Search Results (3,067)

With the increasing demand for high integration, low cost, and large capacities in satellite systems, integrating the antenna and microwave component into the same system has become appealing to the satellite engineer. The dual C-type gold ribbon, performing as the key electromagnetic signal bridge between the microwave component and the antenna, has a significant impact on the electrical performance of satellite antennas. However, during its manufacturing and operating, the interconnection geometry undergoes deformation due to mounting errors and environmental loads. Consequently, these parasitic geometry parameters can significantly increase energy loss during the signal transmission. To address this issue, this paper has proposed a method for determining the design range of the geometrical parameters of the dual C-type gold ribbon, and applied it to the performance prediction of the microstrip antennas and the parameter optimization of the gold ribbon. In this study, a mechanical response analysis of the antennas in the operating environment has been carried out and the manufacturing disturbance has been considered to calculate the geometry fluctuation range. Then, the significance ranking of the geometry parameters has been determined and the key parameters have been selected. Finally, the chaos feedback adaptive whale optimization algorithm–back propagation neural network has been used as a surrogate model to establish the relationship between the geometry parameters and the antenna electromagnetic performance, and the multi-objective red-billed blue magpie optimization algorithm has been combined with the surrogate model to optimize the configuration parameters. This paper provides theoretical guidance for the interconnection geometry design and the optimization of the integration module of the antennas and microwave components. Full article

 Porcine epidemic diarrhea virus (PEDV) continues to circulate globally, causing substantial economic losses to the swine industry. Historically, PEDV strains are classified into the classical G1, epidemic G2, and S-INDEL genotypes. Among these genotypes, the highly virulent and prevalent G2 genotype has been extensively studied. However, recent clinical outbreaks in China necessitate a reevaluation of the epidemiological and evolutionary dynamics of circulating strains. This study analyzed 37 newly sequenced S genes and public sequences to characterize the genetic variations of S-INDEL strains. Our analysis revealed that S-INDEL strains are endemic throughout China, with a phylogenetic analysis identifying two distinct clades: clade 1, comprising early endemic strains, and clade 2, representing a recently dominant, geographically restricted lineage in China. While inter-genotypic recombination has been documented, our findings also demonstrate that intra-genotypic and intra-clade recombination events contributed significantly to the emergence of clade 2, distinguishing its evolutionary pattern from clade 1. A comparative analysis identified 22 clade-specific amino acid changes, 11 of which occurred in the D0 domain. Notably, mutations at positively selected sites—113 and 114 within the D0 domain, a domain associated with pathogenicity—were specific to clade 2. A phylodynamic analysis indicated Germany as the epicenter of S-INDEL dispersal, with China acting as a sink population characterized by localized transmission networks and frequent recombination events. These results demonstrate that contemporary S-INDEL strains, specifically clade 2, exhibit unique recombination patterns and mutations potentially impacting virulence. Continuous surveillance is essential to assess the pathogenic potential of these evolving recombinant variants and the efficacy of vaccines against them.  Full article

Fibrillins (FBNs) are indispensable for plant growth and development, orchestrating multiple physiological processes. However, the precise functional role of FBNs in cotton fiber development remains uncharacterized. This study reports a genome-wide characterization of the FBN gene family in cotton. A total of 28 GhFBN genes were identified in upland cotton, with systematic analyses of their phylogenetic relationships, protein motifs, gene structures, and hormone-responsive cis-regulatory elements. Expression profiling of GhFBN1A during fiber development revealed stage-specific activity across the developmental continuum. Transcriptomic analyses following hormone treatments demonstrated upregulation of GhFBN family members, implicating their involvement in hormone-mediated regulatory networks governing fiber cell development. Collectively, this work presents a detailed molecular characterization of cotton GhFBNs and establishes a theoretical foundation for exploring their potential applications in cotton breeding programs aimed at improving fiber quality. Full article

Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an incomplete and often outdated understanding of how ready the workforce truly is, which can hinder organizational adaptability in rapidly evolving environments. This paper proposes a novel dynamic learner-state ecosystem—an AI-driven solution designed to bridge this gap. Our approach leverages specialized AI agents, orchestrated via the Model Context Protocol (MCP), to continuously track and evolve an individual’s multi-dimensional state (e.g., mastery, confidence, context, and decay). The seamless integration of in-workflow performance data will transform daily work activities into granular and actionable data points through AI-powered dynamic xAPI generation into Learning Record Stores (LRSs). This system enables continuous, authentic performance-based assessment, precise skill gap identification, and highly personalized interventions. The significance of this ecosystem lies in its ability to provide a real-time understanding of everyone’s capabilities, enabling more accurate workforce planning for the future and cultivating a workforce that is continuously learning and adapting. It ultimately helps to transform learning from a disconnected, occasional event into an integrated and responsive part of everyday work. Full article

Accurate evaluation of the operational status of smart meters, as the critical interface between the power grid and its users, is essential for ensuring fairness in power transactions. This highlights the importance of implementing rotation management practices based on meter status. However, the traditional expiration-based rotation method has become inadequate due to the extended service life of modern smart meters, necessitating a shift toward status-driven targeted management. Existing multifactor comprehensive assessment methods often face challenges in balancing accuracy and interpretability. To address these limitations, this study proposes a novel method for analyzing the status of smart meter groups using an interpretable random forest model. The approach incorporates an expert-knowledge-guided grouping assessment strategy, develops a multi-source heterogeneous feature set with strong correlations to meter status, and enhances the random forest model with the SHAP (SHapley Additive exPlanations) interpretability framework. Compared to conventional methods, the proposed approach demonstrates superior efficiency and reliability in predicting the failure rates of smart meter groups within distribution network areas, offering robust support for the maintenance and management of smart meters. Full article

Strengthening climate resilience constitutes a foundational approach through which cities adapt to climate change and mitigate associated environmental risks. However, research on the influence of economic policy environments on climate resilience remains limited. Guided by institutional theory and dynamic capability theory, this study employs a panel dataset comprising 272 Chinese cities at the prefecture level and above, covering the period from 2009 to 2023. It constructs a composite index framework for evaluating the green business environment (GBE) and urban climate resilience (UCR) using the entropy weight method. Employing a two-way fixed-effect regression model, it examined the impact of GBE optimization on UCR empirically and also explored the underlying mechanisms. The results show that improvements in the GBE significantly enhance UCR, with green innovation (GI) in technology functioning as an intermediary mechanism within this relationship. Moreover, climate policy uncertainty (CPU) exerts a moderating effect along this transmission pathway: on the one hand, it amplifies the beneficial effect of the GBE on GI; on the other hand, it hampers the transformation of GI into improved GBEs. The former effect dominates, indicating that optimizing the GBE becomes particularly critical for enhancing UCR under high CPU. To eliminate potential endogenous issues, this paper adopts a two-stage regression model based on the instrumental variable method (2SLS). The above conclusion still holds after undergoing a series of robustness tests. This study reveals the mechanism by which a GBE enhances its growth through GI. By incorporating CPU as a heterogeneous factor, the findings suggest that governments should balance policy incentives with environmental regulations in climate resilience governance. Furthermore, maintaining awareness of the risks stemming from climate policy volatility is of critical importance. By providing a stable and supportive institutional environment, governments can foster steady progress in green innovation and comprehensively improve urban adaptive capacity to climate change. Full article

Widespread species may exhibit considerable genetic variation among populations due to their extensive distribution ranges, and may even give rise to new species in remote areas. Integrative species delimitation via multiple types can provide a robust framework for accurate species identification and rapid discovery of cryptic diversity. The subgenus Tliponius (Hemiptera: Coreidae: Homoeocerus) has several species and three broadly distributed species across China. In this study, we selected as many geographical sample sites of widely distributed species as possible and conducted species identification based on integrated taxonomy of morphological, mitochondrial and SNP data for 28 individuals within Tliponius. Our results revealed a cryptic lineage previously subsumed under the polytypic H. unipunctatus in Yunnan Province and described as Homoeocerus (Tliponius) dianensis Liang, Li & Bu sp. nov. The presence of seven distinct species within Tliponius was supported by species delimitation and divided into two clades: (H. dilatatus + (H. marginellus + (H. unipunctatus + H. dianensis sp. nov.))) and (H. yunnanensis + (H. laevilineus + H. marginiventris). Based on our findings, extensive sampling of widespread species is highly important for the accuracy of species delimitation and the discovery of cryptic species. Full article

The role of rhizosphere bacteria in facilitating plant invasion is increasingly acknowledged, yet the influence of specific microbial functional traits remains insufficiently understood. This study addresses this gap by isolating two bacterial strains, Bacillus sp. ScRB44 and Pseudomonas sp. ScRB22, from the rhizosphere of the invasive weed Solidago canadensis. We assessed their nitrogen utilization capacity and indoleacetic acid (IAA) production capabilities to evaluate their ecological functions. Our three-stage experimental design encompassed strain promotion, nutrient stress, and competition phases. Bacillus sp. ScRB44 demonstrated robust IAA production and significantly improved the nitrogen utilization efficiency, significantly enhancing S. canadensis growth, especially under nutrient-poor conditions, and promoting a shift in biomass allocation toward the roots, thereby conferring a competitive advantage over native species. Conversely, Pseudomonas sp. ScRB22 exhibited limited functional activity and a negligible impact on plant performance. These findings underscore that the ecological impact of rhizosphere bacteria on invasive weeds is closely linked to their specific growth-promoting functions. By enhancing stress adaptation and optimizing resource allocation, certain microorganisms may facilitate the establishment of invasive weeds in adverse environments. This study highlights the significance of microbial functional traits in invasion ecology and suggests novel approaches for microbiome-based invasive weed management, with potential applications in agricultural soil health improvement and ecological restoration. Full article

Fructose-1,6-bisphosphate aldolase (FBA; EC 4.1.2.13) is a key enzyme in glycolysis and the Calvin cycle, which plays crucial roles in carbon allocation and plant growth. The FBA family genes (FBA s) have been identified in several plants. However, their presence and roles in sweet potato remain unexplored. In this study, a total of 20 FBAs were identified in sweet potato and its wild wild diploidrelatives, including seven in sweet potato (Ipomoea batatas, 2n = 6x = 90), seven in I. trifida (2n = 2x = 30), and six in I. triloba (2n = 2x = 30). Their protein physicochemical properties, chromosomal localization, phylogenetic relationship, gene structure, promoter cis-elements, and expression patterns were systematically analyzed. The conserved genes and protein structures suggest a high degree of functional conservation among FBA genes. IbFBAs may participate in storage root development and starch biosynthesis, especially IbFBA1 and IbFBA6, which warrant further investigation as candidate genes. Additionally, the FBAs could respond to drought and salt stress. They are also implicated in hormone crosstalk, particularly with ABA and GA. This work provides valuable insights into the structure and function of FBAs and identifies candidate genes for improving yield, starch content, and abiotic stress tolerance in sweet potatoes. Full article

In this paper, we propose an optoelectronic feed-forward millimeter-wave generator based on the Mach–Zehnder interferometer (MZI) structure. The phase noise of the local oscillation (LO) input is extracted by loop design and used for phase noise suppression of the output, thereby optimizing the phase noise performance of the generator output. The scheme achieves separation of the phase noise by using an MZI structure and a mixing-frequency oscillator to realize the differential and integration process of the phase noise from the LO input source, respectively. Then, it is combined with a feed-forward operation to skillfully realize phase noise rejection of the resulting high-frequency output. The proposed scheme has been demonstrated to facilitate millimeter-wave generation at 40 GHz and 50 GHz. The measured phase noise is as low as −120 dBc/Hz at a 10 kHz offset, and the experimental setup achieves phase noise suppression of up to 36 dB at this frequency offset. Through systematic theoretical analysis and experimental verification, the excellent capabilities of the proposed scheme in high-frequency signal generation and phase noise suppression are fully demonstrated, which provides a new technological path for high-performance millimeter-wave generation, avoiding the deterioration of the phase noise introduced using high-frequency optoelectronic devices other than photodetectors (PDs) to process the signals. Full article

Porcine circovirus type 3 (PCV3) has been detected in wild boars across many countries in Europe, Asia, and South America. However, data regarding the presence of porcine circoviruses in wild boars and ticks remain limited. In this study, we investigated the presence and genetic characteristics of PCV3 in wild boars and parasitizing ticks in Jiangsu, China. Samples, including whole blood, serum, tissues, feces, and oral fluids from wild boars, as well as ticks collected from 47 wild boars, were obtained between March 2021 and November 2022. PCR results indicated that 34.0% (16/47) of wild boars tested positive for PCV3, while ELISA detected 41.9% (18/43) seropositivity. RT-qPCR results showed that 7.2% (6/83) were positive for PCV3 in 83 analyzed tick samples, with all positive samples identified as Amblyomma testudinarium. The PCV3 genome obtained from wild boars was classified as PCV3a and was closely related to the strain identified in domestic pigs in Nanjing, Jiangsu Province. Collectively, these findings confirm the presence of PCV3 in wild boars in Jiangsu and suggest a possible link of PCV3 infection among domestic pigs, wild boars, and ticks, providing new insights into the transmission risk of PCV3 at wildlife–livestock–human interfaces and highlighting the genetic homology between strains from wild and domestic pigs. Full article

The goal of this study was to build an understanding of the quality of Idesia polycarpa fruit Maxim from different ecotypes and to identify the best cultivars, with a view to providing a reference and theoretical basis for the selection and cultivation of I. polycarpa. In this study, we systematically evaluated the fruit quality characteristics of five seed sources, namely SH, SG1, GG, HX, and SG2, at four developmental stages, M1-M4, through a principal component analysis, a correlation analysis, and a significance test. Comparisons between the ecotype yielded that GG was significantly better than the other ecotype in oil content (28.7%) and fresh weight per cluster (155.56 g), while HX exhibited higher SOD content (278.18 U/g) and soluble protein content (27.50 mg·g⁻¹), suggesting a higher level of stress tolerance. The results of the correlation analysis showed that POD was significantly negatively correlated with oil content (r = −0.633) and SOD (r = −0.617) activities, indicating that the antioxidant enzyme system may affect oil accumulation. The results of the principal component analysis showed that the cumulative contribution of the first four principal components reached 89.72%, of which principal component 1 mainly reflected yield-related traits, and principal component 2 was significantly correlated with oil content and soluble protein. Through the evaluation and screening of the five ecotypes, we determined that GG can be utilized as a good single plant in the selection and improvement of new cultivars; our findings can provide theoretical support for the selection of good cultivars of I. polycarpa seed in the central region of Henan. Full article

To enable accurate evaluation of satellite laser communication terminals under solar outage interference, this paper presents the design and implementation of a solar radiation simulation system targeting the 1540–1560 nm communication band. The system reconstructs co-propagating interference conditions through standardized and continuously tunable output, based on high irradiance and spectral uniformity. A compound beam homogenization structure—combining a multimode fiber and an apodizator—achieves 85.8% far-field uniformity over a 200 mm aperture. A power–spectrum co-optimization strategy is introduced for filter design, achieving a spectral matching degree of 78%. The system supports a tunable output from 2.5 to 130 mW with a 50× dynamic range and maintains power control accuracy within ±0.9%. To suppress internal background interference, a BRDF-based optical scattering model is established to trace primary and secondary stray light paths. Simulation results show that by maintaining the surface roughness of key mirrors below 2 nm and incorporating a U-shaped reflective light trap, stray light levels can be reduced to 5.13 × 10⁻¹² W, ensuring stable detection of a 10⁻¹⁰ W signal at a 10:1 signal-to-background ratio. Experimental validation confirms that the system can faithfully reproduce solar outage conditions within a ±3° field of view, achieving consistent performance in spectrum shaping, irradiance uniformity, and background suppression. The proposed platform provides a standardized and practical testbed for ground-based anti-interference assessment of optical communication terminals. Full article

Coal miners’ unsafe behavior is the primary reason for accidents. This research aims to examine the effect of male coal miners’ shared work crew identity on their safety behavior. A 2-2-1 multilevel mediation model is established based on social identity theory and safety climate theory. To validate the model, a paper-and-pencil survey with male coal miners was carried out in Henan Province, China. A total of 212 valid responses from male coal miners nested in 53 work crews were secured, and Mplus was used to analyze the data. Results show that work crew safety climate fully mediates the effect of male coal miners’ shared work crew identity on their safety behavior. In theory, the findings support that social identity brings a safety climate. In practice, the findings highlight that making safety part of work crew norms improves male coal miners’ safety behavior. Limitations and future research are also discussed. Full article

PM_2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm) pollution is one of the most common problems triggered by the acceleration of urbanization. The coordinated development of cities and the environment has been a topic of significant interest in recent years. Based on the spatiotemporal relationship between the evolution of urbanization levels and PM_2.5 concentrations, and starting from multiple factors characterizing urbanization, this study constructs a coupling coordination degree model between PM_2.5 and urbanization levels to explore the interaction and degree of coordination between urbanization and PM_2.5 in Guangdong Province from 2000 to 2021. The research reveals that the conflict between the urbanization process and PM_2.5 pollution in various cities of Guangdong Province is gradually easing. The year 2011 was a turning point as the PM_2.5 pollution levels in cities that were in an uncoordinated phase began to improve. The coupling coordination degree between urbanization and PM_2.5 pollution in Guangdong Province exhibits significant spatial heterogeneity. The coupling coordination degree in most coastal cities is higher than that in inland cities. Cities in economically underdeveloped regions also face relatively lower pressure from pollution emissions. These regions are characterized by lagging urbanization, and their coupling coordination degree is slowly increasing as urbanization progresses. In economically developed regions, the coupling coordination degree between urbanization levels and PM_2.5 pollution has reached a basic level of coordination, although the specific types vary. Full article