Analysis of the medication rules of the national patent compound for the treatment of functional dyspepsia

Objective:Based on data mining software,applying frequent itemsets,association rules,hierarchical clustering,complex networks and other data mining methods to analyze the usage and compatibility of traditional Chinese medicine(TCM)patent compound for functional dyspepsia.Method:Use the Chinese patent database to search the compound for the treatment of functional dyspepsia,exclude traditional Chinese medicine extracts,single drugs,combined use of Chinese and Western medicines,etc.,screen the patented compound of TCM,establish an Excel data table,and apply data mining software to The data is subjected to frequency statistics,association rules,cluster analysis and complex network analysis.Result:A total of 238 prescriptions for functional dyspepsia were screened.The four qi of the drugs were mainly warm and calm,the five flavors were mainly sweet and spicy,and the spleen and stomach were the main meridians.The top 10 Chinese medicines with higher frequency are Shanzha、Chenpi、Gancao、Maiya、Jineijin、Fuling、Baizhu、Shenqu、Houpo、Banxia;frequent itemsets show that the drugs are mainly compatible with qi and spleen,qi and digestion;association rules The analysis shows that the common drug pairs used in the treatment of functional dyspepsia include Chenpi-Shanzha、Maiya-Shanzha、Jineijin-Shanzha,etc.;cluster analysis found that there are 4 types of drugs for functional dyspepsia,mainly including drugs for regulating qi-flowing for harmonizing stomach,drugs for soothing liver and promoting Qi,drugs for eliminating food and resolving accumulation,drugs for benefiting qi and strengthening spleen;the 22-flavor Chinese medicine in the core drug network,the core compatibility is mainly to eliminate stagnation and spleen.Conclusion:Data mining research provides a reference for the clinical treatment of functional dyspepsia and the development of TCM formulas;Clinical treatment of functional dyspepsia should grasp the basic principles of strengthening vital energy and eliminating pathogenic factors to benefit qi,strengthen the spleen,and eliminate food.It is a basic treatment method,taking into account the methods of regulating qi-flowing for harmonizing stomach,soothing the liver and relieving depression,relieving dampness and dampness,and combining the specific conditions of patients with syndrome differentiation and treatment.

Time Slice Analysis Method Based on OTCA Used in fMRI Weak Signal Function Extraction

The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.

Derringer desirability and kinetic plot LC-column comparison approach for MS-compatible lipopeptide analysis

Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antitumor, immune-modulating and cell-penetrating compounds. However, due to their specific structure, chromatographic analysis often requires special buffer systems or the use of trifluoroacetic acid, limiting mass spectrometry detection. Therefore, we used a traditional aqueous/acetonitrile based gradient system, containing 0.1% （m/v） formic acid, to separate four pharmaceutically relevant lipopeptides （polymyxin B1, caspofungin, daptomycin and gramicidin A1）, which were selected based upon hierarchical cluster analysis （HCA） and principal component analysis （PCA）.In total, the performance of four different C18 columns, including one UPLC column, were evaluated using two parallel approaches. First, a Derringer desirability function was used, whereby six single and multiple chromatographic response values were rescaled into one overall D-value per column. Using this approach, the YMC Pack Pro C18 column was ranked as the best column for general MS-compatible lipopeptide separation. Secondly, the kinetic plot approach was used to compare the different columns at different flow rate ranges. As the optimal kinetic column performance is obtained at its maximal pressure, the length elongation factor λ（Pmax/Pexp） was used to transform the obtained experimental data （retention times and peak capacities） and construct kinetic performance limit （KPL） curves, allowing a direct visual and unbiased comparison of the selected columns, whereby the YMC Triart C18 UPLC and ACE C18 columns performed as best. Finally, differences in column performance and the （dis）advantages of both approaches are discussed.

Bioinformatics Analysis of Genes and Pathways of CD11b^(+)/Ly6C^(intermediate)Macrophages after Renal Ischemia-Reperfusion Injury

Renal ischemia-reperfusion injury(IRI)is a major cause of acute kidney injury(AKI),which could induce the poor prognosis.The purpose of this study was to characterize the molecular mechanism of the functional changes of CD11 b^(+)/Ly6 C^(intermediate)macrophages after renal IRI.The gene expression profiles of CD11 b^(+)/Ly6 C^(intermediate)macrophages of the sham surgery mice,and the mice 4 h,24 h and 9 days after renal IRI were downloaded from the Gene Expression Omnibus database.Analysis of m RNA expression profiles was conducted to identify differentially expressed genes(DEGs),biological processes and pathways by the series test of cluster.Protein-protein interaction network was constructed and analysed to discover the key genes.A total of 6738 DEGs were identified and assigned to 20 model profiles.DEGs in profile 13 were one of the predominant expression profiles,which are involved in immune cell chemotaxis and proliferation.Signet analysis showed that Atp5 a1,Atp5 o,Cox4 i,Cdc42,Rac2 and Nhp2 were the key genes involved in oxidation-reduction,apoptosis,migration,M1-M2 differentiation,and proliferation of macrophages.RPS18 may be an appreciate reference gene as it was stable in macrophages.The identified DEGs and their enriched pathways investigate factors that may participate in the functional changes of CD11 b^(+)/Ly6 C^(intermediate)macrophages after renal IRI.Moreover,the vital gene Nhp2 may involve the polarization of macrophages,which may be a new target to affect the process of AKI.

MART(Splitting-Merging Assisted Reliable)Independent Component Analysis for Extracting Accurate Brain Functional Networks

Functional networks(FNs)hold significant promise in understanding brain function.Independent component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determining an optimal model order for ICA remains challenging,leading to criticism about the reliability of FN estimation.Here,we propose a SMART(splitting-merging assisted reliable)ICA method that automatically extracts reliable FNs by clustering independent components(ICs)obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model orders.We extend SMART ICA to multi-subject fMRI analysis,validating its effectiveness using simulated and real fMRI data.Based on simulated data,the method accurately estimates both group-common and group-unique components and demonstrates robustness to parameters.Using two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects,the resulting reliable group-level FNs are greatly similar between the two cohorts,and interestingly the subject-specific FNs show progressive changes while age increases.Furthermore,both small-scale and large-scale brain FN templates are provided as benchmarks for future studies.Taken together,SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data,while also providing linkages between different FNs.

Unsupervised Functional Data Clustering Based on Adaptive Weights

In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be directly used for the clustering of functional data. In this paper, we propose a new unsupervised clustering algorithm based on adaptive weights. In the absence of initialization parameter, we use entropy-type penalty terms and fuzzy partition matrix to find the optimal number of clusters. At the same time, we introduce a measure based on adaptive weights to reflect the difference in information content between different clustering metrics. Simulation experiments show that the proposed algorithm has higher purity than some algorithms.

Applied statistical functions and multivariate analysis of geochemical compositional data to evaluate mineralization in Glojeh polymetallic deposit,NW Iran

Various genesis of epithermal veins as well as host rock cause complication in the modeling process. Thus LINEST and controlling function were applied to improve the accuracy and the quality of the model.The LINEST is a model which is based on multiple linear regression and refers to a branch of applied statistics.This method concerns directly to the application oft-test (TINV and TDIST to analyses of variables in the model)and F- test (FDIST,F-statistic to compare different models) analysis.Backward elimination technique is applied to reduce the number of variables in the model through all the borehole data.After 18 steps,an optimized reduced model (ORM)was constructed and ranked in order of importance as Pb >Ag >P >Hg>Mn>Nb >U>Sr>Sn>As > Cu,with the lowest confidence level (CL)of 92% for Cu.According to the epigenetic vein genesis of Glojeh polymetallic deposit,determination of spatial pattems and elemental associations accompanied by anomaly separation were conducted by K-means cluster and robust factor analysis method based on centered log-ratio (clr)transformed data.Therefore,12 samples (cluster 2)with the maximum distance from centroid,indicates the intensity of vein polymetallic mineralization in the deposit.In addition, an ORM for vein population was extracted for Sb >A1 > As >Mg >Pb >Cu >Ag elements with the R2 up to 0.99. On the other hand,after 23 steps of optimization process at the host rock population,an ORM Was conducted by Ag >Te >Hg >Pb >Mg >A1 >Sb >As represented in descending order oft-values.It revealed that Te and Hg can be considered as pathfinder elements for Au at the host rock.Based on the ORMs at each population Ag,Pb,and As were often associated with Au mineralization.The concentration ratio of (tSb × tA1)vein/(tSb × tA1)baekground as an enrichment index can intensify the mineralization detection.Finally,Glojeh deposit was evaluated to be classified as a vein-style Au (Ag,Pb,As)-polymetallic mineralization.

Functional data analysis: An application to COVID-19 data in the United States in 2020

Background: In this paper, we conduct an analysis of the COVID-19 data in the United States in 2020 via functional data analysis methods. Through this research, we investigate the effectiveness of the practice of public health measures, and assess the correlation between infections and deaths caused by the COVID-19. Additionally, we look into the relationship between COVID-19 spread and geographical locations, and propose a forecasting method to predict the total number of confirmed cases nationwide.Methods: The functional data analysis methods include functional principal analysis methods, functional canonical correlation analysis methods, an expectation-maximization (EM) based clustering algorithm and a functional time series model used for forecasting.Results: It is evident that the practice of public health measures helps to reduce the growth rate of the epidemic outbreak over the nation. We have observed a high canonical correlation between confirmed and death cases. States that are geographically close to the hot spots are likely to be clustered together, and population density appears to be a critical factor affecting the cluster structure. The proposed functional time series model gives more reliable and accurate predictions of the total number of confirmed cases than standard time series methods.Conclusions: The results obtained by applying the functional data analysis methods provide new insights into the COVID-19 data in the United States. With our results and recommendations, the health professionals can make better decisions to reduce the spread of the epidemic, and mitigate its negative effects to the national public health.

基于加权Ripley's K-function的多尺度景观格局分析——以江苏盐城滨海湿地为例

以1987,1992,1997,2002,2007年的遥感影像为例,首次尝试使用加权Ripley's K-function的多尺度格局分析方法,计算了20年来景观异质性在江苏盐城滨海湿地的时间变化和空间分布趋势。通过对研究区的样带划分以及景观类型的点状化处理,建立滨海湿地样带图层和1987—2007年间各类型景观的点格局数据库,从而分析滨海湿地不同类型景观的空间聚集特征变化。基于加权Ripley's K-function的计算表明,在各级空间尺度和时间变化上,各类型湿地的斑块都呈现出空间聚集分布状态,且1987年以来,不同湿地类型的聚集空间特征尺度和空间分布强度均出现了大幅的增减变化,除互花米草滩之外的自然湿地的聚集空间特征尺度和强度都有明显下降甚至少到无法被检测到,而人工湿地却呈现聚集特征尺度和强度的双增长,且该聚集程度有逐渐增强的趋势。分析表明,既考虑样点的空间位置信息又考虑样点分布范围的加权Ripley's K-function方法能很好地表征湿地景观在多尺度上的变异,且与传统空间景观指数等分析方法的结论在一定程度上保持一致。

Ant colony ATTA clustering algorithm of rock mass structural plane in groups

Based on structural surface normal vector spherical distance and the pole stereographic projection Euclidean distance,two distance functions were established.The cluster analysis of structure surface was conducted by the use of ATTA clustering methods based on ant colony piles,and Silhouette index was introduced to evaluate the clustering effect.The clustering analysis of the measured data of Sanshandao Gold Mine shows that ant colony ATTA-based clustering method does better than K-mean clustering analysis.Meanwhile,clustering results of ATTA method based on pole Euclidean distance and ATTA method based on normal vector spherical distance have a great consistence.The clustering results are most close to the pole isopycnic graph.It can efficiently realize grouping of structural plane and determination of the dominant structural surface direction.It is made up for the defects of subjectivity and inaccuracy in icon measurement approach and has great engineering value.

Urban Economic Cluster Template and Its Dynamics of Beijing,China

Economic clusters have been a central focus of current urban and regional research, policies and practices. However, a methodology to identify and analyze policy-relevant economic cluster dynamics is still not well developed. Based on input-output(I-O) data of 1987, 1992, 1997, 2002 and 2007 of Beijing, this article presents an adapted principle component analysis for identifying the evolution of local economic cluster patterns. This research addresses the changes of economic interaction of industries with complementary and common activities over time. The identified clusters provide an insight into the reality of economic development in a diversifying urban economy: the increasing importance of services and the growing interaction between service and manufacturing industries. Our method therefore provides the analysts with a better understanding of the emergence, disappearance and development of economic clusters citywide. The results could be used to assist monitoring urban economic development and designing more practical urban economic strategies.

Development of slope mass rating system using K-means and fuzzy c-means clustering algorithms

Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.

Human wetland dependency and socio-economic evaluation of wetland functions through participatory approach in rural India

Wetlands are an important source of natural resources upon which rural economies depend. They have increasingly been valuable for their goods and services, and the intrinsic ecological value they provide to local populations, as well as people living outside the periphery of the wetlands. Stakeholders＇ participation is essential to the protection and preservation of wetlands because it plays a very important role economically as well as ecologically in the wetland system. The objective of this study was to determine whether gender, educational status, mouzas （which are constituents of a block according to the land reform of the West Bengal Government in India）, and wetland functions have any influence on the annual income of the local community. Considering a floodplain wetland in rural India, the focus was extended to recognize the pattern of wetland functions according to the nature of people＇s involvement through cluster analysis of the male and female populations. Using the statistical software R-2.8.1, an ANOVA （analysis of variance） table was constructed. Since the p value （significance level） was lower than 0.05 for each case, it can be concluded that gender, educational status, mouzas, and wetland functions have a significant influence on annual income. However, S-PLUS-2000 was applied to obtain a complete scenario of the pattern of wetland functions, in terms of involvement of males and females, through cluster analysis. The main conclusion is that gender, educational status, mouzas, and wetland functions have significant impacts on annual income, while the pattern of occupation of the local community based on wetland functions is completely different for the male and female populations.

THE CLASSIFICATION OF INDUSTRIAL FUNCTION OF CHINESE CITIES (INCLUDING ATTACHED COUNTIES)

Represents the first attempt to classify all of China’s295 cities in terms of industrial functions,using 1984 data.Within the framework of economic base theory of urban development,three elements are defined as specialized branch,functional intensity and functional scale.The method used here is based on a combination of the three elements.A number of techniques tried made it possible to base the classification on a composite measure,consisting of the Ward’s Error Method of hierarchical cluster analysis and a supplementary application of Nelson measure.The 295 cities have been grouped into three categories with 19 subcategories and 54 functional groups.The distribution of cities in most of the subcategories are displayed on 8 maps.

Displacement reconstruction and strain refinement of clustering-based homogenization

Recently proposed clustering-based methods provide an efficient way for homogenizing heterogeneous materials,yet without concerning the detailed distribution of the mechanical responses.With coarse fields of the clustering-based methods as an initial guess,we develop an iteration strategy to fastly and accurately resolve the displacement,strain and stress based on the Lippmann-Schwinger equation,thereby benefiting the local mechanical analysis such as the detection of the stress concentration.From a simple elastic case,we explore the convergence of the method and give an instruction for the selection of the reference material.Numerical tests show the efficiency and fast convergence of the reconstruction method in both elastic and hyper-elastic materials.

44份西瓜种质资源苗期耐盐性综合评价

以44份西瓜种质为试验材料,设置0(CK)和150 mmol·L^(-1)NaCl 2个处理水平,测定不同西瓜种质幼苗的15项指标。以15项指标的耐盐系数作为耐盐性评价依据,运用相关性分析、主成分分析、隶属函数值法、聚类分析等多元分析方法进行综合评价。通过主成分分析将15个单项指标转换为4个相互独立的综合指标,累计贡献率为71.10%;以耐盐系数为基础进行聚类分析,筛选出10个高度耐盐、21个中度耐盐、13个弱耐盐西瓜种质资源。采用隶属函数法进行综合评价,排名前5的种质分别是HY-91、DQ-308、W19-15、HY-73、W19-10,归为聚类分析中的第一类,属于强耐盐性品种。

Relation between Family Functioning and Quality of Life among Family Caregivers of Patients with Terminal Cancer Hospitalized in General Wards

Caring for a patient with terminal cancer poses difficulties for family caregivers. Although families of patients with cancer have been classified by type, little is known about the relation between family functioning and quality of life (QOL) in family caregivers. This study aimed to develop a typology of family functioning in family caregivers of patients with terminal cancer and then examine the relation between the family functioning and QOL of family caregivers. From December 2013 to August 2014, fifty-one family caregivers of patients with terminal cancer were recruited at three hospitals in Tokyo, Japan. Perceptions of family functioning were assessed with the Family Relationship Index, and its three subscores were classified into three groups by cluster analysis. Caregivers’ QOL was measured with the Caregiver Quality of Life Index-Cancer. The average total FRI score among 51 caregivers was 8.5 (SD = 2.8). Family functioning was categorized into three clusters: supportive (n = 12), communicative (n = 30), or conflictive (n = 8). Their QOL was categorized into two groups: the communicative group, with relatively high confliction, showed high QOL comparable to the supportive group. Family functioning in the families of patients with terminal cancer hospitalized in general wards was not good. For improving the QOL of family caregivers, it may be important for the family members to express their feelings and distress if they have conflicts.

大凉山地区不同马铃薯品种产量和营养品质的综合评价

为筛选出适宜四川大凉山地区种植的马铃薯品种,对14个马铃薯品种的12个产量与营养品质指标进行测定,并结合主成分分析、隶属函数法、系统聚类分析对马铃薯产量和品质表现进行综合评价。结果表明,单株结薯数、单薯鲜质量、单株块茎鲜质量、单产、还原糖含量的变异系数均超过30%;单株块茎鲜质量与单薯鲜质量、单产和蛋白质含量呈极显著正相关,干物质含量与淀粉含量、蛋白质含量呈极显著正相关,单薯鲜质量与VC含量、锌含量呈显著负相关,蛋白质含量与钾含量呈极显著负相关;主成分分析结果表明,12个指标可用4个主成分来表示,方差累积贡献率达到86.040%。进一步采用隶属函数法和系统聚类分析将14个品种分为3类,筛选出6个综合表现较优的品种,分别为川凉薯10号、青薯9号、川芋50、川凉芋13、云薯108、川芋22号。

20个青贮玉米品种在陇东南地区的生产性能和营养价值评价

为筛选出适合陇东南地区(甘肃天水)种植的优质高产青贮玉米(Zea mays)品种,本研究以20个青贮玉米品种为材料,测定并分析了各品种农艺性状、生物产量、营养物质含量及产量,并采用隶属函数法进行了综合评价。结果表明:粗蛋白含量与绿叶数、果穗数、有效果穗数、果穗长、鲜果穗重和黄叶数显著相关(P<0.05);酸性洗涤纤维和中性洗涤纤维含量与株高、穗位高、全株叶片数和黄叶数极显著相关(P<0.01);淀粉含量与穗位高、全株叶片数、单株鲜重和株高显著相关(P<0.05)。本研究中鲜草产量达到60 t·hm^(-2)以上的品种有5个,干物质产量达到15 t·hm^(-2)以上的品种有6个,‘先玉1620’的总可消化营养物产量最高。综合评价得出,在本试验条件下,青贮综合生产性能高的品种为‘先玉1620’‘文玉3号’和‘科大101’,可以大面积在陇东南地区作为全株青贮玉米品种推广种植。

芦竹属菌草腋芽萌发期耐盐性评价

【目的】筛选腋芽萌发期耐盐性较强的芦竹属菌草品种,为该类菌草耐盐品种培育提供参考。【方法】以国内外不同地区的12个芦竹属菌草品种为试材,对150 mmol·L^(-1) NaCl溶液处理后腋芽萌发期的各个指标(芽长、根长、芽鲜质量、根鲜质量、发芽势、发芽率、发芽指数和活力指数)进行测定。利用模糊隶属函数法和聚类分析法对供试品种的耐盐性进行综合评价。【结果】与对照组相比,在150 mmol·L^(-1) NaCl胁迫下,所有供试品种的发芽势均降低,芽长、根长、芽鲜质量和根鲜质量都减小;除LZ_NO.1、LZ_NO.3和LZ_NO.7外,其他品种的发芽率均下降;活力指数受盐胁迫的影响最大。基于各指标耐盐系数隶属函数值的临近度对12个品种进行聚类分析,结果表明:LZ_NO.1、LZ_NO.3和LZ_NO.7为一类,属高耐盐型;LZ_NO.2、LZ_NO.4和LZ_NO.6为一类,属盐敏感型。【结论】腋芽萌发期耐盐性较强的芦竹属菌草品种为LZ_NO.1、LZ_NO.3和LZ_NO.7;根据活力指数可判定芦竹属菌草品种的质量优劣。