE lines yielded higher specific HGHE performance, while higher DT reduced HGHE operating time. Concurrently, the total energy extracted from the ground decreased with increasing DT and reduced length, thus supporting long-term thermal preservation and allowing HGHE to operate under more favorable conditions. Exploiting air as an alternative or supplemental source to the ground allows significant reduction of the HGHE length and the related installation costs, without compromising the system performance. Full article

(This article belongs to the Special Issue Ground-Source Heat Pumps and Thermal Energy Storage Systems—Energy for the Future)

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