一种pH敏感相分离高分子在免疫分析中的应用

将乙肝表面抗体与N-羟基琥珀酰亚胺丙烯酸酯反应，生成丙烯酰基抗体．丙烯酰基抗体与甲基丙烯酸、丙烯酰胺共聚，生成pH敏感的三元共聚物．三元共聚物溶解．沉淀的临界pH值为3．8．三元共聚物上的抗体能与表面抗原、酶标抗体形成夹心复合物．利用三元共聚物可逆的溶解．沉淀特性，能实现在均相条件下，进行免疫反应，在异相条件下，进行免疫复合物的分离．     

一种提高微电路外壳使用可靠性的方法

简要分析了白瓷双列直插外壳的失效模式和失效机理，并进行了模拟实验，通过对实验结果的分析，提出对成品微电路进行二次电镀能够提高其外壳的使用可靠性。     

含氢硅单晶2210cm-1红外吸收峰本质的理论研究——Ⅰ.振子频率的价键力场计算

本文根据Urey-Bradely 力场的思想,用价键力场的方法对文献[1]中提出的含氢硅单晶中2210cm^-1吸收峰对应的缺陷复合体的两个模型:空位+4H,间隙硅烷,进行了振动频率的计算.在对计算结果和力常数调节合理性分析的基础上,得出了空位+4H模型比较合理的结论.此外还介绍了理论计算揭示的从实验上区分两个模型的可靠途径.     

理想微裂纹系统中的随机扩展效应

本文讨论了在理想微裂纹系统中,由于微裂纹的随机性扩展,对微裂纹统计演化产生的效应。文中提供了一般的理论框架,给出了便于处理的转移概率的表达式。最后,用数值计算的例子展示了随机模型的统计演化特征,并比较了与确定性扩展模型下统计演化的异同。     

损伤断裂图型演化的统计描述

本文采用动力学演化与随机跃迁并存的模型,研究损伤断裂图型的演化规律。根据演化的终态,损伤演化可分为整体稳定(GS)和演化引起剧变(EIC)两种模式,后者联系于断裂现象。本文引入统计描述,并指出,即使微损伤的连接规律是确定性的,无序介质中断裂的出现亦应以概率分布函数描写。     

SW233 PIN驱动器自动测试系统的研制

介绍了一种集成电路自动测试系统，该系统采用计算机并口作通信接口，用VB6编程，实现了对外围测试电路的控制，用IEEE-488接口卡控制测试仪器，可对SW233电路的36个参数进行自动测试，并将测试结果自动保存在数据库中。该测试系统具有自动化程度高、操作方便、测试结果精确等特点。     

Tuning the band gap of the CIGS solar buffer layer Cd1-xZnxS (x=0—1) to achieve high efficiency

To evaluate the impact of zinc sulfate (ZnSO4) concentration on the structural properties of the films, Cd1-xZnxS thin films were formed on glass substrates using chemical bath deposition (CBD) in this study. The effect of ZnSO4 precursor concentration on the surface morphology, optical properties, and morphological structure of the Cd1-xZnxS films was investigated. To study the impact of zinc doping content on the performance metrics of Cu(In1-xGax)Se2 (CIGS) cells in the experimental group and to improve the buffer layer thickness, simulations were run using one-dimensional solar cell capacitance simulator (SCAPS-1D) software.     

Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.     

维生素B12缺乏致神经损害临床分析

维生素B12缺乏多继发于胃肠道外科手术后、贫血及其它内科疾病，其引起的神经系统损害临床表现多样，主要为周围神经损害及亚急性联合变性。测定维生素B1：值、查肌电图等可明确诊断。补充维生素B12治疗有效。