The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.Howev...The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content.展开更多
Although the Mehdiabad zinc-lead deposit is one of the most well-known deposits in the central Iran structural zone,the genesis of the deposit remains controversial.The host rock of the ore is a dolomitic limestone of...Although the Mehdiabad zinc-lead deposit is one of the most well-known deposits in the central Iran structural zone,the genesis of the deposit remains controversial.The host rock of the ore is a dolomitic limestone of the Lower Cretaceous Taft Formation.In the two main orebodies of the deposit,which includes the Black Hill and East Ridge ore zones,the oxide and sulfide ores are observed at the surface and at depth,respectively.The elements Zn,Fe,Mn and Mg are more abundant in the East Ridge ore zone(in both sulfide and oxide ores),with Ba,Pb,Ag and Cu being more abundant in the Black Hill oxide ore.Based on the distribution of elements and their correlation with each other in these ore zones,the elements are divided into three general groups,that of terrigenous elements,chemically-deposited elements and oreforming(hydrothermally deposited)elements,a division that is supported by the results of factor analyses.The spatial distribution of elements is jointly affected by contact with host rocks,the boundary of oxide-sulfide ores and fault zones.The main factors governing the distribution of elements are the mechanical transfer of detrital sediments,chemical sedimentation,transfer by hydrothermal fluids,oxidation and surface dissolution,all of which affected the spatial distribution of elements.The ore-forming elements are mostly affected by hydrothermal fluids and oxidation.This study not only provides additional information about the genesis of the Mehdiabad deposit,but also could assist in the exploitation of ore and further exploration purposes.The results of this study can aid in the exploration and exploitation of the Mehdiabad deposit and similar deposits in the region.展开更多
Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundati...Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation.展开更多
The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum S...The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan.展开更多
BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of post...BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of postoperative nursing interventions,particularly pain management,is crucial for reducing such complications.AIM To investigate the effects of enhanced recovery nursing on CV complications after gastrointestinal surgery in ICU patients and associated risk factors.METHODS A retrospective analysis was conducted on 78 adult patients who underwent gastrointestinal surgery in the ICU of our hospital between February 2023 and September 2024.Among them,40 patients received standard care(control group),while 38 received enhanced recovery nursing(observation group).We compared the incidence of CV complications and nursing satisfaction between the two groups.Patients were divided into CV complication and non-complication groups based on complication occurrence,and logistic regression analysis was used to identify risk factors.RESULTS In the control and observation groups,the incidence of CV complications was 30.0%(12/40)and 18.4%(7/38),with a nursing satisfaction rate of 70.0%(28/40)and 92.1%(35/38),respectively.The postoperative pain score at 14 days was significantly lower in the observation group(0.27±0.15)compared to the control group(1.65±0.37),with all differences being statistically significant(P<0.05).Univariate analysis indicated significant differences in age,body mass index,hypertension,diabetes,smoking history,history of heart failure,and previous myocardial infarction(P<0.05).Multivariate logistic regression identified heart failure history,previous myocardial infarction,age,hypertension,and diabetes as independent risk factors,with odds ratios of 1.195,1.528,1.062,1.836,and 1.942,respectively(all P<0.05).CONCLUSION Implementing enhanced recovery nursing for ICU patients after gastrointestinal surgery is beneficial in reducing the incidence of CV complications and improving nursing satisfaction.展开更多
The concept, fundamental theory, analytical steps and formulae of grey relational analysis (GRA)-a new statistical method or multifactorial analysis in the field of medicine were introduced. GRA of grouping sequence t...The concept, fundamental theory, analytical steps and formulae of grey relational analysis (GRA)-a new statistical method or multifactorial analysis in the field of medicine were introduced. GRA of grouping sequence that is applied to medical study was built by the authors. An example was given to demonstrate it. The superiority of GRA was recounted briefly.展开更多
The operating data of an enterprise has very positive reference significance for controlling risks, improving systems and processes, and enhancing efficiency and effectiveness in the development of an enterprise. If a...The operating data of an enterprise has very positive reference significance for controlling risks, improving systems and processes, and enhancing efficiency and effectiveness in the development of an enterprise. If an enterprise can master its operating status in the form of a data report, the relevant statistical data must take into account timeliness, accuracy, standardization and completeness. The following discusses various factors that restrict the quality of statistical data, and then puts forward management measures to improve the quality of statistical data.展开更多
Understanding the controlling factor of groundwater quality can enhance promoting sustainable development of groundwater resources. To this end, multivariate statistical analysis（MA） and hydrochemical analysis were ...Understanding the controlling factor of groundwater quality can enhance promoting sustainable development of groundwater resources. To this end, multivariate statistical analysis（MA） and hydrochemical analysis were introduced in this work. The results indicate that the canonical discriminant function with 7 parameters was established using the discriminant analysis（DA） method, which can afford 100% correct assignation according to the 3 different clusters（good water（GW）, poor water（PW）, and very poor water（VPW）） obtained from cluster analysis（CA）. According to factor analysis（FA）, 8 factors were extracted from 25 hydrochemical elements and account for 80.897% of the total data variance, suggesting that groundwater with higher concentrations of sodium, calcium, magnesium, chloride, and sulfate in southeastern study area are mainly affected by the natural process; the higher level of arsenic and chromium in groundwater extracted from northwestern part of study area are derived by industrial activities; domestic and agriculture sewage have important contribution to copper, iron, iodine, and phosphate in the northern study area. Therefore, this work can help identify the main controlling factor of groundwater quality in North China plain so as to make better and more informed decisions about how to achieve groundwater resources sustainable development.展开更多
Wastewater dissolved organic matter （DOM） from different processing stages of a sewage treatment plant in Xiamen was characterized using fluorescence and absorption spectroscopy. Parallel factor analysis modeling of...Wastewater dissolved organic matter （DOM） from different processing stages of a sewage treatment plant in Xiamen was characterized using fluorescence and absorption spectroscopy. Parallel factor analysis modeling of excitation-emission matrix spectra revealed five fluorescent components occurring in sewage DOM： one protein-like （C1）, three humic-like （C2, C4 and C5） and one xenobiotic-like （C3） components. During the aerated grit chamber and primary sedimentation tank stage, there was only a slight decrease in fluorescence intensity and the absorption coefficient at 350 nm （a 350 ）. During the second aeration stage, high concentration of protein-like and short-wavelength-excited humic-like components were significantly degraded accompanied by significant loss of DOC （80%） and a 350 （30%）, indicating that C1 and C2 were the dominant constituents of sewage DOM. As a result, long-wavelength- excited C4 and C5 became the dominant humic-like components and the DOM molecular size inferred from the variation of spectral slope S （300–650 nm） and specific absorption （a 280 /DOC） increased. Combination use of F max of C1 and the ratio of C1/C5, or a 350 may provide a quantitative indication for the relative amount of raw or treated sewage in aquatic environment.展开更多
With the rapid growth of economy in China, people＇s living standard has been generally improved, and people＇s requirements on the quality and quantity of infrastructures like transportation convenience, city greenin...With the rapid growth of economy in China, people＇s living standard has been generally improved, and people＇s requirements on the quality and quantity of infrastructures like transportation convenience, city greening have become higher and higher, which requires the government to attach importance to these livelihood is- sues. Based on the China Statistical Yearbook, 6 target factors of 31 provinces and cities in China were conducted with factor analysis, and the conditions of the infras- tructures in the 31 provinces and cities were judged and evaluated through the ex- traction of common factors and the calculation of these common factors, and corre- sponding suggestions were proposed with the aim to improve the infrastructures in China.展开更多
[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was ...[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was analyzed by three models respectively： Finlay and Wilkinson model： the additive main effects and multiplicative interaction （AMMI） model and linear regression-principal components analysis （LR- PCA） model, so as to compare the models. [Result] The Finlay and Wilkinson model was easier, but the analysis of the other two models was more comprehensive, and there was a bit difference between the additive main effects and multiplicative inter- action （AMMI） model and linear regression-principal components analysis （LR-PCA） model. [Conclusion] In practice, while the proper statistical method was usually con- sidered according to the different data, it should be also considered that the same data should be analyzed with different statistical methods in order to get a more reasonable result by comparison.展开更多
This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of glo...This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.展开更多
Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the t...Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the two methods is that the components of PCA are still dependent while ICA has no orthogonality constraint and its latentvariables are independent. Process monitoring with PCA often supposes that process data or principal components is Gaussian distribution. However, this kind of constraint cannot be satisfied by several practical processes. To ex-tend the use of PCA, a nonparametric method is added to PCA to overcome the difficulty, and kernel density estimation （KDE） is rather a good choice. Though ICA is based on non-Gaussian distribution intormation, .KDE can help in the close monitoring of the data. Methods, such as PCA, ICA, PCA.with .KDE（KPCA）, and ICA with KDE,（KICA）, are demonstrated and. compared by applying them to a practical industnal Spheripol craft polypropylene catalyzer reactor instead of a laboratory emulator.展开更多
Structural Health Monitoring(SHM) suggests the use of machine learning algorithms with the aim of understanding specific behaviors in a structural system. This work introduces a pattern recognition methodology for ope...Structural Health Monitoring(SHM) suggests the use of machine learning algorithms with the aim of understanding specific behaviors in a structural system. This work introduces a pattern recognition methodology for operational condition clustering in a structure sample using the well known Density Based Spatial Clustering of Applications with Noise(DBSCAN) algorithm.The methodology was validated using a data set from an experiment with 32 Fiber Bragg Gratings bonded to an aluminum beam placed in cantilever and submitted to cyclic bending loads under 13 different operational conditions(pitch angles). Further, the computational cost and precision of the machine learning pipeline called FA + GA-DBSCAN(which employs a combination of machine learning techniques including factor analysis for dimensionality reduction and a genetic algorithm for the automatic selection of initial parameters of DBSCAN) was measured. The obtained results have shown a good performance, detecting 12 of 13 operational conditions, with an overall precision over 90%.展开更多
Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental...Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, the elemental contents of M. concha from five sampling points in Rushan Bay have been determined by means of inductively coupled plasma optical emission spectrometry(ICP-OES). Based on the contents of 14 inorganic elements(Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, and Zn), the inorganic elemental fingerprint which well reflects the elemental characteristics was constructed. All the data from the five sampling points were discriminated with accuracy through hierarchical cluster analysis(HCA) and principle component analysis(PCA), indicating that a four-factor model which could explain approximately 80% of the detection data was established, and the elements Al, As, Cd, Cu, Ni and Pb could be viewed as the characteristic elements. This investigation suggests that the inorganic elemental fingerprint combined with multivariate statistical analysis is a promising method for verifying the geographical origin of M. concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.展开更多
To clarify the importance of various influencing factors on asphalt pavement rutting deformation and determine a screening method of model indicators,the data of the RIOHTrack full-scale track were examined using the ...To clarify the importance of various influencing factors on asphalt pavement rutting deformation and determine a screening method of model indicators,the data of the RIOHTrack full-scale track were examined using the factor analysis method(FAM).Taking the standard test pavement structure of RIOHTrack as an example,four rutting influencing factors from different aspects were determined through statistical analysis.Furthermore,the common influencing factors among the rutting influencing factors were studied based on FAM.Results show that the common factor can well characterize accumulative ESALs,center-point deflection,and temperature,besides humidity,which indicates that these three influencing factors can have an important impact on rutting.Moreover,an empirical rutting prediction model was established based on the selected influencing factors,which proved to exhibit high prediction accuracy.These analysis results demonstrate that the FAM is an effective screening method for rutting prediction model indicators,which provides a reference for the selection of independent model indicators in other rutting prediction model research when used in other areas and is of great significance for the prediction and control of rutting distress.展开更多
AIM:To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction.METHODS:One hundred ...AIM:To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction.METHODS:One hundred and ninety-one patients presenting to a Gastroenterology clinic with constipation and 32 constipated patients responding to a newspaper advertisement completed a 53-item,wide-ranging selfreport questionnaire.One hundred of these patients had colonic transit measured scintigraphically.Factor analysis determined whether constipation-related symptoms grouped into distinct aspects of symptomatology.Cluster analysis was used to determine whether indi-vidual patients naturally group into distinct subtypes.RESULTS:Cluster analysis yielded a 4 cluster solution with the presence or absence of pain and laxative unresponsiveness providing the main descriptors.Amongst all clusters there was a considerable proportion of patients with demonstrable delayed colon transit,irritable bowel syndrome positive criteria and regular stool frequency.The majority of patients with these characteristics also reported regular laxative use.CONCLUSION:Factor analysis identified four constipation subgroups,based on severity and laxative unresponsiveness,in a constipated population.However,clear stratification into clinically identifiable groups remains imprecise.展开更多
The seismic intensities, lithologic characteristics and terrain features from a 3000 km2-region near the epicenter of the Lushan earthquake are used to analyze earthquake-induced geological disaster. The preliminary r...The seismic intensities, lithologic characteristics and terrain features from a 3000 km2-region near the epicenter of the Lushan earthquake are used to analyze earthquake-induced geological disaster. The preliminary results indicate that secondary effects of the earthquake will affect specific areas, including those with glutenite and carbonate bedrock, a seismic intensity of IX, slopes between 40° and 50°, elevations of less than 2500 m, slope change rates between 20° and 30°, slope curvatures from - 1 to -0.5 and 0. 5 to 1, and relief between 50 and 100 m. Regions with susceptibility indices greater than 0.71 are prone to landslides and collapses. The secondary features are mainly distributed on both sides of the ridges that extend from Baosheng to Shuangshi and from Baosheng to Longxing. Other features are scattered on both sides of the ridges that extend from Qishuping to Baosheng and from Masangping to Lingguan. The distribution of the earthquake-related features trends in the NE direction, and the area that was most affected by the Lushan earthquake covers approximately 52.4 km^2.展开更多
Henry Hub as an important transaction hub for natural gas sets the gas price standard in the USA. In this paper, the factors influencing Henry Hub natural gas prices are analyzed, and the major factors determining the...Henry Hub as an important transaction hub for natural gas sets the gas price standard in the USA. In this paper, the factors influencing Henry Hub natural gas prices are analyzed, and the major factors determining the price levels in the period between January 1997 and December 2016 are studied. It is found that economic conditions, total energy demand, US dollar exchange rate and gas consumption are the major factors. The mechanism of each factor influencing the Henry Hub natural gas price is also explored in the paper.展开更多
Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- a...Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.展开更多
基金financially supported by the National Natural Science Foundation of China(No.52174297).
文摘The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content.
文摘Although the Mehdiabad zinc-lead deposit is one of the most well-known deposits in the central Iran structural zone,the genesis of the deposit remains controversial.The host rock of the ore is a dolomitic limestone of the Lower Cretaceous Taft Formation.In the two main orebodies of the deposit,which includes the Black Hill and East Ridge ore zones,the oxide and sulfide ores are observed at the surface and at depth,respectively.The elements Zn,Fe,Mn and Mg are more abundant in the East Ridge ore zone(in both sulfide and oxide ores),with Ba,Pb,Ag and Cu being more abundant in the Black Hill oxide ore.Based on the distribution of elements and their correlation with each other in these ore zones,the elements are divided into three general groups,that of terrigenous elements,chemically-deposited elements and oreforming(hydrothermally deposited)elements,a division that is supported by the results of factor analyses.The spatial distribution of elements is jointly affected by contact with host rocks,the boundary of oxide-sulfide ores and fault zones.The main factors governing the distribution of elements are the mechanical transfer of detrital sediments,chemical sedimentation,transfer by hydrothermal fluids,oxidation and surface dissolution,all of which affected the spatial distribution of elements.The ore-forming elements are mostly affected by hydrothermal fluids and oxidation.This study not only provides additional information about the genesis of the Mehdiabad deposit,but also could assist in the exploitation of ore and further exploration purposes.The results of this study can aid in the exploration and exploitation of the Mehdiabad deposit and similar deposits in the region.
基金Mid-term Results of the 2024 Langfang Normal University Special Teaching Reform Project on Innovation and Entrepreneurship Education Reform,“Research on the Evaluation System of Innovation and Entrepreneurship Ability for Normal University Students Based on Big Data Application-A Case Study of Langfang Normal University”(Project No.:CXJG2024-06)。
文摘Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation.
基金The authors extend their appreciation to the Ongoing Research Funding Program,number(ORF2025R705),King Saud University,Riyadh,Saudi Arabia,for funding this work.
文摘The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan.
文摘BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of postoperative nursing interventions,particularly pain management,is crucial for reducing such complications.AIM To investigate the effects of enhanced recovery nursing on CV complications after gastrointestinal surgery in ICU patients and associated risk factors.METHODS A retrospective analysis was conducted on 78 adult patients who underwent gastrointestinal surgery in the ICU of our hospital between February 2023 and September 2024.Among them,40 patients received standard care(control group),while 38 received enhanced recovery nursing(observation group).We compared the incidence of CV complications and nursing satisfaction between the two groups.Patients were divided into CV complication and non-complication groups based on complication occurrence,and logistic regression analysis was used to identify risk factors.RESULTS In the control and observation groups,the incidence of CV complications was 30.0%(12/40)and 18.4%(7/38),with a nursing satisfaction rate of 70.0%(28/40)and 92.1%(35/38),respectively.The postoperative pain score at 14 days was significantly lower in the observation group(0.27±0.15)compared to the control group(1.65±0.37),with all differences being statistically significant(P<0.05).Univariate analysis indicated significant differences in age,body mass index,hypertension,diabetes,smoking history,history of heart failure,and previous myocardial infarction(P<0.05).Multivariate logistic regression identified heart failure history,previous myocardial infarction,age,hypertension,and diabetes as independent risk factors,with odds ratios of 1.195,1.528,1.062,1.836,and 1.942,respectively(all P<0.05).CONCLUSION Implementing enhanced recovery nursing for ICU patients after gastrointestinal surgery is beneficial in reducing the incidence of CV complications and improving nursing satisfaction.
文摘The concept, fundamental theory, analytical steps and formulae of grey relational analysis (GRA)-a new statistical method or multifactorial analysis in the field of medicine were introduced. GRA of grouping sequence that is applied to medical study was built by the authors. An example was given to demonstrate it. The superiority of GRA was recounted briefly.
文摘The operating data of an enterprise has very positive reference significance for controlling risks, improving systems and processes, and enhancing efficiency and effectiveness in the development of an enterprise. If an enterprise can master its operating status in the form of a data report, the relevant statistical data must take into account timeliness, accuracy, standardization and completeness. The following discusses various factors that restrict the quality of statistical data, and then puts forward management measures to improve the quality of statistical data.
基金supported by the Major State Basic Research Development Program (No. 2010CB428800)the Geological Survey Projects Foundation of Institute of Hydrogeology and Environmental Geology (No. SK201308)
文摘Understanding the controlling factor of groundwater quality can enhance promoting sustainable development of groundwater resources. To this end, multivariate statistical analysis（MA） and hydrochemical analysis were introduced in this work. The results indicate that the canonical discriminant function with 7 parameters was established using the discriminant analysis（DA） method, which can afford 100% correct assignation according to the 3 different clusters（good water（GW）, poor water（PW）, and very poor water（VPW）） obtained from cluster analysis（CA）. According to factor analysis（FA）, 8 factors were extracted from 25 hydrochemical elements and account for 80.897% of the total data variance, suggesting that groundwater with higher concentrations of sodium, calcium, magnesium, chloride, and sulfate in southeastern study area are mainly affected by the natural process; the higher level of arsenic and chromium in groundwater extracted from northwestern part of study area are derived by industrial activities; domestic and agriculture sewage have important contribution to copper, iron, iodine, and phosphate in the northern study area. Therefore, this work can help identify the main controlling factor of groundwater quality in North China plain so as to make better and more informed decisions about how to achieve groundwater resources sustainable development.
基金supported by the National Natural Science Foundation of China(No.40776041,40676046)the National High Technology Research and Development Program of China(No.2007AA091704)the Program for New Century Excellent Talents in Fujian Province University
文摘Wastewater dissolved organic matter （DOM） from different processing stages of a sewage treatment plant in Xiamen was characterized using fluorescence and absorption spectroscopy. Parallel factor analysis modeling of excitation-emission matrix spectra revealed five fluorescent components occurring in sewage DOM： one protein-like （C1）, three humic-like （C2, C4 and C5） and one xenobiotic-like （C3） components. During the aerated grit chamber and primary sedimentation tank stage, there was only a slight decrease in fluorescence intensity and the absorption coefficient at 350 nm （a 350 ）. During the second aeration stage, high concentration of protein-like and short-wavelength-excited humic-like components were significantly degraded accompanied by significant loss of DOC （80%） and a 350 （30%）, indicating that C1 and C2 were the dominant constituents of sewage DOM. As a result, long-wavelength- excited C4 and C5 became the dominant humic-like components and the DOM molecular size inferred from the variation of spectral slope S （300–650 nm） and specific absorption （a 280 /DOC） increased. Combination use of F max of C1 and the ratio of C1/C5, or a 350 may provide a quantitative indication for the relative amount of raw or treated sewage in aquatic environment.
文摘With the rapid growth of economy in China, people＇s living standard has been generally improved, and people＇s requirements on the quality and quantity of infrastructures like transportation convenience, city greening have become higher and higher, which requires the government to attach importance to these livelihood is- sues. Based on the China Statistical Yearbook, 6 target factors of 31 provinces and cities in China were conducted with factor analysis, and the conditions of the infras- tructures in the 31 provinces and cities were judged and evaluated through the ex- traction of common factors and the calculation of these common factors, and corre- sponding suggestions were proposed with the aim to improve the infrastructures in China.
基金Supported by the Guangdong Technological Program (2009B02001002)the Special Funds of National Agricultural Department for Commonweal Trade Research (nyhyzx07-019)the Earmarked Fund for Modern Agro-industry Technology Research System~~
文摘[Objective] The study aimed to compare several statistical analysis models for estimating the sugarcane （Saccharum spp.） genotypic stability. [Method] The data of sugarcane regional trials in Guangdong, in 2009 was analyzed by three models respectively： Finlay and Wilkinson model： the additive main effects and multiplicative interaction （AMMI） model and linear regression-principal components analysis （LR- PCA） model, so as to compare the models. [Result] The Finlay and Wilkinson model was easier, but the analysis of the other two models was more comprehensive, and there was a bit difference between the additive main effects and multiplicative inter- action （AMMI） model and linear regression-principal components analysis （LR-PCA） model. [Conclusion] In practice, while the proper statistical method was usually con- sidered according to the different data, it should be also considered that the same data should be analyzed with different statistical methods in order to get a more reasonable result by comparison.
文摘This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.
基金Supported by the National Natural Science Foundation of China （No.60574047） and the Doctorate Foundation of the State Education Ministry of China （No.20050335018）.
文摘Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the two methods is that the components of PCA are still dependent while ICA has no orthogonality constraint and its latentvariables are independent. Process monitoring with PCA often supposes that process data or principal components is Gaussian distribution. However, this kind of constraint cannot be satisfied by several practical processes. To ex-tend the use of PCA, a nonparametric method is added to PCA to overcome the difficulty, and kernel density estimation （KDE） is rather a good choice. Though ICA is based on non-Gaussian distribution intormation, .KDE can help in the close monitoring of the data. Methods, such as PCA, ICA, PCA.with .KDE（KPCA）, and ICA with KDE,（KICA）, are demonstrated and. compared by applying them to a practical industnal Spheripol craft polypropylene catalyzer reactor instead of a laboratory emulator.
基金supported by the Centro de Investigación para el Desarrollo y la Innovación (CIDI) from Universidad Pontificia Bolivariana (No. 636B-06/16–57)。
文摘Structural Health Monitoring(SHM) suggests the use of machine learning algorithms with the aim of understanding specific behaviors in a structural system. This work introduces a pattern recognition methodology for operational condition clustering in a structure sample using the well known Density Based Spatial Clustering of Applications with Noise(DBSCAN) algorithm.The methodology was validated using a data set from an experiment with 32 Fiber Bragg Gratings bonded to an aluminum beam placed in cantilever and submitted to cyclic bending loads under 13 different operational conditions(pitch angles). Further, the computational cost and precision of the machine learning pipeline called FA + GA-DBSCAN(which employs a combination of machine learning techniques including factor analysis for dimensionality reduction and a genetic algorithm for the automatic selection of initial parameters of DBSCAN) was measured. The obtained results have shown a good performance, detecting 12 of 13 operational conditions, with an overall precision over 90%.
基金supposed by the Program for Science and Technology of Shandong Province (2011GHY11521)the Department of Education of Shandong Province (No. J11LB07)the Natural Science Foundation of Qingdao City (Nos. 12-1-3-52-(1)-nsh and 12-1-4-16-(7)-jch)
文摘Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, the elemental contents of M. concha from five sampling points in Rushan Bay have been determined by means of inductively coupled plasma optical emission spectrometry(ICP-OES). Based on the contents of 14 inorganic elements(Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, and Zn), the inorganic elemental fingerprint which well reflects the elemental characteristics was constructed. All the data from the five sampling points were discriminated with accuracy through hierarchical cluster analysis(HCA) and principle component analysis(PCA), indicating that a four-factor model which could explain approximately 80% of the detection data was established, and the elements Al, As, Cd, Cu, Ni and Pb could be viewed as the characteristic elements. This investigation suggests that the inorganic elemental fingerprint combined with multivariate statistical analysis is a promising method for verifying the geographical origin of M. concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.
基金The National Key Research and Development Program of China(No.2018YFB1600300,2018YFB1600304,2018YFB1600305)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX21_0133)the Scientific Research Foundation of Graduate School of Southeast University.
文摘To clarify the importance of various influencing factors on asphalt pavement rutting deformation and determine a screening method of model indicators,the data of the RIOHTrack full-scale track were examined using the factor analysis method(FAM).Taking the standard test pavement structure of RIOHTrack as an example,four rutting influencing factors from different aspects were determined through statistical analysis.Furthermore,the common influencing factors among the rutting influencing factors were studied based on FAM.Results show that the common factor can well characterize accumulative ESALs,center-point deflection,and temperature,besides humidity,which indicates that these three influencing factors can have an important impact on rutting.Moreover,an empirical rutting prediction model was established based on the selected influencing factors,which proved to exhibit high prediction accuracy.These analysis results demonstrate that the FAM is an effective screening method for rutting prediction model indicators,which provides a reference for the selection of independent model indicators in other rutting prediction model research when used in other areas and is of great significance for the prediction and control of rutting distress.
基金Supported by National Health and Medical Research Council Australia(ID 455213)
文摘AIM:To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction.METHODS:One hundred and ninety-one patients presenting to a Gastroenterology clinic with constipation and 32 constipated patients responding to a newspaper advertisement completed a 53-item,wide-ranging selfreport questionnaire.One hundred of these patients had colonic transit measured scintigraphically.Factor analysis determined whether constipation-related symptoms grouped into distinct aspects of symptomatology.Cluster analysis was used to determine whether indi-vidual patients naturally group into distinct subtypes.RESULTS:Cluster analysis yielded a 4 cluster solution with the presence or absence of pain and laxative unresponsiveness providing the main descriptors.Amongst all clusters there was a considerable proportion of patients with demonstrable delayed colon transit,irritable bowel syndrome positive criteria and regular stool frequency.The majority of patients with these characteristics also reported regular laxative use.CONCLUSION:Factor analysis identified four constipation subgroups,based on severity and laxative unresponsiveness,in a constipated population.However,clear stratification into clinically identifiable groups remains imprecise.
基金supported by the Director Foundation of the Institute of Seismology,China Earthquake Administration(201056076,201116002)
文摘The seismic intensities, lithologic characteristics and terrain features from a 3000 km2-region near the epicenter of the Lushan earthquake are used to analyze earthquake-induced geological disaster. The preliminary results indicate that secondary effects of the earthquake will affect specific areas, including those with glutenite and carbonate bedrock, a seismic intensity of IX, slopes between 40° and 50°, elevations of less than 2500 m, slope change rates between 20° and 30°, slope curvatures from - 1 to -0.5 and 0. 5 to 1, and relief between 50 and 100 m. Regions with susceptibility indices greater than 0.71 are prone to landslides and collapses. The secondary features are mainly distributed on both sides of the ridges that extend from Baosheng to Shuangshi and from Baosheng to Longxing. Other features are scattered on both sides of the ridges that extend from Qishuping to Baosheng and from Masangping to Lingguan. The distribution of the earthquake-related features trends in the NE direction, and the area that was most affected by the Lushan earthquake covers approximately 52.4 km^2.
基金supported by the National Social Science Foundation of China,2015(Grant No.ZDA059)the National Science Foundation of China,2013(Grant Nos.71373014 and 71303045)+3 种基金the Energy Foundation(USA)Projects,2012(Grant No.12YJAZH056)the special fund of the Research on the Generalized Virtual Economy,2011(Grant No.G-1111-15134)the Philosophy Social Planning project of the Ministry of Education of the People’s Republic of China,2011(Grant No.GX2011-1017Y)‘‘the Fundamental Research Funds for the Central Universities’’in UIBE(No.15YQ09)
文摘Henry Hub as an important transaction hub for natural gas sets the gas price standard in the USA. In this paper, the factors influencing Henry Hub natural gas prices are analyzed, and the major factors determining the price levels in the period between January 1997 and December 2016 are studied. It is found that economic conditions, total energy demand, US dollar exchange rate and gas consumption are the major factors. The mechanism of each factor influencing the Henry Hub natural gas price is also explored in the paper.
文摘Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.
