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摘要： Three-dimensionally (3D) printed composite resin materials for definitive restorations have recently been introduced but doubts still exist regarding their mechanical properties.

关键词： East Asian summer precipitation   Deep convection scheme   Cloud physics scheme   Perturbed parameter ensemble   CAM6  

摘要： This study investigated the impacts of key parameters in CAM6's deep convection and cloud physics schemes on the simulation of summer-mean precipitation over East Asia through conducting perturbed parameter ensemble(PPE)*** the experimental platform of CAM6,a suite of 128 PPE simulations spanning 19792014 were generated through simultaneously perturbing 12 selected *** EOF analysis,this study firstly extracted the first two leading modes of the precipitation simulation *** authors further pinpointed the most critical parameters that have the most influential effects on the precipitation simulation biases,through conducting generalized linear model *** first leading mode of precipitation simulation biases is primarily influenced by parameters from the cloud physics scheme,including the linear effects of dcs and eii,and the nonlinear effect of rhminl**** parameters influence the simulated total precipitation(PrecT)mainly by altering the large-scale precipitation(PrecL).The second leading mode is predominantly governed by the convection scheme parameter dmpdz,reflecting a competition between the changes in convective precipitation(PrecC)and PrecL in response to variations in *** increase in dmpdz induces decreased PrecC and increased PrecL in East Asia,and both of the changes collectively shape the ultimate PrecT response to the adjusted ***,it is noteworthy that the nonlinear effect due to the interaction among parameters warrants attention when concurrently adjusting multiple parameters,and the precipitation biases from the PPE simulations resemble those identified through EOF analysis on the AMIP simulations,implying our findings may provide potential reference for other AGCMs.

关键词： 中成药   益母草颗粒   高效液相色谱法(HPLC)   二极管阵列检测器(DAD)   电雾式检测器(CAD)   多成分检测   质量一致性  

摘要： 目的:系统评价益母草颗粒中4种成分的含量差异,揭示同厂家及不同厂家产品的质量波动规律,为生产工艺优化与质量控制提供科学依据。方法:采用高效液相色谱-二极管阵列检测器-电雾式检测器联用法(HPLC-DAD-CAD),测定19个厂家(53批次,159盒)样品中丁香酸、盐酸益母草碱、阿魏酸、盐酸水苏碱4种成分的含量,绘制指纹图谱,并计算指纹图谱差异度(P_(S))及同厂家不同样品的相对标准偏差(RSD);以P_(S)和4种成分RSD为变量构建主成分分析(PCA)模型,对厂家进行分类;选取涵盖3类一致性组的5个厂家(M1~M5)样本,计算其批内一致性(P_(A))、批间一致性(P_(B))及P_(S) 3个质量一致性参数,并以这5个厂家的P_(A)、P_(B)、P_(S)为变量进行PCA。结果:19个厂家样品中4种指标成分的平均总含量为41.10~97.54 mg/袋,其中2025年版《中华人民共和国药典》质控成分盐酸水苏碱含量为32.46~72.70 mg/袋,均符合要求,其RSD为1.7%~17.1%;其余3种成分含量分别为丁香酸1.43~41.92 mg/袋、盐酸益母草碱0.67~11.85 mg/袋、阿魏酸0.11~3.81 mg/袋,其中盐酸益母草碱在同厂家样品间的含量波动最显著(RSD 4.8%~59.2%)。PCA结果显示,19个厂家可划分为三类,8个厂家样品(M2、M6、M7、M8、M10、M15、M17、M18)一致性较高;5个厂家样品(M3、M9、M12、M13、M14)一致性中等;6个厂家样品(M1、M4、M5、M11、M16、M19)一致性较低。2种方法对5个代表厂家的分类结果一致,其中M2厂家质量一致性和指标成分总含量为M1~M5中最优。结论:该研究建立的HPLC-DAD-CAD多检测器联用技术可实现益母草颗粒中4种成分的精准检测,19个厂家产品中的4种指标成分总含量差异明显,应用2种一致性评价方法结合PCA均能有效将其一致性划分为三类,2种方法的分类结果高度一致,该研究可为益母草颗粒工艺优化及质量标准提升提供科学依据。

关键词： coronary artery disease   coronary sinus Reducer   non-obstructive   refractory angina   AngioNOCAD   angiographically non-obstructive CAD   ANOCA   angina with nonobstructive coronary arteries   CABG   coronary artery bypass grafting   CAD   coronary artery disease   CCS   Canadian Cardiovascular Society   CMD   coronary microvascular dysfunction   CS   coronary sinus   MACE   major adverse cardiac events   MI   myocardial infarction   PCI   percutaneous coronary intervention   RA   refractory angina   SAQ   Seattle Angina Questionnaire  

摘要： Patients with angiographically nonobstructive coronary artery disease (CAD) (AngioNOCAD), including those with previous successful revascularization, often experience refractory angina (RA).

关键词： 广电传输网   CAD   Excel   DXF   设计效率  

摘要： 针对广电传输网CAD设计文件中的文本数据修改效率低、易出错的问题,本文提出一种基于Excel与DXF图形接口的批量处理方法。该方法通过将CAD图纸导出为DXF格式,并利用Excel进行结构化数据处理,实现文本内容的精准批量替换与更新。以某OTN国干传输网工程为例,应用本方法后,其设计修改时间从90min缩短至20min,且错误率为零。本方法无须编程基础,操作简便,可显著提升设计效率与数据一致性。

关键词： 多臂织机   表里换层双层织物   大提花织物   纹样设计   织物组织   降本增效  

摘要： 为突破多臂织机生产复杂花形面料的技术瓶颈,以表里换层双层仿大提花织物为研究对象,开展系统性探索。分析了表里换层双层织物的纹样设计机理,依据经典设计范式与仿大提花设计路径,成功开发了“沦纹叠韵”“萦列花章”和“别具格韵”三款风格迥异的仿大提花织物,详述了其纹样构形、组织设计、工艺参数设定,并试织小样。实践证明:依托表里换层双层组织在多臂织机上实现仿大提花面料的织造具备技术可行性。认为:挖掘多臂织机的潜力,生产复杂花形面料,有助于企业实现降本增效,满足高端面料市场的多元化需求。

关键词： Partial ceramic crown   Long-term   CEREC   Universal adhesive   Self-adhesive resin cement  

摘要： This study evaluated the long-term clinical performance and survival of CAD-CAM-fabricated partial ceramic crowns (PCCs) luted with either self-adhesive resin cement, or conventional luting composite combined with a universal adhesive, applied without or with selective enamel etching.

关键词： U-Net   FoVE增强   Grad-CAM   建筑物提取  

摘要： 在深度学习U-Net网络结构的基础上,尝试提出一种改进方法,结合FoVE滑窗策略和Grad-CAM可视化分析,提升模型在边缘区域的提取精度和对模型识别过程的理解能力。实验中采用Inria遥感建筑物数据集,比对了引入和未引入FoVE策略两种情况下的模型性能。结果表明,引入FoVE滑窗机制后,模型在F1值、IoU、Dice系数和边界IoU等指标上均有所提升,尤其在小型建筑物的识别和边界细节还原方面效果更好。同时,Grad-CAM生成的热力图与建筑物实际位置较为一致,有助于了解模型关注的区域,提高结果的可信度。本文所提出的方法在保持较高分割精度的基础上,提高了模型的稳定性和可解释性,具有一定的实用价值。

关键词： 经编织物   贾卡组织   分区设计   热湿舒适性   跑步服  

摘要： 为研究女跑服的贾卡分区设计,提出通过优化贾卡网孔组织结构和牵拉密度来改善跑步服的透气性和弹力支撑性能。根据女性体表热量分布和出汗特征,将跑步服划分为高热湿区域、轻量化透气区域和弹力支撑区域,测试并分析了36种不同牵拉密度和贾卡组织结构的透气性、弹力拉伸性能及吸芯性能。结果表明:不同贾卡组织结构织物的性能随牵拉密度和网孔比例的变化得到显著优化,分区设计有效提升了跑步服的舒适性和功能性。

关键词： Cardamom pods   Deep Learning   Grad-CAM   Kotlin   Multi-scale domain generative adversarial network   Multispectral imaging  

摘要： Classification of cardamom pods remains a challenging task due to changes in lighting, inconsistencies in texture, and spectral features that overlap with existing methods, which lack the attributes of robustness, interpretability, and real-time usability. This research addresses the aforementioned issues by introducing an advanced dual-stream deep learning model, Di-stream improved Divine Religions Planarian ConvNeXt (DDRPCNeXt), which combines deep spatial features with handcrafted descriptors for enhanced discrimination of spectral and textural features. Supported by the Improved Divine Religions Algorithm (IDRA) metaheuristic optimizer, the model gets to enjoy fast convergence and stable training. Gradient-weighted Class Activation Mapping (Grad-CAM) guarantees that predictions are transparent and interpretable by showing visual heatmaps. The system is made available via a Kotlin cross-platform mobile application, which allows for on-device real-time classification. When tested with a dataset consisting of 1000 high-resolution cardamom images, the framework demonstrated outstanding performance, recording 99.25% accuracy, 99.09% precision, and 99.15% recall and F1-score. Such results validate the suggested solution as a tool for automated agricultural quality control that is accurate, interpretable, and ready to be used in the field.