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28 pages, 3053 KB

Open AccessArticle

The Impact of Vibrations and Transport Systems on Human Comfort and Health: A Perspective on the Development of Sustainable City Buses

by Artūras Kilikevičius, Tautvydas Pravilonis, Jonas Matijošius, Edgar Sokolovskij, Kristina Kilikevičienė and Darius Vainorius

Sustainability 2025, 17(22), 10258; https://doi.org/10.3390/su172210258 (registering DOI) - 16 Nov 2025

Abstract

The objective of advancing sustainable public transportation extends beyond merely reducing pollution; it also aims to enhance the comfort and well-being of both passengers and drivers. This research investigates the influence of the dynamic characteristics of diesel and electric city buses on human [...] Read more.

The objective of advancing sustainable public transportation extends beyond merely reducing pollution; it also aims to enhance the comfort and well-being of both passengers and drivers. This research investigates the influence of the dynamic characteristics of diesel and electric city buses on human comfort, focusing specifically on vibration analysis. Vibrations have a significant impact on the durability of vehicle structures, passenger safety, and drivers’ working conditions, and long-term exposure can have negative health consequences. Based on experimental measurements and mathematical modeling, a dynamic model of a city bus was created, allowing us to assess the damping properties of suspension elements and the effect of load on vibrations. The findings of the study indicate that the judicious implementation of structural solutions and technological measures enhances the reliability of the transport system while simultaneously fostering the advancement of more sustainable and safer public transport options. The acquired data hold significance for both the development of new electric buses and the refurbishment of existing vehicles, aiming to integrate energy efficiency, comfort, and sustainable mobility. Full article

(This article belongs to the Special Issue Sustainable and Smart Transportation Systems)

30 pages, 2794 KB

Open AccessReview

An Update on Novel Pharmacotherapies for the Treatment of Neuroendocrine Tumors

by Khalil Choucair, Roupen Odabashian, Sushmita Nanja Reddy, Asfar Sohail Azmi and Muhammad Wasif Saif

Int. J. Mol. Sci. 2025, 26(22), 11095; https://doi.org/10.3390/ijms262211095 (registering DOI) - 16 Nov 2025

Abstract

Neuroendocrine tumors (NETs) are heterogeneous neoplasms with different molecular characteristics and prognosis. Although slow-growing, NETs are often diagnosed at an advanced stage. The treatment choice depends on primary site, extent, grade, growth rate, somatostatin receptor status, functional status, performance status, and comorbidities. Precise [...] Read more.

Neuroendocrine tumors (NETs) are heterogeneous neoplasms with different molecular characteristics and prognosis. Although slow-growing, NETs are often diagnosed at an advanced stage. The treatment choice depends on primary site, extent, grade, growth rate, somatostatin receptor status, functional status, performance status, and comorbidities. Precise knowledge of the biological and molecular features of NETs has led to the development of novel therapies. Therapeutic options include somatostatin analogs, multi-targeted tyrosine kinase inhibitors (e.g., sunitinib), or mammalian targets of rapamycin (mTOR) inhibitors (e.g., everolimus), telotristat ethyl, chemotherapy, and peptide-receptor radionuclide therapy. Pivotal studies that led to approval, treatment-related adverse events, and safety concerns, as demonstrated in clinical trials and real-world clinical practice. Questions, such as the optimal timing, selection, and sequence of therapies, and biomarkers that predict response to the novel agents in an individual patient, remain to be answered. We propose a stepwise approach for the management of advanced Gastro-entero-pancreatic (GEP)-NETs that utilizes a multidisciplinary team of experts. Biomarkers may assist in both the diagnosis and post-treatment follow-up in patients with GEP-NETs. The next decade of research on GEP-NETs is promising and should provide new insights into the molecular underpinnings of this disease, therapy selection, and the sequencing of the available therapies, along with the potential role of AL in NET pharmacotherapy. Full article

(This article belongs to the Special Issue Molecular Insights into Pancreatic Diseases)

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22 pages, 1020 KB

Open AccessArticle

Performance of Mineral and Plant-Derived Dusts Against the Cabbage Stink Bug (Eurydema ventralis Kolenati) on Brassica Leaves: Mortality and Feeding Injury

by Luka Batistič and Stanislav Trdan

Horticulturae 2025, 11(11), 1384; https://doi.org/10.3390/horticulturae11111384 (registering DOI) - 16 Nov 2025

Abstract

Eurydema ventralis has recently intensified in Brassica production in Central and Southeastern Europe, increasing the need for alternatives to conventional insecticides. This laboratory study evaluated five locally sourced inert and plant-derived dusts on the mortality and feeding damage of E. ventralis adults and [...] Read more.

Eurydema ventralis has recently intensified in Brassica production in Central and Southeastern Europe, increasing the need for alternatives to conventional insecticides. This laboratory study evaluated five locally sourced inert and plant-derived dusts on the mortality and feeding damage of E. ventralis adults and nymphs. The tested materials were diatomaceous earth, zeolite, quartz sand, wood ash of Norway spruce and Ailanthus altissima leaf dust, compared with an untreated control and a lambda-cyhalothrin control. Mortality and feeding damage were recorded over seven days. The insecticide caused complete mortality in both developmental stages. Diatomaceous earth exhibited the highest efficacy among inert dusts, i.e., 78.3% mortality in adults and 55.2% in nymphs, and a feeding damage index of 3.5. Zeolite and wood ash caused moderate mortality (30.4 and 26.1% in adults; 37.9 and 24.1% in nymphs) and feeding indices of 4.5 and 4.5. A. altissima leaf dust caused low mortality (≤14.5%) but reduced feeding damage (3.7), indicating a deterrent or antifeedant effect. Quartz sand showed negligible efficacy. Diatomaceous earth appears most suitable for integration into sustainable Brassica protection, and A. altissima leaf dust may act as a complementary deterrent, though optimized composition and persistence should be further investigated. Full article

(This article belongs to the Special Issue Pest and Disease Management in Horticultural Crops: Challenges, Strategies, and Solutions)

18 pages, 44807 KB

Open AccessArticle

Lactobacillus plantarum 17-5 Alleviates Escherichia coli Mastitis by Inhibiting the cGAS-STING Pathway

by Jia-Ze Han, Meng-Meng Li, Xiao-Wen Yu, Rui-Ning Zhang, Qian Zou, Jun-Chi Deng, Fa-Jian Zhao, Han-Qing Li, Ke Li and Zhen-Gui Yan

Animals 2025, 15(22), 3305; https://doi.org/10.3390/ani15223305 (registering DOI) - 16 Nov 2025

Abstract

Escherichia coli (E. coli) is a major etiological agent of clinical bovine mastitis. This study evaluated the therapeutic potential of Lactobacillus plantarum 17-5 (LP) against E. coli-induced mastitis via clinical, animal, and cellular models. In a trial with mastitic [...] Read more.

Escherichia coli (E. coli) is a major etiological agent of clinical bovine mastitis. This study evaluated the therapeutic potential of Lactobacillus plantarum 17-5 (LP) against E. coli-induced mastitis via clinical, animal, and cellular models. In a trial with mastitic dairy cows, dietary LP significantly reduced systemic inflammatory markers (IL-6, IL-1β, TNF-α) by 2–3-fold (p < 0.05) and milk somatic cell count by 7-fold (p < 0.05). 16S rRNA sequencing revealed these improvements were associated with substantial gut microbiota restructuring, suggesting a link between gut microbial balance and mammary health via the gut–mammary axis. In a murine model, LP mitigated mammary inflammatory injury (histopathology) and restored tight junction integrity while reducing apoptosis (western blot, p < 0.05). In bovine mammary epithelial cells (BMECs), LP suppressed the cGAS-STING pathway, inhibiting NF-κB P65 phosphorylation and downstream pro-inflammatory cytokine production (p < 0.05). Collectively, LP alleviates E. coli-associated mastitis by modulating gut microbiota through the gut–mammary axis and directly inhibiting the cGAS-STING/NF-κB axis, supported by multi-model evidence. Full article

(This article belongs to the Section Veterinary Clinical Studies)

22 pages, 2493 KB

Open AccessArticle

Chemical Profiling and Geographic Differentiation of Ugandan Propolis by GC-MS Through Chemometric Modelling

by Ivan Kahwa, Leonard Kaysser, Rapheal Wangalwa, Susan Billig, Jonans Tusiimire and Claudia Wiesner

Molecules 2025, 30(22), 4435; https://doi.org/10.3390/molecules30224435 (registering DOI) - 16 Nov 2025

Abstract

Propolis is a resinous substance collected by honeybees, and its long-known bioactivity urged research on its exact composition on active ingredients. It was suggested that chemical composition reflects the botanical sources and environmental conditions of its origin; however, information on differences related to [...] Read more.

Propolis is a resinous substance collected by honeybees, and its long-known bioactivity urged research on its exact composition on active ingredients. It was suggested that chemical composition reflects the botanical sources and environmental conditions of its origin; however, information on differences related to geographical origin is still incomplete. Therefore, this study aimed to characterise the volatile and semi-volatile chemical constituents of Ugandan propolis from nine agro-ecological zones using headspace gas chromatography–mass spectrometry (HS-GC-MS) and derivatisation-based GC-MS, coupled with multivariate statistical analysis. In total, 213 volatile and 169 non-volatile compounds were tentatively identified, including monoterpenes (α-pinene), sesquiterpenes (α-copaene), triterpenoids (β-amyrin acetate), diterpene resin acids (abietic acid), phenolic acids (caffeic acid), alkylresorcinols (bilobol) and many others. Multivariate chemometric modelling using partial least-squares discriminant analysis (PLS-DA), orthogonal PLS-DA (oPLS-DA) showed strong geographic discrimination of samples (Q² > 0.90) for several district comparisons. Heatmap clustering and variable importance in projection (VIP) analysis identified chemical markers. Notably, oPLS-DA revealed excellent discrimination between Nakasongola and Bushenyi, and between Adjumani and Bushenyi, in both volatile and non-volatile datasets. The findings provide the first comprehensive chemical profiling of Ugandan propolis, demonstrating the utility of combined GC-MS approaches and multivariate analysis for regional differentiation. This work lays the groundwork for standardising propolis preparations and establishing appropriate quality control in pharmacological applications. Full article

(This article belongs to the Special Issue Exclusive Feature Papers in Analytical Chemistry)

30 pages, 957 KB

Open AccessArticle

Addressing Aircraft Maintenance Delays Using a DMAIC-FMEA Framework: Insights from a Commercial Aviation Case Study

by Khaled Aljaly, Faouzi Masmoudi, Awad M. Aljuaid and Wafik Hachicha

Appl. Sci. 2025, 15(22), 12164; https://doi.org/10.3390/app152212164 (registering DOI) - 16 Nov 2025

Abstract

Aircraft maintenance delays (AMD) remain a significant challenge in commercial aviation, adversely affecting operational efficiency, flight punctuality, and passenger satisfaction. Despite advancements in maintenance strategies, recurring disruptions continue to generate financial losses and reputational risks. This study proposes an integrated five-step framework that [...] Read more.

Aircraft maintenance delays (AMD) remain a significant challenge in commercial aviation, adversely affecting operational efficiency, flight punctuality, and passenger satisfaction. Despite advancements in maintenance strategies, recurring disruptions continue to generate financial losses and reputational risks. This study proposes an integrated five-step framework that combines failure mode and effects analysis (FMEA) with the Define–Measure–Analysis–Improve–Control (DMAIC) methodology to systematically address and reduce AMD. The framework involves the definition of problems, the identification of contributing factors and failure modes, the assessment of risk and root cause analysis, the mitigation of risk, and continuous monitoring. The main contribution of this study lies in the integration of FMEA and DMAIC into a unified data-driven system that proactively reduces maintenance delays, offering a novel approach to continuous process improvement in aviation operations. Its practical applicability is demonstrated through a case study of the AFRIQIYAH Airways Airbus A320 fleet, which represents the majority of the airline’s operations. High-risk landing gear failure modes were identified, evaluated and addressed through targeted improvement projects, including predictive maintenance, supplier diversification, inventory optimization, and improved quality assurance for critical spare parts. Implementing these initiatives is expected to reduce the overall Risk Priority Number (RPN) by approximately 59%, highlighting the effectiveness and potential to minimize AMD. Full article

(This article belongs to the Section Aerospace Science and Engineering)

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10 pages, 936 KB

Open AccessArticle

Responses of the Corylus avellana Colonized by the Tuber Melanosporum Mycorrhiza to Short-Term Rhizosphere Disturbance

by Akale Assamere Habtemariam, Péter Cseh, Mihály Csizmár, Ferenc Fodor and Zoltán Bratek

Appl. Microbiol. 2025, 5(4), 133; https://doi.org/10.3390/applmicrobiol5040133 (registering DOI) - 16 Nov 2025

Abstract

We hypothesized that Tuber melanosporum colonization enhances growth and photosynthetic performance in Corylus avellana seedlings. Forty-eight seedlings were assessed for root colonization (stereomicroscopy, ITS sequencing) and photosynthetic traits (Li-6800F) under short-term disturbed and undisturbed rhizosphere conditions. Mycorrhizal colonization was found in 97.9% of [...] Read more.

We hypothesized that Tuber melanosporum colonization enhances growth and photosynthetic performance in Corylus avellana seedlings. Forty-eight seedlings were assessed for root colonization (stereomicroscopy, ITS sequencing) and photosynthetic traits (Li-6800F) under short-term disturbed and undisturbed rhizosphere conditions. Mycorrhizal colonization was found in 97.9% of seedlings (47/48). The mean colonization was 33.1% (SD = 16.1), 16.7% of seedlings showed more than 50% colonization per seedling, and 65.0% showed more than 30% colonization per seedling. Colonization declined with root depth and correlated with seedling length (r = 0.371, p = 0.01). In disturbed roots, longer root length predicted higher Gsw (r = 0.60), PhiCO₂ (r = 0.77), and PhiPSII (r = 0.70), while collar diameter negatively affected transpiration (r = −0.60). In undisturbed roots, collar-proximal colonization improved PhiPSII (r = 0.69, p = 0.02). Undisturbed seedlings showed ~2× higher CO₂ assimilation, stomatal conductance, quantum yield, and transpiration. These findings confirm that T. melanosporum enhances seedling physiology, especially under undisturbed conditions. Full article

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16 pages, 1401 KB

Open AccessReview

Electric and Hybrid Vehicle Fires—Metal Emission Hazard

by Anna Rabajczyk, Justyna Gniazdowska, Maria Zielecka, Damian Bąk, Anna Dziechciarz, Wojciech Klapsa and Magdalena N. Rabajczyk

Appl. Sci. 2025, 15(22), 12165; https://doi.org/10.3390/app152212165 (registering DOI) - 16 Nov 2025

Abstract

Metals have a crucial impact on the environment and the economy. They constitute macro- and microelements essential for the proper functioning of living organisms. On the other hand, their excess can pose a life-threatening risk. Of particular economic importance are metals such as [...] Read more.

Metals have a crucial impact on the environment and the economy. They constitute macro- and microelements essential for the proper functioning of living organisms. On the other hand, their excess can pose a life-threatening risk. Of particular economic importance are metals such as Co, Ni, Mn, Ti, Al, Cd, Fe, and Li, which are used, among other things, to build batteries in electric and hybrid cars. In the event of a cell fire, significant amounts of metals are rapidly released into the environment. The magnitude of emissions depends on the type of chemistry used in the battery and the type of extinguishing agent used to extinguish the fire. It should be noted that the available literature only provides information on the total amount or concentration of a given metal in the analyzed samples. However, there is no information on the speciation of metals, including their macro and nano forms, which is crucial for determining the toxicity and biological and chemical activity of a given element. Full article

(This article belongs to the Special Issue Materials for Lithium-Ion Batteries: Properties, Structures and Developments)

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24 pages, 3308 KB

Open AccessArticle

Benefits of Steroid Injections into Paraspinous Muscles After Spinal Surgery in a Rat Paraspinal Muscle Retraction Model

by Meei-Ling Sheu, Liang-Yi Pan, Jason Sheehan, De-Wei Lai, Yu-Cheng Chou, Liang-Yu Pan, Chien-Chia Wang, Ying Ju Chen, Hong-Lin Su, Hsi-Kai Tsou and Hung-Chuan Pan

Int. J. Mol. Sci. 2025, 26(22), 11093; https://doi.org/10.3390/ijms262211093 (registering DOI) - 16 Nov 2025

Abstract

Open posterior lumbar surgery involves detaching paraspinal muscles from the spine to decompress neural tissues and to place instruments. While this operation improves the quality of life, it often has adverse effects on skeletal muscles like inflammation, degeneration, and fibrosis. Corticosteroids are well [...] Read more.

Open posterior lumbar surgery involves detaching paraspinal muscles from the spine to decompress neural tissues and to place instruments. While this operation improves the quality of life, it often has adverse effects on skeletal muscles like inflammation, degeneration, and fibrosis. Corticosteroids are well known for their anti-inflammatory function. In this study, we assessed the protective effects of intramuscular injection of corticosteroid on injured paraspinal muscles following surgery on the spine. C2C12 cells were co-exposed to hypoxia and lipopolysaccharide (LPS) to simulate ischemia and inflammatory response after muscle retraction to assess the effect of steroid. In vivo experiment, animals first underwent paraspinous muscle splitting with retractors to induce muscle injury, and later were assessed for neurobehavior, electrophysiology, and protein level related to inflammatory or regeneration following intramuscular (IM) steroid injection. Steroid rescued reduced cell viability caused by hypoxia + LPS, and attenuated induced protein expression of iNOS, COX2, Bad, and Bax. In neurobehavioral assessments (CatWalk, Ethovision, Von Frey test, and open field locomotor), retraction of paraspinous muscles worsened behaviors that were improved by IM steroid injections. The electrophysiology study showed that IM steroid injection lessened the muscle denervation caused by retraction. Similarly, IM steroid injections also attenuated dorsal root ganglion antigenicity of CGRP, Iba-1, and CD68 induced by muscle retraction. Muscle retraction downregulated AChR, desmin, PSD 95, and GAP 43, whereas IM steroid injection attenuated the adverse effects. The restoration of muscle morphology and decreased fibrosis were also facilitated by IM dexamethasone. IM steroid injection appears to protect against retraction damage in paraspinous muscle following spinal surgery. IM steroid paraspinous muscle injection may provide beneficial effects in spinal operations. Full article

(This article belongs to the Section Molecular Biology)

30 pages, 6600 KB

Open AccessArticle

Mineralogical and Geochemical Characteristics of the Fe-Ti Mineralized Mafic-Ultramafic Intrusions at Wajilitag, Tarim Basin, China: With Special Emphasis on the Role of Apatite

by Weicheng Wang, Zhigang Kong, Maohong Chen, Jinmao Yin, Maihemuti Maimaiti and Donghui Liu

Minerals 2025, 15(11), 1208; https://doi.org/10.3390/min15111208 (registering DOI) - 16 Nov 2025

Abstract

The Early Permian Tarim Large Igneous Province is a prominent magmatic-metallogenic province in China, hosting significant Fe-Ti mineralized mafic-ultramafic intrusions. Among them, the Wajilitag Fe-Ti oxide deposit stands out, which is hosted by olivine pyroxenite, clinopyroxenite, and gabbro. In the present study, we [...] Read more.

The Early Permian Tarim Large Igneous Province is a prominent magmatic-metallogenic province in China, hosting significant Fe-Ti mineralized mafic-ultramafic intrusions. Among them, the Wajilitag Fe-Ti oxide deposit stands out, which is hosted by olivine pyroxenite, clinopyroxenite, and gabbro. In the present study, we have examined the mineralogical and geochemical characteristics of apatite to elucidate a deeper understanding of the magmatic evolutionary processes and source characteristics of the mafic-ultramafic intrusions in the Wajilitag area. Petrographic analysis revealed three distinct types of apatite: (1) an inclusion phase within pyroxene and plagioclase, (2) an intergranular phase associated with Fe-Ti oxides, and (3) a late-stage phase found in association with biotite and/or amphibole. Geochemical analysis showed that the inclusion and intergranular apatites exhibited high fluoride (F) and low chlorine (Cl) concentrations, while the late-stage apatite displayed the reverse. A negative correlation between F and Cl was observed, suggesting different formation conditions for each apatite type. The high F/Cl ratios (>3) and enrichment of light rare earth elements (LREEs/HREEs = 12.8–29.5) in the apatite, in conjunction with Sr/Th-La/Sm diagrams, indicated that the parent magma originated from an enriched mantle source, influenced by ancient subduction-related fluids. Furthermore, low sulfur content (0.01%–0.16%) in apatite, along with estimated melt sulfur concentrations (19–54 ppm), points to a low sulfur fugacity environment. These findings collectively suggest that the Wajilitag deposit formed from magma derived from partial melting of an enriched mantle, followed by extensive magmatic differentiation, crystallization of Fe-Ti oxides, and low sulfur fugacity conditions. Full article

(This article belongs to the Special Issue Mineralization and Metallogeny of Iron Deposits)

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22 pages, 968 KB

Open AccessArticle

A Simplified Methodology for Solvent Screening in Selective Extraction of Lipids from Microalgae Based on Hansen Solubility Parameters

by Costas Tsioptsias, Stefania Mitis, Alexandra Rentzela, Kalitsa Alvanou, Dimitra Kelesi, Christos Manolis, Anastasia Stergiou, Sotirios D. Kalamaras and Petros Samaras

Molecules 2025, 30(22), 4428; https://doi.org/10.3390/molecules30224428 (registering DOI) - 16 Nov 2025

Abstract

Microalgae are considered a potential source of fatty acid esters that are suitable for biodiesel production. However, a principal bottleneck in lipids extraction is related to the selection of appropriate solvents in order to obtain an efficient process. In this work, a simple [...] Read more.

Microalgae are considered a potential source of fatty acid esters that are suitable for biodiesel production. However, a principal bottleneck in lipids extraction is related to the selection of appropriate solvents in order to obtain an efficient process. In this work, a simple methodology based on Hansen Solubility Parameters (HSP) was developed, aiming to solvent screening towards selective extraction of lipid compounds: main parameters that were considered for an optimum solvent included the partitioning of free fatty acids and other non-desired solutes, e.g., pigments and phospholipids, as well as the minimum water dissolution. The method takes into account the affinity of a candidate solvent with desired and non-desired solutes along with their relative differences. A large number of solvents (>5000) were scanned by this method for their capacity to selectively extract fatty acid esters from microalgae biomass, and hexane proved to be among the optimum solvents. This prediction was supported by the Snyder’s polarity index as well as ab initio quantum mechanical Density Functional Theory (DFT) calculations of the Gibbs free energy of solvation and partition coefficients. Moreover, model validation carried out by liquid–liquid extraction of algal liquor with hexane and other solvents, and measurement of lipids allocation using paper chromatography and spectroscopy. Low lipids yield was observed, while the extract was enriched in fatty acid esters. A critical discussion is provided regarding the low yield ratios and potential implications due to overestimation of lipids content in microalgae. Full article

32 pages, 23108 KB

Open AccessArticle

Reconstruction of SMAP Soil Moisture Data Based on Residual Autoencoder Network with Convolutional Feature Extraction

by Yaojie Liu, Haoyu Fan, Yan Jin and Shaonan Zhu

Remote Sens. 2025, 17(22), 3729; https://doi.org/10.3390/rs17223729 (registering DOI) - 16 Nov 2025

Abstract

Satellite-based surface soil moisture (SSM) products often contain spatial gaps and reduced reliability due to variations in vegetation cover and type, complex surface conditions such as heterogeneous topography and soil texture, or inherent limitations of satellite microwave sensors. This study presents a residual [...] Read more.

Satellite-based surface soil moisture (SSM) products often contain spatial gaps and reduced reliability due to variations in vegetation cover and type, complex surface conditions such as heterogeneous topography and soil texture, or inherent limitations of satellite microwave sensors. This study presents a residual autoencoder model named TsSMNet, which combines multi-source remote sensing inputs with statistical features derived from SSM time series, including central tendency, dispersion and variability, extremes and distribution, temporal dynamics, magnitude and energy, and count-based features, to reconstruct gap-free SSM estimates. The model incorporates one-dimensional convolutional layers to efficiently capture local continuity patterns within the flattened SSM representations while reducing parameter complexity. TsSMNet was used to generate seamless 9 km SSM data over China from 2016 to 2022, based on the SMAP product, and was evaluated using in situ observations from six networks in the International Soil Moisture Network. The results show that TsSMNet outperforms AutoResNet, Transformer, Random Forest and XGBoost models, reducing the root mean square error (RMSE) by an average of 17.1 percent and achieving a mean RMSE of 0.09 cm³/cm³. Feature importance analysis highlights the strong contribution of temporal predictors to model accuracy. Compared to its variant without time-series features, TsSMNet provides better spatial representation, improved consistency with in situ temporal observations, and enhanced evaluation metrics. The reconstructed product offers improved spatial coverage and continuity relative to the original SMAP data, supporting broader applications in regional-scale hydrological analysis and large-scale climate, ecological, and agricultural studies. Full article

(This article belongs to the Special Issue Remote Sensing for Natural Resources and Environmental Management of Arid and Semi-Arid Regions)

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19 pages, 622 KB

Open AccessArticle

Sustainable Mortar for Non-Structural Applications Using Alkali Bypass Dust

by Riyadh Alturki

Sustainability 2025, 17(22), 10257; https://doi.org/10.3390/su172210257 (registering DOI) - 16 Nov 2025

Abstract

This study investigates the potential of alkali bypass dust (ABD) as a supplementary material to partially replace cement in paste and mortar formulations. The selection of ABD is motivated by the dual objectives of utilizing an industrial waste product to promote sustainable construction [...] Read more.

This study investigates the potential of alkali bypass dust (ABD) as a supplementary material to partially replace cement in paste and mortar formulations. The selection of ABD is motivated by the dual objectives of utilizing an industrial waste product to promote sustainable construction and reducing the carbon footprint associated with cement production. The chemical and mineralogical composition of ABD was characterized using X-ray fluorescence (XRF) and X-ray diffraction (XRD), revealing a composition similar to Portland cement but with a notably lower CaO content (44.32%) and the presence of calcite, portlandite, quartz, and free lime. The incorporation of ABD as a cement replacement significantly influenced the fresh and hardened properties of the mixtures. In paste mixtures, results demonstrated a proportional increase in water demand and setting times with higher ABD content, attributed to its lower reactivity and higher water absorption. Mechanical properties were adversely affected; compressive and flexure strengths in paste mixtures decreased substantially, with a 40% reduction observed at just 10% replacement. This was corroborated by a decrease in density, an increase in water absorption, and a significant drop in ultrasonic pulse velocity (UPV), indicating a more porous and less dense microstructure. In mortar mixtures, a 30% cement replacement with ABD yielded compressive and flexure strengths that remained within acceptable ranges for plastering and masonry applications, despite a reduction in workability. The findings suggest that while high-volume ABD replacement negatively impacts performance, a 30% replacement level presents a viable, sustainable alternative for specific non-structural applications, contingent upon further durability assessments. Full article

(This article belongs to the Section Sustainable Materials)

23 pages, 510 KB

Open AccessArticle

Rice Yield Forecasting in Northeast China with a Dual-Factor ARIMA Model Incorporating SPEI1-Sep. and Sown Area

by Song Nie and Zhi-Qiang Jiang

Forecasting 2025, 7(4), 67; https://doi.org/10.3390/forecast7040067 (registering DOI) - 16 Nov 2025

Abstract

Amid escalating global climate change and geopolitical tensions threatening food supply chains, the three provinces of Northeast China, which serve as a major grain production base, play a crucial role in ensuring national food security. However, the region is experiencing more frequent extreme [...] Read more.

Amid escalating global climate change and geopolitical tensions threatening food supply chains, the three provinces of Northeast China, which serve as a major grain production base, play a crucial role in ensuring national food security. However, the region is experiencing more frequent extreme climatic events and increasing limitations on arable land. This necessitates an evaluation of the combined effects of climate conditions and sown area on rice (Oryza sativa L.) yields. Utilizing provincial panel data from 1990 to 2022, this study conducts baseline panel regression analyses at both the national and Northeast China levels. The results consistently identify the value of the standardized precipitation evapotranspiration index (SPEI) on September as a key climatic factor exerting a significant negative effect on rice total yield, whereas the rice sown area is a robust positive determinant. Based on these findings, we develop a dual-factor analytical framework that incorporates both climatic conditions and rice sown area, utilizing SPEI1-Sep. to identify critical growth stages of rice, with the aim of providing a more comprehensive understanding of their combined effects on yield. To further support predictive accuracy, the comparative performance assessments of the Extreme Gradient Boosting (XGBoost), random forest (RF), and Autoregressive Integrated Moving Average (ARIMA) models are conducted. The results show that the ARIMA model outperforms others in forecasting. Forecasts for 2023–2027 indicate slow yield growth in Jilin Province, with a 1.5% annual increase. Heilongjiang shows minor fluctuations, stabilizing between 24.97 and 25.56 million tons. Liaoning’s yield remains stable, projected between 5.13 and 5.20 million tons. These trends suggest limited overall yield expansion, highlighting the need for region-specific policies and resource management to ensure China’s grain security. This study clarifies the interplay between climate and sown area, demonstrates the relative forecasting advantage of ARIMA in this setting, and provides evidence to support managing yield variability and optimizing agricultural policy in Northeast China, with implications for long-term national food security. Full article

13 pages, 1047 KB

Open AccessArticle

Inactivation of Respiratory Syncytial Virus by Ozone Generated via Dielectric Barrier Discharge Technology with Decrease in Intact Viral Surface Protein

by Akikazu Sakudo, Ryoya Moriyama and Masanori Nieda

Microorganisms 2025, 13(11), 2611; https://doi.org/10.3390/microorganisms13112611 (registering DOI) - 16 Nov 2025

Abstract

Respiratory syncytial virus (RSV) is a major cause of severe respiratory infections, particularly in infants and young children. Although disinfection methods using alcohol and detergents are effective, their application in pediatric environments poses safety concerns. Ozone (O₃) has been employed for [...] Read more.

Respiratory syncytial virus (RSV) is a major cause of severe respiratory infections, particularly in infants and young children. Although disinfection methods using alcohol and detergents are effective, their application in pediatric environments poses safety concerns. Ozone (O₃) has been employed for water treatment, food preservation, and air purification, but its efficacy against RSV has not been well studied. Here, we investigated the inactivation of RSV using a dielectric barrier discharge (DBD)-based ozone generator (SFG1210). The RSV A2 strain was spotted on glass coverslips and exposed to low-concentration ozone (0.5 ppm) for 1 h under controlled temperature (24.6~27.2 °C) and relative humidity (71.9~75.1%) conditions. Subsequent infectivity assays combined with immunochromatography showed that ozone exposure significantly reduced RSV infectivity. Specifically, viral titration assay of median tissue culture infectious dose (TCID₅₀) showed that RSV titers were reduced by more than 6 logs. In addition, biochemical analyses showed significant reductions in intact RSV genomic RNA and F protein levels after ozone treatment, suggesting that ozone inactivates RSV by damaging both the viral genome and surface proteins. These findings demonstrate the potential applicability of the SFG1210 ozone generator as an effective tool for surface disinfection of RSV, providing a safe, non-contact, and practical approach for infection control in healthcare and childcare settings. Full article

(This article belongs to the Section Public Health Microbiology)

18 pages, 4266 KB

Open AccessArticle

Biodegradable Film Mulching Increases Soil Respiration: A Two-Year Field Comparison with Polyethylene Film Mulching in a Semi-Arid Region of Northern China

by Xiaowei Liu, Dejun Wang, Mahepali Bazhabaike, Mingdong Zhou and Tao Yin

Agronomy 2025, 15(11), 2631; https://doi.org/10.3390/agronomy15112631 (registering DOI) - 16 Nov 2025

Abstract

Biodegradable film mulching is increasingly used to replace polyethylene in agriculture, but effects on soil respiration (SR) and components remain unclear, especially during degradation. This study investigated biodegradable mulching’s regulation of SR, root-derived respiration (RDR), and non-root-derived respiration (NRDR) under varying phases. A [...] Read more.

Biodegradable film mulching is increasingly used to replace polyethylene in agriculture, but effects on soil respiration (SR) and components remain unclear, especially during degradation. This study investigated biodegradable mulching’s regulation of SR, root-derived respiration (RDR), and non-root-derived respiration (NRDR) under varying phases. A two-year field experiment was conducted in a rainfed maize system in northern China, comparing conventional tillage with biodegradable film mulching (BM), conventional tillage with polyethylene film mulching (PM), and conventional tillage without mulching (CT). Continuous measurements of soil CO₂ concentration (SCC), temperature, water content, and respiration components were used to assess dynamic responses. Results showed that BM enhanced SR and shifted peak timing, with the SR peaking at 106 days after sowing (DAS) under BM, 91.8 DAS under PM, and 91.2 DAS under CT, mainly through a more sustained RDR (BM peak at 103 DAS with a broader peak and greater cumulative RDR than PM and CT). As the biodegradable plastic film degraded, NRDR was higher during the degradation phase, consistent with a priming-like response. These phase-dependent effects suggest that BM first facilitates root growth then serves as a microbial substrate. Moreover, elevated SCC was positively associated with both RDR and NRDR, indicating that CO₂ may function as a regulatory signal rather than a passive byproduct of respiration. These findings reveal distinct temporal mechanisms by which BM influences soil carbon fluxes and offer mechanistic insights into the sustainable application of biodegradable film mulching. Future research should evaluate long-term effects on microbial community composition, soil carbon balance, and potential trade-offs with crop productivity and environmental risks. Full article

(This article belongs to the Special Issue Microplastics in Farmland and Their Impact on Soil)

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18 pages, 3512 KB

Open AccessArticle

Investigation of Blast Resistance Performance in Reinforced Concrete Slabs Using CONWEP-ALE Coupling Algorithm

by Chengrui Wang, Kai Zhang, Wei Liu and Peng Li

Appl. Sci. 2025, 15(22), 12162; https://doi.org/10.3390/app152212162 (registering DOI) - 16 Nov 2025

Abstract

The Conventional Weapons Effects Program (CONWEP) algorithm often lacks sufficient accuracy in predicting blast responses of reinforced concrete (RC) slabs, while the Arbitrary Lagrangian–Eulerian (ALE) algorithm demands prohibitively high computational resources. To enhance the engineering applicability of blast resistance assessments for RC slabs, [...] Read more.

The Conventional Weapons Effects Program (CONWEP) algorithm often lacks sufficient accuracy in predicting blast responses of reinforced concrete (RC) slabs, while the Arbitrary Lagrangian–Eulerian (ALE) algorithm demands prohibitively high computational resources. To enhance the engineering applicability of blast resistance assessments for RC slabs, this study proposed a novel CONWEP-ALE coupling algorithm. Utilizing validated blast tests on RC slabs, a representative finite element model was established using LS-DYNA. The performance differences between the CONWEP, ALE, and CONWEP-ALE coupling algorithms were systematically compared under three distinct blast scenarios. Key response characteristics, including incident overpressure, structural deformation, and computational time, were analyzed to evaluate the predictive capabilities of each algorithm for RC slab dynamic response. The results demonstrated that the CONWEP-ALE coupling algorithm achieved the lowest average error (23.23%) in predicting incident overpressure among the three algorithms. Both the ALE and CONWEP-ALE coupling algorithms demonstrate superior accuracy over the CONWEP algorithm in predicting the displacement. Crucially, computational time was reduced by approximately 50% using the CONWEP-ALE algorithm for the specific blast scenarios. Thus, the CONWEP-ALE coupling algorithm provides an effective and efficient approach for analyzing the dynamic response and failure modes of blast-loaded RC slabs. Full article

(This article belongs to the Section Civil Engineering)

22 pages, 1957 KB

Open AccessArticle

GWO-Optimized Ensemble Learning for Interpretable and Accurate Prediction of Student Academic Performance in Smart Learning Environments

by Mohammed Husayn, Oluwatayomi Rereloluwa Adegboye and Ahmad Alzubi

Appl. Sci. 2025, 15(22), 12163; https://doi.org/10.3390/app152212163 (registering DOI) - 16 Nov 2025

Abstract

Accurate and interpretable prediction of student academic performance is a cornerstone of data-driven educational support systems, enabling timely interventions, personalized learning pathways, and equitable resource allocation. While ensemble machine learning models such as Random Forest, Extra Trees, and CatBoost have shown promise in [...] Read more.

Accurate and interpretable prediction of student academic performance is a cornerstone of data-driven educational support systems, enabling timely interventions, personalized learning pathways, and equitable resource allocation. While ensemble machine learning models such as Random Forest, Extra Trees, and CatBoost have shown promise in educational data mining, their predictive power and generalizability are often limited by suboptimal weighting schemes and sensitivity to hyperparameter configurations. To address this, we propose a Grey Wolf Optimizer (GWO)-guided ensemble framework that dynamically optimizes each base regressor’s contribution to minimize prediction error while preserving model transparency. Evaluated on a real-world student performance dataset, the proposed approach achieves a coefficient of determination (R²) of 0.93, significantly outperforming individual and conventional ensemble baselines. Furthermore, we integrate SHAP (SHapley Additive exPlanations) to provide educator-friendly interpretability, revealing that daily study hours, study effectiveness, lifestyle score, and screen time are the most influential predictors of exam outcomes. By bridging an optimized machine learning model with educational analytics, this work delivers a robust, transparent, and high-performing AI solution tailored for intelligent tutoring systems, early-warning platforms, and adaptive learning environments. The methodology exemplifies how nature-inspired optimization can enhance not only accuracy but also actionable insight for stakeholders in smart education ecosystems. Full article

(This article belongs to the Special Issue Artificial Intelligence Technologies for Education: Advancements, Challenges, and Impacts, 2nd Edition)

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19 pages, 2141 KB

Open AccessReview

Small Intestinal Bacterial Overgrowth in Children with Short Bowel Syndrome

by Hannah DeGonza, Thu Anh Pham, Rasha Elmaoued, Razan Alkhouri, Ricardo Orlando Castillo and Rajmohan Dharmaraj

Children 2025, 12(11), 1550; https://doi.org/10.3390/children12111550 (registering DOI) - 16 Nov 2025

Abstract

Small Intestinal Bacterial Overgrowth (SIBO) is characterized by an abnormal proliferation of bacteria in the small intestine, leading to gastrointestinal symptoms and nutritional deficiencies. Short Bowel Syndrome (SBS), resulting from extensive surgical resection of the small intestine, predisposes children to SIBO due to [...] Read more.

Small Intestinal Bacterial Overgrowth (SIBO) is characterized by an abnormal proliferation of bacteria in the small intestine, leading to gastrointestinal symptoms and nutritional deficiencies. Short Bowel Syndrome (SBS), resulting from extensive surgical resection of the small intestine, predisposes children to SIBO due to anatomical disruptions, motility dysfunction, parenteral nutrition dependence, and immune dysregulation. Clinical manifestations of SIBO in SBS include bloating, diarrhea, malabsorption, and failure to thrive, with severe cases leading to complications such as D-lactic acidosis. Diagnosis remains challenging, with breath testing being the most commonly used method despite limitations in accuracy, especially in SBS patients. Jejunal aspiration, the gold standard, presents limitations due to contamination risks, potential for sampling error, and a relatively low diagnostic yield. Management involves antibiotics like rifaximin and metronidazole, alongside strategies to address anatomical dysfunction, optimize nutrition, and prevent recurrence. Adjunctive therapies, including probiotics and dietary modifications, show promise but require further validation in children. Emerging treatments, such as glucagon-like peptide-2 (GLP-2) analogs, may enhance mucosal integrity and reduce SIBO risk. Given the chronic and recurrent nature of SIBO in SBS, a multidisciplinary approach is essential, integrating gastroenterological, surgical, and nutritional care to effectively manage the condition. Future research should focus on improving diagnostic methods, refining treatment protocols, and exploring targeted therapies to enhance outcomes and quality of life for affected children. Full article

(This article belongs to the Special Issue Advances in Pediatric Gastroenterology (2nd Edition))

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38 pages, 8506 KB

Open AccessArticle

Quantum-Inspired Cross-Attention Alignment for Turkish Scientific Abstractive Summarization

by Gönül Altay and Ecir Uğur Küçüksille

Electronics 2025, 14(22), 4474; https://doi.org/10.3390/electronics14224474 (registering DOI) - 16 Nov 2025

Abstract

This paper presents a quantum-inspired cross-attention alignment approach for abstractive summarization. The motivation is that current neural summarizers often lose key content and produce summaries that are weakly grounded in the source, especially for long and information-dense scientific articles in low-resource languages. The [...] Read more.

This paper presents a quantum-inspired cross-attention alignment approach for abstractive summarization. The motivation is that current neural summarizers often lose key content and produce summaries that are weakly grounded in the source, especially for long and information-dense scientific articles in low-resource languages. The method itself is model-agnostic and aims to strengthen token-level alignment without introducing additional trainable parameters or inference overhead, by exploiting a Born-rule-based similarity between encoder and decoder states. This general idea is instantiated and tested on the task of summarizing Turkish scientific articles in Mathematics Education, which provides a challenging low-resource test bed with long and dense source texts. Six different fine-tuning variants built upon the mBART-50 model are examined, including SFT, LoRA baselines, and two novel quantum-augmented decoders: the parameter-free SFT + QDA + QKernel and SFT + QDA + QBorn (Born-rule-inspired, learnable classical mapping). Models are trained with five random seeds and evaluated using beam search and sampling schemes. Statistical significance is assessed via bootstrap confidence intervals, Benjamini–Hochberg FDR correction, and Cliff’s δ effect size. Beam search consistently outperforms sampling across all architectures. Our best configuration, SFT + QDA + QKernel, achieves strong results (ROUGE-L: 0.2966, BERTScore-F1: 0.8890) and yields statistically significant, large-effect gains over all baselines. These findings indicate that the proposed parameter-free quantum kernel provides a practical way to improve abstraction quality and faithfulness, particularly in low-resource summarization settings. Full article

(This article belongs to the Special Issue Quantum Computation and Its Applications)

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9 pages, 7115 KB

Open AccessArticle

Surface Evolution and Performance of 45CrNiMoV Steel Modified by Electron Beam Irradiation

by Huihui Wang, Fuquan Long, Zhisen Liang, Shangfeng Cai, Rujin Lv and Shengzhi Hao

Coatings 2025, 15(11), 1335; https://doi.org/10.3390/coatings15111335 (registering DOI) - 16 Nov 2025

Abstract

Enhancing the surface mechanical properties and extending the service life of 45CrNiMoV mold steel are critical goals in mold development. To achieve these objectives, electron beam (EB) irradiation was employed to treat the 45CrNiMoV mold steel. This high-energy physical process enables precise modification [...] Read more.

Enhancing the surface mechanical properties and extending the service life of 45CrNiMoV mold steel are critical goals in mold development. To achieve these objectives, electron beam (EB) irradiation was employed to treat the 45CrNiMoV mold steel. This high-energy physical process enables precise modification of the surface microstructure. By meticulously controlling EB parameters, including energy, dose, and scanning mode, significant structural alterations occur in the surface layer. Consequently, the surface microhardness more than doubles, reaching 812.7 HV. This enhancement is attributed to grain refinement, increased dislocation density, and potential formation of new phases induced by EB irradiation. Beyond hardness improvement, the wear resistance of the treated specimen increases by 2.5-fold. Under standardized testing conditions, wear loss decreases markedly from 0.28 mg to 0.11 mg. This reduction in wear loss not only extends the mold’s operational lifespan but also minimizes maintenance and replacement requirements, thereby reducing production downtime and associated costs. This study transcends mere presentation of experimental data by comprehensively elucidating the intricate relationship between surface microstructure and the overall mechanical properties of 45CrNiMoV mold steel. Advanced characterization techniques, including scanning electron microscopy (SEM) and X-ray diffraction (XRD), were utilized to uncover the underlying mechanisms. The refined microstructure, characterized by fine grains and elevated dislocation density, impedes dislocation movement and crack propagation, thereby enhancing both hardness and wear resistance. Full article

(This article belongs to the Section Surface Characterization, Deposition and Modification)

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18 pages, 5779 KB

Open AccessArticle

Inverting the Concentrations of Chlorophyll-a and Chemical Oxygen Demand in Urban River Networks Using Normalized Hyperspectral Data

by Rongda Guan, Yingzhuo Hou, Maham Arif and Qianguo Xing

Sensors 2025, 25(22), 7004; https://doi.org/10.3390/s25227004 (registering DOI) - 16 Nov 2025

Abstract

Chlorophyll-a (Chl-a) and chemical oxygen demand (COD) are key indicators for water quality evaluation. In previous research on the inversion of Chl-a and COD concentrations using hyperspectral data, disparities in hyperspectral data types have constrained the universality of the inversion models. To solve [...] Read more.

Chlorophyll-a (Chl-a) and chemical oxygen demand (COD) are key indicators for water quality evaluation. In previous research on the inversion of Chl-a and COD concentrations using hyperspectral data, disparities in hyperspectral data types have constrained the universality of the inversion models. To solve this problem, in this study, synchronous in situ hyperspectral data and water samples were collected from 308 stations within the river networks of Zhongshan City. Four inversion models, support vector regression (SVR), random forest (RF), backpropagation neural network (BPNN), and one-dimensional convolutional neural network (1D-CNN), were established using the original reflectance (R), remote sensing reflectance (Rrs), and their normalized forms as inputs. To evaluate the robustness of the models, their performance was assessed via cross-reflectance type validation. For example, a model was trained using R data and then tested with Rrs data. The results show that using the normalized hyperspectral data for modeling not only improves the accuracy of the inversion results of Chl-a and COD concentrations, but also effectively unifies different types of hyperspectral data, thereby improving the versatility of the inversion model. This study provides a reference for constructing a general water quality inversion model based on hyperspectral data. Full article

(This article belongs to the Section Environmental Sensing)

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25 pages, 22359 KB

Open AccessArticle

Hybrid GTAW–FCAW of 316L Stainless Steel Pipes: Influence of Oxygen Content in Baking Gas and Surface Preparation on Oxide Characteristics and Corrosion Behavior

by Mohammad Maroufkhani, Alireza Khodabandeh, Iulian Radu and Mohammad Jahazi

J. Manuf. Mater. Process. 2025, 9(11), 377; https://doi.org/10.3390/jmmp9110377 (registering DOI) - 16 Nov 2025

Abstract

This study investigates the combined effects of oxygen content in the purging gas and pre-weld surface finish on the discoloration and corrosion resistance of AISI 316L pipe joints, with relevance to pipe welding where internal cleaning is constrained. The hybrid GTAW–FCAW process was [...] Read more.

This study investigates the combined effects of oxygen content in the purging gas and pre-weld surface finish on the discoloration and corrosion resistance of AISI 316L pipe joints, with relevance to pipe welding where internal cleaning is constrained. The hybrid GTAW–FCAW process was used. Welds were produced at two oxygen levels (500 and 5000 ppm) and two finishes (40- vs. 60-grit). Discoloration and oxide morphology were examined by SEM/EDS, and corrosion behavior was evaluated without oxide removal using cyclic polarization and electrochemical impedance spectroscopy. The results reveal that higher oxygen levels in the purging gas produced more porous, less protective oxide layers, along with intensified oxidation around surface defects such as micro-holes. Surface roughness was also found to influence corrosion behavior: rougher surfaces exhibited higher resistance to pit initiation, whereas smoother surfaces were more susceptible to initiation but offered greater resistance to pit propagation. The corresponding governing mechanisms were identified and discussed in terms of how surface preparation affects crystallographic texture, heterogeneities and recrystallization. Taken together, the results link oxide morphology and near-surface microstructure to electrochemical response and offer practical guidance for pipe welding when internal cleaning is constrained, balancing purging control with surface preparation to preserve corrosion performance. The findings further highlight the critical roles of both purging-gas composition and surface preparation in the corrosion performance of stainless steel welded pipes. Full article

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21 pages, 8278 KB

Open AccessArticle

Numerical Study on the Aerodynamic and Structural Response Characteristics of a High-Altitude Wind-Capturing Umbrella

by Jian Jiang, Jiaqi Wang, Yan Wang, Chang Cai and Tengyuan Wang

Appl. Sci. 2025, 15(22), 12161; https://doi.org/10.3390/app152212161 (registering DOI) - 16 Nov 2025

Abstract

As global demand for renewable energy continues to grow, high-altitude wind energy, characterized by high speed, wide distribution, and strong stability, has emerged as a promising alternative to low-altitude wind energy. Airborne Wind Energy systems (AWEs) are key to harnessing high-altitude wind, and [...] Read more.

As global demand for renewable energy continues to grow, high-altitude wind energy, characterized by high speed, wide distribution, and strong stability, has emerged as a promising alternative to low-altitude wind energy. Airborne Wind Energy systems (AWEs) are key to harnessing high-altitude wind, and Ground-Generator (Ground-Gen) AWEs are favored for their lower costs and simpler deployment. This study focuses on the umbrella–ladder-type Ground-Gen AWEs, aiming to address the research gap by exploring the influence of canopy permeability on the aerodynamic and structural response characteristics of flexible wind-capturing umbrellas. A single-umbrella model of the high-altitude wind-capturing umbrella was established, and bidirectional fluid–structure interaction (FSI) numerical simulations were conducted using the Arbitrary Lagrangian–Eulerian (ALE) method. Simulations were performed under a 30° angle of attack with two canopy thicknesses (5 × 10⁻⁵ m and 1 × 10⁻⁴ m) and varying permeability (adjusted via viscosity coefficient a and inertial coefficient b). Results showed that higher permeability (smaller a and b) hindered upper canopy inflation, while lower permeability promoted full inflation and more uniform stress distribution. The max/min in-plane shear stress for the model with the lowest permeability (Model F) was approximately 85% lower than that of the model with the highest permeability (Model A). The tension coefficient increased with decreasing permeability. Full inflation resulted in a slightly higher axial load in the upper suspension lines due to the lift force, with a difference of up to 92.3% during slight collapse. This difference becomes significantly more pronounced during severe collapse. Asymmetric flow fields at a 30° attack angle generated a lift force, resulting in higher tension coefficients than those at a 0° attack angle. These findings provide valuable references for the design and optimization of high-altitude wind-capturing umbrellas. Full article

(This article belongs to the Section Aerospace Science and Engineering)

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15 pages, 1291 KB

Open AccessArticle

High Seroprevalence of Toxoplasma gondii and Neospora caninum Infections Among Goats in Mexico Is Associated with Climatic, Environmental, and Risk Factors

by Abel Villa-Mancera, Eunice Vargas-Tizatl, José Manuel Robles-Robles, Fernando Utrera-Quintana, Jaime Olivares-Pérez, Agustín Olmedo-Juárez, Alejandro Córdova-Izquierdo, Roberto González-Garduño, José Luis Ponce-Covarrubias, Nallely Rivero-Perez, Felipe Patricio-Martínez and Huitziméngari Campos-García

Pathogens 2025, 14(11), 1170; https://doi.org/10.3390/pathogens14111170 (registering DOI) - 16 Nov 2025

Abstract

Toxoplasma gondii and Neospora caninum are intracellular protozoan parasites that cause reproductive failure and production losses in ruminants. Considering the limited information on the epidemiology of these infections in goats in different climate regions, this study aimed to estimate the seroprevalence and potential [...] Read more.

Toxoplasma gondii and Neospora caninum are intracellular protozoan parasites that cause reproductive failure and production losses in ruminants. Considering the limited information on the epidemiology of these infections in goats in different climate regions, this study aimed to estimate the seroprevalence and potential risk factors associated with parasitic infections in Mexico. Blood samples were collected from 627 goats in dry and temperate climates in two different states. The levels of T. gondii and N. caninum IgG antibodies were determined using commercially available ELISA kits. The prevalence of T. gondii in the dry and temperate climate, dry climate alone, and temperate climate alone were 52.0%, 57.1%, and 48%, respectively. The prevalence of N. caninum in the dry and temperate climate, dry climate alone, and temperate climate alone were 15.5%, 19.0%, and 12.7%, respectively. Using animal characteristics and farm management information obtained from a questionnaire and remotely sensed climate data, bivariate logistic regression analysis was performed to identify risk factors associated with parasite infections. Significant differences in the seroprevalence of T. gondii in goats were observed between sexes in the temperate climate. The history of abortion was the most significant risk factor for T. gondii in the dry climate. Factors such as goat age and history of abortion were significantly associated with high seropositivity of N. caninum in the dry climate. Sex and the presence of cats were identified as significant factors for T. gondii in regions with a dry and temperate climate. Abortion and climate regions were common risk factors for these infections in the dry and temperate climate regions. The results indicate that regionally adapted monitoring and control programmes may be developed to reduce the prevalence of these two parasites and reduce production losses in the livestock industry. Full article

(This article belongs to the Special Issue Advances in Animal Parasitic Diseases)

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24 pages, 1132 KB

Open AccessArticle

Interplay of Industrial Robots, Education, and Environmental Sustainability in United States: A Quantile-Based Investigation

by Rmzi Khalifa and Hasan Yousef Aljuhmani

Sustainability 2025, 17(22), 10255; https://doi.org/10.3390/su172210255 (registering DOI) - 16 Nov 2025

Abstract

This study explores the dynamic relationship between industrial robots, education, and environmental sustainability in the United States, emphasizing their role in reducing CO₂ emissions. The research aims to quantify how automation, human capital, and the energy transition contribute to carbon mitigation within [...] Read more.

This study explores the dynamic relationship between industrial robots, education, and environmental sustainability in the United States, emphasizing their role in reducing CO₂ emissions. The research aims to quantify how automation, human capital, and the energy transition contribute to carbon mitigation within a data-driven, AI-oriented policy framework. Quarterly data spanning 2011Q1–2024Q4 were analyzed using the advanced Quantile-on-Quantile Autoregressive Distributed Lag (QQARDL) model, which captures heterogeneous long- and short-run effects across emission distributions. Results reveal that industrial robot adoption, education, and renewable energy transition significantly reduce emissions, with the strongest effects occurring at both high- and low-emission quantiles. Economic growth and financial development also support decarbonization when complemented by green finance and innovation, while urbanization increases emissions unless aligned with compact urban design and clean energy systems. The findings imply that AI-driven industrial robotics and education jointly foster sustainability through efficiency, innovation, and awareness. Policymakers are encouraged to integrate automation strategies, renewable energy incentives, and sustainability education into climate policy. This study provides empirical evidence supporting the Resource-Based View, highlighting human capital and intelligent automation as strategic assets for achieving long-term carbon neutrality. Full article

(This article belongs to the Special Issue Applications and Advances of Artificial Intelligence for Sustainable Environment Management and Education)

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16 pages, 4601 KB

Open AccessPerspective

AI in Pediatric Spine Care: Clinical, Research, and Ethical Considerations

by Hans K. Nugraha, Adam P. Rasmussen, Kellen L. Mulford, Linjun Yang, Cody C. Wyles and A. Noelle Larson

J. Clin. Med. 2025, 14(22), 8115; https://doi.org/10.3390/jcm14228115 (registering DOI) - 16 Nov 2025

Abstract

Artificial intelligence (AI) is increasingly shaping pediatric spine care, leveraging its rapid advancements in healthcare to improve efficiency, accuracy, and disease understanding. Moreover, machine learning and deep learning excel at detecting complex patterns. This holds promise in processing spinal deformity data, with the [...] Read more.

Artificial intelligence (AI) is increasingly shaping pediatric spine care, leveraging its rapid advancements in healthcare to improve efficiency, accuracy, and disease understanding. Moreover, machine learning and deep learning excel at detecting complex patterns. This holds promise in processing spinal deformity data, with the potential to surpass traditional statistical methods in predictive accuracy. Challenges persist, however, including unclear clinical implementation guidelines, limited model transparency, and ethical concerns surrounding data privacy and bias. Small sample sizes and the need for larger, diverse datasets further complicate integration. In order to realize AI’s transformative potential in pediatric spine care, these critical obstacles must be addressed for effective and ethical clinical adoption. This review examines the role of AI through applications such as image sorting, surgical outcome prediction, forecasting of spinal curve progression, and vertebral volumetric analysis using deep reasoning. It also explores possible intraoperative contributions from AI, including robotics and optimized screw trajectory planning, and the potential of large language models in clinical practice. Full article

(This article belongs to the Topic Artificial Intelligence in Public Health: Current Trends and Future Possibilities, 2nd Edition)

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