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Search Results (20,041)

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29 pages, 3158 KiB  
Article
A Forecasting Method for COVID-19 Epidemic Trends Using VMD and TSMixer-BiKSA Network
by Yuhong Li, Guihong Bi, Taonan Tong and Shirui Li
Computers 2025, 14(7), 290; https://doi.org/10.3390/computers14070290 - 18 Jul 2025
Abstract
The spread of COVID-19 is influenced by multiple factors, including control policies, virus characteristics, individual behaviors, and environmental conditions, exhibiting highly complex nonlinear dynamic features. The time series of new confirmed cases shows significant nonlinearity and non-stationarity. Traditional prediction methods that rely solely [...] Read more.
The spread of COVID-19 is influenced by multiple factors, including control policies, virus characteristics, individual behaviors, and environmental conditions, exhibiting highly complex nonlinear dynamic features. The time series of new confirmed cases shows significant nonlinearity and non-stationarity. Traditional prediction methods that rely solely on one-dimensional case data struggle to capture the multi-dimensional features of the data and are limited in handling nonlinear and non-stationary characteristics. Their prediction accuracy and generalization capabilities remain insufficient, and most existing studies focus on single-step forecasting, with limited attention to multi-step prediction. To address these challenges, this paper proposes a multi-module fusion prediction model—TSMixer-BiKSA network—that integrates multi-feature inputs, Variational Mode Decomposition (VMD), and a dual-branch parallel architecture for 1- to 3-day-ahead multi-step forecasting of new COVID-19 cases. First, variables highly correlated with the target sequence are selected through correlation analysis to construct a feature matrix, which serves as one input branch. Simultaneously, the case sequence is decomposed using VMD to extract low-complexity, highly regular multi-scale modal components as the other input branch, enhancing the model’s ability to perceive and represent multi-source information. The two input branches are then processed in parallel by the TSMixer-BiKSA network model. Specifically, the TSMixer module employs a multilayer perceptron (MLP) structure to alternately model along the temporal and feature dimensions, capturing cross-time and cross-variable dependencies. The BiGRU module extracts bidirectional dynamic features of the sequence, improving long-term dependency modeling. The KAN module introduces hierarchical nonlinear transformations to enhance high-order feature interactions. Finally, the SA attention mechanism enables the adaptive weighted fusion of multi-source information, reinforcing inter-module synergy and enhancing the overall feature extraction and representation capability. Experimental results based on COVID-19 case data from Italy and the United States demonstrate that the proposed model significantly outperforms existing mainstream methods across various error metrics, achieving higher prediction accuracy and robustness. Full article
19 pages, 13416 KiB  
Article
Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment
by Yong Pan, Jie Zheng, Fangxin Fang, Fanghui Liang, Mengrong Yang, Lei Tong and Hang Xiao
Atmosphere 2025, 16(7), 883; https://doi.org/10.3390/atmos16070883 - 18 Jul 2025
Abstract
In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory [...] Read more.
In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory analysis, TCTM enables the precise identification of source regions, the delineation of key transport corridors, and a quantitative assessment of regional contributions to receptor sites. Focusing on four Yangtze River Delta cities (Hangzhou, Shanghai, Nanjing, Hefei) during a January 2020 pollution event, the results demonstrate that TCTM’s Weighted Concentration Source (WCS) and Source Pollution Characteristic Index (SPCI) outperform traditional PSCF and CWT methods in source-attribution accuracy and resolution. Unlike receptor-based statistical approaches, TCTM reconstructs pollutant transport processes, quantifies spatial decay, and assigns contributions via physically interpretable metrics. This innovative framework offers actionable insights for targeted air-quality management strategies, highlighting its potential as a robust tool for pollution mitigation planning. Full article
(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)
25 pages, 6471 KiB  
Article
Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data
by Choeng-Lyong Lee, Wonbae Bang, Chia-Lun Tsai and GyuWon Lee
Remote Sens. 2025, 17(14), 2506; https://doi.org/10.3390/rs17142506 - 18 Jul 2025
Abstract
A novel classification algorithm for precipitation types (CP) was developed to address frequent misclassification issues between shallow convection and intense stratiform precipitation using existing methods and to enhance an understanding of their physical characteristics. Based on three-dimensional radar data and temperature fields, CP [...] Read more.
A novel classification algorithm for precipitation types (CP) was developed to address frequent misclassification issues between shallow convection and intense stratiform precipitation using existing methods and to enhance an understanding of their physical characteristics. Based on three-dimensional radar data and temperature fields, CP integrates three approaches: Storm Labeling in Three Dimensions (SLTD), a feature parameter-based algorithm (FP), and an advanced subcategorization method. The algorithm classifies precipitation into ten types: four non-precipitating, three stratiform, and three convective categories. CP was evaluated against traditional methods (SHY and FP) through both qualitative and quantitative analyses for mid-latitude warm-season systems. The CP method demonstrated improved performance, with higher skill scores (e.g., POD: 0.567–0.571) compared to SHY (0.349–0.364) and FP (0.455–0.470). Additionally, comparative analyses of vertical mean profiles of radar reflectivity, dynamical, and microphysical variables confirmed the enhanced capability of CP in distinguishing detailed precipitation structures. Full article
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14 pages, 4131 KiB  
Article
An Experimental and Modelling Study on the Effect of Vegetation-Influenced Water Velocity on Cadmium Accumulation in Corbicula fluminea
by Nan Geng, Guojin Sun, Lin Zhang and Hui Wang
Sustainability 2025, 17(14), 6570; https://doi.org/10.3390/su17146570 - 18 Jul 2025
Abstract
Cadmium (Cd) accumulation by benthic organisms poses a significant threat to aquatic environmental safety. Both vegetation and water velocity in rivers could influence this process, yet their coupled interaction mechanisms remain unclear. This study used laboratory flume experiments to simulate four scenarios: static [...] Read more.
Cadmium (Cd) accumulation by benthic organisms poses a significant threat to aquatic environmental safety. Both vegetation and water velocity in rivers could influence this process, yet their coupled interaction mechanisms remain unclear. This study used laboratory flume experiments to simulate four scenarios: static water (C0), pure water velocity (C+H), vegetation-water velocity (V+H), and coexistence of vegetation-water velocity-Corbicula fluminea (C. fluminea) (C+V+H). The dynamics of Cd release from sediment to overlying water and its bioaccumulation within C. fluminea were investigated. A mathematical model coupling Cd release, diffusion, and C. fluminea bioaccumulation was developed based on the lattice Boltzmann method (LBM). The results showed that compared to the non-vegetation group (C+H), the presence of vegetation (V+H, C+V+H) initially reduced sediment resuspension and Cd release. However, the turbulence induced by vegetation significantly increased the Cd diffusion coefficient and equilibrium concentration in the water. Consequently, Cd accumulation in C. fluminea within the vegetation-water velocity group (C+V+H) was significantly higher than in the pure water velocity group (C+H). The established LBM model exhibited good simulation accuracy (for overlying water Cd concentration: R2 = 0.8201–0.942; for C. fluminea Cd concentration: R2 = 0.7604–0.8191) and successfully reproduced the processes of Cd release and bioaccumulation under varying vegetation-water velocity conditions. This study elucidates the mechanism by which vegetation promotes Cd accumulation in C. fluminea by altering water velocity structure and diffusion characteristics, providing crucial theoretical parameters for multi-media migration and transformation models of heavy metals in complex water velocity environments and for early warning systems concerning Cd accumulation risks in riverine organisms. Full article
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44 pages, 5275 KiB  
Review
The Power Regulation Characteristics, Key Challenges, and Solution Pathways of Typical Flexible Resources in Regional Energy Systems
by Houze Jiang, Shilei Lu, Boyang Li and Ran Wang
Energies 2025, 18(14), 3830; https://doi.org/10.3390/en18143830 - 18 Jul 2025
Abstract
The low-carbon transition of the global energy system is an urgent necessity to address climate change and meet growing energy demand. As a major source of energy consumption and emissions, buildings play a key role in this transition. This study systematically analyzes the [...] Read more.
The low-carbon transition of the global energy system is an urgent necessity to address climate change and meet growing energy demand. As a major source of energy consumption and emissions, buildings play a key role in this transition. This study systematically analyzes the flexible resources of building energy systems and vehicle-to-grid (V2G) interaction technologies, and mainly focuses on the regulation characteristics and coordination mechanisms of distributed energy supply (renewable energy and multi-energy cogeneration), energy storage (electric/thermal/cooling), and flexible loads (air conditioning and electric vehicles) within regional energy systems. The study reveals that distributed renewable energy and multi-energy cogeneration technologies form an integrated architecture through a complementary “output fluctuation mitigation–cascade energy supply” mechanism, enabling the coordinated optimization of building energy efficiency and grid regulation. Electricity and thermal energy storage serve as dual pillars of flexibility along the “fast response–economic storage” dimension. Air conditioning loads and electric vehicles (EVs) complement each other via thermodynamic regulation and Vehicle-to-Everything (V2X) technologies, constructing a dual-dimensional regulation mode in terms of both power and time. Ultimately, a dynamic balance system integrating sources, loads, and storage is established, driven by the spatiotemporal complementarity of multi-energy flows. This paper proposes an innovative framework that optimizes energy consumption and enhances grid stability by coordinating distributed renewable energy, energy storage, and flexible loads across multiple time scales. This approach offers a new perspective for achieving sustainable and flexible building energy systems. In addition, this paper explores the application of demand response policies in building energy systems, analyzing the role of policy incentives and market mechanisms in promoting building energy flexibility. Full article
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20 pages, 6319 KiB  
Article
Spatiotemporal Deformation Prediction Model for Retaining Structures Integrating ConvGRU and Cross-Attention Mechanism
by Yanyong Gao, Zhaoyun Xiao, Zhiqun Gong, Shanjing Huang and Haojie Zhu
Buildings 2025, 15(14), 2537; https://doi.org/10.3390/buildings15142537 - 18 Jul 2025
Abstract
With the exponential growth of engineering monitoring data, data-driven neural networks have gained widespread application in predicting retaining structure deformation in foundation pit engineering. However, existing models often overlook the spatial deflection correlations among monitoring points. Therefore, this study proposes a novel deep [...] Read more.
With the exponential growth of engineering monitoring data, data-driven neural networks have gained widespread application in predicting retaining structure deformation in foundation pit engineering. However, existing models often overlook the spatial deflection correlations among monitoring points. Therefore, this study proposes a novel deep learning framework, CGCA (Convolutional Gated Recurrent Unit with Cross-Attention), which integrates ConvGRU and cross-attention mechanisms. The model achieves spatio-temporal feature extraction and deformation prediction via an encoder–decoder architecture. Specifically, the convolutional structure captures spatial dependencies between monitoring points, while the recurrent unit extracts time-series characteristics of deformation. A cross-attention mechanism is introduced to dynamically weight the interactions between spatial and temporal data. Additionally, the model incorporates multi-dimensional inputs, including full-depth inclinometer measurements, construction parameters, and tube burial depths. The optimization strategy combines AdamW and Lookahead to enhance training stability and generalization capability in geotechnical engineering scenarios. Case studies of foundation pit engineering demonstrate that the CGCA model exhibits superior performance and robust generalization capabilities. When validated against standard section (CX1) and complex working condition (CX2) datasets involving adjacent bridge structures, the model achieves determination coefficients (R2) of 0.996 and 0.994, respectively. The root mean square error (RMSE) remains below 0.44 mm, while the mean absolute error (MAE) is less than 0.36 mm. Comparative experiments confirm the effectiveness of the proposed model architecture and the optimization strategy. This framework offers an efficient and reliable technical solution for deformation early warning and dynamic decision-making in foundation pit engineering. Full article
(This article belongs to the Special Issue Research on Intelligent Geotechnical Engineering)
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19 pages, 5968 KiB  
Article
Investigation of Electrical Discharge Processes During Electrolytic–Plasma Nitrocarburizing
by Bauyrzhan Rakhadilov, Laila Sulyubayeva, Almasbek Maulit and Temirlan Alimbekuly
Materials 2025, 18(14), 3381; https://doi.org/10.3390/ma18143381 - 18 Jul 2025
Abstract
In this study, the process of electrolytic–plasma nitrocarburizing (EPNC) of 20-grade steel was investigated using various electrolytes and temperature regimes. At the first stage, optical spectral analysis of plasma emission during EPNC was carried out with spectral registration in the range of 275–850 [...] Read more.
In this study, the process of electrolytic–plasma nitrocarburizing (EPNC) of 20-grade steel was investigated using various electrolytes and temperature regimes. At the first stage, optical spectral analysis of plasma emission during EPNC was carried out with spectral registration in the range of 275–850 nm, which allowed the identification of active components (Hα, CN, Fe I, O I lines, etc.) and the calculation of electron density. Additionally, the EPNC process was recorded using a high-speed camera (1500 frames per second), which made it possible to visually evaluate the dynamics of arc and glow discharges under varying electrolyte compositions. At the next stage, the influence of temperature regimes (650 °C, 750 °C, and 850 °C) on the formation of the hardened layer was studied. Using SEM and EDS methods, the morphology, phase zones, and the distribution of chemical elements were determined. Microhardness measurements along the depth and friction tests were carried out. It was found that a temperature of 750 °C provides the best balance between the uniformity of chemical composition, high microhardness (~800 HV), and a minimal coefficient of friction (~0.48). The obtained results confirm the potential of the selected EPNC regime for improving the performance characteristics of 20-grade steel. Full article
(This article belongs to the Section Metals and Alloys)
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20 pages, 3162 KiB  
Article
Study on Separation of Desulfurization Wastewater in Ship Exhaust Gas Cleaning System with Rotating Dynamic Filtration
by Shiyong Wang, Juan Wu, Yanlin Wu and Wenbo Dong
Membranes 2025, 15(7), 214; https://doi.org/10.3390/membranes15070214 - 18 Jul 2025
Abstract
Current treatment methods for desulfurization wastewater in the ship exhaust gas cleaning (EGC) system face several problems, including process complexity, unstable performance, large spatial requirements, and high energy consumption. This study investigates rotating dynamic filtration (RDF) as an efficient treatment approach through experimental [...] Read more.
Current treatment methods for desulfurization wastewater in the ship exhaust gas cleaning (EGC) system face several problems, including process complexity, unstable performance, large spatial requirements, and high energy consumption. This study investigates rotating dynamic filtration (RDF) as an efficient treatment approach through experimental testing, theoretical analysis, and pilot-scale validation. Flux increases with temperature and pressure but decreases with feed concentration, remaining unaffected by circulation flow. For a small membrane (152 mm), flux consistently increases with rotational speed across all pressures. For a large membrane (374 mm), flux increases with rotational speed at 300 kPa but firstly increases and then decreases at 100 kPa. Filtrate turbidity in all experiments complies with regulatory standards. Due to the unique hydrodynamic characteristics of RDF, back pressure reduces the effective transmembrane pressure, whereas shear force mitigates concentration polarization and cake layer formation. Separation performance is governed by the balance between these two forces. The specific energy consumption of RDF is only 10–30% that of cross-flow filtration (CFF). Under optimized pilot-scale conditions, the wastewater was concentrated 30-fold, with filtrate turbidity consistently below 2 NTU, outperforming CFF. Moreover, continuous operation proves more suitable for marine environments. Full article
(This article belongs to the Section Membrane Applications for Water Treatment)
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10 pages, 3012 KiB  
Article
A Perovskite-Based Photoelectric Synaptic Transistor with Dynamic Nonlinear Response
by Jiahui Liu, Zunxian Yang, Yujie Zheng and Wenkun Su
Photonics 2025, 12(7), 734; https://doi.org/10.3390/photonics12070734 - 18 Jul 2025
Abstract
Nonlinear characteristics are essential for neuromorphic devices to process high-dimensional and unstructured data. However, enabling a device to realize a nonlinear response under the same stimulation condition is challenging as this involves two opposing processes: simultaneous charge accumulation and recombination. In this study, [...] Read more.
Nonlinear characteristics are essential for neuromorphic devices to process high-dimensional and unstructured data. However, enabling a device to realize a nonlinear response under the same stimulation condition is challenging as this involves two opposing processes: simultaneous charge accumulation and recombination. In this study, a hybrid transistor based on a mixed-halide perovskite was fabricated to achieve dynamic nonlinear changes in synaptic plasticity. The utilization of a light-induced mixed-bandgap structure within the mixed perovskite film has been demonstrated to increase the recombination paths of photogenerated carriers of the hybrid film, thereby promoting the formation of nonlinear signals in the device. The constructed heterojunction optoelectronic synaptic transistor, formed by combining a mixed-halide perovskite with a p-type semiconductor, generates dynamic nonlinear decay responses under 400 nm light pulses with an intensity as low as 0.02 mW/cm2. Furthermore, it has been demonstrated that nonlinear photocurrent growth can be achieved under 650 nm light pulses. It is important to note that this novel nonlinear response is characterized by its dynamism. These improvements provide a novel method for expanding the modulation capability of optoelectronic synaptic devices for synaptic plasticity. Full article
(This article belongs to the Special Issue Polaritons Nanophotonics: Physics, Materials and Applications)
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14 pages, 845 KiB  
Article
Cross-Path Planning of UAV Cluster Low-Altitude Flight Based on Inertial Navigation Combined with GPS Localization
by Xiancheng Yang, Ming Zhang, Peihui Yan, Qu Wang, Dongpeng Xie and Yuntian Brian Bai
Electronics 2025, 14(14), 2877; https://doi.org/10.3390/electronics14142877 - 18 Jul 2025
Abstract
To address the challenges of complex low-altitude flight environments for UAVs, where numerous obstacles often lead to GPS signal obstruction and multipath effects, this study proposes an integrated inertial navigation and GPS positioning approach for coordinated cross-path planning in drone swarms. The methodology [...] Read more.
To address the challenges of complex low-altitude flight environments for UAVs, where numerous obstacles often lead to GPS signal obstruction and multipath effects, this study proposes an integrated inertial navigation and GPS positioning approach for coordinated cross-path planning in drone swarms. The methodology involves the following: (1) discretizing continuous 3D airspace into grid cells using occupancy grid mapping to construct an environmental model; (2) analyzing dynamic flight characteristics through attitude angle variations in a 3D Cartesian coordinate system; and (3) implementing collaborative state updates and global positioning through fused inertial–GPS navigation. By incorporating Cramér–Rao lower bound optimization, the system achieves effective cross-path planning for drone formations. Experimental results demonstrate a 98.35% mission success rate with inter-drone navigation time differences maintained below 0.5 s, confirming the method’s effectiveness in enabling synchronized swarm operations while maintaining safe distances during cooperative monitoring and low-altitude flight missions. This approach demonstrates significant advantages in coordinated cross-path planning for UAV clusters. Full article
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16 pages, 4455 KiB  
Article
Durability and Microstructure Analysis of Loess-Based Composite Coal Gangue Porous Vegetation Concrete
by Manman Qiu, Wuyu Zhang, Shuaihua Ye, Xiaohui Li and Jingbang Li
Buildings 2025, 15(14), 2531; https://doi.org/10.3390/buildings15142531 - 18 Jul 2025
Abstract
In order to improve the durability of loess-based composite coal gangue porous planting concrete (LCPC), the effects of fly ash and slag powder content on the durability and microstructure of LCPC were studied. In this paper, fly ash and slag powder were mixed [...] Read more.
In order to improve the durability of loess-based composite coal gangue porous planting concrete (LCPC), the effects of fly ash and slag powder content on the durability and microstructure of LCPC were studied. In this paper, fly ash and slag powder were mixed into LCPC, and freeze-thaw cycle and dry-wet cycle tests were carried out. The compressive strength, dynamic elastic modulus, and mass change were used as evaluation indices to determine the optimal mix ratio for LCPC durability. Scanning electron microscopy (SEM) was performed, and the experimental design was carried out with the water–cement ratio, fly ash, and slag powder content as variables. The microstructure characteristics of LCPC were analyzed. The results show that the maximum number of freeze-thaw cycles can reach 35 times and the maximum number of dry-wet cycles can reach 50 when 5% fly ash and 20% slag powder are used. With an increase in the water-cement ratio, the skeleton of the loess gradually became complete, and its structure became more compact. In the micro-morphology diagram, the mixed fly ash and slag powder particles are not obvious, but with an increase in dosage, the size of the cracks and pores gradually decreases. The incorporation of fly ash and slag powder can play a positive role in the durability of LCPC and improvement of its microstructure. The results of this study are crucial for improving the application performance of ecological restoration, soil improvement, and long-term stability of structures, and can provide a scientific basis for the sustainable development of environmentally friendly building materials. Full article
(This article belongs to the Special Issue Soil–Structure Interactions for Civil Infrastructure)
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26 pages, 5344 KiB  
Article
Sliding Mode Repetitive Control Based on the Unknown Dynamics Estimator of a Two-Stage Supply Pressure Hydraulic Hexapod Robot
by Ziqi Liu, Bo Jin, Junkui Dong, Qingyun Yao, Yinglian Jin, Tao Liu and Binrui Wang
Biomimetics 2025, 10(7), 472; https://doi.org/10.3390/biomimetics10070472 - 18 Jul 2025
Abstract
Hydraulic actuated legged robots display bright prospects and significant research value in areas such as unmanned area surveying, disaster rescue, military fields, and other scenarios owing to their excellent bionic characteristics, particularly their heavy payload capabilities and high power density. To realize the [...] Read more.
Hydraulic actuated legged robots display bright prospects and significant research value in areas such as unmanned area surveying, disaster rescue, military fields, and other scenarios owing to their excellent bionic characteristics, particularly their heavy payload capabilities and high power density. To realize the all-terrain adaptation locomotion of the hydraulic hexapod robot (HHR) with a heavy payload, one alternative control framework is position–posture control based on joint position control. As the foundation for the steady locomotion of HHRs, it is imperative to realize high-precision joint position control to improve the robustness under external disturbances during the walking process and to complete the attitude control task. To address the above issues, this paper proposes a sliding mode repetitive control based on the unknown dynamics estimator (SMRC + UDE) for the knee and hip joints of the HHR with a two-stage supply pressure hydraulic system (TSS). The effectiveness of the SMRC + UDE method is verified using a simulation environment and the ZJUHEX01 prototype experimental platform, and it is compared with the results for PID and adaptive robust sliding mode control (ARSMC). The results show that SMRC + UDE may be more suitable for our HHR, considering both the control performance and efficiency factors. Full article
(This article belongs to the Section Locomotion and Bioinspired Robotics)
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11 pages, 1095 KiB  
Article
A Microsurgical Technique for Removing the Spermatheca of Bumblebee Females and Its Application
by Mingsheng Zhuang, Fan Yang, Zhongyan Xia, Yu Fei, Fugang Liu, Zhengyi Zhang, Zhihao Zhang and Jilian Li
Insects 2025, 16(7), 734; https://doi.org/10.3390/insects16070734 - 18 Jul 2025
Abstract
To solve the technical bottleneck caused by the absence of a feasible method for removing the spermatheca in social insects, we developed a microsurgical technique specifically designed for bumblebee females. In this study, the invention of this technique is based on the anatomical [...] Read more.
To solve the technical bottleneck caused by the absence of a feasible method for removing the spermatheca in social insects, we developed a microsurgical technique specifically designed for bumblebee females. In this study, the invention of this technique is based on the anatomical characteristics of the sting chamber of bumblebees and uses a bespoke scalpel to precisely remove the spermatheca, which is small in size and deeply embedded within the body. During the removal operation, a small wound was observed and a small amount of hemolymph flowed out. The wound healed very quickly and the survival rate of treated individuals was high. The results showed that there was no significant impact on the critical life activities of queens and workers, including longevity, mating behavior, oviposition capacity, and overwintering survival rate after the spermatheca was removed using this technique. These findings further confirm the feasibility and applicability of the technique and provide strong technical support for exploring the evolutionary dynamics and potential function of the spermatheca in social insects. Full article
(This article belongs to the Section Social Insects and Apiculture)
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13 pages, 2355 KiB  
Review
Comparison Study of Converter-Based I–V Tracers in Photovoltaic Power Systems for Outdoor Detection
by Weidong Xiao
Energies 2025, 18(14), 3818; https://doi.org/10.3390/en18143818 - 17 Jul 2025
Abstract
Current–voltage (I–V) characteristics are an important measure of photovoltaic (PV) generators, corresponding to environmental conditions regarding solar irradiance and temperature. The I–V curve tracer is a widely used instrument in power engineering to evaluate system performance and detect fault conditions in PV power [...] Read more.
Current–voltage (I–V) characteristics are an important measure of photovoltaic (PV) generators, corresponding to environmental conditions regarding solar irradiance and temperature. The I–V curve tracer is a widely used instrument in power engineering to evaluate system performance and detect fault conditions in PV power systems. Several technologies have been applied to develop the device and trace I–V characteristics, improving accuracy, speed, and portability. Focusing on the outdoor environment, this paper presents an in-depth analysis and comparison of the system design and dynamics to identify the I–V tracing performance based on different power conversion topologies and data acquisition methods. This is a valuable reference for industry and academia to further the technology and promote sustainable power generation. Full article
(This article belongs to the Special Issue Digital Modeling, Operation and Control of Sustainable Energy Systems)
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17 pages, 9414 KiB  
Article
Influence of High-Speed Flow on Aerodynamic Lift of Pantograph at 400 km/h
by Zhao Xu, Hongwei Zhang, Wen Wang and Guobin Lin
Infrastructures 2025, 10(7), 188; https://doi.org/10.3390/infrastructures10070188 - 17 Jul 2025
Abstract
This study examines pantograph aerodynamic lift at 400 km/h, and uncovers the dynamic behaviors and mechanisms that influence pantograph–catenary performance. Using computational fluid dynamics (CFD) with a compressible fluid model and an SST k-ω turbulence model, aerodynamic characteristics were analyzed. Simulation data at [...] Read more.
This study examines pantograph aerodynamic lift at 400 km/h, and uncovers the dynamic behaviors and mechanisms that influence pantograph–catenary performance. Using computational fluid dynamics (CFD) with a compressible fluid model and an SST k-ω turbulence model, aerodynamic characteristics were analyzed. Simulation data at 300, 350, and 400 km/h showed lift fluctuation amplitude increases with speed, peaking near 50 N at 400 km/h. Power spectral density (PSD) energy, dominated by low frequencies, peaked around 10 dB/Hz in the low-frequency band, highlighting exacerbated lift instability. Component analysis revealed the smallest lift-to-drag ratio and most significant fluctuations at the head, primarily due to boundary-layer separation and vortex shedding from its non-streamlined design. Turbulence energy analysis identified the head and base as main turbulence sources; however, base vibrations are absorbed by the vehicle body, while the head causes pantograph–catenary vibrations due to direct contact. These findings confirm that aerodynamic instability at the head is the main cause of contact force fluctuations. Optimizing head design is necessary to suppress fluctuations, ensuring safe operation at 400 km/h and above. Results provide a theoretical foundation for aerodynamic optimization and improved dynamic performance of high-speed pantographs. Full article
(This article belongs to the Special Issue The Resilience of Railway Networks: Enhancing Safety and Robustness)
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