医科达数字化电子直线加速器控制软件IPV基本原理与应用解读

目的 介绍医科达数字化医用电子直线加速器控制软件里子项目和项目成分值(IPV)的工作原理,并具体说明控制软件通过三类子项目及其项目分项实时监测、控制子系统的运行状态。方法 首先介绍医科达数字化医用电子直线加速器的控制系统组成,然后介绍控制软件里子项目和项目分项的定义和分类,以及各类子项目的基本原理,最后通过分析高功率移相器的运动控制具体说明控制软件的子项目在实时监测、控制子系统运行状态的应用。结果 通过分析原理和举例详细、具体说明了控制软件IPV的工作原理及其应用,使用户尤其是维修人员能掌握相应理论知识,在日常使用和维修时能通过软件快速准确地查找运行参数,并根据相关子系统的控制原理分析问题和解决故障。结论 用户尤其是维修人员掌握这些子项目及其项目分项的工作原理,就能在日常使用或维修、校准时,快速准确地通过控制软件查看、校准运行参数,解决设备故障,并避免错误操作引起事故。     

嗜肺军团菌致病性与效应蛋白的研究进展

嗜肺军团菌是一种可以引起军团菌肺炎和庞蒂亚克热的兼性胞内病原菌，主要侵染阿米巴原虫和人类巨噬细胞。该菌在宿主胞内能依靠Dot/Icm IVB型分泌系统产生的效应蛋白成功逃避溶酶体的降解。本文主要对嗜肺军团菌的致病物质、胞内存活与增殖机制及其效应蛋白的生物学功能进行综述，详细介绍嗜肺军团菌的毒力因子与致病机制，为军团病防治的研究提供新思路，也为其他胞内病原菌所致感染性疾病的研究提供重要的借鉴意义。     

Sliding mode control of time‐varying delay Markov jump with quantized output

This paper investigates the quantized sliding mode control of Markov jump systems with time‐varying delay. A dynamical adjustment law is explored to quantize the system output. By constructing an observer‐based integral sliding surface, a sliding mode controller is designed to take over the dynamical motion of state estimation and ensure the reachability of sliding surface. A new scaling manner is developed to build the bound between the system output and quantized error. With the help of separation strategies for controller synthesis and general transition probabilities and a lower bound theorem for nonlinear integral terms, a new synthesis method to ensure the required stability and meet the required performance is proposed in the form of linear matrix inequalities. The validity of the proposed control method is illustrated by a numerical example.     

Safety profile of the adjuvanted recombinant zoster vaccine: Pooled analysis of two large randomised phase 3 trials

Background

The ZOE-50 (NCT01165177) and ZOE-70 (NCT01165229) phase 3 clinical trials showed that the adjuvanted recombinant zoster vaccine (RZV) was ≥90% efficacious in preventing herpes zoster in adults. Here we present a comprehensive overview of the safety data from these studies.

A low cost smart system to analyze different types of edible Bird's nest adulteration based on colorimetric sensor array

This study was performed to develop a low-cost smart system for identification and quantification of adulterated edible bird's nest (EBN). The smart system was constructed with a colorimetric sensor array (CSA), a smartphone and a multi-layered network model. The CSA were used to collect the odor character of EBN and the response signals of CSA were captured by the smartphone systems. The principal component analysis (PCA) and hierarchical cluster analysis (HAC) were used to inquiry the similarity among authentic and adulterated EBNs. The multi-layered network model was constructed to analyze EBN adulteration. In this model, discrimination of authentic EBN and adulterated EBN was realized using back-propagation neural networks (BPNN) algorithm. Then, another BPNN-based model was developed to identify the type of adulterant in the mixed EBN. Finally, adulterated percentage prediction model for each kind of adulterate EBN was built using partial least square (PLS) method. Results showed that recognition rates of the authentic EBN and adulterated EBN was as high as 90%. The correlation coefficient of percentage prediction model for calibration set was 0.886, and 0.869 for prediction set. The low-cost smart system provides a real-time, nondestructive tool to authenticate EBN for customers and retailers.