Study on the Medication Rules of Traditional Chinese Medicine Prescriptions for the Treatment of New Crown Pneumonia Based on Data Mining Technology

[Objectives]This study was conducted to analyze the medication rules of clinical prescriptions of traditional Chinese medicine decoction pieces for the treatment of novel coronavirus pneumonia(COVID-19)during the epidemic in multiple regions based on data mining technology,so as to provide a reference for the treatment of COVID-19 with traditional Chinese medicine.[Methods]The traditional Chinese medicine prescriptions used since the outbreak of COVID-19 in Hubei Province during the fight against the epidemic from February 25,2020 to February 14,2022,the traditional Chinese medicine prescriptions used by Guizhou traditional Chinese medicine expert team aiding Hubei Province,the traditional Chinese medicine prescriptions for rehabilitation and conditioning of patients in Ezhou of Hubei Province after discharge,the traditional Chinese medicine prescriptions for the prevention and treatment of COVID-19 in Guizhou Province,and the traditional Chinese medicine prescriptions for the treatment of COVID-19 collected from the end of 2019 to the present from the Chinese database of CNKI were collected as the data of this study.Excel was used to establish a database and enter it into the TCM inheritance calculation platform V3.5,and the association rules and k-means clustering algorithm were used to analyze the frequency of herbal medicines in prescriptions during the treatment of COVID-19,the frequency of four natures,five flavors,meridian distribution,and drug combinations.[Results]A total of 1859 COVID-19 patients treated with traditional Chinese medicine were included,and the proportion of males was higher than that of females,and middle-aged and elderly people were the most common group.A total of 2170 prescriptions of traditional Chinese medicine were included,involving a total of 383 traditional Chinese medicines.High-frequency medicines included poria,Radix Bupleuri,Radix Scutellariae,Herba Pogostemonis,Fructus Forsythiae,Flos Loniceraeetc.The four natures were mainly concentrated in cold,warm and neutral,and the five flavors were mainly concentrated in bitter,pungent and sweet.The herbal medicines were mainly attributed to the lungs and stomach meridians,and were mainly of heat-clearing,exterior syndrome-relieving and diuresis-promoting and damp-clearing types.A total of 24 high-frequency herbal combinations and 35 association rule were excavated,and 3 types of formulas were obtained by cluster analysis.[Conclusions]The analysis results and medicine combinations obtained in the formulas are consistent with the traditional Chinese medicine treatment theory of COVID-19 caused by wind-heat filth accompanied with damp and toxin.

A Novel Incremental Mining Algorithm of Frequent Patterns for Web Usage Mining

Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.

Design of an Intelligent Usage Parameter Control in ATM Networks

This paper presents the principle of the fuzzy associate memory controlled leaky bucket (FAMLB) and several concepts for Usage Parameter Control (UPC) in ATM networks. The multiplex weight and random fuzzy rules adjustment method in the system architecture are introduced. The conclusions show that the FAMLB is a better dynamic method of UPC than the traditional ones.

Research on Herb Pairs of Classical Formulae of ZHANG ZhongJing Using Big Data Technology

Objective To analyze various herbal combinations in Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》),seeking to identify fundamental rules dictating the selection of herbal combinations through probability models and big data technology.Methods A total of 252 formulae were collected from Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》)by ZHANG Zhong-Jing.Formulae were then preprocessed with all herb names standardized.The concepts of candidate herb pair and candidate herb pair probability were proposed to analyze the rules of combinations in classical formulae based on probability statistics.MapReduce parallel computing framework of distributed big data technology was adopted to analyze large data samples combined with inverted index algorithm.Results The results showed that the core herbs were Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Cinnamomi Ramulus(Gui Zhi,桂枝),Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Jujubae Fructus(Da Zao,大枣),Paeoniae Radix Alba(Bai Shao,白芍),etc.43 high-frequency pairs co-occurring 10 times or above were extracted,and 35 of these combinations were recognized as traditional herb pairs,such as Cinnamomi Ramulus(Gui Zhi,桂枝)-Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Jujubae Fructus(Da Zao,大枣),and Cinnamomi Ramulus(Gui Zhi,桂枝)-Ginseng Radix Et Rhizoma(Ren Shen,人参).The other 8 pairs of combinations,such as Paeoniae Radix Alba(Bai Shao,白芍)-Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Paeoniae Radix Alba(Bai Shao,白芍)-Jujubae Fructus(Da Zao,大枣),and Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Ginseng Radix Et Rhizoma(Ren Shen,人参),were not defined traditionally,but in connection with commonly used herbs.Classical formulae took the core herbs as principles,focusing on tonifying deficiency,strengthening the spleen and the stomach,strengthening the healthy Qi,and eliminating pathogenic factors.The compatibility pattern of properties involved was mainly acrid and sweet,which reflected the compatibility laws of benefiting Qi and tonifying Yang,replenishing Qi and nourishing blood,etc.Conclusions The research of classical formulae provides common understanding of some basic rules that have been adopted to tackle common illnesses/diseases using herbal medicine.The results help to reinforce theoretical understanding and development of traditional Chinese medicine(TCM),and revealing the hidden rules of combination in TCM data.Analyzing wider data samples of various herbal combinations through computation and big data technology can further optimize the use of TCM.

Employ Game Teaching Methodinthe Primary School English Classroom

on the basis of linguistics, psychology and other related theory, we should carry outgame teaching method to make students learn easily and happily because of the lack of interestand other problems in some parts of our country.

A Data Mining-Based Study on Medication Rules of Chinese Herbs to Treat Heart Failure with Preserved Ejection Fraction

Objective:To summarize the medication rules of Chinese herbs to treat heart failure with preserved ejection fraction(HFPEF)based on data mining and to provide references for clinical utilization.Methods:The China National Knowledge Infrastructure(CNKI),Wanfang database(Wanfang),VIP database(VIP),Chinese Biomedical Literature(CBM),PubMed,Embase,and Cochrane Library databases were searched from inception to October 2021 to identify relevant literature on treating HFPEF with Chinese herbs.Microsoft Excel 2019 was used to set up a database,and then,association rule analysis and hierarchical cluster analysis were performed by using apriori algorithm and hclust function respectively in R-Studio(Version 4.0.3).Results:A total of 182 qualified papers were included,involving a total of 92 prescriptions,130 Chinese herbs,and 872 individual herbs prescribed,with an average of 9.5 herbs per prescription.The six most frequently prescribed herbs were Astragali Radix(Huangqi),Salviae Miltiorrhizae Radix Et Rhizoma(Danshen),Poria(Fuling),Glycyrrhizae Radix Et Rhizoma(Gancao),Cinnamomi Ramulus(Guizhi),and Ginseng Radix Et Rhizoma(Renshen).There were 35 herbs used more than 5 times,involving 11 efficacy categories.The top three categories were deficiency-tonifying herbs,blood-activating and stasis-removing herbs,and dampnessdraining diuretic herbs.The most commonly used herbs were mainly warm and sweet.The primary meridian tropisms were Lung Meridian,Heart Meridian and Spleen Meridian.Association rule analysis yielded 26 association rules,such as Astragali Radix(Huangqi)&Salviae Miltiorrhizae Radix Et Rhizoma(Danshen),Poria(Fuling),Cinnamomi Ramulus(Guizhi)&Atractylodis Macrocephalae Rhizoma(Baizhu).Hierarchical cluster analysis yielded four herb classes,and their functions were mainly qi-replenishing and yang-warming,bloodactivating and diuresis-inducing.Conclusions:HFPEF is the syndrome of root vacuity and tip repletion,and its core pathogenesis is"deficiency","stasis",and"wafer",with"deficiency"being the most principal,which is closely related to Xin(heart),Fei(Lung),and Pi(Spleen).The treatment of this disease occurs by improving qi,warming yang,activating blood and inducing diuresis.Astragali Radix(Huangqi)with Salviae Miltiorrhizae Radix Et Rhizoma(Danshen)is the basic combination of herbs applied.

Mining Compatibility Rules from Irregular Chinese Traditional Medicine Database by Apriori Agorithm

This paper aims to mine the knowledge and rules on compatibility of drugs from the prescriptions for curing arrhythmia in the Chinese traditional medicine database by Apriori algorithm. For data preparation, 1 113 prescriptions for arrhythmia, including 535 herbs （ totally 10884 counts of herbs） were collected into the database. The prescription data were preprocessed through redundancy reduction, normalized storage, and knowledge induction according to the pretreatment demands of data mining. Then the Apriori algorithm was used to analyze the data and form the related technical rules and treatment procedures. The experimental result of compatibility of drugs for curing arrhythmia from the Chinese traditional medicine database shows that the prescription compatibility obtained by Apriori algorithm generally accords with the basic law of traditional Chinese medicine for arrhythmia. Some special compatibilities unreported were also discovered in the experiment, which may be used as the basis for developing new prescriptions for arrhythmia.

TO WHAT EXTENT IS IT NECESSARY TO TEACH EXPLICIT RULES OF USAGE TO FOREIGN LANGUAGE LEARNERS?

IntroductionNowadays English teachers feel that teaching grammar is a tough problem to solve.Languageteaching is no longer regarded simply as imparting knowledge about the target language,but teachinglearners how to actually use the target language in real-life communication.Developments in modernlinguistic and teaching methodologies have challenged traditional teaching perspectives,however,inChina English teaching is still generally conducted in the traditional way.This is especially so forgrammar teaching.Grammar is so much the main concern in class that it is explained explicitly,andthe language materials and samples are arranged to highlight it.English is taught by giving studentsdetailed explanations of the grammatical points in isolation.Teachers make a careful analysis of thetexts to make sure that students have understood every single word of the text they are learning.Somepeople might think that these students should learn English very well,because they are learningEnglish so systematically,but this is not the case at all.

基于数据挖掘探究补肾益髓法治疗阿尔茨海默病的用药规律

目的运用数据挖掘分析方法总结归纳补肾益髓类中药复方治疗阿尔茨海默病(alzheimer′s disease,AD)的核心药物及用药规律。方法将自数据库建立起至2022年4月于中文数据库中国知网、万方、维普,中国临床试验注册中心,英文数据库PubMed、Web of science中检索到的补肾益髓法治疗AD的临床研究文献作为数据来源,利用SPSS modeler 18.0和SPSS Statistic 25.0软件对纳入文献中记载的复方药物进行频次统计、关联分析、系统聚类分析和因子分析;通过Cytoscape 3.8.0构建中药核心复杂网络,并对网络中的中药进行拓扑分析。结果经筛选,得到69篇文献共计70首处方,108味中药;单味药物属熟地黄应用次数最高;补虚药、活血化瘀药、安神药应用最为广泛;网络拓扑学筛选得到包括熟地黄、石菖蒲、枸杞子、远志在内的12味核心中药;关联分析得到常用药物关联规则37条,最为常见的药对为“熟地黄-枸杞子”“石菖蒲-远志”等,使用频次最高的药物组合为“熟地黄-石菖蒲-远志”;系统聚类分析在欧式平方距离为15时可归纳为3个潜在聚类方,因子分析共提取4个公因子,其药物组成体现了地黄饮子、六味地黄丸、左归丸等补肾经方的药物配伍规律。结论补肾益髓法治疗AD以补肾填精益髓为主体,辅以活血祛瘀、宁心安神、豁痰开窍;针对AD病机治疗标本兼顾,体现了中医药整体观念、辨证施治的诊疗特点。

高明利教授治疗类风湿关节炎用药规律总结及机制分析

目的通过对门诊处方的收集整理,分析高明利教授治疗类风湿关节炎的用药规律、核心药物及作用机制。方法收集2021年7月—2022年12月,类风湿关节炎患者首次就诊于辽宁中医药大学附属医院,高明利教授专家门诊的首诊处方,采用数据挖掘联合网络药理学及分子对接的方法,运用《中医传承计算平台》对药物的频次、性味、归经和功效进行分类统计,对所有处方进行K-means聚类分析;运用R语言进行Apriori关联规则分析得到核心药物;通过TCMSP数据库查找核心药物活性成分及靶点,并在DisGeNet数据库中预测治疗靶点;对预测的治疗靶点进行GO、KEGG富集分析,构建治疗靶点的蛋白互作网络并进行重要治疗靶点的筛选;以重要治疗靶点作为蛋白受体,核心药物活性成分作为配体进行分子对接验证。结果研究共纳入中药处方169首,涉及中药216味,高频用药为穿山龙、甘草、延胡索、白芍、桂枝、川芎、黄芪、透骨草等;药物四气以温性为主,兼有寒性等;五味以甘味为主,兼有苦味等;归经以足厥阴肝经为首;功效以补虚为主,兼活血化瘀、清热、祛风湿等;聚类分析得到以穿山龙、延胡索、透骨草、川芎、桂枝为首的处方3类;关联规则分析根据置信度、支持度、提升度筛选出核心药物为透骨草、延胡索、穿山龙;药物有效活性成分有槲皮素、山柰酚等,药物预测治疗靶点118个;主要富集在TNF、IL17、HIF-1等炎性信号通路上;核心治疗靶点为TNF、IL6、IL1B、CCL2、IL10等。结论高明利教授门诊治疗类风湿关节炎的治疗原则以“通痹扶正”为主,以镇痛通络、益气扶正为主要的治疗方法,核心药物为穿山龙、延胡索、透骨草,其中有效成分为槲皮素、山柰酚等,能够作用于以TNF、IL6、IL1B、CCL2、IL10等为代表的治疗靶点通过TNF、IL-17等炎性信号通路发挥治疗效果。

基于数据挖掘技术探究中药复方治疗肝纤维化的用药规律

目的:运用数据挖掘技术研究中药复方治疗肝纤维化的用药规律,以期为肝纤维化临床治疗提供指导和参考。方法:以肝纤维化为主题,收集、整理中国知网、万方数据库、维普中文科技期刊数据库收录的文献为本研究数据来源,建立数据库,采用Excel 2019、SPSS Statistics 22.0和IBM SPSS Modeler 18.0软件进行频次分析、关联规则分析、因子分析和系统聚类分析,对符合本研究纳入标准的复方进行数据挖掘。结果:在符合纳入标准的134个中药复方中,涉及159味中药,总用药频次为1437次。使用频次≥10次的中药有31味,最常用的单味中药是丹参;四气以寒、温为主,五味以苦、甘、辛味居多,药物归经多归于肝经、脾经,用药频次分析提示排名前3位的药物类别为补虚药、活血化瘀药、清热药。关联规则分析表明,关联强度最高的药对组合有8组,因子分析提取11个公因子,系统聚类分析归为6大类,复杂网络分析得出核心处方为丹参、赤芍、鳖甲、黄芪、白术、白芍、柴胡、当归。结论:中医药治疗肝纤维化的基本治法为活血化瘀、理气扶正、清热利湿,核心处方对中医药治疗肝纤维化遣方用药具有借鉴意义。

基于数据挖掘探讨中药防治黄曲霉菌感染的用药规律

本研究基于网络药理学等数据挖掘方法探究中药干预黄曲霉菌感染的用药规律。通过GeneCards数据库获得并筛选黄曲霉菌感染潜在靶点,同时在中药系统药理学数据库与分析平台(TCMSP)筛选口服生物利用度≥30%、类药性≥0.18的候选化合物及中药,随后构建关键靶点-候选化合物-候选中药网络,并通过检索各候选中药的性、味、归经等相关信息,分析出相关用药规律。结果表明:利用数据库共筛选出69个黄曲霉菌感染相关靶点,收集到54个候选化合物,筛选到275味中药。用药频次统计结果显示,防治黄曲霉菌感染的候选中药中,苦味、寒性居多,主要归肝、肺二经。本文系统地分析了中药干预黄曲霉菌感染的小分子物质基础,归纳了一般用药规律,可为临床治疗黄曲霉菌感染等相关疾病的新药研发及中药治疗提供一定的参考及思路。

川芎常用药对配伍应用浅析

川芎作为我国传统中药,具有悠久的应用历史,在临床中具有广泛的治疗作用和重要的药用价值。药对配伍是中医遣方用药的一大特色。通过归纳川芎药对在古医籍中的应用情况、应用规律及配伍理论,整理并总结了川芎几种常见典型药对配伍形式及其作用,如川芎与羌活祛风除湿通络,川芎与白芷祛风活血止痛,川芎与细辛行气散寒,川芎与赤芍活血祛瘀,川芎与当归补中寓通,川芎与黄芪益气活血,川芎与天麻行气通络,川芎与丹参活血通经,川芎与香附行气解郁。主要用于外感证、气滞证、血瘀证、血虚证等证型,治疗头痛、痹证、中风等内科疾病,痛经、月经不调、胎漏胎动不安等妇科疾病,疮痈肿毒等外科疾病。为临床上更好地应用川芎药对进行治疗提供参考。

《神农本草经》辛以止咳药在经方中的运用探析

《神农本草经》中辛味且明确具有止咳作用的药物有12味,在《伤寒杂病论》中用到8味。通过分析这12种药物的功效及配伍成的13首止咳逆经方的应用,并结合《黄帝内经》五味用药理论,总结出辛以止咳的机制及组方用药特点:1)辛以止咳药在“主咳逆”的基础上,尚以主温中、主风寒、主化湿及特殊功效,如款冬花“主喉痹”、桂枝“主补中益气”、芫花“主下水”达到止咳逆;2)辛以止咳配伍规律有辛散酸收,基础药对为干姜细辛-五味子,根据不同病因有所加减,如生姜-细辛-五味子、干姜-细辛-五味子-半夏和干姜-五味子;辛甘发散,药对为生姜-甘草或干姜-甘草;辛散苦降,药对为款冬花-紫菀、桂枝-麻黄、半夏-芍药或附子-芍药;3)辛以润之贯穿于辛以止咳的全过程,在此基础上当外邪袭表,辛以散之;阳虚津凝时,辛以温之;饮邪不化时,辛以和之。

制约“们”字用法的语法规则和语用原则

现代汉语中“们”的用法和功能一直是汉语数范畴研究中的热点问题。学界多有讨论,却一直悬而未决。我们认为只有准确地把问题归档至它们应在的位置,才能为从根本上解决这些问题创造条件。本文提出“们”的用法是刚性的语法规则和柔性的语用原则共同作用的结果。前者决定了必用或者必不用“们”的语法条件,而后者则定义了可用可不用时使用“们”的语用环境。原本可不用却使用“们”主要是受语用因素的驱动,目的在于凸显和强化名词性成分的复数义。这种刚柔并济的处理方案不仅可以消除有关此问题的讨论中经常不得不使用“倾向”等等模棱两可的不理想概括方式,为相关的语言现象提供更加彻底的分析实践和更为深刻的理论解释,同时也为语言现象的全面解释提供了可行的分析框架。

经方药对在子宫内膜异位症治疗中的应用及规律探析

目的挖掘经方药对在子宫内膜异位症(EMs)治疗中的应用及规律。方法收集2018年1月1日至2022年12月31日在北京中医药大学第三附属医院妇科就诊的EMs患者的结构化电子病历信息,纳入使用含经方药对处方干预的数据资料,构建数据库。梳理经方中药,并统计频次、药性、药味、归经及功效,明确高频中药。通过IBM SPSS Modeler 18.0对EMs用药进行Apriori关联规则分析。采用IBM SPSS Statistics 26对高频药物进行聚类分析和因子分析。结果共纳入EMs患者376例,896张中医处方,涉及292味中药,总使用频次14703次,其中经方中药79味,累计频次为7571次,占51.49%。获得高频中药30味,以活血化瘀药、补虚药、清热药、理气药居多,包括麦芽、牡丹皮、当归、熟地黄等,药性以温、寒、平为主,药味以苦、辛、甘为多,归经主入肝、脾经。共产生2441条有效的关联规则,其中对药81条。聚类分析将高频中药分为6类,因子分析产生6个公因子。最终预测形成一个潜在处方,由20味中药组成,包括肾气丸、温经汤、当归芍药散和薏苡附子败酱散4首经方的主要药味。结论中医药治疗EMs以补虚化瘀为主,常选用活血化瘀、温阳补虚、理气化痰类中药,体现了EMs阳虚瘀结的病理特点。经方药对在EMs治疗中较常应用,结合临床也产生了一些新的药对,并预测形成1个用治EMs的可能处方,为中医药治疗EMs遣方用药提供了依据和参考。

张士卿教授治疗小儿多动症的用药规律

目的:基于数据挖掘技术分析全国名中医张士卿教授治疗小儿多动症(attention deficit hyperactivity disorder,ADHD)的用药规律。方法:收集2020年11月至2021年4月张士卿在甘肃中医药大学附属医院门诊治疗ADHD的处方。采用Excel 2016建立中药数据库并进行中药频次、四气五味及归经频次统计,对频次≥20次的中药四气五味及归经进行可视化分析;采用IBM SPSS Modeler 18.0软件中的Apriori算法对频次≥20次的中药进行关联规则分析;应用SPSS 25.0软件进行聚类分析和因子分析。结果:共筛选出89份处方,149味中药,其中使用频次≥20次的药物有33味,以赤芍、牡蛎、蝉蜕、白芍、龙骨、炙甘草、黄芩、法半夏、钩藤、党参出现频次较高;药物分类以疏风清热药、熄风止痉药多见;四气以寒、温为主,五味以辛、苦、甘居多,归经以肝、肺和胃经多见。关联规则分析显示置信度、支持度均最高的为龙骨→牡蛎。聚类分析共得到7类组合;因子分析共提取初始特征值>1的11个公因子。结论:全国名中医张士卿教授治疗ADHD以柴胡加龙骨牡蛎汤加减,以清离定巽法为主,随证配伍疏风清热药、熄风止痉药、补血药、清热化痰药等药物。

基于药对探讨中药复方配伍规律的思考

复方的配伍规律是中药方剂理论的核心问题。近年来,药对配伍研究已成为继拆方试验和正交试验之后方剂配伍规律研究的又一重点取向。从复方中特定两味药的配伍形式——药对出发,阐述药对理论的历史渊源、药对的组成方式(包括四气配对、五味配对、归经配对、引经配对、毒性配对、升降浮沉配对、七情相合配对等),以及药对在复方配伍规律研究中的作用。通过以上研究表明,从药效物质基础、作用机制、临床配伍应用等方面对药对的配伍展开系统而深入的研究,不仅对于理解药对配伍理论具有重要意义,而且对于复方配伍规律的研究具有重要价值。

现代汉语虚词用法知识库建设综述

现代汉语虚词用法繁杂多样,虚词用法的研究对汉语语义理解及语法分析起着非常重要地作用。该文在分析虚词及词汇知识库研究现状的基础上,对三位一体的现代汉语虚词用法知识库中虚词用法词典、虚词用法规则库和虚词用法标注语料库的建设过程进行了详细描述,对虚词知识库现存的问题进行了分析。利用已经构建的现代汉语虚词知识库,对虚词用法自动识别进行了研究,并对现代汉语虚词知识库的应用进行了初步的探讨。