Objectives—To evaluate the contribution of traYc fumes to exposure to benzene in urban workers, an investigation on personal exposure to benzene in traYc police from the city of Rome was carried out. Methods—The study was performed from December 1998 to June 1999. DiVusive Radiello personal samplers were used to measure external exposures to benzene and alkyl benzenes during the workshift in 13...

We describe an approach to automatic discovery of samplers in the form of human interpretable probabilistic programs. Specifically, we learn the procedure code of samplers for one-dimensional distributions. We formulate a Bayesian approach to this problem by specifying an adaptor grammar prior over probabilistic program code, and use approximate Bayesian computation to learn a program whose exe...

This paper presents a performance and statistical analysis of random number generators and discrete Gaussian samplers implemented in software. Most Lattice-based cryptographic schemes utilise discrete Gaussian sampling and will require a quality random source. We examine a range of candidates for this purpose, including NIST DRBGs, stream ciphers and well-known PRNGs. The performance of these r...

Automated scanning electron microscope analyses of gunshot residue samplers are being performed by many crime laboratories all over the world. Often the criminalist-technician operators of these instruments do not have adequate training for the interpretation of spectra generated by energy dispersive X-ray spectroscopy (parts I and II of this series) and distinguishing gunshot residue from simi...

Nonparametric Bayesian approaches to clustering, information retrieval, language modeling and object recognition have recently shown great promise as a new paradigm for unsupervised data analysis. Most contributions have focused on the Dirichlet process mixture models or extensions thereof for which efficient Gibbs samplers exist. In this paper we explore Gibbs samplers for infinite complexity ...

Monte Carlo approaches have recently been proposed to quantify connectivity in neuronal networks. The key problem is to sample from the conditional distribution of a single neuronal spike train, given the activity of the other neurons in the network. Dependencies between neurons are usually relatively weak; however, temporal dependencies within the spike train of a single neuron are typically s...

A key limitation of sampling algorithms for approximate inference is that it is difficult to quantify their approximation error. Widely used sampling schemes, such as sequential importance sampling with resampling and MetropolisHastings, produce output samples drawn from a distribution that may be far from the target posterior distribution. This paper shows how to upper-bound the symmetric KL d...

Perfect sampling using the coupling from the past (CFTP) algorithm was introduced by Propp and Wilson in 1996. In much the way rejection sampling allows one to convert samplers from one distribution into samplers from another, CFTP allows one to convert Markov chain Monte Carlo algorithms from approximate samplers of the steady-state distribution into perfect ones. Since 1996 CFTP has been appl...

The availability of polycyclic aromatic hydrocarbons (PAHs) from marine sediments to the ragworm (Nereis virens) was studied. Concentrations of PAHs in pore waters were determined using silicone rubber passive samplers. Calculated bioconcentration factors confirmed that partitioning of PAHs between the lipid phase of the polychaetes and pore water is a passive process. Low biota-sediment accumu...

Several samplers (IOM, CIP 10-I v1, ACCU-CAP, and Button) were evaluated at various wood industry companies using the CALTOOL system. The results obtained show that compared to the CALTOOL mouth, which can be considered to be representative of the exposure of a person placed at the same location under the same experimental conditions, the concentrations measured by the IOM, CIP 10-I v1, and ACC...