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关键词： 技工院校   数控专业   CAD   赛训一体   课程模式构建  

摘要： 构建了“赛训一体”的CAD课程,对提升学生专业技能与职业素养的意义重大。本文分析了技工院校数控专业CAD“赛训一体”课程模式构建的必要性,探讨了当前存在的问题,并提出了针对性的构建策略,以期推动技工院校数控专业教学改革,提高人才培养质量。

摘要： Risk stratification in patients with known coronary artery disease (CAD) remains a clinical challenge, especially in asymptomatic individuals. While stress cardiac magnetic resonance imaging (MRI) has strong prognostic value, current models do not fully exploit the richness of available clinical and imaging data. Machine learning (ML) offers an opportunity to optimize prediction by capturing complex patterns in high-dimensional datasets.

关键词： 明代中后期   山东   纺织品   商品经济   生产结构   流通路径  

摘要： 文章旨在探究明代中后期山东纺织品的生产、流通及其在北方商品经济中的定位。研究基于地方志等史料,区分丝织与棉织两类产品,系统梳理了其地域分布、工艺特点与市场流向。研究发现,明中叶后山东纺织业逐步复苏,丝织品如临清帕幔、历城黄绢等虽参与流通但地位弱于江南;棉织业则随赋役改革与市场需求而兴起,形成了如历城平机布、濮州坚密布等具有区域声誉的商品,并逐步打破“南布北运”格局。研究表明,山东纺织业的复苏是官府推动与民间适应共同作用的结果,临清作为生产与流通枢纽,促进了区域性纺织市场的形成,反映了明代北方商品经济的内在活力与发展路径。

关键词： 测试   生物基纺织品   苯并噻唑类物质   超声萃取   液相色谱-串联质谱  

摘要： 建立了一种同时测定生物基纺织品中5种苯并噻唑类物质的高效液相色谱-串联质谱分析方法。取1.0 g生物基纺织样品,加入20 mL甲醇,40℃超声萃取30 min,萃取液经0.22μm滤膜过滤后,采用Athena C18(2.1 mm×150 mm,1.8μm)色谱柱分离,以不同体积比的乙酸溶液-乙腈混合液为流动相进行梯度洗脱,采用电喷雾离子源,在正离子模式下进行多反应监测(MRM)模式质谱分析,外标法定量。结果表明,5种苯并噻唑类物质在10~250μg/L范围内与定量离子的响应强度呈线性关系,检出限(S/N=10)为0.2 mg/kg。按照标准加入法进行回收试验,回收率为86.4%~106.2%,测定值的相对标准偏差(n=6)为4.1%~8.2%。该方法用于8份样品的分析,在一份生物基复合面料中检出2-氨基苯并噻唑,检出量为2.6 mg/kg。

关键词： CAD   农业机械   参数化建模   结构优化   仿真  

摘要： 随着农业现代化水平的不断提高,农业机械的结构复杂性和功能集成度显著提升,传统设计方法已难以满足快速迭代与高可靠性的研发需求。计算机辅助设计(CAD)技术凭借其精确建模、参数化设计、仿真分析与协同制造等优势,广泛应用于农业机械的产品开发全过程。文章系统分析了农业机械设计中的关键难点,阐述了CAD技术体系及其在农业机械结构设计中的具体实践,如拖拉机传动系统建模、收割机关键部件曲面建模、播种机排种机构运动仿真等,以期为智能农机与数字农业的深入发展提供参考。

关键词： 干燥速率   蒸发速率   Origin软件   曲线拟合   切线斜率  

摘要： 利用最小二乘法拟合线性方程的斜率求干燥速率,数据点的选取主要依靠检测人员的主观判断,不同的检测人员选取的数据点不一样,检测结果也不一样。利用Origin软件拟合时间-蒸发量函数曲线,通过函数拟合相关系数R值判断函数曲线与水分蒸发趋势的符合程度,以拟合曲线切线的最大斜率为干燥速率,消除了因不同试验人员选取数据点不同而造成的结果差异。通过比对仪器方法、Origin软件测试方法和标准测试方法的检测结果,Origin软件测试方法能够快速绘制反映水分蒸发趋势的时间-蒸发量曲线和准确计算干燥速率,结果的准确性高、重现性好。

关键词： coronary artery bypass grafting   percutaneous coronary intervention   coronary artery intervention   COVID-19   arterial grafting   cardiac surgery   ATIH   Agence Technique de l’Information sur l’Hospitalisation   CABG   coronary artery bypass grafting   CAD   coronary artery disease   CAGR   compound annual growth rate   LOS   length of stay   MI   myocardial infarction   PCI   percutaneous coronary intervention  

摘要： This study aimed to analyze temporal trends in coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) in France from 2017 to 2022.

关键词： C. elegans   Dendrite   Glia   Adherens junctions   Morphogenesis  

摘要： Adherens junctions (AJs) stabilize cell contacts by coupling adhesion molecules to the cytoskeleton. AJ proteins have been studied extensively in epithelia, but less is known about their roles in other cell types. Here, we describe a role for AJ proteins in C. elegans glia. Previously, we showed that C. elegans glia use the adhesion molecule SAX-7/L1CAM to anchor the dendritic endings of URX and BAG sensory neurons at the nose during embryo elongation, allowing their dendrites to stretch to their full lengths. Using cell-specific rescue and depletion experiments, we show that the AJ proteins MAGI-1 and HMR-1/Cadherin also act in glia to promote URX and BAG dendrite extension. MAGI-1 is a multi-PDZ domain protein that can simultaneously interact with PDZ-binding (PB) motifs in SAX-7 and HMP-2/beta-catenin thus potentially bridging SAX-7 to the cadherincatenin complex. The SAX-7 PB motif also binds AFD-1/afadin. Double-mutant analyses indicate that many of these players act redundantly, consistent with parallel interactions among them. As MAGI-1, HMR-1 and AFD-1 are all found in epithelial AJs, we propose that an AJ-like complex in glia promotes dendrite extension.

关键词： Breast Cancer   Mammography   AI CAD  

摘要： Purpose: To evaluate the characteristics of breast cancers detected and missed by artificial intelligence-based computer-assisted diagnosis (AI-CAD) during screening mammography. Materials and Methods: This retrospective secondary analysis was conducted using data from the Artificial Intelligence for Breast Cancer Screening in Mammography trial (***: NCT05024591), a prospective, multicenter cohort study performed from 2021 to 2022. AI-CAD results were categorized into nine subgroups based on abnormality scores (in 10% increments). Positive predictive values of recall (PPV1s) were calculated for each subgroup and by breast density, and AI-CAD scores were compared with mammographic and pathologic features. Results: A total of 24 543 women (mean age +/- SD, 59.8 years +/- 11.2), including two with bilateral cancer, were included;148 cancers were confirmed by pathologic evaluation after 1 year of follow-up. AI-CAD results were negative in 23 010 cases (93.8%) and positive in 1535 (6.2%). The overall PPV1 was 8.7% (133 of 1535), with a sensitivity of 89.9% and specificity of 94.3%;PPV1 increased with higher abnormality scores but remained below 3% in groups 1 and 3 for dense breasts. AI-CAD detected 3.4% (five of 148) of cancers missed by radiologists but missed 8.1% (12 of 148) that were detected at radiologist recall. Abnormality scores were lower in patients presenting with mammographic asymmetry (P = .001) and luminal A subtype (P = .032). Conclusion: AI-CAD shows potential to improve breast cancer detection in screening programs and to support radiologists in mammogram interpretation. Understanding the imaging and pathologic features of cancers detected or missed by AI-CAD may enhance its effective clinical application. Clinical trial registration no. NCT05024591

关键词： artificial intelligence   CAD4TB   household contacts   tuberculosis   Xpert MTB/RIF  

摘要： Background Tuberculosis remains the leading cause of death by a single infectious agent globally, with Ethiopia among the highest tuberculosis- and human immunodeficiency virus/tuberculosis-burden countries. Diagnostic gaps-particularly among household contacts (HHCs) unable to expectorate-hinder early case detection. Computer-aided detection software for chest radiography and nonrespiratory molecular assays, such as stool-based Xpert MTB/RIF testing, represent promising strategies for scalable *** We conducted a prospective diagnostic accuracy study at St Luke Catholic Hospital, Oromia, Ethiopia, enrolling 478 participants (152 tuberculosis index patients and 326 HHCs). All HHCs >= 4 years underwent digital chest radiographic screening, with or without CAD4TB (Delft Imaging) software assistance, and provided stool and sputum samples for Xpert MTB/RIF testing. The accuracy of CAD4TB and stool Xpert testing was evaluated against sputum Xpert testing as the *** CAD4TB showed strong diagnostic performance, with a sensitivity of 0.77 (95% confidence interval, .70-.83) and specificity of 0.93 (.90-.96). Performance was higher among adults (sensitivity and specificity, 0.79 and 0.94) than in children (0.64 and 0.92). Stool and sputum Xpert testing demonstrated high concordance (Cohen's kappa = 0.76), with a sensitivity of 0.77 (95% confidence interval, .70-.84) and specificity of 0.97 (.93-.99). During the study, 10.6% of HHCs (34 of 321) were newly diagnosed microbiologically with *** The combined use of CAD4TB and stool Xpert testing significantly improves tuberculosis detection, particularly among HHCs in high-burden, low-resource settings. This strategy is especially valuable in children and adults unable to produce sputum and where radiological expertise is limited.