A network pharmacology approach to explore the mechanism of action of Yiqi Fumai lyophilized injection in the treatment of novel coronavirus disease

Background:Shengmai decoction,which has been included in the diagnosis and treatment of coronavirus disease 2019(COVID-19),is effective in the early treatment of patients with severe COVID-19.Yiqi Fumai lyophilized injection(YQFM)is a modern Chinese medicine preparation of the Shengmai decoction.The mechanism of its intervention at the molecular level in the severe stage of COVID-19 remains unclear.Therefore,it is necessary to investigate the mechanism of YQFM in the treatment of patients with severe COVID-19.Methods:The corresponding target genes of the main active ingredients in YQFM and COVID-19 were obtained by using multiple databases and literature retrieval.A protein-protein interaction network was constructed,and enrichment analysis of the target was performed using Cytoscape 3.8.1.Lastly,the docking of all the identified compounds with angiotensin-converting enzyme II was confirmed by applying molecular docking technology.Results:YQFM has anti-inflammatory effects on RAW267.4 macrophages.The main active compounds of YQFM are all effective anti-inflammatory agents,and these active compounds also show beneficial physiological functions,such as anti-oxidation,anti-bacterial,and anticancer activities.Gene Ontology analysis showed enrichment in the following pathways:lipopolysaccharides,interleukins,NF-kappa B,interleukin-2 and others,revealing that YQFM may play a role in the treatment of patients with severe COVID-19 through these pathways.Conclusion:YQFM has multicomponent and multitarget characteristics,and it could reduce lung injury by inhibiting inflammatory reactions,promoting antiviral activities,and regulating immunity,among other functions,to treat patients with severe COVID-19.

Effect of Chromium on CCT Diagrams of Novel Air-Cooled Bainite Steels Analyzed by Neural Network

The quantitative effects of chromium content on continuous cooling transformation （CCT） diagrams of novel air-cooled bainite steels were analyzed using artificial neural network models. The results showed that the chromium may retard the high and medium-temperature martensite transformation.

Network analysis and molecular docking of the mechanism of Shengmai decoction in treating patients with severe novel coronavirus pneumonia

Background:Studies have shown that,Shengmai injection(Shengmai decoction)which has been included in the diagnosis and treatment of coronavirus disease 2019(COVID-19),is effective in the early treatment of patients with severe COVID-19.However,the mechanism of its intervention in severe stage of COVID-19 at molecular level is still unclear.Therefore,it is necessary to further explore the mechanism of Shengmai decoction in the treatment of patients with severe COVID-19 based on network pharmacology.Methods:The Traditional Chinese Medicine Systems Pharmacology,BATMAN,UniProt databases and the published literatures which contain the reported compounds that have therapeutic effects on COVID-19 were used to screen out the active ingredients and targets of Shengmai decoction,and the“drug-active compound-target”network was constructed.The GeneCards database was used to screen out the targets of COVID-19.The protein-protein interaction network map was constructed by mapping two genes,and the network of active ingredients,targets and disease was constructed using Cytoscape software.Thereafter,Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the key targets were performed using the Metascape Site Maintenance website and David databases.The Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment of the mapping targets were analyzed.Results:The active component-target network contained 73 main compounds and 457 targets.The first five main active components(hydroquinone,guanosine,ophiopogon C,ophiopogon B,ophiopogon D)were obtained by topological analysis of 33 common targets.Using the Matthews correlation coefficient algorithm,the key targets included albumin,tumor necrosis factor,and cyclic adenosine response element binding.Compounds in Shengmai decoction were found to have good binding effect and strong interaction with caspase-8,caspase-3,apoptosis regulator Bcl-2,tumor necrosis factor,C-C motif chemokine 3,to inhibit the inflammatory response and improve lung injury.Additionally,31 biological processes were obtained by Gene Ontology enrichment,mainly related to lipopolysaccharide response and cytokine-mediated signal pathways,and 71 biological processes were obtained by Kyoto Encyclopedia of Genes and Genomes enrichment,mainly related to pulmonary tuberculosis,hepatitis B,and mitogen-activated protein kinase signal pathways.Conclusion:Shengmai decoction has multicomponent,multitarget and multichannel characteristics,which can provide an important theoretical basis to treat patients with severe COVID-19.

Quantitative analysis of Ni effect on CCT diagrams of novel air-cooled bainite steels using artificial neural network models

The quantitative effect of Ni content on continuous cooling transformation （CCT） diagrams of novel air-cooled bainite steels was analyzed using artificial neural network models. The results showed that Ni may retard the high- and medium-temperature transformation and martensite transformation. The results conform to the materials science theories.

Considerations on Novel Network Routing Mechanism

Routing is the cornerstone of network architecture, and a new routing mechanism is a requisite for constructing new network architecture. The current routing mechanism of the Internet layer is basically the single next-hop routing mechanism, which is the root of transmission congestion in the network. To solve this congestion problem, a fundamental measure is to change the route selection mode of current routing mechanism to allow parallel transmission over multiple routes. Currently, Border Gateway Protocol (BGP) is the only inter-domain routing protocol used in the Internet, but the routing system using BGP suffers scalability problem. To solve the scalability issue of the current inter-domain routing system, a new hierarchical routing system, i.e. Scalable Inter-Domain Routing Architecture (s-idra), is suggested. In addition to scalability, the current routing system is facing other challenges including security, Quality of Service (QoS), multicasting, mobility and dynamic network topology. Therefore, the research on routing protocols, especially the protocol for the new network architecture, is still a tough task and has a long way to go.

Novel Minimum Passive Element Realization of All-Pass Network Using A Modified Current Conveyor

1. IntroductionA large number of networks for realizing first and second order transfer functions using a currentconveyor have been reported in the literature. Especially, the networks that can offer highinput impedance attract attention, for high input impedance has the advantage that the networksmay be used in cascade without requiring impedance matching device. In the Higashimura and

Combined Linear Multi-Model for Reliable Route Recommender in Next Generation Network

Network analysis is a promisingfield in the area of network applications as different types of traffic grow enormously and exponentially.Reliable route prediction is a challenging task in the Large Scale Networks(LSN).Various non-self-learning and self-learning approaches have been adopted to predict reliable routing.Routing protocols decide how to send all the packets from source to the destination addresses across the network through their IP.In the current era,dynamic protocols are preferred as they network self-learning internally using an algorithm and may not entail being updated physically more than the static protocols.A novel method named Reliable Route Prediction Model(RRPM)is proposed tofind the best routes in the given hefty gage network to balance the load of the entire network to advance the network recital.The task is carried out in two phases.In thefirst phase,Network Embedding(NE)based node classification is carried out.The second phase involves the network analysis to predict the route of the LSN.The experiment is carried out for average data transmission and rerouting time is measured between RRPM and Routing Information Protocol(RIP)protocol models with before and after failure links.It was observed that average transmission time for RIP protocol has measured as 18.5 ms and RRPM protocol has measured as 18.2 ms.Hence the proposed RRPM model outperforms well than the traditional routefinding protocols such as RIP and Open Shortest Path First(OSPF).

全维可定义网络5.0新型网络架构

【目的】面对万物智能互联时代的新兴产业向网络技术提出的确定性、安全性、管控能力等方面的需求,尽力而为、形式单一的IP网络难以同时提供网络质量、安全性、管理能力和效率的性能保障。新的历史阶段急需一个新的网络体系架构,在充分考虑网络广泛互联的基础上,更深度地关注网络空间安全和产业应用对网络的精细要求。【方法】本文提出了全维可定义网络5.0新型网络架构,采用“以网络为中心、能力内生、全维定义”的全新网络架构设计理念,提出了一套覆盖数据面、控制面、管理面和内生安全体系的新型核心协议体系,利用泛在IP、人工智能等技术进行高效的寻址、路由规划、可信管理等。【结果】通过这种架构,网络5.0将网络中的存储、计算资源和多等级转发能力进行高效整合,从而更好地满足应用需求,并实现网络的内生安全、确定性传输、算网融合、差异化服务等功能,显著降低了网络应用的复杂性,提高了网络效率和应用质量。【结论】全维可定义网络5.0促进了泛在场景应用的发展,使得网络从一个单纯的连接工具转变为一个功能丰富、服务多元、安全可靠的平台,并已成功实践和验证在多个应用领域中,成为新型网络架构主流发展路径之一。

网络名师工作室的内涵与使命:引领教育适应新常态

以2020年春季为分水岭,教育领域正在从线下教学常态向混合教学新常态转型,为了探索转型后的教学样态,我国加强了基层教学组织的建设。网络名师工作室就是在网络学习空间与实体学习空间共同存在的背景下,为适应教学变革的现实需求,由具有独特的空间思维与空间应用专长的教学名师领衔所建立的、率先开展新质教育研究与实践的教师专业成长共同体。通过梳理当前的工作室建设过程中存在的窘境,并结合对江苏地区已经建立的网络名师工作室的调研分析,研究提出,网络名师工作室应当率先思考如何顺应混合教学的现实存在,如何形成基于数据的教学决策,如何组织适应个性的教学活动,并将信息化教学变革作为关键任务。工作室不同于一般的基层教学组织,需要更加强调事务的“实”、问题的“真”、过程的“活”,文章还就如何发挥工作室的三大效应进行了分析,并对未来发展进行了思考。

通算存智一体协同的未来网络模型

针对智能时代多样化多形态业务对未来网络按需、精准、高效服务的诉求,提出了一种通算存智一体协同的网络模型(3CI-CoNet)。首先以通信技术连接计算设备与存储设备,构建网内计算和网内存储的硬件底座,然后在底座上部署智能网络模型及算法,为网内业务构建智能的网络环境,同时链接与行业/应用相关的智能设备、平台及算法,为新兴应用提供智能的网络服务,保障各业务的有序高效运行。设计了3CI-CoNet的层次化功能架构,包含基础资源层、智能接入层、按需服务层和业务表达层,各层次间相辅相成,协同构建了智能的网络环境和网络服务。进一步,结合自动驾驶和智能制造中的典型场景,论述了3CI-CoNet及其功能架构、运营机制对多形态业务高效运行的支撑作用,阐述了3CI-CoNet在智能时代的推广和应用价值。以智能制造中多AGV按需调度业务场景为原型,通过将3CI-CoNet与其他网络模型相对比,定性定量论证了3CI-CoNet对提升业务效能具有积极作用。最后,总结了3CI-CoNet的未来发展趋势和面临的技术挑战。

基于相关性分析和生成对抗网络的电网缺失数据填补方法

城市电网新型电力系统中多元资源增多,数据采集难度加大,导致数据随机缺失率升高,难以满足精细化分析决策需求。为解决新型电力系统中配网量测数据在采集与传输过程中频发的缺失问题,文中提出一种基于波动互相关分析(fluctuation cross-correlation analysis,FCCA)算法和生成对抗网络(generative adversarial network,GAN)的电网缺失数据填补方法。首先,融合FCCA算法提出强相关性电网数据多维特征提取方法;其次,基于核主成分分析(kernel principal component analysis,KPCA)对多维特征数据集进行降维处理;最后,设计改进型GAN结构,融合电网数据多维特征对低维向量进行重构,实现缺失数据填补。算例采用真实电网数据进行算法验证,并在某城市电网试运行。结果表明,所提方法比传统数据填补方法具有更高填补精度。因此,在新型电力系统中量测数据连续缺失和缺失量较大的情况下,融合强相关性特征进行数据填补,对提升量测数据的完整性和可用性有明显优势。

NOVELL网络常见错误的检测与排除

论述用Ｃ语言编程实现的ＮＯＶＥＬＬ网络常见错误数据库的设计，及其常见错误检测与排除系统的主程序编程技术，并提供常见错误信息的利用与故障排除实例．

面向6G多维扩展的新型多址接入技术综述

随着移动通信技术的不断演进,第6代移动通信(6G)将实现从万物互联到万物智联的跨越,满足更高的数据需求和更广泛的应用场景。新型多址接入技术和多维扩展技术将在6G中协同发挥作用,为构建高效、智能、可靠的通信网络提供关键支持,满足未来通信的多重需求。该文旨在探讨新型多址接入技术在6G多维扩展通信网络中的应用潜力。首先,该文对比了传统多址接入技术与6G潜在新型多址接入技术,并重点阐述了非正交多址接入技术在提升频谱效率和系统容量方面的优势。然后,详细介绍了卫星通信、无人机(UAV)通信和智能反射面(IRS)等多维扩展技术在6G场景下的优势。进一步,讨论了新型多址技术与卫星通信、UAV以及IRS相结合的优势及协同应用。最后,探讨了基于新型多址接入技术的多维扩展网络中的关键技术挑战,包括大规模多入多出技术、太赫兹技术、通感算一体化、用户信息安全、不完美信道状态信息(CSI)估计,同时对新型编码技术、人工智能和机器学习等研究方向进行了展望。

NOVELL网融入因特网的应用实例

随着Internet网络技术的发展和企业内部基础网络设施的改善，许多原有运行在Novell局域网上基于DOS和数据库的信息管理系统，迫切需要能融入TCP／IP互联网络，以实现全局范围内的数据共享，并能保留原有系统功能和保护已有投资利益．本文介绍了一种解决此类问题的网络互联方案．实际的联网结果表明。

Novell网的安全策略研究

介绍了利用 Netware操作系统自身的功能来检查 Novell的安全漏洞 ,讨论了网络病毒的防范措施对超级用户的管理和利用超级用户进行网络的安全管理等维护措施。

Novell局域网入网登录界面及其管理程序的设计

针对 Novell局域网入网调用应用程序的步骤较复杂 ,Netware提供设计的菜单界面为西文 ,安全性不甚高的情况 ,设计了“登录程序”及“登录管理系统”两个软件。该软件具有入网登录方便。

基于CGAN增强的新冠病毒拉曼光谱深度学习分类研究

新型冠状病毒的出现给全球经济、公共安全等方面带来严重损失。如今新型冠状病毒仍然在全球肆虐,加强病毒的检测和诊断是一项急需解决的工作,快速且准确地诊断新冠病毒对疫情防控尤为重要。随着技术的发展,深度学习在检测识别方面有了许多突破性进展,吸引着研究者的广泛关注。然而深度学习需要大量数据进行模型训练,而新冠病毒的拉曼光谱采集过程受到器件和环境等诸多问题的限制,导致获取大批量的数据非常困难。有限的训练数据会阻碍深度学习模型的训练,导致深度学习模型训练受阻,精度有限,以至于深度学习模型在真正的检测中表现不佳。为解决这一问题,该研究引入条件生成对抗网络,自动提取拉曼光谱数据特征,通过学习生成新的光谱来完成新冠病毒的拉曼光谱数据扩充工作。这些方法能有效增加训练集数量从而提高模型准确性。利用数据增强后的拉曼光谱数据和深度神经网络以及传统的机器学习方法逻辑回归、决策树、随机森林、支持向量机、KNN算法,完成新冠病毒的诊断。实验结果表明,深度神经网络对是否感染新型冠状病毒的预测准确率达到98%,高于传统机器学习算法,证明了深度学习模型在新冠病毒拉曼光谱检测中的优越性。该研究还对比了增强前后的数据集在不同模型中的表现,证明了数据增强的作用。与传统的检测方法相比,该方法具有无损、快速、准确等特点,为生物医学检测新冠病毒提供了一种新的思路。该方法可以为快速准确检测新冠病毒提供辅助,所采用的方法不仅可以应用于新冠病毒检测,还可以推广到其他疾病的诊断中,具有一定的实际应用价值。

Novell 网络环境下多用户数据库访问冲突的解决方法

使用登记文件来记录Ｎｏｖｅｌ网络文件服务器上共享数据库的使用情况，解决多用户数据库的访问冲突问题．以Ｎｏｖｅｌ网络ＦｏｘＰｒｏｆｏｒＤｏｓ为例，详细说明了这种方法的实现技术．

网络小说故事空间形态的文学生态性

相对于传统小说而言,网络小说是一种空间性文本,主要建构了拟现实态空间和超现实态空间。拟现实态空间主要指网络小说中以乡村和城市为主的空间形态,其中又分为内向型小空间和外向型跨域大空间两种形态。而超现实态空间主要表现为网络玄幻小说的“阶梯式空间”、网络盗墓小说的“积木式空间”和网络穿越小说(网络同人小说)的“缺口式空间”。各类空间形态构成了不同的文本形式和审美特征。网络小说的空间形态具有文学生态性,一是内在性地推动了网络类型小说的发展,二是体现为文学的一种空间现代性面孔。深入探究网络小说的故事空间形态,会发现一个不一样的文学大陆。

中国网络侦探小说的写作困境与出路

中国传统通俗文学凭借网络实现了整体繁荣,商业类型写作推动了网络叙事的发展和文化影响力的提升,但网络侦探小说却陷入了写作困境。不仅在主流文学网站中几乎看不到网络侦探小说的身影,同时网络侦探小说也没有代表性的作家作品,且很少入选各类权威榜单。中国网络侦探小说陷入了发展困境,这种局面的产生是由以下两方面的原因决定的:一是,中国传统侦探小说写作本身的“先天不足”,到了网络时代并没有太大的改观;二是,网络侦探小说与现有的“爽文”写作机制“水土不服”,并不是所有的类型都能够以超长篇的“小白文”形式存在。学界有必要也有责任为网络侦探小说的发展寻找出路,与当下获得巨大成功的“起点模式”相比,以大赛、版权开发为核心的“豆瓣模式”或许更有利于推动中国网络侦探小说的发展。