The Foundation of the Classification and Diagnosis Standards for the Constitulions of TCM

The Traditional Chinese Medicine (TCM) ConstitutionClassification and the Constitutions in Chinese MedicineQuestionnaire (CCMQ) are based on nearly 30 years' researchon physique structure,physiological functions,psychologicalcharacteristics and reactive states.Epidemiology,immunology,molecular biology,genetics,mathematical statistics and multicrosseddisciplines were applied and many arguments were putforward by TCM experts,epidemiological specialists and constitutionexperts to establish the standardization tool Classificationand Diagnosis Standards for the Constitutions of TCM.At thesame time,basic research on constitution classification wasconducted to supply the objective basis of the classification standards.The Standards were used to conduct 21,948 cases ofepidemiological investigation on a national scale and showedgreat applicability,practicability and maneuverability.TheStandards were applied abroad in the medical services of TCMand were also an effective tool in the development of preventivetreatment of diseases by TCM.

A Review on the Classification and Grading Criteria of Road Transport Natural Disasters

This review summarizes and analyzes the basic information of various types of road transport natural disaster emergencies,refers to various types of road transport emergency plans,and combines the actual needs of road transport emergency rescue with national emergency related laws.It also proposes the classification criteria and grading standard for the emergencies of road transport natural disasters based on the classification and grading standard of the regulations,which provide a basis to take reasonable and effective disposal measures in the emergency response of road transport emergencies under natural disaster conditions.

Response of silicate chemical composition variation on thermal metamorphism of ordinary chondrites and classification of petrologic types:the case of L chondrites from Grove Mountains,Antarctica

Analysis of the thermal metamorphism of the ordinary chondrites is a key premise for gaining insights into the accretion and heating of rocky bodies in the early solar system.Such an analysis also represents an essential condition for constraining the early thermal and evolutionary histories of asteroids and terrestrial planets.Classifying ordinary chondrites into petrologic type(type 3–6)is the criterion for studying the thermal metamorphism of their parent bodies.However,the boundary between the unequilibrated(type 3)and equilibrated(type 4–6)chondrites is ambiguous at present,thus,limiting the understanding of their thermal metamorphism.In this study,the petrology,mineralogy and chemical composition of a set of seven ordinary chondrites with different degrees of thermal metamorphism collected from Grove Mountains(Antarctica)have been studied.The results demonstrated that these chondrite samples were L3.7,L3.8,L3.9,L3.9/4,L4,L5 and L6 type meteorites,with optimal correlations of Si,Mg,Fe,Mn and Ca with equilibrium degree of the olivine and low-calcium pyroxene and petrologic type.In this respect,the multi-parameter classification standard PMD(SiO2)-PMD(MgO)-PMD(MnO)-PMD(CaO)based on the percent mean deviation(PMD)of the chemical compositions of the olivine and low-calcium pyroxene was proposed to distinguish between the unequilibrated and equilibrated meteorites.The proposed standard exhibited high“resolution”in terms of classification,thus,also deepening the understanding of the effect of the silicate mineral composition in the thermal metamorphism of chondrites.Highlights The chemical groups and petrologic types of the selected seven Antarctic chondrites were L3.7,L3.8,L3.9,L3.9/4,L4,L5 and L6.A new method for petrologic type classification is proposed to distinguish the unequilibrated and equilibrated chondrites.The above developed multi-parameter system exhibited high“resolution”in terms of classification.

Statistical Characteristics of Raindrop Size Distribution in the Tibetan Plateau and Southern China

The characteristics of raindrop size distribution （DSD） over the Tibetan Plateau and southern China are studied in this paper, using the DSD data from April to August 2014 collected by HSC-PS32 disdrometers in Nagqu and Yangjiang, com- prising a total of 9430 and 63661-rain raindrop spectra, respectively. The raindrop spectra, characteristics of parameter variations with rainfall rate, and the relationships between reflectivity factor （Z） and rainfall rate （R） are analyzed, as well as their DSD changes with precipitation type and rainfall rate. The results show that the average raindrop spectra appear to be one-peak curves, the number concentration for larger drops increase significantly with rainfall rate, and its value over southern China is much higher, especially in convective rain larger drops, especially for convective rain in southern China. Standardized Gamma distributions better describe DSD for All three Gamma parameters for stratiform precipitation over the Tibetan Plateau are much higher, while its shape parameter （,u） and mass-weighted mean diameter （Dm）, for convective precipitation, are less. In terms of parameter variation with rainfall rate, the normalized intercept parameter （Nw） over the Tibetan Plateau for stratiform rain increases with rainfall rate, which is opposite to the situation in convective rain. The/1 over the Tibetan Plateau for stratiform and convective precipitation types decreases with an increase in rainfall rate, which is opposite to the case for Dm variation. In Z-R relationships, like ＂Z = ARb＇＇, the coefficient A over the Tibetan Plateau is smaller, while its b is higher, when the rain type transfers from stratiform to convective ones. Furthermore, with an increase in rainfall rate, parameters A and b over southern China increase gradually, while A over the Tibetan Plateau decreases sub- stantially, which differs from the findings of previous studies. In terms of geographic location and climate over the Tibetan Plateau and southern China, the precipitation in the pre-flood seasons is dominated by strong convective rain, while weak convective rain occurs frequently in northern Tibet with lower humidity and higher altitude.

Automatic Classification of Swedish Metadata Using Dewey Decimal Classification:A Comparison of Approaches

Purpose:With more and more digital collections of various information resources becoming available,also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization systems.While the ultimate purpose is to understand the value of automatically produced Dewey Decimal Classification(DDC)classes for Swedish digital collections,the paper aims to evaluate the performance of six machine learning algorithms as well as a string-matching algorithm based on characteristics of DDC.Design/methodology/approach:State-of-the-art machine learning algorithms require at least 1,000 training examples per class.The complete data set at the time of research involved 143,838 records which had to be reduced to top three hierarchical levels of DDC in order to provide sufficient training data(totaling 802 classes in the training and testing sample,out of 14,413 classes at all levels).Findings:Evaluation shows that Support Vector Machine with linear kernel outperforms other machine learning algorithms as well as the string-matching algorithm on average;the string-matching algorithm outperforms machine learning for specific classes when characteristics of DDC are most suitable for the task.Word embeddings combined with different types of neural networks(simple linear network,standard neural network,1 D convolutional neural network,and recurrent neural network)produced worse results than Support Vector Machine,but reach close results,with the benefit of a smaller representation size.Impact of features in machine learning shows that using keywords or combining titles and keywords gives better results than using only titles as input.Stemming only marginally improves the results.Removed stop-words reduced accuracy in most cases,while removing less frequent words increased it marginally.The greatest impact is produced by the number of training examples:81.90%accuracy on the training set is achieved when at least 1,000 records per class are available in the training set,and 66.13%when too few records(often less than A Comparison of Approaches100 per class)on which to train are available—and these hold only for top 3 hierarchical levels(803 instead of 14,413 classes).Research limitations:Having to reduce the number of hierarchical levels to top three levels of DDC because of the lack of training data for all classes,skews the results so that they work in experimental conditions but barely for end users in operational retrieval systems.Practical implications:In conclusion,for operative information retrieval systems applying purely automatic DDC does not work,either using machine learning(because of the lack of training data for the large number of DDC classes)or using string-matching algorithm(because DDC characteristics perform well for automatic classification only in a small number of classes).Over time,more training examples may become available,and DDC may be enriched with synonyms in order to enhance accuracy of automatic classification which may also benefit information retrieval performance based on DDC.In order for quality information services to reach the objective of highest possible precision and recall,automatic classification should never be implemented on its own;instead,machine-aided indexing that combines the efficiency of automatic suggestions with quality of human decisions at the final stage should be the way for the future.Originality/value:The study explored machine learning on a large classification system of over 14,000 classes which is used in operational information retrieval systems.Due to lack of sufficient training data across the entire set of classes,an approach complementing machine learning,that of string matching,was applied.This combination should be explored further since it provides the potential for real-life applications with large target classification systems.

中国大健康产业统计分类与产业规模再测算

由于产业间深度融合,新业态、新模式持续涌现,健康产业的边界不断拓展,原有的健康产业统计分类已不能满足大健康产业的统计需要,官方统计也未测算出健康产业增加值,无法全面、及时反映大健康产业的发展状况。因此,文章首先在健康产业基础上从供给和需求角度界定并拓展大健康产业的内涵及外延;其次,在《健康产业统计分类(2019)》的基础上,基于国民经济核算理论,引入“大健康总产品”概念,聚焦“全生命周期”和“全人群”两个着力点,从全产业链产品供给及全口径人群健康需求两个视角探讨大健康产业统计分类标准,补充和完善大健康产业统计分类;最后,依据现有的投入产出表、经济普查及统计年鉴数据,计算各行业的大健康分离系数,据此推算我国大健康产业及健康服务业增加值。结果显示:2018年我国大健康产业增加值为10.27万亿元,其中健康服务业增加值为7.04万亿元,预测2020年、2030年健康服务业增加值分别为8.46万亿元、21.27万亿元,基本符合《“健康中国2030”规划纲要》对健康服务业发展规模的预期。

NIM5驾驭氢钟守时能力分析

时间频率量值源头的独立自主是建设我国综合PNT体系的重要基础。为进一步评估基于我国国家秒长基准的原子时标守时能力,利用改进的有限脉冲响应钟差预测与频率调控方法,对激光冷却铯原子喷泉钟与氢钟的频差实测数据进行后处理,分别产生了自主型时标和溯源型时标。通过国际原子时合作链路将两个时标与协调世界时进行了长期比对实验,结果表明:2021年12月~2022年12月期间,两个时标的时间偏差均优于±4 ns、频率稳定度均优于8×10^(-16)/5 d。

中国海洋自然资源调查现状与展望

海洋自然资源是国民经济和社会发展的重要保障,也是海洋强国建设和生态文明建设的必要基础。为全力支撑自然资源部履行“两统一”职责(统一行使全民所有自然资源资产所有者职责和统一行使所有国土空间用途管制和生态保护修复职责),中国地质调查局组织实施海洋自然资源综合调查评价,开展我国重点海域海洋自然资源综合调查与评价试点示范。基于我国已开展的海洋自然资源相关的综合性调查评价数据资料,结合我国重点海域海洋地质、海洋生物、物理海洋等补充调查评价结果,基本查明了我国海洋矿产、海洋能、海洋生物、海洋空间等海洋自然资源的主要特征;通过梳理总结国内外自然资源体系研究进展,基于我国基本国情,以自然资源科学和地球系统科学理论为指导,面向自然资源综合管理为基本原则,结合资源自然属性和国家相关法律法规,初步提出了涉及多学科、多门类的海洋自然资源三级分类体系,从分类体系、空间分层、工作流程等不同角度,提出了3种构建海洋自然资源调查标准体系的方法。下一步,将大力加强地质科技创新能力,加快构建动态海洋自然资源数据库,快速提升海洋自然资源公益服务水平,进一步完善海洋自然资源综合监测体系,推动海洋自然资源工作高质量发展。

专业技术类职业与技能类职业的差异、划分与职业标准建设

专业技术人员与技能人员是职业分类的两个相关类别,但在分类过程中,一些“跨界”职业究竟应如何归类尚存争议,且此科分类事关后续职业标准开发、人才队伍建设、技能等级评价(或专业技术等级考核)等,亟需深入研究。基于对职业分类的功能作用、职业分类大典的修订背景的梳理,通过回溯《中华人民共和国职业分类大典(2022年版)》修订过程,凝练出科学划分专业技术类职业和技能类职业的依据,尝试建立判定两类职业表述和专业技术或技能等级描述的标准话语体系,为两类人员职业生涯的贯通、接续发展提供依据,旨在为完善我国现代职业分类、职业标准体系提供理论基础。

国际标准行业分类的演化进展、标准更新与中国启示

行业分类的科学建立、及时更新和有效实施对国民经济发展具有重要意义。在行业分类体系中,联合国发布的《国际标准行业分类》(ISIC)最具影响力,是各国行业分类标准制定的风向标。以ISIC的国际进展为研究主线,系统梳理ISIC的发展历程,从差异性角度剖析ISIC各个版本在分类原则、分类结构、符号体系等方面的演变规律,并归纳总结最新版ISIC Rev.5的基本结构和主要变化。之后,结合我国经济发展现状和统计工作需要,分析ISIC更新对我国国民经济行业分类标准修订工作的启示,以期探寻我国国民经济行业分类的优化路径。

西北地区农村生活污水排放标准对比及分析

西北地区农村生活污水整体治理率低于全国平均水平,为有效提升区域农村污水治理率,提高当地村落水环境管理水平,西北各省(自治区)政府陆续颁布农村生活污水处理污染物排放标准。通过剖析山西省、陕西省、甘肃省、青海省、宁夏回族自治区、新疆维吾尔自治区和内蒙古自治区七省(自治区)农村生活污水排放标准与《城镇污水处理厂污染物排放标准》和《农田灌溉水质标准》,发现西北七省(自治区)标准分级主要基于地表水环境质量标准和处理设施规模两方面进行划分,且各地标准在控制指标选取上与城镇污水处理厂污染物排放标准基本一致,但标准限值相对宽松。同时,西北七省(自治区)三级标准均可满足西北地区农田灌溉水质要求,其中内蒙古、甘肃和新疆更是作出了明确规定。此外,通过深入总结分析西北地区农村生活污水排放标准,可引导地方农村生活污水治理从执着于《城镇污水处理厂污染物排放标准》到优先考虑适宜区域的地方标准,更可为西北地区优选农村生活污水处理适用技术与治理模式提供思路,进而有助于提升地方政府的农村水环境治理相关政策决策水平。

基于CNN与LSTM复合深度模型的恒星光谱分类算法

恒星光谱分类是天文学领域中非常重要的研究方向。随着科技的迅猛发展,大型巡天望远镜采集的恒星光谱数据已经达到了TB或甚至PB级别,传统的分类方法已经无法满足如此庞大数据量的处理需求。正确分类光谱对于研究恒星的物理性质以及演化过程具有重要意义。CNN通过卷积运算学习数据的局部特征,去除冗余信息,并通过最大池化运算对特征进行压缩。然而,由于原始CNN模型的全连接层缺乏长距离依赖挖掘的功能,如果加入LSTM网络,通过其独特的三个“门”的远距离依赖挖掘能力可提取的重要特征,并检测特征中的微小差异,恰好可以解决这个问题。因此,提出了一种基于CNN和LSTM复合的深度模型,用于对LAMOST DR8中的恒星光谱进行分类。这种模型能够更好地学习恒星光谱的特征,为恒星演化研究提供了重要的帮助。为了提高模型的收敛速度,使用了常见的Z-Score标准化方法对数据进行处理。提出的模型在F、G、K三分类实验中取得了94.56%的分类准确率。同时,与前人使用过的RBM、PILDNN、PILDNN、DBN、Inception v3、1D-SSCNN、LSTM方法进行对比,结果表明该方法具有更高的分类准确率。在十分类实验中,该方法取得了97.35%的准确率,并且相比于仅使用LSTM、1D-SSCNN方法的实验结果,该方法的结果更好,且训练时间减少了近十倍。使用F1-score对每类恒星光谱分类准确度进行说明,在三分类和十分类实验中,每类的F1值都在0.9以上。与前人在文献中的实验结果进行对比,该模型的结果更好。通过混淆矩阵的结果,可以得出该模型在光谱种类越多的实验中准确率越高,甚至可以达到100%。综上所述,所提出的基于CNN和LSTM相结合的模型可以有效地对大规模恒星光谱数据进行分类,并取得了优异的分类效果。

国内外增材制造标准建设现状及分析

为规范和指导增材制造技术的发展以及推动国内增材制造标准建设,介绍了由ISO/TC 261与ASTM F42联合发布的国外标准体系框架,以及由全国增材制造标准化技术委员会SAC/TC562发布的国内增材制造标准体系框架,并结合现有标准框架对国际标准化组织(ISO)增材制造标准、美国材料实验协会(ASTM)增材制造标准、国际自动机工程师学会(SAE)增材制造标准,以及国内增材制造国家标准、行业标准、地方标准、团体标准展开分类和研究。同时结合增材制造标准体系建设、质量认证、政策规划、行业应用等对国内外现有的增材制造标准展开了全面的对比分析。结果表明,ISO发布的增材制造标准大多为通用标准,而ASTM和SAE则以专用标准为主。国内方面,国家标准以关键技术标准为主,而行业标准则集中在航空航天、医疗器械等领域。标准建设方面国内标准更关注特定工艺、材料等而国外标准则涉及到资质认可和制造规范的要求。

龙胆种子质量分级标准研究

以16批龙胆种子为试验材料,获取龙胆种子真实性、净度、含水量、百粒重、生活力、发芽率和发芽势等指标的数据,采用主成分分析、系统聚类分析和K-均值聚类分析等多元统计分析方法对龙胆种子进行三级标准划分,初步制定龙胆种子的质量分级标准。结果表明,一级:净度≥79.95%,含水量≥6.40%,生活力≥87.17%,百粒重≥5.00 mg,发芽率≥77.50%,发芽势≥36.50%;二级:55.62%≤净度<79.95%,5.91%≤含水量<6.40%,86.170%≤生活力<87.17%,4.72 mg≤百粒重<5.00 mg, 69.33%≤发芽率<77.50%,31.75%≤发芽势<36.50%;三级:净度<55.62%,含水量<5.91%,生活力<86.17%,百粒重<4.72 mg,发芽率<69.33%,发芽势<31.75%。

基于GF-1卫星影像数据融合的冬小麦田空间信息提取

为给高标准农田建设规划和粮食安全生产措施的制定提供准确信息,在对国产GF-1/PMS卫星影像进行辐射定标、大气校正、几何校正和裁剪等预处理的基础上,经过影像融合提取了高标准麦田多地物的点像元光谱信息,通过分析不同地物光谱特征,利用波段反射率、归一化差值植被指数(NDVI)和差值植被指数(DVI)构建植被光谱特征指标阈值,进而对冬小麦田及非麦田进行分类,以获取高标准麦田的空间分布信息。结果表明,光谱特征指标选择BR_(4)>0.3、NDVI>0.619和DVI>0.317,可以较准确地从影像中识别出冬小麦田,并减少田间道路被误判为冬小麦田像元。在非麦田分类中,选择BR_(3)>0.15和BR_(4)>0.2,可将建筑用地与河流(沟渠)区分开。利用田间样方统计面积和遥感提取面积进行精度验证,总体精度可达97.33%,说明通过中、高空间分辨率遥感数据融合,结合多重光谱特征指标建立合理的分类阈值,可以准确提取冬小麦田及非麦田的分布信息。

省域高职院校分类发展的现实背景、框架设计与推进路径

省域高职院校分类发展,不仅是推进高职教育高质量发展、构建省域现代职教体系的重要举措,更是政府优化管理,引导高职院校多样化、特色化发展的有效路径。本科院校分类评价已进入全面普及阶段,但高职院校内部分类及分类评价尚未真正实现。对分类必要性、现状及问题进行梳理,明确分类的原则和标准,搭建起“3×3+1”的“十宫格”省域高职院校三维分类框架,并以浙江为例,进行了分类运用。提出要转变管理理念,加强政府宏观引导,分层分类推进高水平高职院校建设进程;探索多维评价,构建分类评价指标体系,做到现实与未来联动、共性与个性兼顾;合理运用结果,完善分类评价资源配置,激励高职院校开展良性竞争;坚持特色办学,在类型宫格与省域需求中追求高水平,为高质量分类发展提供内生动力。

面向新标准的矿山资源储量管理系统研发与应用

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