Multiplex Rapid Test with Acceptable Diagnosis Performance as a Solution to Increase Diagnosis of Hepatitis B and C Viruses in Pregnant Women in an Area of High Prevalence of Both Hepatitis Viruses Associated with HIV

Background and Objective: HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV) are very widespread in the world, however, less than 20% of the people affected are diagnosed and treated. This study aimed to determine the prevalence of HIV, HCV and HBV co-infections in pregnant women at Bangui Community University Hospital and the cost of screening. Methods: A cross-sectional study involving consenting pregnant women who came for antenatal care was performed. HIV, HCV antibodies and HBV antigens were detected using Exacto Triplex? HIV/HCV/HBsAg rapid test, cross-validated by ELISA tests. Sociodemographic and professional data, the modes of transmission and prevention of HIV and both hepatitis viruses were collected in a standard sheet and analyzed using the Epi-Info software version 7. Results: Pregnant women aged 15 to 24 were the most affected (45.3%);high school girls (46.0%), and pregnant women living in cohabitation (65.3%) were the most represented. Twenty-five (16.7%) worked in the formal sector, 12.7% were unemployed housewives and the remainder in the informal sector. The prevalence of HIV, HBV, and HCV viruses was 11.8%, 21.9% and 22.2%, respectively. The prevalence of co-infections was 8.6% for HIV-HBV, 10.2% for HIV-HCV, 14.7% for HBV-HCV and 6.5% for HIV-HBV-HCV. All positive results and 10% of negative results by the rapid test were confirmed by ELISA tests. The serology of the three viruses costs 39,000 FCFA (60 Euros) by ELISA compared to 10,000 FCFA (15.00 Euros) with Exacto Triplex? HIV/HCV/AgHBs (BioSynex, Strasbourg, France). Conclusion: The low level of education and awareness of hepatitis are barriers to development and indicate the importance of improving the literacy rate of women in the Central African Republic (CAR). Likewise, the high prevalence of the three viruses shows the need for the urgent establishment of a national program to combat viral hepatitis in the CAR.

Attribute Reduction with Test Cost Constraint

In many machine learning applications,data are not free,and there is a test cost for each data item. For the economical reason,some existing works try to minimize the test cost and at the same time,preserve a particular property of a given decision system. In this paper,we point out that the test cost one can afford is limited in some applications. Hence,one has to sacrifice respective properties to keep the test cost under a budget. To formalize this issue,we define the test cost constraint attribute reduction problem,where the optimization objective is to minimize the conditional information entropy. This problem is an essential generalization of both the test-cost-sensitive attribute reduction problem and the 0-1 knapsack problem,therefore it is more challenging. We propose a heuristic algorithm based on the information gain and test costs to deal with the new problem. The algorithm is tested on four UCI（University of California-Irvine） datasets with various test cost settings. Experimental results indicate the appropriate setting of the only user-specified parameter λ.

Area-time associated test cost model for SoC and lower bound of test time

A novel test access mechanism （TAM） architecture with multi test-channel （TC） based on IEEE Standard 1500 is proposed instead of the traditional sub-TAM structure. The cost model of an area-time associated test and the corresponding lower bound of system-on-chip （SoC） test time are established based on this TAM architecture. The model provides a more reliable method to control the SoC scheduling and reduces the complexity in related algorithm research. The result based on the area time associated test cost model has been validated using the ITC02 test benchmark.

A computational model of the human glucose-insulin regulatory system

Objective：A computational model of insulin secretion and glucose metabolism for assisting the diagnosis of diabetes mellitus in clinical research is introduced.The proposed method for the estimation of parameters for a system of ordinary differential equations（ODEs）that represent the time course of plasma glucose and insulin concentrations during glucose tolerance test（GTT）in physiological studies is presented.The aim of this study was to explore how to interpret those laboratory glucose and insulin data as well as enhance the Ackerman mathematical model.Methods：Parameters estimation for a system of ODEs was performed by minimizing the sum of squared residuals（SSR）function,which quantifies the difference between theoretical model predictions and GTT＇s experimental observations.Our proposed perturbation search and multiple-shooting methods were applied during the estimating process.Results：Based on the Ackerman＇s published data,we estimated the key parameters by applying R-based iterative computer programs.As a result,the theoretically simulated curves perfectly matched the experimental data points.Our model showed that the estimated parameters,computed frequency and period values,were proven a good indicator of diabetes.Conclusion：The present paper introduces a computational algorithm to biomedical problems,particularly to endocrinology and metabolism fields,which involves two coupled differential equations with four parameters describing the glucose-insulin regulatory system that Ackerman proposed earlier.The enhanced approach may provide clinicians in endocrinology and metabolism field insight into the transition nature of human metabolic mechanism from normal to impaired glucose tolerance.

Multiple Objective Test Design for Accelerated Destructive Degradation Tests

Accelerated destructive degradation tests(ADDTs)are powerful to provide reliability information in the degradation processes with destructive measurements.In order to carry out an ADDT efficiently,both the estimation precision of parameters and the test cost should be considered.On the basis of the given degradation model and failure criterion,a multiple-objective optimization model for the design of ADDTs is proposed.Under constrains of the maximum measurement time,the total sample size and the number of stress levels,a comprehensive target function is suggested to reflect both the precision of lifetime estimation and total cost,and the optimal test plan is obtained,which is composed by optimal choices for samples size,measurement frequency,and the number of measurements at each stress level.A real example is illustrated to demonstrate the implementation of the proposed approach.

Test sequencing problem arising at the design stage for reducing life cycle cost

Previous test sequencing algorithms only consider the execution cost of a test at the application stage. Due to the fact that the placement cost of some tests at the design stage is considerably high compared with the execution cost, the sequential diagnosis strategy obtained by previous methods is actually not optimal from the view of life cycle. In this paper, the test sequencing problem based on life cycle cost is presented. It is formulated as an optimization problem, which is non-deterministic polynomial-time hard （NP-hard）. An algorithm and a strategy to improve its computational efficiency are proposed. The formulation and algorithms are tested on various simulated systems and comparisons are made with the extant test sequencing methods. Application on a pump rotational speed control （PRSC） system of a spacecraft is studied in detail. Both the simulation results and the real-world case application results suggest that the solution proposed in this paper can significantly reduce the life cycle cost of a sequential fault diagnosis strategy.

On Test Data Compression Using Selective Don＇t-Care Identification

This paper proposes an effective method for reducing test data volume undermultiple scan chain designs. The proposed method is based on reduction of distinct scan vectorsusing selective don't-care identification. Selective don't-care identification is repeatedlyexecuted under condition that each bit of frequent scan vectors is fixed to binary values (0 or 1).Besides, a code extension technique is adopted for improving compression efficiency with keepingdecompressor circuits simple in the manner that the code length for infrequent scan vectors isdesigned as double of that for frequent ones. The effectiveness of the proposed method is shownthrough experiments for ISCAS'89 and ITC'99 benchmark circuits.