Search Results (370)

Understanding the migratory strategies of plateau-endemic species is essential for informing effective conservation, especially under climate change. The Black-necked Crane (Grus nigricollis), a high-altitude specialist, has shown notable population growth in recent years. We analysed satellite tracking data from 16 individuals of a western subpopulation in the lake basin region of northern Tibet (2021–2024), focusing on migration patterns, stopover use, and habitat selection. This subpopulation exhibited short-distance (mean: 284.21 km), intra-Tibet migrations with low reliance on stopover sites. Autumn migration was shorter, more direct, higher in altitude, and slower in speed than spring migration. Juveniles used smaller, more fragmented habitats than subadults, and their spatial range expanded over time. Given these patterns, we infer that the short-distance migration strategy may reduce energetic demands and mortality risks while increasing route flexibility—characteristics that may benefit population growth. We refer to this as a low-energy, high-efficiency migration strategy, which we hypothesise could support faster population growth and enhance resilience to environmental change. We recommend prioritizing the conservation of short-distance migration corridors, such as the typical lake basin area in northern Tibet–Yarlung Tsangpo River system, which may help sustain plateau-endemic migratory populations under future climate scenarios. Full article

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

Cotton fiber initiation determines the fiber yield, yet the genetic basis underlying lint and fuzz initiation has still not been fully uncovered. Here, map-based cloning was carried out to identify the fiberless mutant genes derived from a cross between Gossypium hirsutum acc. WT and a natural fiberless mutant, fbl_SHZ. The 12:3:1 segregation ratio in F₂ populations (including 1848 and 3100 individuals that were developed in 2016 and 2018, respectively) revealed dominant epistasis, with the fuzz gene exerting dominance over the lint gene. Genetic linkage analysis revealed that GhMYB25like_A12 controls fuzz fiber initiation, while both GhMYB25like_A12 and GhMYB25like_D12 regulate lint fiber development. Sequencing analyses showed that the fbl_SHZ mutant exhibited a K104M mutation in the R2R3 domain of GhMYB25like_A12 and a transposable element insertion in GhMYB25like_D12, leading to fiberless seeds. Knockout of GhMYB25like_A12 produced fuzzless seeds, knockout of GhMYB25like_D12 led to no obvious change in seeds, and knockout of both (GhMYB25like_A12&D12) resulted in fiberless seeds. The 12:3:1 ratio reappeared in the F₂ population developed from the GhMYB25like_A12&D12 mutated plants as female and Jin668 as the male, which further confirmed the genetic interaction observed in fbl_SHZ. RNA-seq analysis revealed that GhMYB25like regulates cotton fiber initiation through multiple pathways, especially fatty acid metabolism. This study elucidates the key genes and their genetic interaction mechanisms governing cotton fiber initiation, providing a theoretical foundation for genetic improvement of cotton fiber traits. Full article

This study aimed to explore the effects of dietary supplementation with soy isoflavones (SI) in the later stages of pregnancy on the antioxidant capacity of sows and intestinal health of newborn piglets. Forty sows with similar body weights and parity (average of 1–2 parity) were randomly divided into two groups (n = 20): the control group and SI group (dose: 100 mg/kg of feed). Feeding was started on day 85 of gestation and continued until farrowing. SI supplementation significantly increased the antioxidant levels in the serum of the sows and newborn piglets, placental tissue, and the intestinal tract of the piglets. This observation was indicated by a decreased activity of the oxidative stress marker malondialdehyde (MDA); increased activity of antioxidant enzymes such as superoxide dismutase, glutathione peroxidase, and catalase; and enhanced total antioxidant capacity. The organ indices of the intestine and liver and the villus height/crypt depth of the jejunum of newborn piglets significantly increased. SI supplementation activated the Nrf2 signaling pathway in the jejunum of neonatal piglets and the expression of placental antioxidant proteins, and it downregulated the expression of the Bax and Caspase 3 apoptotic proteins in the placenta and neonatal piglets. Intestinal and placental barrier integrity was strengthened. For example, ZO-1, Occludin, and Claudin 1 exhibited elevated expression. In conclusion, dietary supplementation with SI enhanced the antioxidant capacity of sows and piglets and improved the health of the placenta and intestinal tract of newborn piglets. Full article

Ubiquitous digital array radar (UDAR) extends the integration time of moving targets by deploying a wide transmitting beam and multiple narrow receiving beams to cover the entire observed airspace. By exchanging time for energy, it effectively improves the detection ability for weak targets. Nevertheless, target motion introduces severe across-range unit (ARU), across-Doppler unit (ADU), and across-beam unit (ABU) effects, dispersing target energy across the range–Doppler-beam space. This paper proposes a beam domain angle rotation compensation and keystone-matched filtering (BARC-KTMF) algorithm to address the “three-crossing” challenge. This algorithm first corrects ABU by rotating beam–domain coordinates to align scattered energy into the final beam unit, reshaping the signal distribution pattern. Then, the KTMF method is utilized to focus target energy in the time-frequency domain. Furthermore, a special spatial windowing technique is developed to improve computational efficiency through parallel block processing. Simulation results show that the proposed approach achieves an excellent signal-to-noise ratio (SNR) gain over the typical single-beam and multi-beam long-time coherent integration (LTCI) methods under low SNR conditions. Additionally, the presented algorithm also has the capability of coarse estimation for the target incident angle. This work extends the LTCI technique to the beam domain, offering a robust framework for high-speed weak target detection. Full article

Tungsten and tungsten alloys are widely used in important industrial fields due to their high density, hardness, melting point, and corrosion resistance. However, machining often leaves processing marks on their surface, significantly affecting the surface quality of precision components in industrial applications. Electrolytic polishing offers high efficiency, low workpiece wear, and simple processing. In this study, an electrolytic polishing method is adopted and a novel trisodium phosphate–sodium hydroxide electrolytic polishing electrolyte is developed to study the effects of temperature, voltage, polishing time, and solution composition on the surface roughness of a tungsten–nickel–iron alloy. The optimal voltage, temperature, and polishing time are determined to be 15 V, 55 °C, and 35 s, respectively, when the concentrations of trisodium phosphate and sodium hydroxide are 100 g·L⁻¹ and 6 g·L⁻¹. In addition, glycerol is introduced into the electrolyte as an additive. The calculated LUMO value of glycerol is −5.90 eV and the HOMO value is 0.40 eV. Moreover, electron enrichment in the hydroxyl region of glycerol can form an adsorption layer on the surface of the tungsten alloy, inhibit the formation of micro-pits, balance ion diffusion, and thus promote the formation of a smooth surface. At 100 mL·L⁻¹ of glycerol, the roughness of the tungsten–nickel–iron alloy decreases significantly from 1.134 μm to 0.582 μm. The electrochemical polishing mechanism of the tungsten alloy in a trisodium phosphate electrolyte is further investigated and explained according to viscous film theory. This study demonstrates that the trisodium phosphate–sodium hydroxide–glycerol electrolyte is suitable for electropolishing tungsten–nickel–iron alloys. Overall, the results support the application of tungsten–nickel–iron alloy in the electronics, medical, and atomic energy industries. Full article

Maintenance scheduling of hydropower units is essential for ensuring the operational security and stability of large-scale cascaded hydropower systems and for improving the efficiency of water energy utilization. This study takes the Cascaded Hydropower System of the Lower Jinsha River (CHSJS) as a representative case, identifying four key challenges facing maintenance planning: multi-dimensional influencing factor coupling, spatial and temporal conflicts with generation dispatch, coordination with transmission line maintenance, and compound uncertainties of inflow and load. To address these issues, four strategic recommendations are proposed: (1) identifying and quantifying the impacts of multi-factor influences on maintenance planning; (2) developing integrated models for the co-optimization of power generation dispatch and maintenance scheduling; (3) formulating coordinated maintenance strategies for hydropower units and associated transmission infrastructure; and (4) constructing joint models to manage the coupled uncertainties of inflow and load. The strategy proposed in this study was applied to the CHSJS, obtaining the weight of the impact factor. The coordinated unit maintenance arrangements of transmission line maintenance periods increased from 56% to 97%. This study highlights the critical need for synergistic optimization of generation dispatch and maintenance scheduling in large-scale cascaded hydropower systems and provides a methodological foundation for future research and practical applications. Full article

The ability to collaborate with new teammates, adapt to unfamiliar environments, and engage in effective planning is essential for multi-drone agents within unmanned combat systems. This paper introduces DETEAMSK (Model-based Reinforcement Learning by Decoupling the Identification of Teammates and Tasks), a model-based reinforcement learning method in intelligent top-level planning and decisions designed for ad hoc teamwork among multi-drone agents. It specifically addresses integrated reconnaissance and strike missions in urban combat scenarios under varying conditions. DETEAMSK’s performance is evaluated through comprehensive, multidimensional experiments and compared with other baseline models. The results demonstrate that DETEAMSK exhibits superior effectiveness, robustness, and generalization capabilities across a range of task domains. Moreover, the model-based reinforcement learning approach offers distinct advantages over traditional models, such as the PLASTIC-Model, and model-free approaches, like the PLASTIC-Policy, due to its unique “dynamic decoupling identification” feature. This study provides valuable insights for advancing both theoretical and applied research in model-based reinforcement learning methods for multi-drone systems. Full article

Rapid urbanization has exacerbated the urban heat island effect, posing a significant threat to human health and urban ecosystems. While numerous studies have demonstrated that urban morphology significantly influences land surface temperatures (LSTs), few have systematically explored the impact and contribution of urban morphology on LST across different functional zones. Therefore, this study takes Xi’an as a case and employs an interpretable CatBoost-SHAP machine learning model to evaluate the nonlinear influence of building landscape features on LST in different functional zones during summer. The results indicate the following: (1) The highest LST in the study area reached 52.68 °C, while the lowest was 21.68 °C. High-temperature areas were predominantly concentrated in the urban center and industrial zones with dense buildings, whereas areas around water bodies and green spaces exhibited relatively lower temperatures. (2) SHAP analysis revealed that landscape indicators exerted the most substantial impact across all functional zones, with green space zones contributing up to 62%. Among these, fractional vegetation coverage (FVC), as a core landscape factor, served as the primary cooling factor in all six functional zones and consistently demonstrated a negative effect. (3) Population density (POP) exhibited a generally high SHAP contribution across all functional zones, showing a positive correlation. Its effect was most pronounced in commercial zones, accounting for 16%. When POP ranged between 0 and 250 people, the warming effect was particularly prominent. (4) The mean building height (MBH) constituted a major influencing factor in most functional zones, especially in residential zones, where the SHAP value reached 0.7643. Within the range of 10–20 m, the SHAP value increased sharply, indicating a significant warming effect. (5) This study proposes targeted cooling strategies tailored to six functional zones, providing a scientific basis for formulating targeted mitigation strategies for different functional zones to alleviate the urban heat island effect. Full article

Autonomous exploration of autonomous vehicles in off-road environments remains challenging due to the adverse impact on exploration efficiency and safety caused by uneven terrain. In this paper, we propose a path planning framework for autonomous exploration to obtain feasible and smooth paths for autonomous vehicles in 3D off-road environments. In our framework, we design a target selection strategy based on 3D terrain traversability analysis, and the traversability is evaluated by integrating vehicle dynamics with geometric indicators of the terrain. This strategy detects the frontiers within 3D environments and utilizes the traversability cost of frontiers as the pivotal weight within the clustering process, ensuring the accessibility of candidate points. Additionally, we introduced a more precise approach to evaluate navigation costs in off-road terrain. To obtain a smooth local path, we generate a cluster of local paths based on the global path and evaluate the optimal local path through the traversability and smoothness of the path. The method is validated in simulations and real-world environments based on representative off-road scenarios. The results demonstrate that our method reduces the exploration time by up to 36.52% and ensures the safety of the vehicle while exploring unknown 3D off-road terrain compared with state-of-the-art methods. Full article

This study aimed to determine whether the fetuses experienced hypoxic distress or intra-partum death due to compromised oxygen supply by quantitatively analyzing the lung structures of deceased captive South China Tiger (Panthera tigris amoyensis, SCT) cubs. Furthermore, it investigated the etiology and mechanisms of asphyxia in the deceased cubs and explored potential factors contributing to the high mortality rate of SCT cubs. The research focused on three deceased SCT cubs, using three deceased neonatal Amur Tigers (P. t. altaica, AT) with no inbreeding background as controls. Histological analysis of the cubs’ lungs was conducted using hematoxylin–eosin (H&E) and special staining techniques. The possible causes of death in SCT cubs were evaluated by comparing pulmonary pathological changes and morphological parameters, including alveolar space (P(ASP)) values, mean alveolar linear intercept (L_m), and mean thickness of alveolar septa (Tas). Our research reveals that hypoxia is one of the most significant factors contributing to the mortality of tiger cubs. Additionally, we hypothesize that inbreeding depression may lead to abnormal lung development (e.g., thickening of lung tissue) in SCT cubs. This study lays the foundation for comprehensive investigations into the mortality of highly inbred SCT cubs. Full article

Direct chemical vapor deposition (CVD) growth of hexagonal boron nitride (h-BN) on insulating substrates offers a promising pathway to circumvent transfer-induced defects and enhance device integration. This comprehensive review systematically evaluates recent advances in CVD techniques for h-BN synthesis on insulating substrates, including metal–organic CVD (MOCVD), low-pressure CVD (LPCVD), atmospheric-pressure CVD (APCVD), and plasma-enhanced CVD (PECVD). Key challenges, including precursor selection, high-temperature processing, achieving single-crystalline films, and maintaining phase purity, are critically analyzed. Special emphasis is placed on comparative performance metrics across different growth methodologies. Furthermore, crucial research directions for future development in this field are outlined. This review aims to serve as a reference for advancing h-BN synthesis toward practical applications in next-generation electronic and optoelectronic devices. Full article

The frequent occurrence of natural disasters creates a symmetry-breaking scenario between pre-disaster planning and post-disaster rescue operations, such as post-disaster supply–demand mismatches for materials and the risk of potential facility failures. Thus, we propose a dual-uncertainty multi-scenario multi-period facility location allocation model for humanitarian rescue. The model employs two polyhedral uncertainty sets to represent facility failure risks and demand uncertainty at disaster points. Moreover, by constructing diverse disaster scenarios, it simulates material distribution schemes across different relief periods, enhancing its realism. Given that the model integrates three subproblems—facility location, supply–demand matching analysis, and emergency material allocation—we design a hybrid algorithm (DCSA-MA) that combines the discrete crow search algorithm (DCSA) and the material allocation (MA) method for its solution. Experimental results demonstrate that the model maintains a relatively high material satisfaction rate even under significant demand fluctuations. The number of facility failures has a direct bearing on emergency rescue effectiveness. The DCSA-MA method achieves a superior material satisfaction rate compared to other algorithms across various disaster scenarios and multiple rescue periods. Furthermore, DCSA-MA outperforms other algorithms in terms of solution quality, convergence, computational time, and stability. These findings indicate that DCSA-MA is an effective and highly stable approach. Full article

Caffeic acid phenethyl ester (CAPE) is identified to be an efficacious bioactive polyphenol in propolis for ameliorating glucose and lipid metabolism disorders and inflammation. In this study, an alcohol-induced zebrafish inflammation model was established. CAPE treatments at different concentrations (0.04, 0.2, and 1.0 μg/mL) were administered to alcohol-exposed zebrafish to investigate the underlying mechanisms of alleviating alcohol-induced liver inflammation using transcriptomic analysis and 16S rRNA gene sequencing methods. The results indicated that CAPE decreased the expressions of TNF-α and IL-1β and significantly increased the expression of IL-10 (p < 0.0001). Based on the KEGG enrichment analysis of transcriptomic sequencing, CAPE effectively alleviated the inflammation in zebrafish mainly through pancreatic secretion, complement and coagulation cascades, and protein digestion and absorption. Molecular docking supported the potential of CAPE in targeting cholecystokinin (CCK) A Receptor (CCKAR) and mediating the regulation of pancreatic secretion and related inflammation pathways. Moreover, intestinal microbiota analysis demonstrated that CAPE could improve the alcohol-induced microbiota disorder. Additionally, there was a significant correlation between the key genes related to lipid and sterol metabolism among the KEGG-enriched pathways and the specific intestinal microbial communities in zebrafish. Flavobacterium from Bacteroidota was significantly positively correlated with CEL1, CEL2, and LPIN (p < 0.01), which suggested that the anti-inflammatory function of CAPE was closely associated with the intestinal microbiota improvement. In conclusion, our findings demonstrated that CAPE could ameliorate liver inflammation in alcohol-induced zebrafish, which was mainly associated with the regulation of pancreatic secretion and intestinal microbiota disorder. This study emphasized the anti-inflammatory mechanisms of CAPE based on targeting the pancreatic secretion pathway, which will broaden the application of natural antioxidants in improving metabolic and inflammatory problems. Full article

Pulsed eddy current (PEC) testing technology has been widely used in the field of non-destructive testing of metal grounding structures due to its wide-band excitation and response characteristics. However, multi-source noise in industrial environments can significantly degrade the performance of PEC sensors, thereby limiting their detection accuracy. This study proposes a multi-modal joint pulsed eddy current signal sensor denoising method that integrates the inductive disturbance mechanism. This method constructs the Improved Whale Optimization -Variational Mode Decomposition-Singular Value Decomposition-Wavelet Threshold Denoising (IWOA-VMD-SVD-WTD) fourth-order processing architecture: IWOA adaptively optimizes the VMD essential variables (K, α) and employs the optimized VMD to decompose the perception coefficient (IMF) of the PEC signal. It utilizes the correlation coefficient criterion to filter and identify the primary noise components within the signal, and the SVD-WTD joint denoising model is established to reconstruct each component to remove the noise signal received by the PEC sensor. To ascertain the efficacy of this approach, we compared the IWOA-VMD-SVD-WTD method with other denoising methods under three different noise levels through experiments. The test results show that compared with other VMD-based denoising techniques, the average signal-to-noise ratio (SNR) of the PEC signal received by the receiving coil for 200 noise signals in different noise environments is 24.31 dB, 29.72 dB and 29.64 dB, respectively. The average SNR of the other two denoising techniques in different noise environments is 15.48 dB, 18.87 dB, 18.46 dB and 19.32 dB, 27.13 dB, 26.78 dB, respectively, which is significantly better than other denoising methods. In addition, in practical applications, this method is better than other technologies in denoising PEC signals and successfully achieves noise reduction and signal feature extraction. This study provides a new technical solution for extracting pure and impurity-free PEC signals in complex electromagnetic environments. Full article