课程文献中心 更多>>

关键词： 气质联用技术   纺织品   农药残留  

摘要： 纺织品中的农药残留不仅危害生态环境和人体健康,而且威胁到我国纺织品出口利益。目前,纺织品农药残留检测技术日趋成熟。其中,气相色谱-质谱(GC-MS)联用技术以其优良的分离性、灵敏性和准确性在该领域得到了广泛应用。综述了气相色谱-质谱(GC-MS)联用技术在纺织品农药残留检测中的应用情况并进行了未来展望,旨在为该技术在纺织品农残检测领域的未来发展提供参考。

关键词： Bare GCE   CaM@rGO   Catechol   Electrochemical sensor   Hydroquinone   Nanocomposite  

摘要： Hydroquinone (HQ) and catechol (CC) are widespread environmental pollutants known for their high toxicity and poor biodegradability. Herein, we devised an electrochemical sensor for sensitive and selective detection of HQ and CC. The glassy carbon electrode (GCE) was meticulously modified by using the Ca-perovskite (CaTiO₃/GCE), zinc-based metal-organic frameworks (Zn-MOF/GCE), and their nanocomposite with reduced graphene oxide (rGO), i.e., CaTiO₃-Zn-MoF@rGO/GCE (CaM@rGO/GCE). The CaM@rGO/GCE sensor showed stupendous electrochemical performance due to the synergistic effects of rGO's high conductivity and Ca-perovskite's electrocatalytic activity. Furthermore, the Zn-MOF component ensures the sensor's remarkable stability. The developed sensor boasts impressive selectivity towards HQ and CC, achieving exceptionally low detection limits (0.0086 µM (S/N = 3) for HQ, 0.0115 µM (S/N = 3) for CC), and broad linear ranges (0.05–105 µM for HQ, 0.05–120 µM for CC). The sensor shows better sensitivity to hydroquinone (HQ) than catechol (CC) due to the absence of intramolecular hydrogen bonding in HQ. The sensor's real-world applicability was validated by analyzing environmental water samples, demonstrating its immense potential for practical environmental monitoring. © 2024 Elsevier B.V.

关键词： Aphasia   Grad-CAM   Explainable AI   XAI   Speech recognition   Spoken keyword classification   Impaired speech   Deep learning  

摘要： Aphasia, a language disorder caused by brain injury, presents significant speech recognition and classification challenges due to irregular speech patterns. While the standard Grad-CAM (Gradient-weighted Class Activation Mapping) technique is widely used for model interpretation, its application to impaired speech remains largely unexplored. To address this gap, we introduce a set of extension studies of enhanced Grad-CAM techniques, namely Enhanced Directional Grad-CAM (ED-GCAM), Multi-Scale Channel-wise Grad-CAM (MSCW-GCAM), Stochastic Gradient-Dropout Integrated Grad-CAM (SGD-GCAM), and Enhanced Hierarchical Filtered Grad-CAM (EH-FCAM) to improve interpretability and performance in aphasia speech keyword classification. When applied to attention-based CNN models, these techniques generate more focused, class-specific heatmaps, providing a deeper understanding of model behaviour, particularly in noisy and impaired speech. Our results demonstrate that these enhanced Grad-CAM methods outperform the standard Grad-CAM by offering more detailed and meaningful explanations, which is critical for interpreting models applied to aphasia speech. We compare our approach using qualitative and perturbation-based trustworthiness, infidelity and sufficiency scores as quantitative metrics. Among the techniques, ED-GCAM outperformed all others. The proposed methods significantly improve the accuracy and transparency of speech processing models, with potential suggestions for clinical applications.

关键词： Additive manufacturing   Bone drilling   Craniotomy   Medical training   Neurosurgery   Simulation model   3D   3-dimensional   CAD   Computer-aided design   DAP   Digital Anatomy Printer   FFF   Fused filament fabrication (process)   Gy   Gyroid (infill pattern)   MJ   Material jetting (process)   MM   Multimaterial   OR-IW80   Outer-Rigid10k & Interior-White resin 80% infill density   OW-IR20   Outer-White resin & Interior-Rigid10K 20% infill density   OW-IR40   Outer-White resin & Interior-Rigid10K 40% infill density   PETG   Polyethylene terephthalate glycol (material)   PEEK   Polyether ether ketone (material)   PLA   Polylactic acid   SLA   Stereolithography (process)   STN   Standard Trade Name  

摘要： Three-dimensional (3D) printing technology presents a promising avenue for the development of affordable neurosurgical simulation models, addressing many challenges related to the use of cadavers, animal models, and direct patient engagement. The aim of this study is to introduce and evaluate a new high-fidelity neurosurgical simulation model targeted for both burr hole and craniotomy procedures.

关键词： atherosclerosis   atherosclerotic cardiovascular disease   atherosclerosis imaging   coronary artery disease   coronary CT angiography   polygenic risk score   quantitative computed tomography   ASCVD   AUC   area under the curve   CACS   coronary artery calcium scoring   CAD   CTA   computed tomography angiography   HRP   high-risk plaque   LDL   low-density lipoprotein   MACE   major adverse cardiovascular events   PAV   percent atheroma volume   PR   positive remodeling   PRS  

摘要： The longitudinal relation between coronary artery disease (CAD) polygenic risk score (PRS) and long-term plaque progression and high-risk plaque (HRP) features is unknown.

关键词： 标准   检测   纺织品   色牢度  

摘要： 文章通过对GB/T 14576—2009《纺织品色牢度试验耐光、汗复合色牢度》、ISO 105-B07:2009(E)《纺织品色牢度试验第B07部分:耐光、汗复合色牢度》、AATCC TM125-2013e2(2020)《耐光汗色牢度的试验方法》、JIS L 0888:2018《耐光和耐汗色牢度的试验方法》标准的设备、测试原理、试样准备、标准材料、汗液制备、曝晒条件中的关键指标及曝晒方法和评级方面的解读分析,为从事纺织品耐光色牢度检测的试验人员提供全面的参考。

关键词： 构造实体几何(CSG)   混合几何   CAD几何   RMC   网格化   蒙特卡罗  

摘要： 为拓展蒙特卡罗程序RMC基于计算机辅助设计(CAD)几何输运能力,面向新型数值反应堆的RMC基于CAD几何建模输运提供新的计算手段。首先采用开源网格化内核处理CAD几何模型,实现全流程自主化的RMC基于CAD几何输运方法,其次开发了CAD与构造实体几何(CSG)的混合几何输运框架,提高几何处理效率和RMC输运效率。通过燃料球、VERA-3A燃料组件等模型的数值计算,验证了自主化CAD几何处理方法、混合几何建模输运方法的正确性;与现有CAD几何建模输运方法相比,混合几何建模输运方法在几何处理时间、计算效率等方面取得显著提升。因此,本研究开发的RMC基于CAD几何输运拓展功能可以用于新型数值反应堆的中子学分析计算。

关键词： plasticity   modified   state  

摘要： The modified Cam-clay(MCC)model was the first modern soil plasticity model,serving as the foundation for many advanced soil plasticity ***,it is essentially a two-dimensional(2D)constitutive model because it assumes that two principal stresses are always equal under triaxial ***,it cannot accurately represent a true triaxial stress state where the three principal stresses vary independently.

关键词： 气相色谱-质谱联用技术   纺织品   检测技术   应用  

摘要： 气相色谱-质谱(GC-MS)联用技术作为纺织行业检测领域中重要的现代技术手段,具有高效分离能力、快速分析速度、低样品消耗等优势,实现了对样品高效分离与鉴定。文章详述了气相色谱-质谱联用技术的基本原理,综述其在纺织行业中纺织品的禁用偶氮染料、有机氯载体、含氯酚类物质、有机锡化合物、邻苯二甲酸酯、挥发性有机化合物检测应用进展,总结气相色谱-质谱联用技术在纺织品检测中存在的问题,并对其未来的研究发展进行展望。

关键词： 目标检测   机织物疵点   YOLOv7   小目标语义   注意力机制  

摘要： 针对在机织物检测中,现有算法对于小目标的机织物疵点检测效果不佳,同时图像受噪声、类别不均影响导致算法学习困难、精度低的现状,提出使用一种可学习数据增强网络与YOLOv7直接相连,实现端到端训练,使输入图像能够在训练过程中得到转译,以提高图像的输入质量。设计了一种核选择注意力机制,并将其嵌入到YOLOv7的小目标检测头中,使网络更加关注小目标的特征。最后,将ELAN模块与一种基于像素的Transformer相结合,形成了ELAN⁃Transformer,并将其引入到YOLOv7的骨干网络中,克服ELAN模块在处理小疵点区域时的局限性,使网络对疵点区域的语义感知能力得到显著增强,提高了对疵点目标的准确性和鲁棒性。试验结果表明:在包含微小机织物疵点数据集上测试,该研究算法能更好地检出小目标机织物疵点,mAP@0.5达到95.2%,精度达到95.5%,召回率相比于原YOLOv7提升了2.8个百分点,满足纺织企业对机织物微小疵点的检测需求。