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关键词： 钎焊热循环   GH4169   显微组织   力学性能   缺口敏感性  

摘要： 为探究不同峰值温度的多次钎焊热循环对GH4169合金组织与性能的影响规律,以GH4169合金为研究对象,系统研究了钎焊热循环工艺对GH4169合金的析出相、晶粒尺寸、拉伸性能及持久性能的影响。结果表明:δ相的析出量随热循环温度的升高呈下降趋势,形态由针状转变为棒状后再转变为颗粒状;在970~1010℃范围内,晶粒尺寸变化不大,而当温度升高至1020℃以上时,晶粒显著长大。抗拉强度和硬度均随热循环温度的升高先增加后降低,并在1010℃时达到峰值,这主要得益于该温度下适量δ相溶解与γ″、γ′强化相的充分析出,而晶粒尺寸并未发生明显粗化;室温冲击韧性在不同的热循环范围具有不同的变化趋势,970~990℃范围内随温度升高而降低,这是由δ相的部分形态由针状转变为棒状所导致;990~1010℃范围内随着温度升高而增加,是由δ相溶解,无强化相析出带消失所导致,而继续增加热循环温度导致冲击韧性下降则是由于晶粒尺寸长大。持久寿命随热循环温度的升高先缩短后延长,在990~1000℃范围内达到最低点,这是由δ相的部分形态由针状转变为棒状,促进微孔形核,降低合金的抗蠕变能力所致。当温度进一步升高至1020℃以上时,γ″强化相大量析出并辅以晶粒显著长大,合金的蠕变性能得以显著改善,但针状δ相含量大幅度降低导致缺口敏感性增强。综合考虑力学性能与缺口敏感性,建议在1010℃左右进行钎焊热循环,可获得较为平衡的强度与持久性能;若服役环境对缺口敏感性要求较高,可选择970~980℃的热循环温度,以降低蠕变失效风险。

关键词： Adolescent hip dysplasia   Cam morphology   FAI   Hip   MRI  

摘要： Hip dysplasia and cam morphology are both common causes of hip pain in pediatric patients. However, there is limited literature on how the presence of hip dysplasia may affect the prevalence of cam morphology.

关键词： 3D-print   CAD/CAM   Color stability   Dental material   Discoloration   Resin composite  

摘要： This study aimed to evaluate the color stability of four three-dimensionally-printed (3D) resin composites, and compare them with nine other commonly used subtractive computer-aided designing/computer-aided manufacturing (CAD/CAM) materials and resin composites for direct restoration.

关键词： 2D-to-BIM conversion   BIM object generation   CAD material layer annotation   Semantic enrichment  

摘要： This study proposes a method for semantically enriching a building information model (BIM) by converting and supplementing material layer information in computer-aided-design (CAD) drawings into semantically rich BIM objects. Despite the widespread adoption of BIMs, practices relying on CAD drawings are still prevalent and fully automated conversion from CAD-to-BIM remains challenging. Previous studies on automatically converting 2D drawings into a BIM have primarily focused on geometric reconstruction, often overlooking textual data such as material layer annotations, which contain essential BIM object details. However, the recognition and conversion of material layer annotations to BIM objects pose several challenges, including inconsistent annotation formats, vague associations between annotations and objects, and missing material function and property information. To address these challenges, this paper introduces a four-step method: (1) semantic clustering of material layer annotations into groups corresponding to individual objects; (2) material layer function assignment using a newly proposed mistake-driven prompting technique, which incorporates feedback from common mistaken cases; (3) object type classification using a large language model based solely on material layer texts; and (4) automated generation of BIM objects semantically enriched with material property information in single-directional composite or light-framed structures. Validation on 90 real-world cases demonstrated a 99.9% weighted average adjusted Rand index for semantic clustering, a 99.5% weighted F1-score for layer function assignment, a 92.7% weighted F1-score for object type classification, and 100% accuracy in BIM object generation. This method is expected to enable a more complete 2D-to-BIM conversion by complementing geometric reconstruction with semantically rich material layer information.

关键词： Antiangiogenic bioactivity   CAM   Clerodendrum infortunatum   Deep learning  

摘要： Clerodendrum infortunatum Linn has long been valued in traditional medicine for its therapeutic properties. Phytochemical studies have revealed the presence of alkaloids, flavonoids, terpenoids, and phenolic compounds that contribute to its anticancer and anti-inflammatory activities. Since inflammation and angiogenesis are strongly correlated, this study investigated novel bioactive compounds in the ethyl acetate root extract of C. infortunatum and evaluated their antiangiogenic potential

关键词： ConvNeXt–MaxViT fusion   KOA severity grading   Radiographic deep learning   Transformer–CNN hybrid   Mid–late fusion   Grad-CAM++ explainability  

摘要： Knee Osteoarthritis (KOA) is a progressive degenerative joint disorder and a major cause of disability worldwide. Radiographic grading using the Kellgren–Lawrence (KL) scale remains the standard diagnostic method, but inherent subjectivity and difficulty in detecting subtle structural changes reduce diagnostic reliability. Thus, an automated, robust, and explainable system is clinically essential.

关键词： artificial intelligence   liver imaging   AI in liver imaging   LI-RADS   2D   two-dimensional   3D   three dimensional   AI   Artificial intelligence   AUROC   area under the receiver operating characteristic curve   AUC   area under the curve   BD-LSTM   bidirectional long short-term memory   CAD   computer-aided detection/diagnosis   C index   concordance index   CEUS   contrast enhanced US   CLAIM   Checklist for Artificial Intelligence in Medical Imaging   CNN   convolutional neural network   CT   computed tomography   DCNN   deep convolutional neural network   DL   deep learning   DSC   dice similarity coefficient   DWT   discrete wavelet transform   EHR   electronic health record   FAD   food and drug administration   FLL   focal liver lesion   GDPR   General Data Protection Regulation   HCC   hepatocellular carcinoma   HIPPA   Health Insurance Portability and Accountability   HRI   hepatorenal index   IT   information technology   LI-RADS   Liver Imaging Reporting and Data System   LSN   liver surface nodularity   LSTM   long short-term memory   MASLD   metabolic dysfunction–associated steatotic liver disease   METAVIR   meta-analysis of histological data in viral hepatitis   MR   magnetic resonance   MRI   magnetic resonance imaging   MRI-PDFF   magnetic resonance imaging proton density fat fraction   ML   machine learning   MVI   microvascular invasion   NLP   natural-language processing   PACS   picture archiving and communication system   RECISR   response evaluation criteria in solid tumors   RF   radiofrequency   RNN   recurrent neural network   SSL   Self-Supervised Learning   SVM   support vector machine   SWE   shear wave elastography   TACE   transarterial chemoembolization   US   ultrasound  

摘要： Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhanced diagnostic accuracy, efficiency, and reproducibility. The integration of machine learning and deep learning algorithms into radiological workflows has shown significant promise across a wide range of liver diseases. Key applications include automated liver segmentation on computed tomography (CT) and magnetic resonance imaging (MRI), enabling accurate liver volumetry and lesion localization. In metabolic dysfunction–associated steatotic liver disease, AI facilitates the detection and quantification of hepatic steatosis using advanced image analysis on ultrasound, CT, and MRI, providing a non-invasive alternative to biopsy. AI algorithms also demonstrate strong performance in detecting, classifying, and characterizing focal liver lesions such as hemangioma, focal nodular hyperplasia, hepatocellular carcinoma (HCC), and metastases, improving lesion conspicuity, standardizing reporting through LI-RADS, and reducing inter-observer variability. Beyond diagnosis, AI is increasingly applied for risk stratification and prognostication in HCC, integrating imaging, clinical, and laboratory data to predict tumor development, aggressiveness, treatment response, and survival outcomes. Despite these advances, the clinical implementation of AI in liver imaging faces notable challenges such as the need for data harmonization across scanners and institutions, rigorous validation in diverse patient populations, regulatory approval, and ethical considerations surrounding patient privacy, algorithmic bias, and transparency. Addressing these limitations through robust research, multi-center studies, and carefully designed clinical integration strategies is essential to safely and effectively harness AI’s potential. With continued development and validation, AI has the capacity to enhance diagnostic workflows, enable precision medicine, and ultimately improve patient outcomes in hepatolo

关键词： complex PCI   mechanical circulatory support   percutaneous coronary intervention   sex-specific outcomes   women’s health   ACS   acute coronary syndrome   CAD   coronary artery disease   IABP   intra-aortic balloon pump   MACE   major adverse cardiovascular events   MCS   mechanical circulatory support   MI   myocardial infarction   PCI   percutaneous coronary intervention  

摘要： Sex-based disparities persist in the management of patients with coronary artery disease undergoing complex percutaneous coronary intervention (PCI).

关键词： 石英纤维   间隔织物   延展性   连接层  

摘要： 为适用飞行器变体需求,研究石英织物的延展性能,分别设计了三种连接方式的间隔结构,使用不同石英纤维制备了九种石英间隔织物。经延展性测试发现,织物的延展性与纱线细度、连接纱线路径及弯折角度有关,纱线越细、连接纱线路径越长、弯折角越小,织物的延展性越高。

关键词： NX   CAM   数控车削加工   刀轨设置   后处理器  

摘要： 计算机辅助制造(CAM)凭借高效、数字化特征,在智能制造领域占据举足轻重的地位。以典型螺纹轴零件为研究对象,通过NX2312软件完成其CAM全流程,对NX数控车削编程模块展开全面深入解析。研究重点涵盖四层级几何体构建、车削刀轨工序设置、程序后处理器优化等关键内容。同时,系统阐述了数控车削加工工艺在NX-CAM中的实现路径,该技术策略可有效提升编程效率。经仿真加工与试制验证,所设计的工艺方案、刀轨工序及优化后的后处理器可加工出合格零件,且各项指标满足机床性能要求,为NX软件在数控车削加工中的工程应用提供了技术支撑。