Search Results (2,889)

Terahertz (THz) has attracted substantial attention owing to its unique advantages in high-speed communications. However, conventional THz waveguide systems are inherently constrained by high transmission losses, stringent fabrication precision requirements, and extreme sensitivity to structural defects. Topological edge states with topological protection have driven significant advancements in THz wave manipulation. Nevertheless, the width of the topological waveguide based on edge states remains restricted. In this work, we put forward a type of spin photonic crystal with three-layer heterostructures, where large-area topological waveguide states are demonstrated. The results show that these topological waveguide states are localized within the region of Dirac photonic crystals. They also display spin-momentum-locking characteristics and maintain strong robustness against defects and sharp bends. Furthermore, a THz beam splitter and a topological beam modulator are implemented. The designed heterostructures expand the applications of multi-functional topological devices and provide a prospective pathway for overcoming the waveguide bottleneck in THz applications. Full article

Background/Objectives: Perceptions of obesity critically influence people’s eating behaviors and responses to food stimuli. However, few studies have investigated the impact of negative body perception on behavioral and neural responses to food stimuli. This study investigates how elevated body dissatisfaction modulates food-related inhibitory control. Methods: Fifty-one participants comprising three cohorts—overweight/obese individuals (OO), normal-weight participants exhibiting high negative body image (HNN), and healthy controls—performed a food-specific inhibitory control task under EEG recording. Results: The results showed that the HNN cohort achieved superior no-go accuracy and enhanced inhibitory control compared to controls. An event-related potentials (ERPs) analysis revealed increased conflict detection (P200) for high-calorie foods and reduced conflict resolution (LPP) in the HNN group, similar to the overweight/obese group. A multivariate pattern analysis (MVPA) identified earlier neural discrimination in the HNN group, suggesting more efficient inhibitory processing. Conclusions: These findings underscore negative body perception as a critical modulator of food-related cognitive control mechanisms. Full article

Electromagnetic pneumatic microvalves, widely used in knitting machines, typically operate based on a spring-return mechanism. When the coil is energized, the electromagnetic force overcomes the spring force to attract the armature, opening the valve. Upon de-energization, the armature returns to its original position under the restoring force of the spring, closing the valve. However, most existing electromagnetic microvalves adopt a radially asymmetric magnetic yoke design, which generates additional radial forces during operation, leading to armature misalignment or even sticking. Additionally, the inductance effect of the coil causes a significant delay in the armature release response, making it difficult to meet the knitting machine’s requirements for rapid response and high reliability. To address these issues, this paper proposes an improved electromagnetic microvalve design. First, the magnetic yoke structure is modified to be radially symmetric, eliminating unnecessary radial forces and preventing armature sticking during operation. Second, a permanent magnet assist mechanism is introduced at the armature release end to enhance release speed and reduce delays caused by the inductance effect. The effectiveness of the proposed design is validated through electromagnetic numerical simulations, and a multi-objective genetic algorithm is further employed to optimize the geometric dimensions of the electromagnet. The optimization results indicate that, while maintaining the fundamental power supply principle of conventional designs, the new microvalve structure achieves a pull-in time comparable to traditional designs during engagement but significantly reduces the release response time by approximately 80.2%, effectively preventing armature sticking due to radial forces. The findings of this study provide a feasible and efficient technical solution for the design of electromagnetic microvalves in textile machinery applications. Full article

The development of anode-free sodium metal batteries (AFSMBs) offers a promising pathway to achieve ultrahigh energy density and cost efficiency inherent to conventional sodium ion/metal batteries. However, irreversible Na plating/stripping and dendritic growth remain critical barriers. Herein, we demonstrate that separator engineering is a pivotal strategy for stabilizing AFSMBs. Through systematic evaluation of four separators—2500 separator (PP), 2325 separator (PP/PE/PP), glass fiber (GF), and an Al₂O₃-coated PE membrane, we reveal that the Al₂O₃-coated separator uniquely enables exceptional interfacial kinetics and morphological control. Na||Na symmetric cells with Al₂O₃ coated separator exhibit ultralow polarization (4.5 mV) and the highest exchange current density (1.77 × 10⁻² mA cm⁻²), while the anode-free AlC-NFPP full cells retain 91.6% capacity after 150 cycles at 2C. Specifically, the Al₂O₃ coating homogenizes Na⁺ flux, promotes dense and planar Na deposition, and facilitates near-complete stripping with minimal “dead Na”. This work establishes ceramic-functionalized separators as essential enablers of practical high-energy AFSMBs. Full article

Membrane bioreactors (MBRs) have been utilized for maricultural wastewater treatment, where high-salinity stress results in dramatic membrane fouling in the actual process. A microalgal–bacterial symbiotic system (MBSS) offers advantages for photosynthetic oxygen production, dynamically regulating the structure of extracellular polymeric substances (EPSs) and improving the salinity tolerance of bacteria and algae. This study centered on the mechanisms of membrane fouling mitigation via the microalgal–bacterial interactions in the MBSS, including improving the pollutant removal, optimizing the system parameters, and controlling the gel layer formation. Moreover, the contribution of electrochemistry to decreasing the inhibitory effects of high-salinity stress was investigated in the MBSS. Furthermore, patterns of shifts in microbial communities and the impacts have been explored using metagenomic technology. Finally, this review aims to offer new insights for membrane fouling mitigation in actual maricultural wastewater treatment. Full article

The unique characteristics of desert vegetation, such as different leaf morphology, discrete canopy structures, sparse and uneven distribution, etc., pose significant challenges for remote sensing-based estimation of fractional vegetation cover (FVC). The Unmanned Aerial Vehicle (UAV) system can accurately distinguish vegetation patches, extract weak vegetation signals, and navigate through complex terrain, making it suitable for applications in small-scale FVC extraction. In this study, we selected the floodplain fan with Caragana korshinskii Kom as the constructive species in Hatengtaohai National Nature Reserve, Bayannur, Inner Mongolia, China, as our study area. We investigated the remote sensing extraction method of desert sparse vegetation cover by placing samples across three gradients: the top, middle, and edge of the fan. We then acquired UAV multispectral images; evaluated the applicability of various vegetation indices (VIs) using methods such as supervised classification, linear regression models, and machine learning; and explored the feasibility and stability of multiple machine learning models in this region. Our results indicate the following: (1) We discovered that the multispectral vegetation index is superior to the visible vegetation index and more suitable for FVC extraction in vegetation-sparse desert regions. (2) By comparing five machine learning regression models, it was found that the XGBoost and KNN models exhibited relatively lower estimation performance in the study area. The spatial distribution of plots appeared to influence the stability of the SVM model when estimating fractional vegetation cover (FVC). In contrast, the RF and LASSO models demonstrated robust stability across both training and testing datasets. Notably, the RF model achieved the best inversion performance (R² = 0.876, RMSE = 0.020, MAE = 0.016), indicating that RF is one of the most suitable models for retrieving FVC in naturally sparse desert vegetation. This study provides a valuable contribution to the limited existing research on remote sensing-based estimation of FVC and characterization of spatial heterogeneity in small-scale desert sparse vegetation ecosystems dominated by a single species. Full article

Refining the land use structure can boost land utilization efficiency and curtail regional carbon emissions. Nevertheless, prior research has predominantly concentrated on static linear planning analysis. It has failed to account for how future dynamic alterations in driving factors (such as GDP and population) affect simulation outcomes and how the land use spatial configuration impacts the attainment of the carbon-neutrality goal. In this research, 1 km spatial resolution LULC products were employed to meticulously simulate multiple land use scenarios across China at the national level from 2030 to 2060. This was performed by taking into account the dynamic changes in driving factors. Subsequently, an analysis was carried out on the low-carbon land use spatial structure required to reach the carbon-neutrality target. The findings are as follows: (1) When employing the PLUS (Patch—based Land Use Simulation) model to conduct simulations of various land use scenarios in China by taking into account the dynamic alterations in driving factors, a high degree of precision was attained across diverse scenarios. The sustainable development scenario demonstrated the best performance, with kappa, OA, and FoM values of 0.9101, 93.15%, and 0.3895, respectively. This implies that the simulation approach based on dynamic factors is highly suitable for national-scale applications. (2) The simulation accuracy of the PLUS and GeoSOS-FLUS (Systems for Geographical Modeling and Optimization, Simulation of Future Land Utilization) models was validated for six scenarios by extrapolating the trends of influencing factors. Moreover, a set of scenarios was added to each model as a control group without extrapolation. The present research demonstrated that projecting the trends of factors having an impact notably improved the simulation precision of both the PLUS and GeoSOS-FLUS models. When contrasted with the GeoSOS-FLUS model, the PLUS model attained superior simulation accuracy across all six scenarios. The highest precision indicators were observed in the sustainable development scenario, with kappa, OA, and FoM values reaching 0.9101, 93.15%, and 0.3895, respectively. The precise simulation method of the PLUS model, which considers the dynamic changes in influencing factors, is highly applicable at the national scale. (3) Under the sustainable development scenario, it is anticipated that China’s land use carbon emissions will reach their peak in 2030 and achieve the carbon-neutrality target by 2060. Net carbon emissions are expected to decline by 14.36% compared to the 2020 levels. From the perspective of dynamic changes in influencing factors, the PLUS model was used to accurately simulate China’s future land use. Based on these simulations, multi-scenario predictions of future carbon emissions were made, and the results uncover the spatiotemporal evolution characteristics of China’s carbon emissions. This study aims to offer a solid scientific basis for policy-making related to China’s low-carbon economy and high-quality development. It also intends to present Chinese solutions and key paths for achieving carbon peak and carbon neutrality. Full article

Microbial feed additives can effectively promote the healthy development of aquaculture, and Lactobacillus acidophilus can be utilized to mitigate disease risks and enhance productivity while minimizing antibiotic use. This article summarizes research on the application of L. acidophilus in aquaculture, focusing on growth and nutrient utilization, intestinal structure and microbial communities, disease prevention and control in aquatic organisms, and the regulation of water quality. This review holds significant implications for the development of compound feed additives and environmental regulators involving L. acidophilus, as well as for future aquatic food safety. Full article

Surface electromyographic (sEMG) signal-driven joint-angle estimation plays a critical role in intelligent rehabilitation systems, as its accuracy directly affects both control performance and rehabilitation efficacy. This study proposes a continuous elbow joint angle estimation method based on time–frequency domain analysis. Raw sEMG signals were processed using the Short-Time Fourier Transform (STFT) to extract time–frequency features. A Scale Temporal–Channel Cross-Encoder (STCCE) network was developed, integrating temporal and channel attention mechanisms to enhance feature representation and establish the mapping from sEMG signals to elbow joint angles. The model was trained and evaluated on a dataset comprising approximately 103,000 samples collected from seven subjects. In the single-subject test set, the proposed STCCE model achieved an average Mean Absolute Error (MAE) of $2.96\pm {0.24}^{\circ }$, Root Mean Square Error (RMSE) of $4.41\pm {0.45}^{\circ }$, Coefficient of Determination ($R^2$) of $0.9924\pm 0.0020$, and Correlation Coefficient (CC) of $0.9963\pm 0.0010$. It achieved a MAE of ${3.30}^{\circ }$, RMSE of ${4.75}^{\circ }$, $R^2$ of 0.9915, and CC of 0.9962 on the multi-subject test set, and an average MAE of $15.53\pm {1.80}^{\circ }$, RMSE of $21.72\pm {2.85}^{\circ }$, $R^2$ of $0.8141\pm 0.0540$, and CC of $0.9100\pm 0.0306$ on the inter-subject test set. These results demonstrated that the STCCE model enabled accurate joint-angle estimation in the time–frequency domain, contributing to a better motion intent perception for upper-limb rehabilitation. Full article

In this study, we analyzed data from 2992 cows to comprehensively evaluate the adult weight (WEI), a key growth and body-size indicator, in West China cattle, aiming to estimate the related phenotypic and genetic parameters. The analysis focused on four weight traits while considering non-genetic factors such as parity, season, year, and birth weight. Data were processed and corrected using a MIXED procedure and a multi-trait animal model. Results showed that these non-genetic factors significantly affected the weight traits (p < 0.05), which had high heritability (0.25–0.39) (p < 0.01). WEI is crucial for improving the genetic traits of cattle in western China and provides innovative approaches for optimizing herd management, enhancing the efficiency of genetic selection, and boosting beef cattle productivity. Full article

The conductors of high-speed railway OCSs (Overhead Contact Systems) are susceptible to conductor galloping due to the impact of natural elements such as strong winds, rain, and snow, resulting in conductor fatigue damage and significantly compromising train operational safety. Consequently, monitoring the galloping status of conductors is crucial, and instance segmentation techniques, by delineating the pixel-level contours of each conductor, can significantly aid in the identification and study of galloping phenomena. This work expands upon the YOLO11-seg model and introduces an instance segmentation approach for galloping video and image sensor data of OCS conductors. The algorithm, designed for the stripe-like distribution of OCS conductors in the data, employs four-direction Sobel filters to extract edge features in horizontal, vertical, and diagonal orientations. These features are subsequently integrated with the original convolutional branch to form the FDSE (Four Direction Sobel Enhancement) module. It integrates the ECA (Efficient Channel Attention) mechanism for the adaptive augmentation of conductor characteristics and utilizes the FL (Focal Loss) function to mitigate the class-imbalance issue between positive and negative samples, hence enhancing the model’s sensitivity to conductors. Consequently, segmentation outcomes from neighboring frames are utilized, and mask-difference analysis is performed to autonomously detect conductor galloping locations, emphasizing their contours for the clear depiction of galloping characteristics. Experimental results demonstrate that the enhanced YOLO11-seg model achieves 85.38% precision, 77.30% recall, 84.25% AP@0.5, 81.14% F1-score, and a real-time processing speed of 44.78 FPS. When combined with the galloping visualization module, it can issue real-time alerts of conductor galloping anomalies, providing robust technical support for railway OCS safety monitoring. Full article

The construction and maintenance of an ecological security pattern (ESP) are important for promoting the regional development of ecological civilizations, realizing sustainable and healthy development, and creating a harmonious and beautiful space for human beings and nature to thrive. Traditional construction methods have the limitations of a single dimension, a single method, and excessive human subjective intervention for source and corridor identification, without considering the multidimensional quality of the sources and the structural connectivity and resilience optimization of the corridors. Therefore, an ecological civilization demonstration area (Jiangxi Province) was used as the study area, a new research method for ESP was proposed, and an empirical study was conducted. To evaluate ecosystem service (ES) importance–disturbance–risk and extract sustainability sources through the deep embedded clustering–self-organizing map (DEC–SOM) deep unsupervised learning clustering algorithm, ecological networks (ENs) were constructed by applying the minimum cumulative resistance (MCR) gravity model and circuit theory. The ENs were then optimized to improve performance by combining the comparative advantages of the two approaches in terms of structural connectivity and resilience. A comparative analysis of EN performance was constructed among different functional control zones, and the ESP was constructed to include 42 ecological sources, 134 corridors, 210 restoration nodes, and 280 protection nodes. An ESP of ‘1 nucleus, 3 belts, 6 zones, and multiple corridors’ was constructed, and the key restoration components and protection functions were clarified. This study offers a valuable reference for ecological management, protection, and restoration and provides insights into the promotion of harmonious symbiosis between human beings and nature and sustainable regional development. Full article

To improve commutation accuracy and effectively suppress torque ripple in brushless DC motors (BLDCMs), this paper presents a novel commutation correction strategy integrated into an enhanced direct torque control (DTC) framework. The proposed method estimates the commutation angle error in real time by analyzing the integral difference in phase currents across adjacent 30° conduction intervals, enabling dynamic and accurate commutation correction. This correction mechanism is seamlessly embedded into a modified DTC algorithm that employs a three-level torque hysteresis comparator and introduces a novel zero-voltage vector selection strategy to minimize torque ripple. Compared with conventional DTC approaches employing dual-loop control and standard zero vectors, the proposed method achieves up to a 58% reduction in torque ripple along with improved commutation precision, as demonstrated through both simulation and experimental validation. These results confirm the method’s effectiveness and its potential for application in high-performance BLDCMs drive systems. Full article

Organic farming is widely recognized as a promising practice for sustainable agriculture, yet its long-term ecological impacts remain insufficiently investigated. In this study, we evaluated these impacts by comparing heavy metal concentrations, soil invertebrate communities, and microbial profiles between long-term organic and conventional farming systems. A comparative analysis was conducted on 24 plot soils from two paired organic and conventional farm systems in Beijing, each managed continuously for over 20 years. Our results revealed that soils under organic management consistently contained 10.8% to 73.7% lower heavy metals, along with reduced geo-accumulation indices (I_geo, a standardized metric for soil contamination assessment), indicating decreased contamination risks. In terms of soil fauna, while conventional soils showed higher Collembola abundance, organic farming significantly enhanced Collembola richness and diversity by 20.6% to 55.0%. Microbial sequencing likewise revealed enhanced richness and diversity of bacteria and fungi in organic soils. These microbial communities also displayed shifts in dominant taxa and more stable co-occurrence networks under organic management. Principal component analysis and Mantel tests identified soil pH and nutrients as key drivers of soil biodiversity, while heavy metals also imposed negative influences. Collectively, these findings demonstrate that long-term organic farming not only mitigates environmental risks associated with soil contaminants but also promotes belowground ecological integrity by supporting biodiversity of soil fauna and microbiota. This study highlights the ecological significance of sustained organic practices and provides critical insights for advancing sustainable agricultural developments. Full article

Codonopsis pilosula polysaccharides have demonstrated multiple biological activities including immune regulation, antitumor, and antioxidant properties. The rapid development and integrated application of multi-omics can facilitate the unraveling of the complex network of immune system regulation. In this study, C. pilosula alkali-extracted polysaccharide (CPAP) were prepared, and their effects on gut microbiota compositions, metabolic pathways, and protein expressions in peripheral blood and solid tumors in mice were further evaluated. The 16S rDNA sequencing results showed that CPAP could effectively promote the enrichment of intestinal Lactobacillus in tumor-bearing mice. In addition, it could be inferred from peripheral blood and solid tumor proteomics results that CPAP might activate T cell-mediated antitumor immune functions by regulating purine metabolism and alleviate tumor-caused inflammation by promoting neutrophil degranulation, finally inducing apoptosis in tumor cells by increasing oxidative stress. These results will provide a theoretical foundation and data support for the further development of CPAP as dietary adjuvants targeting immune deficiency-related diseases. Full article