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关键词： Aortic stenosis   Transcatheter aortic valve implantation   TAVI   Atherosclerosis   Coronary artery disease   Peripheral artery disease   Stroke   AS   Aortic stenosis   AVA   Aortic valve area   APG   Aortic valve pressure gradient   AV   Aortic velocity   ASCVD   Atherosclerotic vascular disease   BMI   Body mass index   CABG   Coronary artery bypass graft   CAD   Coronary artery disease   CI   Confidence interval   CVE   Cerebrovascular event   eGFR   Estimated glomerular filtration rate   HR   Hazard ratio   LVEF   Left ventricular ejection fraction   MI   Myocardial infarction   PAD   Peripheral artery disease   SAVR   Surgical aortic valve replacement   STS   Society of Thoracic Surgeons   TAVI   Transcatheter aortic valve implantation   TIA   Transient ischemic attack  

摘要： Degenerative aortic valve disease and atherosclerotic vascular disease (ASCVD) frequently coexist. ASCVD may impact pre-procedural planning and patient outcomes.

关键词： 虚拟仿真   纺织品检测   教学探索   实验教学  

摘要： 虚拟仿真技术在职业教育工科类教学中具有重要的应用价值。针对“纺织品检测技术”课程在传统实验教学中存在的设备资源不足、操作演示受限、安全风险较高以及教学覆盖不全面等问题,研究通过构建涵盖基础认知、设备拆装与仿真实训的“三阶贯通”教学模式(课前预习、课中强化、课后巩固),打破传统教学的时空局限。研究表明,该模式能够生动呈现仪器结构与工作原理,支持学生进行反复、自主的仿真操作训练,不仅显著提升了学生的学习积极性和对检测原理的理解深度,还增强了实际操作技能的训练效果与安全性,为工科类职业教育的实践教学改革提供了有益参考。

关键词： 土地利用   ResNet50   卷积块注意力模块(CBAM)   自动混合精度(AMP)   图像分类   卷积神经网络(CNN)  

摘要： 在土地利用类型图像分类领域,传统分类方法在特征提取准确性与分类精度方面存在局限性,难以满足实际应用需求。本文以ResNet50为核心架构,引入卷积块注意力模块(convolutional block attention module,CBAM),强化特征提取,并采用自动混合精度(automatic mixed precision,AMP)技术提高计算效率,构建了CAM-ResNet网络。实验结果显示,CAM-ResNet网络的总体精度达98.19%,较原网络高出10.16个百分点。消融实验进一步证明,CBAM注意力机制显著增强了模型的特征提取能力,AMP训练技术提高了模型的收敛速度,CAM-ResNet网络在土地利用类型遥感图像分类中具有一定的有效性和优越性。

关键词： coronary artery disease   mitral valve   mitral valve repair   robotic   CABG   coronary artery bypass grafting   CAD   coronary artery disease   DMR   degenerative mitral valve regurgitation   IABP   intra-aortic balloon pump   LOS   length of stay   MAC   mitral annular calcification   MV   mitral valve   PCI   percutaneous coronary intervention   RMVS   robotic mitral valve surgery   SMVS   sternotomy mitral valve surgery  

摘要： Some patients with degenerative mitral valve regurgitation have incidental coronary artery disease. When these patients are referred to our robotic cardiac surgery program, they are offered robotic mitral valve surgery combined with staged percutaneous coronary intervention performed during the same hospital admission. The objective of this study is to compare this new “hybrid” approach with the “conventional” operation consisting of sternotomy mitral valve surgery with coronary artery bypass grafting performed as a single procedure.

摘要： The use of computer-aided design and computer-aided manufacturing (CAD-CAM) in restorative dentistry requires instruction and training. Given the increasing product diversity and limited availability of in-person instruction and support, it is unclear if alternative training methods are beneficial.

关键词： 新型化学纤维   功能纺织品   高性能纤维   高性能特种纤维   协同创新   融合发展  

摘要： 文章主要介绍了新型化学纤维的核心类别和优势,论述了新型化学纤维与功能纺织品和谐共生关系,探讨了新型化学纤维与功能纺织品如何通过协同创新促进二者融合发展,以提高产业价值,最大化发挥纺织品的功能优势,促进纺织产业高质量发展。

关键词： 复合加工   差异化   鲁正伟   高端化   复合创新  

摘要： 在柯桥纺织产业的完整链条中,复合加工作为衔接织造与后整理的关键环节,承担着赋予面料复合功能、提升产品附加值的重要作用。通过将不同性能的材料科学结合,该工序能实现防水、透湿、保暖、抗菌等“1+1>2”的功能整合,直接推动面料向高端化、差异化发展,成为柯桥纺织从规模优势向价值优势跃升的重要技术支点。鲁正伟从2002年赴柯桥投身复合加工行业以来,凭借近十年来扎根一线的扎实经验,逐步积累了丰富的技术底蕴。

关键词： Visual explanation   Object detector   XAI   CAM-based method  

摘要： Visual explanation for object detectors is crucial for ensuring model reliability and promoting their application across a variety of domains. However, existing visual explanation methods often produce low-quality heat maps that highlight only parts of important regions for detected instances. This limitation reduces the interpretability of object detectors and hinders effective model analysis. To address this issue, we propose Spatial Sensitive Grad-CAM++, a visual explanation method for object detectors designed to enhance the quality of heat maps. The proposed method introduces a weighted combination of gradient maps into the heat map computation, taking into account the architecture of object detectors. This approach enables a more accurate representation of each CNN channel’s contribution to the final heat map, resulting in high-quality heat maps that better identify important regions. In quantitative evaluations using the deletion and insertion metrics, we confirm that the proposed method outperforms existing methods by approximately 30% and 8%, respectively. In qualitative evaluations, we further demonstrate the superiority of the proposed method. These results suggest that the proposed method provides more faithful explanations, allowing for more accurate and reliable model analysis.