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Recent Articles  

25 pages, 1068 KB  
Article
Explainable Cattle Identification via ArcFace Embeddings and Vision–Language Explanations
by Ahmet Saygılı
Appl. Sci. 2026, 16(18), 9076; https://doi.org/10.3390/app16189076 (registering DOI) - 12 Sep 2026
Abstract
Individual cattle identification underpins traceability, genetic management and disease surveillance in precision livestock farming. Ear tags and RFID remain the dominant practice but are subject to loss, tampering and welfare concerns, which motivates contactless biometric alternatives. Most deep learning systems used for this [...] Read more.
Individual cattle identification underpins traceability, genetic management and disease surveillance in precision livestock farming. Ear tags and RFID remain the dominant practice but are subject to loss, tampering and welfare concerns, which motivates contactless biometric alternatives. Most deep learning systems used for this task optimise recognition accuracy under a closed-set assumption, provide little quantitative evidence for their explanations, and do not separate threshold selection from final evaluation. We present an offline, explainable cattle identification framework that integrates a ConvNeXt-Tiny backbone trained with ArcFace, cosine-similarity open-set decision making, Grad-CAM attribution and a locally hosted vision–language model. We evaluate it under a protocol that separates the training, enrolment, threshold selection and test roles, so that the conditions under which each reported number holds are explicit. Of the 300 identities in a publicly available cattle face dataset, 99 are withheld from training entirely, the enrolment gallery is disjoint from the training images, and the decision threshold is selected on a development split and frozen before the test split is scored. Working from 128 × 128 pixel images, and on 343 known and 478 unknown test queries, the framework attains a Top-1 accuracy of 98.25%, a known-versus-unknown ROC-AUC of 0.9887 and a detection equal error rate of 4.59%. At the high-security operating point the false accept rate is 2.72%, and the misidentification rate is zero at every threshold examined. Confidence intervals are obtained by identity-level rather than image-level resampling, which widens the interval on the false accept rate by a factor of 2.2. An ablation over sixteen configurations retrained on the identical split shows that the muzzle-focused cropping usually assumed necessary in the literature is in fact counterproductive, and quantitative explanation metrics show that the model’s evidence is distributed across the face rather than concentrated in the muzzle region. Full article
(This article belongs to the Section Agricultural Science and Technology)
24 pages, 2093 KB  
Article
Evaluating the Combined Impacts of Anthropogenic Disturbances and Climate Change on Future Streamflow Variations in the Minjiang River Basin
by Minghao Chen, Kaijie Chen, Taihua Wang and Cong Li
Hydrology 2026, 13(9), 247; https://doi.org/10.3390/hydrology13090247 (registering DOI) - 12 Sep 2026
Abstract
Future streamflow projections are critical for water management. In this study, we coupled the Geomorphology-Based Ecohydrological Model (GBEHM) with the Physics-aware Hybrid Learning and eXtreme Gradient Boosting models to provide a preliminary assessment of streamflow variations in the Minjiang River basin (MRB) over [...] Read more.
Future streamflow projections are critical for water management. In this study, we coupled the Geomorphology-Based Ecohydrological Model (GBEHM) with the Physics-aware Hybrid Learning and eXtreme Gradient Boosting models to provide a preliminary assessment of streamflow variations in the Minjiang River basin (MRB) over the period of 2020–2099 under the emission scenarios of five CMIP6 models, using data from the 2010s as the baseline. We considered both climatic and anthropogenic influences, assuming that the current anthropogenic disturbances and river network configuration will remain unchanged. The performance of the GBEHM is acceptable, with error metrics exceeding 0.80 and 0.60 before and after the impoundment of the Zipingpu Reservoir, respectively. The cascade of data-driven models demonstrates good performance, with error metrics exceeding 0.90 over the whole simulation period. Under the influence of climate change, the decadal mean streamflow at Zipingpu station will decrease by 2.73–12.16% before 2069 and increase thereafter, while at Gaochang station, it will generally increase by 1.44–13.67% after 2020. Moreover, the decadal mean streamflow at Pengshan station will increase by 13.22–36.41% over the coming decades. However, the combined effects of anthropogenic disturbances and climate change will significantly decrease future streamflow by 61.91–112.16 m3/s on average, corresponding to a reduction of 14.08–25.51% from the baseline. We also suggest strategies to mitigate future water risks and enhance basin management in the MRB. Full article
18 pages, 2573 KB  
Article
Hyperspectral Response and Quantitative Determination of Protein in Complex Semi-Fluid Matrices: A Case Study of Highly Viscous Royal Jelly
by Fansong Zeng, Sheng Hu, Huimin Fang, Shihao Guan, Muhammad Hassan and Chao Zhao
Sustainability 2026, 18(18), 9382; https://doi.org/10.3390/su18189382 (registering DOI) - 12 Sep 2026
Abstract
Protein content is one of the most important indicators for evaluating the nutritional value and quality grade of royal jelly. To achieve rapid and non-destructive quantification of protein content in royal jelly, this study employed near-infrared hyperspectral imaging (NIR-HSI) to acquire hyperspectral images [...] Read more.
Protein content is one of the most important indicators for evaluating the nutritional value and quality grade of royal jelly. To achieve rapid and non-destructive quantification of protein content in royal jelly, this study employed near-infrared hyperspectral imaging (NIR-HSI) to acquire hyperspectral images of royal jelly samples, while the Kjeldahl method was simultaneously used as the reference method for protein determination. During data processing, seven spectral preprocessing methods—including the first derivative (1-Der), the second derivative (2-Der), Savitzky–Golay smoothing (SG), normalization (Normalize), baseline correction (Baseline), standard normal variate (SNV), and multiplicative scatter correction (MSC)—were comparatively evaluated. After outlier samples were identified and removed using the Mahalanobis distance method, Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR) models were established for quantitative prediction of protein content in royal jelly. The PLSR models consistently outperformed the PCR models in predicting protein content in royal jelly. Among all preprocessing methods, the PLSR model developed using 1-Der spectra processing exhibited the best predictive performance, with a determination coefficient of calibration set () of 0.94, a determination coefficient of cross-validation set () of 0.90, a determination coefficient of prediction set () of 0.97, and a root mean square error of prediction (RMSEP) of 0.31%. These results support the feasibility of rapid and non-destructive laboratory-scale screening of protein content in royal jelly. The proposed method circumvents the drawbacks of conventional physicochemical analyses, which are labor-intensive, time-consuming and sample-destructive, and provides a basis for rapid and non-destructive laboratory-scale screening of protein content in royal jelly. Full article
(This article belongs to the Special Issue Sustainable Agricultural Engineering Technology and Development)
20 pages, 1371 KB  
Article
An Investigative Study of Widely Used Ergonomic Risk Assessment Methods Based on Machine Learning and MCDM Approaches
by Şura Toptancı, Asli Kaya Karakutuk and Fatih Fırat
Appl. Sci. 2026, 16(18), 9075; https://doi.org/10.3390/app16189075 (registering DOI) - 12 Sep 2026
Abstract
REBA, RULA, and OWAS are widely used observational ergonomic risk assessment methods based on predefined ordinal scoring rules. The final risk scores generated by these methods play a critical role in determining and prioritizing ergonomic interventions under limited resources to reduce musculoskeletal risks [...] Read more.
REBA, RULA, and OWAS are widely used observational ergonomic risk assessment methods based on predefined ordinal scoring rules. The final risk scores generated by these methods play a critical role in determining and prioritizing ergonomic interventions under limited resources to reduce musculoskeletal risks and related losses. Because the corresponding scores are deterministic functions of their component inputs, the present study focuses on machine-learning (ML) models as surrogate-analysis tools rather than replacements for exact scoring procedures. Ordinal Logistic Regression (AT, IT, SE), Random Forest (RF), Ordinal XGBoost, and Ordinal LightGBM were evaluated on full-factorial rule-space datasets using 5 × 3 nested cross-validation, 95% confidence intervals, and Friedman tests with Nemenyi post-hoc comparisons. Local transition fidelity and controlled adjacent-category and Gaussian perturbations were additionally examined against the exact scoring rules, while Random-Forest SHAP analysis was used to characterize the fitted surrogate structures. RF provided the highest overall clean-rule-space fidelity for REBA (MAE = 0.287, QWK = 0.982), RULA (MAE = 0.011, QWK = 0.991), and OWAS (MAE = 0.244, QWK = 0.929). However, under controlled input perturbations, the exact scoring procedures generally retained lower error than the clean-trained RF surrogates, indicating that the results do not support replacing the original rules with ML. Weight-sensitivity analysis further showed that the SRP-based method ranking was conditional on criterion weights: RULA ranked first in 52.23% of 100,000 sampled weight vectors, followed by OWAS (37.43%) and REBA (10.35%). Overall, the framework provides a reproducible way to examine surrogate fidelity, local rule-space transitions, model interpretation, and the weight sensitivity of ergonomic method selection. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
29 pages, 27006 KB  
Article
Hierarchical Multi-Objective Optimization of Multi-Stage Fast-Charging Protocols Based on a Reduced-Order Electrochemical–Thermal–Aging Model
by Boru Zhou, Bo Peng, Xinran Ding, Jiarong Liang, Guodong Fan and Xi Zhang
Energies 2026, 19(18), 4325; https://doi.org/10.3390/en19184325 (registering DOI) - 12 Sep 2026
Abstract
Fast charging is critical to the wider adoption of electric vehicles, but simply increasing the charging current intensifies polarization and degradation, creating an inherent conflict between the charging speed and battery lifetime. Multi-stage charging can alleviate this conflict by redistributing the current throughout [...] Read more.
Fast charging is critical to the wider adoption of electric vehicles, but simply increasing the charging current intensifies polarization and degradation, creating an inherent conflict between the charging speed and battery lifetime. Multi-stage charging can alleviate this conflict by redistributing the current throughout charging, although its performance depends jointly on the protocol structure and stage parameters. To address this problem, this work proposes a hierarchical multi-objective optimization method that coordinates these two design levels. A reduced-order electrochemical–thermal–aging model, developed and validated using systematic degradation experiments, is employed to predict electrothermal responses and capacity loss throughout the battery lifetime. For each candidate stage number, the charging rates, switching voltages, and exit-current ratios are jointly optimized, while the resulting Pareto performance and implementation complexity are compared at the structure level. The results showed that a three-stage structure captures most of the attainable performance gains without unnecessary control complexity. Full-lifetime cycling experiments demonstrated that the representative protocols achieved different balances between charging speeds and cycle lives. The 4C-referenced protocols extended cycle lives by 25.2–35.9% with only 2.7–4.1% longer initial charging times. The 3C-referenced protocols shortened initial charging times by 5.6–8.6%, while their cycle lives remained broadly comparable to 3C CCCV, ranging from a 9.5% decrease to a 6.9% increase. Multi-level degradation analyses further associated the lifetime improvements with a slower accumulation of anode-related capacity loss and interfacial deposits, together with reduced impedance growth. Full article
(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)
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30 pages, 18614 KB  
Article
A Laser Weeding Method Based on Adaptive Safety Constraints and Priority Target Scheduling for Maize Fields
by Yuqi Zhang, Xuehai Wang, Hu Lei, Lili Fu and Yanlei Xu
Agriculture 2026, 16(18), 1961; https://doi.org/10.3390/agriculture16181961 (registering DOI) - 12 Sep 2026
Abstract
Laser weeding offers significant advantages over conventional weed control methods; however, its practical deployment in maize fields remains challenging due to dynamic target variations, imprecise weed localization, and inefficient laser execution. In this study, a closed-loop laser weeding framework was developed for maize [...] Read more.
Laser weeding offers significant advantages over conventional weed control methods; however, its practical deployment in maize fields remains challenging due to dynamic target variations, imprecise weed localization, and inefficient laser execution. In this study, a closed-loop laser weeding framework was developed for maize fields by integrating visual perception, multi-target tracking, safety-constrained decision making, and priority-based laser scheduling to achieve accurate and efficient weed treatment under dynamic field conditions. The system consists of visual perception, galvanometer control, and laser emission modules. ByteTrack was introduced to achieve stable ID assignment and continuous position feedback for weed targets, thereby reducing repeated ineffective irradiation and energy consumption. A target scheduling strategy constrained by a maize safety zone was further developed. An adaptive elliptical safety zone was constructed to screen candidate weed targets and optimize their priorities. By incorporating safety-zone modeling, galvanometer transition cost, and target urgency, the proposed strategy optimizes the laser striking sequence while reducing crop-injury risk and improving target-selection efficiency. The method was deployed on the developed platform and evaluated through field experiments under different travel speeds and illumination conditions. The results showed that the average weeding rate, maize seedling injury rate, and weed regrowth rate were 83.67%, 2.23%, and 5.23% under three travel speeds, and 82.57%, 2.63%, and 4.87% under three illumination levels, respectively. These results demonstrate that the proposed method enables stable weed tracking and efficient laser weeding while improving real-time performance, operational safety, and intelligent decision making. This study provides a deployable technical solution for precision laser weeding in field applications. Full article
(This article belongs to the Section Agricultural Technology)
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14 pages, 1039 KB  
Article
The Inferior Vena Cava Collapsibility Index as a Non-Invasive Haemodynamic Tool in Mechanically Ventilated Surgical Neonates: A Monocentric Observational Study
by Carmine Mattia, Roberta Leonardi, Chiara Distefano, Maria Grazia Scuderi, Vincenzo Di Benedetto, Martino Ruggieri, Pietro Sciacca and Pasqua Betta
Children 2026, 13(9), 1238; https://doi.org/10.3390/children13091238 (registering DOI) - 12 Sep 2026
Abstract
Background/Objectives: Hypovolaemia and hypotension in the postoperative neonatal period are life-threatening conditions difficult to diagnose with standard clinical parameters. The inferior vena cava collapsibility index (IVCCI) is a validated non-invasive tool in adults; its application in mechanically ventilated surgical neonates remains poorly [...] Read more.
Background/Objectives: Hypovolaemia and hypotension in the postoperative neonatal period are life-threatening conditions difficult to diagnose with standard clinical parameters. The inferior vena cava collapsibility index (IVCCI) is a validated non-invasive tool in adults; its application in mechanically ventilated surgical neonates remains poorly defined. This study aimed to evaluate the association of the IVCCI with echocardiographic haemodynamic indices and its changes following volume expansion in surgically treated neonates. Methods: This monocentric observational study enrolled 36 surgical neonates (mean gestational age 38.1 weeks; mean weight 2799 g) with postoperative hypovolaemia and oliguria at the UOC NICU-Neonatology, AOU Policlinico G. Rodolico–San Marco, Catania (July 2020–September 2023). All patients were on controlled invasive mechanical ventilation. The IVCCI, cardiac output (CO), stroke volume (SV), and peak Doppler velocities (Vmax) of the pulmonary artery and aorta were measured before and 4–6 h after colloid infusion (10–20 mL/kg). Results: The IVCCI decreased significantly from 44.05 ± 7.8% to 15.14 ± 4.3% (p < 0.001). MAP improved from 36.89 ± 5.12 to 55.99 ± 4.87 mmHg (p < 0.001) and pH from 7.32 ± 0.04 to 7.36 ± 0.03 (p < 0.01). The Vmax, SV, and CO of both ventricles increased significantly (all p < 0.001). Significant inverse correlations were found between the IVCCI and MAP, Vmax, CO, and SV (all p < 0.001). No correlation was found with gestational age, birth weight, or pain scores. Conclusions: The IVCCI is a feasible and clinically useful non-invasive echocardiographic parameter for haemodynamic monitoring in critically ill surgical neonates. Its significant correlation with cardiac function indices supports its potential role in the bedside assessment of suspected hypovolaemia. Larger prospective studies are warranted. Full article
(This article belongs to the Special Issue Surgical Neonates: Challenges, Innovations, and Long-Term Outcomes)
29 pages, 1183 KB  
Article
The Impact of the Digital Economy on Carbon Emissions from China’s Livestock Industry: Moderating Effects and Spatial Spillovers
by Xiaolin Wu, Yue Hu and Xinglong Yang
Agriculture 2026, 16(18), 1962; https://doi.org/10.3390/agriculture16181962 (registering DOI) - 12 Sep 2026
Abstract
In recent years, China’s Central No. 1 Document has repeatedly highlighted the need to advance agricultural digitalization and green transformation, with the aim of improving production efficiency while reducing carbon emissions. For the livestock sector, emission reduction is an essential component of achieving [...] Read more.
In recent years, China’s Central No. 1 Document has repeatedly highlighted the need to advance agricultural digitalization and green transformation, with the aim of improving production efficiency while reducing carbon emissions. For the livestock sector, emission reduction is an essential component of achieving the agricultural “dual carbon” goals, and digital transformation is becoming a functional mechanism for achieving a lower carbon footprint. Using balanced panel data, this study evaluates the development level of the digital economy and livestock-related carbon emissions, and further investigates how the former affects the latter. In addition, the paper examines whether regional economic development moderates this relationship and whether the effects extend across neighboring regions through spatial spillovers. According to the derived data: (1) During the sample period, livestock carbon emissions in China generally declined with fluctuations, although clear regional disparities remained; (2) The digital economy contributes to lower carbon emissions in livestock production; such emissions tend to be lower in regions with more advanced digital development; (3) The carbon reduction effect of the digital economy is further enhanced by regional economic development, indicating that its impact is more significant in more developed regions; (4) Spatial spillovers are also evident, as digital development in neighboring regions influences local livestock emissions. Collectively, the results highlight the importance of coordinating digitalization with low-carbon transitions in the livestock sector. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
17 pages, 1460 KB  
Article
Multidisciplinary Comfort Assessment of the Goldoni Theatre in Bagnacavallo
by Antonella Bevilacqua and Lamberto Tronchin
Appl. Sci. 2026, 16(18), 9073; https://doi.org/10.3390/app16189073 (registering DOI) - 12 Sep 2026
Abstract
Indoor environmental comfort is essential in performing arts spaces due to its influence on both audience engagement and performers’ experience during live events. This paper primarily investigates the acoustic response of the Goldoni Theatre, with an additional assessment of its thermo-hygrometric and lighting [...] Read more.
Indoor environmental comfort is essential in performing arts spaces due to its influence on both audience engagement and performers’ experience during live events. This paper primarily investigates the acoustic response of the Goldoni Theatre, with an additional assessment of its thermo-hygrometric and lighting conditions across audience areas. Acoustic measurements were conducted under unoccupied conditions to evaluate the sound field in accordance with standard requirements. The results indicate favourable listening conditions for both music and speech. Complementary surveys were carried out during the summer season to assess thermal comfort while the HVAC system was not in operation, as well as illuminance levels. The findings show that air temperature falls within the optimal comfort range when unconditioned, fluctuating between 24.6 °C and 26.2 °C, whereas illuminance levels remain below the recommended lower limit, specifically between 156 and 190 lux. Overall, this study provides an acoustically focused evaluation of the theatre in Bagnacavallo, complemented by an assessment of its thermal and lighting conditions, which reflects the candlelight practices as typical of similar historical opera houses. Full article
32 pages, 509 KB  
Article
Evaluating Large Language Models for Symbolic Security Protocol Analysis
by Paolo Modesti, Syed Ahmed, Ioannis Sfyrakis and Derek Enodolomwanyi
Electronics 2026, 15(18), 4141; https://doi.org/10.3390/electronics15184141 (registering DOI) - 12 Sep 2026
Abstract
Security protocols verification relies on formal tools such as ProVerif and OFMC. This study
evaluates whether large language models (LLMs) can perform comparable analysis. We
test GPT and DeepSeek in chat and reasoning modes over three runs on 130 obfuscated
AnB/AnBx protocols covering [...] Read more.
Security protocols verification relies on formal tools such as ProVerif and OFMC. This study
evaluates whether large language models (LLMs) can perform comparable analysis. We
test GPT and DeepSeek in chat and reasoning modes over three runs on 130 obfuscated
AnB/AnBx protocols covering 388 security goals, scored against ProVerif and OFMC. Each
provider uses a single model in both modes, switching reasoning on and off, so both
contrasts isolate reasoning itself. Chat models achieve 72.7% recall at 27.3% precision for
GPT and 69.3% recall at 27.2% precision for DeepSeek. Reasoning models reverse this
trade-off, reaching 66.5% precision and 54.5% recall for GPT and 45.4% precision and
57.3% recall for DeepSeek. Enabling reasoning lifts precision from 27.3% to 64.8% for
GPT and from 27.2% to 44.4% for DeepSeek on the consolidated verdict. The goal set
is imbalanced, with 89 vulnerable goals against 299 secure ones; a trivial always-secure
predictor scores 77.1% accuracy, which only GPT reasoning exceeds. All models perform
worst on authentication goals: reasoning models detect well under half of injective and
non-injective agreement attacks, whereas chat models over-flag them at low precision.
Confidentiality is the exception, with F1 up to 95.7% in reasoning mode. Verdicts are
unstable across runs: identical on 89.7% of goals for GPT reasoning, 74.0% for DeepSeek
reasoning, 70.1% for GPT chat, and 61.6% for DeepSeek chat. Self-reported confidence
is uniformly high yet shows no meaningful correlation with correctness. All results rest
on a single zero-shot prompt and two model providers, which limits generalisability.
On this benchmark, LLMs do not match formal verification, but may serve, at best, as
pre-screening filters. Full article
(This article belongs to the Special Issue Machine Learning Applications and Cybersecurity)
13 pages, 769 KB  
Article
Ultrasound-Guided Botulinum Toxin Type A Infiltration for Post-Surgical Parotid Sialocele: A Case Series
by Gianmaria Mancini, Alessia Maria Romeo, Alessandro Calvo, Antonio Bottari, Alberto Stagno, Enrico Nastro Siniscalchi and Giorgio Lo Giudice
Appl. Sci. 2026, 16(18), 9074; https://doi.org/10.3390/app16189074 (registering DOI) - 12 Sep 2026
Abstract
Parotid sialocele is a challenging complication following major salivary gland surgery. Traditional conservative management often fails, while revision surgery carries a high risk of iatrogenic facial nerve injury. This retrospective, single-center case series evaluated the clinical efficacy and safety of ultrasound-guided Botulinum Toxin [...] Read more.
Parotid sialocele is a challenging complication following major salivary gland surgery. Traditional conservative management often fails, while revision surgery carries a high risk of iatrogenic facial nerve injury. This retrospective, single-center case series evaluated the clinical efficacy and safety of ultrasound-guided Botulinum Toxin Type A (BoNT-A) infiltration in eight consecutive patients presenting with post-surgical parotid sialoceles. The protocol comprised complete ultrasound-guided evacuative aspiration followed by intraglandular injections of OnabotulinumtoxinA into functional parenchyma using a standardized grid mapping technique. Dosage was individualized based on the sonographic estimation of the residual volume of glandular tissue. Post-procedure care included a soft diet, temporary avoidance of sialagogues, and strict avoidance of local massage for 24 h. Complete clinical and sonographic resolution was achieved in all 8 treated cases within a mean interval of 10 days post-injection. Follow-up at 3 months confirmed no recurrences or late-onset complications. No local or systemic adverse events were recorded. In this preliminary case series, ultrasound-guided intraglandular BoNT-A injection represented a safe and encouraging minimally invasive second-line option for post-surgical parotid sialoceles. Full article
(This article belongs to the Special Issue Advanced Technologies in Oral Surgery—2nd Edition)
60 pages, 4354 KB  
Review
Understanding Polycaprolactone Degradation: Molecular Mechanisms and Implications for Biomedical Device Design
by Paulina Dziemiańczyk, Dawid Łysik, Francois Vernay and Joanna Mystkowska
Materials 2026, 19(18), 3894; https://doi.org/10.3390/ma19183894 (registering DOI) - 12 Sep 2026
Abstract
Polycaprolactone (PCL) is a widely used biodegradable polyester in tissue engineering, drug delivery, and temporary implant design. While its favorable processability, biocompatibility, and low melting temperature are highly advantageous, its slow and condition-dependent degradation remains a major limitation for precise temporal control in [...] Read more.
Polycaprolactone (PCL) is a widely used biodegradable polyester in tissue engineering, drug delivery, and temporary implant design. While its favorable processability, biocompatibility, and low melting temperature are highly advantageous, its slow and condition-dependent degradation remains a major limitation for precise temporal control in biomedical applications. Despite extensive literature on PCL, a critical knowledge gap remains in linking fundamental molecular chain scission directly to macroscopic structural evolution, mechanical failure, and predictable in vivo device performance. To address this, this review provides a comprehensive synthesis of PCL degradation mechanisms, with a particular emphasis on PCL-bioceramic composites designed for hard tissue engineering. We elucidate the progressive degradation pathway—distinguishing between initial hydrolytic chain scission, oligomer formation, the generation of low-molecular-weight degradation products, and their subsequent metabolic fate under physiological conditions. Furthermore, this review critically evaluates how fundamental variables—specifically molecular weight, crystallinity, bioceramic fillers, device geometry, and physiological environments—alter degradation kinetics. By connecting molecular weight reduction to subsequent mass loss, thermal behavior, and mechanical deterioration, we establish a framework for understanding how structural reorganization and crystallinity evolution govern material failure. This review bridges the gap between simplified in vitro models and complex in vivo realities, supporting the rational design of composite biomedical devices with tailored, predictable resorption profiles. Full article
(This article belongs to the Special Issue Biomaterials for Regenerative Medicine: Synthesis, Characterization and Application)
16 pages, 1011 KB  
Article
Receptor Structure Shapes Host Range but Incompletely Predicts High Activity in Klebsiella pneumoniae Phage Cocktails
by Roman B. Gorodnichev, Anastasiia O. Krivulia, Maryam O. Sidorskaia, Maria A. Kornienko, Narina K. Abdraimova, Maja V. Malakhova, Marina V. Zaychikova, Dmitry A. Bespiatykh and Egor A. Shitikov
Antibiotics 2026, 15(9), 900; https://doi.org/10.3390/antibiotics15090900 (registering DOI) - 12 Sep 2026
Abstract
Background. Rational design of phage cocktails typically relies on the lytic spectrum. However, susceptibility criteria vary widely among studies, ranging from qualitative lysis in spot tests to quantitative endpoints based on serial-dilution titration or efficiency of plating. Methods. We investigated this discrepancy using [...] Read more.
Background. Rational design of phage cocktails typically relies on the lytic spectrum. However, susceptibility criteria vary widely among studies, ranging from qualitative lysis in spot tests to quantitative endpoints based on serial-dilution titration or efficiency of plating. Methods. We investigated this discrepancy using four commercial phage cocktails and two capsule-specific monophages against a clinically representative collection of 448 Klebsiella pneumoniae isolates comprising 56 capsule types, collected in 2018–2025 from 12 medical centers. Using a modified Gratia titration assay, we defined host range (HR) as specific lysis at any dilution and putative therapeutic applicability (PTA) as lysis at dilutions corresponding to ≥106 plaque-forming units per mL. Results. We identified a systematic discrepancy between these two measures of cocktail efficacy. HR coverage reached 64%, whereas PTA was significantly lower, with a median HR–PTA difference of 36%. This discrepancy persisted for capsule-specific monophages tested against KL2 isolates (n = 69), indicating that neither nominal capsule matching nor low component titres fully explained the loss of activity. This pattern provides indirect functional evidence that post-adsorption barriers contribute to the HR–PTA discrepancy, although adsorption and intracellular antiphage mechanisms were not assessed directly. Capsule type was the principal and most robust predictor of efficacy, whereas spatiotemporal factors, including year and medical centre, had only a weak effect on PTA. Conclusions. Capsule matching can therefore help estimate population-level coverage but does not fully predict high-titre activity. Phage selection should incorporate serial-dilution testing rather than rely on spot-test lysis alone. Cocktail design should account for both receptor coverage and functional activity against representative isolates within individual capsule types. Full article
(This article belongs to the Special Issue Bacteriophage Therapy: A Renaissance Weapon—Recent Developments and Application, 3rd Edition)
19 pages, 862 KB  
Article
Optimizing Rooftop Utilization for Sustainable Energy Systems: An LCA-Based Comparison of PV, PVT, and Solar Thermal Technologies
by Justyna Gołębiowska and Agnieszka Żelazna
Sustainability 2026, 18(18), 9381; https://doi.org/10.3390/su18189381 (registering DOI) - 12 Sep 2026
Abstract
This study addresses the role of solar energy technologies in supporting sustainable and low-carbon residential energy systems through a comparative assessment of selected system configurations for a single-family house located in Lublin, Poland: photovoltaic–thermal (PVT) collectors, a hybrid system combining photovoltaic (PV) panels [...] Read more.
This study addresses the role of solar energy technologies in supporting sustainable and low-carbon residential energy systems through a comparative assessment of selected system configurations for a single-family house located in Lublin, Poland: photovoltaic–thermal (PVT) collectors, a hybrid system combining photovoltaic (PV) panels and solar thermal (ST) collectors, and a standalone PV installation. The analysis was carried out under the primary assumption of limited rooftop area available for renewable energy systems. The operational performance of each configuration was simulated using POLYSUN v. 2025.1 software, while the environmental impacts over a 25-year lifetime were evaluated using life cycle assessment (LCA) in SimaPro v. 10.3.0.1, including IPCC 2021 Global Warming Potential (GWP100) and ReCiPe 2016 Endpoint indicators. The results indicate that the PV + ST configuration achieved the best energy and environmental performance, providing the highest solar contribution (57.8%), the lowest total energy consumption (5136 kWh/year), and the lowest environmental impacts in both impact assessment methods (64.3 tCO2 eq. and 3487 Pt). Under the adopted design assumptions, the PVT system exhibited intermediate overall performance between the PV + ST and standalone PV systems. The study demonstrates that combining energy performance analysis with LCA provides a more comprehensive basis for selecting sustainable solar technologies for low-carbon residential buildings than energy indicators alone. Full article
(This article belongs to the Special Issue Innovative and Smart Renewable Energy Technologies for Developing Low-Carbon and Sustainable Societies)
33 pages, 12505 KB  
Article
Age-Differentiated Accessibility and Spatial Equity of Urban Fitness Facilities: Implications for Socially Sustainable Neighbourhood Planning in Central Harbin, China
by Muyu Sun, Ying Pang and Jun Zhang
Sustainability 2026, 18(18), 9380; https://doi.org/10.3390/su18189380 (registering DOI) - 12 Sep 2026
Abstract
Equitable access to health-promoting public services is an important component of socially sustainable urban development, yet fitness-facility accessibility is often assessed under homogeneous demand assumptions. This study develops an age-differentiated framework for central Harbin, China, integrating 100 m age-stratified population data, facility functional [...] Read more.
Equitable access to health-promoting public services is an important component of socially sustainable urban development, yet fitness-facility accessibility is often assessed under homogeneous demand assumptions. This study develops an age-differentiated framework for central Harbin, China, integrating 100 m age-stratified population data, facility functional area, pedestrian-network travel costs, and physical-activity participation rates within an MGH-3SFCA model. Accessibility was evaluated for four age groups at 15 min, with shorter-threshold comparisons, population exposure analysis, bivariate LISA, and sensitivity tests. Adults and students generally formed the relatively higher-accessibility pair, whereas children and seniors remained more disadvantaged. More than 91% of each age group was located in zero, very low, or low accessibility classes. High-intensity ball-sports facilities were dominated by geographic non-coverage, while resistance-training facilities were more widely reachable but mostly at very low levels. The adult–senior zero-accessibility population gap widened from 3.52 percentage points at 15 min to 13.66 at 5 min. High–Low clusters occupied only 5.90–7.39% of land grids but contained 11.77–13.25% of corresponding populations. Broad spatial patterns were stable to alternative composite weighting, while some age contrasts were specification-dependent. The framework supports age-responsive and socially sustainable neighbourhood planning by distinguishing spatial coverage, population exposure, and potential local mismatch. Full article
34 pages, 473 KB  
Article
Sustainable Career Readiness in the GenAI Era: Student Perceptions of Automation, Entry-Level Employment, and Pedagogical Support
by Vasso Stylianou, Despo Ktoridou, Andreas Savva, Epaminondas Epaminonda and Maria Michailidis
Sustainability 2026, 18(18), 9379; https://doi.org/10.3390/su18189379 (registering DOI) - 12 Sep 2026
Abstract
Generative artificial intelligence (GenAI) is reshaping higher education and early-career work, raising questions about how universities can support pedagogically sustainable career readiness. This study examines undergraduate students’ perceptions of AI, automation, entry-level employment, and perceived preparedness for an AI-augmented labor market. Survey data [...] Read more.
Generative artificial intelligence (GenAI) is reshaping higher education and early-career work, raising questions about how universities can support pedagogically sustainable career readiness. This study examines undergraduate students’ perceptions of AI, automation, entry-level employment, and perceived preparedness for an AI-augmented labor market. Survey data were collected from 153 undergraduate students. The questionnaire examined awareness of AI and automation, perceived risks to traditional entry-level work, anxiety and perceived preparedness regarding post-graduation employment, skill priorities, and desired institutional support. The findings indicate substantial awareness of AI-related change, with many students expecting routine junior tasks such as data entry, basic research, report generation, customer support, and simple coding-related work to be affected. However, confidence in academic preparation was weaker and more uncertain. Students emphasized human-centered capabilities, including critical thinking, creativity, communication, and problem solving, alongside AI literacy and practical exposure to digital tools. The study identifies an awareness-preparedness gap and argues that higher education institutions should strengthen GenAI-era curriculum design, AI-authentic assessment, experiential learning, career guidance, and ethical AI literacy to support perceived preparedness and sustainable career readiness. Full article
(This article belongs to the Special Issue Generative AI and the Future of Pedagogical Sustainability: Balancing Creative Innovation with Ethical Fairness)
28 pages, 2322 KB  
Article
UX Design Guidelines for Teaching Procedural Knowledge in Educational VR: Medium-Specific Message Design Strategies, Learning Effects, and Consistent Improvement Across Learners
by Yurim Oh and Jungjo Na
Appl. Sci. 2026, 16(18), 9072; https://doi.org/10.3390/app16189072 (registering DOI) - 12 Sep 2026
Abstract
Research on educational virtual reality (VR) has focused on learning outcomes, but less on the design strategies that create those outcomes or whether benefits are consistent across different learners. This study created user experience (UX) design guidelines for educational VR by analyzing strategies [...] Read more.
Research on educational virtual reality (VR) has focused on learning outcomes, but less on the design strategies that create those outcomes or whether benefits are consistent across different learners. This study created user experience (UX) design guidelines for educational VR by analyzing strategies from print, video, and digital media, then adapting their functions for immersive VR. A two-dimensional framework combined five instructional functions from Gagné’s events of instruction and Merrill’s four content types. Guided by cognitive load theory and multimedia learning theory, five guidelines were developed: Space-Centered Stimulus Presentation, Environment-Intrinsic Context Learning Guidance, Body-Tracking-Based Direct Performance Induction, Integrated Structural Real-Time Feedback, and Multi-Scenario Retention and Transfer Training. A CPR prototype focused on compression-only resuscitation was tested with 40 adults in experimental and comparison groups. The experimental group showed significantly larger gains in knowledge (r = 0.704, large), performance (r = 0.395, medium), and usability (r = 0.385, medium). An exploratory analysis found that all experimental participants improved, compared to 45% and 75% in the comparison group (Fisher’s exact p < 0.001 and p = 0.047). Semi-structured interviews with 22 participants revealed that both groups experienced hand-tracking errors; however, the comparison group also reported issues such as feedback separation, redundant presentation, and unclear flow, causing extraneous cognitive load, whereas the experimental group cited the spatially integrated guidance (heart character, sternum display) as beneficial for learning. These results suggest that VR design guided by these guidelines can lead to greater and more consistent learning improvements among users. Full article
(This article belongs to the Special Issue Extended Reality (XR) and User Experience (UX) Technologies)
32 pages, 775 KB  
Article
Retrieval-Guided Transfer Learning for Low-Resource Ebola Drug–Target Affinity Prediction
by Mubarakah Alotaibi and Nada Al Taweraqi
Int. J. Mol. Sci. 2026, 27(18), 8147; https://doi.org/10.3390/ijms27188147 (registering DOI) - 12 Sep 2026
Abstract
Drug–target affinity (DTA) prediction plays an important role in computational drug discovery; however, its application to emerging infectious diseases such as Ebola remains challenging because of the limited availability of experimentally measured affinity data. To address this low-resource setting, we propose a retrieval-guided [...] Read more.
Drug–target affinity (DTA) prediction plays an important role in computational drug discovery; however, its application to emerging infectious diseases such as Ebola remains challenging because of the limited availability of experimentally measured affinity data. To address this low-resource setting, we propose a retrieval-guided transfer-learning framework that leverages BindingDB interactions to improve Ebola DTA prediction. The framework uses a two-stage strategy. In Stage I, source interactions are selected using random sampling, compound-similarity retrieval, protein-similarity retrieval, or hybrid compound–protein retrieval at source-data budgets of 50,000 and 300,000 interactions and combined with Ebola training data to learn transferable representations. In Stage II, the pretrained compound and protein encoders are frozen, while the prediction layers are adapted to the Ebola domain. The framework was implemented with DeepDTA and GraphDTA and evaluated across five random seeds using a scaffold-based split, with conventional machine-learning models and single-stage deep learning as baselines. The best overall configuration, GraphDTA with protein-similarity-guided retrieval at the 50,000-interaction budget, achieved RMSE =0.5498±0.1073, R2=0.8809±0.0452, and Pearson =0.9395±0.0237, outperforming the strongest conventional machine-learning model (Extra Trees, RMSE =0.6065±0.0642) and single-stage GraphDTA (RMSE =0.6533±0.0752). Across both source-data budgets and both DTA backbones, all targeted retrieval configurations achieved lower mean RMSE than their corresponding random-retrieval configurations. At the 50,000-interaction budget, matched seed-wise analysis further showed consistent improvements for protein-guided retrieval across all five seeds for both backbones. Retrieval characterization showed stronger target-domain similarity and substantially lower cross-strategy overlap at 50,000 than at 300,000 interactions, while post hoc sequence analysis independently confirmed enrichment of sequence-level relatedness with protein-guided retrieval. Increasing the source-data budget from 50,000 to 300,000 did not uniformly improve predictive performance, indicating that source-data relevance and retrieval selectivity should be considered jointly with source-data quantity. Finally, virtual-screening and approved-drug repurposing case studies across six Ebola virus targets demonstrate the use of the framework for computational prioritization of compound–target hypotheses. Overall, the findings support relevance-guided source-data selection as an effective strategy for transfer learning in low-resource DTA prediction. Full article
(This article belongs to the Section Molecular Pharmacology)
21 pages, 11315 KB  
Article
Point Localization and Pose Estimation Based on RGB-D and HSN-YOLOv8n-seg Model for Marigold Harvesting
by Baojian Ma, Yinghui Xia and Bangbang Chen
Horticulturae 2026, 12(9), 1156; https://doi.org/10.3390/horticulturae12091156 (registering DOI) - 12 Sep 2026
Abstract
Accurate picking-point localization and pose estimation are essential for selective robotic harvesting of marigolds, yet side-view imaging suffers from slender pedicel morphology, frequent occlusions, and weak visual contrast at the corolla–pedicel junction. This study aims to deliver a reliable perception framework that outputs [...] Read more.
Accurate picking-point localization and pose estimation are essential for selective robotic harvesting of marigolds, yet side-view imaging suffers from slender pedicel morphology, frequent occlusions, and weak visual contrast at the corolla–pedicel junction. This study aims to deliver a reliable perception framework that outputs both the 3D picking-point coordinates and the corresponding grasping pose angle for each harvestable flower. To achieve this, we propose an RGB-D based pipeline that integrates depth-assisted foreground extraction, a lightweight instance segmentation model, a dual-strategy corolla–pedicel association module, and geometric pose estimation. To improve pedicel segmentation under weak-boundary and occlusion conditions, an enhanced lightweight model, HSN-YOLOv8n-seg, was developed by incorporating Haar wavelet downsampling to preserve fine-grained texture features, Spatial Group-wise Enhancement to strengthen responses in ambiguous regions, and a lightweight segmentation head to improve mask boundary delineation. The model achieved a Precision of 78.53% and an mAP50 (mean Average Precision at IoU threshold 0.5) of 75.43%, with only 3.17 M parameters and an inference time of 9.42 ms, outperforming representative lightweight segmentation models such as YOLOv9t and YOLOv11n. The framework computes the pedicel centroid as the candidate picking point and pairs it with the corresponding corolla centroid via distance priority matching and cross-line verification; the axis connecting the paired centroids defines the picking pose. Outdoor experiments showed that the largest group-wise mean localization error was 0.0095 m (individual sample maximum: 0.0107 m), and the largest group-wise mean pose angle error was 5.11° (individual sample maximum: 14.14°). Overall, the framework consistently maintains reliable perception under occlusion and indistinct corolla–pedicel boundaries, demonstrating its potential for automated marigold harvesting. Nevertheless, further validation under diverse and complex field backgrounds is necessary before practical deployment. Full article
(This article belongs to the Section Floriculture, Nursery and Landscape, and Turf)
26 pages, 10612 KB  
Article
Comparison of EDGAR, ODIAC, and MEIC Grid CO2 Emission Inventories: Historical and Current Versions
by Chunlin Jin, Xingxing Jiang and Youmei Han
Remote Sens. 2026, 18(18), 3144; https://doi.org/10.3390/rs18183144 (registering DOI) - 12 Sep 2026
Abstract
High-resolution gridded CO2 emission inventories underpin carbon cycle research and facilitate bridging global and national climate mitigation targets with regional emission assessments and site-specific mitigation actions. Major datasets including ODIAC, EDGAR, MEIC-global and MEIC-China adopt inconsistent spatial proxies and accounting frameworks, causing [...] Read more.
High-resolution gridded CO2 emission inventories underpin carbon cycle research and facilitate bridging global and national climate mitigation targets with regional emission assessments and site-specific mitigation actions. Major datasets including ODIAC, EDGAR, MEIC-global and MEIC-China adopt inconsistent spatial proxies and accounting frameworks, causing notable discrepancies. This study compares historical and latest versions at the global, top five emitting national, and grid scales, analyzing cross-version/inter-inventory variations and grid scale effects. The results reveal global total emission deviations of only 7.97% and 2.03%, yet pronounced regional heterogeneity. Maximum discrepancies reach 17.58% in Russia and 44.68% in Japan; grid-scale deviations over 50% exceed 35%. Post-v2022 ODIAC and post-v8.0 EDGAR have reduced version uncertainty, whereas MEIC-China shows large inter-version differences of 14.52% and 17.88% from long update cycles. Grid scale exerts nonlinear impacts on discrepancies, with the most pronounced transitions observed around 2°: discrepancies tend to amplify at resolutions finer than 2°, whereas discrepancies gradually diminish and appear to stabilize at resolutions coarser than 2°. This work clarifies core inventory characteristics, informing data selection, fusion and precision carbon management. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
17 pages, 4866 KB  
Article
Low-Temperature Thermomechanical Consolidation of Aluminosilicate Sorbents Impregnated with Model Oil-Containing Radioactive Waste
by Yerbolat Koyanbayev, Viktor Baklanov, Nuriya Mukhamedova, Arman Miniyazov, Igor Sokolov, Dilyara Belgibayeva, Ospan Oken, Aisara Sabyrtayeva and Anel Raiko
Materials 2026, 19(18), 3893; https://doi.org/10.3390/ma19183893 (registering DOI) - 12 Sep 2026
Abstract
This paper investigates the possibility of pressure-assisted thermomechanical consolidation and thermal treatment without applied pressure during the low-temperature consolidation of oil-saturated aluminosilicate sorbents for their subsequent application in the conditioning of liquid oil-containing radioactive waste (RAW). The Premium and Absorbent sorbents saturated with [...] Read more.
This paper investigates the possibility of pressure-assisted thermomechanical consolidation and thermal treatment without applied pressure during the low-temperature consolidation of oil-saturated aluminosilicate sorbents for their subsequent application in the conditioning of liquid oil-containing radioactive waste (RAW). The Premium and Absorbent sorbents saturated with transformer oil not containing radionuclides were used as model RAW systems. It was established that pressure-assisted thermomechanical consolidation leads to the formation of a denser structure and a reduction in hydrocarbon-phase losses compared with thermal treatment without applied pressure. For Premium, mass losses decreased from 0.74 to 0.35 g (by 53%), and for Absorbent, from 0.75 to 0.47 g (by 37%), and the consolidated samples were characterized by a more homogeneous microstructure and increased resistance to exudation. It was established that the efficiency of hydrocarbon-phase retention is determined by both the treatment conditions and the mineral composition of the sorbent. The obtained results indicate the prospects of low-temperature pressure-assisted thermomechanical consolidation at a temperature of 150 °C, a pressure of 1.5 MPa, and a holding time of 20 s for the conditioning of oil-containing RAW without the use of additional binding components. Full article
(This article belongs to the Section Materials Chemistry)
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28 pages, 1151 KB  
Review
Engineering the Cellular Microenvironment for Human Induced Pluripotent Stem Cell Cardiac Differentiation: Beyond Wnt Signaling
by Gustavo Rosero, Ana Belén Peñaherrera-Pazmiño and Camilo Pérez-Sosa
Bioengineering 2026, 13(9), 1062; https://doi.org/10.3390/bioengineering13091062 (registering DOI) - 12 Sep 2026
Abstract
Human induced pluripotent stem cells (hiPSCs) have revolutionized cardiovascular research by providing a renewable source of patient-specific cardiomyocytes for disease modeling, drug discovery, precision medicine, and regenerative therapies. Temporal modulation of canonical Wnt/β-catenin signaling has established the current gold standard for efficient and [...] Read more.
Human induced pluripotent stem cells (hiPSCs) have revolutionized cardiovascular research by providing a renewable source of patient-specific cardiomyocytes for disease modeling, drug discovery, precision medicine, and regenerative therapies. Temporal modulation of canonical Wnt/β-catenin signaling has established the current gold standard for efficient and reproducible cardiac differentiation under chemically defined conditions. However, conventional Wnt-based protocols consistently generate cardiomyocytes with fetal-like structural, electrophysiological, metabolic, and contractile characteristics, highlighting that lineage specification alone is insufficient to achieve functional maturation. This review discusses recent advances in engineering the cardiac developmental niche by integrating extracellular matrix remodeling, biomaterials, biomechanical and bioelectrical stimulation, metabolic regulation, multicellular interactions, and microfluidic technologies to better recapitulate the dynamic microenvironment of human cardiogenesis. We further examine how emerging bioengineered platforms, including engineered heart tissues, cardiac organoids, and heart-on-chip systems, enhance the physiological relevance of hiPSC-derived cardiac models. Finally, we discuss future perspectives arising from the convergence of developmental biology, tissue engineering, biomaterials, artificial intelligence, and microphysiological systems, proposing that the next generation of cardiac differentiation platforms will depend on integrating canonical Wnt signaling within biomimetic developmental microenvironments to generate mature human cardiac tissues with enhanced translational potential. By advancing physiologically relevant human cardiac models for disease modeling, drug discovery, and regenerative medicine, this work also supports the research and innovation priorities underlying Sustainable Development Goal 3 (SDG 3), particularly those related to reducing the burden of non-communicable diseases and strengthening health-related research and development. Full article
(This article belongs to the Special Issue Engineering Stem Cells and Their Derivatives for Wound Healing and Tissue Regeneration)
11 pages, 360 KB  
Article
Long-Term Clinical and Radiological Outcomes of Cementless Total Knee Arthroplasty in Patients with Rheumatoid Arthritis
by Filippo Calanna, Silvia De Martinis, Leonardo Clausetti, Alessia Invernizzi, Luca Tanel, Roberto Viganò, Alessandra Menon, Alessio Maione, Riccardo Compagnoni, Paolo Ferrua and Pietro S. Randelli
J. Clin. Med. 2026, 15(18), 7091; https://doi.org/10.3390/jcm15187091 (registering DOI) - 12 Sep 2026
Abstract
Background: Total knee arthroplasty (TKA) is an established treatment for end-stage rheumatoid arthritis (RA). Although cemented fixation has traditionally been preferred because of concerns regarding poor bone quality, advances in implant design and osseointegration have renewed interest in cementless fixation. This study evaluated [...] Read more.
Background: Total knee arthroplasty (TKA) is an established treatment for end-stage rheumatoid arthritis (RA). Although cemented fixation has traditionally been preferred because of concerns regarding poor bone quality, advances in implant design and osseointegration have renewed interest in cementless fixation. This study evaluated the long-term clinical and radiological outcomes of cementless TKA in patients with RA. Methods: A retrospective single-center study included adult patients with RA who underwent primary cementless TKA between 2004 and 2021 using the same cruciate retaining implant. Clinical outcomes were assessed using range of motion (ROM), Visual Analog Scale (VAS), Oxford Knee Score (OKS), and patient satisfaction. Radiographic evaluation assessed implant fixation, while implant survivorship was analyzed using bilateral clustering via a Marginal Cox model analysis. Results: Seventy-five cementless TKAs performed in 52 patients were analyzed after a mean clinical follow-up of 10.8 ± 3.8 years. Mean ROM was 101° ± 26.5°, mean VAS score was 0.88 ± 1.84, and mean OKS was 40.3 ± 7.1. Overall, patients were satisfied or very satisfied in 89.6% of implants. Radiographic assessment showed no evidence of progressive radiolucent lines, osteolysis, implant subsidence, aseptic loosening, or malalignment. Only one revision was required because of periprosthetic joint infection, resulting in an implant survivorship of 98.3% at long-term follow-up. Conclusions: Cementless TKA demonstrated excellent long-term implant survival, durable radiographic fixation, and favorable clinical and functional outcomes in patients with rheumatoid arthritis. These findings support modern cementless fixation as a reliable and effective alternative to cemented TKA in carefully selected RA patients. Full article
(This article belongs to the Special Issue Knee Arthroplasty: Recent Advances and Future Challenges)
13 pages, 543 KB  
Article
Genetic Testing Abnormalities in Children with Autism Spectrum Disorder: Prevalence, Patterns, and Clinical Associations
by Viswabhaskar Susarla, Mariah George, Ananthi Rathinam and Danish Bhatti
Neurol. Int. 2026, 18(9), 172; https://doi.org/10.3390/neurolint18090172 (registering DOI) - 12 Sep 2026
Abstract
Background: Genetic testing in autism spectrum disorder (ASD) can reveal a wide range of chromosomal and sequence-level abnormalities, yet large real-world neurology cohorts rarely report the full spectrum of findings alongside clinical correlates and patterns of testing. We characterized genetic findings in an [...] Read more.
Background: Genetic testing in autism spectrum disorder (ASD) can reveal a wide range of chromosomal and sequence-level abnormalities, yet large real-world neurology cohorts rarely report the full spectrum of findings alongside clinical correlates and patterns of testing. We characterized genetic findings in an 1884-patient ASD cohort and examined factors associated with both abnormal findings and the use of genetic testing. Methods: This retrospective cross-sectional study included 1884 patients. Genetic testing was performed in 1011 patients; the primary outcome was an abnormal versus normal genetic result among those tested. All 371 abnormal findings were catalogued in a de-identified supplement. The primary multivariable model included age, sex, seizure history, and EEG abnormality ( N = 901); an MRI-inclusive sensitivity model used 422 complete cases, and a separate full-cohort model evaluated factors associated with genetic testing. Results: Abnormal genetic findings were documented in 371/1011 tested patients (36.7%, 95% CI 33.7–39.8%). In the primary model, female sex (aOR 1.483, 95% CI 1.089–2.018; p = 0.012) and seizure history (aOR 1.634, 95% CI 1.136–2.352; p = 0.008) were independently associated with abnormal findings, whereas EEG abnormality was not significant after adjustment (aOR 1.373, p = 0.084). In the MRI-inclusive sensitivity model, female sex and seizure history remained significant, while MRI abnormality was not independently associated (aOR 1.235, p = 0.302). Genetic testing was more common among patients who also underwent EEG or MRI (both p < 0.001). Conclusions: More than one-third of tested patients had an abnormal genetic finding, spanning a broad range of copy-number, sequence, homozygosity, Fragile X-related, chromosomal, and syndromic findings. Seizure history and female sex were the principal adjusted correlates of abnormal findings. Genetic testing clustered with EEG and MRI use, reflecting observed patterns of neurological work-up within this cohort rather than temporal or causal relationships. Full article
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31 pages, 5453 KB  
Article
IBT-PPO: A Dual-Stage Intelligent Forecasting and Reinforcement Learning Framework for Optimal Scheduling in Hybrid Renewable Energy Systems
by Hammad Alnuman, Ghulam Abbas and Paolo Mercorelli
Energies 2026, 19(18), 4324; https://doi.org/10.3390/en19184324 (registering DOI) - 12 Sep 2026
Abstract
In this work, Intelligent Bidirectional Long Short-Term Memory with Temporal Fusion Transformer-based prediction and Proximal Policy Optimization (IBT-PPO) is proposed in response to the challenges of uncertain renewable generation, fluctuating demand, and inefficient energy scheduling in hybrid renewable energy systems. The algorithm is [...] Read more.
In this work, Intelligent Bidirectional Long Short-Term Memory with Temporal Fusion Transformer-based prediction and Proximal Policy Optimization (IBT-PPO) is proposed in response to the challenges of uncertain renewable generation, fluctuating demand, and inefficient energy scheduling in hybrid renewable energy systems. The algorithm is based on a dual-stage framework that integrates machine learning forecasting with reinforcement learning-based planning. Initially, a hybrid Bi-LSTM-TFT model is employed to generate accurate short-term forecasts of wind power, solar power, and demand, which employs temporal dependencies and multi-horizon patterns. After that, the PPO strategy is designed to optimize scheduling decisions, adaptively balancing battery usage, grid reliance, and renewable dispatch. To enhance robustness, adaptive feature weighting and temporal gating strategies are incorporated, ensuring stable convergence and reduced planning redundancy. Subsequently, the energy allocation is refined through iterative learning to minimize operational cost and maximize renewable penetration. The proposed framework is evaluated as an offline/post hoc forecasting and scheduling approach, with the Bi-LSTM–TFT module exploiting historical temporal representations and the PPO agent optimizing energy-management decisions based on the resulting forecasts. The experimental evaluation is carried out using the Open Power System Data (OPSD) dataset, which provides realistic time-series data for wind, solar, demand, and electricity prices. Thus, the IBT-PPO system integrates multi-horizon probabilistic forecasting and adaptive feature weighting for better prediction and planning accuracy and achieves a 24.1% cost reduction and 95.5% renewable utilization, thereby advancing efficient and intelligent energy prediction and planning. Full article
(This article belongs to the Topic Intelligent, Flexible, and Effective Operation of Smart Grids with Novel Energy Technologies and Equipment)
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11 pages, 282 KB  
Article
Perception of Barriers to Sports Practice in Persons with Disabilities in Chile: A Socio-Ecological Approach
by Fernando Muñoz-Hinrichsen, Diana Camargo Rojas, Luís Torres Paz, Marco Kokaly Farah, Noemi Ortega Díaz, Juan López Jofré, Sophie Pombet Ortiz, Martín Lanas Araos, Jorge Pérez-Contreras, Alan Martínez Aros and Felipe Herrera Miranda
Healthcare 2026, 14(18), 2989; https://doi.org/10.3390/healthcare14182989 (registering DOI) - 12 Sep 2026
Abstract
Background: Participation in physical and sports activities is essential for the overall health of persons with disabilities (PWD). However, these individuals encounter multiple environmental and contextual barriers limiting sports engagement. Objective: This study aimed to analyze the perceived barriers to sports participation among [...] Read more.
Background: Participation in physical and sports activities is essential for the overall health of persons with disabilities (PWD). However, these individuals encounter multiple environmental and contextual barriers limiting sports engagement. Objective: This study aimed to analyze the perceived barriers to sports participation among PWD in Chile using a socio-ecological framework, evaluating differences by sex and sports practice status while adjusting for potential demographic confounders. Methods: A quantitative, cross-sectional design was conducted with a convenience sample of 245 PWD. Perceptions across four socio-ecological dimensions (intrapersonal, interpersonal, organizational, and community) were measured using the short Spanish version of the Barriers to Physical Activity Questionnaire for People with Mobility Impairments (BPAQ-MI). Non-parametric Mann–Whitney U tests were performed as primary bivariate analyses due to non-normal data distribution, followed by Analysis of Covariance (ANCOVA) models controlling for age and sex. Results: Bivariate analyses showed no significant differences by sex. When comparing sports participants versus non-participants, athletes perceived significantly lower barriers in the organizational (U=5357, p<0.001, r=0.286) and community (U=6216, p=0.020, r=0.172) dimensions. After adjusting for age and sex via ANCOVA, sports practice remained a significant independent predictor of lower organizational barriers (F=7.814, p=0.006, ηp2=0.032), and a significant interaction between sports practice and sex was identified in the community dimension (F=4.671, p=0.032, ηp2=0.019). Community-level barriers were rated highest across all groups. Conclusions: Sports participation is associated with a lower perception of organizational barriers, even when controlling for age. The prominent community-level obstacles underscore the need for targeted, context-specific public policies that enhance accessibility and inclusive infrastructure. Full article
(This article belongs to the Special Issue Physical Fitness in People with Disabilities: Assessment and Intervention Strategies in Physical Activity and Sport)
34 pages, 1193 KB  
Article
Multi-Criteria MILP Model Integrating Kirchhoff’s Current Law for Optimal Green Feeder Bus Network Design: A Case Study of Ho Chi Minh City Metro Line 1
by Hong Le Xuan, Vinh Cao Huu, Thai Nguyen and Dong Doan Van
Appl. Sci. 2026, 16(18), 9071; https://doi.org/10.3390/app16189071 (registering DOI) - 12 Sep 2026
Abstract
Integrating an efficient feeder bus network is critical to maximizing the passenger-carrying capacity of urban mass transit systems. This study proposes a Kirchhoff’s Current Law-based Network Flow Model (KCL-NFM) that integrates Mixed-Integer Linear Programming (MILP) formulations—ranging from fundamental to advanced multi-objective levels—to optimize [...] Read more.
Integrating an efficient feeder bus network is critical to maximizing the passenger-carrying capacity of urban mass transit systems. This study proposes a Kirchhoff’s Current Law-based Network Flow Model (KCL-NFM) that integrates Mixed-Integer Linear Programming (MILP) formulations—ranging from fundamental to advanced multi-objective levels—to optimize feeder bus fleet size and the number of operational routes for Ho Chi Minh City Metro Line 1 across various planning horizons from 2024 to post-2040. By systematically optimizing operational frequency and route length constraints, the analysis identifies a practical operating point with a vehicle rotation rate of 2.5 round trips per hour and a maximum round trip length of 5 km. Experimental simulations demonstrate that the Advanced MILP model achieves a significant fleet size reduction of 53.6% to 55.4%—equivalent to eliminating over 200 redundant units in long-term scenarios. This efficiency translates into a 128% increase in revenue per bus and substantial capital savings of 740 billion VND (~29.1 million USD), representing a 58.7% reduction in capital expenditure (CAPEX), while maintaining vehicle load factors within a realistic operational threshold of 95% to 113%. Furthermore, sensitivity analysis reveals that transitioning to a 100% medium-sized electric bus fleet completely eliminates direct operational (tailpipe) carbon dioxide (CO2) emissions. This green transition not only mitigates urban congestion but also indicates the framework’s potential to support transport planners in designing economically viable and environmentally sustainable multi-modal transit systems. Full article
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