Compressive Strength of Basic Magnesium Sulfate Cement Coral Aggregate Concrete(MCAC)on Non-Destructive Testing

Basic magnesium sulfate cement coral aggregate concrete(MCAC)is a new type of concrete consisting of basic magnesium sulfate cement,coarse coral aggregate,coral reef sand and seawater.The rebound hammer(RH),the ultrasonic pulse velocity(UPV)and the compressive strength(fcu)tests of 14 sets of cube specimens of the MCAC after 28 d of aging were conducted.The impact of the content and length of sisal fiber on the relationship between the fcu-RH and the fcu-UPV was determined.A mathematical model was established to predict the strength of the MCAC using the UPV,RH,and comprehensive UPV/RH methods and to obtain the curves of test strength.The applicability of the test strength curves of ordinary portland concrete(OPC),light-weight aggregate concrete(LAC),and coral aggregate concrete(CAC)to MCAC was assessed.The results showed that the test strength curves of OPC,LAC and CAC were inappropriate to determine the strength of MCAC using non-destructive method.The relative standard error of the curves of test strength of the RH method and the comprehensive method met the specifications,whereas that of the UPV method did not.

An Analysis of the Listening Comprehension in CET-6——Illustrated by the CET-6 Test on June,2018

The College English Test Band Six(CET-6)is one of the most widely applied exam across China.As a national teaching test,CET-6 is sponsored by the Department of higher education of the Ministry of education of The People’s Republic of China and held twice a year.In this study,77 sophomores of different majors were tested using the listening test in June 2018.It is ensured that the test method is exactly same as that of CET-6.The purpose of this paper is to analyze the content and specification of CET-6 listening comprehension test,and to evaluate this part in detail according to the real data,including score report and item analysis,trying to provide some enlightenment for the revision of the examination.

Research of testing method based on UML statecharts

Unified modeling language （UML） is a powerful graphical modeling language with intuitional meaning. It provides various diagrams to depict system characteristics and complex environment from different viewpoints and different application layers. UML-based software development and modeling environments have been widely accepted in industry, including areas in which safety is an important issue such as spaceflight, defense, automobile, etc. To ensure and improve software quality becomes a main concern in the field. As one of the key techniques for software quality, software testing can effectively detect system faults. UML based software testing based is an important research direction in software engineering. The key to software testing is the generation of test cases. This dissertation studies an approach to generating test cases from UML statecharts.

Reliability Design of Ice-Maker System Subjected to Repetitive Loading

Parametric Accelerated Life Testing (ALT) was used to improve the reliability of ice-maker system with a fractured helix upper dispenser in field. By using bond graphs and state equations, a variety of mechanical loads in the assembly were analyzed. The acceleration factor was derived from a generalized life-stress failure model with a new load concept. To reproduce the failure modes and mechanisms causing the fracture, new sample size equation was derived. The sample size equation with the acceleration factor also enabled the parametric accelerated life testing to quickly reproduce early failure in field. Consequently, the failure modes and mechanisms found were identical with those of the failed sample. The design of this testing should help an engineer uncover the design parameters affecting the reliability of fractured helix upper dispenser in field. By eliminating the design flaws, gaps and weldline, the B1 life of the redesign of helix upper dispenser is now guaranteed to be over 10 years with a yearly failure rate of 0.1% that is the reliability quantitative test specifications (RQ).

Preparation of Polyclonal Antibody against Human MxA Protein and Its Specificity to Diversified Myxovirus Resistant Protein A

Objective To study the human myxovirus resistant protein A （MxA）, a specifically induced peptide by interferon I, and to use its level as a diagnostic criterion for viral infections. Methods Anti-MxA antisera from immunized mice were prepared with the expressed MxA protein of pET32a-MxA in E. coli BL-21（DE3）. To confirm the antiserum activity and specificity, the expression product of BL21, wild type MxA pEGFP-CI-wMxA and site-directed mutant MxA pEGFP-Cl-mMxA（N589S） stably transfected 3T3 cells and induced A549 cells were detected by Western blot with the antisera using non-MxA transfected or non-IFN-[3 induced cells, intact A549, NIH 3T3 cells transfected with pEGFP-CI and pET32a （＋）-transformed BL-21 as controls. Results The antisera had specific positive immunoreactivity to the NIH3T3 cells transformed with pEGFP-CI-wMxA and pEGFP-CI-mMxA, INF-β induced A549 cells and BL21 proteins expressed with pET32a （＋）-MxA. The hybridization signals from IFN-β induced A549 cells depended on the IFN-β inducing concentrations. Meanwhile, immunohistochemical assay showed that NIH 3T3 cells with pEGFP-C 1-wMxA and pEGFP-C 1-mMxA had 〉 98% of positive cells at 1：50 dilution of the serum and A549 cells induced by 20 ng/mL IFN-[3 for 48 h showed 95% positive cells. pEGFP-Cl-transfected NIH 3T3 cells were all negative. Conclusion Anti-sera are highly specific to diversified MxAs. The antibody is detectable by Western blot, immunocytochemistry and immunofluorescence assay.

An adaptive lack of fit test for big data

New technological advancements combined with powerful computer hardware and high-speed network make big data available.The massive sample size of big data introduces unique computational challenges on scalability and storage of statistical methods.In this paper,we focus on the lack of fit test of parametric regression models under the framework of big data.We develop a computationally feasible testing approach via integrating the divide-and-conquer algorithm into a powerful nonparametric test statistic.Our theory results show that under mild conditions,the asymptotic null distribution of the proposed test is standard normal.Furthermore,the proposed test benefits fromthe use of data-driven bandwidth procedure and thus possesses certain adaptive property.Simulation studies show that the proposed method has satisfactory performances,and it is illustrated with an analysis of an airline data.

A General Approach to Testing Volatility Models in Time Series

Volatility models have been playing important roles in economics and finance.Using a generalized spectral second order derivative approach,we propose a new class of generally applicable omnibus tests for the adequacy of linear and nonlinear volatility models.Our tests have a convenient asymptotic null N(0,1)distribution,and can detect a wide range of misspecifications for volatility dynamics,including both neglected linear and nonlinear volatility dynamics.Distinct from the existing diagnostic tests for volatility models,our tests are robust to time-varying higher order moments of unknown form(e.g.,time-varying skewness and kurtosis).They check a large number of lags and are therefore expected to be powerful against neglected volatility dynamics that occurs at higher order lags or display long memory properties.Despite using a large number of lags,our tests do not suffer much from the loss of a large number of degrees of freedom,because our approach naturally discounts higher order lags,which is consistent with the stylized fact that economic or financial markets are affected more by the recent past events than by the remote past events.No specific estimation method is required,and parameter estimation uncertainty has no impact on the convenient limit N(0,1)distribution of the test statistics.Moreover,there is no need to formulate an alternative volatility model,and only estimated standardized residuals are needed to implement our tests.We do not have to calculate tedious and model-specific score functions or derivatives of volatility models with respect to estimated parameters,which are required in some existing popular diagnostic tests for volatility models.We examine the finite sample performance of the proposed tests.It is documented that the new tests are rather powerful in detecting neglected nonlinear volatility dynamics which the existing tests can easily miss.They are useful diagnostic tools for practitioners when modelling volatility dynamics.