抗HIV感染治疗模型及临床数据模拟

基于饱和发生率和艾滋病病毒（HIV）诱导CD4+ T细胞凋亡的机制,提出了一个改进的抗HIV感染治疗模型。新模型有病毒清除平衡点和持续带毒平衡点。证明了若模型的基本再生数[R0]小于1,则病毒清除平衡点全局渐近稳定;若模型的[R0]大于1,则持续带毒平衡点局部渐近稳定。基于斯坦福大学HIV耐药性数据库,用新模型模拟一组患者抗HIV感染治疗并做疗效的长期预测。数值模拟结果说明抗病毒治疗无法抑制HIV诱导CD4+ T细胞凋亡;HIV耐药性出现后若不及时更换治疗方案,耐药性会增强;长期预测表明该组患者的抗HIV感染治疗以失败告终。     

合成免疫策略治疗慢性乙肝病毒感染综述

慢性乙型肝炎病毒(Hepatitis B Virus,HBV) 感染可诱发肝硬化与肝癌,是危害人类健康的重大疾病。基于对 HBV 感染持续不愈主要是机体免疫功能缺陷所致的认识,提出用“合成免疫”策略重建抗 HBV 免疫功能,消除感染以预防致命病变的发生。用优化的基因治疗载体微环 DNA,在体内表达一套工程抗体,模拟急性 HBV感染康复时机体的免疫反应,由单克隆抗体中和病毒,双靶向抗体将非特异的 T 淋巴细胞转化为抗 HBV 的 T 淋巴细胞,杀死 HBV 感染的肝细胞,两者协同达到根治慢性 HBV 感染的目的。微环 DNA 安全、经济,可建立一个安全、高效、可负担的抗 HBV 免疫体系,有效消除 HBV 的危害。     

文件型病毒的清除

所谓文件型病毒是指寄生在正常可执行或动态链接库文件(如COM、EXE和DLL)中,通过运行被感染的文件而激活的一种病毒。虽然现在的电脑病毒越来越向着网络化蠕虫类发展,但仍然还有许多文件型的病毒横行。由于许多用户对查杀文件型病毒存在误解,因此这类病毒往往被认为很难清除,最     

神秘的3783病毒

最近,笔者发现了一种新的病毒,用目前常用的KV300、VRVNT、KILL等杀毒软件均不能发现和清除,因其感染EXE和COM文件时,使文件长度增长3783字节,故取名为3783病毒.它是一种两栖型(又称混合型)病毒,它既是系统型病毒,感染硬盘主引导扇区(即0道0头1扇区)和软盘的逻辑0扇区,又是文件型病毒,专门感染EXE文件和COM文件.3783病毒的神秘之处在于以下几点:其一,3783病毒感染硬盘和软盘时,病毒的首语句是JMP 013E(EB 3C),特别是软盘的逻辑0扇区,DOS 5.0以上版本的引导程序的首语     

一个微机“病毒”的感染,激活原理及其防治办法

目前,一个微机病毒〈下称病毒〉在国内微机上迅速蔓延开来,降低了微机使用效率,产生了一些不良影响。该病毒的表现形式是:在英文方式下,屏幕上出现一个类似台球运动的园点;在中文方式下,屏幕滚动反应极慢。打印24点阵汉字时,导致机器死锁。FORMAT/S命令格式化的系统盘不能启动,3~+网络系统软件失效……。对此,国内报刊已作了一些报道。本文分析该病毒的感染,激活原理,探讨防治办法。一、病毒的病理机制、感染激活条件病毒由病毒装入模块,病原体控制模块、感染模块和激活模块组成。物理上,病毒装入模块位于带病盘的逻辑第0扇段,而其它三个模块位于带病盘数据区,这些模块的逻辑关系见图1。     

血清C-反应蛋白在小儿支原体肺炎鉴别诊断中的临床观察

目的:观察血清C-反应蛋白(CRP)水平在小儿细菌性肺炎和支原体肺炎中的临床改变,探讨提高小儿支原体肺炎诊断符合率的检查方法方法:选择确诊为肺炎的患儿158例,根据其他实验室检查及临床疗效,分为细菌感染组82例和支原体感染组76例,比较两组患者就诊时血清CRP水平及治疗过程中血清CRP改变情况结果:细菌感染组与支原体感染组血清CRP阳性例数和就诊时血清CRP水平比较,差异具有高度统计学意义(P＜0.01);细菌感染组惠儿血清CRP水平与治疗天数呈正相关性(r=0.833,P＜0.01)结论:在小儿肺炎的诊断及治疗过程中,应积极行血清CRP,可提示患儿肺炎类型并指导临床治疗.     

封杀"中国一号"

“中国一号“计算机病毒是江民病毒快速反应小组捕获的一种新的网络蠕虫病毒,根据病毒体内特有的标记“R.P.China Version1.0“而得名,也称“尼姆达“(Nimda)病毒,是针对微软信件浏览器的弱点和WindowsNT/2000、IIS的漏洞编写出的一种传播性强、破坏力大的病毒.它在Windows9X/ME、WindowsNT、Windows2000等操作系统中传播,感染以nws、eml、doc、exe为扩展名的文件,并加以破坏或替换.清除该病毒的具体方法:……     

封杀“中国一号“

“中国一号“计算机病毒是江民病毒快速反应小组捕获的一种新的网络蠕虫病毒,根据病毒体内特有的标记“R.P.China Version1.0“而得名,也称“尼姆达“(Nimda)病毒,是针对微软信件浏览器的弱点和WindowsNT/2000、IIS的漏洞编写出的一种传播性强、破坏力大的病毒.它在Windows9X/ME、WindowsNT、Windows2000等操作系统中传播,感染以nws、eml、doc、exe为扩展名的文件,并加以破坏或替换.清除该病毒的具体方法:……     

自己手工修复中毒文件

现在的病毒非常厉害,不仅驻留系统、破坏文件,而且还会感染硬盘中的所有程序文件,造成病毒无法彻底查杀清除。对付这类文件感染型的病毒,该如何才能完全彻底的清除,抑制病毒的反复重生感染呢？     

面向复杂网络的中药方剂配伍规律挖掘算法

针对传统方剂配伍规律分析方法的不足,提出一种面向复杂网络的新型中药(traditional Chinese medicine,TCM)方剂配伍规律挖掘算法。根据中药方剂特性并结合点式互信息构建TCM网络模型,结合TCM网络的小世界特性提出TCM网络的局部适应度模型,分析TCM网络的特性并挖掘TCM网络中配伍关系紧密、相似度较大的药物群。以4 000余首经典方剂作为实验对象,验证了所提方法具有较好的有效性,与经典LFM(local fitness measure)算法对比,平均模块度值提高了0.05,为中药方剂的配伍规律进行探索及新药研发提供了新思路。     

基于二维概率元胞自动机的HBV动力学模型

为描述免疫系统中细胞微粒的多样性以及微粒运动和相互作用的随机性,在传统元胞自动机基础上,借用粗粒化思想,将多个状态变量引入元胞之中,并提出了“次级元胞”的概念,以表示不同类型的细胞粒子;应用该模型模拟乙型肝炎病毒（HBV）在无药物治疗情况下的自然感染和抗HBV药物药效比较,以及考察肝细胞感染率的影响因素,获得了较好的效果。     

Optimal control of a delayed system subject to mixed control-state constraints with application to a within-host model of hepatitis virus B

This paper deals with the problem of optimal control of a delayed differential equation system subject to mixed control-state constraints with application to a within-host model of hepatitis B virus (HBV). Our method consists to transform the optimal control problem of a delayed differential equation with mixed control-state constraints to a nondelayed problem in order to derive necessary optimality conditions. This theory is applied to a deterministic HBV model with two constant delays. We derive conditions under which is optimal to eradicate HBV within the body of a host. Through numerical simulations, we found that the best control strategy to reduce the HBV infection is the combination of treatment in blocking new infection and treatment in inhibiting viral production.     

Iterative learning control for robotic-assisted upper limb stroke rehabilitation in the presence of muscle fatigue

The use of iterative learning control to regulate assistive functional electrical stimulation applied to the muscles of patients undergoing robotic-assisted upper limb stroke rehabilitation has been followed through small scale clinical trials. These trials confirmed that an increase in patient ability to complete the specified task also led to a reduction in the level of electrical stimulation required. This previous work assumed that the effects of muscle fatigue could be neglected but if a patient suffers fatigue during a rehabilitation session then their the session goals are not achieved or, more likely, the session must be abandoned due to the time limits imposed by the ethical approval required to conduct such sessions. In this paper the results of the first investigation into enhancing the control scheme to remove or lessen the effects of fatigue and hence make better use of the time available for a session are given. The scheme considered adds a feedback loop around the muscle model used, where the performance results given are based on a model for the dynamics constructed using patient data collected in previous clinical trials.     

中医推拿动素的规范化描述模型与实例应用

按照中国普通人的手型特征,将手掌划分为22处具有不同用力等级（0～10）的施力点,建立中医推拿的动作编码词汇表,给出形式化规范语言描述模型,包括实例表达、实例检索、实例修正、实例使用与保存4个步骤。应用人因工程Jack软件工具进行手法修正并分析医师推拿手掌的疲劳值。给出一个脊髓型颈椎病患者实例,验证该模型和方法的有效性。     

Combining case-based reasoning with Bee Colony Optimization for dose planning in well differentiated thyroid cancer treatment

Thyroid cancers are the most common endocrine carcinomas. Case-based reasoning (CBR) is used in this paper to describe a physician’s expertise, intuition and experience when treating patients with well differentiated thyroid cancer. Various clinical parameters (the patient’s diagnosis, the patient’s age, the tumor size, the existence of metastases in the lymph nodes and the existence of distant metastases) influence a physician’s decision-making in dose planning. The weights (importance) of these parameters are determined here with the Bee Colony Optimization (BCO) meta-heuristic. The proposed CBR–BCO model suggests the I-131 iodine dose in radioactive iodine therapy. This approach is tested on real data from patients treated in the Department of Nuclear Medicine, Clinical Center Kragujevac, Serbia. By comparing the results that are obtained through the developed CBR–BCO model with those resulting from the physician’s decision, it has been found that the developed model is highly reflective of reality.     

Tag-based personalized image ranking in event browsing

Many image sharing websites, e.g. Flickr, Google+ , allow users to upload images as an event, and users can browse the images others uploaded as events. The fact that people usually browse only the first few images of an event then decide whether the event is what they want makes us believe that it is necessary to present those images people favor on the very first position for each event. Here we propose a new tag- based personalized image-ranking algorithm in event browsing such that it gives image higher score if it: a) is important in the event, b) matches user’s preference. c) matches user’s query. To this end, we first adopt a local matching model to assign images an original score based on whether this image satisfies user’s query and preference. We then propose a global ranking model to take the local scores as initial values and make the salience scores iteratively smooth with respect to all images returned from the events of the query.     

Learning efficiency of redundant neural networks in Bayesianestimation

This paper proves that the Bayesian stochastic complexity of a layered neural network is asymptotically smaller than that of a regular statistical model if it contains the true distribution. We consider a case when a three-layer perceptron with M input units, H hidden units and N output units is trained to estimate the true distribution represented by the model with H(0) hidden units and prove that the stochastic complexity is asymptotically smaller than (1/2) {H(0 ) (M+N)+R} log n where n is the number of training samples and R is a function of H-H(0), M, and N that is far smaller than the number of redundant parameters. Since the generalization error of Bayesian estimation is equal to the increase of stochastic complexity, it is smaller than (1/2 n) {H(0) (M+N)+R} if it has an asymptotic expansion. Based on the results, the difference between layered neural networks and regular statistical models is discussed from the statistical point of view.     

Antiviral therapy using a fuzzy controller optimized by modified evolutionary algorithms: a comparative study

Hepatitis is usually caused by a viral infection or metabolic diseases. Hepatitis type B virus (HBV) infection is among the most common causes of hepatitis and can result in serious liver diseases. Several dynamic models have been developed to mathematically describe the HBV infection and antiviral therapy. In addition, different control strategies have been reported in the literature to deal with optimal antiviral therapy problem of infectious diseases. In this paper, a set of optimized closed-loop fuzzy controllers are employed for optimal treatment of basic HBV infection. To optimize the proposed scheme, five modified and modern optimization algorithms are investigated. After designing the controller, some parameters of the HBV infection model are considered to be unknown, and the robustness of the optimized controller is studied. Experimental results show that the covariance matrix adaptation–evolution strategy-based optimized closed-loop fuzzy controller has the best performance in terms of total cost of an objective function defined based on maximization of uninfected target cells, minimization of free HBVs and minimization of drug usage. In addition, the execution time of this optimization algorithm is only 8 % more than the execution time of imperialist competition algorithm as the investigated algorithm with the best convergence speed.