Human Salmonellosis: Estimation of Dose-Illness from Outbreak Data

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.     

基于虚拟仪器的土壤水分测试系统开发

采用PCl-812PG数据采集卡,基于虚拟仪器技术,以Delphi作为平台开发了土壤含水量测试系统,对AZS -2土壤水分传感器的功能进行了扩展。标定结果及实际应用表明,此系统性能稳定,精度较高。     

一个数据流查询系统的设计与实现

就目前大多数数据流查询处理过程中可能出现的一些问题，根据数据流处理的特点和要求，提出了新的查询处理结构，实现了数据共享及多流多查询环境下查询的处理．     

转型期中国农村区域消费水平与结构的实证分析

农村消费市场低迷是制约我国经济发展的主要因素。运用主成分聚类方法及Panel Data数据模型,结合1994—2003年的时序截面数据,对我国农村区域消费水平与结构的差异进行静态与动态分析。     

利用数控增益放大器提高A/D转换器的分辨率

文章介绍利用数控增益放大器LH0086大幅度提高A／D转换器分辨率的方法,可将8位A／D转换器的分辨率提高到接近16位A／D的水平,适用于高速数据系采集系统,给出了相应的硬件原理图和软件框图。     

Data relaying with constraints in hierarchical sensor networks

In this paper we present and discuss several optimisation problems that arise in the management of data flow in wireless sensor networks (WSNets). We consider a hierarchical architecture for WSNets composed of sensors, relays, and relay gateways. Sensors send data they generate at a known average bit rate to relays in one hop. The relay nodes use a multi-hop mechanism to reach a set of assigned gateways which then forward the data directly to the base station. We are concerned with finding an assignment of relay gateways to relays so that certain constraints are satisfied. We define a unified model in which constraints such as lifetime, data delay, and data flow splitting are formulated in terms of four optimisation problem in graphs.     

Substance use disorders and referral to treatment in substantiated cases of child maltreatment

Parents with substance use disorders (SUD) require treatment and support in order to provide children with appropriate care and protection. Using the 2012 National Child Abuse and Neglect Data System (NCANDS), this paper analysed 464 313 substantiated child maltreatment reports to determine (i) the proportion and characteristics of reports involving substance abuse; and (ii) the child and caregiver/perpetrator (C/P) characteristics that predicted referral to treatment as recorded in service plans. Findings indicate that 12% (N = 53 234) of maltreatment reports involved C/P SUD. Yet, of those reports, only (19%) (N = 10 088) were referred to substance abuse treatment as part of their service plan, indicating a large gap between those who need treatment and those who receive it. This finding is important given that parental SUD is consistently linked to poorer child outcomes. Amongst other variables, reports indicate that C/P with co‐occurring emotional disturbance were three times more likely to be referred to treatment for SUD as part of service plans. Additional research is needed regarding the characteristics that distinguish C/P who receive referrals for SUD treatment in substantiated cases of child maltreatment.     

A latent variable model for analyzing mixed longitudinal (k,l)-inflated count and ordinal responses

A random effects model for analyzing mixed longitudinal count and ordinal data is presented where the count response is inflated in two points (k and l) and an (k,l)-Inflated Power series distribution is used as its distribution. A full likelihood-based approach is used to obtain maximum likelihood estimates of parameters of the model. For data with non-ignorable missing values models with probit model for missing mechanism are used.The dependence between longitudinal sequences of responses and inflation parameters are investigated using a random effects approach. Also, to investigate the correlation between mixed ordinal and count responses of each individuals at each time, a shared random effect is used. In order to assess the performance of the model, a simulation study is performed for a case that the count response has (k,l)-Inflated Binomial distribution. Performance comparisons of count-ordinal random effect model, Zero-Inflated ordinal random effects model and (k,l)-Inflated ordinal random effects model are also given. The model is applied to a real social data set from the first two waves of the national longitudinal study of adolescent to adult health (Add Health study). In this data set, the joint responses are the number of days in a month that each individual smoked as the count response and the general health condition of each individual as the ordinal response. For the count response there is incidence of excess values of 0 and 30.     

Bayesian Estimation and Model Choice in Item Response Models

Item response models are essential tools for analyzing results from many educational and psychological tests. Such models are used to quantify the probability of correct response as a function of unobserved examinee ability and other parameters explaining the difficulty and the discriminatory power of the questions in the test. Some of these models also incorporate a threshold parameter for the probability of the correct response to account for the effect of guessing the correct answer in multiple choice type tests. In this article we consider fitting of such models using the Gibbs sampler. A data augmentation method to analyze a normal-ogive model incorporating a threshold guessing parameter is introduced and compared with a Metropolis-Hastings sampling method. The proposed method is an order of magnitude more efficient than the existing method. Another objective of this paper is to develop Bayesian model choice techniques for model discrimination. A predictive approach based on a variant of the Bayes factor is used and compared with another decision theoretic method which minimizes an expected loss function on the predictive space. A classical model choice technique based on a modified likelihood ratio test statistic is shown as one component of the second criterion. As a consequence the Bayesian methods proposed in this paper are contrasted with the classical approach based on the likelihood ratio test. Several examples are given to illustrate the methods.     

革命时代的生活与文学之美——《这边风景》简论

对于王蒙个体和当代文学史来说,《这边风景》都是别具典型意义的作品。小说深入、直观地展现了作家16年新疆生涯,饱含着当年的王蒙与今日的王蒙对青春岁月的极大热忱与真诚。它以丰富的经典细节,表现了革命年代边疆百姓的切肤生活和情感,而"意识流"和"小说人语"手法的运用,扩展了作品的艺术表现力,构成了作家穿越文化时空的灵魂对话。