A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus...A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.展开更多
Objective:To establish a polymerase chain reaction(PCR) technique based on cytochrome b {cytb) gene of mitochondria DNA(mtDNA) for blood meal identification.Methods:The PCR technique was established based on published...Objective:To establish a polymerase chain reaction(PCR) technique based on cytochrome b {cytb) gene of mitochondria DNA(mtDNA) for blood meal identification.Methods:The PCR technique was established based on published information and validated using blood sample of laboratory animals of which their whole gene sequences are available in CenBank.PCR was next performed to compile gene sequences of different species of wild rodents.The primers used were complementary to the conserved region of the cytb gene of vertebrate's mtDNA.A total of 100 blood samples,both from laboratory animals and wild rodents were collected und analyzed.The obtained unknown sequences were compared with those in the GenBank database using BLAST program to identify the vertebrate animal species.Results:Gene sequences of 11 species of wild animals caught in 9 localities of Peninsular Malaysia were compiled using the established PCR. The animals involved were Rattus(rattus) tanezumi,Rattus tiomanicus,Leopoldamys sabanus, Tupaia glis,Tupaia minor,Niviventor cremoriventor,Rhinosciurus laticaudatus,Calloseiurus caniseps,Sundamys muelleri,Rattus rajah,and Maxomys whitelwadi.The BLAST results confirmed the host with exact or nearly exact matches(>89%identity).Ten new gene sequences have been deposited in CenBank database since September 2010.Conclusions:This study indicates that the PCR direct sequencing system using universal primer sets for vertebrate cytb gene is a promising technique for blood meal identification.展开更多
Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread e...Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control（NC） machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters＇ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters＇ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures（MTBF）. The relative error of the proposed method is 5.8020×10-4 compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.展开更多
基金Project(2014ZX04014-011)supported by State Key Science&Technology Program of ChinaProject([2016]414)supported by the 13th Five-year Program of Education Department of Jilin Province,China
文摘A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.
基金financially supported by a grant(JPP-IMR Code:09-030) from the Ministry of Health,Malaysia
文摘Objective:To establish a polymerase chain reaction(PCR) technique based on cytochrome b {cytb) gene of mitochondria DNA(mtDNA) for blood meal identification.Methods:The PCR technique was established based on published information and validated using blood sample of laboratory animals of which their whole gene sequences are available in CenBank.PCR was next performed to compile gene sequences of different species of wild rodents.The primers used were complementary to the conserved region of the cytb gene of vertebrate's mtDNA.A total of 100 blood samples,both from laboratory animals and wild rodents were collected und analyzed.The obtained unknown sequences were compared with those in the GenBank database using BLAST program to identify the vertebrate animal species.Results:Gene sequences of 11 species of wild animals caught in 9 localities of Peninsular Malaysia were compiled using the established PCR. The animals involved were Rattus(rattus) tanezumi,Rattus tiomanicus,Leopoldamys sabanus, Tupaia glis,Tupaia minor,Niviventor cremoriventor,Rhinosciurus laticaudatus,Calloseiurus caniseps,Sundamys muelleri,Rattus rajah,and Maxomys whitelwadi.The BLAST results confirmed the host with exact or nearly exact matches(>89%identity).Ten new gene sequences have been deposited in CenBank database since September 2010.Conclusions:This study indicates that the PCR direct sequencing system using universal primer sets for vertebrate cytb gene is a promising technique for blood meal identification.
基金Supported by Research on Reliability Assessment and Test Methods of Heavy Machine Tools,China(State Key Science&Technology Project High-grade NC Machine Tools and Basic Manufacturing Equipment,Grant No.2014ZX04014-011)Reliability Modeling of Machining Centers Considering the Cutting Loads,China(Science&Technology Development Plan for Jilin Province,Grant No.3D513S292414)Graduate Innovation Fund of Jilin University,China(Grant No.2014053)
文摘Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control（NC） machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters＇ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters＇ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures（MTBF）. The relative error of the proposed method is 5.8020×10-4 compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.
