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24 pages, 3729 KiB  
Article
Multi-Source Heterogeneous Data Fusion Algorithm for Vessel Trajectories in Canal Scenarios
by Jiayu Zhang, Mei Wang, Ruixiang Kan and Zihang Xiong
Electronics 2025, 14(16), 3223; https://doi.org/10.3390/electronics14163223 (registering DOI) - 14 Aug 2025
Abstract
With the globalization of trade, maritime transport is playing an increasingly strategic role in sustaining international commerce. As a result, research into the tracking and fusion of multi-source vessel data in canal environments has become critical for enhancing maritime situational awareness. In the [...] Read more.
With the globalization of trade, maritime transport is playing an increasingly strategic role in sustaining international commerce. As a result, research into the tracking and fusion of multi-source vessel data in canal environments has become critical for enhancing maritime situational awareness. In the existing research and development, the heterogeneity of and variability in vessel flow data often lead to multiple issues in tracking algorithms, as well as in subsequent trajectory-matching processes. The existing tracking and matching frameworks typically suffer from three major limitations: insufficient capacity to extract fine-grained features from multi-source data; difficulty in balancing global context with local dynamics during multi-scale feature tracking; and an inadequate ability to model long-range temporal dependencies in trajectory matching. To address these challenges, this study proposes the Shape Similarity and Generalized Distance Adjustment (SSGDA) framework, a novel vessel trajectory-matching approach designed to track and associate multi-source heterogeneous vessel data in complex canal environments. The primary contributions of this work are summarized as follows: (1) an enhanced optimization strategy for trajectory fusion based on Enhanced Particle Swarm Optimization (E-PSO) designed for the proposed trajectory-matching framework; (2) the proposal of a trajectory similarity measurement method utilizing a distance-based reward–penalty mechanism, followed by empirical validation using the publicly available FVessel dataset. Comprehensive aggregation and analysis of the experimental results demonstrate that the proposed SSGDA method achieved a matching precision of 96.30%, outperforming all comparative approaches. Additionally, the proposed method reduced the mean-squared error between trajectory points by 97.82 pixel units. These findings further highlight the strong research potential and practical applicability of the proposed framework in real-world canal scenarios. Full article
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19 pages, 3876 KiB  
Article
Kinetics and Evolution Modeling of Hydrogen-Induced Cracking in Low-Carbon Steel
by Iván Mortera-Bravo, Jorge Luis González-Velázquez, Diego Israel Rívas-López and Manuel Alejandro Beltrán-Zuñiga
Materials 2025, 18(16), 3813; https://doi.org/10.3390/ma18163813 (registering DOI) - 14 Aug 2025
Abstract
The kinetics and evolution of hydrogen-induced cracking (HIC) were modeled using a theoretical model developed by Gonzalez to calculate the individual crack growth rate and a computational algorithm based on a Poisson distribution to generate the initial spatial distribution of HIC nuclei. Additionally, [...] Read more.
The kinetics and evolution of hydrogen-induced cracking (HIC) were modeled using a theoretical model developed by Gonzalez to calculate the individual crack growth rate and a computational algorithm based on a Poisson distribution to generate the initial spatial distribution of HIC nuclei. Additionally, the Monte Carlo method was used to model the interconnection of individual HIC cracks. The results of the computational model were compared versus experimental results of HIC induced by cathodic charging experiments in low-carbon steel plates. The model was capable of accurately emulating the kinetics of HIC, considering the first stage of nucleation and growth of randomly dispersed individual HIC cracks, followed by a second stage where the individual cracks interconnect with each other to form large cracks that subsequently grow. The study was complemented with the fractographic examination of the HIC cracks to verify if the fracture mechanism is consistent with the crack morphology and propagation mode in the proposed model. The results indicate that HIC propagation occurs by cleavage and quasi-cleavage mechanisms, with crack interconnection by ductile shear tearing, where the driving force for HIC is the accumulated hydrogen pressure within the internal HIC cracks, explaining why the crack growth rates are nearly constant in each stage of HIC growth. Full article
(This article belongs to the Special Issue Fracture and Fatigue in Metals and Alloys)
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14 pages, 880 KiB  
Article
Trends and Projections of the Prevalence of Diabetes Mellitus in Pregnancy and Fetal–Neonatal Metabolic Disorders, 2010–2035: A Nationwide Population-Based Study from Hungary
by Tímea Csákvári, Diána Elmer, Krisztina Palkovics, Luca Fanni Sántics-Kajos, Bettina Kovács, Kálmán Kovács, József Bódis and Imre Boncz
J. Clin. Med. 2025, 14(16), 5740; https://doi.org/10.3390/jcm14165740 (registering DOI) - 14 Aug 2025
Abstract
Objectives: Diabetes in pregnancy represents a significant public health concern with established impacts on both maternal and fetal health outcomes. Our aim was to evaluate the epidemiology of diabetes mellitus in pregnancy (DMP) and specific fetal and neonatal transient metabolic disorders (FNTMDs) [...] Read more.
Objectives: Diabetes in pregnancy represents a significant public health concern with established impacts on both maternal and fetal health outcomes. Our aim was to evaluate the epidemiology of diabetes mellitus in pregnancy (DMP) and specific fetal and neonatal transient metabolic disorders (FNTMDs) in Hungary between 2010 and 2024, as well as to project future trends through to 2035. Methods: We carried out a quantitative, retrospective study using nationwide real-world data from the Hungarian ‘Pulvita’ Health Data Warehouse. ICD-10 codes O24.0–O24.9 (DMP) and P70.0–P70.9 (FNTMDs) were included. Annual patient numbers, the number of hospital days, and the number of DMP patients per 1000 women aged 15–49, as well as the number of FNTMD patients per 1000 live births, were analyzed with joinpoint regression analysis and different forecasting models to project future prevalence up to 2035. Results: Despite a 14.2% decrease in live births, DMP cases increased significantly (54.9% inpatient, 26.6% outpatient), with GDM incidence per thousand reproductive-age women rising by 85.7%. FNTMD cases showed similar trends, with GDM-related infant syndromes more than doubling (154% increase). Projections indicate that DMP prevalence could reach 4.60 per 1000 reproductive-age women by 2035, while FNTMD cases show varying trends between inpatient (increasing) and outpatient (stabilizing) care. Conclusions: These findings demonstrate a continuing upward trend in diabetes-related pregnancy complications, despite shorter hospital stays, suggesting an urgent need for enhanced preventive programs and specialized care service planning. Full article
(This article belongs to the Special Issue Epidemiology of Hyperglycemia in Pregnancy and Its Maternofetal Adverse Outcomes)
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21 pages, 971 KiB  
Article
Lightning Nowcasting Using Dual-Polarization Weather Radar and Machine Learning Approaches: Evaluation of Feature Engineering Strategies and Operational Integration
by Marcos Antonio Alves, Rosana Alves Molina, Bruno Alberto Soares Oliveira, Daniel Calvo, Marcos Cesar Andrade Araujo Filho, Douglas Batista da Silva Ferreira, Ana Paula Paes Santos, Ivan Saraiva, Osmar Pinto, Jr. and Eugenio Lopes Daher
Climate 2025, 13(8), 168; https://doi.org/10.3390/cli13080168 (registering DOI) - 14 Aug 2025
Abstract
Lightning nowcasting is crucial for ensuring safety and operational continuity in weather-exposed industries such as mining. This study evaluates three machine learning (ML)-based approaches for predicting lightning using dual-polarimetric weather radar data collected in the eastern Amazon, Brazil. The strategies propose advances in [...] Read more.
Lightning nowcasting is crucial for ensuring safety and operational continuity in weather-exposed industries such as mining. This study evaluates three machine learning (ML)-based approaches for predicting lightning using dual-polarimetric weather radar data collected in the eastern Amazon, Brazil. The strategies propose advances in literature in three ways by involving (i) grouping radar variables by temperature layers, (ii) statistical summaries at key altitudes, and (iii) analyzing all the 18 levels of reflectivity data combined with Principal Component Analysis (PCA) dimensionality reduction and ensemble models. For each approach, models such as Random Forest, Support Vector Machines, and XGBoost were trained and tested using data from 2021–2022 with class balancing and feature engineering techniques. Among the approaches, the PCA-based ensemble achieved the best generalization (recall = 0.89, F1 = 0.77), while the layer-based method had the highest recall (0.97), and the altitude-based strategy offered a computationally efficient alternative with competitive results. These findings confirm the predictive value of radar-derived features and emphasize the role of feature representation in model performance. Additionally, the best model was integrated into the operational LEWAIS alert system, and four integration strategies were tested. The strategy that combined alerts from both ML and LEWAIS systems reduced the failure-to-warn rate to 0.0531 and increased the lead time to 10.18 min, making it ideal for safety-critical applications. Overall, the results show that ML models based solely on radar inputs can achieve robust lightning nowcasting, supporting both scientific advancement and industrial risk mitigation. Full article
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19 pages, 6304 KiB  
Article
Digital Image Processing and Convolutional Neural Network Applied to Detect Mitral Stenosis in Echocardiograms: Clinical Decision Support
by Genilton de França Barros Filho, José Fernando de Morais Firmino, Israel Solha, Ewerton Freitas de Medeiros, Alex dos Santos Felix, José Carlos de Lima Júnior, Marcelo Dantas Tavares de Melo and Marcelo Cavalcanti Rodrigues
J. Imaging 2025, 11(8), 272; https://doi.org/10.3390/jimaging11080272 (registering DOI) - 14 Aug 2025
Abstract
The mitral valve is the most susceptible to pathological alterations, such as mitral stenosis, characterized by failure of the valve to open completely. In this context, the objective of this study was to apply digital image processing (DIP) and develop a convolutional neural [...] Read more.
The mitral valve is the most susceptible to pathological alterations, such as mitral stenosis, characterized by failure of the valve to open completely. In this context, the objective of this study was to apply digital image processing (DIP) and develop a convolutional neural network (CNN) to provide decision support for specialists in the diagnosis of mitral stenosis based on transesophageal echocardiography examinations. The following procedures were implemented: acquisition of echocardiogram exams; application of DIP; use of augmentation techniques; and development of a CNN. The DIP classified 26.7% cases without stenosis, 26.7% with mild stenosis, 13.3% with moderate stenosis, and 33.3% with severe stenosis. A CNN was initially developed to classify videos into those four categories. However, the number of acquired exams was insufficient to effectively train the model for this purpose. So, the final model was trained to differentiate between videos with or without stenosis, achieving an accuracy of 92% with a loss of 0.26. The results demonstrate that both DIP and CNN are effective in distinguishing between cases with and without stenosis. Moreover, DIP was capable of classifying varying degrees of stenosis severity—mild, moderate, and severe—highlighting its potential as a valuable tool in clinical decision support. Full article
(This article belongs to the Section Medical Imaging)
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19 pages, 11068 KiB  
Article
A Deep Learning Approach for Classifying Developmental Stages of Ixodes ricinus Ticks on Images Captured Using a Microscope’s High-Resolution CMOS Sensor
by Aleksandra Marzec, Anna Filipowska, Oliwia Humeniuk, Wojciech Filipowski and Paweł Raif
Sensors 2025, 25(16), 5038; https://doi.org/10.3390/s25165038 (registering DOI) - 14 Aug 2025
Abstract
This article presents a deep learning approach for classifying the developmental stages (larvae, nymphs, adult females, and adult males) of Ixodes ricinus ticks, the most common tick species in Europe and a major vector of tick-borne pathogens, including Borrelia burgdorferi, Anaplasma phagocytophilum [...] Read more.
This article presents a deep learning approach for classifying the developmental stages (larvae, nymphs, adult females, and adult males) of Ixodes ricinus ticks, the most common tick species in Europe and a major vector of tick-borne pathogens, including Borrelia burgdorferi, Anaplasma phagocytophilum, and tick-borne encephalitis virus (TBEV). Each developmental stage plays a different role in disease transmission, with nymphs considered the most epidemiologically relevant stage due to their small size and high prevalence. We developed a convolutional neural network (CNN) model trained on a dataset of microscopic tick images collected in the area of Upper Silesia, Poland. Grad-CAM, an XAI technique, was used to identify the regions of the image that most influenced the model’s decisions. This work is the first to utilize a CNN model for the identification of European tick fauna stages. Compared to existing solutions focused on North American tick species, our model addresses the specific challenge of distinguishing developmental stages within I. ricinus. This solution has the potential to be a valuable tool in entomology, healthcare, and tick-borne disease management. Full article
(This article belongs to the Section Sensing and Imaging)
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24 pages, 6242 KiB  
Article
Study on Fatigue Crack Propagation Behavior of Fiber/Al-Li Laminates Under Typical Overload
by Weiying Meng, Jiayi Tan, Sihui Li, Xiao Huang and Jiaying Wang
Materials 2025, 18(16), 3812; https://doi.org/10.3390/ma18163812 (registering DOI) - 14 Aug 2025
Abstract
Fiber metal laminates are applied in aerospace equipment due to their excellent crack propagation performance. However, during the service process of fiber metal laminates, the coupling between overload effect and fiber bridging effect makes the crack propagation behavior complex, which makes it difficult [...] Read more.
Fiber metal laminates are applied in aerospace equipment due to their excellent crack propagation performance. However, during the service process of fiber metal laminates, the coupling between overload effect and fiber bridging effect makes the crack propagation behavior complex, which makes it difficult to predict. Addressing this issue, the fatigue crack propagation behavior of Fiber/Al-Li laminates under typical overload conditions was analyzed and predicted in this paper. Firstly, based on flight loading characteristics, fatigue crack propagation tests under constant amplitude and single-peak tensile/compressive overload were designed and conducted for Fiber/Al-Li laminates. The crack propagation behavior characteristics under typical overload conditions were analyzed and investigated. Secondly, the influence mechanism of thickness dimensions was revealed based on fatigue crack propagation characteristics under constant amplitude loading. A thickness size effect factor was introduced to improve the equivalent crack length model, where the crack propagation behavior of non-overload stages was simulated. Thirdly, improved Wheeler theory was adopted to characterize the overload hysteresis effect in the hysteresis zone under tensile overload; improved incremental plasticity theory was used to describe crack propagation behavior in the overload zone under compression overload. Finally, based on crack behavior characteristics under single-peak tensile and compressive overloads, the improved equivalent crack length model was combined to establish, respectively, the prediction models on crack propagation behavior under single-peak tensile and compressive overloads for Fiber/Al-Li laminates. Through experimental verification, the overall prediction error rate of the crack propagation model under tensile overload is up to 9.7%, and the overall prediction error rate of the crack growth model under compressive overload is up to 8.1%. Compared with similar models (not found) for thicker fiber metal laminates, the effectiveness and advancement of the proposed model are verified. Full article
(This article belongs to the Special Issue Dynamic Behavior of Advanced Materials and Structures (Second Edition))
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11 pages, 5480 KiB  
Article
A 5 kW Near-Single-Mode Oscillating–Amplifying Fiber Laser Employing a Broadband Output Coupler with Simultaneous Raman Suppression and Spectral Narrowing
by Jiazheng Wu, Miao Yu, Yi Cao, Shiqi Jiang, Shihao Sun and Junlong Wang
Photonics 2025, 12(8), 813; https://doi.org/10.3390/photonics12080813 (registering DOI) - 14 Aug 2025
Abstract
In this work, we propose and demonstrate a novel approach to suppressing stimulated Raman scattering in an oscillating–amplifying integrated fiber laser (OAIFL) by changing the spectral bandwidth of the output-coupler fiber Bragg gratings (OC-FBGs). The reflectance bandwidth of the fiber Bragg grating (FBG) [...] Read more.
In this work, we propose and demonstrate a novel approach to suppressing stimulated Raman scattering in an oscillating–amplifying integrated fiber laser (OAIFL) by changing the spectral bandwidth of the output-coupler fiber Bragg gratings (OC-FBGs). The reflectance bandwidth of the fiber Bragg grating (FBG) in the oscillating section was systematically investigated as a critical parameter for SRS mitigation. Three types of long-period FBGs with distinct reflectance bandwidths (1.2 nm, 1.3 nm, and 2 nm) were comparatively studied as output couplers. The experimental results demonstrated a direct correlation between FBG bandwidth and SRS suppression efficiency, with the configuration of the OC-FBG with a 2 nm bandwidth achieving optimal suppression performance. Concurrently, the output power was enhanced to 5.02 kW with improved power scalability. And excellent beam quality was obtained with M2 < 1.3. Remarkably, in the architecture of this laser, increasing the bandwidth of the output couplers in the oscillating section had a relatively minor effect on the optical-to-optical (O-O) efficiency, which reached up to 78%. Additionally, this modification also reduced the 3 dB bandwidth of the laser output, thereby achieving a beam output with enhanced monochromaticity. Full article
(This article belongs to the Special Issue High-Power Fiber Lasers)
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15 pages, 2345 KiB  
Article
Design and Verification of Beam Diagnostics System for Pepper-Pot Method
by Xianfang Bao, Peng Lu, Renli Zhu, Yuzhong Qian, Lizhen Liang and Lan Tian
Appl. Sci. 2025, 15(16), 8952; https://doi.org/10.3390/app15168952 (registering DOI) - 14 Aug 2025
Abstract
The pepper-pot method is a beam diagnostics technique used to measure the transverse beam profile, divergence angle, and envelope in particle accelerators. However, its practical application faces challenges, such as insufficient point recognition accuracy and signal quality degradation in complex environments. Based on [...] Read more.
The pepper-pot method is a beam diagnostics technique used to measure the transverse beam profile, divergence angle, and envelope in particle accelerators. However, its practical application faces challenges, such as insufficient point recognition accuracy and signal quality degradation in complex environments. Based on the Boron Neutron Capture Therapy (BNCT) facility at the Hefei Comprehensive National Science Center—Energy Research Institute (Anhui Energy Laboratory), this study developed an improved pepper-pot beam diagnostics system to optimize the beam quality of the accelerator ion source. The key innovation is adaptive threshold segmentation for spot segmentation, and the experimental results indicate that the enhanced image segmentation method outperforms traditional methods in terms of segmentation accuracy and robustness. Full article
(This article belongs to the Section Applied Physics General)
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14 pages, 3633 KiB  
Article
Insecticide Resistance Evolution Negatively Affects the Fitness of Aphis gossypii Glover During Selection on Cotton Plants Under Laboratory Conditions
by Hina Gul, Ali Güncan, Arzlan Abbas, Zeeshan Ullah, Xie Yuqing, Farman Ullah, Nicolas Desneux and Xiaoxia Liu
Plants 2025, 14(16), 2527; https://doi.org/10.3390/plants14162527 (registering DOI) - 14 Aug 2025
Abstract
The cotton aphid, Aphis gossypii Glover, is among the most economically significant sap-sucking insect pests, inflicting substantial economic losses worldwide. Insecticides such as thiamethoxam, bifenthrin, and flonicamid are commonly used to manage this pest, despite the inherent risk of developing resistance. In this [...] Read more.
The cotton aphid, Aphis gossypii Glover, is among the most economically significant sap-sucking insect pests, inflicting substantial economic losses worldwide. Insecticides such as thiamethoxam, bifenthrin, and flonicamid are commonly used to manage this pest, despite the inherent risk of developing resistance. In this study, we investigated the evolution of insecticide resistance in A. gossypii after continuous selection with thiamethoxam, bifenthrin, and flonicamid over more than ten generations in a controlled laboratory environment. We assessed the fitness of resistant strains using an age-stage, two-sex life table approach, comparing them to a susceptible population. The results indicated that A. gossypii achieved resistance levels of 158.60-fold against thiamethoxam, 129.18-fold against bifenthrin, and 104.75-fold against flonicamid. Furthermore, life table analyses revealed that the developmental stages were significantly extended, while longevity decreased in all resistant strains compared to the susceptible population. Additionally, the net reproductive rate (R0), fecundity, and reproductive days were notably reduced in the resistant cohorts when compared to the susceptible strain. Overall, these findings provide valuable insights into the laboratory-induced evolution of insecticide resistance and the associated fitness costs in A. gossypii when feeding on cotton plants. This information could be instrumental in formulating effective resistance management strategies to control this significant pest. Full article
(This article belongs to the Section Plant Protection and Biotic Interactions)
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14 pages, 19891 KiB  
Article
Investigating Surface Morphology and Subsurface Damage Evolution in Nanoscratching of Single-Crystal 4H-SiC
by Jianpu Xi, Xinxing Ban, Zhen Hui, Wenlan Ba, Lijuan Deng and Hui Qiu
Micromachines 2025, 16(8), 935; https://doi.org/10.3390/mi16080935 (registering DOI) - 14 Aug 2025
Abstract
Single-crystal 4H silicon carbide (4H-SiC) is a key substrate material for third-generation semiconductor devices, where surface and subsurface integrity critically affect performance and reliability. This study systematically examined the evolution of surface morphology and subsurface damage (SSD) during nanoscratching of 4H-SiC under varying [...] Read more.
Single-crystal 4H silicon carbide (4H-SiC) is a key substrate material for third-generation semiconductor devices, where surface and subsurface integrity critically affect performance and reliability. This study systematically examined the evolution of surface morphology and subsurface damage (SSD) during nanoscratching of 4H-SiC under varying normal loads (0–100 mN) using a nanoindenter equipped with a diamond Berkovich tip. Scratch characteristics were assessed using scanning electron microscopy (SEM), while cross-sectional SSD was characterised via focused ion beam (FIB) slicing and transmission electron microscopy (TEM). The results revealed three distinct material removal regimes: ductile removal below 14.5 mN, a brittle-to-ductile transition between 14.5–59.3 mN, and brittle removal above 59.3 mN. Notably, substantial subsurface damage—including median cracks exceeding 4 μm and dislocation clusters—was observed even within the transition zone where the surface appeared smooth. A thin amorphous layer at the indenter-substrate interface suppressed immediate surface defects but promoted subsurface damage nucleation. Crack propagation followed slip lines or their intersections, demonstrating sensitivity to local stress states. These findings offer important insights into nanoscale damage mechanisms, which are essential for optimizing precision machining processes to minimise SSD in SiC substrates. Full article
(This article belongs to the Special Issue Ultra-Precision Surface Abrasive Micro-Machining: Advances and Applications)
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21 pages, 1608 KiB  
Article
Predicting Efficiency and Capacity of Drag Embedment Anchors in Sand Seabed Using Tree Machine Learning Algorithms
by Mojtaba Olyasani, Hamed Azimi and Hodjat Shiri
Geotechnics 2025, 5(3), 56; https://doi.org/10.3390/geotechnics5030056 (registering DOI) - 14 Aug 2025
Abstract
Drag embedment anchors (DEAs) play a vital role in maintaining the stability and safety of offshore structures, including floating wind turbines, oil rigs, and marine renewable energy systems. Accurate prediction of anchor performance is essential for optimizing mooring system designs, reducing costs, and [...] Read more.
Drag embedment anchors (DEAs) play a vital role in maintaining the stability and safety of offshore structures, including floating wind turbines, oil rigs, and marine renewable energy systems. Accurate prediction of anchor performance is essential for optimizing mooring system designs, reducing costs, and minimizing risks in challenging marine environments. By leveraging advanced machine learning techniques, this research provides innovative solutions to longstanding challenges in geotechnical engineering, paving the way for more efficient and reliable offshore operations. The findings contribute significantly to developing sustainable marine infrastructure while addressing the growing global demand for renewable energy solutions in coastal and deep-water environments. This current study evaluated tree-based machine learning algorithms, e.g., decision tree regression (DTR) and random forest regression (RFR), to predict the holding capacity and efficiency of DEAs in sand seabed. To train and validate the results of machine learning models, the K-fold cross-validation method, with K = 5, was utilized. Eleven geotechnical and geometric parameters, including sand friction angle (φ), fluke-shank angle (α), and anchor dimensions, were analyzed using 23 model configurations. Results demonstrated that RFR outperformed DTR, achieving the highest accuracy for capacity prediction (R = 0.985, RMSE = 344.577 KN) and for efficiency (R = 0.977, RMSE = 0.821 KN). Key findings revealed that soil strength dominated capacity, while fluke-shank angle critically influenced efficiency. Single-parameter models failed to capture complex soil-anchor interactions, underscoring the necessity of multivariate analysis. The ensemble approach of RFR provided superior generalization across diverse seabed conditions, maintaining errors within ±10% for capacity and ±5% for efficiency. Full article
(This article belongs to the Special Issue Recent Developments in the Machine Learning Modeling of Geotechnical Data)
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20 pages, 6817 KiB  
Review
A Review of Jurassic Paleoclimatic Changes and Tectonic Evolution in the Qaidam Block, Northern Qinghai-Tibetan Plateau
by Ruiyang Chai, Yanan Zhou, Anliang Xiong, Zhenwei Chen, Dongwei Liu, Nan Jiang, Xin Cheng, Jingong Zhang and Hanning Wu
Sustainability 2025, 17(16), 7337; https://doi.org/10.3390/su17167337 (registering DOI) - 14 Aug 2025
Abstract
Understanding the mechanisms and speed of paleo-aridification in the Qaidam Block—driven by tectonic uplift and shifts in atmospheric circulation—provides critical long-term context for assessing modern climate variability and anthropogenic impacts on water resources and desertification. This knowledge is essential for informing sustainable development [...] Read more.
Understanding the mechanisms and speed of paleo-aridification in the Qaidam Block—driven by tectonic uplift and shifts in atmospheric circulation—provides critical long-term context for assessing modern climate variability and anthropogenic impacts on water resources and desertification. This knowledge is essential for informing sustainable development strategies. We reconstruct the post-Triassic–Jurassic extinction tectonic-climatic evolution of the Qaidam Block on the northern Qinghai-Tibet Plateau margin through an integrated analysis of sedimentary facies, palynological assemblages, and Chemical Index of Alteration values from Late Triassic to Jurassic strata. The Indo-Eurasian convergence drove the uplift of the East Kunlun Orogen and strike-slip movement along the Altyn Tagh Fault, establishing a basin-range system. During the initial Late Triassic to Early Jurassic period, warm-humid conditions supported gymnosperm/fern-dominated ecosystems and facilitated coal formation. A Middle Jurassic shift from extensional to compressional tectonics coincided with a climatic transition from warm-humid, through cold-arid, to hot-arid states. This aridification, evidenced by a Bathonian-stage surge in drought-tolerant Classopollis pollen and a sharp decline in Chemical Index of Alteration values, intensified in the Late Jurassic due to the Yanshanian orogeny and distal subduction effects. Resultant thrust-strike-slip faulting and southeastward depocenter migration, under persistent aridity and intensified atmospheric circulation, drove widespread development of aeolian dune systems (e.g., Hongshuigou Formation) and arid fluvial-lacustrine environments. The tectonic-climate-ecosystem framework reveals how Jurassic tectonic processes amplified feedback to accelerate aridification. This mechanism provides a critical geological analog for addressing the current sustainability challenges facing the Qaidam Basin. Full article
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18 pages, 1463 KiB  
Article
Breed-Specific Responses of Rabbit Semen to Chilling Storage: Sperm Quality, Acrosome Status, and Oxidative Stress Biomarkers
by Ibtissem Boulbina, Mohammed El Amine Bekara, Hacina AinBaziz, Simona Mattioli and Cesare Castellini
Animals 2025, 15(16), 2384; https://doi.org/10.3390/ani15162384 (registering DOI) - 14 Aug 2025
Abstract
Artificial insemination (AI) in rabbits depends largely on chilled semen storage, but the physiological responses to chilling and associated biochemical changes in seminal plasma (SP) remain poorly understood, particularly across breeds. This study aimed to compare the semen preservation capacity of Algerian local [...] Read more.
Artificial insemination (AI) in rabbits depends largely on chilled semen storage, but the physiological responses to chilling and associated biochemical changes in seminal plasma (SP) remain poorly understood, particularly across breeds. This study aimed to compare the semen preservation capacity of Algerian local population (LAP) and New Zealand White (NZW) rabbits and to explore the relationship between SP oxidative stress biomarkers and sperm traits during 72 h of chilled storage at 5 °C. Semen pools (nine/breed) were evaluated at 0, 4, 24, 48, and 72 h for motility, viability, and acrosome status. Oxidative stress markers were also assessed in the SP, including malondialdehyde (MDA), reactive oxygen metabolites (ROMs), superoxide dismutase (SOD), glutathione peroxidase (GPX), and catalase (CAT). LAP sperm showed higher motility (p < 0.001) and viability (p < 0.05), particularly between 4 h and 48 h, and exhibited a lower rate of acrosome reaction (p < 0.001) from 48 h to 72 h. Lower SOD and higher CAT activity in LAP (p < 0.001), correlated with MDA and acrosome status, respectively, may reflect a more balanced antioxidant response. Lipid peroxidation did not appear to be the main factor driving sperm deterioration (p > 0.05). These results demonstrate that LAP rabbits exhibit better resilience to chilled storage compared to NZW and highlight the potential value of CAT and SOD activities as indicators of sperm resilience during chilled storage. Further studies are required to validate and extend these findings, with the aim of improving semen preservation strategies. Full article
(This article belongs to the Section Animal Reproduction)
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24 pages, 9802 KiB  
Article
Threshold Dynamics of Vegetation Carbon Sink Loss Under Multiscale Droughts in the Mongolian Plateau
by Hongguang Chen, Mulan Wang, Fanhao Meng, Chula Sa, Min Luo, Wenfeng Chi and Sonomdagva Chonokhuu
Atmosphere 2025, 16(8), 964; https://doi.org/10.3390/atmos16080964 (registering DOI) - 14 Aug 2025
Abstract
Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics [...] Read more.
Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics and regional differentiation of GPP responses to the synergistic effects of meteorological drought (MD) and soil moisture drought (SD), particularly in the drought-sensitive Mongolian Plateau. This study focuses on the Mongolian Plateau from 1982 to 2021, using the standardized precipitation index (SPI) and standardized soil moisture index (SSI) to characterize MD and SD, respectively. The study combines the three-threshold run theory, cross-wavelet analysis, Spearman correlation analysis, and copula models to systematically investigate the variation characteristics, propagation patterns, and the probability and thresholds for triggering GPP loss under different time scales (monthly, seasonal, semi-annual, and annual). The results show that (1) both types of droughts exhibited significant intensification trends, with SD intensifying at a faster rate (annual scale SSI12 trend: −0.34/10a). The intensification trend strengthened with increasing time scales. MD exhibited high frequency, short duration, and low intensity, while SD showed the opposite characteristics. The most significant aridification occurred in the central region. (2) The average propagation time from MD to SD was 11.22 months. The average response time of GPP to MD was 10.46 months, while the response time to SD was significantly shorter (approximately 2 months on average); the correlation between SSI and GPP was significantly higher than that between SPI and GPP. (3) The conditional probability of triggering mild GPP loss (e.g., <40th percentile) was relatively high for both drought types, and the probability of loss increased as the time scales extended. Compared to MD, SD was more likely to induce severe GPP loss. Additionally, the drought intensity threshold for triggering mild loss was lower (i.e., mild drought could trigger it), while higher drought intensity was required to trigger severe and extreme losses. Therefore, this study provides practical guidance for regional drought early-warning systems and ecosystem adaptive management, while laying an important theoretical foundation for a deeper understanding of drought response mechanisms. Full article
(This article belongs to the Special Issue The Response of Plateau Vegetation to Climatic and Anthropogenic Drivers)
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17 pages, 273 KiB  
Article
The Parallels Between the Glossolalia and the Theatre of the Absurd
by Antonia Čačić
Religions 2025, 16(8), 1052; https://doi.org/10.3390/rel16081052 (registering DOI) - 14 Aug 2025
Abstract
The primary focus of this article is on the deconstruction of language within the context of glossolalia and the Theatre of the Absurd. Following World War II, the expression of absurdity in the literature and theatre gave rise to the Theatre of the [...] Read more.
The primary focus of this article is on the deconstruction of language within the context of glossolalia and the Theatre of the Absurd. Following World War II, the expression of absurdity in the literature and theatre gave rise to the Theatre of the Absurd as an anti-literary movement. Glossolalia appears both in the first Christian communities and within the charismatic renewal movement in modern times and refers to the gift of speaking in tongues. The objective of comparing these two occurrences is to identify their similarities and differences in their treatment of the language. Both glossolalia and the Theatre of the Absurd contain destructive aspects as they disintegrate language, but they also contain creative elements; glossolalia is prayer, and the Theatre of the Absurd has artistic merit. To consider the extent to which language deconstruction might serve as a prelude to creative endeavours, this analogy appears to be significant. Full article
(This article belongs to the Section Religions and Humanities/Philosophies)
11 pages, 734 KiB  
Article
Hereditary Transthyretin Amyloidosis: Genetic Characterization of the TTR P.Val142Ile Variant in a Calabrian Kindred
by Francesca Dinatolo, Radha Procopio, Valentina Rocca, Elisa Lo Feudo, Adele Dattola, Lucia D’Antona, Fernanda Fabiani, Emma Colao, Rosario Amato, Francesco Trapasso, Giuseppe Viglietto and Rodolfo Iuliano
Genes 2025, 16(8), 960; https://doi.org/10.3390/genes16080960 (registering DOI) - 14 Aug 2025
Abstract
Background: Hereditary transthyretin amyloidosis (ATTRv) is a systemic disorder caused by homozygosity or compound heterozygosity for pathogenic mutations in the TTR gene, leading to destabilization of the transthyretin tetramer, misfolding of monomers, and subsequent amyloid fibril deposition. Among over 150 known TTR variants, [...] Read more.
Background: Hereditary transthyretin amyloidosis (ATTRv) is a systemic disorder caused by homozygosity or compound heterozygosity for pathogenic mutations in the TTR gene, leading to destabilization of the transthyretin tetramer, misfolding of monomers, and subsequent amyloid fibril deposition. Among over 150 known TTR variants, p.Val142Ile is particularly associated with late-onset cardiac involvement and is the most prevalent amyloidogenic mutation in individuals of African and, to a lesser extent, European descent. This study reports the identification and familial segregation of the p.Val142Ile mutation in a large multigenerational family from Calabria (Southern Italy). Methods: Genomic DNA was extracted from peripheral blood, and Sanger sequencing of the TTR gene was performed in the proband and extended family. Results: The proband was a 75-year-old man with clinical features suggestive of cardiac amyloidosis. Genetic testing revealed homozygosity for the TTR p.Val142Ile variant. Family screening revealed multiple heterozygous carriers across three generations, most of whom were asymptomatic. Discussion: This is the first report of a native Calabrian family carrying this variant, previously unreported in this region, where p.Phe84Leu was considered the only endemic TTR mutation. Our findings expand the mutational landscape of ATTRv in Southern Italy and highlight the presence of p.Val142Ile in a previously unrecognized geographic area. These results reinforce the importance of including TTR sequencing in the work-up of unexplained cardiomyopathy, particularly in Southern Italy, where atypical variants may be emerging. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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15 pages, 1864 KiB  
Article
Interaction Between Two Independent Chaotic Neural Networks Installed in the Motion Control Systems of Two Roving Robots
by Shigetoshi Nara, Naoya Miyahara, Yutaka Yamaguti and Ichiro Tsuda
Dynamics 2025, 5(3), 32; https://doi.org/10.3390/dynamics5030032 (registering DOI) - 14 Aug 2025
Abstract
The high-dimensional chaos generated in a neural network consisting of pseudo-neuron devices invented by one of the authors (S.N.) has been successfully applied to control the complex motion of a roving robot, e.g., to solve a maze, as reported in the previous papers. [...] Read more.
The high-dimensional chaos generated in a neural network consisting of pseudo-neuron devices invented by one of the authors (S.N.) has been successfully applied to control the complex motion of a roving robot, e.g., to solve a maze, as reported in the previous papers. On the basis of successful works and the concept that chaos plays important functional roles in biological systems, in the present paper, we report new experiments to show the functional aspects of chaos via behavioral interactions in an ill-posed context and solve problems with chaotic neural networks. Explicitly, experiments on two roving robots in a maze (labyrinth) are reported, in which both seek to catch each other or one chases and the other flees, mimicking the survival activities of insects in natural environments. The two-dimensional robot motion is controlled with motion control systems, each of which is equipped with a chaotic neural network to generate autonomous and adaptive actions depending on sensor inputs of obstacles and/or target detection information including uncertainty. We report both computer experiments and practical hardware implementations, where for the latter, only the chaotic neural network is run on a desktop computer, the motion signals are coded into two-dimensional space, and sensor signals are transferred via Bluetooth device between robots and computers. Full article
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9 pages, 271 KiB  
Article
Electrophysiological Evidence of Contralateral Neuromuscular Effects Following Long-Term Botulinum Toxin Therapy in Hemifacial Spasm
by Tehran Aliyeva, Mehmet Fevzi Oztekin, Yasemin Eren and Zeynep Nese Oztekin
Toxins 2025, 17(8), 407; https://doi.org/10.3390/toxins17080407 (registering DOI) - 14 Aug 2025
Abstract
Hemifacial spasm (HFS) is a cranial nerve disorder characterized by involuntary contractions of muscles innervated by the facial nerve. Botulinum toxin type A (BoNT-A) is widely used for symptom control. Although local diffusion is well established, the extent and clinical relevance of BoNT-A [...] Read more.
Hemifacial spasm (HFS) is a cranial nerve disorder characterized by involuntary contractions of muscles innervated by the facial nerve. Botulinum toxin type A (BoNT-A) is widely used for symptom control. Although local diffusion is well established, the extent and clinical relevance of BoNT-A spread to contralateral muscles remain unclear. This study aimed to investigate the contralateral neuromuscular effects of BoNT-A in patients undergoing long-term treatment with BoNT-A. This retrospective cross-sectional study included 39 patients with HFS (mean age, 58.6 ± 8.5 years). Bilateral compound muscle action potentials (CMAPs) were recorded before and four weeks after the BoNT-A injection. Single-fiber electromyography (SFEMG) jitter and mean consecutive difference (MCD) were evaluated contralaterally using concentric needle electrodes. Patients were categorized as first-time (n = 10) or long-term (n = 29; treatment duration: 1–20 years) BoNT-A recipients. Contralateral CMAP amplitudes decreased by 21.1% post-injection (p < 0.001). MCD increased from 33.2 ± 5.6 to 37.0 ± 5.3 µs (p < 0.001), and jitter rose by 81%, from 7.9 ± 6.2 to 14.3 ± 8.1 µs (p < 0.001). The percentage increase in MCD was significantly higher in long-term versus first-time patients (12.7% vs. 7.5%; p = 0.039), suggesting a cumulative neuromuscular effect. Spontaneous myokymia or fasciculations were clinically observed in four long-term patients. These findings provide electrophysiological evidence that unilateral BoNT-A injections may induce neuromuscular transmission abnormalities in the contralateral facial muscles. This effect appears more pronounced in chronically treated individuals, highlighting the need for awareness of potential bilateral spread when planning long-term therapy. Full article
(This article belongs to the Special Issue Advances in the Treatment of Movement Disorders with Botulinum Toxins)
18 pages, 1014 KiB  
Article
Antimicrobial Activity of Ethyl (2-(Methylcarbamoyl)phenyl)carbamate and Its Mixed Ligand Ni(II) and Co(II) Complexes
by Slava Tsoneva, Miglena Milusheva, Nikola Burdzhiev, Petya Marinova, Evelina Varbanova, Yulian Tumbarski, Rositsa Mihaylova, Emiliya Cherneva and Stoyanka Nikolova
Inorganics 2025, 13(8), 267; https://doi.org/10.3390/inorganics13080267 (registering DOI) - 14 Aug 2025
Abstract
The aim of this paper is to obtain ethyl (2-(methylcarbamoyl)phenyl)carbamate and its metal complexes as promising antimicrobial agents. The title compound was synthesized using the ring-opening of isatoic anhydride with methylamine and further acylation with ethyl chloroformate. All metal complexes were successfully obtained [...] Read more.
The aim of this paper is to obtain ethyl (2-(methylcarbamoyl)phenyl)carbamate and its metal complexes as promising antimicrobial agents. The title compound was synthesized using the ring-opening of isatoic anhydride with methylamine and further acylation with ethyl chloroformate. All metal complexes were successfully obtained after mixing the ligand dissolved in DMSO and water solutions of the corresponding metal salts and sodium hydroxide, in a metal-to-ligand-to base ratio 1:2:2. As a result, mixed ligand complexes of ethyl 2-(methylcarbamoyl)phenyl)carbamate and 3-methylquinazoline-2,4(1H,3H)-dione were obtained. The obtained complexes were characterized by their melting points, FTIR, NMR spectroscopy, and MP-AES. Then, the antimicrobial effect of the compounds against both Gram-negative and Gram-positive bacteria, yeasts, and fungi was studied. Only the Co(II) complex showed antimicrobial activity against almost all Gram-positive and Gram-negative bacteria. The cobalt complex exhibited promising antimicrobial activity against Gram-positive Micrococcus luteus with inhibition zones of 20 mm, Listeria monocytogenes (15 mm), Staphylococcus aureus (13 mm), as well as Gram-negative Klebsiella pneumoniae (13 mm) and Proteus vulgaris (13 mm). Given the potential of metal complexes as antimicrobial agents, understanding their cytotoxic effects is crucial for evaluating their therapeutic safety. To assess the in vitro biocompatibility of the experimental compounds, a range of cell viability assays was conducted using human malignant leukemic cell lines (LAMA-84, K-562) and normal murine fibroblast cells (CCL-1). The Ni(II) complex shows IC50 = 105.1 µM against human malignant leukemic cell lines LAMA-84. Based on the reported results, it may be concluded that the mixed cobalt complex of 2-(methylcarbamoyl)phenyl)carbamate and 3-methylquinazoline-2,4(1H,3H)-dione can be attributed as a promising antimicrobial agent. Future in vivo tests will contribute to establishing the antimicrobial properties of this complex. Full article
(This article belongs to the Special Issue Synthesis, Structural Analysis and Biological Activity of Metal Complexes)
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23 pages, 1140 KiB  
Review
Hypersensitivity to Folic Acid and/or Folinic Acid—A Review of Clinical Cases, Potential Mechanism, Possible Cross-Allergies and Current Diagnostic Options
by Kinga Lis
Curr. Issues Mol. Biol. 2025, 47(8), 654; https://doi.org/10.3390/cimb47080654 (registering DOI) - 14 Aug 2025
Abstract
Folic acid and its derivatives (e.g., folinic acid) are a group of water-soluble compounds collectively known as vitamin B9. Synthetic folic acid is a component of dietary supplements, medications and other pharmaceuticals and fortified foods. Folinic acid (5-formyltetrahydrofolic acid) is the active metabolite [...] Read more.
Folic acid and its derivatives (e.g., folinic acid) are a group of water-soluble compounds collectively known as vitamin B9. Synthetic folic acid is a component of dietary supplements, medications and other pharmaceuticals and fortified foods. Folinic acid (5-formyltetrahydrofolic acid) is the active metabolite of folic acid. It is used to treat vitamin B9 deficiency and as an adjunct to various combination therapies. Hypersensitivity reactions to folic acid or folinic acid are rare and occur following exposure to synthetic folic acid or its derivatives but not on natural folates. In people allergic to folates, cross-reactions are possible following exposure to folic acid analogues (including antifolates, e.g., methotrexate). The mechanism of hypersensitivity to folic acid and/or folinic acid has not been clearly established. Both IgE-dependent and non-IgE-dependent hypersensitivity reactions are likely. It is possible that folic or folinic acid is either an immunogen or a hapten. Diagnosing hypersensitivity to folic/folinic acid is difficult. There are no validated in vitro or in vivo diagnostic tests. The basophil activation test (BAT) appears to be a promising tool for diagnosing folate allergy. The aims of the manuscript were to review published clinical cases of hypersensitivity reactions to folic or folinic acid, potential mechanisms of these reactions and possible cross-allergies, and current diagnostic possibilities of folate hypersensitivity. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Regulation in Allergy and Immune Diseases, Immunodeficiencies, 2nd Edition)
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4 pages, 163 KiB  
Editorial
Sustainable Catalysis for Green Chemistry and Energy Transition
by Muhammad Saeed Akhtar and Wajid Zaman
Catalysts 2025, 15(8), 773; https://doi.org/10.3390/catal15080773 (registering DOI) - 14 Aug 2025
Abstract
Catalysis sits at the heart of sustainable development, and plays an instrumental role in addressing modern environmental challenges [...] Full article
(This article belongs to the Special Issue Sustainable Catalysis for Green Chemistry and Energy Transition)
18 pages, 1307 KiB  
Review
Smart Theranostic Platforms Based on Carbohydrate Hydrogels
by Silvia Romano, Sorur Yazdanpanah, Raffaele Conte, Agnello De Rosa, Antonio Fico, Gianfranco Peluso, Parisa Pedram and Arash Moeini
Macromol 2025, 5(3), 37; https://doi.org/10.3390/macromol5030037 (registering DOI) - 14 Aug 2025
Abstract
Carbohydrate-based hydrogels represent a new advancement in the development of multifunctional biomedical systems, thanks to their intrinsic biocompatibility, structural versatility, and capacity for functional modification. This review examines the latest progress made in employing these materials as intelligent theranostic platforms, with a particular [...] Read more.
Carbohydrate-based hydrogels represent a new advancement in the development of multifunctional biomedical systems, thanks to their intrinsic biocompatibility, structural versatility, and capacity for functional modification. This review examines the latest progress made in employing these materials as intelligent theranostic platforms, with a particular focus on their role as biosensors and therapeutic drug delivery devices. Engineered to interact dynamically with the biological environment, carbohydrate hydrogels enable the site-specific release of therapeutic agents while simultaneously supporting the monitoring of key physiological markers. Their dual functionality offers significant advantages in managing complex pathologies such as cancer, metabolic disorders, and chronic inflammation, where personalized treatment and real-time feedback are essential. By exploring their biological application, this review underscores the pivotal role played by carbohydrate hydrogels in advanced therapeutic technologies. Full article
(This article belongs to the Special Issue Recent Trends in Carbohydrate-Based Therapeutics)
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9 pages, 3634 KiB  
Article
Van Der Waals Mask-Assisted Strategy for Deterministic Fabrication of Two-Dimensional Organic−Inorganic Hybrid Perovskites Lateral Heterostructures
by Bin Han, Mengke Lin, Yanren Tang, Xingyu Liu, Bingtao Lian, Qi Qiu, Shukai Ding and Bingshe Xu
Inorganics 2025, 13(8), 266; https://doi.org/10.3390/inorganics13080266 (registering DOI) - 14 Aug 2025
Abstract
Two-dimensional (2D) organic−inorganic hybrid perovskites (OIHPs) have emerged as promising candidates for next-generation optoelectronic applications. While vertical heterostructures of 2D OIHPs have been explored through mechanical stacking, the controlled fabrication of lateral heterostructures remains a significant challenge. Here, we present a lithography-free, van [...] Read more.
Two-dimensional (2D) organic−inorganic hybrid perovskites (OIHPs) have emerged as promising candidates for next-generation optoelectronic applications. While vertical heterostructures of 2D OIHPs have been explored through mechanical stacking, the controlled fabrication of lateral heterostructures remains a significant challenge. Here, we present a lithography-free, van der Waals mask-assisted strategy for the deterministic fabrication of 2D OIHP lateral heterostructures. Mechanically exfoliated 2D materials such as graphene serve as removable masks that enable selective conversion of unmasked perovskite regions via ion exchange reaction. This technique enables the fabrication of various lateral heterostructures, such as BA2MA2Pb3I10/MAPbI3, PEAPbI4/MAPbI3, as well as BA2MAPb2I7/MAPbBr3. Furthermore, complex multiheterostructures and superlattices can be constructed through sequential masking and conversion processes. Moreover, to investigate the electronic properties and demonstrate potential device applications of the lateral heterostructures, we have fabricated an electrical diode based on a BA2MA2Pb3I10/MAPbI3 lateral heterostructure. Stable electrical rectifying behavior with a rectification ratio of around 10 was observed. This general and flexible approach provides a robust platform for constructing 2D OIHPs lateral heterostructures and opens new pathways for their integration into high-performance optoelectronic devices. Full article
(This article belongs to the Section Inorganic Materials)
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14 pages, 375 KiB  
Article
Rule-Based Generation of de Bruijn Sequences: Memory and Learning
by Francisco J. Muñoz and Juan Carlos Nuño
Mathematics 2025, 13(16), 2598; https://doi.org/10.3390/math13162598 (registering DOI) - 14 Aug 2025
Abstract
We investigate binary sequences generated by non-Markovian rules with memory length μ, similar to those adopted in elementary cellular automata. This generation procedure is equivalent to a shift register, and certain rules produce sequences with maximal periods, known as de Bruijn sequences. [...] Read more.
We investigate binary sequences generated by non-Markovian rules with memory length μ, similar to those adopted in elementary cellular automata. This generation procedure is equivalent to a shift register, and certain rules produce sequences with maximal periods, known as de Bruijn sequences. We introduce a novel methodology for generating de Bruijn sequences that combines (i) a set of derived properties that significantly reduce the space of feasible generating rules and (ii) a neural-network-based classifier that identifies which rules produce de Bruijn sequences. The experiments for some values of μ demonstrate the approach’s effectiveness and computational efficiency. Full article
(This article belongs to the Section E: Applied Mathematics)
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17 pages, 4659 KiB  
Article
Multi-Agent Reinforcement Learning-Based Cooperative Encirclement Control of Autonomous Surface Vehicles Against Multiple Targets
by Xingru Qu, Chu Li, Shang Jiang, Guanqun Liu and Rubo Zhang
J. Mar. Sci. Eng. 2025, 13(8), 1558; https://doi.org/10.3390/jmse13081558 (registering DOI) - 14 Aug 2025
Abstract
Autonomous surface vehicles (ASVs) have been widely applied in ocean engineering due to their small size, low cost, and high mobility. However, more relevant encirclement control methods with many-to-one are simple and do not consider the system dynamics. This article proposes a cooperative [...] Read more.
Autonomous surface vehicles (ASVs) have been widely applied in ocean engineering due to their small size, low cost, and high mobility. However, more relevant encirclement control methods with many-to-one are simple and do not consider the system dynamics. This article proposes a cooperative encirclement control method for ASVs against multiple targets based on multi-agent reinforcement learning. Firstly, a dynamic target allocation algorithm is designed based on location information of both vehicles and targets, enabling vehicles to select encirclement targets in real-time according to relative distances. Subsequently, the whole encirclement process is divided into multiple stages, and a multi-stage reward function is developed based on curriculum learning to guide ASVs in completing encirclement tasks progressively, from simpler to more complex scenarios. Then, the actor and critic networks incorporating long short-term memory are constructed, respectively, and a multi-agent soft actor-critic reinforcement learning algorithm is employed to train ASVs, enhancing cooperative target encirclement maneuvers. Finally, the effectiveness and superiority of the proposed method is validated through a six-on-two encirclement simulation. Full article
(This article belongs to the Section Ocean Engineering)
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