ln this study, 12 maize populations were improved with the improved S1 selection method, aiming to increase the improvement efficiency of maize popula-tions. The results showed that number of rows per spike, number of...ln this study, 12 maize populations were improved with the improved S1 selection method, aiming to increase the improvement efficiency of maize popula-tions. The results showed that number of rows per spike, number of grains per row and 100-grain weight were the three important component traits of maize yield. The highest genetic increment was found in Mengqun 2, fol owed by Mengqun 4, Mengqun 1 and other 7 maize populations. Negative genetic increment was shown in Mengqun 3 and 3 introduced foreign maize populations. Some changes were shown in spikes, plant traits and genetic diversity of maize populations. Based on our results, we concluded that Mengqun 2, Mengqun 4, Zhongzong 7, Mengqun C and Mengqun A could be directly used for the line breeding by selfing for their higher genetic increment of yield and better improvement effects of other agricultural traits. Compared with these 5 populations, the improvement potential of other maize populations was limited for their lower genetic increment.展开更多
The fruit-bearing quantities of nut Korean pines (Pinus Koraiensis) of natural stands in Changbai Mountain, Xiaoxing'an Mountain, and Wanda Mountain and of artificial forest in Hegang area of Heilongjiang Province...The fruit-bearing quantities of nut Korean pines (Pinus Koraiensis) of natural stands in Changbai Mountain, Xiaoxing'an Mountain, and Wanda Mountain and of artificial forest in Hegang area of Heilongjiang Province were investigated and measured by seed collection of singletree during 1988–1998. In order to evaluate the elite nut tree of fructification, the characteristics of fructification of Korena pine, including, the fruit-bearing quantity, output of seed, quantity of cone, cone size, seed size, the ratio of null seed by solid seed, seed percentage of cone, rate of the cones infested with pest, and fruit-bearing index, etc., were analyzed with the variance analysis, multiple comparison and stepwise regression to obtain the contribution ratio of each fruit-bearing factor to fruit-bearing quantity. The multiple correlation factors and the partial correlation factors for fruit-bearing quantities of Korean pine were determined for different geographical areas, and the cone length, thousand-grain-weight, and the seed percentage of cone were considered as important indices for selection of elite trees. The method of modified weighted coefficients was adopted to select the elite nut trees of Korean pine. Standards for selecting elite nut trees from the natural stands and artificial forest of Korean pine were established. This study could provde selection method and standard of elite nut trees for setting up seed orchard of Korean Pine.展开更多
To research the effect of the selection method of multi — objects genetic algorithm problem on optimizing result, this method is analyzed theoretically and discussed by using an autonomous underwater vehicle (AUV) as...To research the effect of the selection method of multi — objects genetic algorithm problem on optimizing result, this method is analyzed theoretically and discussed by using an autonomous underwater vehicle (AUV) as an object. A changing weight value method is put forward and a selection formula is modified. Some experiments were implemented on an AUV, TwinBurger. The results shows that this method is effective and feasible.展开更多
One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developi...One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.展开更多
The increasing prevalence of diabetes has led to a growing population of endstage kidney disease(ESKD)patients with diabetes.Currently,kidney transplantation is the best treatment option for ESKD patients;however,it i...The increasing prevalence of diabetes has led to a growing population of endstage kidney disease(ESKD)patients with diabetes.Currently,kidney transplantation is the best treatment option for ESKD patients;however,it is limited by the lack of donors.Therefore,dialysis has become the standard treatment for ESKD patients.However,the optimal dialysis method for diabetic ESKD patients remains controversial.ESKD patients with diabetes often present with complex conditions and numerous complications.Furthermore,these patients face a high risk of infection and technical failure,are more susceptible to malnutrition,have difficulty establishing vascular access,and experience more frequent blood sugar fluctuations than the general population.Therefore,this article reviews nine critical aspects:Survival rate,glucose metabolism disorder,infectious complications,cardiovascular events,residual renal function,quality of life,economic benefits,malnutrition,and volume load.This study aims to assist clinicians in selecting individualized treatment methods by comparing the advantages and disadvantages of hemodialysis and peritoneal dialysis,thereby improving patients’quality of life and survival rates.展开更多
Several millions of people suffer from Parkinson’s disease globally.Parkinson’s affects about 1%of people over 60 and its symptoms increase with age.The voice may be affected and patients experience abnormalities in...Several millions of people suffer from Parkinson’s disease globally.Parkinson’s affects about 1%of people over 60 and its symptoms increase with age.The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners,but which could be analyzed using recorded speech signals.With the huge advancements of technology,the medical data has increased dramatically,and therefore,there is a need to apply data mining and machine learning methods to extract new knowledge from this data.Several classification methods were used to analyze medical data sets and diagnostic problems,such as Parkinson’s Disease(PD).In addition,to improve the performance of classification,feature selection methods have been extensively used in many fields.This paper aims to propose a comprehensive approach to enhance the prediction of PD using several machine learning methods with different feature selection methods such as filter-based and wrapper-based.The dataset includes 240 recodes with 46 acoustic features extracted from3 voice recording replications for 80 patients.The experimental results showed improvements when wrapper-based features selection method was used with K-NN classifier with accuracy of 88.33%.The best obtained results were compared with other studies and it was found that this study provides comparable and superior results.展开更多
Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil s...Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.展开更多
Mining method selection is the first and the most critical problem in mine design and depends on some parameters such as geotechnical and geological features and economic and geographic factors. In this paper, the fac...Mining method selection is the first and the most critical problem in mine design and depends on some parameters such as geotechnical and geological features and economic and geographic factors. In this paper, the factors affecting mining method selection are determined. These factors include shape, thick- ness, depth, slope, RMR and RSS of the orebody, RMR and RSS of the hanging wall and footwall. Then, the priorities of these factors are calculated. In order to calculate the priorities of factors and select the best mining method for Qapiliq salt mine, Iran, based on these priorities, fuzzy analytical hierarchy process （AHP） technique is used. For this purpose, a questionnaire was prepared and was given to the associated experts. Finally, after a comparison carried out based on the effective factors, between the four mining methods including area mining, room and pillar, cut and fill and stope and pillar methods, the stope and nillar mining method was selected as the most suitable method to this mine.展开更多
Aiming to deficiency of the filter and wrapper feature selection methods, anew method based on composite method of filter and wrapper method is proposed. First the methodfilters original features to form a feature sub...Aiming to deficiency of the filter and wrapper feature selection methods, anew method based on composite method of filter and wrapper method is proposed. First the methodfilters original features to form a feature subset which can meet classification correctness rate,then applies wrapper feature selection method select optimal feature subset. A successful techniquefor solving optimization problems is given by genetic algorithm (GA). GA is applied to the problemof optimal feature selection. The composite method saves computing time several times of the wrappermethod with holding the classification accuracy in data simulation and experiment on bearing faultfeature selection. So this method possesses excellent optimization property, can save more selectiontime, and has the characteristics of high accuracy and high efficiency.展开更多
The Cu-Zr-Ce-O catalysts prepared using the coprecipitation method exhibited better catalytic performance for CO selective oxidation. The Cu-Zr-Ce-O catalysts pretreated with different methods were studied by CO-TPR a...The Cu-Zr-Ce-O catalysts prepared using the coprecipitation method exhibited better catalytic performance for CO selective oxidation. The Cu-Zr-Ce-O catalysts pretreated with different methods were studied by CO-TPR and XPS techniques. The results showed that the Cu-Zr-Ce-O catalyst pretreated with oxygen exhibited the best catalytic performance and had the widest operating temperature window, with CO conversion above 99% from 160 to 200 ℃. The O2 pretreatment caused an enrichment of the oxygen storaged on the Cu active species and promoted the conversion of adsorbed oxygen into surface lattice oxygen. It also improved the amount of Cu＋/Cu^2＋ ionic pair, and then facilitated the formation of CuO active species on the catalyst for selective CO oxidation.展开更多
Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to br...Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools Mix P and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop(Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction(GBLUP) method which has been applied widely. Our results showed that both Mix P and gsbay could accurately estimate single-nucleotide polymorphism(SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values(GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by Mix P; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by Mix P and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with Mix P the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by Mix P and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.展开更多
We propose an improved finite temperature Lanczos method using the stochastic state selection method. In the finite temperature Lanczos method, we generate Lanczos states and calculate the eigenvalues. In addition we ...We propose an improved finite temperature Lanczos method using the stochastic state selection method. In the finite temperature Lanczos method, we generate Lanczos states and calculate the eigenvalues. In addition we have to calculate matrix elements that are the values of an operator between two Lanczos states. In the calculations of the matrix elements we have to keep the set of Lanczos states on the computer memory. Therefore the memory limits the system size in the calculations. Here we propose an application of the stochastic state selection method in order to weaken this limitation. This method is to select some parts of basis states stochastically and to abandon other basis state. Only by the selected basis states we calculate the inner product. After making the statistical average, we can obtain the correct value of the inner product. By the stochastic state selection method we can reduce the number of the basis states for calculations. As a result we can relax the limitation on the computer memory. In order to study the Higgs mode at finite temperature, we calculate the dynamical correlations of the two spin operators in the spin-1/2 Heisenberg antiferromagnet on the square lattice using the improved finite temperature Lanczos method. Our results on the lattices of up to 32 sites show that the Higgs mode exists at low temperature and it disappears gradually when the temperature becomes large. At high temperature we do not find this mode in the dynamical correlations.展开更多
Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to cap...Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to capture process properties. In quantitative online applications,the robustness of the established NIR model is often deteriorated by process condition variations,nonlinear of the properties or the high-dimensional of the NIR data set. To cope with such situation,a novel method based on principal component analysis( PCA) and artificial neural network( ANN) is proposed and a new sample-selection method is mentioned. The advantage of the presented approach is that it can select proper calibration samples and establish robust model effectively. The performance of the method was tested on a spectroscopic data set from a refinery process. Compared with traditional partial leastsquares( PLS),principal component regression( PCR) and several other modeling methods, the proposed approach was found to achieve good accuracy in the prediction of gasoline properties. An application of the proposed method is also reported.展开更多
Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in ...Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in a base station, a false alarm is occurred, and the energy of the nodes is consumed. To detect the false report, statistical en-route filtering method is proposed. In this paper, we proposed the secure path cycle selection method using fuzzy rule-based system to consume effective energy. The method makes balanced energy consumption of each node. Moreover, the lifetime of the whole network will be increased. The base station determines the path cycle using the fuzzy rule-based system. The performance of the proposed method is demonstrated using simulation studies with the three methods.展开更多
Objective To study the policies of integrating medical resources and centralized drug procurement in China from 2018 to 2020,and to provide a reference for large pharmaceutical commercial companies to select partners....Objective To study the policies of integrating medical resources and centralized drug procurement in China from 2018 to 2020,and to provide a reference for large pharmaceutical commercial companies to select partners.Methods Analytic hierarchy process(AHP)and fuzzy synthesis evaluation method were used to establish the index evaluation system and assign values to each index.Results and Conclusion According to the questionnaire survey data,the weight of each evaluation index was determined,and the evaluation results were obtained by using the fuzzy synthesis evaluation method.The selection of production enterprises by large pharmaceutical commercial companies includes five first-level indicators and 11 second-level indicators.They can provide a favorable reference for the selection of production enterprises by large pharmaceutical commercial companies against the background of complex pharmaceutical industry.展开更多
Objective To investigate the difference between different surgical methods for thoracic ossification of ligamentum flavum(OLF) combined with cervical spondylotic myelopathy(CSM) . Methods From January 1991 to January ...Objective To investigate the difference between different surgical methods for thoracic ossification of ligamentum flavum(OLF) combined with cervical spondylotic myelopathy(CSM) . Methods From January 1991 to January 2003,56 cases展开更多
Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monit...Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.展开更多
基金Supported by Science and Technology Innovation Guiding and Incentive Fund of Inner Mongolia Autonomous Region(20111705)~~
文摘ln this study, 12 maize populations were improved with the improved S1 selection method, aiming to increase the improvement efficiency of maize popula-tions. The results showed that number of rows per spike, number of grains per row and 100-grain weight were the three important component traits of maize yield. The highest genetic increment was found in Mengqun 2, fol owed by Mengqun 4, Mengqun 1 and other 7 maize populations. Negative genetic increment was shown in Mengqun 3 and 3 introduced foreign maize populations. Some changes were shown in spikes, plant traits and genetic diversity of maize populations. Based on our results, we concluded that Mengqun 2, Mengqun 4, Zhongzong 7, Mengqun C and Mengqun A could be directly used for the line breeding by selfing for their higher genetic increment of yield and better improvement effects of other agricultural traits. Compared with these 5 populations, the improvement potential of other maize populations was limited for their lower genetic increment.
基金Sciences and Technology Office of Heilongjiang Province (a grant G99B5-10).
文摘The fruit-bearing quantities of nut Korean pines (Pinus Koraiensis) of natural stands in Changbai Mountain, Xiaoxing'an Mountain, and Wanda Mountain and of artificial forest in Hegang area of Heilongjiang Province were investigated and measured by seed collection of singletree during 1988–1998. In order to evaluate the elite nut tree of fructification, the characteristics of fructification of Korena pine, including, the fruit-bearing quantity, output of seed, quantity of cone, cone size, seed size, the ratio of null seed by solid seed, seed percentage of cone, rate of the cones infested with pest, and fruit-bearing index, etc., were analyzed with the variance analysis, multiple comparison and stepwise regression to obtain the contribution ratio of each fruit-bearing factor to fruit-bearing quantity. The multiple correlation factors and the partial correlation factors for fruit-bearing quantities of Korean pine were determined for different geographical areas, and the cone length, thousand-grain-weight, and the seed percentage of cone were considered as important indices for selection of elite trees. The method of modified weighted coefficients was adopted to select the elite nut trees of Korean pine. Standards for selecting elite nut trees from the natural stands and artificial forest of Korean pine were established. This study could provde selection method and standard of elite nut trees for setting up seed orchard of Korean Pine.
文摘To research the effect of the selection method of multi — objects genetic algorithm problem on optimizing result, this method is analyzed theoretically and discussed by using an autonomous underwater vehicle (AUV) as an object. A changing weight value method is put forward and a selection formula is modified. Some experiments were implemented on an AUV, TwinBurger. The results shows that this method is effective and feasible.
文摘One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.
基金Supported by Science and Technology Department of Jilin Province,No.YDZJ202201ZYTS110 and No.20200201352JC.
文摘The increasing prevalence of diabetes has led to a growing population of endstage kidney disease(ESKD)patients with diabetes.Currently,kidney transplantation is the best treatment option for ESKD patients;however,it is limited by the lack of donors.Therefore,dialysis has become the standard treatment for ESKD patients.However,the optimal dialysis method for diabetic ESKD patients remains controversial.ESKD patients with diabetes often present with complex conditions and numerous complications.Furthermore,these patients face a high risk of infection and technical failure,are more susceptible to malnutrition,have difficulty establishing vascular access,and experience more frequent blood sugar fluctuations than the general population.Therefore,this article reviews nine critical aspects:Survival rate,glucose metabolism disorder,infectious complications,cardiovascular events,residual renal function,quality of life,economic benefits,malnutrition,and volume load.This study aims to assist clinicians in selecting individualized treatment methods by comparing the advantages and disadvantages of hemodialysis and peritoneal dialysis,thereby improving patients’quality of life and survival rates.
基金This research was funded by the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia under the Project Number(77/442).
文摘Several millions of people suffer from Parkinson’s disease globally.Parkinson’s affects about 1%of people over 60 and its symptoms increase with age.The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners,but which could be analyzed using recorded speech signals.With the huge advancements of technology,the medical data has increased dramatically,and therefore,there is a need to apply data mining and machine learning methods to extract new knowledge from this data.Several classification methods were used to analyze medical data sets and diagnostic problems,such as Parkinson’s Disease(PD).In addition,to improve the performance of classification,feature selection methods have been extensively used in many fields.This paper aims to propose a comprehensive approach to enhance the prediction of PD using several machine learning methods with different feature selection methods such as filter-based and wrapper-based.The dataset includes 240 recodes with 46 acoustic features extracted from3 voice recording replications for 80 patients.The experimental results showed improvements when wrapper-based features selection method was used with K-NN classifier with accuracy of 88.33%.The best obtained results were compared with other studies and it was found that this study provides comparable and superior results.
基金supported financially by the National Natural Science Foundation of China (91325301, 41571212 and 41137224)the Project of "One-Three-Five" Strategic Planning & Frontier Sciences of the Institute of Soil Science, Chinese Academy of Sciences (ISSASIP1622)the National Key Basic Research Special Foundation of China (2012FY112100)
文摘Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.
文摘Mining method selection is the first and the most critical problem in mine design and depends on some parameters such as geotechnical and geological features and economic and geographic factors. In this paper, the factors affecting mining method selection are determined. These factors include shape, thick- ness, depth, slope, RMR and RSS of the orebody, RMR and RSS of the hanging wall and footwall. Then, the priorities of these factors are calculated. In order to calculate the priorities of factors and select the best mining method for Qapiliq salt mine, Iran, based on these priorities, fuzzy analytical hierarchy process （AHP） technique is used. For this purpose, a questionnaire was prepared and was given to the associated experts. Finally, after a comparison carried out based on the effective factors, between the four mining methods including area mining, room and pillar, cut and fill and stope and pillar methods, the stope and nillar mining method was selected as the most suitable method to this mine.
基金This project is supported by Scientific Research Foundation of National Defence of China (No.41319040202).
文摘Aiming to deficiency of the filter and wrapper feature selection methods, anew method based on composite method of filter and wrapper method is proposed. First the methodfilters original features to form a feature subset which can meet classification correctness rate,then applies wrapper feature selection method select optimal feature subset. A successful techniquefor solving optimization problems is given by genetic algorithm (GA). GA is applied to the problemof optimal feature selection. The composite method saves computing time several times of the wrappermethod with holding the classification accuracy in data simulation and experiment on bearing faultfeature selection. So this method possesses excellent optimization property, can save more selectiontime, and has the characteristics of high accuracy and high efficiency.
基金supported by the National Natural Science Foundation of China(Grant No.30800776)the State High-Tech Development Plan of China(Grant No.2008AA101002)the Recommend International Advanced Agricultural Science and Technology Plan of China(Grant No2011-G2A)
基金supported by the National Nature Science Foundation of China (Project No.20576023)the Natural Science Foundation of Guangdong Province (Project No.06025660).
文摘The Cu-Zr-Ce-O catalysts prepared using the coprecipitation method exhibited better catalytic performance for CO selective oxidation. The Cu-Zr-Ce-O catalysts pretreated with different methods were studied by CO-TPR and XPS techniques. The results showed that the Cu-Zr-Ce-O catalyst pretreated with oxygen exhibited the best catalytic performance and had the widest operating temperature window, with CO conversion above 99% from 160 to 200 ℃. The O2 pretreatment caused an enrichment of the oxygen storaged on the Cu active species and promoted the conversion of adsorbed oxygen into surface lattice oxygen. It also improved the amount of Cu＋/Cu^2＋ ionic pair, and then facilitated the formation of CuO active species on the catalyst for selective CO oxidation.
基金supported by the National High-Tech R&D Program (863 Program No. 2012AA10A405)the earmarked fund for Modern Agro-industry Technology Research Systemthe National Natural Science Foundation of China (No. 31302182)
文摘Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools Mix P and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop(Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction(GBLUP) method which has been applied widely. Our results showed that both Mix P and gsbay could accurately estimate single-nucleotide polymorphism(SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values(GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by Mix P; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by Mix P and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with Mix P the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by Mix P and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.
文摘We propose an improved finite temperature Lanczos method using the stochastic state selection method. In the finite temperature Lanczos method, we generate Lanczos states and calculate the eigenvalues. In addition we have to calculate matrix elements that are the values of an operator between two Lanczos states. In the calculations of the matrix elements we have to keep the set of Lanczos states on the computer memory. Therefore the memory limits the system size in the calculations. Here we propose an application of the stochastic state selection method in order to weaken this limitation. This method is to select some parts of basis states stochastically and to abandon other basis state. Only by the selected basis states we calculate the inner product. After making the statistical average, we can obtain the correct value of the inner product. By the stochastic state selection method we can reduce the number of the basis states for calculations. As a result we can relax the limitation on the computer memory. In order to study the Higgs mode at finite temperature, we calculate the dynamical correlations of the two spin operators in the spin-1/2 Heisenberg antiferromagnet on the square lattice using the improved finite temperature Lanczos method. Our results on the lattices of up to 32 sites show that the Higgs mode exists at low temperature and it disappears gradually when the temperature becomes large. At high temperature we do not find this mode in the dynamical correlations.
基金National Natural Science Foundations of China(Nos.U1162202,61222303)National High-Tech Research and Development Program of China(No.2013AA040701)the Fundamental Research Funds for the Central Universities and Shanghai Leading Academic Discipline Project,China(No.B504)
文摘Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to capture process properties. In quantitative online applications,the robustness of the established NIR model is often deteriorated by process condition variations,nonlinear of the properties or the high-dimensional of the NIR data set. To cope with such situation,a novel method based on principal component analysis( PCA) and artificial neural network( ANN) is proposed and a new sample-selection method is mentioned. The advantage of the presented approach is that it can select proper calibration samples and establish robust model effectively. The performance of the method was tested on a spectroscopic data set from a refinery process. Compared with traditional partial leastsquares( PLS),principal component regression( PCR) and several other modeling methods, the proposed approach was found to achieve good accuracy in the prediction of gasoline properties. An application of the proposed method is also reported.
文摘Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in a base station, a false alarm is occurred, and the energy of the nodes is consumed. To detect the false report, statistical en-route filtering method is proposed. In this paper, we proposed the secure path cycle selection method using fuzzy rule-based system to consume effective energy. The method makes balanced energy consumption of each node. Moreover, the lifetime of the whole network will be increased. The base station determines the path cycle using the fuzzy rule-based system. The performance of the proposed method is demonstrated using simulation studies with the three methods.
基金2021 Scientific Research of Liaoning Provincial Department of Education Fund(No.LJKZ0298)Key projects of Shenyang Philosophy and Social Science Planning Fund(No.SZ202001L).
文摘Objective To study the policies of integrating medical resources and centralized drug procurement in China from 2018 to 2020,and to provide a reference for large pharmaceutical commercial companies to select partners.Methods Analytic hierarchy process(AHP)and fuzzy synthesis evaluation method were used to establish the index evaluation system and assign values to each index.Results and Conclusion According to the questionnaire survey data,the weight of each evaluation index was determined,and the evaluation results were obtained by using the fuzzy synthesis evaluation method.The selection of production enterprises by large pharmaceutical commercial companies includes five first-level indicators and 11 second-level indicators.They can provide a favorable reference for the selection of production enterprises by large pharmaceutical commercial companies against the background of complex pharmaceutical industry.
文摘Objective To investigate the difference between different surgical methods for thoracic ossification of ligamentum flavum(OLF) combined with cervical spondylotic myelopathy(CSM) . Methods From January 1991 to January 2003,56 cases
基金supported in part by National Natural Science Foundation of China(NSFC)(51627811,51707064)Project Supported by the National Key Research and Development Program of China(2017YFB090204)Project of State Grid Corporation of China(SGTYHT/16-JS-198)
文摘Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.
