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Factor analysis and machine learning for predicting endpoint carbon content in converter steelmaking 被引量:1
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作者 Lihua Zhao Shuai Yang +3 位作者 Yongzhao Xu Zhongliang Wang Xin Liu Yanping Bao 《International Journal of Minerals,Metallurgy and Materials》 2025年第10期2469-2482,共14页
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
关键词 CONVERTER endpoint carbon content parameter classification factor analysis improved particle swarm optimization support vector machine
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WPPSI-III in Sudan:Validity,reliability,and confirmatory factor analysis in khartoum kindergarten and primary schools
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作者 Rwaa Omer Ali Ahmed Salaheldin Farah Attallah Bakhiet +2 位作者 Ayman Mohamed Taha Abdelaziz Ahmed FadlAlMawla AbdulRadi Ismael Salamah Albursan 《Journal of Psychology in Africa》 2025年第4期431-439,共9页
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
关键词 intelligence tests VALIDATION RELIABILITY primary schools kindergartens confirmatory factor analysis cognitive abilities WPPSI-III SUDAN
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Research on the Construction of an Evaluation System for Innovation and Entrepreneurship Capabilities of Normal University Students Based on Factor Analysis Method
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作者 Fang Liu Chi Li Lihua Jia 《Journal of Contemporary Educational Research》 2025年第8期320-327,共8页
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
关键词 Factor analysis Innovation and entrepreneurship capability Indicator system Evaluation system UNIVERSITIES Normal university students
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Analysis of inflammatory response and its factors after dental implant surgery in patients with type 2 diabetes
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作者 Zhang-Yi Li Heng-Yang Yu Hong Liang 《World Journal of Diabetes》 2025年第10期238-248,共11页
BACKGROUND Dental implants are widely used to replace missing teeth.Currently,clinicians assess osseointegration success by measuring the implant’s stability within the bone and monitoring the marginal tissue height.... BACKGROUND Dental implants are widely used to replace missing teeth.Currently,clinicians assess osseointegration success by measuring the implant’s stability within the bone and monitoring the marginal tissue height.Diabetes,especially type 2 diabetes mellitus(T2DM),has been reported to impair implant healing,drastically reducing implant success rates.AIM To analyze the high-risk factors for inflammatory response and prognosis after dental implantation in patients with T2DM,and provide strong evidence for reducing the incidence of postimplant peri-implantitis(PI).METHODS We performed a retrospective review of 146 patients with T2DM who had dental implants placed at Tianjin Fifth Central Hospital,between September 2021 and September 2023,which was regarded as the observation group.Moreover,60 ageand gender-matched individuals with normal blood glucose levels served as the control group.The general information,postoperative periodontal indices,and levels of inflammatory factors were comprehensively analyzed and compared.Furthermore,the incidence of postimplant PI was counted,and multivariate logistic regression was used to identify the determinants of postimplant PI.RESULTS In terms of the periodontal indices,the probing depth,modified sulcus bleeding index,and marginal bone loss in the observation cohorts began to increase significantly at 6 months and 3 months,respectively,after the completion of dental implant restoration.The T2DM cases demonstrated significantly elevated counts of leukocytes,lymphocytes,and neutrophils compared to the controls at 24 hours postoperatively.Moreover,the TNF-α,IL-1β,and IL-6 concentrations started to increase significantly in the gingival crevicular fluid 3 months after the completion of dental implant restoration in both cohorts,with the observation group exhibiting higher levels than the controls at each time point.63 out of the 146 cases developed PI.Multivariate logistic regression analysis indicated that high glycosylated hemoglobin levels,smoking,daily tooth-brushing frequency of less than once,and the anterior tooth as the implant site independently contributed to postimplant PI in T2DM cases,while a tooth-brushing duration of≥3 minutes was a protective factor.CONCLUSION Patients with T2DM are at risk of developing PI following dental implantation.Clinically,it is necessary to enhance the identification of risk factors for postimplant PI,improve risk prediction,prevention,and control,and formulate targeted intervention countermeasures to reduce the occurrence of postimplant PI. 展开更多
关键词 Type 2 diabetes mellitus Dental implants Inflammatory response Factor analysis Periodontal prognosis
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Nursing interventions’impact on cardiovascular complications after gastrointestinal surgery in intensive care unit:Risk factor analysis
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作者 Ling Wang Peng Yang +1 位作者 Xue-Qing He Han Xia 《World Journal of Gastrointestinal Surgery》 2025年第8期133-141,共9页
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
关键词 Enhanced recovery nursing interventions Intensive care unit Gastrointestinal surgery Cardiovascular complications Risk factor analysis
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Analysis of risk factors for bile leakage after laparoscopic exploration and primary suture of common bile duct
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作者 Qing-Song Yang Meng Zhang +5 位作者 Chang-Song Ma Da Teng Ao Li Ji-Dong Dong Xi-Fei Wang Fu-Bao Liu 《World Journal of Gastrointestinal Surgery》 2025年第3期278-287,共10页
BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is cruc... BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is crucial for improving surgical outcomes.AIM To explore the value analysis of common risk factors for bile leakage after LCBDE and PDC,with a focus on strict adherence to indications.METHODS Clinical data of 106 cases undergoing LCBDE+PDC in the Hepatobiliary and Pancreatic Surgery Department(Division 1)of Chuzhou First People’s Hospital from April 2019 to March 2024 were collected.Retrospective and multiple factor regression analysis were conducted on common risk factors for bile leakage.The change in surgical time was analyzed using the cumulative summation(CUSUM)method,and the minimum number of cases required to complete the learning curve for PDC was obtained based on the proposed fitting curve by identifying the CUSUM maximum value.RESULTS Multifactor logistic regression analysis showed that fibrinous inflammation and direct bilirubin/indirect bilirubin were significant independent high-risk factors for postoperative bile leakage(P<0.05).The time to drain removal and length of hospital stay in cases without bile leakage were significantly shorter than in cases with bile leakage(P<0.05),with statistical significance.The CUSUM method indicated that a minimum of 51 cases were required for the surgeon to complete the learning curve(P=0.023).CONCLUSION With a good assessment of duodenal papilla sphincter function,unobstructed bile-pancreatic duct convergence,exact stone clearance,and sufficient surgical experience to complete the learning curve,PDC remains the preferred method for bile duct closure and is worthy of clinical promotion. 展开更多
关键词 Laparoscopic common bile duct exploration Primary duct closure Bile leakage Risk factor analysis Cumulative summation
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Correlation of resilience with anxiety and depression in patients with prostate cancer and analysis of influencing factors
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作者 Jiang-Lei Qu Hai-Yang Lu +1 位作者 Xiao-Bo Fu Wen-Tao Gai 《World Journal of Psychiatry》 2025年第8期261-269,共9页
BACKGROUND The development of prostate cancer(PC)frequently intensifies negative emotional states,such as anxiety and depression,which compromise the effectiveness of radical surgery and reduce treatment adherence.In ... BACKGROUND The development of prostate cancer(PC)frequently intensifies negative emotional states,such as anxiety and depression,which compromise the effectiveness of radical surgery and reduce treatment adherence.In this study,we hypothesized that psychological resilience plays a crucial role in this process and explored its impact.AIM To investigate the association of resilience with anxiety and depression in patients with PC and to analyze the influencing factors.METHODS We selected 147 patients with PC who visited Qingdao Traditional Chinese Medicine Hospital from January 2022 to June 2024.The resilience scores of patients with PC were assessed using the Connor-Davidson Resilience Scale(CDRISC)from the tenacity,self-improvement,and optimism dimensions.Based on the total CD-RISC score,patients were categorized into groups A(total CD-RISC score>63 points,n=69)and B(total CD-RISC score≤63 points,n=78)for comparative analysis of anxiety[Hamilton Anxiety Rating Scale(HAMA)],depression[Hamilton Depression Rating Scale(HAMD)],sexual function[International Index of Erectile Function-5(IIEF-5)and Sexual Life Quality Questionnaire-Quality of Life(SLQQ-QOL)],and quality of life[the EORTC Core Quality of Life Question naire(QLQ-C30)].The association between CD-RISC and the above indicators was analyzed with Spearman correlation coefficients,and the influencing factors of resilience in patients with PC were identified with binary logistic regression.RESULTS Group A demonstrated statistically lower HAMA and HAMD scores and markedly higher scores of IIEF-5,SLQQQOL,and various QLQ-C30 aspects.Correlation analysis revealed that CD-RISC was significantly negatively correlated with HAMA and HAMD scores and significantly positively correlated with IIEF-5,SLQQ-QOL,and QLQ-C30 total scores.Binary logistic regression analysis revealed educational and per capita monthly household income levels as significant influencing factors of resilience in patients with PC.CONCLUSION Our results indicate a significant correlation of resilience with anxiety and depression in patients with PC.The milder the anxiety and depression emotions in patients,the higher their resilience.Further,assisting patients with PC to improve their educational and per capita monthly household income levels will help their resilience to some extent. 展开更多
关键词 Prostate cancer RESILIENCE ANXIETY DEPRESSION analysis of influencing factors
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A Proportional Integral Controller-Enhanced Non-Negative Latent Factor Analysis Model
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作者 Ye Yuan Siyang Lu Xin Luo 《IEEE/CAA Journal of Automatica Sinica》 2025年第6期1246-1259,共14页
A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimens... A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at https://github.com/yuanyeswu/PINLF/blob/mainIPINLF-code.zip. 展开更多
关键词 High-dimensional and incomplete(HDI)data learning algorithm non-negative latent factor(NLF)analysis proportional integral(PI)controller
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Machine learning identifies key cells and therapeutic targets during ferroptosis after spinal cord injury
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作者 Yigang Lv Zhen Li +10 位作者 Lusen Shi Huan Jian Fan Yang Jichuan Qiu Chao Li Peng Xiao Wendong Ruan Hao Li Xueying Li Shiqing Feng Hengxing Zhou 《Neural Regeneration Research》 2026年第6期2495-2505,共11页
Ferroptosis,a type of cell death that mainly involves iron metabolism imbalance and lipid peroxidation,is strongly correlated with the phagocytic response caused by bleeding after spinal cord injury.Thus,in this study... Ferroptosis,a type of cell death that mainly involves iron metabolism imbalance and lipid peroxidation,is strongly correlated with the phagocytic response caused by bleeding after spinal cord injury.Thus,in this study,bulk RNA sequencing data(GSE47681 and GSE5296)and single-cell RNA sequencing data(GSE162610)were acquired from gene expression databases.We then conducted differential analysis and immune infiltration analysis.Atf3 and Piezo1 were identified as key ferroptosis genes through random forest and least absolute shrinkage and selection operator algorithms.Further analysis of single-cell RNA sequencing data revealed a close relationship between ferroptosis and cell types such as macrophages/microglia and their intrinsic state transition processes.Differences in transcription factor regulation and intercellular communication networks were found in ferroptosis-related cells,confirming the high expression of Atf3 and Piezo1 in these cells.Molecular docking analysis confirmed that the proteins encoded by these genes can bind cycloheximide.In a mouse model of T8 spinal cord injury,low-dose cycloheximide treatment was found to improve neurological function,decrease levels of the pro-inflammatory cytokine inducible nitric oxide synthase,and increase levels of the anti-inflammatory cytokine arginase 1.Correspondingly,the expression of the ferroptosis-related gene Gpx4 increased in macrophages/microglia,while the expression of Acsl4 decreased.Our findings reveal the important role of ferroptosis in the treatment of spinal cord injury,identify the key cell types and genes involved in ferroptosis after spinal cord injury,and validate the efficacy of potential drug therapies,pointing to new directions in the treatment of spinal cord injury. 展开更多
关键词 bioinformatic analyses bulk-RNA sequencing cellular communication analysis ferroptosis machine learning analysis neurological function RNA velocity analysis single-cell RNA sequencing therapeutic drugs transcription factor analysis
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Geographical differentiation of riverine DOM composition and source apportionment:A case study of a riverine network of a mountainous stream,a Plain River,and an artificial canal
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作者 Jun-wei Zhao Shuang-bing Huang +2 位作者 Zhao-xin Su Wei-Chao Huang Yong Qian 《Journal of Groundwater Science and Engineering》 2026年第1期59-68,共10页
To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river ... To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter(DOM)in typical rivers,this study conducted a multi-spectral investigation on three representative river types within Shandong Province:The mountainous Dawen River,the plain Tuhai River,and the artificial East Grand Canal.The DOM composition was analyzed using Ultraviolet-Visible(UV-Vis)absorption spectroscopy,Excitation-Emission Matrix(EEM)fluorescence spectroscopy,and parallel factor analysis(PARAFAC),while Principal Component Analysis(PCA)was employed to quantify the synergistic effects of natural processes and anthropogenic activities.Results revealed significant spatial heterogeneity in DOM composition and sources.The plain river exhibited the highest aromaticity(humic-like components:43.3%)due to long-term agricultural non-point source inputs and urban wastewater discharge.The mountain stream,shaped by complex terrain and relatively intact ecosystems,was dominated by autochthonous DOM derived from microbial metabolism,with higher Fluorescence Index(FI=2.12)and biological index(BIX=1.35)than other river types.The artificial canal retained protein-like components(64.2%),largely attributed to winter hydrological stagnation and disturbances from shipping activities.Further analysis demonstrated that geographical settings(e.g.,mountain terrain)and anthropogenic activities(e.g.,agriculture,shipping)jointly regulated DOM composition by altering the balance between input and transformation processes.Integrated fluorescence parameters and PCA results suggested differentiated management strategies:protecting ecological integrity in mountain streams to sustain selfpurification,enhancing non-point source interception in plain rivers,and mitigating shipping pollution in canals.This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers,providing critical insights for precision water environment management at the watershed scale. 展开更多
关键词 Dissolved organic matter(DOM) UV-Vis spectroscopy Parallel factor analysis(PARAFAC) Geographical settings Anthropogenic activities
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Agricultural Input and Output in Jiangsu Province with Case Analysis
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作者 杜华章 《Agricultural Science & Technology》 CAS 2014年第11期2006-2010,2025,共6页
[Objective] The aim was to explore interrelationship between agricultural input and output in Jiangsu and the influence degrees of input factors on agricultur-al output. [Method] Quantitative analysis and evaluation w... [Objective] The aim was to explore interrelationship between agricultural input and output in Jiangsu and the influence degrees of input factors on agricultur-al output. [Method] Quantitative analysis and evaluation were made on agricultural input and output in Jiangsu during 1990-2012 as per factor analysis and regression analysis. [Result] The result of factor analysis showed that since the 1990s, the comprehensive efficiency of agricultural input/output in Jiangsu was growing and in-put/output of agriculture, forestry, animal husbandry and fishery, crop farming, and of food production were extracted, whose scores reflect the changes of input/output ef-ficiencies in terms of agriculture, forestry, animal husbandry, fishery, crop farming and food production in the two decades. The results of regression analysis indicated that the effects of the three indices on agricultural output tended to be volatile and the influence degrees were concluded also by regression parameters. [Conclusion] The research provides theoretical references for agricultural input/output structure in Jiangsu Province. 展开更多
关键词 Agriculture Input/output Factor analysis Regression analysis Jiangsu Province
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Factor Analysis Based on the Level of Urban Facilities in Different Regions 被引量:1
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作者 于淼 《Agricultural Science & Technology》 CAS 2017年第6期1102-1105,共4页
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
关键词 Factor analysis INFRASTRUCTURE EVALUATION
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Characterization of dissolved organic matter in urban sewage using excitation emission matrix fluorescence spectroscopy and parallel factor analysis 被引量:43
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作者 Weidong Guo Jing Xu +3 位作者 Jiangping Wang Yingrou Wen Jianfu Zhuo Yuchao Yan 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2010年第11期1728-1734,共7页
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
关键词 dissolved organic matter SEWAGE fluorescence EEM parallel factor analysis
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An unsupervised pattern recognition methodology based on factor analysis and a genetic-DBSCAN algorithm to infer operational conditions from strain measurements in structural applications 被引量:7
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作者 Juan Carlos PERAFAN-LOPEZ Julian SIERRA-PEREZ 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2021年第2期165-181,共17页
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
关键词 CLUSTERING DBSCAN Factor analysis FBGs Pattern recognition Strain field
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Preoperative risk factor analysis in orthotopic liver transplantation with pretransplant artificial liver support therapy 被引量:8
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作者 Jin-Zhong Yuan Qi-Fa Ye Ling-Ling Zhao Ying-Zi Ming Hong Sun Shai-Hong Zhu Zu-Fa Huang Min-Min Wang 《World Journal of Gastroenterology》 SCIE CAS CSCD 2006年第31期5055-5059,共5页
AIM: To assess the value of pre-transplant artificial liver support in reducing the pre-operative risk factors relating to early mortality after orthotopic liver transplantation (OLT). METHODS: Fifty adult patient... AIM: To assess the value of pre-transplant artificial liver support in reducing the pre-operative risk factors relating to early mortality after orthotopic liver transplantation (OLT). METHODS: Fifty adult patients with various stages and various etiologies undergoing OLT procedures were treated with molecular adsorbent recycling system (MARS) as preoperative liver support therapy. The study included two parts, the first one is to evaluate the medical effectiveness of single MARS treatment with some clinical and laboratory parameters, which were supposed to be the therapeutical pre-transplant risk factors, the second part is to study the patients undergoing OLT using the regression analysis on preoperative risk factors relating to early mortality (30 d) after OLT. RESULTS: In the 50 patients, the statistically significant improvement in the biochemical parameters was observed (pre-treatment and post-treatment). Eight patients avoided the scheduled Ltx due to significant relief of clinical condition or recovery of failing liver function, 8 patients died, 34 patients were successfully bridged to Ltx, the immediate outcome of this 34 patients within 30d observation was: 28 kept alive and 6 patients died. CONCLUSION: Pre-operative SOFA, level of creatinine, INR, TNF-α, IL-10 are the main preoperative risk factors that cause early death after operation, MARS treatment before transplantion can relieve these factors significantly. 展开更多
关键词 Liver transplantation Artificial liver Sequential Organ Failure Assessment Risk factors analysis
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Analysis of three types of triterpenoids in tetraploid white birches(Betula platyphylla Suk.) and selection of plus trees 被引量:4
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作者 Sui Wang Hui Zhao +2 位作者 Jing Jiang Guifeng Liu Chuanping Yang 《Journal of Forestry Research》 SCIE CAS CSCD 2015年第3期623-633,共11页
Betulin, oleanolic acid, and betulinic acid are naturally occurring pentacyclic triterpenoids that have significant medicinal value. Considerable amounts of these triterpenoids are available in the outer bark of white... Betulin, oleanolic acid, and betulinic acid are naturally occurring pentacyclic triterpenoids that have significant medicinal value. Considerable amounts of these triterpenoids are available in the outer bark of white birch. In this study, we used ultrasound-assisted extraction (UAE) to extract triterpenoids from birch bark rapidly and with high efficiency. Using high performance liquid chro- matography (HPLC), three types of triterpenoids were separated and detected. We examined the differences among triterpenoids extracted from diploid versus tetra- ploid white birch. Then, we used factor analysis to screen out tetraploid white birches with comprehensively excel- lent performance. The results indicate that the optimum conditions for extraction include the use of ethanol as an extraction solvent, a solid-to-liquid ratio of 0.1 g/10 ml, ultrasonic power set at 100 W, a temperature of 60 ℃ and an extraction time of 15 min. A reversed-phase C18 col- umn (4.6 mm × 250 mm × 5 μm) with a column tem- perature of 30 ℃ and the mobile phase composed of A (acetonitrile) and B (0.1% aqueous phosphoric acid, v/v) at a flow rate of 0.5 ml/min were used, and the detection wavelength was 195 nm. No significant difference wasobserved between diploid and tetraploid white birch in terms of the content of three types of triterpenoids (at a confidence level of 0.05). As triterpenoid content, height, and DBH (diameter at breast height) are strongly interre- lated, we used factor analysis to evaluate all individuals, and we screened out six plus trees with excellent com- prehensive characters. 展开更多
关键词 Betula platyphylla Suk TRITERPENOIDS Highperformance liquid chromatography (HPLC) TETRAPLOID DIPLOID Factor analysis
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Factor Analysis on the Factors that Influencing Rural Environmental Pollution in the Hilly Area of Sichuan Province,China 被引量:13
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作者 LING Jing DENG Liang-ji 《Asian Agricultural Research》 2011年第2期69-72,共4页
By using factor analysis method and establishing analysis indicator system from four aspects including crop production,poultry farming,rural life and township enterprises,the difference,features,and types of factors i... By using factor analysis method and establishing analysis indicator system from four aspects including crop production,poultry farming,rural life and township enterprises,the difference,features,and types of factors influencing the rural environmental pollution in the hilly area in Sichuan Province,China.Results prove that the major factor influencing rural environmental pollution in the study area is livestock and poultry breeding,flowed by crop planting,rural life,and township enterprises.Hence future pollution prevention and control should set about from livestock and poultry breeding.Meanwhile,attention should be paid to the prevention and control of rural environmental pollution caused by rural life and township enterprise production. 展开更多
关键词 Rural area Environmental pollution Influencing factors Factor analysis Hilly area in Sichuan Province China
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Simulated photo-degradation of dissolved organic matter in lakes revealed by three-dimensional excitation-emission matrix with regional integration and parallel factor analysis 被引量:4
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作者 Jin Zhang Fanhao Song +5 位作者 Tingting Li Kefu Xie Huiying Yao Baoshan Xing Zhongyu Li Yingchen Bai 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2020年第4期310-320,共11页
Simulated photo-degradation of fluorescent dissolved organic matter(FDOM) in Lake Baihua(BH) and Lake Hongfeng(HF) was investigated with three-dimensional excitationemission matrix(3 DEEM) fluorescence combined with t... Simulated photo-degradation of fluorescent dissolved organic matter(FDOM) in Lake Baihua(BH) and Lake Hongfeng(HF) was investigated with three-dimensional excitationemission matrix(3 DEEM) fluorescence combined with the fluorescence regional integration(FRI),parallel factor(PARAFAC) analysis,and multi-order kinetic models.In the FRI analysis,fulvic-like and humic-like materials were the main constituents for both BH-FDOM and HF-FDOM.Four individual components were identified by use of PARAFAC analysis as humic-like components(C1),fulvic-like components(C2),protein-like components(C3) and unidentified components(C4).The maximum 3 DEEM fluorescence intensity of PARAFAC components C1-C3 decreased by about 60%,70% and 90%,respectively after photo-degradation.The multi-order kinetic model was acceptable to represent the photo-degradation of FDOM with correlation coefficient(Radj2)(0.963-0.998).The photo-degradation rate constants(kn) showed differences of three orders of magnitude,from 1.09 × 10-6 to 4.02 × 10-4 min-1,and half-life of multi-order model(T1/2n)ranged from 5.26 to 64.01 min.The decreased values of fluorescence index(FI) and biogenic index(BI),the fact that of percent fluorescence response parameter of Region I(PⅠ,n) showed the greatest change ratio,followed by percent fluorescence response parameter of Region II(PⅡ,n,while the largest decrease ratio was found for C3 components,and the lowest T1/2n was observed for C3,indicated preferential degradation of protein-like materials/components derived from biological sources during photodegradation.This research on the degradation of FDOM by 3 DEEM/FRI-PARAFAC would be beneficial to understanding the photo-degradation of FD OM in natural environments and accurately predicting the environmental behaviors of contaminants in the presence of FDOM. 展开更多
关键词 Fluorescent dissolved organic matter PHOTO-DEGRADATION Fluorescence regional integration Parallel factor analysis Three-dimensional excitationemission matrix Multi-order kinetic models
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Rutting influencing factors and prediction model for asphalt pavements based on the factor analysis method 被引量:5
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作者 Liu Gang Chen Leilei +1 位作者 Qian Zhendong Zhou Xiayang 《Journal of Southeast University(English Edition)》 EI CAS 2021年第4期421-428,共8页
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
关键词 asphalt pavement rutting prediction influencing factors RIOHTrack full-scale track factor analysis method
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Research on Competitiveness of County Economy Based on Factor Analysis and Cluster Analysis——Taking 88 Counties in Guizhou as Samples 被引量:9
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作者 HAN De-jun LU Jing-fang ZHANG Wen-zhuan 《Asian Agricultural Research》 2011年第2期28-31,共4页
17 indices are selected,such as the growth rate of total regional output value,the proportion of tertiary industry in GDP,per capita financial expenditure,and soil erosion rate of Guizhou Province in 2009.According to... 17 indices are selected,such as the growth rate of total regional output value,the proportion of tertiary industry in GDP,per capita financial expenditure,and soil erosion rate of Guizhou Province in 2009.According to the relevant indices data of statistical yearbook and governmental website,by using the method of factor analysis and the method of cluster analysis,we assess the competitiveness of county economy in 88 counties of Guizhou Province.The results show that the competitiveness of county economy in Guizhou Province is impacted by factors of location and economic foundation.In addition,the resources environment,economic structure,economic developmental speed and other factors also impact the competitiveness of county economy in Guizhou Province.Based on these,in the light of the developmental characteristics of different counties in conjunction with different developmental advantages in different regions,we should adopt different developmental strategies according to local conditions,which is significant to rapid,healthy and sustainable development of county economy in Guizhou Province. 展开更多
关键词 County Economy COMPETITIVENESS Factor analysis Cluster analysis China
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