Search Results (10,155)

With the continuous increase in the proportion of distributed energy output in the distribution network and the limited equipment on the management side of the active distribution network, it is very important to give full play to the regulating role of the dispatchable potential of large-scale electric vehicles for the economic operation of the distribution network. To deal with this issue, this paper proposes an optimal dispatching model of the distribution network considering the combination of the dispatchable potential of electric vehicle clusters and demand response. Firstly, the active distribution network dispatching model with the demand response is introduced, and the equipment involved in the active distribution network dispatching is modeled. Secondly, the bidirectional long short-term memory network algorithm is used to process the historical data of electric vehicles to reduce the uncertainty of the model. Then, the shared energy-storage characteristics based on the dispatchable potential of electric vehicle clusters are fully explored and the effect of peak shaving and valley filling after the demand response is fully explored. This approach significantly reduces the network loss and operating cost of the active distribution network. Finally, the modified IEEE-33 bus test system is utilized for test analysis in the case analysis, and the test results show that the established active distribution network model can reduce the early construction cost of the system’s energy-storage equipment, improve the energy-utilization efficiency, and realize the economic operation of the active distribution network. Full article

Three-dimensional environment reconstruction refers to the creation of mathematical models of three-dimensional objects suitable for computer representation and processing. This paper proposes a novel 3D environment reconstruction approach that addresses the field-of-view limitations commonly faced by LiDAR-based systems. A rotary-driven LiDAR mechanism is designed to enable uniform and seamless full-field-of-view scanning, thereby overcoming blind spots in traditional setups. To complement the hardware, a multi-sensor fusion framework—LV-SLAM (LiDAR-Visual Simultaneous Localization and Mapping)—is introduced. The framework consists of two key modules: multi-threaded feature registration and a two-phase loop closure detection mechanism, both designed to enhance the system’s accuracy and robustness. Extensive experiments on the KITTI benchmark demonstrate that LV-SLAM outperforms state-of-the-art methods including LOAM, LeGO-LOAM, and FAST-LIO2. Our method reduces the average absolute trajectory error (ATE) from 6.90 m (LOAM) to 2.48 m, and achieves lower relative pose error (RPE), indicating improved global consistency and reduced drift. We further validate the system in real-world indoor and outdoor environments. Compared with fixed-angle scans, the rotary LiDAR mechanism produces more complete reconstructions with fewer occlusions. Geometric accuracy evaluation shows that the root mean square error between reconstructed and actual building dimensions remains below 5 cm. The proposed system offers a robust and accurate solution for high-fidelity 3D reconstruction, particularly suitable for GNSS-denied and structurally complex environments. Full article

Ginger powder (GP) has antioxidant properties and can be a suitable alternative to antibiotics in laying hen diets; however, research on its effects remains limited. Therefore, our study aimed to evaluate the impact of dietary GP supplementation on production performance during the pre-peak production stage. A total of 270 hens, 18 weeks old and averaging 1.83 ± 0.03 kg, were divided into three groups: control (CN, basal diet), CN + 5 g/kg GP (T1), and CN + 10 g/kg GP (T2), with six replicates of 15 hens each, in a 10-week feeding trial. Dietary GP had no significant effect on feed intake (p > 0.05), but it dose-dependently improved laying rate, egg mass, and feed conversion ratio (p < 0.05). Egg quality parameters, including albumen height, Haugh unit, eggshell thickness, and strength, were also linearly improved with GP supplementation (p < 0.05). Dietary GP linearly enhanced the antioxidant status of hens (p < 0.01) and reduced malondialdehyde activity (p < 0.0001). Furthermore, 10 g/kg GP supplementation slightly improved gizzard index and liver morphology, and it linearly enhanced intestinal morphology (p < 0.01). These findings suggest that 10 g/kg GP supplementation can improve the productivity and health of laying hens. Full article

The genus Trichoderma plays a pivotal role in sustainable agriculture through its multifaceted contributions to plant health and productivity. This review explores Trichoderma’s biological functions, including its roles as a biocontrol agent, plant growth promoter, and stress resilience enhancer. By producing various enzymes, secondary metabolites, and volatile organic compounds, Trichoderma effectively suppresses plant pathogens, promotes root development, and primes plant immune responses. This review details the evolutionary adaptations of Trichoderma, which has transitioned from saprotrophism to mycoparasitism and established beneficial symbiotic relationships with plants. It also highlights the ecological versatility of Trichoderma in colonizing plant roots and improving soil health, while emphasizing its role in mitigating both biotic and abiotic stressors. With increasing recognition as a biostimulant and biocontrol agent, Trichoderma has become a key player in reducing chemical inputs and advancing eco-friendly farming practices. This review addresses challenges such as strain selection, formulation stability, and regulatory hurdles and concludes by advocating for continued research to optimize Trichoderma’s applications in addressing climate change, enhancing food security, and promoting a sustainable agricultural future. Full article

The epidermal growth factor receptor (EGFR) is a key target for both cancer diagnosis and therapeutic interventions. Assessing EGFR expression before therapy has become routine in clinical practice, yet current methods like biopsy and immunohistochemistry (IHC) have significant limitations, including invasiveness, limited repeatability, and lack of real-time, whole-body data. EGFR-targeted imaging has emerged as a promising alternative. EGFR-targeting peptides, owing to their favorable physicochemical properties and versatility, are increasingly being explored for a variety of applications, including molecular imaging, drug delivery, and targeted therapy. Recent advances have demonstrated the potential of EGFR-targeting peptides conjugated to imaging probes for non-invasive, real-time in vivo tumor detection, precision therapy, and surgical guidance. Here, we provide a comprehensive overview of the latest progress in EGFR-targeting peptides development, with a particular focus on their application in the development of molecular imaging agents, including fluorescence imaging, PET/CT, magnetic resonance imaging, and multimodal imaging. Furthermore, we examine the challenges and future directions concerning the development and clinical application of EGFR-targeting peptide-based imaging probes. Finally, we highlight emerging technologies such as artificial intelligence, mutation-specific peptides, and multimodal imaging platforms, which offer significant potential for advancing the diagnosis and treatment of EGFR-targeted cancers. Full article

With the development of the automotive industry, the performance of commercial vehicle braking systems is crucial for road traffic safety. However, traditional braking systems are no longer able to meet the growing demand for response speed, control accuracy, and adaptability to complex operating conditions. To this end, this article focuses on improving the braking performance of commercial vehicles, designs and develops a new integrated high-response-speed EBS, explains its structure and function, proposes a pressure delay compensation control method for wire-controlled braking systems, establishes relevant models, designs control processes, and conducts braking simulations. Braking experiments are also conducted on a commercial 6 × 4 tractor on different road surfaces. The research results show that the system has good braking response performance under typical working conditions such as low adhesion, high adhesion, and opposite docking. The braking time is short (for example, the initial braking time at 40 km/h on high-adhesion roads is only 2.209 s, and the initial braking time at 50 km/h on opposite roads is 6.68 s), and the braking safety performance is superior, meeting the requirements of relevant standards. The contribution of this study lies in the proposed time delay compensation control method for wire-controlled braking, which effectively solves the problem of low control accuracy caused by time delay in wire-controlled braking systems. The integrated EBS designed integrates multiple functions, improves driving safety and comfort, and provides strong support for the upgrade of commercial vehicle braking technology, with good application prospects. Full article

Understanding the environmental drivers of radial growth in the Pinus massoniana (lamb.) is essential for improving forest productivity and carbon sequestration in subtropical ecosystems. This study used the basal area increment (BAI) as an indicator of radial growth to investigate the main factors affecting the radial growth rate of P. massoniana and the changes in BAI with these factors. A total of 58 high quality tree ring series were analyzed. Six common methods were used to comprehensively analyze the importance of nine factor variables on the BAI, including tree age, competition index, average temperature, and so on. Generalized additive models (GAMs) were developed to explore the nonlinear relationships between each selected variable and the BAI. The results revealed the following: (1) Age and Competition Index was identified as the primary driving force; (2) BAI increased with Age when tree age was below 69 years; (3) from the overall trend, the BAI of P. massoniana decreased with the increase in the Competition Index. These findings provide a scientific basis for developing management plans for P. massoniana forests. Full article

Efficient task offloading for delay-sensitive applications, such as autonomous driving, presents a significant challenge in multi-hop Vehicular Edge Computing (VEC) networks, primarily due to high vehicle mobility, dynamic network topologies, and complex end-to-end congestion problems. To address these issues, this paper proposes a graph attention-based reinforcement learning algorithm, named GAPO. The algorithm models the dynamic VEC network as an attributed graph and utilizes a graph neural network (GNN) to learn a network state representation that captures the global topological structure and node contextual information. Building on this foundation, an attention-based Actor–Critic framework makes joint offloading decisions by intelligently selecting the optimal destination and collaboratively determining the ratios for offloading and resource allocation. A multi-objective reward function, designed to minimize task latency and to alleviate link congestion, guides the entire learning process. Comprehensive simulation experiments and ablation studies show that, compared to traditional heuristic algorithms and standard deep reinforcement learning methods, GAPO significantly reduces average task completion latency and substantially decreases backbone link congestion. In conclusion, by deeply integrating the state-aware capabilities of GNNs with the decision-making abilities of DRL, GAPO provides an efficient, adaptive, and congestion-aware solution to the resource management problems in dynamic VEC environments. Full article

In the summer of 2022, central and eastern China experienced prolonged extreme high temperatures and severe drought, leading to significant economic losses. To gain a more profound understanding of this drought event and furnish a reference for forecasting similar events in the future, this study examines the circulation anomalies associated with the drought. Employing a diagnostic method focused on temperature and moisture anomalies, this study introduces a novel approach to quantify and compare the relative significance of moisture transport and warm air dynamics in contributing to the drought. This study examines the atmospheric circulation anomalies linked to the drought event and compares the relative contributions of water vapor transport and warm air activity in causing the drought, using two parameters defined in the paper. The results show the following: (1) The West Pacific Subtropical High (WPSH) was more intense than usual and extended westward, consistently controlling the Yangtze River Basin. Simultaneously, the polar vortex area was smaller and weaker, the South Asian High area was larger and stronger, and it shifted eastward. These factors collectively led to weakened water vapor transport conditions and prevailing subsiding air motions in the Yangtze River Basin, causing frequent high temperatures. (2) By defining I_q and I_t to represent the contributions of moisture and temperature to precipitation, we found that the drought event in the Yangtze River Basin was driven by both reduced moisture supplies in the lower troposphere and higher-than-normal temperatures, with temperature playing a dominant role. Full article

Background/Objectives: The diminished efficacy of azoles in treating fungal infections is attributed to the emergence of resistance among pathogenic fungi. Employing a synergistic approach with other compounds to enhance the antifungal activity of azoles has shown promise, yet the availability of clinically valuable adjuvants for azoles and allylamines remains limited. Studies have demonstrated that the human host environment provides multiple carbon sources, which can influence the susceptibility of C. albicans to antifungal agents. Therefore, a comprehensive investigation into the mechanisms by which carbon sources modulate the susceptibility of C. albicans to azoles may uncover a novel pathway for enhancing the antifungal efficacy of azoles. Methods: This study explored the impact of various carbon sources on the antifungal efficacy of azoles through methodologies including minimum inhibitory concentration (MIC) assessments, super-MIC growth (SMG) assays, disk diffusion tests, and spot assays. Additionally, the mechanism by which galactose augments the antifungal activity of azoles was investigated using a range of experimental approaches, such as gene knockout and overexpression techniques, quantitative real-time PCR (qRT-PCR), Western blot analysis, and cycloheximide (CHX) chase experiments. Results: This study observed that galactose enhances the efficacy of azoles against C. albicans by inhibiting the translation of Erg1. This results in the suppression of Erg1 protein levels and subsequent inhibition of ergosterol biosynthesis in C. albicans. Conclusions: In C. albicans, the translation of Erg1 is inhibited when galactose is utilized as a carbon source instead of glucose. This novel discovery of galactose’s inhibitory effect on Erg1 translation is expected to enhance the antifungal efficacy of azoles. Full article

Morphology is an important characteristic of the hydraulic and gravitational processes driving gully erosion. In this study, field scouring experiments were conducted on five experimental plots using terrestrial laser scanning to study gully erosion processes. The erosion and deposition on a gully slope were quantified using the M3C2 algorithm. The results show that the proportion of sediment yield of the gully slope in the whole slope–gully system ranged from 81.5% to 99.7% for different flow discharges (25, 40, 55, 70, and 85 L/min). Compared with low flow discharges (25 and 40 L/min), the gully slope presented more intense gully head retreat and higher erosion intensity under relatively high discharges (55, 70, and 85 L/min). Alcove expansion processes were characterized by horizontal and vertical cycles. Vertical dynamic changes were dominated by the co-evolution of collapses of the gully head and the deepening of the alcove. Horizontal development mainly manifested as a widening of the alcove caused by the hydraulic erosion of the gully wall. The roughness of the gully slope increased gradually with the increase in scour times and then tended towards stability. These results provide a reference for understanding the processes and mechanisms of gully erosion. Full article

In this study, we investigated the effects of air packaging, vacuum packaging and modified atmosphere packaging (CO₂/N₂: 80/20) on the purine metabolism and enzyme activities of refrigerated large yellow croakers. The results showed that modified atmosphere packaging significantly inhibited microbial growth, delayed adenosine triphosphate degradation and maintained higher IMP content (1.93 μmol/g on day 21) compared to the air packaging group (2.82 μmol/g on day 12). The total purine content increased with storage time, with hypoxanthine content increasing significantly and occupying most of the total content, which was the key factor for the elevation of purine, followed by adenine content showing a significant decreasing trend. Hypoxanthine accumulation was significantly suppressed in the modified atmosphere packaging group (2.31 μmol/g on day 18), which was much lower than that in the air packaging group (5.64 μmol/g), whereas xanthine and guanine did not show significant differences among the groups. The key enzymes xanthine oxidase and purine nucleoside phosphorylase were much less active in modified atmosphere packaging, effectively delaying the cascade reaction of inosine monophosphate → hypoxanthine → xanthine. The study confirmed that modified atmosphere packaging intervenes in purine metabolism through enzyme activity regulation, providing a theoretical basis for the preservation of low purine aquatic products. Full article

High-performance waterproof and breathable nanofiber membranes (WBNMs) are in great demand for various advanced applications. However, the fabrication of such membranes often relies on fluorinated materials or involves complex preparation processes, limiting their practical use. In this study, we present an innovative approach by utilizing silicon-containing polyurethane (SiPU) as a single-component, fluorine-free raw material to prepare high-performance WBNMs via a simple one-step electrospinning process. The electrospinning technique enables the formation of SiPU nanofibrous membranes with a small maximum pore size (d_max) and high porosity, while the intrinsic hydrophobicity of SiPU imparts excellent water-repellent characteristics to the membranes. As a result, the single-component SiPU WBNM exhibits superior waterproofness and breathability, with a hydrostatic pressure of 52 kPa and a water vapor transmission rate (WVTR) of 5798 g m⁻² d⁻¹. Moreover, the optimized SiPU-14 WBNM demonstrates outstanding mechanical properties, including a tensile strength of 6.15 MPa and an elongation at break of 98.80%. These findings indicate that the single-component SiPU-14 WBNMs not only achieve excellent waterproof and breathable performance but also possess robust mechanical strength, thereby enhancing the comfort and expanding the potential applications of protective textiles, such as outdoor apparel and car seats. Full article

Traditional path planning algorithms often fail to simultaneously ensure operational efficiency, energy constraint compliance, and environmental adaptability in agricultural scenarios, thereby hindering the advancement of precision agriculture. To address these challenges, this study proposes a deep reinforcement learning algorithm, MoE-D3QN, which integrates a Mixture-of-Experts mechanism with a Bi-directional Long Short-Term Memory model. This design enhances the efficiency and robustness of UAV path planning in agricultural environments. Building upon this algorithm, a hierarchical coverage path planning framework is developed. Multi-level task maps are constructed using crop information extracted from Sentinel-2 remote sensing imagery. Additionally, a dynamic energy consumption model and a progressive composite reward function are incorporated to further optimize UAV path planning in complex farmland conditions. Simulation experiments reveal that in the two-level scenario, the MoE-D3QN algorithm achieves a coverage efficiency of 0.8378, representing an improvement of 37.84–63.38% over traditional algorithms and 19.19–63.38% over conventional reinforcement learning methods. The redundancy rate is reduced to 3.23%, which is 38.71–41.94% lower than traditional methods and 4.46–42.77% lower than reinforcement learning counterparts. In the three-level scenario, MoE-D3QN achieves a coverage efficiency of 0.8261, exceeding traditional algorithms by 52.13–71.45% and reinforcement learning approaches by 10.15–50.2%. The redundancy rate is further reduced to 5.26%, which is significantly lower than the 57.89–92.11% observed with traditional methods and the 15.57–18.98% reported for reinforcement learning algorithms. These findings demonstrate that the MoE-D3QN algorithm exhibits high-quality planning performance in complex farmland environments, indicating its strong potential for widespread application in precision agriculture. Full article

The green transformation of traditional energy structures and the development of the new energy industry are crucial drivers of sustainable development in the country. The ASEAN Plan of Action for Energy Cooperation (2016–2025; APAEC [2016–2025]), established in 2016, has significantly promoted the growth of the new energy sector and enhanced energy structures across Association of Southeast Asian Nations (ASEAN). This initiative has also inspired these countries to develop corresponding industrial policies aimed at supporting the new energy vehicle (NEV) industry, resulting in significant growth in this sector within the ASEAN region. This paper analyzes the factors influencing the development of the NEV industry in the context of ASEAN’s new energy policies, drawing empirical insights from data collected across six ASEAN countries from 2013 to 2024. Following the implementation of the APAEC (2016–2025), it was observed that ASEAN countries reached a consensus on energy development and cooperation, collaboratively advancing the NEV industry through regional policies. Furthermore, factors such as national governance, financial development, education levels, and the size of the automotive market positively contribute to the growth of the NEV industry in ASEAN. Conversely, high energy consumption can hinder its progress. Additionally, further research indicates that the APAEC (2016–2025) has exerted a more pronounced impact on countries with robust automotive industry foundations or those prioritizing relevant policies. The findings of this paper offer valuable insights for ASEAN countries in the formulating policies for the NEV industry, optimizing energy structures, and achieving low-carbon energy transition and sustainable development. Full article