Multivariate Analysis of Community Structure Variation of Plankton and Zoobenthos in Municipal Polluted River

[Objective] The plankton and macrobenthos samples in municipal polluted river were analyzed by different methods, so as to explore the method suitable for biological data analysis in heavy polluted area. [Method] Shannon-Wiener diversity index, cluster analysis of multivariate statistical analysis and MDS （Non-matric Multi- dimentional Scaling）analysis were used to analyze biological data of phytoplankton, zooplankton and Zoobenthos collected from the representative municipal polluted river in Pearl River Delta. The sediment samples were also collected to determine. Pb, Cd, Hg, Cr, As, Cu, Ni, Zn, as well as CODe, and NH3-N of porewater. Hakanson potential ecological risk index method was used to evaluate the ecological risk. [Re- suit] Shannon-Wiener diversity index analysis results can not effectively reflect the difference of pollution status of various stations in heavy polluted area; despite the presence of some problems, multivariate analysis method is superior to the Shannon-Wiener diversity index method in biological monitoring of heavy polluted river in the city. [Conclusion] The paper provided theoretical basis for biological data analysis in heavy polluted area.

Groundwater quality assessment using multivariate analysis,geostatistical modeling, and water quality index(WQI): a case of study in the Boumerzoug-El Khroub valley of Northeast Algeria

In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.

ASSESSMENT OF LOCAL INFLUENCE IN MULTIVARIATE ANALYSIS

A recent method for assessing the local influence is introduced by Cook(1986), in which the normal curvature of the influence graph based on the likelihood displacement is used to monitor the influence of small perturbation. Since then this method has been applied to various kind of models. However, the local influence in multivariate analysis is still an unexplored area because the influence for many statistics in multivariate analysis is not convenient to handle based on the Cook's likelihood displacement. In this paper, we suggest a method with a slight modification in Cook's approach to assess the local influence of small perturbation on a certain statistic. The local influence of the perturbation on eigenvalue and eigenvector of variance-covariance matrix in theoretical and sample version is assessed, some results for the other statistics in multivariate analysis such as generalized variance, canonical correlations are studied. Finally, two examples are analysed for illustration.

In-line spectroscopy combined with multivariate analysis methods for endpoint determination in column chromatographic adsorption processes for herbal medicine

Objective: In a chromatographic cycle, the adsorption process is a critical unit operation that has a significant impact on downstream processes and, ultimately, the quality of the final products. The development of a rapid method to determine the endpoints of adsorption processes in a large-scale manufacturing is of substantial importance for herbal medicine(HM) manufacturers.Methods: In this study, the adsorption of saponins on a macroporous resin column chromatograph, a critical unit operation in Panax notoginseng(Burkill) F.H.Chen injection manufacturing, was considered as an example. The evaluation results of in-line ultraviolet and visible spectra combined with various multivariate analysis methods, including the moving block standard deviation(MBSD), difference between the moving block average and the target spectrum(DMBA-TS), soft-independent modeling of class analogy(SIMCA), and partial least-squares discriminant analysis(PLS-DA), were compared.Results: MBSD was unsuitable for adsorption processes. The relative standard errors of prediction between the predicted and experimental endpoints were 13.2%, 4.67%, and 5.71% using DMBA-TS, SIMCA, and PLS-DA, respectively.Conclusions: Among the considered analysis methods, SIMCA and PLS-DA were more effective for endpoint determination. The results of this study provide a more comprehensive overview of the effectiveness of various multivariate analysis methods to facilitate the selection of the most suitable method. This study was also conducive to address the issues of the in-line detection of adsorption endpoints to guide practical HM manufacturing.

Hydrogeochemical processes and multivariate analysis for groundwater quality in the arid Maadher region of Hodna,northern Algeria

This study focused on water quality and hydrogeochemical processes(evolution,origin)in the Maadher region,central Hodna in Algeria.In recent decades,the excessive exploitation of this resource due to urbanization,irrigation,and the effect of climate change reaching the countries of northern Africa have caused a decline in water levels and hydrochemical changes in the aquifer.The sampling campaign in 2019 based on 13 physicochemical parameters was carried out on the water from 32 boreholes in the study area,compared to data archives of both sampling campaigns in 1967 and 1996.The result revealed that the groundwater as a whole has moderate freshwater quality,due to its total dissolved solids(TDS)content and other dissolved ions of concern(nitrate NO),which exceed WHO standards.In addition,Piper diagram indicates that the hydrochemical facies of sulfate–chloride–nitrate–calcium(SO–Cl–NO–Catype),which globally characterizes the study area and these elements are the dominant dissolved ions.Principal component analysis and hierarchical cluster analysis(HCA)methodologies are applied in order to define the major control factors that affect the hydrochemistry of Maadher plain.Three distinct water groups were found,illustrating a different evolution of salinity(EC and TDS).The HCA indicated an interesting cluster with a distinct contamination signature and most likely with significantly higher sulfate,chloride,and nitrate concentrations.Anthropogenic processes also play an important role in the study area.The water resource comes from Bousaada Wadi,the exchange at the aquifer depth and the agricultural practices contribute to the deterioration of the quality.

A New Fracability Evaluation Approach for Shale Reservoirs Based on Multivariate Analysis: A Case Study in Zhaotong Shale Gas Demonstration Zone in Sichuan, China

Fracability characterizes the effectiveness of hydraulic fracturing.The existing assessment methods cannot reflect the actual value of the effectiveness due to a lack of comprehensive consideration and neglect of the influences of engineering factors.This study aims to solve this problem by implementing geological static data and production dynamic data in multivariate analysis in Zhaotong shale gas demonstration zone.First,the reservoir quality index(RQI)was introduced to evaluate the exploration potential by integrating the geological parameters with gray relational analysis.Moreover,the differences in fracturing fluid types and proppant sizes were considered,and the operating parameters were normalized on the basis of the equivalence principle.Finally,the general reservoir fracability index(GRFI)was proposed based on a dimensioned processing of the various parameters.A case study was conducted to verify the accuracy and feasibility of this new approach.The results demonstrate that(1)the organic carbon and gas content are adjusted to contribute the most to the calculation of the RQI,while the effective porosity contributes the least;(2)the fracturing scale is the main operating parameter determining the fracability,which has the strongest correlation with the effectiveness of fracking;and(3)the GRFI has a positive correlation with shale gas production,and the lower limit of the GRFI of 2,000 corresponds to a daily production of 50,000 m3/d;this value is defined as the threshold value of a stripper well.The GRFI is consistent with the productivity trend of shale gas wells in the research block,which suggests that the new model is accurate and practical for well candidate selection.

Multivariate analysis of the risk for pulmonary complication after gastrointestinal surgery

AIM: To identify the risk factors for postoperative pulmonary complications (PPC) after gastrointestinal surgery. METHODS: A total of 1 002 patients undergoing gastrointestinal surgery in the Second Affiliated Hospital, Sun Yat-Sen University, during December 1999 and December 2003, were retrospectively studied. RESULTS: The overall incidence of PPC was 22.8% (228/ 1 002). Multivariate logistic analysis identified nine risk factors associated with PPC, including age odds ratio (OR = 1.040) history of respiratory diseases (OR = 2.976), serum albumin (OR = 0.954), chemotherapy 2 wk before operation (OR = 3.214), volume of preoperative erythrocyte transfusion (OR = 1.002), length of preoperative antibiotic therapy (OR = 1.072), intraoperative intratracheal intubation (OR = 1.002), nasogastric intubation (OR = 1.050) and postoperative mechanical ventilation (OR = 1.878). Logistic regression equation for predicting the risk of PPC was P(1) =q/[1+e-(-3.488+0.039×+1.090×Rd+0.001×Rbc-0.0047×Alb+0.002×Lii+ 0.049×Lni+0.630×Lmv+0.070×Dat+1.168×a)].

Multivariate analysis of serum surface-enhanced Raman spectroscopy of liver cancer patients

Early diagnosis of liver cancer plays a significant role in reducing its high mortality.In this preliminary study,the feasibility of using serum surface-enhanced Raman spectroscopy(SERS)to identify liver cancer was studied.Serum samples were obtained from liver cancer patients and healthy controls.The differences between the SERS spectra of pre-operation and postoperation of liver cancer patients were also analyzed.The general shape and trend of SERS spectra of health control and liver cancer patients were similar.Multivariate analysis,e.g.,PLSSVM,might be useful for the discrimination of serum SERS spectra of pre-operation and post-operation.

Multivariate analysis for ordination and comparison of size of Artemia cysts

It is known that the biometrics of brine shrimp cysts is of strain inherent. The analysis and comparison of the cyst charcters for the identification of unknown cysts from different geqraphical origin become mpible. In this paper, multivallate methods, mainly Principle Component Analysis (PCA) and Nonmetric Multi-dimensional Scaling (MDS), are used for the purpose. od results are gained with the analysis of the published data and some row data from cyst sizes. It shows that multivariate methods can cluster the similar characteristics of batch cysts and make out impure or mingled cysts of different origin. Amng others, MDS, with row data from the cyst measurement, can be easily used for the analysis of cyst ordination and comparison. The result demonstrates that the cysts of Chinese parthenopnetic brine shrimp are well discriminated by their geographic locations along the coastal China with larger size disttibuting in the south.

The Method for Optimum Estimation of COVID-19 Variant Type Virus Infection Status Analysis by the Multivariate Analysis Considering the Environmental Variability Impact in Japan

Currently, the estimated value of the effective reproduction number (ERN), which is an index for grasping the COVID-19 infection status, is used for important planning and evaluation of infection prevention measures. Since ERN in the Sequential SIR model fluctuates in multiple dimensions due to changes in the surrounding environment, it is difficult to set the appropriate accuracy of the uncertainty region of the estimated data. The challenge in this study is to build a mathematical model of infectious disease according to the characteristics and data characteristics of the infectious disease and select an appropriate estimation method. Highly accurate quantitative research that analyzes the validity of “how infectious diseases prevail” from an academic point of view is the key to prediction and estimation in appropriate infection situation analysis. In this study, we adopted a statistical multivariate analysis method (T method) that enables evaluation and prediction of important factors related to ERN estimation and analysis of phenomena that change in real time (time series analysis). It was clarified that it is possible to estimate with higher accuracy by applying the T method to the estimated value of ERN by the current SIR mathematical model.

Multivariate Analysis of Femoral Adductor Muscle Contracture after Total Hip Arthroplasty in Patients with Avascular Necrosis of Femoral Head

Objective:This study is to investigate the nisk factors of femoral head contracture after total hip arthroplasty(THA)in patients with avascular necrosis of femoral head.Methods:Retrospective analysis was perfomed in 361 cases of femoral head necrosis patients taking THA fom September 2016 to December 2017.A total of 179 patents with no significant preoperative adductor muscle contraction were finally enrolled in this study.These 179 patients were further divided into two groups:contracture group(64 cases)and noncompaction group(115 cases).The chi-square test was used to compare the differences between the two groups.Risk factors were identifed by logistic regession analysis.Results:of the patients included,64 patients (35.75%)developed into end adductor muscle contracture.There were signuificant differences in limb shortening.surgical history,whether taction,surgical approach,surgical methods,and fumctional training between the two goups(P<0.05).Logistic regression analysis showed that shortness of extremity,sugical approach,effective taction,surgical history,and etiology were the factors affecting femoral head contracture after THA in patients with avascular necrosis of femoral head.Conclusions:Preoperative traction therapy,surgical methods,and postoperative functional training are the factors that affect the adductor muscle contraction after THA.

Factors contributing to myasthenic crisis after thymectomy-a multivariate analysis study

Objective To evaluate the risk factors of myasthenic crisis (MC) after thymectomy for myasthenia gravis (MG) . Methods A retrospective study was conducted in 84 patients with MG from July 1995 to December 2009. The following factors were evaluated: sex,age,history of preoperative myasthenic crisis,Ossermen classification, steroid hormones use and anticholinesterase drugs before operation,operation methods,operation time,thymoma,

Analysis of optical axis deviation caused by structural stiffness in equatorial telescopes

The impact of structural stiffness on optical axis deviation poses a significant challenge in the design of equatorial telescope structures.A comprehensive analysis during the design process can reduce the reliance of a telescope on advanced control technologies,thereby improving its economic feasibility.Although full-system finite element analyses are reliable,they are encumbered by significant time requirements and limitations in covering all possible telescope orientations.Therefore,we propose an efficient and comprehensive analytical method to evaluate the optical axis deviation of equatorial telescopes across a full range of angles.To address the challenge of ensuring that the analysis covers all possible positions of an equatorial telescope,based on a model from SiTian project,we analyze the optical axis deviations caused by the fork arm at 25 different angles and then use fitting methods to obtain results for all angles.Based on the analysis results of the optical axis deviation caused by the stiffness of the optical tube in the horizontal position,we derive the results for the tube at any position using geometric relationships.Finally,we calculate the coupling factors and combine these impacts.Furthermore,we identify six discrete feature points to reflect possible telescope orientations and conduct comprehensive finite element analyses.The results are in alignment with those acquired through a comprehensive computational approach.

Multivariate analysis by Cox Proportional Hazards Model on pro gnoses of patients with bile duct carcinoma after resection

OBJECTIVE: To evaluate the influence of various clinicopathologic factors on the survival of patients with bile duct carcinoma after curative resection. METHODS: A retrospective analysis was performed on 86 cases of bile duct carcinoma treated from January 1981 to September 1995. Fifteen clinicopathologic factors that could possibly influence survival were selected. A multivariate analysis of these individuals was performed using the Cox Proportional Hazards Model. RESULTS: The overall cumulative survival rate was 73% for 1 year, 32% for 3 years and 19% for 5 years. The results of univariate analysis showed that the major significant prognostic factors for influencing survival of these patients were type of histological lesion, lymph node metastasis, pancreatic invasion, duodenal invasion, perineural invasion, macroscopic vessel involvement, resected surgical margin and depth of cancer invasion (P

Analysis of fatty acid composition of sea cucumber Apostichopus japonicus using multivariate statistics

Fatty acids(FAs) provide energy and also can be used to trace trophic relationships among organisms.Sea cucumber Apostichopus japonicus goes into a state of aestivation during warm summer months.We examined fatty acid profiles in aestivated and non-aestivated A.japonicus using multivariate analyses(PERMANOVA,MDS,ANOSIM,and SIMPER).The results indicate that the fatty acid profiles of aestivated and non-aestivated sea cucumbers differed significantly.The FAs that were produced by bacteria and brown kelp contributed the most to the differences in the fatty acid composition of aestivated and nonaestivated sea cucumbers.Aestivated sea cucumbers may synthesize FAs from heterotrophic bacteria during early aestivation,and long chain FAs such as eicosapentaenoic(EPA) and docosahexaenoic acid(DHA) that produced from intestinal degradation,are digested during deep aestivation.Specific changes in the fatty acid composition of A.japonicus during aestivation needs more detailed study in the future.

Multivariate analysis of subjective evaluation of indoor lighting environment

Though subjective feelings affected by lighting have been studied a lot,multivariate experimental studies are lacking in this research field.Central composite rotatable design(CCRD)was applied to investigate the influence of illuminance,correlated color temperature(CCT)and illuminance uniformity on satisfaction in this study.A series of subject experiments were carried out and polynomial regression models of luminous satisfaction for different activity scenarios were generated.Illuminance and CCT affected the satisfaction significantly in visual task scenarios,and the effect of them was independent with each other,which was demonstrated by the regression model(R2=0.89).The variation of luminous satisfaction in general activity scenarios cannot be fully explained by the three investigated factors.The results contributed to the knowledge of multivariate analysis of luminous environment and indicated that much could be expected referring to the application of CCRD in this field.

Subnanometer-resolved chemical imaging via multivariate analysis of tip-enhanced Raman maps

Tip-enhanced Raman spectroscopy(TERS)is a powerful surface analysis technique that can provide subnanometer-resolved images of nanostructures with site-specific chemical fingerprints.However,due to the limitation of weak Raman signals and the resultant difficulty in achieving TERS imaging with good signal-to-noise ratios(SNRs),the conventional single-peak analysis is unsuitable for distinguishing complex molecular architectures at the subnanometer scale.Here we demonstrate that the combination of subnanometer-resolved TERS imaging and advanced multivariate analysis can provide an unbiased panoramic view of the chemical identity and spatial distribution of different molecules on surfaces,yielding high-quality chemical images despite limited SNRs in individual pixel-level spectra.This methodology allows us to exploit the full power of TERS imaging and unambiguously distinguish between adjacent molecules with a resolution of~0.4 nm,as well as to resolve submolecular features and the differences in molecular adsorption configurations.Our results provide a promising methodology that promotes TERS imaging as a routine analytical technique for the analysis of complex nanostructures on surfaces.

Physicochemical Properties of Banana Flour as Influenced by Variety and Stage of Ripeness： Multivariate Statistical Analysis

Physicochemical properties of banana flour （BF） were studied in two varieties （Cavendish and Dream） and two stages of ripeness （green and ripe）. BF＇s were analyzed for pH, total soluble solids （TSS）, water holding capacity （WHC） and oil holding capacity （OHC） at 40℃, 60 ℃ and 80 ℃, color values L＊, a＊ and b＊, back extrusion force and viscosity. Physicochemical data were analyzed by Multivariate Analysis of Variance, discriminant analysis and cluster analysis. All statistical analyses showed that physicochemical properties of BF prepared from different variety and stage of ripeness were different from each other. Viscosity, WHC40, WHC60 and TSS were recommended methods for discrimination between banana flour prepared from the two varieties, whilst viscosity, WHC60 and WHC80 were suggested for differentiation of banana flour prepared using green and ripe banana.

Comparative Multivariate Analysis of Codon and Amino Acid Usage in Three Leishmania Genomes

Multivariate analysis of codon and amino acid usage was performed for three Leishmania species, including L. donovani, L. infantum and L. major. It was revealed that all three species are under mutational bias and translational selection. Lower GC12 and higher GC3s in all three parasites suggests that the ancestral highly expressed genes （HEGs）, compared to lowly expressed genes （LEGs）, might have been rich in AT-content. This also suggests that there must have been a faster rate of evolution under GC-bias in LEGs. It was observed from the esti- mation of synonymous/non-synonymous substitutions in HEGs that the HEG dataset of L. donovani is much closer to L. major evolutionarily. This is also supported by the higher ds value as compared to ds between L. donovani and L. major, suggesting the conservation of synonymous codon positions between these two species and the role of translational selection in shaping the composition of protein-coding genes.