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关键词： Crack initiation   Fatigue failure evolution   Hydraulic motor   Variable-curvature cam ring  

摘要： The variable-curvature cam ring serves as the critical component governing the service life of the hydraulic motor, which can achieve ultra-high torque and is widely used in heavy-load machinery. The fatigue failure of cam ring will lead to damage and shutdown of hydraulic motor, potentially leading to severe safety accidents. However, there is still a lack of a deep understanding about failure evolution behaviors and mechanisms of variable-curvature cam ring. For that, this study systematically investigates the multi-scale failure characteristics of the cam ring under heavy-load conditions at different time intervals. The detailed fatigue failure behaviors are revealed about morphology, microstructure, and nanoscale defects. The results reflect that the inner dead point of cam ring is the most obvious failure position due to its vast stress and poor surface morphology. Moreover, the cracks typically expand in an intergranular manner during fatigue failure process. Yet, the residual austenite serves as a turning point for the crack to transition from intergranular expansion to intragranular expansion. Furthermore, the interaction between dislocation behaviors and carbide formation becomes the key to the origin of cracks. Within a relatively short damage time, the rearranged dislocation contacts with the tips of carbides, resulting in the formation of highly refined micro-cracks. When the cumulative damage time is longer, the interwoven cracks formed by the networked dislocations surrounding the carbides completely divide the carbide interior, causing the fragmentation of the carbides. Moreover, reducing roughness in inner dead point and stress concentration areas, including residual austenite and carbides, is meaningful.

关键词： Cancer detection   Conditional diffusion model   Explainable artificial intelligence   Gradient-weighted class activation mapping   Spectral synthesis   Surface-Enhanced Raman Spectroscopy (SERS)  

摘要： Surface-enhanced Raman spectroscopy (SERS) has been widely applied for non-invasive, rapid measurement-based cancer detection; while its performance is highly dependent on sufficient training data for machine learning models. However, although large cancer cohorts are available in high-level research institutions, stringent privacy regulations and the sensitive nature of patient data limit cross-institutional sharing, constraining most SERS cancer detection studies to small sample sizes. This scarcity of training data results in model overfitting and insufficient generalization capability. To address these challenges, this study proposes CAM-Diffusion, a method that integrates Gradient-Weighted Class Activation Mapping (Grad-CAM) with conditional diffusion models to generate high-quality synthetic SERS spectra and provide interpretable localization of key features. The 1D-Grad-CAM module identifies discriminative Raman shift regions that contribute significantly to cancer classification through gradient-weighted mechanisms and constructs masks to guide the conditional diffusion process. CAM-Diffusion utilizes mask-guided cross-attention mechanisms to improve feature learning in key diagnostic regions through differential allocation of attention weights. Using a serum SERS dataset comprising four cancer types, two benign diseases, and healthy controls, five-fold cross-validation experiments under limited training data scenarios demonstrate that CAM-Diffusion achieved consistent performance improvements across eight classifiers, with accuracy gains ranging from 2.29% to 7.82%. In conclusion, CAM-Diffusion identifies key spectral regions, generates high-quality SERS spectral data, and substantially improves classifier performance through interpretability-guided synthesis.

关键词： 技术性贸易壁垒   纺织品召回   标准   儿童服装   召回风险  

摘要： 为揭示中国纺织品出口面临的技术性贸易壁垒（TBT）风险特征，以2015—2025年欧盟非食品类消费品快速预警系统（Safety Gate）与美国消费品安全委员会（CPSC）官网的召回数据为切入点，采用数据统计分析与标准对比分析方法，对召回主要风险因素及欧美与中国相关标准差异进行研究。结果表明：欧盟召回涉及中国纺织品的有603次，远超美国的169次，儿童服装为欧美市场的高风险品类；欧盟召回核心风险为绳带引发的受伤、勒毙类危害，美国则聚焦在烧伤、火灾类风险。中国标准与欧美标准在绳带分类、小部件测试、化学物质限值、防火测试方法等方面存在差异。文章从标准对标、产品设计、合规检测等方面提出建议，可为中国纺织企业突破技术性贸易壁垒提供参考。

关键词： 等几何分析   模态分析   嵌入域方法   NURBS   自由振动  

摘要： 传统有限元法求解三维结构模态问题时，常因几何复杂导致网格划分耗时且需进行几何简化，从而影响计算效率与精度。针对上述问题，提出无需网格划分、无需几何清理的模态问题嵌入域等几何分析方法。该方法直接利用CAD模型进行模态仿真，避免了传统有限元法中几何离散化带来的误差。推导了模态问题嵌入域等几何分析，建立了自由振动等几何分析算法，实现了结构振动问题的数值仿真。选取夹紧圆盘、带孔支座和转向架三类典型三维结构开展算例验证，对于固支圆盘，将计算结果与文献参考解进行对比，收敛结果良好。对于带孔支座与转向架构件，将数值计算结果与商业有限元软件的分析结果进行对比，前10阶固有频率误差均小于3%，表明所提方法具有良好的精度和适用性。研究结果为复杂三维结构的高精度模态分析提供了有效途径。

摘要： This paper proposes a novel stopper-limited quasi-zero-stiffness isolator featuring piecewise cam negative stiffness (QSI-SP). Comprehensive static and dynamic analyses of the suspension system are respectively conducted. The derived steady-state analytical solution by the multi-scale method under the harmonic excitation demonstrates close agreement with numerical simulation. Key factors influencing the system’s vibration isolation performance and the system stability are investigated and evaluated in detail. The results show that the optimal solution for the unilateral gap of the limiter is the single-side gap of the stopper is equal to half of the straight-line segment distance of the cam. Controlling the stopper’s damping parameter to exceed its critical damping ratio significantly improves vibration isolation performance. When the excitation is within the range of the critical excitation amplitude, its amplitude can be tuned via the damping ratio of the linear viscous damping, enabling superior performance under larger excitation without focusing on the influence of damping ratio for the linear viscous damping on the absolute displacement transmissibility. Meanwhile, compared with other vibration isolation systems, the QSI-SP system demonstrates superior operational stability and ride comfort.

关键词： 纺织品   缺陷检测   注意力机制   哈尔小波下采样(HWD)模块   边界聚合   深度学习   YOLOv11算法  

摘要： 针对织物缺陷检测任务中小目标缺陷占比较高，小目标检测精度较差，以及模型训练过程中特征信息丢失和边界定位模糊的问题，提出一种改进YOLOv11的纺织缺陷检测方法。将Monte Carlo attention（MCA）注意力模块整合到C3k2模块中，提升模型的小目标检测能力；并引入哈尔小波下采样（HWD）模块替换原始下采样模块，保留更多的特征信息；使用选择性边界聚合（SBA）模块优化颈部网络中的特征融合模块，通过边界特征和语义信息的有效融合，增强算法边界与细节信息的检测能力，提升检测准确度；辅助引入Shape-IoU损失函数，关注边界框自身的形状和尺寸等绝对信息，提升边界框回归收敛速度与定位精度。试验结果表明：相较于原始YOLOv11模型，在有效控制参数量和计算成本的情况下，改进模型的mAP@0.5达到49.5%，提升了4.3个百分点，边界框回归收敛轮次减少37.5%，验证了各改进模块的有效性。认为：该改进YOLOv11算法可有效解决复杂纺织场景下小目标缺陷检测精度低、边界定位模糊的行业痛点，具备良好的工程应用价值。

关键词： FAI syndrome   Squat   Hip joint   Biomechanics   Kinematics   Kinetics  

摘要： Femoroacetabular impingement syndrome (FAIS) is a movement-related disorder and causing hip and/or groin pain in young active adults. Movement patterns in individuals with FAIS may be modifiable through conservative management. Identifying biomechanical differences between cohorts with asymptomatic cam morphology (FAIM) and FAIS could reveal relevant treatment targets. This study compared lower limb kinematics and kinetics between FAIS, FAIM, and healthy controls during double- (DLS) and single-leg squats (SLS).

关键词： Glioblastoma   Cd38   Tumor microenvironment   Immunosuppression   L1CAM   STAT   NF-κB  

摘要： Glioblastoma (GBM), a lethal primary brain malignancy, is characterized by dysregulated recruitment of tumor-associated macrophages and myeloid-derived suppressor cells, which promotes tumor growth, and enables immune evasion. Given CD38’s role as a multifunctional glycoprotein in hematological malignancies where it regulates immune cell trafficking, we hypothesized that CD38 overexpression in GBM modulates the tumor immune microenvironment.

关键词： 1TM   single-pass transmembrane   7TM   7-pass transmembrane   7TMD   7-pass transmembrane domain   AA   amino acid   ADGR   Adhesion G protein–coupled receptor   AFM   atomic force microscopy   aGPCR   adhesion GPCR   AIS   adolescent idiopathic scoliosis   AT1   alveolar type 1   AT2   alveolar type 2   BRET   bioluminescence energy transfer   CAM   chorioallantoic membrane   CE   convergence and extension   CNS   central nervous system   COPD   chronic obstructive pulmonary disease   CRN   craniorachischisis   cryo-EM   cryogenic electron microscopy   CTF   C-terminal fragment   DHEA   dehydroepiandrosterone   ECL   extracellular loop   EGF   epidermal growth factor-like   EMT   epithelial-to-mesenchymal transition   EndMT   endothelial-to-mesenchymal transition   ENT   extracellular N-terminus   ER   endoplasmic reticulum   GAIN   GPCR autoproteolysis-inducing   GPCR   G protein–coupled receptor   GPS   GPCR proteolysis site   GRKs   G protein receptor kinases   GRN   generic residue numbering   hASMC   human airway smooth muscle cells   HIV   human immunodeficiency virus   HormR   hormone receptor motif   ICL   intracellular loop   ICT   intracellular C-terminus   IPF   idiopathic pulmonary fibrosis   KO   knockout   KRT1   keratin 1   LEC   lymphatic endothelial cells   MAGUK   membrane-associated guanylate kinase   MD   molecular dynamics   NK   natural killer   NRS   NTF release sensor   NTF   N-terminal fragment   PBM   PDZ-binding motif   PC1   polycystin-1   PCP   planar cell polarity   PKD1   polycystic kidney disease 1   PNS   peripheral nervous system   PR3   proteinase 3   PTK7   protein tyrosine kinase 7   SARS-CoV-2   severe acute respiratory syndrome coronavirus 2   SNP   single nucleotide polymorphism   TG2   transglutaminase-2   TIA   tethered/intramolecular agonist   TLR   Toll-like receptor   TMH   transmembrane helix   Treg   regulatory T cells  

摘要： Adhesion G protein–coupled receptors (aGPCRs) constitute a structurally and functionally distinct group within the superfamily of GPCRs. In 2015, the International Union of Pharmacology invited the Adhesion GPCR Consortium to publish a comprehensive review about aGPCRs and establish a unified nomenclature. Since then, substantial progress has been made in delineating the biological roles, molecular architecture, biochemical properties, expression profiles, ligand repertoire, and activation and signaling strategies of aGPCRs. Commensurate with these advances, their relevance to human pathophysiology has become increasingly apparent. In a coordinated effort, the Adhesion GPCR Consortium has reviewed recent progress in this field and provides a comprehensive assessment of the current understanding of aGPCR biology, including a focus on human and mammalian aGPCRs, their evolutionary origins, methodological approaches, and model systems for their investigation, as well as emerging approaches for their therapeutic targeting.

关键词： Algorithm-hardware co-design   Deep learning   Intra-row weeding   Lactuca sativa   Mechanical weed control   Precision agriculture  

摘要： Intra-row weed competition severely threatens lettuce (Lactuca sativa L.) cultivation by aggressively consuming soil moisture, nutrients, and light, thereby compromising biomass accumulation and marketable yield. While autonomous mechanical weeding offers a sustainable, chemical-free alternative, its widespread adoption is frequently constrained by prohibitive computational costs and hardware expenses associated with complex robotic systems. To bridge this gap, this study presents a cost-effective intelligent weeding method based on an algorithm-hardware co-design paradigm. On the mechanical front, a novel cam-push rod actuator is designed to replace expensive servo-driven manipulators. Based on a kinematic mathematical model, the cam profile was rigorously optimized to generate a deterministic lateral avoidance trajectory. This "physically encoded" intelligence ensures rapid, precise blade-retraction trajectory tailored to the specific rosette morphology of lettuce seedlings. Synergistically, the system integrates a bespokeightweightdetection model, You Only Look Once-GSBA-Tiny (YOLO-GSBA-Tiny). Through systematic structural pruning and the integration of attention mechanisms, the model reduces parameters and Giga Floating-Point Operations Per Second (GFLOPs) by 69.0 % and 55.6 %, respectively, compared to YOLO 8n, while maintaining a mean average precision of 97.8 %. Controlled environment trials validated the prototype's efficacy, achieving a weed removal rate of 93.86 % with a minimal crop damage rate of 2.08 %. Agronomically, this precision is critical for eliminating competition during the crop’s critical weed-free period, maximizing resource use efficiency, and safeguarding yield potential. Ultimately, this work demonstrates that empowering simple, mathematically optimized mechanical systems with efficient artificial intelligence (AI) provides an agronomically sound and economically scalable pathway for precision weed management.