Avian metapneumovirus(aMPV),a paramyxovirus,causes acute respiratory diseases in turkeys and swollen head syndrome in chickens.This study established a reverse genetics system for aMPV subtype B LN16-A strain based on...Avian metapneumovirus(aMPV),a paramyxovirus,causes acute respiratory diseases in turkeys and swollen head syndrome in chickens.This study established a reverse genetics system for aMPV subtype B LN16-A strain based on T7 RNA polymerase.Full-length cDNA of the LN16-A strain was constructed by assembling 5 cDNA fragments between the T7 promoter and hepatitis delta virus ribozyme.Transfection of this plasmid,along with the supporting plasmids encoding the N,P,M2-1,and L proteins of LN16-A into BSR-T7/5 cells,resulted in the recovery of aMPV subtype B.To identify an effective insertion site,the enhanced green fluorescent protein(EGFP)gene was inserted into different sites of the LN16-A genome to generate recombinant LN16-As.The results showed that the expression levels of EGFP at the site between the G and L genes of LN16-A were significantly higher than those at the other two sites(between the leader and N genes or replacing the SH gene).To verify the availability of the site between G and L for foreign gene expression,the VP2 gene of very virulent infectious bursal disease virus(vvIBDV)was inserted into this site,and recombinant LN16-A(rLN16A-vvVP2)was successfully rescued.Single immunization of specificpathogen-free chickens with rLN16A-vvVP2 induced high levels of neutralizing antibodies and provided 100%protection against the virulent aMPV subtype B and vvIBDV.Establishing a reverse genetics system here provides an important foundation for understanding aMPV pathogenesis and developing novel vector vaccines.展开更多
[Objective] The research aimed to provide reference for increasing the genetic transformation efficiency of Ginkgo biloba mediated by Agrobacterium.[Method] Taking the mature embryos of Ginkgo biloba seeds as explants...[Objective] The research aimed to provide reference for increasing the genetic transformation efficiency of Ginkgo biloba mediated by Agrobacterium.[Method] Taking the mature embryos of Ginkgo biloba seeds as explants,after 48 hours＇ pre-cultivation on MS medium in the absence of phytohormone,GUS gene was transmitted into embryos of Ginkgo biloba mediated by three kinds of Agrobacterium.Transient expression of GUS gene activity was observed through histochemical staining,and the influencing factors of the expression of GUS gene were analyzed.And the expression vector of 1-deoxy-D-xylulose-5-phosphate reductoisomerase in the biosynthesis approach of biobalide precursor of Ginkgo biloba was constructed.[Result] A more suitable genetic transformation scheme was obtained as follows：taking embryos of Ginkgo biloba as explants,using EHA105 Agrobacterium with pCAMBIA1304＋ for infection,co-culture for 3 days and GUS staining.The results showed that transient expression rate of GUS after transformation was higher.[Conclusion] The research provide a more effective method for further study on the transgene of Ginkgo biloba.展开更多
This paper describes a robust support vector regression （SVR） methodology, which can offer superior performance for important process engineering problems. The method incorporates hybrid support vector regression an...This paper describes a robust support vector regression （SVR） methodology, which can offer superior performance for important process engineering problems. The method incorporates hybrid support vector regression and genetic algorithm technique （SVR-GA） for efficient tuning of SVR meta-parameters. The algorithm has been applied for prediction of pressure drop of solid liquid slurry flow. A comparison with selected correlations in the lit- erature showed that the developed SVR correlation noticeably improved the prediction of pressure drop over a wide range of operating conditions, physical properties, and pipe diameters.展开更多
A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced eff...A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.展开更多
To solve the multi-class fault diagnosis tasks,decision tree support vector machine(DTSVM),which combines SVM and decision tree using the concept of dichotomy,is proposed.Since the classification performance of DTSVM ...To solve the multi-class fault diagnosis tasks,decision tree support vector machine(DTSVM),which combines SVM and decision tree using the concept of dichotomy,is proposed.Since the classification performance of DTSVM highly depends on its structure,to cluster the multi-classes with maximum distance between the clustering centers of the two sub-classes,genetic algorithm is introduced into the formation of decision tree,so that the most separable classes would be separated at each node of decisions tree.Numerical simulations conducted on three datasets compared with"one-against-all"and"one-against-one"demonstrate the proposed method has better performance and higher generalization ability than the two conventional methods.展开更多
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ...This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection.展开更多
In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(S...In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.展开更多
Support vector machines （SVMs） have been introduced as effective methods for solving classification problems. However, due to some limitations in practical applications, their generalization performance is sometimes...Support vector machines （SVMs） have been introduced as effective methods for solving classification problems. However, due to some limitations in practical applications, their generalization performance is sometimes far from the expected level. Therefore, it is meaningful to study SVM ensemble learning. In this paper, a novel genetic algorithm based ensemble learning method, namely Direct Genetic Ensemble （DGE）, is proposed. DGE adopts the predictive accuracy of ensemble as the fitness function and searches a good ensemble from the ensemble space. In essence, DGE is also a selective ensemble learning method because the base classifiers of the ensemble are selected according to the solution of genetic algorithm. In comparison with other ensemble learning methods, DGE works on a higher level and is more direct. Different strategies of constructing diverse base classifiers can be utilized in DGE. Experimental results show that SVM ensembles constructed by DGE can achieve better performance than single SVMs, hagged and boosted SVM ensembles. In addition, some valuable conclusions are obtained.展开更多
[Objective] The aim was to clone the mitochondrial-related gene nad1 and produce transgenic rice plants with nad1.[Method] The total RNA was extracted from rice seedlings and reverse transcripted into cDNA.Then the ta...[Objective] The aim was to clone the mitochondrial-related gene nad1 and produce transgenic rice plants with nad1.[Method] The total RNA was extracted from rice seedlings and reverse transcripted into cDNA.Then the target gene nad1 was amplified by using the cDNA as template.The nad1 and Rf1b,a sequence of signal peptide of mitochondria,were linked to binary expression vector pCAMBIA1305.1.The recombinant plasmid was transformed into the callus by Agrobacterium-mediated approach.[Result] The target gene nad1 was 978 bp.The binary expression vector carrying nad1 and signal peptide of mitochondria was constructed successfully.In addition,a lot of transgenic plants were obtained.[Conclusion] The study will provide basis to investigate the effect of over-expression of nad1 on rice plant growth.展开更多
In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying result...In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.展开更多
The etiopathogenesis of gastrointestinal diseases is varied in nature.Various etiogenic factors described are infective,inflammatory,viral,bacterial,parasitic,dietary and lifestyle change.Rare causative agents are imm...The etiopathogenesis of gastrointestinal diseases is varied in nature.Various etiogenic factors described are infective,inflammatory,viral,bacterial,parasitic,dietary and lifestyle change.Rare causative agents are immunological,and others associated as idiopathic,are undiagnosed by all possible means.Some of the rare diseases are congenital in nature,passing from the parent to the child.Many of the undiagnosed diseases are now being diagnosed as genetic and the genes have been implicated as a causative agent.There is a search for newer treatments for such diseases,which is called genomic medicine.Genomic medicine is an emerging medical discipline that involves the use of genomic information about an individual.This is used both for diagnostic as well as therapeutic decisions to improve the current health domain and pave the way for policymakers for its clinical use.In the developing era of precision medicine,genomics,epigenomics,environmental exposure,and other data would be used to more accurately guide individual diagnosis and treatment.Genomic medicine is already making an impact in the fields of oncology,pharmacology,rare,infectious and many undiagnosed diseases.It is beginning to fuel new approaches in certain medical specialties.Oncology is at the leading edge of incorporating genomics,as diagnostics for genetic and genomic markers are increasingly included in cancer screening,and to guide tailored treatment strategies.Genetics and genetic medicine have been reported to play a role in gastroenterology in several ways,including genetic testing(hereditary pancreatitis and hereditary gastrointestinal cancer syndromes).Genetic testing can also help subtype diseases,such as classifying pancreatitis as idiopathic or hereditary.Gene therapy is a promising approach for treating gastrointestinal diseases that are not effectively treated by conventional pharmaceuticals and surgeries.Gene therapy strategies include gene addition,gene editing,messenger RNA therapy,and gene silencing.Understanding genetic determinants,advances in genetics,have led to a better understanding of the genetic factors that contribute to human disease.Family-member risk stratification and genetic diagnosis can help identify family members who are at risk,which can lead to preventive treatments,lifestyle recommendations,and routine follow ups.Selecting target genes helps identify the gene targets associated with each gastrointestinal disease.Common gastrointestinal diseases associated with genetic abnormalities include-inflammatory bowel disease,gastroesophageal reflux disease,non-alcoholic fatty liver disease,and irritable bowel syndrome.With advancing tools and technology,research in the search of newer and individualized treatment,genes and genetic medicines are expected to play a significant role in human health and gastroenterology.展开更多
In order to lay a foundation for researching the function of Rosa rugose (R. rugosa) RrGlu gene, the RrGlu gene was amplified from the styles of R. rugosa “Tanghong”, a gene expression vector named PBI121-RrGlu was ...In order to lay a foundation for researching the function of Rosa rugose (R. rugosa) RrGlu gene, the RrGlu gene was amplified from the styles of R. rugosa “Tanghong”, a gene expression vector named PBI121-RrGlu was constructed and the vector was introduced into tobacco with the agrobacterium-mediated method. PCR results showed that the RrGlu gene was integrated into the tobacco genome.展开更多
Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are ...Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefore, the sales volume forecasting process is a critical one for most businesses, and also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. Recently, various prediction Artificial Intelligent (AI) techniques have been proposed in forecasting. Support Vector Regression (SVR) has been applied successfully to solve problems in numerous fields and proved to be a better prediction model. However, the select of appropriate SVR parameters is difficult. Therefore, to improve the accuracy of SVR, a hybrid intelligent support system based on evolutionary computation to solve the difficulties involved with the parameters selection is presented in this research. Genetic Algorithms (GAs) are used to optimize free parameters of SVR. The experimental results indicate that GA-SVR can achieve better forecasting accuracy and performance than traditional SVR and artificial neural network (ANN) prediction models in sales volume forecasting.展开更多
Corporate net value is efficiently described on its stock price, offering investors a chance to include a potentially surplus value to the net worth of the overall investment portfolio. Financial analysis of corporati...Corporate net value is efficiently described on its stock price, offering investors a chance to include a potentially surplus value to the net worth of the overall investment portfolio. Financial analysis of corporations extracted from the accounting statements is constantly demanded to support decisions making of portfolio managers. Econometrics and Artificial Intelligence methods aim to extract hidden information from complex accounting and financial data. Support Vector Machines hybrids optimized in their components by Genetic Algorithms provide effective results in corporate financial analysis.展开更多
[Objective] This study aimed to clone the gene atp6 from rice mitochondria, construct the binary expression vector 35S ：： Rflb5＇ ：： atp6 and obtain transgenic plants with atp6. [Method] The special primers were d...[Objective] This study aimed to clone the gene atp6 from rice mitochondria, construct the binary expression vector 35S ：： Rflb5＇ ：： atp6 and obtain transgenic plants with atp6. [Method] The special primers were designed according to the sequence of target gene. With the TRIzol method the total RNA was extracted from rice seedlings and reverse transcripted to cDNA. The ORF of atp6 was amplified by PCR, and ligated to binary expression vector pCAMBIA1302 which contains se- quence of signal peptide from mitochondria （Rflb5＇）. The recombinant plasmid was then transformed into rice callus mediated by Agrobacterium. [Result] The binary expression vector 35S ：： Rflb5＇ ：： atp6 was constructed, and positive transgenic plants were obtained. [Conclusion] This study lays foundation for understanding influence of atp6 gene over-expression on rice growth.展开更多
Parkinson’s disease (PD) is the most common disease of motor system degeneration that occurs when the dopamine-producing cells are damaged in substantia nigra. To detect PD, various signals have been investigated, in...Parkinson’s disease (PD) is the most common disease of motor system degeneration that occurs when the dopamine-producing cells are damaged in substantia nigra. To detect PD, various signals have been investigated, including EEG, gait and speech. Since approximately 90 percent of the people with PD suffer from speech disorders, speech analysis is considered as the most common technique for this aim. This paper proposes a new algorithm for diagnosing of Parkinson’s disease based on voice analysis. In the first step, genetic algorithm (GA) is undertaken for selecting optimized features from all extracted features. Afterwards a network based on support vector machine (SVM) is used for classification between healthy and people with Parkinson. The dataset of this research is composed of a range of biomedical voice signals from 31 people, 23 with Parkinson’s disease and 8 healthy people. The subjects were asked to pronounce letter “A” for 3 seconds. 22 linear and non-linear features were extracted from the signals that 14 features were based on F0 (fundamental frequency or pitch), jitter, shimmer and noise to harmonics ratio, which are main factors in voice signal. Because changing in these factors is noticeable for the people with PD, optimized features were selected among them. Of the various numbers of optimized features, the data classification was investigated. Results show that the classification accuracy percent of 94.50 per 4 optimized features, the accuracy percent of 93.66 per 7 optimized features and the accuracy percent of 94.22 per 9 optimized features, could be achieved. It can be observed that the best classification accuracy may be achieved using Fhi (Hz), Fho (Hz), jitter (RAP) and shimmer (APQ5).展开更多
Recombinant adeno-associated virus （rAAV） vectors have been extensively used for experimental gene therapy of inherited human diseases. Several advantages, such as simple vector construction, high targeting frequenc...Recombinant adeno-associated virus （rAAV） vectors have been extensively used for experimental gene therapy of inherited human diseases. Several advantages, such as simple vector construction, high targeting frequency by homologous recombination, and applica- bility to many cell types, make rAAV an attractive approach for targeted genome editing. Combined with cloning by somatic cell nuclear transfer （SCNT）, this technology has recently been successfully adapted to generate gene-targeted pigs as models for cystic fibrosis, hereditary tyrosinemia type 1, and breast cancer. This review summarizes the development of rAAV for targeted genome editing in mammalian cells and provides strategies for enhancing the rAAV-mediated targeting frequency by homologous recombination. We discuss current development and application of the rAAV vectors for targeted genome editing in porcine primary fibroblasts, which are subse- quently used as donor cells for SCNT to generate cloned genetically designed pigs and provide positive perspectives for the generation of gene-targeted pigs with rAAV in the future.展开更多
Objective To construct green fluorescent protein (GFP)-labeled pSELECT-GFP zeohBMP2 eukaryotic expression vector.Methods The encoding fragment of hBMP2 gene was obtained from a recombinant plasmid pcDNA3.1/CT-hBMP2 by...Objective To construct green fluorescent protein (GFP)-labeled pSELECT-GFP zeohBMP2 eukaryotic expression vector.Methods The encoding fragment of hBMP2 gene was obtained from a recombinant plasmid pcDNA3.1/CT-hBMP2 by using polymerase展开更多
The rough set-genetic support vector machine(SVM) model is applied to supply chain performance evaluation. First, the rough set theory is used to remove the redundant factors that affect the performance evaluation of ...The rough set-genetic support vector machine(SVM) model is applied to supply chain performance evaluation. First, the rough set theory is used to remove the redundant factors that affect the performance evaluation of supply chain to obtain the core influencing factors. Then the support vector machine is used to extract the core influencing factors to predict the level of supply chain performance. In the process of SVM classification, the genetic algorithm is used to optimize the parameters of the SVM algorithm to obtain the best parameter model, and then the supply chain performance evaluation level is predicted. Finally, an example is used to predict this model, and compared with the result of using only rough set-support vector machine to predict. The results show that the method of rough set-genetic support vector machine can predict the level of supply chain performance more accurately and the prediction result is more realistic, which is a scientific and feasible method.展开更多
Objective： To construct an eukaryotic expression vector that contains Smac gene, which is regulated by human Uroplakin Ib （UpIb） promoter. Methods： For the directionality of Smac expression in the transitional cel...Objective： To construct an eukaryotic expression vector that contains Smac gene, which is regulated by human Uroplakin Ib （UpIb） promoter. Methods： For the directionality of Smac expression in the transitional cell carcinoma of bladder, internal CMV and T7 promoter sequences in eukaryotic expression vector pcDNA3.1-Smac were replaced with UpIb promoter to construct a new plasmid. The plasmid DNA was identified by gel electrophoresis after being double digested at respective sites, and then the sequence was analyzed. The expression of Smac mRNA and protein in BIU87 cell line were detected after the transfection by using the newly constructed vector. Results： The Smac gene-carrying and UpIb promoter-regulated eukaryotic expression vector pcDNA3-UpIb-promoter-Smac was successfully constructed. The expression of Smac mRNA was approximately increased by 2.1 times and the expression of Smac protein was increased in about 71% BIU87 cells. Conclusion： The new vector can be effectively expressed in bladder cancer cells and be of great significance for bladder cancer-targeted gene therapy.展开更多
基金supported by the grants from the National Key Research and Development Program of China(2022YFD1800604)the China Agriculture Research System(CARS-41)the Heilongjiang Touyan Innovation Team Program,China。
文摘Avian metapneumovirus(aMPV),a paramyxovirus,causes acute respiratory diseases in turkeys and swollen head syndrome in chickens.This study established a reverse genetics system for aMPV subtype B LN16-A strain based on T7 RNA polymerase.Full-length cDNA of the LN16-A strain was constructed by assembling 5 cDNA fragments between the T7 promoter and hepatitis delta virus ribozyme.Transfection of this plasmid,along with the supporting plasmids encoding the N,P,M2-1,and L proteins of LN16-A into BSR-T7/5 cells,resulted in the recovery of aMPV subtype B.To identify an effective insertion site,the enhanced green fluorescent protein(EGFP)gene was inserted into different sites of the LN16-A genome to generate recombinant LN16-As.The results showed that the expression levels of EGFP at the site between the G and L genes of LN16-A were significantly higher than those at the other two sites(between the leader and N genes or replacing the SH gene).To verify the availability of the site between G and L for foreign gene expression,the VP2 gene of very virulent infectious bursal disease virus(vvIBDV)was inserted into this site,and recombinant LN16-A(rLN16A-vvVP2)was successfully rescued.Single immunization of specificpathogen-free chickens with rLN16A-vvVP2 induced high levels of neutralizing antibodies and provided 100%protection against the virulent aMPV subtype B and vvIBDV.Establishing a reverse genetics system here provides an important foundation for understanding aMPV pathogenesis and developing novel vector vaccines.
文摘[Objective] The research aimed to provide reference for increasing the genetic transformation efficiency of Ginkgo biloba mediated by Agrobacterium.[Method] Taking the mature embryos of Ginkgo biloba seeds as explants,after 48 hours＇ pre-cultivation on MS medium in the absence of phytohormone,GUS gene was transmitted into embryos of Ginkgo biloba mediated by three kinds of Agrobacterium.Transient expression of GUS gene activity was observed through histochemical staining,and the influencing factors of the expression of GUS gene were analyzed.And the expression vector of 1-deoxy-D-xylulose-5-phosphate reductoisomerase in the biosynthesis approach of biobalide precursor of Ginkgo biloba was constructed.[Result] A more suitable genetic transformation scheme was obtained as follows：taking embryos of Ginkgo biloba as explants,using EHA105 Agrobacterium with pCAMBIA1304＋ for infection,co-culture for 3 days and GUS staining.The results showed that transient expression rate of GUS after transformation was higher.[Conclusion] The research provide a more effective method for further study on the transgene of Ginkgo biloba.
文摘This paper describes a robust support vector regression （SVR） methodology, which can offer superior performance for important process engineering problems. The method incorporates hybrid support vector regression and genetic algorithm technique （SVR-GA） for efficient tuning of SVR meta-parameters. The algorithm has been applied for prediction of pressure drop of solid liquid slurry flow. A comparison with selected correlations in the lit- erature showed that the developed SVR correlation noticeably improved the prediction of pressure drop over a wide range of operating conditions, physical properties, and pipe diameters.
文摘A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.
基金supported by the National Natural Science Foundation of China(60604021,60874054)
文摘To solve the multi-class fault diagnosis tasks,decision tree support vector machine(DTSVM),which combines SVM and decision tree using the concept of dichotomy,is proposed.Since the classification performance of DTSVM highly depends on its structure,to cluster the multi-classes with maximum distance between the clustering centers of the two sub-classes,genetic algorithm is introduced into the formation of decision tree,so that the most separable classes would be separated at each node of decisions tree.Numerical simulations conducted on three datasets compared with"one-against-all"and"one-against-one"demonstrate the proposed method has better performance and higher generalization ability than the two conventional methods.
基金Supported by the National Natural Science Foundation of China(21076179)the National Basic Research Program of China(2012CB720500)
文摘This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection.
基金Projects(61471370,61401479)supported by the National Natural Science Foundation of China
文摘In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.
基金This work was supported by National Basic Research Programof China under Grant2002cb312200 01 3National Nature ScienceFoundation of China under Grant60174038.
文摘Support vector machines （SVMs） have been introduced as effective methods for solving classification problems. However, due to some limitations in practical applications, their generalization performance is sometimes far from the expected level. Therefore, it is meaningful to study SVM ensemble learning. In this paper, a novel genetic algorithm based ensemble learning method, namely Direct Genetic Ensemble （DGE）, is proposed. DGE adopts the predictive accuracy of ensemble as the fitness function and searches a good ensemble from the ensemble space. In essence, DGE is also a selective ensemble learning method because the base classifiers of the ensemble are selected according to the solution of genetic algorithm. In comparison with other ensemble learning methods, DGE works on a higher level and is more direct. Different strategies of constructing diverse base classifiers can be utilized in DGE. Experimental results show that SVM ensembles constructed by DGE can achieve better performance than single SVMs, hagged and boosted SVM ensembles. In addition, some valuable conclusions are obtained.
基金Supported by the National Natural Science Foundation of China(30871318)~~
文摘[Objective] The aim was to clone the mitochondrial-related gene nad1 and produce transgenic rice plants with nad1.[Method] The total RNA was extracted from rice seedlings and reverse transcripted into cDNA.Then the target gene nad1 was amplified by using the cDNA as template.The nad1 and Rf1b,a sequence of signal peptide of mitochondria,were linked to binary expression vector pCAMBIA1305.1.The recombinant plasmid was transformed into the callus by Agrobacterium-mediated approach.[Result] The target gene nad1 was 978 bp.The binary expression vector carrying nad1 and signal peptide of mitochondria was constructed successfully.In addition,a lot of transgenic plants were obtained.[Conclusion] The study will provide basis to investigate the effect of over-expression of nad1 on rice plant growth.
基金Project supported by the National Basic Research Program (973) of China (No. 2002CB312200) and the Center for Bioinformatics Pro-gram Grant of Harvard Center of Neurodegeneration and Repair,Harvard Medical School, Harvard University, Boston, USA
文摘In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.
文摘The etiopathogenesis of gastrointestinal diseases is varied in nature.Various etiogenic factors described are infective,inflammatory,viral,bacterial,parasitic,dietary and lifestyle change.Rare causative agents are immunological,and others associated as idiopathic,are undiagnosed by all possible means.Some of the rare diseases are congenital in nature,passing from the parent to the child.Many of the undiagnosed diseases are now being diagnosed as genetic and the genes have been implicated as a causative agent.There is a search for newer treatments for such diseases,which is called genomic medicine.Genomic medicine is an emerging medical discipline that involves the use of genomic information about an individual.This is used both for diagnostic as well as therapeutic decisions to improve the current health domain and pave the way for policymakers for its clinical use.In the developing era of precision medicine,genomics,epigenomics,environmental exposure,and other data would be used to more accurately guide individual diagnosis and treatment.Genomic medicine is already making an impact in the fields of oncology,pharmacology,rare,infectious and many undiagnosed diseases.It is beginning to fuel new approaches in certain medical specialties.Oncology is at the leading edge of incorporating genomics,as diagnostics for genetic and genomic markers are increasingly included in cancer screening,and to guide tailored treatment strategies.Genetics and genetic medicine have been reported to play a role in gastroenterology in several ways,including genetic testing(hereditary pancreatitis and hereditary gastrointestinal cancer syndromes).Genetic testing can also help subtype diseases,such as classifying pancreatitis as idiopathic or hereditary.Gene therapy is a promising approach for treating gastrointestinal diseases that are not effectively treated by conventional pharmaceuticals and surgeries.Gene therapy strategies include gene addition,gene editing,messenger RNA therapy,and gene silencing.Understanding genetic determinants,advances in genetics,have led to a better understanding of the genetic factors that contribute to human disease.Family-member risk stratification and genetic diagnosis can help identify family members who are at risk,which can lead to preventive treatments,lifestyle recommendations,and routine follow ups.Selecting target genes helps identify the gene targets associated with each gastrointestinal disease.Common gastrointestinal diseases associated with genetic abnormalities include-inflammatory bowel disease,gastroesophageal reflux disease,non-alcoholic fatty liver disease,and irritable bowel syndrome.With advancing tools and technology,research in the search of newer and individualized treatment,genes and genetic medicines are expected to play a significant role in human health and gastroenterology.
文摘In order to lay a foundation for researching the function of Rosa rugose (R. rugosa) RrGlu gene, the RrGlu gene was amplified from the styles of R. rugosa “Tanghong”, a gene expression vector named PBI121-RrGlu was constructed and the vector was introduced into tobacco with the agrobacterium-mediated method. PCR results showed that the RrGlu gene was integrated into the tobacco genome.
文摘Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefore, the sales volume forecasting process is a critical one for most businesses, and also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. Recently, various prediction Artificial Intelligent (AI) techniques have been proposed in forecasting. Support Vector Regression (SVR) has been applied successfully to solve problems in numerous fields and proved to be a better prediction model. However, the select of appropriate SVR parameters is difficult. Therefore, to improve the accuracy of SVR, a hybrid intelligent support system based on evolutionary computation to solve the difficulties involved with the parameters selection is presented in this research. Genetic Algorithms (GAs) are used to optimize free parameters of SVR. The experimental results indicate that GA-SVR can achieve better forecasting accuracy and performance than traditional SVR and artificial neural network (ANN) prediction models in sales volume forecasting.
文摘Corporate net value is efficiently described on its stock price, offering investors a chance to include a potentially surplus value to the net worth of the overall investment portfolio. Financial analysis of corporations extracted from the accounting statements is constantly demanded to support decisions making of portfolio managers. Econometrics and Artificial Intelligence methods aim to extract hidden information from complex accounting and financial data. Support Vector Machines hybrids optimized in their components by Genetic Algorithms provide effective results in corporate financial analysis.
基金Supported by National Natural Science Foundation of China(3117022631170296)~~
文摘[Objective] This study aimed to clone the gene atp6 from rice mitochondria, construct the binary expression vector 35S ：： Rflb5＇ ：： atp6 and obtain transgenic plants with atp6. [Method] The special primers were designed according to the sequence of target gene. With the TRIzol method the total RNA was extracted from rice seedlings and reverse transcripted to cDNA. The ORF of atp6 was amplified by PCR, and ligated to binary expression vector pCAMBIA1302 which contains se- quence of signal peptide from mitochondria （Rflb5＇）. The recombinant plasmid was then transformed into rice callus mediated by Agrobacterium. [Result] The binary expression vector 35S ：： Rflb5＇ ：： atp6 was constructed, and positive transgenic plants were obtained. [Conclusion] This study lays foundation for understanding influence of atp6 gene over-expression on rice growth.
文摘Parkinson’s disease (PD) is the most common disease of motor system degeneration that occurs when the dopamine-producing cells are damaged in substantia nigra. To detect PD, various signals have been investigated, including EEG, gait and speech. Since approximately 90 percent of the people with PD suffer from speech disorders, speech analysis is considered as the most common technique for this aim. This paper proposes a new algorithm for diagnosing of Parkinson’s disease based on voice analysis. In the first step, genetic algorithm (GA) is undertaken for selecting optimized features from all extracted features. Afterwards a network based on support vector machine (SVM) is used for classification between healthy and people with Parkinson. The dataset of this research is composed of a range of biomedical voice signals from 31 people, 23 with Parkinson’s disease and 8 healthy people. The subjects were asked to pronounce letter “A” for 3 seconds. 22 linear and non-linear features were extracted from the signals that 14 features were based on F0 (fundamental frequency or pitch), jitter, shimmer and noise to harmonics ratio, which are main factors in voice signal. Because changing in these factors is noticeable for the people with PD, optimized features were selected among them. Of the various numbers of optimized features, the data classification was investigated. Results show that the classification accuracy percent of 94.50 per 4 optimized features, the accuracy percent of 93.66 per 7 optimized features and the accuracy percent of 94.22 per 9 optimized features, could be achieved. It can be observed that the best classification accuracy may be achieved using Fhi (Hz), Fho (Hz), jitter (RAP) and shimmer (APQ5).
基金supported by the grants from the Danish National Researeh Infrastructure Programme to the Danish Genetieally Modified Animal Resource(DAG- MAR)as well as from the"Sino一Danish Breast Caneer Research Centre"under the ausPiees of the Danish National Researeh Foundation(Grundforskningsfonden)the National Natural Seience Foundation of China
文摘Recombinant adeno-associated virus （rAAV） vectors have been extensively used for experimental gene therapy of inherited human diseases. Several advantages, such as simple vector construction, high targeting frequency by homologous recombination, and applica- bility to many cell types, make rAAV an attractive approach for targeted genome editing. Combined with cloning by somatic cell nuclear transfer （SCNT）, this technology has recently been successfully adapted to generate gene-targeted pigs as models for cystic fibrosis, hereditary tyrosinemia type 1, and breast cancer. This review summarizes the development of rAAV for targeted genome editing in mammalian cells and provides strategies for enhancing the rAAV-mediated targeting frequency by homologous recombination. We discuss current development and application of the rAAV vectors for targeted genome editing in porcine primary fibroblasts, which are subse- quently used as donor cells for SCNT to generate cloned genetically designed pigs and provide positive perspectives for the generation of gene-targeted pigs with rAAV in the future.
文摘Objective To construct green fluorescent protein (GFP)-labeled pSELECT-GFP zeohBMP2 eukaryotic expression vector.Methods The encoding fragment of hBMP2 gene was obtained from a recombinant plasmid pcDNA3.1/CT-hBMP2 by using polymerase
文摘The rough set-genetic support vector machine(SVM) model is applied to supply chain performance evaluation. First, the rough set theory is used to remove the redundant factors that affect the performance evaluation of supply chain to obtain the core influencing factors. Then the support vector machine is used to extract the core influencing factors to predict the level of supply chain performance. In the process of SVM classification, the genetic algorithm is used to optimize the parameters of the SVM algorithm to obtain the best parameter model, and then the supply chain performance evaluation level is predicted. Finally, an example is used to predict this model, and compared with the result of using only rough set-support vector machine to predict. The results show that the method of rough set-genetic support vector machine can predict the level of supply chain performance more accurately and the prediction result is more realistic, which is a scientific and feasible method.
基金National Natural Science Foundation of China(30271301)
文摘Objective： To construct an eukaryotic expression vector that contains Smac gene, which is regulated by human Uroplakin Ib （UpIb） promoter. Methods： For the directionality of Smac expression in the transitional cell carcinoma of bladder, internal CMV and T7 promoter sequences in eukaryotic expression vector pcDNA3.1-Smac were replaced with UpIb promoter to construct a new plasmid. The plasmid DNA was identified by gel electrophoresis after being double digested at respective sites, and then the sequence was analyzed. The expression of Smac mRNA and protein in BIU87 cell line were detected after the transfection by using the newly constructed vector. Results： The Smac gene-carrying and UpIb promoter-regulated eukaryotic expression vector pcDNA3-UpIb-promoter-Smac was successfully constructed. The expression of Smac mRNA was approximately increased by 2.1 times and the expression of Smac protein was increased in about 71% BIU87 cells. Conclusion： The new vector can be effectively expressed in bladder cancer cells and be of great significance for bladder cancer-targeted gene therapy.
