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15 pages, 2153 KB

Open AccessReview

Assessing the Potential for Modifying Certain Eradication Measures for Xylella fastidiosa subsp. pauca in Olive Groves of Apulia (Italy)

by Marco Scortichini

Agriculture 2026, 16(2), 145; https://doi.org/10.3390/agriculture16020145 (registering DOI) - 6 Jan 2026

Abstract

Sometimes, mandatory rules for eradicating pathogens specifically target crops that hold intrinsic economic value, cultural heritage, and are a lucrative tourist attraction as well as an appealing part of the landscape due to their historical presence in the region. An example of this [...] Read more.

Sometimes, mandatory rules for eradicating pathogens specifically target crops that hold intrinsic economic value, cultural heritage, and are a lucrative tourist attraction as well as an appealing part of the landscape due to their historical presence in the region. An example of this is the introduction of Xylella fastidiosa subsp. pauca (Xfp), mainly vectored by Philaenus spumarius to olive groves in Apulia. Twelve years after the first official report on its presence and numerous studies, this review aims to reconsider some of the quarantine measures in place to prevent the spread of Xfp. Surveys carried out within the demarcated areas have shown a low incidence of Xfp over the years ranging from 0.06% to 0.70%. Furthermore, the bacterium is now present throughout the region, from the south to the north, potentially suggesting that the bacterium may be endemic in the region. Epidemiological models have indicated low or negligible infectivity for asymptomatic trees. Rigorous vector control, achieved through the mechanical removal of eggs and juvenile forms, coupled with the contemporary reduction in the Xfp load within the olive crown using bactericidal compounds, could effectively reduce the spread of Xfp in both infected and demarcated areas. These actions could also serve as preventive measures in current free areas. Once the prevalence of both vectors and Xfp is low, only olive trees in demarcated areas that test positive for the bacterium should be uprooted. Trees within a 50 m radius of an Xfp-positive olive tree should not be removed if they test negative for Xfp upon detection. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

13 pages, 1092 KB

Open AccessArticle

Analysis of Pharmacokinetic and Pharmacodynamic Interactions Between Chlorpromazine and Risperidone via Simultaneous Measurement of Multiple Receptor Occupancy in the Rat Brain

by Gaku Akashita, Eriko Nakatani, Shimako Tanaka and Takashi Okura

Biomedicines 2026, 14(1), 118; https://doi.org/10.3390/biomedicines14010118 (registering DOI) - 6 Jan 2026

Abstract

Background/Objectives: Combination therapy for schizophrenia may exacerbate side effects mediated by multiple brain receptors. This study aimed to elucidate the pharmacodynamic and pharmacokinetic interactions between chlorpromazine and risperidone. We investigated dopamine 2 (D₂), serotonin 2A (5-HT_2A), histamine 1 (H [...] Read more.

Background/Objectives: Combination therapy for schizophrenia may exacerbate side effects mediated by multiple brain receptors. This study aimed to elucidate the pharmacodynamic and pharmacokinetic interactions between chlorpromazine and risperidone. We investigated dopamine 2 (D₂), serotonin 2A (5-HT_2A), histamine 1 (H₁), and muscarinic acetylcholine (mACh) receptor occupancy in the brain as well as pharmacokinetic interactions after oral administration of chlorpromazine and risperidone in rats. Methods: Rats were orally administered chlorpromazine, risperidone, or their combination. A tracer cocktail solution was injected intravenously to measure multiple receptor occupancies simultaneously. Tracer and drug concentrations in the brain tissue and plasma were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Results: Receptor occupancy increased in a dose-dependent manner. The doses required for 70% D₂ receptor occupancy were 4.5 mg/kg for chlorpromazine and 1.5 mg/kg for risperidone. Co-administration of chlorpromazine (4.5 mg/kg) and risperidone (1.5 mg/kg) resulted in an increase in D₂ and 5-HT_2A receptor occupancy to approximately 90%. Risperidone alone caused a transient increase in H₁ receptor occupancy to 80%, while co-administration increased mACh receptor occupancy to 60%. Co-administration with chlorpromazine significantly increased the plasma concentrations of risperidone and its metabolite, paliperidone, and decreased the oral clearance of risperidone by 5.9-fold. Conclusions: Co-administration of chlorpromazine and risperidone increases the occupancy of D₂, 5-HT_2A, and mACh receptors in the rat brain and increases the plasma concentrations of risperidone and paliperidone, suggesting a potential risk of enhanced adverse effects due to both pharmacokinetic and pharmacodynamic interactions involving target and non-target brain receptors. Full article

(This article belongs to the Section Drug Discovery, Development and Delivery)

39 pages, 15947 KB

Open AccessArticle

Damage Characterisation of Scour in Riprap-Protected Jackets and Hybrid Foundations

by João Chambel, Tiago Fazeres-Ferradosa, Mahdi Alemi, Francisco Taveira-Pinto and Pedro Lomonaco

J. Mar. Sci. Eng. 2026, 14(2), 114; https://doi.org/10.3390/jmse14020114 (registering DOI) - 6 Jan 2026

Abstract

The global transition towards sustainable energy has accelerated the development and deployment of offshore wind turbines. Jacket foundations, commonly installed in intermediate to deep water depths to access available space and higher load capacities, are built to withstand intensified hydrodynamic loads. Due to [...] Read more.

The global transition towards sustainable energy has accelerated the development and deployment of offshore wind turbines. Jacket foundations, commonly installed in intermediate to deep water depths to access available space and higher load capacities, are built to withstand intensified hydrodynamic loads. Due to their structural complexity near the seabed, however, they are prone to local and global scour, which can compromise stability and increase maintenance costs. While extensive research has addressed scour protections around monopiles, limited attention has been given to complex foundation geometries or even hybrid configurations that combine energy-harvesting devices with structural support. These hybrid systems introduce highly unsteady flow fields and amplified turbulence effects that current design frameworks appear to be unable to capture. This study provides an experimental characterisation of scour damage in riprap-protected jackets as well as additional tests for a hybrid jacket foundation. A novel adaptation of a high-resolution overlapping sub-area methodology was employed. For the first time, it was successfully applied to quantify the damage to riprap protections for a complex offshore foundation. Results revealed that, although hybrid jackets showed the capacity to attenuate incident waves, the scour protection experienced damage numbers (S_3D) two to six times higher than conventional jackets due to flow amplifications. The findings highlight the need for revised design guidelines that can account for the complex hydrodynamic-structural interactions of next-generation marine harvesting technologies integrated into complex foundations. Full article

(This article belongs to the Topic Advancements and Challenges in Marine Renewable Energy and Marine Structures)

26 pages, 6223 KB

Open AccessArticle

Two-Phase Distributed Genetic-Based Algorithm for Time-Aware Shaper Scheduling in Industrial Sensor Networks

by Ray-I Chang, Ting-Wei Hsu and Yen-Ting Chen

Sensors 2026, 26(2), 377; https://doi.org/10.3390/s26020377 (registering DOI) - 6 Jan 2026

Abstract

Time-Sensitive Networking (TSN), particularly the Time-Aware Shaper (TAS) specified by IEEE 802.1Qbv, is critical for real-time communication in Industrial Sensor Networks (ISNs). However, many TAS scheduling approaches rely on centralized computation and can face scalability bottlenecks in large networks. In addition, global-only schedulers [...] Read more.

Time-Sensitive Networking (TSN), particularly the Time-Aware Shaper (TAS) specified by IEEE 802.1Qbv, is critical for real-time communication in Industrial Sensor Networks (ISNs). However, many TAS scheduling approaches rely on centralized computation and can face scalability bottlenecks in large networks. In addition, global-only schedulers often generate fragmented Gate Control Lists (GCLs) that exceed per-port entry limits on resource-constrained switches, reducing deployability. This paper proposes a two-phase distributed genetic-based algorithm, 2PDGA, for TAS scheduling. Phase I runs a network-level genetic algorithm (GA) to select routing paths and release offsets and construct a conflict-free baseline schedule. Phase II performs per-switch local refinement to merge windows and enforce device-specific GCL caps with lightweight coordination. We evaluate 2PDGA on 1512 configurations (three topologies, 8–20 switches, and guard bands

δ_{g b} \in {0,100,200} ns

). At

δ_{g b} = 0

ns, 2PDGA achieves 92.9% and 99.8% CAP@8/CAP@16, respectively, compliance while maintaining a median latency of 42.1

μ

s. Phase II reduces the average max-per-port GCL entries by 7.7%. These results indicate improved hardware deployability under strict GCL caps, supporting practical deployment in real-world Industry 4.0 applications. Full article

(This article belongs to the Special Issue Architectures, Protocols and Algorithms of Sensor Networks—Second Edition)

15 pages, 447 KB

Open AccessReview

From Adults to Adolescents: Bridging Scientific Potential and Evidence-Based Paths for Psychedelic-Assisted Interventions

by Mayank Gupta, Aaron Krasner and Priyal Khurana

Psychoactives 2026, 5(1), 2; https://doi.org/10.3390/psychoactives5010002 (registering DOI) - 6 Jan 2026

Abstract

Adolescent mental health conditions, particularly treatment-resistant depression (TRD), represent a growing public health challenge associated with high morbidity, functional impairment, and elevated suicide risk. Psychedelic-assisted therapies have shown robust antidepressant and transdiagnostic effects in rigorously controlled adult trials. Extending this work to adolescents [...] Read more.

Adolescent mental health conditions, particularly treatment-resistant depression (TRD), represent a growing public health challenge associated with high morbidity, functional impairment, and elevated suicide risk. Psychedelic-assisted therapies have shown robust antidepressant and transdiagnostic effects in rigorously controlled adult trials. Extending this work to adolescents is scientifically compelling yet ethically complex, given neurodevelopmental vulnerabilities and the paucity of pediatric data. This review examines the historical context of psychedelic use, summarizes adult efficacy and mechanistic insights, explores adolescent-specific opportunities and risks, and considers applications in co-occurring neurodevelopmental disorders. Conventional treatments, including selective serotonin reuptake inhibitors and psychotherapy, are often inadequate for a narrow but substantial subset of clinical phenotypes, prompting interest in novel and rapid-acting interventions. Psychedelic-assisted therapies have shown promising results in adults with refractory mood disorders, yet their applicability to adolescents remains uncertain due to ongoing neurodevelopment and ethical constraints. This review critically examines evidence from adult psychedelic and psychedelic-adjacent interventions, including esketamine, and evaluates their potential relevance to adolescent populations through a developmental, mechanistic, and ethical lens. Rather than advocating for premature clinical adoption, we highlight translational gaps, developmental risks, and research priorities paramount to responsibly assess these approaches in youth. Full article

(This article belongs to the Special Issue New Psychoactive Substances and Emerging Trends: Pharmacology, Neurotoxicity and Public Health Implications)

22 pages, 7225 KB

Open AccessArticle

Experimental and Numerical Study on the Two-Dimensional Longitudinal Temperature Rise Behavior of Fire Smoke in the Shenzhen–Zhongshan Ultra-Wide Cross-Section Undersea Tunnel

by Xiujun Yang, Rongliang Pan, Chenhao Ran and Maohua Zhong

Fire 2026, 9(1), 29; https://doi.org/10.3390/fire9010029 (registering DOI) - 6 Jan 2026

Abstract

The Shenzhen–Zhongshan Link is a key cross-sea corridor in the Guangdong–Hong Kong–Macao Greater Bay Area. As a representative ultra-wide cross-section undersea tunnel, it exhibits smoke spread behaviors that differ fundamentally from those of traditional road tunnels. In particular, the radial flow region of [...] Read more.

The Shenzhen–Zhongshan Link is a key cross-sea corridor in the Guangdong–Hong Kong–Macao Greater Bay Area. As a representative ultra-wide cross-section undersea tunnel, it exhibits smoke spread behaviors that differ fundamentally from those of traditional road tunnels. In particular, the radial flow region of fire smoke is more pronounced, resulting in substantial lateral variations in smoke dynamics parameters. These characteristics render classical one-dimensional ceiling jet temperature rise theories insufficient for capturing the multidimensional thermal behavior in such geometries. In this study, the immersed-tunnel section of the Shenzhen–Zhongshan Link was investigated through a combination of full-scale fire experiments and Fire Dynamics Simulator (FDS) simulations. The longitudinal attenuation and lateral distribution characteristics of hot smoke temperature rise during spread in an ultra-wide tunnel were systematically obtained. Based on a simplified one-dimensional ceiling jet concept, differences in hot smoke diffusion distance were employed to characterize the lateral temperature rise ratio at any longitudinal location, from which a lateral distribution model was developed. The classical one-dimensional average temperature rise decay model was further reformulated to derive a modified longitudinal decay model applicable to the tunnel centerline of ultra-wide cross-sections. By integrating these characteristic models, a two-dimensional longitudinal prediction framework for hot smoke temperature rise in ultra-wide tunnels was established. Validation against full-scale fire experiments demonstrates that the proposed model can predict the two-dimensional thermal field with an accuracy within 25%. The findings of this study provide a theoretical basis for fire scenario reconstruction in the Shenzhen–Zhongshan undersea tunnel and offer a technical foundation for optimizing emergency ventilation strategies during fire incidents. Full article

(This article belongs to the Special Issue Modeling, Experiment and Simulation of Tunnel Fire)

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13 pages, 542 KB

Open AccessArticle

Influence of Teucrium montanum Hydrolate Integration on the Functional Performance of Chitosan-Based Films

by Ljubica Živković, Kristina Cvetković, Jelena Mitrović, Dani Dordevic, Pero Sailović, Ivana Karabegović and Bojana Danilović

Processes 2026, 14(2), 200; https://doi.org/10.3390/pr14020200 (registering DOI) - 6 Jan 2026

Abstract

Natural biodegradable polymers such as chitosan are gaining increasing importance due to their favorable mechanical properties. Conversely, their limited antimicrobial and antioxidant activity requires enhancement with bioactive components. This study investigated the effect of Teucrium montanum L. hydrolate on the functional properties of [...] Read more.

Natural biodegradable polymers such as chitosan are gaining increasing importance due to their favorable mechanical properties. Conversely, their limited antimicrobial and antioxidant activity requires enhancement with bioactive components. This study investigated the effect of Teucrium montanum L. hydrolate on the functional properties of chitosan films. The hydrolate was obtained as a by-product of hydrodistillation, and films were prepared with 0.6% (CH-TMh1), 0.8% (CH-TMh2), and 1.2% (CH-TMh3) hydrolate, along with a control film without hydrolate (CH). Hydrolate-enriched films exhibited greater thickness and elongation at break, with the highest values observed in CH-TMh3. The addition of hydrolate reduced moisture content (from 30.09% in CH to 12.25% in CH-TMh3), solubility, and swelling degree. Antioxidant activity increased significantly, with CH-TMh2 showing the highest free radical scavenging activity (92.9%) and total polyphenol content (38.78 mg GAE/g). Films containing hydrolate also displayed pronounced antimicrobial activity, with the largest inhibition zones against S. aureus ATCC 25923 (16.33 mm). Moderate activity was observed against B. subtilis, while there was no activity against C. albicans ATCC 2091. These results confirm that chitosan films enriched with T. montanum L. hydrolate possess improved mechanical, antioxidant, and antimicrobial properties, making them promising for potential application in the packaging of specific food products. Full article

(This article belongs to the Special Issue Advancements in Low-Dimensional Materials: Focus on Detailed Methodologies)

41 pages, 5139 KB

Open AccessReview

Deep Reinforcement Learning for Sustainable Urban Mobility: A Bibliometric and Empirical Review

by Sharique Jamal, Farheen Siddiqui, M. Afshar Alam, Mohammad Ayman-Mursaleen, Sherin Zafar and Sameena Naaz

Sensors 2026, 26(2), 376; https://doi.org/10.3390/s26020376 (registering DOI) - 6 Jan 2026

Abstract

This paper provides an empirical basis for a Computational Integration Framework (CIF), a systematic and scientifically supported implementation of artificial intelligence (AI) in smart city applications. This study is a methodological framework-with-validation study, where large-scale bibliometric analysis is used as a justification for [...] Read more.

This paper provides an empirical basis for a Computational Integration Framework (CIF), a systematic and scientifically supported implementation of artificial intelligence (AI) in smart city applications. This study is a methodological framework-with-validation study, where large-scale bibliometric analysis is used as a justification for design in the identification of strategically relevant urban areas rather than a single research study. This evidence determines urban mobility as the most mature and computationally optimal domain for empirical verification. The exploitation of CIF is realized using a DRL-driven traffic signal control system to show that bibliometrically informed domain selection can be put into application by way of an algorithm. The empirical results show that the most traditional control strategies accomplish significant performance gains, such as about 48% reduction in average wait time, over 30% increase in traffic efficiency, and considerable reductions in fuel consumption and CO₂ emissions. A federated DRL solution maintains around 96% of central performance while still maintaining data privacy, which suggests that deployment in real-world situations is feasible. The contribution of this study is threefold: evidence-based domain selection through bibliometric analyses; introduction of CIF as an AI decision support bridge between AI techniques and urban application domains; and computational verification of the feasibility of DRL for sustainable urban mobility. These findings reveal policy information relevant to goals governing global sustainability, including the European Green Deal (EGD) and the United Nations Sustainable Development Goals (SDGs), and thus, the paper is a methodological framework paper based on literature and validated through computational experimentation. Full article

(This article belongs to the Special Issue Edge Artificial Intelligence and Data Science for IoT-Enabled Systems)

37 pages, 2009 KB

Open AccessArticle

Spatiotemporal Lattice-Constrained Event Linking and Automatic Labeling for Cross-Document Accident Reports

by Wenhua Zeng, Wenhu Tang, Diping Yuan, Bo Zhang and Yuhui Zeng

Appl. Sci. 2026, 16(2), 595; https://doi.org/10.3390/app16020595 (registering DOI) - 6 Jan 2026

Abstract

Constructing reusable accident-text corpora is hindered by anonymization, heterogeneous sources, and sparse labels, which complicate cross-document event linking. We propose a spatiotemporal lattice-constrained approach that encodes administrative hierarchies and temporal granularity, defines domain-informed consistency criteria, instantiates spatial/temporal relations via a subset of RCC-8 [...] Read more.

Constructing reusable accident-text corpora is hindered by anonymization, heterogeneous sources, and sparse labels, which complicate cross-document event linking. We propose a spatiotemporal lattice-constrained approach that encodes administrative hierarchies and temporal granularity, defines domain-informed consistency criteria, instantiates spatial/temporal relations via a subset of RCC-8 and Allen’s interval algebra, estimates anchor weights via smoothing with monotonic projection, and fuses signals using a constrained monotonic network with explicit probability calibration. An active-learning decision rule—combining maximum probability with a probability-gap criterion—supports scalable automatic labeling, and controlled augmentation leverages instruction-tuned LLMs under lattice constraints. Experiments show competitive ranking (Hit@1 = 41.51%, Hit@5 = 77.33%) and discrimination (ROC-AUC = 87.34%), with the best F1 (62.46%). The method yields the lowest calibration errors (Brier = 0.14; ECE = 1.97%), maintains performance across sources, and exhibits the smallest F1 fluctuation across thresholds (Δ = 1.7%). In deployment-oriented analyses, it auto-labels 77.7% of cases with 97.51% accuracy among high-confidence outputs while routing 22.3% to review, where the true-positive rate is 81.46%. These findings indicate that integrating structured constraints with calibrated probabilistic fusion enables accurate, auditable, and scalable event linking for accident-corpus construction. Full article

16 pages, 1249 KB

Open AccessArticle

Sagittal Alignment Reciprocal Changes After Thoracolumbar/Lumbar Anterior Vertebral Body Tethering

by Taha Furkan Yağcı, Serkan Bayram, Murat Korkmaz, Şahin Karalar, Adem Bayraktar, Gökhan Bayrak and Turgut Akgül

J. Clin. Med. 2026, 15(2), 447; https://doi.org/10.3390/jcm15020447 (registering DOI) - 6 Jan 2026

Abstract

Background/Objective: The anterior vertebral body tethering (AVBT) technique, which preserves spinal mobility and avoids possible fusion problems in adolescent idiopathic scoliosis (AIS) patients, continues to be increasingly used in spine surgery. The study aims to report the early-to-early-mid postoperative radiological results of thoracolumbar/lumbar [...] Read more.

Background/Objective: The anterior vertebral body tethering (AVBT) technique, which preserves spinal mobility and avoids possible fusion problems in adolescent idiopathic scoliosis (AIS) patients, continues to be increasingly used in spine surgery. The study aims to report the early-to-early-mid postoperative radiological results of thoracolumbar/lumbar AVBT on sagittal alignment, and the second aim is to compare AVBT with selective thoracic fusion (STF) and non-selective fusion (NSF) groups in AIS patients. Methods: Patients with a diagnosis of AIS were retrospectively evaluated in the study. All patients were categorized into three groups based on the surgical technique performed: AVBT (n = 17), NSF (n = 19), and STF (n = 15). The major curvature degree, coracoid height difference (CHD), sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), lumbar lordosis (LL), thoracic kyphosis (TK), cervical lordosis (CL), C7 tilt, sagittal vertical axis (SVA), T1 pelvic angle (TPA), and T1 spinopelvic inclination (T1SPI) were measured for radiological comparison. Scoliosis Research Society-22 (SRS-22) and Oswestry Disability Index (ODI) scores were used at the final follow-up for functional evaluation. Results: The T1SPI value of the NSF group was significantly higher than the STF group in the final follow-up (p = 0.033). The mean decrease of 8.85 ± 7.85 units in the final follow-up value compared to the postoperative CHD value of the patients in the AVBT group was found to be significant (p = 0.028). Statistically significant differences were found between preoperative and the first postoperative CL and TPA measurements (p = 0.001 and p = 0.042, respectively), as well as between preoperative and final follow-up CL measurements in the AVBT group (p = 0.001). No statistically significant differences were observed between the groups in CHD, SS, PT, PI, LL, TK, CL, C7 tilt, SVA, and TPA values (p > 0.05); similarly, the SRS-22 and ODI scores did not differ significantly among the groups (p > 0.05). Conclusions: Thoracolumbar/lumbar AVBT surgery led to significant improvements in shoulder asymmetry and cervical lordosis of AIS patients in the early to early-mid postoperative period. However, compared with spinal fusion techniques, thoracolumbar/lumbar AVBT did not demonstrate superiority in functional scores or sagittal parameters. The mid- to long-term benefits of thoracolumbar/lumbar AVBT remain uncertain and require further investigation. Full article

(This article belongs to the Section Orthopedics)

23 pages, 1825 KB

Open AccessArticle

Analysis of Wind-Induced Response During the Lifting Construction of Super-Large-Span Heavy Steel Box Girders

by Shuhong Zhu, Xiaotong Sun, Xiaofeng Liu, Wenjie Li and Bin Liang

Buildings 2026, 16(2), 251; https://doi.org/10.3390/buildings16020251 (registering DOI) - 6 Jan 2026

Abstract

Wind-induced response poses a significant challenge to the stability of extra-large-span heavy steel box girders during synchronous lifting operations. This study adopted a method combining numerical simulation with on-site monitoring to investigate the aerodynamic characteristics the beam during the overall hoisting process of [...] Read more.

Wind-induced response poses a significant challenge to the stability of extra-large-span heavy steel box girders during synchronous lifting operations. This study adopted a method combining numerical simulation with on-site monitoring to investigate the aerodynamic characteristics the beam during the overall hoisting process of the Xiaotun Bridge. A high-fidelity finite element model was established using Midas NFX 2024 R1, and fluid–structure interaction (FSI) analysis was conducted, utilizing the RANS k-ε turbulence model to simulate stochastic wind fields. The results show that during the lifting stage from 3 m to 25 m, the maximum horizontal displacement of the steel box girder rapidly increases at wind angles of 90° and 60°, and the peak displacement is reached at 25 m. Under a strong breeze at a 90° wind angle and 25 m lifting height, the maximum lateral displacement was 42.88 mm based on FSI analysis, which is approximately 50% higher than the 28.58 mm obtained from linear static analysis. Subsequently, during the 25 m to 45 m lifting stage, the displacement gradually decreases and exhibits a linear correlation with lifting height. Concurrently, the maximum stress of the lifting lug of the steel box girder increases rapidly in the 3–25 m lifting stage, reaches the maximum at 25 m, and gradually stabilizes in the 25–45 m lifting stage. The lug stress under the same critical condition reached 190.80 MPa in FSI analysis, compared with 123.83 MPa in static analysis, highlighting a significant dynamic amplification. Furthermore, the detrimental coupling effect between mechanical vibrations from the lifting platform and wind loads was quantified; the anti-overturning stability coefficient was reduced by 10.48% under longitudinal vibration compared with lateral vibration, and a further reduction of up to 39.33% was caused by their synergy with wind excitation. Field monitoring validated the numerical model, with stress discrepancies below 9.7%. Based on these findings, a critical on-site wind speed threshold of 9.38 m/s was proposed, and integrated control methods were implemented to ensure construction safety. During on-site lifting, lifting lug stresses were monitored in real time, and if the predefined threshold was exceeded, contingency measures were immediately activated to ensure a controlled termination. Full article

(This article belongs to the Section Building Structures)

32 pages, 44207 KB

Open AccessArticle

Is Satellite-Derived Bathymetry Vertical Accuracy Dependent on Satellite Mission and Processing Method?

by Monica Palaseanu-Lovejoy, Jeffrey Danielson, Minsu Kim, Bryan Eder, Gretchen Imahori and Curt Storlazzi

Remote Sens. 2026, 18(2), 195; https://doi.org/10.3390/rs18020195 (registering DOI) - 6 Jan 2026

Abstract

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; [...] Read more.

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all SDB methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the Iterative Closest Point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error (RMSE). Thus, it is recommended to perform detrending where possible to achieve an error distribution as close to normality as possible for which error metrics are more diagnostic. Full article

25 pages, 1591 KB

Open AccessEssay

Deep Learning-Based Identification of Pathogenicity Genes in Phytophthora infestans Using Time-Series Transcriptomics

by Yinfei Dai, Shihao Lu, Jie Fan, Mengjiao Qiao, Yuheng Zhu, Enshuang Zhao and Hao Zhang

Plants 2026, 15(2), 178; https://doi.org/10.3390/plants15020178 (registering DOI) - 6 Jan 2026

Abstract

Potato (Solanum tuberosum L.) is the world’s fourth most important food crop, and despite China producing nearly one quarter of the global yield, its potato production is severely constrained by late blight. Identifying genes associated with pathogenicity is essential for breeding resistant [...] Read more.

Potato (Solanum tuberosum L.) is the world’s fourth most important food crop, and despite China producing nearly one quarter of the global yield, its potato production is severely constrained by late blight. Identifying genes associated with pathogenicity is essential for breeding resistant cultivars and strengthening plant protection strategies. Traditional approaches based on differential expression and statistical modeling often fail to capture temporal dynamics or provide interpretable insights. Here, we introduce an LSTM–Transformer hybrid model designed for data-driven discovery of pathogenicity-related genes from gene expression time-series. The analysis was performed on a time-series expression dataset comprising 32,917 genes across 18 samples (three infection time points × six biological replicates per condition). In this study, we identified 200 high-confidence pathogenicity-related genes from potato infection time-series data. These genes are enriched in 15 biologically meaningful pathways, including plant immunity signaling, reactive oxygen species regulation, secondary metabolic processes, and stress-responsive transcriptional programs. Several newly uncovered candidates participate in defense hormone pathways and cell wall modification, suggesting previously unrecognized roles in late blight susceptibility and resistance. By revealing functional groups and regulatory signatures that characterize pathogenicity, this work provides valuable molecular targets for developing late blight-resistant cultivars. The framework integrates a biologically informed temporal–attention architecture, a gene time-series-specific data partitioning strategy, and an interpretable deep analysis module. A final methodological contribution is the use of a temporal attention-based analytical framework that enables reliable gene prioritization from time-series expression data. Full article

(This article belongs to the Special Issue Applications of Bioinformatics in Plant Science)

19 pages, 5684 KB

Open AccessArticle

SDDNet: Two-Stage Network for Forgings Surface Defect Detection

by Shentao Wang, Depeng Gao, Byung-Won Min, Yue Hong, Tingting Xu and Zhongyue Xiong

Symmetry 2026, 18(1), 104; https://doi.org/10.3390/sym18010104 (registering DOI) - 6 Jan 2026

Abstract

Detecting surface defects in forgings is crucial for ensuring the reliability of automotive components such as steering knuckles. In fluorescent magnetic particle inspection (FDMPI) images, normal forging surfaces generally exhibit locally symmetric texture patterns, whereas cracks and other flaws appear as locally asymmetric [...] Read more.

Detecting surface defects in forgings is crucial for ensuring the reliability of automotive components such as steering knuckles. In fluorescent magnetic particle inspection (FDMPI) images, normal forging surfaces generally exhibit locally symmetric texture patterns, whereas cracks and other flaws appear as locally asymmetric regions. Traditional FDMPI inspection relies on manual visual judgement, which is inefficient and error-prone. This paper introduces SDDNet, a symmetry-aware deep learning model for surface defect detection in FDMPI images. A dedicated FDMPI dataset is constructed and further expanded using a denoising diffusion probabilistic model (DDPM) to improve training robustness. To better separate symmetric background textures from asymmetric defect cues, SDDNet integrates a UPerNet-based segmentation layer for background suppression and a Scale-Variant Inception Module (SVIM) within an RTMDet framework for multi-scale feature extraction. Experiments show that SDDNet effectively suppresses background noise and significantly improves detection accuracy, achieving a mean average precision (mAP) of 45.5% on the FDMPI dataset, 19% higher than the baseline, and 71.5% mAP on the NEU-DET dataset, outperforming existing methods by up to 8.1%. Full article

(This article belongs to the Special Issue Symmetry/Asymmetry in Image Processing and Computer Vision)

14 pages, 3428 KB

Open AccessArticle

A SiC-MOSFET Bidirectional Switch Solution for Direct Matrix Converter Topologies

by Hernán Lezcano, Rodrigo Romero, Sergio Nuñez, Bruno Sanabria, Fabian Palacios-Pereira, Edgar Maqueda, Sergio Toledo, Julio Pacher, David Caballero, Raúl Gregor and Marco Rivera

Actuators 2026, 15(1), 40; https://doi.org/10.3390/act15010040 (registering DOI) - 6 Jan 2026

Abstract

Bidirectional switches are highly required power electronics units for the design of power converters, especially for direct matrix converters. This article presents the design and implementation of a compact bidirectional switch based on SiC-MOSFET technology, aimed at high-efficiency, high-density power electronics applications. The [...] Read more.

Bidirectional switches are highly required power electronics units for the design of power converters, especially for direct matrix converters. This article presents the design and implementation of a compact bidirectional switch based on SiC-MOSFET technology, aimed at high-efficiency, high-density power electronics applications. The proposed architecture employs surface-mount components, optimizing both the occupied area and electrical performance. The selected switching device is the IMBG120R053M2H from Infineon, a SiC-MOSFET known for its low on-resistance, high reverse-voltage blocking capability, and excellent switching speed. To drive the power devices, the UCC21521 gate driver integrates two independent isolated outputs in a single package, enabling precise control and reduced electromagnetic interference (EMI). The developed design supports bidirectional current conduction and voltage blocking, offering a robust and scalable solution for next-generation power converters. Design criteria, simulation results, and experimental validations are discussed. Full article

(This article belongs to the Special Issue Power Electronics and Actuators—Second Edition)

16 pages, 2143 KB

Open AccessArticle

A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability

by Zhuowen Feng, Pengyu Lai, Abu Shahir Md Khalid Hasan, Fuad Fatani, Alborz Alaeddini, Liling Huang, Zhong Chen and Qiliang Li

Materials 2026, 19(2), 228; https://doi.org/10.3390/ma19020228 (registering DOI) - 6 Jan 2026

Abstract

Silicon carbide (SiC) power converters are increasingly used in automotive, renewable energy, and industrial applications. While reliability assessments are typically performed at either the device or system level, an integrative approach that simultaneously evaluates both levels remains underexplored. This article presents a novel [...] Read more.

Silicon carbide (SiC) power converters are increasingly used in automotive, renewable energy, and industrial applications. While reliability assessments are typically performed at either the device or system level, an integrative approach that simultaneously evaluates both levels remains underexplored. This article presents a novel system-level simulation method with two strategies to evaluate the reliability of power devices and a resonant converter under varying temperatures and total ionizing doses (TIDs). Temperature-sensitive electrical parameters (TSEPs), such as on-state resistance (

R_{ON}

) and threshold voltage shift (

Δ V_{TH}

), are calibrated and analyzed using a B1505A curve tracer. These parameters are incorporated into the system-level simulation of a 300 W resonant converter with a boosting cell. Both Silicon (Si) and SiC-based power resonant converters are assessed for power application in space engineering and harsh environments. Additionally, gate-oxide degradation and

Δ V_{TH}

-related issues are discussed based on the simulation results. The thermal-strategy results indicate that SiC MOSFETs maintain a more stable conduction loss at elevated temperatures, exhibiting higher reliability due to their high thermal conductivity. Conversely, increased TIDs result in a negative shift in conduction losses across all SiC devices under the radiation strategy, affecting the long-term reliability of the power converter. Full article

(This article belongs to the Special Issue Wide- and Ultra-Wide-Bandgap Semiconductors: Properties, Synthesis and Devices)

17 pages, 484 KB

Open AccessArticle

Basil as a Green Alternative to Synthetic Additives in Clean Label Gilthead Sea Bream Patties

by Branislav Šojić, Sandra Zavadlav, Danijela Bursać Kovačević, Nadežda Seratlić, Sanja Vojvodić, Predrag Ikonić, Tatjana Peulić, Nemanja Teslić, Miloš Županjac and Branimir Pavlić

Foods 2026, 15(2), 198; https://doi.org/10.3390/foods15020198 (registering DOI) - 6 Jan 2026

Abstract

This study investigated the effectiveness of basil (Ocimum basilicum L.) extract obtained by hydrodistillation (EO) and lipid extract (LE) obtained via supercritical fluid extraction in preserving the quality of ground fish patties during refrigerated storage. Gilthead sea bream (Sparus aurata) [...] Read more.

This study investigated the effectiveness of basil (Ocimum basilicum L.) extract obtained by hydrodistillation (EO) and lipid extract (LE) obtained via supercritical fluid extraction in preserving the quality of ground fish patties during refrigerated storage. Gilthead sea bream (Sparus aurata) patties were formulated with varying concentrations of EO and LE and evaluated over three days at 4 °C. The chemical composition of the extracts, analyzed by GC-MS, revealed linalool, eucalyptol, and τ-cadinol as dominant bioactive compounds, with EO richer in monoterpenes and LE in sesquiterpenes. Both extracts significantly reduced lipid oxidation (TBARS) and protein oxidation (thiol content), with the strongest antioxidative effect observed in patties containing 0.150 µL/g of LE. Color parameters (L*, a*, b*, ΔE) were moderately influenced, without adverse effects on product appearance. pH and water activity values remained stable across treatments, while total volatile basic nitrogen (TVB-N) levels confirmed delayed spoilage in extract-treated patties. Results highlight the potential of basil extracts, especially LE obtained by SFE, as effective natural antioxidants in fish-based products. These findings support the development of clean-label, health-promoting products tailored to individual needs, and show that ground fish porridge has promise as a viable material for the production of innovative seafood products. Full article

(This article belongs to the Special Issue Novel Processing Technologies for Improving Quality and Storage Stability of Food)

30 pages, 6524 KB

Open AccessArticle

Modeling and Assessment of Salinity Reduction Strategies in the Jarahi River, Iran

by Javad Ahadiyan, Narges Yarahamdi, Asghar Akbari, Seyed Mohsen Sajjadi, Hossein Azizi Nadian and Farhad Bahmanpouri

Hydrology 2026, 13(1), 22; https://doi.org/10.3390/hydrology13010022 (registering DOI) - 6 Jan 2026

Abstract

This study investigates the spatial and temporal variations in salinity in the Jarahi River and its traditional channels using field measurements and numerical simulations. The primary objective is to assess the effectiveness of different management strategies for salinity reduction under minimum-discharge conditions. Salinity [...] Read more.

This study investigates the spatial and temporal variations in salinity in the Jarahi River and its traditional channels using field measurements and numerical simulations. The primary objective is to assess the effectiveness of different management strategies for salinity reduction under minimum-discharge conditions. Salinity dynamics were analyzed through electrical conductivity (EC) measurements collected over a one-year period and simulated using the MIKE 11 hydrodynamic model. Model performance was evaluated by comparing simulated and observed EC values at key monitoring stations. The results indicate that maximum salinity levels occur during March and April in both the main river and traditional channels, while the highest temporal variability in EC was observed in October. The comparison between observed and simulated data showed a relative error of less than 10%, confirming the reliability of the model simulations. Four management scenarios were evaluated: (1) preventing inflow from the Motbeg drainage, (2) blocking non-centralized drainage inputs, (3) removing all inlet drains, and (4) increasing discharge releases from the Ramshir Dam. The first and third scenarios led to the highest salinity reductions, reaching up to 39% (approximately 1266 µS/cm) in the Gorgor channel, while reductions of up to 53% were observed in traditional streams such as Mansuri and Omal-Sakher under the third scenario. Increasing dam releases resulted in a maximum reduction of 23% (724 µS/cm) at the Gorgor station. Finally, the proposed management strategies significantly reduced salinity levels along the river system, particularly at the entrance of the Jahangiri traditional stream, providing practical insights for salinity control and river basin management. Full article

(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)

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23 pages, 277 KB

Open AccessArticle

Sustainability-Oriented Student Perspectives on University–Government–Kindergarten Collaboration in Early Childhood Teacher Education

by Beibei Zhang, Qinglei Hu and Shizhu Gou

Sustainability 2026, 18(2), 584; https://doi.org/10.3390/su18020584 (registering DOI) - 6 Jan 2026

Abstract

This study examines the effectiveness of the University–Government–Kindergarten Collaboration (UGK) model in training early childhood teacher candidates (TCs), using the Education for Sustainable Development (ESD) framework to assess its role in enhancing TCs’ competencies. Data were collected through a survey of 210 TCs [...] Read more.

This study examines the effectiveness of the University–Government–Kindergarten Collaboration (UGK) model in training early childhood teacher candidates (TCs), using the Education for Sustainable Development (ESD) framework to assess its role in enhancing TCs’ competencies. Data were collected through a survey of 210 TCs and in-depth interviews with 12 participants. The findings indicate a structural imbalance in UGK: while university–kindergarten collaboration shows some effectiveness, the lack of governmental leadership weakens tripartite synergy. From an ESD perspective, although UGK fosters basic collaborative skills, it does not systematically develop higher-order ESD competencies such as systems thinking, normative awareness, critical thinking, and strategic action. By shifting the focus from institutional to student experience, this study offers a new analytical framework for teacher education models. It concludes that optimizing UGK requires stronger governmental coordination, deeper university–kindergarten cooperation, and explicit integration of ESD core competencies throughout the training system. Full article

(This article belongs to the Section Sustainable Education and Approaches)

15 pages, 635 KB

Open AccessArticle

Clinical Remission and Its Determinants in Adult Severe Asthma Patients Receiving Biologic Therapy: A Retrospective Analysis

by Dane Ediger, Esma Nur Aktepe Sezgin, Raziye Tülümen Öztürk and Burcu Çoban

J. Clin. Med. 2026, 15(2), 442; https://doi.org/10.3390/jcm15020442 - 6 Jan 2026

Abstract

Background/Objectives: In recent years, the concept of clinical remission under treatment in asthma has gained increasing attention. It is defined as the absence of exacerbations, asthma symptoms, and oral corticosteroid use for at least 12 months, together with improved or stable lung function. [...] Read more.

Background/Objectives: In recent years, the concept of clinical remission under treatment in asthma has gained increasing attention. It is defined as the absence of exacerbations, asthma symptoms, and oral corticosteroid use for at least 12 months, together with improved or stable lung function. This study aimed to evaluate the clinical remission rates and associated factors in patients with severe asthma receiving biologic therapy with either omalizumab (anti-IgE) or mepolizumab (anti-IL-5). Methods: Adult patients with severe asthma and type 2 inflammation who started omalizumab or mepolizumab between January 2009 and December 2023 in our allergy clinic were retrospectively analyzed. Sociodemographic and clinical characteristics were reviewed. Clinical remission rates were assessed at the first and most recent years of maintenance therapy. Independent markers were identified using multivariable analyses. Results: A total of 160 patients were included (mean age 53.8 ± 14.6 years; 81.9% female). Of these, 85.6% received omalizumab and 14.4% mepolizumab. Remission rates at one year and at the latest follow-up were 60.0% and 43.7%, respectively. Patients achieving remission had higher total IgE levels. Psychiatric comorbidity negatively affected remission. The one-year remission rates were 91.3% in the mepolizumab group and 54.7% in the omalizumab group. Higher baseline blood eosinophil counts and Asthma Control Test (ACT) scores were positive markers, while psychiatric disease was inversely associated. Conclusions: Omalizumab and mepolizumab achieved meaningful clinical remission rates in severe asthma. Elevated ACT scores and eosinophil counts and absence of psychiatric comorbidities were independent markers, underscoring the need for individualized biologic therapy to achieve sustained remission. Full article

(This article belongs to the Special Issue Advances in Pulmonary Disease Management and Innovation in Treatment)

28 pages, 3413 KB

Open AccessArticle

The Mechanism of Ultrasonic Lysis of Enterococcus faecium F11.1G in Repairing LPS-Induced Inflammatory Damage in IECs via RNA-seq and LC-MS

by Tiantian Bai, Yanlong Zhang, Guangxu E, Meng Zhang, Xuefeng Guo and Junfeng Liu

Cells 2026, 15(2), 103; https://doi.org/10.3390/cells15020103 - 6 Jan 2026

Abstract

Lipopolysaccharide (LPS)-induced damage to the intestinal epithelial barrier leads to gut inflammation, and intracellular metabolites of lactic acid bacteria may participate in regulating this process to exert probiotic effects. This study aimed to investigate the repair effects and molecular mechanisms of ultrasonic disruption-treated [...] Read more.

Lipopolysaccharide (LPS)-induced damage to the intestinal epithelial barrier leads to gut inflammation, and intracellular metabolites of lactic acid bacteria may participate in regulating this process to exert probiotic effects. This study aimed to investigate the repair effects and molecular mechanisms of ultrasonic disruption-treated Enterococcus faecium F11.1G (F11.1G) on the model (primary lamb IECs + 5 μg/mL LPS for 6 h). Then, results demonstrated that 10⁸ CFU/mL F11.1G significantly suppressed the excessive secretion of pro-inflammatory factors (IL-6, IL-8, IL-1β, TNF-α) induced by LPS. Gene Ontology (GO) analysis revealed that differentially expressed genes (DEGs) were primarily enriched in cellular response to lipopolysaccharide, inflammatory response, and canonical NF-κB signaling pathways. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed enrichment in NF-κB signaling pathway and MAPK signaling pathway. PPI network identified key genes including IL-1β, TNF, IL-8, RELB, FOS, TNFAIP3, NFKBIA, and MMP9. KEGG analysis indicated differentially abundant metabolites (DAMs) enrichment in purine metabolism and the endocannabinoid system. Spearman correlation analysis revealed positive correlations between pro-inflammatory genes and endogenous protective metabolites, such as adenosine and PEA, while showing negative correlations with multiple purine metabolites. Correlational analysis indicates that F11.1G alleviates intestinal inflammatory damage primarily by suppressing NF-κB/MAPK pathway activation and may synergistically regulate purine and endocannabinoid metabolism. Full article

(This article belongs to the Topic Bioactive Compounds and Therapeutics: Molecular Aspects, Metabolic Profiles, and Omics Studies 2nd Edition)

17 pages, 1469 KB

Open AccessArticle

A MASPSO-Optimized CNN–GRU–Attention Hybrid Model for Short-Term Wind Speed Forecasting

by Haoran Du and Yaling Sun

Sustainability 2026, 18(2), 583; https://doi.org/10.3390/su18020583 - 6 Jan 2026

Abstract

Short-term wind speed forecasting is challenged by the nonlinear, non-stationary, and highly volatile characteristics of wind speed series, which hinder the performance of traditional prediction models. To improve forecasting capability, this study proposes a hybrid modeling framework that integrates multi-strategy adaptive particle swarm [...] Read more.

Short-term wind speed forecasting is challenged by the nonlinear, non-stationary, and highly volatile characteristics of wind speed series, which hinder the performance of traditional prediction models. To improve forecasting capability, this study proposes a hybrid modeling framework that integrates multi-strategy adaptive particle swarm optimization (MASPSO), a convolutional neural network (CNN), a gated recurrent unit (GRU), and an attention mechanism. Within this modeling architecture, the CNN extracts multi-scale spatial patterns, the GRU captures dynamic temporal dependencies, and the attention mechanism highlights salient feature components. MASPSO is further incorporated to perform global hyperparameter optimization, thereby improving both prediction accuracy and generalization. Evaluation on real wind farm data confirms that the proposed modeling framework delivers consistently superior forecasting accuracy across different wind speed conditions, with significantly reduced prediction errors and improved robustness in multi-step forecasting tasks. Full article

(This article belongs to the Special Issue Advances in Sustainable Energy Technologies and Energy Systems)

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18 pages, 4285 KB

Open AccessArticle

Eye-Tracking and Emotion-Based Evaluation of Wardrobe Front Colors and Textures in Bedroom Interiors

by Yushu Chen, Wangyu Xu and Xinyu Ma

Multimodal Technol. Interact. 2026, 10(1), 7; https://doi.org/10.3390/mti10010007 (registering DOI) - 6 Jan 2026

Abstract

Wardrobe fronts form a major visual element in bedroom interiors, yet material selection for their colors and textures often relies on intuition rather than evidence. This study develops a data-driven framework that links gaze behavior and affective responses to occupants’ preferences for wardrobe [...] Read more.

Wardrobe fronts form a major visual element in bedroom interiors, yet material selection for their colors and textures often relies on intuition rather than evidence. This study develops a data-driven framework that links gaze behavior and affective responses to occupants’ preferences for wardrobe front materials. Forty adults evaluated color and texture swatches and rendered bedroom scenes while eye-tracking data capturing attraction, retention, and exploration were collected. Pairwise choices were modeled using a Bradley–Terry approach, and visual-attention features were integrated with emotion ratings to construct an interpretable attention index for predicting preferences. Results show that neutral light colors and structured wood-like textures consistently rank highest, with scene context reducing preference differences but not altering the order. Shorter time to first fixation and longer fixation duration were the strongest predictors of desirability, demonstrating the combined influence of rapid visual capture and sustained attention. Within the tested stimulus set and viewing conditions, the proposed pipeline yields consistent preference rankings and an interpretable attention-based score that supports evidence-informed shortlisting of wardrobe-front materials. The reported relationships between gaze, affect, and choice are associative and are intended to guide design decisions within the scope of the present experimental settings. Full article

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36 pages, 1215 KB

Open AccessArticle

Conceptual Basis of Adaptation of a Field-Oriented Control System for Traction Induction Motors to the Operating Parameters of a Locomotive

by Vaidas Lukoševičius, Sergey Goolak, Ihor Derehuz, Larysa Neduzha, Artūras Keršys and Vytautas Dzerkelis

Energies 2026, 19(2), 298; https://doi.org/10.3390/en19020298 - 6 Jan 2026

Abstract

Field-oriented control (FOC) of induction motors (IMs) is used in railway rolling stock. In such control systems, a fixed frequency of the pulse-width modulation (PWM) inverter is used, which leads to an increase in power losses in the traction drive. To optimize power [...] Read more.

Field-oriented control (FOC) of induction motors (IMs) is used in railway rolling stock. In such control systems, a fixed frequency of the pulse-width modulation (PWM) inverter is used, which leads to an increase in power losses in the traction drive. To optimize power losses in the locomotive traction drive system, it is proposed to adapt the number of PWM inverter pulses to the frequency of the FOC speed controller, which is proportional to the locomotive speed. To solve this problem, conceptual foundations for adapting FOC to the locomotive speed have been developed, the key aspects of which are algorithms for adapting the PWM inverter frequency, the controller parameters and the parameters of the FOC speed controller frequency filters. The most significant results of the work are the methods for adjusting the maximum of the controllers of the basic FOC IM system, the filter structure and the inverter control scheme, adapted to the locomotive speed. The modeling results have shown the effectiveness of the proposed technical solutions. The proposed approach to developing FOC will allow minimizing the consumption of energy resources by the locomotive in the entire range of changes in its speed. Full article

(This article belongs to the Special Issue Forecasting and Optimization in Transport Energy Management Systems, 2nd Edition)

32 pages, 981 KB

Open AccessReview

AI in Parkinson’s Disease: A Short Review of Machine Learning Approaches for Diagnosis

by Arjita Sharma, Abhishek Agarwal, Michel Kalenga Wa Kalenga, Vishal Gupta and Vishal Srivastava

Processes 2026, 14(2), 199; https://doi.org/10.3390/pr14020199 - 6 Jan 2026

Abstract

Parkinson’s disease is a neurodegenerative disorder with progressive impairment in patients worldwide, featuring manifestations of both motor dysfunction and various/list-specific non-motor symptoms. Early diagnosis and personalized treatment thus remain the biggest challenges in managing the disease. Artificial intelligence (AI), especially machine learning techniques, [...] Read more.

Parkinson’s disease is a neurodegenerative disorder with progressive impairment in patients worldwide, featuring manifestations of both motor dysfunction and various/list-specific non-motor symptoms. Early diagnosis and personalized treatment thus remain the biggest challenges in managing the disease. Artificial intelligence (AI), especially machine learning techniques, has shown immense potential for countering such challenges during the past years. This short review aims to summarize recent innovations in applying Machine Learning (ML) and Deep Learning (DL) to Parkinson’s disease, explicitly directed toward developing diagnostic tools, the prediction of progression, and personalized treatment strategies. We discuss several ML and DL approaches, including supervised and unsupervised learning models that have been applied to classify symptoms and identify biomarkers. In addition, integrating clinical and imaging data into disease models continues to advance. This indicates the emerging role of DL in bypassing the limitations of standard methods. This review of the future of AI in Parkinson’s disease research outlines its possible directions for enhancing patient care and clinical outcomes. Full article

(This article belongs to the Section AI-Enabled Process Engineering)

23 pages, 1593 KB

Open AccessArticle

Research on the Coupling Coordination Degree and Obstacle Factors of Digital Inclusive Finance and Digital Agriculture in Rural China

by Lunqiu Huang, Jun Wen, Junzeng Liu and Dong Han

Agriculture 2026, 16(2), 144; https://doi.org/10.3390/agriculture16020144 - 6 Jan 2026

Abstract

In the context of advancing agricultural and rural modernization in China, digital agriculture has gained significant governmental attention. However, existing research has predominantly focused on examining the relationship from digital inclusive finance to digital agriculture, while in-depth investigations into their bidirectional coupled coordination, [...] Read more.

In the context of advancing agricultural and rural modernization in China, digital agriculture has gained significant governmental attention. However, existing research has predominantly focused on examining the relationship from digital inclusive finance to digital agriculture, while in-depth investigations into their bidirectional coupled coordination, spatiotemporal evolution, and underlying obstacle factors remain limited. To address this research gap, this study aims to construct innovative evaluation index systems for both domains and to establish a coupling coordination degree model alongside an obstacle degree model. This methodological framework is designed to examine the bidirectional coupled coordination, reveal its spatiotemporal evolution patterns, and identify key obstacle factors across 30 Chinese provinces. Results indicate a consistent annual improvement in the coupling coordination level across provinces. Many regions have progressed from moderate or mild dysfunction to marginal or primary coordination, with coordination degrees ranging between 0.5 and 0.6 by 2022. Specifically, the eastern region recorded 0.586, the central region 0.562, and the western region 0.531. Regional disparities are identified as the primary source of variation. Key obstacles include insufficient support from digital finance to agriculture, the east–west development gap, low actual usage of digital financial services, volatility in agricultural production price indices, and high agricultural carbon emissions. Recommendations focus on bridging regional gaps, strengthening financial support, and addressing these impediments, which are crucial for promoting sustainable development. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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