Development of a Web-Based GIS of Flood Zones in the Municipality of Ouagadougou in Burkina Faso

This document describes the creation of an informative Web GIS aimed at mitigating the impacts of flooding in the municipality of Ouagadougou, in Burkina Faso, a region that is highly sensitive to climate change. Burkina Faso, which is undergoing rapid urbanization, faces major natural threats, particularly flooding, as demonstrated by the severe floods of 2009 that caused loss of life, injury, structural damage and economic losses in Ouagadougou. The aim of this research is to develop a web map highlighting the municipality’s flood-prone areas, with a view to informing and raising awareness of flood risk reduction. Using the Leaflet JavaScript mapping library, the study uses HTML, CSS and JavaScript to implement web mapping technology. Data on Ouagadougou’s flood zones is generated by a multi-criteria analysis combining Saaty’s AHP method and GIS in QGIS, integrating seven (7) parameters including hydrography, altitude, slope, rainfall, soil types, land use and soil moisture index. QGIS processes and maps the themes, PostgreSQL with PostGIS serves as the DBMS and GeoServer functions as the map server. The Web GIS platform allows users to visualize the different flood risks, from very low to very high, or the high-risk areas specific to Ouagadougou. The AHP calculations classify the municipality into five flood vulnerability zones: very low (24.48%), low (27.93%), medium (23.01%), high (17.11%) and very high (7.47%). Effective risk management requires communication and awareness-raising. This online mapping application serves as a tool for communication, management and flood prevention in Ouagadougou, helping to mitigate flood-related natural disasters.

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.

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.

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.

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.

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.

Optimum Designing of Gas Distribution Networks of Ilam Province by Using GIS Network and Spatial Analysis

Undoubtedly, pipeline transport is considered as significant economical artery of country and national valuable resources, so it is necessary to use latest technologies, major standards and instructions and the best human resources in designing, operation and supervision in construction and also protection of it. Also, all authorities and involved of construction and operation of gas industries installation should observe safety criteria, health and environment and aware of them ever. In fact, in designing of these programs, in addition to technical and economical points, environmental characteristics should be considered in order to their construction has minimum damage to environment. On the other hand, common and traditional approaches of pipeline routing are based on using costly and time-consuming methods. In these methods, it is not easily to use all effective parameters in determining optimum way. According to capability of analysis of network spatial information systems in incorporation of spatial data, for using all effective parameters in routing, this environment is used, therefore weighted overlay analysis (Boleyn, index and fuzzy) and shortest path are modeled for finding optimum path of pipeline in GIS environment.

Safety Risk Assessment of Overturning Construction of Towering Structure Based on Cloud Matter–Element Coupled Model

Rapid urbanization has led to a surge in the number of towering structures,and overturning is widely used because it can better accommodate the construction of shaped structures such as variable sections.The complexity of the construction process makes the construction risk have certain randomness,so this paper proposes a cloudbased coupled matter-element model to address the ambiguity and randomness in the safety risk assessment of overturning construction of towering structures.In the pretended model,the digital eigenvalues of the cloud model are used to replace the eigenvalues in the matter–element basic element,and calculate the cloud correlation of the risk assessment metrics through the correlation algorithm of the cloud model to build the computational model.Meanwhile,the improved hierarchical analysis method based on the cloud model is used to determine the weight of the index.The comprehensive evaluation scores of the evaluation event are then obtained through the weighted average method,and the safety risk level is determined accordingly.Through empirical analysis,(1)the improved hierarchical analysis method based on the cloud model can incorporate the data of multiple decisionmakers into the calculation formula to determine theweights,which makes the assessment resultsmore credible;(2)the evaluation results of the cloud-basedmatter-element coupledmodelmethod are basically consistent with those of the other two commonly used methods,and the confidence factor is less than 0.05,indicating that the cloudbased physical element coupled model method is reasonable and practical for towering structure overturning;(3)the cloud-based coupled element model method,which confirms the reliability of risk level by performing Spearman correlation on comprehensive assessment scores,can provide more comprehensive information of instances compared with other methods,and more comprehensively reflects the fuzzy uncertainty relationship between assessment indexes,which makes the assessment results more realistic,scientific and reliable.

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.

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.

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.

Fuzzy color morphological sieves

To solve the problems that exist in the color morphological sieves, a new fuzzy color morphological sieve is proposed.The method adopts color fuzzy model to define extrema and selects more rational regional merging way to produce better results.It can deal with the maxima or the minima areas respectively and the approach is simple and agile in design.The color fuzzy model and the steps of the algorithm are discussed.The evaluation of the performance shows the new method can produce the best synthetical performance.

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 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.

Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model:A case study from an agro-urban region of Pakistan

In Punjab(Pakistan),the increasing population and expansion of land use for agriculture have severely exploited the regional groundwater resources.Intensive pumping has resulted in a rapid decline in the level of the water table as well as its quality.Better management practices and artificial recharge are needed for the development of sustainable groundwater resources.This study proposes a methodology to delineate favorable groundwater potential recharge zones(FPRI)by integrating maps of groundwater potential recharge index(PRI)with the DRASTIC-based groundwater vulnerability index(VI).In order to evaluate both indexes,different thematic layers corresponding to each index were overlaid in ArcGIS.In the overlay analysis,the weights(for various thematic layers)and rating values(for sub-classes)were allocated based on a review of published literature.Both were then normalized and modified using the analytical hierarchical process(AHP)and a frequency ratio model respectively.After evaluating PRI and FPRI,these maps were validated using the area under the curve(AUC)method.The PRI map indicates that 53%of the area assessed exists in very low to low recharge zones,22%in moderate,and 25%in high to excellent potential recharge zones.The VI map indicates that 38%of the area assessed exists in very low to low vulnerability,33%in moderate,and 29%in high to very high vulnerability zones.The FPRI map shows that the central region of Punjab is moderately-to-highly favorable for recharge due to its low vulnerability and high recharge potential.During the validation process,it was found that the AUC estimated with modified weights and rating values was 79%and 67%,for PRI and VI indexes,respectively.The AUC was less when evaluated using original weights and rating values taken from published literature.Maps of favorable groundwater potential recharge zones are helpful for planning and implementation of wells and hydraulic structures in this region.

Teamwork and Physician Burnout: The Moderating Role of Perceived Organisational Support

Burnout is an important issue which has attracted the attention of physicians and health practitioners. Several studies have reported the negative effect of physician burnout and the adverse effect it has on the individual and health institutions. This study therefore examined the moderating effect of perceived organizational support on the relationship between teamwork and physician burnout in the Chinese context. Using a survey data consisting of a sample of physicians from hospitals within the Jiangsu Province of China, we estimated three models in a hierarchical framework and identified that in the presence of respondent’s demographic characteristics as control variables, perceived organizational support, play a very vital role in improving teamwork while reducing burnout among physicians.

Research on Global Higher Education Quality Based on BP Neural Network and Analytic Hierarchy Process

Having a universal, fair, democratic and practical higher education system plays a particularly important role in the future development of the country. However, the higher education system in various countries is uneven. It is of great significance to establish a general evaluation system for the development of global education. In this paper, 23 indicators are preliminarily selected from the education data of Universitas 21 and Global Statistical Yearbook. After the gray correlation analysis, 12 indicators were selected. On the one hand, principal component analysis is used to reduce the dimension of these 12 indicators in 50 countries, and the first four principal components with cumulative contribution rate of 99% are finally selected as the input parameters of BP neural network. On the other hand, 12 indicators are divided into four aspects as the standard of scheme decision-making. Finally, a higher education quality evaluation and decision-making model based on BP neural network and analytic hierarchy process are established. Then eight countries are selected to use the model to evaluate their current higher education quality. Based on the input and evaluation results of the four aspects of higher education in various countries, the analytic hierarchy process is used to make program decision, and several improvement suggestions are put forward for the current education policies of various countries.