Use of a Chemical Probe to Increase Safety for Human Volunteers in Toxicokinetic Studies

To avoid interspecies extrapolation in toxicokinetics and drug development, it is convenient to directly develop human data. In that case, exposure dose should pose null or negligible risk to the exposed individual, but still be sufficiently high to allow quantification. We propose to reduce the dose received by human volunteers during exposure, and to compensate for loss of information by exposing the same volunteers to a nontoxic agent. This method was applied to develop 1,3-butadiene (BD) exposure protocols for humans. To study the potential of such a procedure, we worked with simulated data. Three exposure times (20, 10, and 5 minutes) and four exposure concentrations (2, 1, 0.8, and 0.5 ppm) were used to define 12 inhalation exposure scenarios for BD. Isoflurane was used as a probe, with simulated exposure of 20 subjects to 20 ppm isoflurane during 15 minutes. Isoflurane or BD-exhaled air concentrations were supposed to be measured 10 times. A three-compartment physiological toxicokinetic model was used to jointly describe BD and isoflurane data. For each subject, BD data were analyzed, in a Bayesian framework, either alone or together with the isoflurane data. The precision of BD metabolic rate constant or fraction metabolized was increased, and bias reduced, when BD and probe data were considered jointly. An exposure to 10 ppm x min BD and 300 ppm x min isoflurane gave equivalent precision and bias as a unique exposure to 40 ppm x min BD. The BD dose received by volunteers could therefore be at least quartered if BD exposure was supplemented with that of a probe.     

Ist Das Normalarbeitsverhältnis Noch Armutsvermeidend?

The article tests the hypothesis that welfare state retrenchment and labor market deregulation have increased poverty within the German working population using a time series of poverty ratios based on different income concepts for a period of 14 years (1991–2004). The basic assumption is that changes in the societal context (welfare state, labor market, houschold structures), besides individual risk factors, explain the development of poverty over time. Using data from the German Socio-Economic Panel Study it is shown that changing labor market conditions and tax regulations have increased poverty, and this has not been attenuated by additional income sources (welfare state, household members) or by recent changes in household composition. As a result, poverty has increased for full-time employees during the observation period, especially so in Eastern Germany.     

D-distribution and its applications

We derive the distribution of the sum ofn independent doubly truncated Poisson variables not necessarily identically distributed. This distribution is called a D-distribution. Its p.d.f. can be expressed in terms of a D-number and an incomplete exponential function which are both defined in this paper. We investigate the relationship between these numbers and distributions, and use these relationships to derive recurrence relations and other properties of the D-distribution. A minimum variance unbiased estimates of the p.d.f. of this D-distribution is also obtained. Some example are included at the end to illustrate the use of this D-distribution.     

An Effective Statistical Approach for Comparative Risk Assessment1

Comparative risk assessment is an evaluation process designed to rank environmental problems based on the severity of potential hazards. The purpose of this paper is to provide an effective statistical approach to analyze perceived environmental risks. Environmental problems, evaluative criteria, and other potential moderator variables need to be determined first, and then the risk perception data collected. Repeated measures analysis is used to first test for interactions between environmental problems and potential moderator variables. If there are no significant interactions, then the risk difference among environmental problems is tested unconditionally; otherwise the risk difference is tested conditionally. Cluster analysis for environmental problems is performed only when the risk difference is significant. The clustering results can be objectively determined by using the simultaneous T² confidence intervals. Risk-based priority setting is made according to the clusters obtained. To illustrate this approach, an empirical study of comparative socioeconomic risks in Taiwan was conducted. Socioeconomic impacts areas including social security, quality of life, production cost, investment willingness, and economic resources are used as evaluative criteria. Results indicate that selected impact areas do affect relative risk differences among 24 environmental problems, and the difference is significant for each area. Therefore, cluster analysis is conducted separately for each impact area. Risk-based priority settings for clusters of environmental problems are reported.     

Some remarks on bootstrap techniques for constructing confidence intervals

As techniques of constructing confidence intervals for a parameter, the classical, the studentized and the prepivoted bootstrap are discussed and compared in a Monte-Carlo study.     

试论学位论文资源的开发与利用

博硕士学位论文具有很高的信息价值,也是科研人员的重要参考文献。如何合理地开发和利用这些信息资料,在现有条件下实现优化管理是当前图书工作面临的一个现实问题。高校图书馆利用80/20法则管理学位论文可以更好地利用信息资源,发挥高校的科研优势,取得最佳管理效果,值得应用和推广。     

SZ and CMB reconstruction using generalized morphological component analysis

In the last decade, the study of cosmic microwave background (CMB) data has become one of the most powerful tools for studying and understanding the Universe. More precisely, measuring the CMB power spectrum leads to the estimation of most cosmological parameters. Nevertheless, accessing such precious physical information requires extracting several different astrophysical components from the data. Recovering those astrophysical sources (CMB, Sunyaev–Zel’dovich clusters, galactic dust) thus amounts to a component separation problem which has already led to an intensive activity in the field of CMB studies. In this paper, we introduce a new sparsity-based component separation method coined Generalized Morphological Component Analysis (GMCA). The GMCA approach is formulated in a Bayesian maximum a posteriori (MAP) framework. Numerical results show that this new source recovery technique performs well compared to state-of-the-art component separation methods already applied to CMB data.