The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS

Purpose： To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach： We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare these methods. We offer the correct syntax to deactivate the similarity algorithm for clustering analysis within the hierarchical clustering module of SPSS. Findings： When one inputs co-occurrence matrices into the data editor of the SPSS hierarchical clustering module without deactivating the embedded similarity algorithm, the program calculates similarity twice, and thus distorts and overestimates the degree of similarity. Practical implications： We offer the correct syntax to block the similarity algorithm for clustering analysis in the SPSS hierarchical clustering module in the case of co-occurrence matrices. This syntax enables researchers to avoid obtaining incorrect results. Originality/value： This paper presents a method of editing syntax to prevent the default use of a similarity algorithm for SPSS＇s hierarchical clustering module. This will help researchers, especially those from China, to properly implement the co-occurrence matrix when using SPSS for hierarchical cluster analysis, in order to provide more scientific and rational results.

Compatibility Rules of Neonatal Parenteral Nutrition Prescriptions Based on Association Rules and Hierarchical Cluster Analysis

[Objectives]To explore the compatibility rules of neonatal parenteral nutrition(PN)prescriptions based on association rules and hierarchical cluster analysis,thereby providing a reference for standardizing neonatal parenteral nutrition supportive therapy.[Methods]The data about neonatal PN formulations prepared by the Pharmacy Intravenous Admixture Services(PIVAS)of the Affiliated Hospital of Chengde Medical University from July 2015 to June 2021 were collected.The general information of the prescriptions and the frequency of drug use were analyzed with Excel 2019;the boxplot of drug dosing was drawn using GraphPad 8.0 software;and SPSS Modeler 18.0 and SPSS Statistics 26.0 were used to perform association rules and hierarchical cluster analysis.[Results]A total of 11488 PN prescriptions were collected from 1421 newborns,involving 18 kinds of drugs,which were divided into 11 types of nutrients.Association rules analysis yielded 84 nutrient substance combinations.The combination of fat emulsion-water-soluble vitamins-fat-soluble vitamins-glucose-amino acids had the highest confidence(99.95%).The hierarchical cluster analysis divided nutrients into 5 types.[Conclusions]The prescriptions of PN for newborns were composed of five types of nutrients:amino acids,fat emulsion,glucose,water-soluble vitamins,and fat-soluble vitamins.According to the lack of electrolytes and trace elements,appropriate drugs can be chosen to meet nutritional demands.This study provides reference basis for reasonable selection of drugs for neonatal PN prescriptions and further standardization of PN supportive therapy in newborns.

Water Quality Assessment in the Bamoun Plateau, Western-Cameroon: Hydrogeochemical Modelling and Multivariate Statistical Analysis Approach

This study focuses on the geochemical and bacteriological investigation of surface and ground water in the Bamoun plateau (Western-Cameroon). During the period from September 2013 to August 2014, 71 samples were collected from two springs, one borehole, four wells and the Nchi stream for analysis of major elements. In order to obtain the characteristics of the various species of bacteria, 7 samples were selected. The analytical method adopted for this study is the conventional hydrochemical technic and multivariate statistical analysis, coupled with the hydrogeochemical modelling. The results revealed that, water from the zone under study are acidic to basic, very weakly to weakly mineralized. Four types of water were identified: 1) CaMg-HCO3;2) CaMg-Cl-SO4;3) NaCl-SO4 and 4) NaK-HCO3. The major elements were all listed in the World Health Organization guidelines for drinking water quality, except for nitrates which was found at a concentration > 50 mg /l NO-3 in the borehole F401. As for the hydrobiological aspect, the entire sample contained all the bacteriological species except for spring S301 and well P401. According to the hydrogeochemical modelling, the Gibbs model and multivariate statistical tests, the quality of surface and ground water of the Foumban locality is influenced by two important factors: 1) the natural factors characterized by the water-rock interaction, evapotranspiration/crystallization, 2) the anthropogenic factors such as: uncontrolled discharges of liquid and solid effluents of all kinds and without any prior treatment within the ground and the strong urbanization accompanied by lack of sanitation and insufficient care.

Determination of bioactive components in the fruits of Cercis chinensis Bunge by HPLC-MS/MS and quality evaluation by principal components and hierarchical cluster analyses

The fruits of leguminous plants Cercis Chinensis Bunge are still overlooked although they have been reported to be antioxidative because of the limited information on the phytochemicals of C.chinensis fruits.A simple,rapid and sensitive HPLC-MS/MS method was developed for the identification and quantitation of the major bioactive components in C.chinensis fruits.Eighteen polyphenols were identified,which are first reported in C.chinensis fruits.Moreover,ten components were simultaneously quantified.The validated quantitative method was proved to be sensitive,reproducible and accurate.Then,it was applied to analyze batches of C.chinensis fruits from different phytomorph and areas.The principal components analysis(PCA)realized visualization and reduction of data set dimension while the hierarchical cluster analysis(HCA)indicated that the content of phenolic acids or all ten components might be used to differentiate C.chinensis fruits of different phytomorph.

Multivariate analysis of fluorescence and source identification of dissolved organic matter in Jiaozhou Bay, China

Hierarchical clustering analysis and principal component analysis （PCA） methods were used to assess the similarities and dissimilarities of the entire Excitation-emission matrix spectroscopy （EEMs） data sets of samples collected from Jiaozhou Bay, China. The results demonstrate that multivariate analysis facilitates the complex data treatment and spectral sorting processes, and also enhances the probability to reveal otherwise hidden information concerning the chemical characteristics of the dissolved organic matter （DOM）. The distribution of different water samples as revealed by multivariate results has been used to track the movement of DOM material in the study area, and the interpretation is supported by the results obtained from the numerical simulation model of substance tracing technique, which show that the substance discharged by Haibo River can be distributed in Jiaozhou Bay.

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.

Mathematical Tools of Cluster Analysis

The paper deals with cluster analysis and comparison of clustering methods. Cluster analysis belongs to multivariate statistical methods. Cluster analysis is defined as general logical technique, procedure, which allows clustering variable objects into groups-clusters on the basis of similarity or dissimilarity. Cluster analysis involves computational procedures, of which purpose is to reduce a set of data on several relatively homogenous groups-clusters, while the condition of reduction is maximal and simultaneously minimal similarity of clusters. Similarity of objects is studied by the degree of similarity (correlation coefficient and association coefficient) or the degree of dissimilarity-degree of distance (distance coefficient). Methods of cluster analysis are on the basis of clustering classified as hierarchical or non-hierarchical methods.

Analysis of genetic diversity in banana cultivars(Musa cvs.) from the South of Oman using AFLP markers and classification by phylogenetic,hierarchical clustering and principal component analyses

Banana is an important crop grown in Oman and there is a dearth of information on its genetic diversity to assist in crop breeding and improvement programs.This study employed amplified fragment length polymorphism(AFLP) to investigate the genetic variation in local banana cultivars from the southern region of Oman.Using 12 primer combinations,a total of 1094 bands were scored,of which 1012 were polymorphic.Eighty-two unique markers were identified,which revealed the distinct separation of the seven cultivars.The results obtained show that AFLP can be used to differentiate the banana cultivars.Further classification by phylogenetic,hierarchical clustering and principal component analyses showed significant differences between the clusters found with molecular markers and those clusters created by previous studies using morphological analysis.Based on the analytical results,a consensus dendrogram of the banana cultivars is presented.

Anthropogenic disturbance of aquatic biodiversity and water quality of an urban river in Penang, Malaysia

Malaysia's rapid economic and demographic development have placed negative pressure on its water supplies and the quality of the Juru River, which is close to the nation's capital and its major source of water. Healthy aquatic ecosystems are supported by physicochemical properties and biological diversity. This study evaluated the anthropogenic impacts on aquatic biodiversity, especially plankton, fish, and macrobenthos, as well as the water quality of the Juru River in the Penang area. Aquatic biodiversity and river water parameters were collected from ten sampling stations along the Juru River. Seven variables were used to assess the physicochemical environment: pH, temperature, total suspended solids (TSS), salinity, dissolved oxygen (DO), biochemical oxygen demand (BOD), and chemical oxygen demand. At each sampling station, the total number of plankton, fish, and macrobenthic taxa were counted and analyzed. The relationships between the physicochemical parameters and aquatic biodiversity were investigated with biotypological analysis, principal component analysis, hierarchical cluster analysis, and linear regression analysis. These analyses showed that the richness and diversity indices were generally influenced by salinity, temperature, TSS, BOD, and pH. The data obtained in this study supported the bioindicator concept. The findings, as they related to scientifically informed conservation, could serve as a model for Juru River management, as well as for river management throughout Malaysia and other tropical Asian countries.

Evaluation preparation technology of Xiaochaihu granules using fingerprint-peak pattern matching

An approach was proposed to evaluate preparation technology by means of fingerprint-peak matching technology of high performance liquid chromatography with diode array detector （HPLC-DAD）. Similarity and hierarchical clustering analysis （HCA） were applied to identify the 15 batches of Xiaochaihu granules from different manufacturers and our laboratory, and peak pattern matching between the composite formulae and Radix Bupleuri Chinensis, which was one of the main ingredients of Xiaochaihu granules, was utilized to evaluate the preparation technology of Xiaochaihu granules via the indexes of the relative deviation of retention time （RT） and UV spectrum feature similarity of their corresponding peaks. Eleven matching peaks were found between Xiaochaihu granules and Radix Bupleuri Chinensis. However, the saikosaponin A and saikosaponin D, which are the important active components in Radix Bupleuri Chinensis, were not found in Xiaochaihu granules from any manufacturers. The peak areas of 11 characteristic peaks of Xiaochaihu granules samples formed a matrix of 11 × 15. The result of HCA showed that Xiaochaihu granules samples were divided into four kinds of category. Xiaochaihu granules samples from the same manufacturer were basically clustered of the same category. The results suggested that the saikosaponin A and saikosaponin D are prone to structural transformation under the condition of decoction and in the presence of the organic acidic components. These active components, existing in raw herb, might transform to a series of non-active secondary saikosaponin due to unfavourable preparation technology. So the conventional decoction-based preparation technology of Xiaochaihu granules might greatly affect its quality and therapeutic effectiveness. This study demonstrates that fingerprint-peak matching technology can not only be used for quality control of this composite formulae, but also provide some guidance for preparation technology of Xiaochaihu granules.

Identification and determination of the major constituents in traditional Chinese medicine Longdan Xiegan Pill by HPLC-DAD-ESI-MS

A novel and sensitive HPLC-UV method has been developed for the simultaneous determination of twelve major compounds in Longdan Xiegan Pill.The chemical profile of the twelve compounds,including geniposidic acid（1）,geniposide（2）,gentiopicroside（3）,liquiritin（4）,crocin（5）,baicalin（6）,wogonoside（7）,baicalein（8）,glycyrrhizic acid（9）,wogonin（10）,oroxylin A（11）and aristolochic acid A（12）,was acquired using high-performance liquid chromatography-diode array detector coupled with an electrospray tandem mass spectrometer（HPLC-DAD-ESI-MS）.The analysis was performed on a Dikma Platisil ODS C18 column（250 mm×4.6 mm,5 μm）with a gradient solvent system of acetonitrile-0.1% aqueous formic acid.The validation was carried out and the linearities（r〉0.9996）,repeatability（RSD〈1.8%）,intra-and inter-day precision（RSD〈1.3%）,and recoveries（ranging from 96.6% to 103.4%）were acceptable.The limits of detection（LOD）of these compounds ranged from 0.29 to 4.17 ng.Aristolochic acid A,which is the toxic ingredient,was not detected in all the batches of Longdan Xiegan Pill.Furthermore,hierarchical cluster analysis was used to evaluate the variation of the herbal prescription.The proposed method is simple,effective and suitable for the quality control of this traditional Chinese medicine（TCM）.

Quantification of six bioactive compounds in Zhenqi Fuzheng preparation by high-performance liquid chromatography coupled with diode array detector and evaporative light scattering detector

A simple and accurate high-performance liquid chromatography（HPLC）coupled with diode array detector（DAD）and evaporative light scattering detector（ELSD）was established for the determination of six bioactive compounds in Zhenqi Fuzheng preparation（ZFP）.The monitoring wavelengths were 254,275 and 328 nm.Under the optimum conditions,good separation was achieved,and the assay was fully validated in respect of precision,repeatability and accuracy.The proposed method was successfully applied to quantify the six ingredients in 31 batches of ZFP samples and evaluate the variation by hierarchical cluster analysis（HCA）,which demonstrated significant variations on the content of these compounds in the samples from different manufacturers with different preparation procedures.The developed HPLC method can be used as a valid analytical method to evaluate the intrinsic quality of this preparation.

Simultaneous quantification of 18 bioactive constituents in Ziziphus jujuba fruits by HPLC coupled with a chemometric method

The fruit of Ziziphus jujuba Mill., known as Hongzao(or Hong-Zao) in Chinese and cultivated in China for more than 4 000 years, has shown to have hepatoprotective property. In previous study, we have isolated and identified 27 known compounds from Z. jujuba fruits, which demonstrated anti-tumor activity. In this study, a high-performance liquid chromatography-diode-array detection-mass spectrometry(HPLC-DAD-MS) method was successfully applied to the simultaneous characterization and quantitation of 18 constituents in 28 Z. jujuba samples, comprised of 12 cultivars from different regions in China, by comparing their HPLC retention times, MS spectra, UV spectra, and NMR data with those of reference compounds. The quantitative method was validated with excellent linearity(R^(2 )> 0.999 1), preferable intra-and inter-day precisions(RSD < 2.78%), and good recoveries(94.96%–102.65%). The content variation of 18 compounds was analyzed by a chemometric method(hierarchical cluster analysis). In addition, these constituents showed protection against carbon tetrachloride(CCl_(4)) intoxicated Hep G2 cell lines by decreasing lactic dehydrogenase(LDH) levels. Results in this study illustrated that the content of all 18 compounds examined has significant difference and variation among cultivars and extracts. The proposed method can serve as a prerequisite for quality control of bioactive compounds in Z. jujuba products.

Identification of coastal water quality by multivariate statistical techniques in two typical bays of northern Zhejiang Province,East China Sea

The Hangzhou Bay（HZB） and Xiangshan Bay（XSB）, in northern Zhejiang Province and connect to the East China Sea（ECS） were considerably affected by the consequence of water quality degradation. In this study, we analyzed physical and biogeochemical properties of water quality via multivariate statistical techniques. Hierarchical cluster analysis（HCA） grouped HZB and XSB into two subareas of different pollution sources based on similar physical and biogeochemical properties. Principal component analysis（PCA） identified three latent pollution sources in HZB and XSB respectively and emphasized the importance of terrestrial inputs, coastal industries as well as natural processes in determining the water quality of the two bays. Therefore, proper measurement for the protection of aquatic ecoenvironment in HZB and XSB were of great urgency.

Highway Cost Prediction Based on LSSVM Optimized by Intial Parameters

The cost of highway is affected by many factors.Its composition and calculation are complicated and have great ambiguity.Calculating the cost of highway according to the traditional highway engineering estimation method is a completely tedious task.Constructing a highway cost prediction model can forecast the value promptly and improve the accuracy of highway engineering cost.This work sorts out and collects 60 sets of measured data of highway engineering;establishes an expressway cost index system based on 10 factors,including main route mileage,roadbed width,roadbed earthwork,and number of bridges;and processes the data through principal component analysis(PCA)and hierarchical cluster analysis.Particle swarm optimization(PSO)is used to obtain the optimal parameter combination of the regularization parameter c and the kernel function width coefficientin least squares support vector machine(LSSVM).Results show that the average relative and mean square errors of the PCA-PSO-LSSVM model are 0.79%and 10.01%,respectively.Compared with BP neural networks and unoptimized LSSVM model,the PCA-PSO-LSSVM model has smaller relative errors,better generalization ability,and higher prediction accuracy,thereby providing a new method for highway cost prediction in complex environments.

Rapid Quantification of Chinese Medicine Zuo Jin Pill via RRLC

A rapid method based on rapid resolution liquid chromatography（RRLC） coupled with a diode array detector（DAD） was developed for the simultaneous determination of six major constituents（magnoflorine,jatrorrhizine,coptisine,palmatine,berberine and evodiamine） in traditional Chinese medicine（TCM） Zuo Jin Pill（ZJP）.The satisfactory chromatographic separation was carried on an Eclipse Plus C18 column（1.8 μm i.d.,150 mm×4.6 mm） by linear gradient elution with a mobile phase of acetonitrile-acetate buffer.All the calibration curves show good linearity（r2 0.9998）.The detection limits and quantification limits ranged in 1.4―12 ng and 4.8―30 ng,respectively.The intra-and inter-day precisions were less than 0.63% with accuracies 98.60%―100.78%,and the recoveries were from 99.45% to 100.46%.Furthermore,hierarchical cluster analysis（HCA） was used to evaluate the variation of the herbal prescription.The results demonstrate that this analytical method is simple,sensitive and reliable for rapidly analyzing six major bioactive compounds in ZJPs and is helpful to comprehensively evaluating the quality of this TCM.

Study on Diseased Peanut Leaves by Fourier Transform Infrared Spectroscopy

[ Objective] The paper was to study the application d Fourier transform infrared spectroscopy （FTIR technology） in identification of peanut diseases. [Method] By using FFIR technology, combined with the methods of principal component analysis and hierarchical cluster analysis, the healthy leaves and three kinds of diseased leaves （ eereospera black spot, cercospora brown spot and web blotch） were identified in the paper. [ Result ] IR spectra of both diseased and healthy samples were similar, but tiny differences in wave-numbers and absorption intensities of peaks were observed in the range of 1 750 -800 cm-1. Significant differences were found in second derivative speclra in the range of 3 600 - 2 800 and 1 750 -650 cm-1 which were selected to perform principle component and hier- archical cluster analysis. Three principal components had the cumulative contribution rate of 94.9% ; the correct rate of principal component analysis for classifica- tion was 100% and the correct rate of hierarchical cluster analysis for identification reached 94.6%. [ Conclusion] Fourier transform infrared spectroscopy has a tmtential to be develoned as a nowerful means for identification of cren diseases.

An HPLC Fingerprint Identification of Dried Barks of Ilex rotunda and Ilex godajam

[Objectives] A simple and reliable HPLC fingerprint method was developed for the identification of dried barks of Ilex rotunda and I. godajam. [Methods] Nine batches of dried barks of I. rotunda,and seven batches of dried barks of I. godajam collected from different pharmacies and arboretums in different regions of China were used to establish fingerprints. The software Similarity Evaluation System of Chromatographic Fingerprints of Traditional Chinese Medicine( 2004 A Edition) was used to evaluate the fingerprints. [Results]The fingerprints of dried barks of I. rotunda and I. godajam were established. Methodological study met the technical requirements of fingerprints. The similarities of the fingerprints of dried barks of I. rotunda and I. godajam were all more than 0. 8 and 0. 9 respectively. There were 31 and 28 common peaks in I. rotunda and I. godajam,which could be classified into two clusters by principal component analysis( PCA) and hierarchical cluster analysis. [Conclusions] The feasibility and advantages of used HPLC fingerprints were verified,and the results indicated that the HPLC fingerprint as a characteristic distinguishing method combining similarity evaluation,principal component analysis and hierarchical cluster analysis can be successfully used to identify the authenticity of dried barks of I. rotunda and I. godajam.

Multivariate statistical analysis of chemical and stable isotopic data as indicative of groundwater evolution with reduced exploitation

Groundwater resources in the North China Plain(NCP)are undergoing tremendous changes in response to the operation of groundwater exploitation reduction(GWER)project.To identify groundwater evolution in this complex context,hierarchical cluster analysis(HCA)and principal component analysis(PCA)were combined to interpret an integrated dataset of stable isotopes and chemical data from four sampling campaigns in a pilot area of groundwater control.We proposed a novel HCA approach integrating stable isotopes and chemical signals,which successfully partitioned the groundwater samples into the unconfined and the confined water samples.Stable isotopic evidence showed that the lateral inflow and the surface water may contribute more to groundwater recharge in this region than local modern precipitation.The unconfined water's main hydrochemical types were Na type with mixed anions,and Na-Cl-SO_(4)type,while the confined water was mainly Na-Cl and Na-SO_(4)types.Geochemical processes mainly involved the dissolution/precipitation of halite,gypsum,Glauber's salt,feldspar,calcite and dolomite,as well as the cation exchange.PCA results showed that water-rock interaction(i.e.,salinity-based and alkalinity-based processes)predominated the hydrochemical evolution,along with local nitrate contamination resulting from fertilizers and domestic sewage.The GWER project regulated the natural evolution of unconfined water chemistry,and significantly reduced the unconfined water's salinity(mainly Na^(+),Mg^(2+),SO_(4)^(2-)).This may be attributed to upward leakage from low-salinity confined water at some parts of the aquifer.Additionally,insignificant changes in the confined water's salinity reflected that the impact of GWER on the confined aquifer was negligible.This study facilitates the groundwater classification effectively in the areas lack of geological data,and enhances the knowledge of groundwater chemical evolution in such a region where groundwater restoration is in progress,with important implications for groundwater sustainable management in similar basins worldwide.

Quality assessment of crude and processed Leonuri Fructus by chemical and color analysis combined with chemometric method

Objective： Crude Leonuri Fructus（CLF）, the fruits of the Leonurus japonicus Houtt, and processed Leonuri Fructus（PLF） by stir-baking as the important Chinese herbal medicines, have been used in China and other Asian countries for thousands of years. The objective of this research is to reveal the difference between CLF and PLF.Methods： The sensory technologies of the colorimetry, sensitive and validated HPLC-ELSD and GC combined with flame ionization detector（GC-FID） were employed to discriminate CLF and its processed product PLF. The color parameters of the samples were determined by colorimetric instrument CR-410. Moreover, the content of stachydrine and six fatty acids were determined by HPLC and GC. Subsequently,analysis of variance（ANOVA）, principal components analysis（PCA）, hierarchical cluster analysis（HCA）,and Kendall＇s correlation test were performed for data analysis.Results： The CLF and PLF were divided into two categories by PCA and HCA in terms of their component content and color. The results distinctly demonstrated significant changes in color and the content of indicative components between CLF and PLF.Conclusion： The study revealed that HPLC, GC, and colorimetric method in combination with chemometric method could be used as comprehensive quality evaluation for CLF and PLF.