Duration Adjustment of Acute Exposure Guideline Level Values for Trichloroethylene Using a Physiologically-Based Pharmacokinetic Model

Acute Exposure Guideline Level (AEGL) recommendations are developed for 10-minute, 30-minute, 1-hour, 4-hours, and 8-hours exposure durations and are designated for three levels of severity: AEGL-1 represents concentrations above which acute exposures may cause noticeable discomfort including irritation; AEGL-2 represents concentrations above which acute exposure may cause irreversible health effects or impaired ability to escape; and AEGL-3 represents concentrations above which exposure may cause life-threatening health effects or death. The default procedure for setting AEGL values across durations when applicable data are unavailable involves estimation based on Haber's rule, which has an underlying assumption that cumulative exposure is the determinant of toxicity. For acute exposure to trichloroethylene (TCE), however, experimental data indicate that momentary tissue concentration, and not the cumulative amount of exposure, is important. We employed an alternative approach to duration adjustments in which a physiologically-based pharmacokinetic (PBPK) model was used to predict the arterial blood concentrations [TCE(a)] associated with adverse outcomes appropriate for AEGL-1, -2, or -3-level effects. The PBPK model was then used to estimate the atmospheric concentration that produces equivalent [TCE(a)] at each of the AEGL-specific exposure durations. This approach yielded [TCE(a)] values of 4.89 mg/l for AEGL-1, 18.7 mg/l for AEGL-2, and 310 mg/l for AEGL-3. Duration adjustments based on equivalent target tissue doses should provide similar degrees of toxicity protection at different exposure durations.     

Recognition of Emotions in Gait Patterns by Means of Artificial Neural Nets

This paper describes an application of emotion recognition in human gait by means of kinetic and kinematic data using artificial neural nets. Two experiments were undertaken, one attempting to identify participants’ emotional states from gait patterns, and the second analyzing effects on gait patterns of listening to music while walking. In the first experiment gait was analyzed as participants attempted to simulate four distinct emotional states (normal, happy, sad, angry). In the second experiment, participants were asked to listen to different types of music (excitatory, calming, no music) before and during gait analysis. Derived data were fed into different types of artificial neural nets. Results showed not only a clear distinction between individuals, but also revealed clear indications of emotion recognition in nets.     

Frailty models and copulas: similarities and differences

Copulas and frailty models are important tools to model bivariate survival data. Equivalence between Archimedean copula models and shared frailty models, e.g. between the Clayton-Oakes copula model and the shared gamma frailty model, has often been claimed in the literature. In this note we show that, in both the models, there is indeed a well-known equivalence between the copula functions; the modeling of the marginal survival functions, however, is quite different. The latter fact leads to different joint survival functions.     

Weighted Logrank Permutation Tests for Randomly Right Censored Life Science Data

In biomedical research, weighted logrank tests are frequently applied to compare two samples of randomly right censored survival times. We address the question how to combine a number of weighted logrank statistics to achieve good power of the corresponding survival test for a whole linear space or cone of alternatives, which are given by hazard rates. This leads to a new class of semiparametric projection tests that are motivated by likelihood ratio tests for an asymptotic model. We show that these tests can be carried out as permutation tests and discuss their asymptotic properties. A simulation study together with the analysis of a classical data set illustrates the advantages.     

Nonparametric density estimation for multivariate bounded data

We propose a new nonparametric estimator for the density function of multivariate bounded data. As frequently observed in practice, the variables may be partially bounded (e.g. nonnegative) or completely bounded (e.g. in the unit interval). In addition, the variables may have a point mass. We reduce the conditions on the underlying density to a minimum by proposing a nonparametric approach. By using a gamma, a beta, or a local linear kernel (also called boundary kernels), in a product kernel, the suggested estimator becomes simple in implementation and robust to the well known boundary bias problem. We investigate the mean integrated squared error properties, including the rate of convergence, uniform strong consistency and asymptotic normality. We establish consistency of the least squares cross-validation method to select optimal bandwidth parameters. A detailed simulation study investigates the performance of the estimators. Applications using lottery and corporate finance data are provided.     

Priming the sexual system: implicit versus explicit activation

We investigated implicit versus explicit activation of the sexual system using a priming paradigm in which sexual slides were preceded by either sexual or neutral primes. In the first experiment, primes were made inaccessible to conscious cognitive elaboration. Identification of sexual targets was facilitated by sexual primes, indicating that sexual representations in memory can be activated automatically. In the second experiment, in which primes were presented at a conscious level, identification of sexual targets was decelerated by sexual primes. Primes elicited subjective sexual arousal in Experiment 2 only, demonstrating that the activation of subjective experience requires conscious cognitive elaboration. With the addition of a sexually specific physiological measure, to be constructed to measure initial genital responses, this paradigm may help elucidate activational mechanisms of sexual response.     

Comparison of retrospective surveys with a longitudinal follow-up in Senegal: SFS,DHS and Niakhar

This study compares the data obtained from two retrospective surveys: the Senegal Fertility Survey (SFS) and the Demographic and Health Survey (DHS) with the data obtained from a longitudinal follow-up study held among the Sereer, living in a rural area of Senegal (Niakhar). The study shows that the fertility level is slightly higher in the retrospective surveys than in the longitudinal follow-up, the difference being mainly due to an overestimation of the fertility rate of the age group 15–19 years. The mortality levels and trends among under five children are correctly estimated by the DHS, but are underestimated by the SFS. The age pattern of mortality is slightly biased in the DHS and SFS, owing to errors on age at the time of death in these retrospective surveys. The comparison of the nutritional status was difficult to make because of the small sample size used in the DHS.     

Ethnic intermarriage in times of social change: The case of latvia

We gain insight into the dynamics of ethnic intermarriage in times of social change by studying marriages between Latvians and Russians (including Belarussians and Ukrainians) that occurred in Latvia before and after independence from the Soviet Union. Before independence, ethnic intermarriage was already rather common, involving about 17% of the marriages annually. Since independence, intermarriage between Russians and Latvians has increased substantially. Part of this increase can be explained by selective emigration, but at least half of it may be due to integrative processes. Although there were more marriages between Russian men and Latvian women before independence, the gender pattern reversed after independence. Intermarriage levels were the highest among the less educated, children of mixed couples, partners with similar educational levels, and people in the countryside.