人工智能在新型冠状病毒肺炎中的研究综述

新型冠状病毒肺炎（corona virus disease,COVID-19）的暴发对全球人类的生命财产安全造成了巨大威胁。人工智能（artificial intelligence,AI）为助力打赢这场疫情攻坚战发挥了不可替代的作用。由于AI的助力,医疗资源紧张的问题得到大幅度缓解,并提高了医疗诊断效率,同时也避免接触感染的风险。阐述了COVID-19和AI的背景知识,从疫情趋势预测、疫情溯源追踪、检测诊断、药物开发、疫苗研制、药物再利用、网络舆论管控以及基因组测序这8个疫情防控的环节讨论了AI在本次COVID-19中的研究进展,并列举本次疫情中AI所面临的挑战,浅谈本次疫情对我国AI产业影响以及两者的辩证关系,对全文进行总结。     

卫生经济学应用于慢性病防控决策的战略研究

为提高当前慢性病防控体系的效率,更好地遏制慢性病的流行,保护公众健康,2015年中国工程院设立了"卫生经济学应用于慢性病防控决策的战略研究"重大咨询项目。课题组调研发现,作为一种重要的卫生决策工具,卫生经济学在慢性病防控决策过程中尚处于初级应用阶段。对卫生经济学的重要性认识不足,对卫生经济学的方法的掌握和应用能力有限,制约了其在慢性病防控决策中的应用,因此建议建立多元主体参与的卫生经济学研究力量,加强卫生经济学应用于慢性病防控决策的大数据积累及应用研究,提出将卫生经济学应用于我国慢性病防控决策的战略框架。     

输电线路外力破坏防控措施浅析

输电线路保护工作中存在电力行政执法主体缺位、"防外破"闭环管控机制不完善、外破违法行为代价低等问题,对线路的安全运行带来严重威胁,通过政企联动开展电力设施保护各项活动,在队伍、宣传、防控、追责等方面着力,把安全知识和意识传递给工商企业、特种车辆驾驶员以及花农种植户,强化输电线路外破防控,保障电网安全运行。     

2010年我国恶意代码新特点的研究

文章以公安部2010年计算机病毒疫情调查活动的数据作为基础,以国家计算机病毒应急处理中心国家级恶意代码样本库作为支撑,结合信息网络安全通报机制成员单位汇总的情况和各反病毒研究机构发布的安全报告,阐述了2010年我国恶意代码发展的总体情况,分析了2010年我国恶意代码出现的新特点,探索了今后恶意代码的发展趋势并提出对策建议。     

基于数据仓库技术的疫情决策支持系统的研究

为了疫情监测的网络化,信息化,标准化,及疫情预防控制信息系统的统一化,对疫情监测及预警展开研究,构建了一个以数据仓库技术为基础,结合联机分析处理技术的疫情监测决策支持系统。该系统通过建立数据仓库对来自不同数据源的疫情数据进行存储,采用联机分析处理技术对各级部门上传的疫情数据进行多角度、多侧面的分析,为决策人员做出决策提供强大的辅助支持。     

利用触发器提升医院疫情上报效率

疫情信息的及时、准确反馈是保障传染病有效预防和控制的前提。只有将突发应急体系和现有医疗信息网络进行融合,完善医院内部信息系统才能更好的提高应对突发卫生事件的能力。该文主要阐述了在医院信息系统中使用触发器提高疫情上报效率的方法和体会。     

Protein Interactome Analysis for Countering Pathogen Drug Resistance

Drug-resistant varieties of pathogens are now a recognized global threat. Insights into the routes for drug resistance in these pathogens are critical for developing more effective antibacterial drugs. A systems-level analysis of the genes, proteins, and interactions involved is an important step to gaining such insights. This paper discusses some of the computational challenges that must be surmounted to enable such an analysis; viz., unreliability of bacterial interactome maps, paucity of bacterial intera...     

网络攻击与防范研究

随着信息时代的到来,越来越多的企业或个人逐步意识到信息安全防护的重要性。计算机网络、数据通信、电子商务、办公自动化等领域需要解决信息安全问题。如何保护企业或个人的信息系统免遭非法入侵？对目前计算机网络存在的网络攻击方法进行了分析,从发现正确的目标到执行攻击,并提出相应的防范措施。     

Understanding dengue fever dynamics: a study of seasonality in vector-borne disease models

Dengue fever dynamics show seasonality, with the disease transmission being higher during the warmer seasons. In this paper, we analyse seasonally forced epidemic models with and without vector dynamics. We assume small seasonal effects and obtain approximations for the real response of each state variable and also for the corresponding amplitude and phase via decomposition of the sinusoidal forcing into imaginary exponential functions. The analysis begins with the simplest susceptible-infected-susceptible (SIS) model, followed by the simplest model with vector dynamics, susceptible-infected-susceptible for hosts and uninfected-vector (SISUV). Finally, we compare the more complex susceptible-infected-recovered (SIR) and susceptible-infected-recovered for hosts and uninfected-vector (SIRUV) models and conclude that the models give basically the same information when we replace, in the SIR model, the human infectivity by a function of both human and mosquito infectivities.     

A mass spectrometric strategy for profiling glycoproteinoses, Pompe disease, and sialic acid storage diseases

Glycoproteinoses, Pompe disease, and sialic acid storage diseases are characterized by a massive accumulation of unprocessed oligosaccharides and/or glycoconjugates in urine. The identification of these glycocompounds is essential for a proper diagnosis. In this study, we investigated the potential of MALDI‐TOF‐MS to identify glycocompounds present in urine from patients with different inborn errors of glycan metabolism. Urinary glycocompounds were permethylated, and analyzed using GC‐MS and MALDI‐TOF‐MS. In order to confirm tentative assignments, a second aliquot of urine was purified on a C18 Sep‐Pak cartridge and glycocompounds were desalted on a column of nonporous graphitized carbon. The glycocompounds were then sequentially on‐plate digested using an array of exoglycosidases. A range of disease‐specific oligosaccharides as well as glycopeptides was identified for all oligosacchariduria models. In addition, free sialic acid accumulated in urine from a patient suffering from French‐type sialuria, has been detected by a GC‐MS approach, which could be applied to other sialic acid storage diseases. This procedure is simple, and can be performed in few simple steps in less than 24 h. This current method can be applied for newborn screening for other inherited metabolic diseases as well as for assessing treatments in clinical trials.