课程文献中心 更多>>

关键词： Agave tequilana   agaves   C3 and CAM plants   camphene   drought   ethyl isovalerate   microbial volatile organic compounds   nonanal   Solanum lycopersicum   tomato   yield  

摘要： Plants interact with their associated microbiota through diverse chemical cues, including microbial volatile organic compounds (mVOCs) that act as airborne signals that modulate plant physiology and stress resilience. This is particularly relevant under drought, a major constraint on global plant productivity. Although short-term physiological responses to microbial volatiles have been widely documented, their longer-term effects on functional plant traits and performance remain poorly understood, especially in species with contrasting photosynthetic strategies and water-use characteristics. We investigated the effects of selected mVOCs-camphene (CAMP ethyl isovalerate (EV their combination (EV + CAMP and nonanal-in Agave tequilana and Solanum lycopersicum cv. Micro-Tom (tomato representing CAM and C3 species, respectively. Agave and tomato seedlings were exposed once to volatiles and then grown for eight and four and a half months, respectively, under defined water-limiting regimes. In Agave, we evaluated four groups of traits: leaf and biomass, roots, pigments and sugars and proline;whereas in tomato, we assessed growth and yield. EV followed by CAMP enhanced A. tequilana performance under moderate and severe water limitation, promoting leaf and root development, increased relative water content, as well as higher carbohydrates and chlorophyll levels. In tomato, volatile exposure increased fruit yield from 0.10 to 2.65-fold under both well-watered and moderate drought, with EV exerting the strongest effect under moderate drought. Nonanal yielded net negative effects on agaves, while the mix EV + CAMP showed positive effects on tomato, but poor results on A. tequilana. Our results demonstrate that EV and CAMP, alone or in combination, act as biologically active airborne signals that modulate plant physiological plasticity under water limitation. Remarkably, a single volatile exposure produced lasting effects on vegetative and reproductive development, highlighting

摘要： 本文对加强高校党组织建设的重要性和现存不足进行分析，提出运用PDCA循环理论，通过计划阶段的目标体系构建、执行阶段的“4+4”路径创新、检查阶段的评价指标体系、处理阶段的经验转化和整改提升四个维度，探索构建高校党组织建设的科学化路径，为推动“一融双高”目标落地提供理论支撑与参考。党的二十大做出了“增强党组织政治功能和组织功能”的重大部署，《中国共产党普通高等学校基层组织工作条例》也明确提出，“增强党组织功能是高校落实新时代党的建设总要求、提升高校党建工作水平的现实需要”。高校是培养社会主义建设者和接班人的主阵地，加强党组织建设尤为重要，是确保高校落实立德树人根本任务的基础工作，也是实现“一融双高”即“党建与业务深度融合、以高质量党建引领事业高质量发展”的重要途径。

关键词： Remote sensing images   semantic segmentation   im age reconstruction   pixel relationship constraint   intersection optimization strategy   Segment Anything Model  

摘要： Remote sensing image semantic segmentation plays a pivotal role in converting complex image data into quantifiable geographic spatial information, underpinning applications such as disaster assessment, urban planning, and agricultural resource investigation. Fully supervised semantic segmentation methods rely heavily on labour-intensive pixel-level annotations, prompting a shift towards weakly supervised semantic segmentation (WSSS) that utilizes image-level annotations. However, remote sensing images are characterized by dense, intricate targets and the absence of distinct backgrounds, leading to challenges, such as sparse activation of local regions, incomplete localization in class activation maps (CAMs and noisy, rough boundaries in pseudo-labels generated from image-level supervision. To address these issues, we propose a deep learning method with pixel relationship constraints for WSSS in remote sensing images. Specifically, we design an image reconstruction (IR) loss function to provide pixel-level supervision, enhancing the completeness of CAMs;a pixel relationship constraint (PRC) module to strengthen the global correlation of target regions and improve detailed information extraction;and an intersection optimization strategy (IOS) based on the Segment Anything Model (SAM) to refine pseudo-labels and segmentation results by mitigating noise. Here, we show that our method achieves mean Intersection over Union (mIoU) values of 63.85%, 71.20%, and 40.96% on the Vaihingen, Potsdam, and iSAID datasets, respectively, reaching 89.25%, 89.02%, and 65.66% of the performance of fully supervised methods. This work advances WSSS for remote sensing images by addressing key limitations of CAM-based pseudo-labels generation, offering a cost-effective alternative to fully supervised approaches and facilitating broader applications in geographic information science and earth observation. The code is available at .

关键词： Power equipment   image   feature extraction   Grad-CAM heatmap   CNN  

摘要： To accurately extract image features of power equipment, improve the diagnostic efficiency of power equipment faults, and ensure the stable operation of the power system, this study optimizes the convolutional neural network algorithm using gradient weighted class activation mapping heatmap. Based on the optimized algorithm, a method for extracting image features of power equipment has been developed. The experiment analyzed the feature extraction performance of the optimization algorithm on the MS COCO, ImageNet, LFW, and ORB datasets. The results demonstrated that the algorithm had an accuracy rate of over 96% in extracting different features from images in different datasets, and its feature extraction accuracy rate was also over 94% under the influence of interference. In the analysis of the actual effectiveness of optimization methods, the extraction error rate of features from images of different power equipment was less than 3%. Therefore, the proposed method for extracting image features of power equipment can accurately extract features from different power equipment images, thereby enabling accurate diagnosis of the operating status of power equipment and improving the stability of power system operation.

关键词： Barley   Cinnamyl Alcohol Dehydrogenase (CAD)   Genome editing   Lignin   Orange lemma  

摘要： Barley (Hordeum vulgareL.) is one of the world’s major cereal crops and is widely used for feed, brewing, and food. Reducing lignin content in barley grain and straw is beneficial for improving forage digestibility and enhancing the efficiency of bioethanol production. The orange lemma mutation—characterized by orange pigmentation of husks and nodes—has long been associated with altered lignin metabolism; however, its genetic basis has remained unclear. We show thatCinnamyl Alcohol Dehydrogenase(CAD) is the causal gene underlying the orange lemma phenotype in barley. Genetic mapping using a ‘Haruna Nijo’ × ‘L053’ F₂ population and the Barley 50 K SNP array defined a candidate region on chromosome 6H containing theCADgene. Sequence analysis revealed that all orange lemma mutants, including both naturally occurring and EMS-induced lines, carried nucleotide changes in theCADgene, resulting in amino acid substitutions or premature stop codons. Furthermore, CRISPR/Cas9-mediated knockout ofCADin the cultivar ‘Golden Promise’ reproduced the orange lemma phenotype, providing functional validation. The knockout plants also showed significantly lower lignin content than wild-type plants. These findings resolve a long-standing question regarding the genetic basis of the orange lemma trait and demonstrate that disruption ofCADalters lignin accumulation in barley. This work provides a valuable genetic resource for breeding barley cultivars with improved biomass utilization for feed and bioenergy applications.

关键词： Stage Cam Box   image-based   edge-computing   hydrology   water level  

摘要： Monitoring headwater streams poses a persistent challenge in hydrology due to their remote locations and highly variable conditions. Traditional methods often fall short in such environments. To overcome these limitations, we developed the Stage Cam Box (SCB a compact, autonomous sensing unit designed for continuous water level monitoring using image-based techniques. The SCB operates by analysing the visible portion of a high-contrast target installed in the streambed, allowing for non-contact, real-time water level estimation. This technical note presents a detailed description of the software as well as preliminary experimental results in adverse sunlight conditions. This work supports the development of scalable, low-cost sensor networks for high-resolution, autonomous hydrological monitoring in previously inaccessible headwater regions.

关键词： CNC machining   Toolpath strategy   Canned cycle programming   Parametric G-code   Pocket milling   CAM  

摘要： This paper introduces an innovative modular CNC toolpath strategy for the milling of circular and regular polygonal pockets. The method integrates two adjustable motion components, a three-dimensional helical descent and a two-dimensional spiral path, based on parametric interpolation algorithms with variable radius, pitch, and step-over. Cutting conditions, including spindle speed and feed rate, are independently configurable for each stage. In the case of circular pockets, these motions are combined into a continuous sequence that achieves both roughing and finishing. Although circular pocket machining has long been supported by conventional canned cycles and extensively studied in the literature, opportunities remain for alternative strategies that expand user choice, improve adaptability, and provide controller-level flexibility. For polygonal pockets, the helical-spiral motions are used to clear the interior volume up to a safe boundary, followed by a separate contouring phase to accurately define the final geometry. The complete strategy is implemented as a custom G-code routine suitable for integration into CNC controllers as a dedicated canned cycle, reducing dependence on external CAM software. The method is exportable as a G01-only program, enabling execution on CNC systems without canned cycle or macro capabilities. MATLAB simulations and CNC-based tests demonstrate the geometric consistency and adaptability of the toolpath generation process across different pocket configurations. A comparative cycle time analysis against conventional canned cycles and CAM-generated toolpaths highlighted the strategy's efficiency, showing that it can stand as a competitive alternative. Additionally, a physical machining test on a CNC milling machine confirmed the method's practical feasibility.

关键词： Three-body wear   Microhardness   Chewing simulator   Surface roughness, CAD/CAM  

摘要： Background Computer aided designed/ computer aided manufactured (CAD/CAM) materials offer diverse options for prosthetic rehabilitations, yet correlation between materials' surface properties and aging through chewing simulation needs characterization. The aim of this study is to measure and evaluate the effect of three body wear on three CAD/CAM materials (poly methylmethacrylate (PMMA composite resin and polyether ether ketone (PEEK regarding their microhardness and surface roughness. Methods Seventy-two disc-shaped specimens (20 & times;6 mm) were fabricated (n = 24/ group) from PMMA (Yamahachi PMMA Disk Nano-ceramic Composite (Grandio Blocs, VOCO and PEEK (BioHPP, Bredent). Specimens were subjected to 120,000 chewing cycles in a chewing simulator using a 3-body wear protocol with a pumice slurry. Wear volume (mm(3 was measured digitally. Surface roughness (& micro;m) and Vickers hardness (VHN) were evaluated twice: at baseline and within the wear facets post-simulation. Data were analyzed using Two-way and One-way ANOVA (P-value < 0.05 and Pearson correlation was used to measure the relationship between properties. Results One-way ANOVA revealed a significant difference between material types (P = 0.000* with composite exhibiting the lowest mean volume loss (0.08 mm(3 significantly outperforming PEEK (0.23mm(3 and PMMA (0.55 mm(3)). For surface roughness, a significant interaction was observed between material type and wear simulation (P = 0.000* while there was no significant interaction between them on surface hardness (P = 0.89). Composite significantly outperformed PEEK and PMMA regarding all tested properties. Conclusion The 3-body wear simulation induced significantly different volumetric loss across all groups, with the magnitude of loss largely dependent on the material's specific composition and baseline hardness. In addition, the surface roughness and microhardness of three investigated materials were considerably impacted by three-body wear. PMMA have

关键词： Computer aided design  

摘要： Articulation modeling aims to infer movable parts and their motion parameters for a 3D object, enabling interactive animation, simulation, and shape editing. In this paper, we present Sketch2Arti, the first sketch-based articulation modeling system for CAD objects. Our key observation is that designers naturally communicate articulation intent through lightweight sketches (e.g., arrows and strokes) that indicate how parts should move, yet translating such sketches into articulated 3D models remains largely manual. Sketch2Arti bridges this gap by enabling users to specify articulation through simple 2D sketches drawn from a chosen viewpoint. Given a CAD model and user sketches, our approach automatically discovers the corresponding movable parts and predicts their motion parameters, allowing iterative modeling of multiple articulations on complex objects with fine-grained control. Importantly, Sketch2Arti is trained in a category-agnostic manner without requiring object category information, leading to strong generalization to diverse objects beyond existing articulation datasets. Moreover, for shell models lacking interior structures, Sketch2Arti supports controllable internal completion guided by user sketches, generating plausible internal components consistent with the existing geometry and predicted motion constraints. Comprehensive experiments and user evaluations demonstrate the effectiveness, controllability, and generalization of Sketch2Arti. © 2026 Copyright held by the owner/author(s).

关键词： 纺织品出口   TBT通报   贸易伙伴   通报特征   标准  

摘要： 为应对技术性贸易壁垒（TBT）对中国纺织品出口的制约，以2015—2025年中国纺织品主要贸易伙伴TBT通报为研究对象，梳理贸易伙伴分布及通报特征，分析通报变化趋势与出口影响。研究发现，中国纺织品主要贸易伙伴呈多元化格局，TBT通报覆盖纺织全产业链，通报成员可划分为4个聚类组别，通报整体呈现数量波动上升、标准和法规严格的趋势。TBT措施对中国纺织品出口具有双重影响：一方面推动产业转型升级，另一方面也增加了出口成本与市场准入难度。在此基础上，提出了政府、行业与企业协同发力的应对策略，可为纺织品企业规避风险、推动产业高质量发展提供参考。