A theoretical method is presented,which analyzes properties of surface acoustic waves propagating on metallic gratings with finite thickness by combining finite element method with variational principle on surface aco...A theoretical method is presented,which analyzes properties of surface acoustic waves propagating on metallic gratings with finite thickness by combining finite element method with variational principle on surface acoustic waves propagating on periodic metal gratings. Based on D.P.Chen and Haus theory,a finite element method is used to investigate the effects of metallic gratings upon the propagation of surface acoustic waves.The coupling-of-modes parameters contributed by mechanical loading are expressed by the matrix derived from the finite element method.Consequently D.P.Chen and Haus theory can also be applied to analyze the properties of surface acoustic waves propagating on metallic gratings with finite thickness and arbitrary shape.Finally,the characteristics of surface acoustic waves propagating under gold and aluminum or silver gratings on a few piezoelectric crystals are studied.Numerical results of the coupling-of-modes parameters of the surface acoustic waves are obtained.展开更多
Block principle and pattern classification component analysis （BPCA） is a recently developed technique in computer vision In this paper, we propose a robust and sparse BPCA with Lp-norm, referred to as BPCALp-S, whi...Block principle and pattern classification component analysis （BPCA） is a recently developed technique in computer vision In this paper, we propose a robust and sparse BPCA with Lp-norm, referred to as BPCALp-S, which inherits the robustness of BPCA-L1 due to the employment of adjustable Lp-norm. In order to perform a sparse modelling, the elastic net is integrated into the objective function. An iterative algorithm which extracts feature vectors one by one greedily is elaborately designed. The monotonicity of the proposed iterative procedure is theoretically guaranteed. Experiments of image classification and reconstruction on several benchmark sets show the effectiveness of the proposed approach.展开更多
Brain arteriovenous malformation(BAVM) is frequently described as vascular malformation. Although computer tomography(CT), magnetic resonance imaging(MRI) and angiography can clearly detect lesions, there are no diagn...Brain arteriovenous malformation(BAVM) is frequently described as vascular malformation. Although computer tomography(CT), magnetic resonance imaging(MRI) and angiography can clearly detect lesions, there are no diagnostic biological markers of BAVM available. Current study demonstrated that micro RNA(mi RNA)showed a feasible marker for vascular disease. To find key correlations between these mi RNAs and the onset of BAVM, we carried out chip analysis of serum mi RNAs by identifying 18 potential markers of BAVM. We then constructed a principle component analysis and logistic regression(PCA-LR) model to analyze the 18 mi RNAs collected from 77 patients. Another 9 independent samples were used to test the resulting model. The results showed that mi RNAs hsa-mir-126-3p and hsa-mir-140 are important protective factors, while hsa-mir-338 is a dominating risk factor, all of which have stronger correlation with BAVM than others. We also compared the testing results using PCA-LR model with those using LR model. The comparison revealed that PCA-LR model is better in predicting the disease.展开更多
In this paper, a set of variational formulas of solving nonlinear instability critical loads are established from the viewpoint of variational principle. The paper shows that it is very convenient to solve nonlinear i...In this paper, a set of variational formulas of solving nonlinear instability critical loads are established from the viewpoint of variational principle. The paper shows that it is very convenient to solve nonlinear instability critical load by using the variational formulas suggested in this paper.展开更多
range of new social and economic challenges is facing the world following the end of the Cold War inthe 1990s, which come along with the progress of globalization. The United Nations hopes to get global businesses inv...range of new social and economic challenges is facing the world following the end of the Cold War inthe 1990s, which come along with the progress of globalization. The United Nations hopes to get global businesses involved in this process by boosting corporate citizenship. Meanwhile, the world body, for the sake of its own development, tries to expand its influence in such a way as to encourage not only state players but also non-state players worldwide to adopt sustainable and socially responsible oolicies.展开更多
Traditionally, Chinese indigenous cattle is geographically widespread. The present study analyzed based on genome-wide variants to evaluate the genetic background among 157 individuals from four representative indigen...Traditionally, Chinese indigenous cattle is geographically widespread. The present study analyzed based on genome-wide variants to evaluate the genetic background among 157 individuals from four representative indigenous cattle breeds of Hubei Province of China： Yiling yellow cattle （YL）, Bashan cattle （BS）, Wuling cattle （WL）, Zaobei cattle （ZB）, and 21 indi- viduals of Qinchuan cattle （QC） from the nearby Shanxi Province of China. Linkage disequilibrium （LD） analysis showed the LD of YL was the lowest （~=0.32） when the distance between markers was approximately 2 kb. Principle component analysis （PCA）, and neighbor-joining （NJ）-tree revealed a separation of Yiling yellow cattle from other geographic nearby local cattle breeds. In PCA plot, the YL and QC groups were segregated as expected; moreover, YL individuals clustered together more obviously. In the N J-tree, the YL group formed an independent branch and BS, WL, ZB groups were mixed. We then used the FST statistic approach to reveal long-term selection sweep of YL and other 4 cattle breeds. According to the selective sweep, we identified the unique pathways of YL, associated with production traits. Based on the results, it can be proposed that YL has its unique genetic characteristics of excellence resource, and it is an indispensable cattle breed in China.展开更多
Banana is one of the main economic agrotypes in Zhangzhou, Fujian Province. The multitemporal ENVlSAT ASAR data with different polarization are used to classify the banana fields in this paper. Principal component ana...Banana is one of the main economic agrotypes in Zhangzhou, Fujian Province. The multitemporal ENVlSAT ASAR data with different polarization are used to classify the banana fields in this paper. Principal component analysis （PCA） was applied for six pairs of ASAR dual-polarization data. For its large leaves, banana has high backscatter. So the value of banana fields is high and shows very bright in the 1st component, which makes it much easier for banana fields extraction. Dual-polarization data provide more information, and the W and VH backscatter of banana show different characters with other land covers. Based on the analysis of the radar signature of banana fields and other land covers and the 1st compo- nent, banana fields are classified using object-oriented classifier. Compared to the field survey data and ASTER data, the accuracy of banana fields in the study area is 83.5%. It shows that the principal component analysis provides the useful information in SAR images analysis and makes the extraction of banana fields easier.展开更多
Optical coherence tomography(OCT)provides significant advantages of high resolution(approaching the histopathology level)realtime imaging of tsess without use of contrast agents.Based on these advantages,the microstru...Optical coherence tomography(OCT)provides significant advantages of high resolution(approaching the histopathology level)realtime imaging of tsess without use of contrast agents.Based on these advantages,the microstructural features of tumors can be visualized and detected intra-operatively.However,it is still not clinically accepted for tumor margin delin-eation due to poor specificity and accuracy.In contrast,Raman spectroscopy(RS)can obtain tissue information at the molecular level,but does not provide real-time inaging capability.Therefore,combining OCT and RS could provide synergy.To this end,we present a tissue analysis and dassification method using both the slope of OCT intensity signal Vs depth and the principle components from the RS spectrum as the indicators for tissuse characterization.The goal of this study was to understand prediction accuracy of OCT and combined OCT/RS method for dassification of optically similar tisues and organs.Our pilot experiments were performed on mouse kidneys,livers,and small intestines(SIs).The prediction accuracy with five-fold cross validation of the method has been evaluated by the support vector machine(SVM)method.The results demonstrate that tissue characterization based on the OCT/RS method was superior compared to using OCT structural information alone.This combined OCT/RS method is potentially useful as a noninvasive optical biopsy technique for rapid and automatic tissue characterization during surgery.展开更多
The mechanical behaviors of shape memory alloy （SMA） wires reinforced smart structure with damage were analyzed through the variational principle, a governing equation for the structure was derived, mathematical exp...The mechanical behaviors of shape memory alloy （SMA） wires reinforced smart structure with damage were analyzed through the variational principle, a governing equation for the structure was derived, mathematical expressions for the meso-displacement field, stressstrain field of typical element with damage were presented, and a failure criterion for interface failure between SMA wires and matrix was established under two kinds of actuation which are dead-load and temperature, where the temperature is included in effective free restoring strain. In addition, there are some other composing factors in the failure criterion such as the interface properties, dynamical properties of SMA, initial debonding length L - l etc. The results are significant to understand structural strength self-adapted control and failure mechanism of SMA wires reinforced smart structure with damage.展开更多
In this study,multivariate analysis methods,including a principal component analysis(PCA)and partial least square(PLS)analysis,were applied to reveal the inner relationship of the key variables in the process of H_(2)...In this study,multivariate analysis methods,including a principal component analysis(PCA)and partial least square(PLS)analysis,were applied to reveal the inner relationship of the key variables in the process of H_(2)O_(2)-assisted Na_(2)CO_(3)(HSC)pretreatment of corn stover.A total of 120 pretreatment experiments were implemented at the lab scale under different conditions by varying the particle size of the corn stover and process variables.The results showed that the Na_(2)CO_(3) dosage and pretreatment temperature had a strong influence on lignin removal,whereas pulp refining instrument(PFI)refining and Na_(2)CO_(3) dosage played positive roles in the final total sugar yield.Furthermore,it was found that pretreatment conditions had a more significant impact on the amelioration of pretreatment effectiveness compared with the properties of raw corn stover.In addition,a prediction of the effectiveness of the corn stover HSC pretreatment based on a PLS analysis was conducted for the first time,and the test results of the predictability based on additional pretreatment experiments proved that the developed PLS model achieved a good predictive performance(particularly for the final total sugar yield),indicating that the developed PLS model can be used to predict the effectiveness of HSC pretreatment.Therefore,multivariate analysis can be potentially used to monitor and control the pretreatment process in future large-scale biorefinery applications.展开更多
Background:Stem hardness is one of the major influencing factors for plant architecture in upland cotton(Gossypium hirsutum L.).Evaluating hardness phenotypic traits is very important for the selection of elite lines ...Background:Stem hardness is one of the major influencing factors for plant architecture in upland cotton(Gossypium hirsutum L.).Evaluating hardness phenotypic traits is very important for the selection of elite lines for resistance to lodging in Gossypium hirsutum L.Cotton breeders are interested in using diverse genotypes to enhance fiber quality and high-yield.Few pieces of research for hardness and its relationship with fiber quality and yield were found.This study was designed to find the relationship of stem hardness traits with fiber quality and yield contributing traits of upland cotton.Results:Experiments were carried out to measure the bending,acupuncture,and compression properties of the stem from a collection of upland cotton genotypes,comprising 237 accessions.The results showed that the genotypic difference in stem hardness was highly significant among the genotypes,and the stem hardness traits(BL,BU,AL,AU,CL,and CU)have a positive association with fiber quality traits and yield-related traits.Statistical analyses of the results showed that in descriptive statistics result bending(BL,BU)has a maximum coefficient of variance,but fiber length and fiber strength have less coefficient of variance among the genotypes.Principal component analysis(PCA)trimmed quantitative characters into nine principal components.The first nine principal components(PC)with Eigenvalues>1 explained 86%of the variation among 237 accessions of cotton.Both 2017 and 2018,PCA results indicated that BL,BU,FL,FE,and LI contributed to their variability in PC1,and BU,AU,CU,FD,LP,and FWPB have shown their variability in PC2.Conclusion:We describe here the systematic study of the mechanism involved in the regulation of enhancing fiber quality and yield by stem bending strength,acupuncture,and compression properties of G.hirsutum.展开更多
NonLocal Means(NLM),taking fully advantage of image redundancy,has been proved to be very effective in noise removal.However,high computational load limits its wide application.Based on Principle Component Analysis(PC...NonLocal Means(NLM),taking fully advantage of image redundancy,has been proved to be very effective in noise removal.However,high computational load limits its wide application.Based on Principle Component Analysis(PCA),Principle Neighborhood Dictionary(PND) was proposed to reduce the computational load of NLM.Nevertheless,as the principle components in PND method are computed directly from noisy image neighborhoods,they are prone to be inaccurate due to the presence of noise.In this paper,an improved scheme for image denoising is proposed.This scheme is based on PND and uses preprocessing via Gaussian filter to eliminate the influence of noise.PCA is then used to project those filtered image neighborhood vectors onto a lower-dimensional space.With the preproc-essing process,the principle components computed are more accurate resulting in an improved de-noising performance.A comparison with some NLM based and state-of-art denoising methods shows that the proposed method performs well in terms of Peak Signal to Noise Ratio(PSNR) as well as image visual fidelity.The experimental results demonstrate that our method outperforms existing methods both subjectively and objectively.展开更多
Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feat...Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feature to improve the accuracy and efficiency when they are used for pattern recognition and clustering analysis. A Poisson Model-based Kernel (PMK) was proposed based on the Poisson distribution of the SAGE data. Kernel Principle Component Analysis (KPCA) with PMK was proposed and used in feature-extract analysis of mouse retinal SAGE data. The computa-tional results show that this algorithm can extract feature effectively and reduce dimensions of SAGE data.展开更多
How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle co...How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.展开更多
[Objective] The aim was to study on distribution of inorganic elements in kernel of Amygdalus communis L., providing reference for quality evaluation of A. communis L. species. [Method] Totally 26 species of inorganic...[Objective] The aim was to study on distribution of inorganic elements in kernel of Amygdalus communis L., providing reference for quality evaluation of A. communis L. species. [Method] Totally 26 species of inorganic elements in kernel, including Al, B, Be, Ca, Co, Cu, Fe, Mg, Mn, Mo, Na, Ni, P, Pb, Si, Sn, Sr, Ti, Zn, Cd, As, Se, V, Hg, Cr and K were measured with inductively coupled plasma emission spectrum （ICP-OES） and principal components analysis （PCA）. [Result] A. communis L. of different species and in different factories showed a similar curve in content of inorganic elements; absolute contents of the elements differed significantly. In addition, the accumulated variance contribution of five principle factors achieved as high as 84.371% and the variance contribution made by the first three factors accounted for 67.546%, proving that Fe, Ti, Pb, Na, Se, Cu, Mo, K, Zn, Ni, Ca and Sr were characteristic elements. [Conclusion] The method, which is brief, rapid and accurate, can be used for determination of inorganic elements in kernel of A. communis L., providing theoretical references for further development and utilization of A. communis L.展开更多
HPLC fingerprinting and quantification of gentiopicroside（GPS） and loganic acid（LA） in Gentianae Macrophyllae Radix（GMR） crude drugs were developed in this study.The samples were separated on Zorbax SB-C_（18） ...HPLC fingerprinting and quantification of gentiopicroside（GPS） and loganic acid（LA） in Gentianae Macrophyllae Radix（GMR） crude drugs were developed in this study.The samples were separated on Zorbax SB-C_（18） column（250 mm×4.6 mm, 5μm） with a linear gradient of acetonitrile and 0.04%phosphoric acid.The HPLC flow rate was 1.0 mL/min and a UV absorption was measured at 230 nm.An orthogonal L9（3^4） test was applied for the optimization of sample extraction conditions,and an aliquot of GMR sample（g） was extracted with 15-fold of 50%ethanol（mL） for 30 min by sonication.Quantitative analysis showed that the content of GPS（14.05 mg/g-74.61 mg/g） in all samples was obviously higher than that of LA（1.13 mg/g-40.46 mg/g）. Based on the content ratio of GPS over LA（1.8-11.4）,samples originated from Gentiana macrophylla（with content ratio of GPS over LA≤4.3） could be distinguished from those from G.dahurica and G.dahurica var.gracilipes（with content ratio of GPS over LA≥4.8）.The principle components analysis of the HPLC fingerprints showed that samples originated from G.macrophylla and G.dahurica（including G.dahurica var.gracilipes） could be divided into two groups.This established HPLC-DAD method could be efficiently used for the species identification and quality control of GMR crude drugs.展开更多
Polycyclic aromatic hydrocarbons （PAHs） are mainly produced by combustion processes and consist of a number of toxic com- pounds. They are always emitted as a mixture and have become a major type of pollutants in ur...Polycyclic aromatic hydrocarbons （PAHs） are mainly produced by combustion processes and consist of a number of toxic com- pounds. They are always emitted as a mixture and have become a major type of pollutants in urban areas. The degree of soil contamination by PAHs is of special concern in areas immediately in proximity to cities with heavy traffic, factories, older buildings, and infrastructure. The accumulation of soil PAHs is also affected by non-anthropogenie factors, such as climate, vegetation, and soil property. This paper reviews three typical source identification techniques, including diagnostic ratios, positive matrix factorization, and principle components analysis. The advantages or disadvantages of these techniques are analyzed. It is recommended that multiple identification techniques be used to determine the sources in order to minimize the weaknesses inherent in each method and thereby to strengthen the conclusions for PAH source identification.展开更多
This study addressed the relationship of river water pollution characteristics to land covers and human activities in the catchments in a complete river system named Cao-E River in eastern China.Based on the hydrogeoc...This study addressed the relationship of river water pollution characteristics to land covers and human activities in the catchments in a complete river system named Cao-E River in eastern China.Based on the hydrogeochemical data collected monthly over a period of 3 years,cluster analysis(CA) and principal component analysis(PCA) were adopted to categorize the river reaches and reveal their pollution characteristics.According to the differences of water quality in the river reaches and land use patterns and average population densities in their catchments,the whole river system could be categorized into three groups of river reaches,i.e.,non-point sources pollution reaches(NPSPR),urban reaches(UR) and mixed sources pollution reaches(MSPR).In UR and MSPR,the water quality was mainly impacted by nutrient and organic pollution,while in NPSPR nutrient pollution was the main cause.The nitrate was the main nitrogen form in NPSPR and particulate phosphorus was the main phosphorus form in MSPR.There were no apparent trends for the variations of pollutant concentrations with increasing river flows in NPSPR and MSPR,while in UR the pollutant concentrations decreased with increasing river flows.Thus dry season was the critical period for water pollution control in UR.Therefore,catchment land covers and human activities had significant impact on river reach water pollution type,nutrient forms and water quality responses to hydrological conditions,which might be crucial for developing strategies to combat water pollution in watershed scale.展开更多
The presence of heavy metals（HMs） in particulate matters（PMs） particularly fine particles such as PM2.5 poses potential risk to the health of human being. The purpose of this study was to analyze the contents of H...The presence of heavy metals（HMs） in particulate matters（PMs） particularly fine particles such as PM2.5 poses potential risk to the health of human being. The purpose of this study was to analyze the contents of HMs in PM2.5 in the atmospheric monitoring stations in Isfahan city,Iran, in different seasons between March 2014 and March 2015 and their source identification using principle component analysis（PCA）. The samples of PM2.5 were taken using a high volume sampler in 7 monitoring stations located throughout the city and industrial zones since March 2014 to March 2015. The HMs content of the samples was measured using ICP-MS.The results showed that the concentrations of As, Cd and Ni were in a range of 23–36, 1–12,and 5–76 ng/m3 at all the stations which exceeded the US-EPA standards. Furthermore,the concentrations of Cr and Cu reached to 153 and 167 ng/m3 in some stations which were also higher than the standard levels. Depending on the potential sources of HMs, their concentration in PM2.5 through the various seasons was different. PCA illustrated that the different potential sources of HMs in the atmosphere, showing that the most important sources of HMs originated from fossil fuel combustion, abrasion of vehicle tires, industrial activities（e.g., iron and steel industries） and dust storms. Management and control of air pollution of industrial plants and vehicles are suggested for decreasing the risk of the HMs in the region.展开更多
基金supported by the National Nature Science Foundation of China(10974171)Zhejiang Province Nature Science Foundation(LY12A04003)
文摘A theoretical method is presented,which analyzes properties of surface acoustic waves propagating on metallic gratings with finite thickness by combining finite element method with variational principle on surface acoustic waves propagating on periodic metal gratings. Based on D.P.Chen and Haus theory,a finite element method is used to investigate the effects of metallic gratings upon the propagation of surface acoustic waves.The coupling-of-modes parameters contributed by mechanical loading are expressed by the matrix derived from the finite element method.Consequently D.P.Chen and Haus theory can also be applied to analyze the properties of surface acoustic waves propagating on metallic gratings with finite thickness and arbitrary shape.Finally,the characteristics of surface acoustic waves propagating under gold and aluminum or silver gratings on a few piezoelectric crystals are studied.Numerical results of the coupling-of-modes parameters of the surface acoustic waves are obtained.
基金the National Natural Science Foundation of China(No.61572033)the Natural Science Foundation of Education Department of Anhui Province of China(No.KJ2015ZD08)the Higher Education Promotion Plan of Anhui Province of China(No.TSKJ2015B14)
文摘Block principle and pattern classification component analysis （BPCA） is a recently developed technique in computer vision In this paper, we propose a robust and sparse BPCA with Lp-norm, referred to as BPCALp-S, which inherits the robustness of BPCA-L1 due to the employment of adjustable Lp-norm. In order to perform a sparse modelling, the elastic net is integrated into the objective function. An iterative algorithm which extracts feature vectors one by one greedily is elaborately designed. The monotonicity of the proposed iterative procedure is theoretically guaranteed. Experiments of image classification and reconstruction on several benchmark sets show the effectiveness of the proposed approach.
文摘Brain arteriovenous malformation(BAVM) is frequently described as vascular malformation. Although computer tomography(CT), magnetic resonance imaging(MRI) and angiography can clearly detect lesions, there are no diagnostic biological markers of BAVM available. Current study demonstrated that micro RNA(mi RNA)showed a feasible marker for vascular disease. To find key correlations between these mi RNAs and the onset of BAVM, we carried out chip analysis of serum mi RNAs by identifying 18 potential markers of BAVM. We then constructed a principle component analysis and logistic regression(PCA-LR) model to analyze the 18 mi RNAs collected from 77 patients. Another 9 independent samples were used to test the resulting model. The results showed that mi RNAs hsa-mir-126-3p and hsa-mir-140 are important protective factors, while hsa-mir-338 is a dominating risk factor, all of which have stronger correlation with BAVM than others. We also compared the testing results using PCA-LR model with those using LR model. The comparison revealed that PCA-LR model is better in predicting the disease.
文摘In this paper, a set of variational formulas of solving nonlinear instability critical loads are established from the viewpoint of variational principle. The paper shows that it is very convenient to solve nonlinear instability critical load by using the variational formulas suggested in this paper.
文摘range of new social and economic challenges is facing the world following the end of the Cold War inthe 1990s, which come along with the progress of globalization. The United Nations hopes to get global businesses involved in this process by boosting corporate citizenship. Meanwhile, the world body, for the sake of its own development, tries to expand its influence in such a way as to encourage not only state players but also non-state players worldwide to adopt sustainable and socially responsible oolicies.
基金funded in part by the National Natural Science Foundation of China (31402039,31472079,31372294)the Beijing Natural Science Foundation (6154032)+2 种基金the Species and Breed Resources Conservation of the Ministry of Agriculture of China (2017-2019)the Cattle Breeding Innovative Research Team of Chinese Academy of Agricultural Sciences (cxgc-ias-03)the National Beef Cattle Industrial Technology System (CARS-37)
文摘Traditionally, Chinese indigenous cattle is geographically widespread. The present study analyzed based on genome-wide variants to evaluate the genetic background among 157 individuals from four representative indigenous cattle breeds of Hubei Province of China： Yiling yellow cattle （YL）, Bashan cattle （BS）, Wuling cattle （WL）, Zaobei cattle （ZB）, and 21 indi- viduals of Qinchuan cattle （QC） from the nearby Shanxi Province of China. Linkage disequilibrium （LD） analysis showed the LD of YL was the lowest （~=0.32） when the distance between markers was approximately 2 kb. Principle component analysis （PCA）, and neighbor-joining （NJ）-tree revealed a separation of Yiling yellow cattle from other geographic nearby local cattle breeds. In PCA plot, the YL and QC groups were segregated as expected; moreover, YL individuals clustered together more obviously. In the N J-tree, the YL group formed an independent branch and BS, WL, ZB groups were mixed. We then used the FST statistic approach to reveal long-term selection sweep of YL and other 4 cattle breeds. According to the selective sweep, we identified the unique pathways of YL, associated with production traits. Based on the results, it can be proposed that YL has its unique genetic characteristics of excellence resource, and it is an indispensable cattle breed in China.
基金Supported by the Program for New Century Excellent Talents in University (NCET-05-0573)Fujian Science and Technology Project (No2006I0018)the Science Project of the Education Department of Fujian Province(No 2006F5022)
文摘Banana is one of the main economic agrotypes in Zhangzhou, Fujian Province. The multitemporal ENVlSAT ASAR data with different polarization are used to classify the banana fields in this paper. Principal component analysis （PCA） was applied for six pairs of ASAR dual-polarization data. For its large leaves, banana has high backscatter. So the value of banana fields is high and shows very bright in the 1st component, which makes it much easier for banana fields extraction. Dual-polarization data provide more information, and the W and VH backscatter of banana show different characters with other land covers. Based on the analysis of the radar signature of banana fields and other land covers and the 1st compo- nent, banana fields are classified using object-oriented classifier. Compared to the field survey data and ASTER data, the accuracy of banana fields in the study area is 83.5%. It shows that the principal component analysis provides the useful information in SAR images analysis and makes the extraction of banana fields easier.
基金supported in part by the grants to Kirill Larin from NIH 1R01EY022362,1R01HL120140,U54HG006348,and DOD PRJ71Tsupported by grants to Wei-Chuan Shih from NSF CAREER Award (CBET-1151154)+1 种基金NASA Early Career Faculty Grant (NNX12AQ44G)Gulf of Mexico Research Initiative (GoMRI-030).
文摘Optical coherence tomography(OCT)provides significant advantages of high resolution(approaching the histopathology level)realtime imaging of tsess without use of contrast agents.Based on these advantages,the microstructural features of tumors can be visualized and detected intra-operatively.However,it is still not clinically accepted for tumor margin delin-eation due to poor specificity and accuracy.In contrast,Raman spectroscopy(RS)can obtain tissue information at the molecular level,but does not provide real-time inaging capability.Therefore,combining OCT and RS could provide synergy.To this end,we present a tissue analysis and dassification method using both the slope of OCT intensity signal Vs depth and the principle components from the RS spectrum as the indicators for tissuse characterization.The goal of this study was to understand prediction accuracy of OCT and combined OCT/RS method for dassification of optically similar tisues and organs.Our pilot experiments were performed on mouse kidneys,livers,and small intestines(SIs).The prediction accuracy with five-fold cross validation of the method has been evaluated by the support vector machine(SVM)method.The results demonstrate that tissue characterization based on the OCT/RS method was superior compared to using OCT structural information alone.This combined OCT/RS method is potentially useful as a noninvasive optical biopsy technique for rapid and automatic tissue characterization during surgery.
基金Project partially supported by the Aeronautical Science Foundation of China (No. 05G52054).
文摘The mechanical behaviors of shape memory alloy （SMA） wires reinforced smart structure with damage were analyzed through the variational principle, a governing equation for the structure was derived, mathematical expressions for the meso-displacement field, stressstrain field of typical element with damage were presented, and a failure criterion for interface failure between SMA wires and matrix was established under two kinds of actuation which are dead-load and temperature, where the temperature is included in effective free restoring strain. In addition, there are some other composing factors in the failure criterion such as the interface properties, dynamical properties of SMA, initial debonding length L - l etc. The results are significant to understand structural strength self-adapted control and failure mechanism of SMA wires reinforced smart structure with damage.
基金This work was financially supported by the National Natural Science Foundation of China(No.31870568)Shandong Provincial Natural Science Foundation for Distinguished Young Scholars(China)(No.ZR2019JQ10)+1 种基金the Major Program of the Shandong Province Natural Science Foundation(No.ZR2018ZB0208)the"Transformational Technologies for Clean Energy and Demonstration"Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA21060201).
文摘In this study,multivariate analysis methods,including a principal component analysis(PCA)and partial least square(PLS)analysis,were applied to reveal the inner relationship of the key variables in the process of H_(2)O_(2)-assisted Na_(2)CO_(3)(HSC)pretreatment of corn stover.A total of 120 pretreatment experiments were implemented at the lab scale under different conditions by varying the particle size of the corn stover and process variables.The results showed that the Na_(2)CO_(3) dosage and pretreatment temperature had a strong influence on lignin removal,whereas pulp refining instrument(PFI)refining and Na_(2)CO_(3) dosage played positive roles in the final total sugar yield.Furthermore,it was found that pretreatment conditions had a more significant impact on the amelioration of pretreatment effectiveness compared with the properties of raw corn stover.In addition,a prediction of the effectiveness of the corn stover HSC pretreatment based on a PLS analysis was conducted for the first time,and the test results of the predictability based on additional pretreatment experiments proved that the developed PLS model achieved a good predictive performance(particularly for the final total sugar yield),indicating that the developed PLS model can be used to predict the effectiveness of HSC pretreatment.Therefore,multivariate analysis can be potentially used to monitor and control the pretreatment process in future large-scale biorefinery applications.
基金National Key Technology R&D Program,Ministry of Science and Technology(2016YFD0100306,2016YFD0100203)National Natural Science Foundation of China(grants 31671746).
文摘Background:Stem hardness is one of the major influencing factors for plant architecture in upland cotton(Gossypium hirsutum L.).Evaluating hardness phenotypic traits is very important for the selection of elite lines for resistance to lodging in Gossypium hirsutum L.Cotton breeders are interested in using diverse genotypes to enhance fiber quality and high-yield.Few pieces of research for hardness and its relationship with fiber quality and yield were found.This study was designed to find the relationship of stem hardness traits with fiber quality and yield contributing traits of upland cotton.Results:Experiments were carried out to measure the bending,acupuncture,and compression properties of the stem from a collection of upland cotton genotypes,comprising 237 accessions.The results showed that the genotypic difference in stem hardness was highly significant among the genotypes,and the stem hardness traits(BL,BU,AL,AU,CL,and CU)have a positive association with fiber quality traits and yield-related traits.Statistical analyses of the results showed that in descriptive statistics result bending(BL,BU)has a maximum coefficient of variance,but fiber length and fiber strength have less coefficient of variance among the genotypes.Principal component analysis(PCA)trimmed quantitative characters into nine principal components.The first nine principal components(PC)with Eigenvalues>1 explained 86%of the variation among 237 accessions of cotton.Both 2017 and 2018,PCA results indicated that BL,BU,FL,FE,and LI contributed to their variability in PC1,and BU,AU,CU,FD,LP,and FWPB have shown their variability in PC2.Conclusion:We describe here the systematic study of the mechanism involved in the regulation of enhancing fiber quality and yield by stem bending strength,acupuncture,and compression properties of G.hirsutum.
基金Supported by the National Natural Science Foundation of China (No. 60776795,60736043,60902031,and 60805012)the Research Fund for the Doctoral Program of Higher Education of China (No. 200807010004,20070701023)the Fundamental Research Funds for the Central Universities of China (No. JY10000902028)
文摘NonLocal Means(NLM),taking fully advantage of image redundancy,has been proved to be very effective in noise removal.However,high computational load limits its wide application.Based on Principle Component Analysis(PCA),Principle Neighborhood Dictionary(PND) was proposed to reduce the computational load of NLM.Nevertheless,as the principle components in PND method are computed directly from noisy image neighborhoods,they are prone to be inaccurate due to the presence of noise.In this paper,an improved scheme for image denoising is proposed.This scheme is based on PND and uses preprocessing via Gaussian filter to eliminate the influence of noise.PCA is then used to project those filtered image neighborhood vectors onto a lower-dimensional space.With the preproc-essing process,the principle components computed are more accurate resulting in an improved de-noising performance.A comparison with some NLM based and state-of-art denoising methods shows that the proposed method performs well in terms of Peak Signal to Noise Ratio(PSNR) as well as image visual fidelity.The experimental results demonstrate that our method outperforms existing methods both subjectively and objectively.
基金Supported by the National Natural Science Foundation of China (No. 50877004)
文摘Serial Analysis of Gene Expression (SAGE) is a powerful tool to analyze whole-genome expression profiles. SAGE data, characterized by large quantity and high dimensions, need reducing their dimensions and extract feature to improve the accuracy and efficiency when they are used for pattern recognition and clustering analysis. A Poisson Model-based Kernel (PMK) was proposed based on the Poisson distribution of the SAGE data. Kernel Principle Component Analysis (KPCA) with PMK was proposed and used in feature-extract analysis of mouse retinal SAGE data. The computa-tional results show that this algorithm can extract feature effectively and reduce dimensions of SAGE data.
基金National Key Science & Technology Special Projects(Grant No.2008ZX05000-004)CNPC Projects(Grant No.2008E-0610-10).
文摘How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.
基金Supported by the Pillar Program of Ministry of Science and Technology of the People's Republic of China (2012BAI27B07)the Fundamental Research Funds for the Central Universities (11NZYTH02)+1 种基金Sichuan Key Technology Research and Development Program (2011SZ0233)Academic Technology for Excellent Youth Follow-up Plan in Sichuan (2011JQ0051)~~
文摘[Objective] The aim was to study on distribution of inorganic elements in kernel of Amygdalus communis L., providing reference for quality evaluation of A. communis L. species. [Method] Totally 26 species of inorganic elements in kernel, including Al, B, Be, Ca, Co, Cu, Fe, Mg, Mn, Mo, Na, Ni, P, Pb, Si, Sn, Sr, Ti, Zn, Cd, As, Se, V, Hg, Cr and K were measured with inductively coupled plasma emission spectrum （ICP-OES） and principal components analysis （PCA）. [Result] A. communis L. of different species and in different factories showed a similar curve in content of inorganic elements; absolute contents of the elements differed significantly. In addition, the accumulated variance contribution of five principle factors achieved as high as 84.371% and the variance contribution made by the first three factors accounted for 67.546%, proving that Fe, Ti, Pb, Na, Se, Cu, Mo, K, Zn, Ni, Ca and Sr were characteristic elements. [Conclusion] The method, which is brief, rapid and accurate, can be used for determination of inorganic elements in kernel of A. communis L., providing theoretical references for further development and utilization of A. communis L.
基金Research Program of Science Technology of Traditional Chinese Medicine(TCM) Sponsored by the State Administration of TCM of China(Grant No.04-05ZL01)
文摘HPLC fingerprinting and quantification of gentiopicroside（GPS） and loganic acid（LA） in Gentianae Macrophyllae Radix（GMR） crude drugs were developed in this study.The samples were separated on Zorbax SB-C_（18） column（250 mm×4.6 mm, 5μm） with a linear gradient of acetonitrile and 0.04%phosphoric acid.The HPLC flow rate was 1.0 mL/min and a UV absorption was measured at 230 nm.An orthogonal L9（3^4） test was applied for the optimization of sample extraction conditions,and an aliquot of GMR sample（g） was extracted with 15-fold of 50%ethanol（mL） for 30 min by sonication.Quantitative analysis showed that the content of GPS（14.05 mg/g-74.61 mg/g） in all samples was obviously higher than that of LA（1.13 mg/g-40.46 mg/g）. Based on the content ratio of GPS over LA（1.8-11.4）,samples originated from Gentiana macrophylla（with content ratio of GPS over LA≤4.3） could be distinguished from those from G.dahurica and G.dahurica var.gracilipes（with content ratio of GPS over LA≥4.8）.The principle components analysis of the HPLC fingerprints showed that samples originated from G.macrophylla and G.dahurica（including G.dahurica var.gracilipes） could be divided into two groups.This established HPLC-DAD method could be efficiently used for the species identification and quality control of GMR crude drugs.
基金the financial support from the National Natural Science Foundation of China(No.41671085)
文摘Polycyclic aromatic hydrocarbons （PAHs） are mainly produced by combustion processes and consist of a number of toxic com- pounds. They are always emitted as a mixture and have become a major type of pollutants in urban areas. The degree of soil contamination by PAHs is of special concern in areas immediately in proximity to cities with heavy traffic, factories, older buildings, and infrastructure. The accumulation of soil PAHs is also affected by non-anthropogenie factors, such as climate, vegetation, and soil property. This paper reviews three typical source identification techniques, including diagnostic ratios, positive matrix factorization, and principle components analysis. The advantages or disadvantages of these techniques are analyzed. It is recommended that multiple identification techniques be used to determine the sources in order to minimize the weaknesses inherent in each method and thereby to strengthen the conclusions for PAH source identification.
基金Supported by the National Natural Science Foundation of China (No. 40871104)the National High Technology Research andDevelopment Program (863 Program) of China (No. 2007AA10Z218)
文摘This study addressed the relationship of river water pollution characteristics to land covers and human activities in the catchments in a complete river system named Cao-E River in eastern China.Based on the hydrogeochemical data collected monthly over a period of 3 years,cluster analysis(CA) and principal component analysis(PCA) were adopted to categorize the river reaches and reveal their pollution characteristics.According to the differences of water quality in the river reaches and land use patterns and average population densities in their catchments,the whole river system could be categorized into three groups of river reaches,i.e.,non-point sources pollution reaches(NPSPR),urban reaches(UR) and mixed sources pollution reaches(MSPR).In UR and MSPR,the water quality was mainly impacted by nutrient and organic pollution,while in NPSPR nutrient pollution was the main cause.The nitrate was the main nitrogen form in NPSPR and particulate phosphorus was the main phosphorus form in MSPR.There were no apparent trends for the variations of pollutant concentrations with increasing river flows in NPSPR and MSPR,while in UR the pollutant concentrations decreased with increasing river flows.Thus dry season was the critical period for water pollution control in UR.Therefore,catchment land covers and human activities had significant impact on river reach water pollution type,nutrient forms and water quality responses to hydrological conditions,which might be crucial for developing strategies to combat water pollution in watershed scale.
基金financially supported by the Fundamental Research Funds for the central University,China University of Geosciences(Wuhan)(No.CUG150602)the International collaboration project funded by the China University of Geosciences(Wuhan)
文摘The presence of heavy metals（HMs） in particulate matters（PMs） particularly fine particles such as PM2.5 poses potential risk to the health of human being. The purpose of this study was to analyze the contents of HMs in PM2.5 in the atmospheric monitoring stations in Isfahan city,Iran, in different seasons between March 2014 and March 2015 and their source identification using principle component analysis（PCA）. The samples of PM2.5 were taken using a high volume sampler in 7 monitoring stations located throughout the city and industrial zones since March 2014 to March 2015. The HMs content of the samples was measured using ICP-MS.The results showed that the concentrations of As, Cd and Ni were in a range of 23–36, 1–12,and 5–76 ng/m3 at all the stations which exceeded the US-EPA standards. Furthermore,the concentrations of Cr and Cu reached to 153 and 167 ng/m3 in some stations which were also higher than the standard levels. Depending on the potential sources of HMs, their concentration in PM2.5 through the various seasons was different. PCA illustrated that the different potential sources of HMs in the atmosphere, showing that the most important sources of HMs originated from fossil fuel combustion, abrasion of vehicle tires, industrial activities（e.g., iron and steel industries） and dust storms. Management and control of air pollution of industrial plants and vehicles are suggested for decreasing the risk of the HMs in the region.
