Learning Conditional Distributions using Mixtures of Truncated Basis Functions

Mixtures of Truncated Basis Functions (MoTBFs) have recently been proposed for modelling univariate and joint distributions in hybrid Bayesian networks. In this paper we analyse the problem of learning conditional MoTBF distributions from data. Our approach utilizes a new technique for learning joint MoTBF densities, then propose a method for using these to generate the conditional distributions. The main contribution of this work is conveyed through an empirical investigation into the properties of the new learning procedure, where we also compare the merits of our approach to those obtained by other proposals

Composite drill stem of epoxy fiber glass reinforced with boron filaments and a retrievable core liner/sample return container for the Apollo lunar surface drill

Composite drill stem of epoxy fiber glass and boron filaments and lunar core sampling system for Apollo lunar surface dril

Learning Mixtures of Polynomials of Conditional Densities from Data

Mixtures of polynomials (MoPs) are a non-parametric density estimation technique for hybrid Bayesian networks with continuous and discrete variables. We propose two methods for learning MoP approximations of conditional densities from data. Both approaches are based on learning MoP approximations of the joint density and the marginal density of the conditioning variables, but they differ as to how the MoP approximation of the quotient of the two densities is found. We illustrate the methods using data sampled from a simple Gaussian Bayesian network. We study and compare the performance of these methods with the approach for learning mixtures of truncated basis functions from data

Reliability analysis of dynamic systems by translating temporal fault trees into Bayesian networks

Classical combinatorial fault trees can be used to assess combinations of failures but are unable to capture sequences of faults, which are important in complex dynamic systems. A number of proposed techniques extend fault tree analysis for dynamic systems. One of such technique, Pandora, introduces temporal gates to capture the sequencing of events and allows qualitative analysis of temporal fault trees. Pandora can be easily integrated in model-based design and analysis techniques. It is, therefore, useful to explore the possible avenues for quantitative analysis of Pandora temporal fault trees, and we identify Bayesian Networks as a possible framework for such analysis. We describe how Pandora fault trees can be translated to Bayesian Networks for dynamic dependability analysis and demonstrate the process on a simplified fuel system model. The conversion facilitates predictive reliability analysis of Pandora fault trees, but also opens the way for post-hoc diagnostic analysis of failures

A nested case-control study of polychlorinated biphenyls, organochlorine pesticides, and thyroid cancer in the Janus Serum Bank cohort

Background: Polychlorinated biphenyls (PCBs) and organochlorine pesticides have been associated with altered thyroid hormone levels in humans, but their relationship with thyroid cancer is unknown. Methods: We conducted a nested case-control study of thyroid cancer in the Norwegian Janus Serum Bank cohort using pre-diagnostic blood samples from 1972 to 1985. Incident thyroid cancer (n = 108) was ascertained through 2008. Controls were matched 2:1 by age, date of blood draw, gender, and county. We used gas chromatography/mass spectrometry to quantify 36 PCB congeners and metabolites of pesticides DDT, chlordane, hexachlorocyclohexane, and hexachlorobenzene. PCBs and pesticide metabolites were evaluated individually and summed by degree of chlorination and parent compound, respectively. Odds ratios (OR) and 95% confidence intervals (CI) were computed using conditional logistic regression per specified increase in lipid-adjusted concentration. We additionally stratified analyses by birth cohort (1923–1932, 1933–1942, 1943–1957). Results: Increasing concentration of DDT metabolites (OR per 1000 ng/g = 0.80, 95%CI = 0.66–0.98) was inversely associated with thyroid cancer. Associations for PCBs were null or in inverse direction. We observed interactions for total PCBs, moderately-chlorinated PCBs, and chlordane metabolites with birth cohort (p ≤ 0.04). Among participants born 1943–1957, total PCBs (OR per 100 ng/g = 1.25, 95%CI = 1.00–1.56), moderately-chlorinated PCBs (OR per 100 ng/g = 1.31, 95%CI = 1.01–1.70), and chlordane metabolites (OR per 10 ng/g = 1.78, 95%CI = 1.09–2.93) were positively associated with thyroid cancer. For individuals born before 1943, associations were generally null or in the inverse direction. Conclusions: Emissions of PCBs and OC pesticides varied over time. Different risk patterns by birth cohort suggest the potential importance of timing of exposure in thyroid cancer risk. Further evaluation of these associations is warranted

Lung cancer mortality in towns near paper, pulp and board industries in Spain: a point source pollution study

<p>Abstract</p> <p>Background</p> <p>This study sought to ascertain whether there might be excess lung cancer mortality among the population residing in the vicinity of Spanish paper and board industries which report their emissions to the European Pollutant Emission Register (EPER).</p> <p>Methods</p> <p>This was an ecological study that modelled the Standardised Mortality Ratio (SMR) for lung cancer in 8073 Spanish towns over the period 1994–2003. Population exposure to industrial pollution was estimated on the basis of distance from town of residence to pollution source. An exploratory, near-versus-far analysis was conducted, using mixed Poisson regression models and an analysis of the effect of municipal proximity within a 50-kilometre radius of each of the 18 installations.</p> <p>Results</p> <p>Results varied for the different facilities. In two instances there was an increasing mortality gradient with proximity to the installation, though this was exclusively observed among men.</p> <p>Conclusion</p> <p>The study of cancer mortality in areas surrounding pollutant foci is a useful tool for environmental surveillance, and serves to highlight areas of interest susceptible to being investigated by ad hoc studies. Despite present limitations, recognition is therefore due to the advance represented by publication of the EPER and the study of pollutant foci.</p

Pre-diagnostic serum concentrations of organochlorines and risk of acute myeloid leukemia: A nested case-control study in the Norwegian Janus Serum Bank Cohort

Background: Epidemiologic studies suggest an increased risk of leukemia among individuals occupationally exposed to some organochlorine (OC) compounds. Associations between serum OC pesticide and polychlorinated biphenyl (PCB) levels and risk of acute myeloid leukemia (AML), the most common subtype of acute leukemia in adult populations, have not been evaluated prospectively in the general population. Objective: We evaluated the risk of AML in relation to pre-diagnostic serum levels of OC pesticides and PCBs in a case-control study nested within the Janus Serum Bank Cohort. Methods: Janus is a large population-based cohort containing biologic samples collected beginning in the early 1970s from ~318,000 individuals in Norway. Serum levels of 11 OC pesticides or their metabolites and 34 PCB congeners were measured in 56 AML cases and 288 controls. Conditional logistic regression was conducted to evaluate associations between lipid-adjusted serum OC levels and risk of AML. Results: Higher serum levels of total chlordane/heptachlor metabolites were associated with AML risk (3rd vs. 1st tertile odds ratio (OR) = 2.26, 95% confidence interval (CI) = 0.91–5.63; ptrend = 0.11). Significant exposure-response associations were observed for levels of heptachlor epoxide (3rd vs. 1st tertile OR = 2.85, 95% CI = 1.05–7.73; ptrend = 0.02) and dieldrin (3rd vs. 1st tertile OR = 2.71, 95% CI = 1.07–6.83; ptrend = 0.03). No significant exposure-response associations with AML risk were observed for total DDT or individual isomers and derivatives. Higher serum levels of p,p′-DDT showed a non-significant increase in risk, but the exposure-response became attenuated when co-adjusting for heptachlor epoxide or dieldrin levels. Serum PCB levels were not significantly associated with AML risk. Conclusions: Our data suggest that higher serum levels of dieldrin and metabolites derived from chlordane/heptachlor are associated with risk of AML in the general Norwegian population, based on samples collected on average ~17 years before diagnosis. Further research in populations with historically high or recent exposure to DDT is warranted to assess the association with AML risk with body burden of specific DDT isomers and derivatives

AGRICOH: A Consortium of Agricultural Cohorts

AGRICOH is a recently formed consortium of agricultural cohort studies involving 22 cohorts from nine countries in five continents: South Africa (1), Canada (3), Costa Rica (2), USA (6), Republic of Korea (1), New Zealand (2), Denmark (1), France (3) and Norway (3). The aim of AGRICOH, initiated by the US National Cancer Institute (NCI) and coordinated by the International Agency for Research on Cancer (IARC), is to promote and sustain collaboration and pooling of data to investigate the association between a wide range of agricultural exposures and a wide range of health outcomes, with a particular focus on associations that cannot easily be addressed in individual studies because of rare exposures (e.g., use of infrequently applied chemicals) or relatively rare outcomes (e.g., certain types of cancer, neurologic and auto-immune diseases). To facilitate future projects the need for data harmonization of selected variables is required and is underway. Altogether, AGRICOH provides excellent opportunities for studying cancer, respiratory, neurologic, and auto-immune diseases as well as reproductive and allergic disorders, injuries and overall mortality in association with a wide array of exposures, prominent among these the application of pesticides