Epithermal neutron activation analysis of short-lived radionuclides using a pneumatic transport system and a pulsed D-T neutron generator

A pneumatic transport system for the detection and characterization of short-lived (of order 60 s or less) radionuclides produced during irradiation by a D-T neutron generator was constructed. Target samples of indium, palladium, and germanium were irradiated by the neutron generator embedded in a graphite monolith to produce epithermal activation products. The three radioisotopes of interest are palladium-107, palladium-109, and germanium-75. The experimental half-lives of each of the three isotopes, with the specific activity in parenthesis are: 21.82±3.71 (49.36 nCi/g), 279.21±27.80 (158.91 nCi/g), and 48.51±12.58 (504.78 nCi/g) respectively. These experimental half-lives agree with the published half-lives. The Monte Carlo N-Particle (MCNP) radiation transport code was used to model the graphite pile, the pneumatic transport tube, and the neutron generator. This resulted in benchmarking and validation of the experimental results. In order to reach an agreement between the experimental results and MCNP, a modification was required to the neutron absorption reaction rate produced from MCNP using isomeric to ground state ratios to accurately account for the decay mode most common with these short-lived radioisotopes

Вплив пропелерної модуляції на ефективність просторової режекції завад адаптивними антенами бортових систем зв'язку

Розглянуто проблему впливу пропелерної модуляції на ефективність просторової режекції завад адаптивними антенами бортових систем зв’язку

Efficient p-value estimation in massively parallel testing problems

We present a new method to efficiently estimate very large numbers of p-values using empirically constructed null distributions of a test statistic. The need to evaluate a very large number of p-values is increasingly common with modern genomic data, and when interaction effects are of interest, the number of tests can easily run into billions. When the asymptotic distribution is not easily available, permutations are typically used to obtain p-values but these can be computationally infeasible in large problems. Our method constructs a prediction model to obtain a first approximation to the p-values and uses Bayesian methods to choose a fraction of these to be refined by permutations. We apply and evaluate our method on the study of association between 2-way interactions of genetic markers and colorectal cancer using the data from the first phase of a large, genome-wide case–control study. The results show enormous computational savings as compared to evaluating a full set of permutations, with little decrease in accuracy

A factor model to analyze heterogeneity in gene expression

<p>Abstract</p> <p>Background</p> <p>Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene dependence structure. This leads to correlation among test statistics which affects a strong control of the false discovery proportion. A recent method called FAMT allows capturing the gene dependence into factors in order to improve high-dimensional multiple testing procedures. In the subsequent analyses aiming at a functional characterization of the differentially expressed genes, our study shows how these factors can be used both to identify the components of expression heterogeneity and to give more insight into the underlying biological processes.</p> <p>Results</p> <p>The use of factors to characterize simple patterns of heterogeneity is first demonstrated on illustrative gene expression data sets. An expression data set primarily generated to map QTL for fatness in chickens is then analyzed. Contrarily to the analysis based on the raw data, a relevant functional information about a QTL region is revealed by factor-adjustment of the gene expressions. Additionally, the interpretation of the independent factors regarding known information about both experimental design and genes shows that some factors may have different and complex origins.</p> <p>Conclusions</p> <p>As biological information and technological biases are identified in what was before simply considered as statistical noise, analyzing heterogeneity in gene expression yields a new point of view on transcriptomic data.</p

CFH and ARMS2 genetic risk determines progression to neovascular age-related macular degeneration after antioxidant and zinc supplementation

We evaluated the influence of an antioxidant and zinc nutritional supplement [the Age-Related Eye Disease Study (AREDS) formulation] on delaying or preventing progression to neovascular AMD (NV) in persons with age-related macular degeneration (AMD). AREDS subjects (n = 802) with category 3 or 4 AMD at baseline who had been treated with placebo or the AREDS formulation were evaluated for differences in the risk of progression to NV as a function of complement factor H (CFH) and age-related maculopathy susceptibility 2 (ARMS2) genotype groups. We used published genetic grouping: a two-SNP haplotype risk-calling algorithm to assess CFH, and either the single SNP rs10490924 or 372_815del443ins54 to mark ARMS2 risk. Progression risk was determined using the Cox proportional hazard model. Genetics–treatment interaction on NV risk was assessed using a multiiterative bootstrap validation analysis. We identified strong interaction of genetics with AREDS formulation treatment on the development of NV. Individuals with high CFH and no ARMS2 risk alleles and taking the AREDS formulation had increased progression to NV compared with placebo. Those with low CFH risk and high ARMS2 risk had decreased progression risk. Analysis of CFH and ARMS2 genotype groups from a validation dataset reinforces this conclusion. Bootstrapping analysis confirms the presence of a genetics–treatment interaction and suggests that individual treatment response to the AREDS formulation is largely determined by genetics. The AREDS formulation modifies the risk of progression to NV based on individual genetics. Its use should be based on patient-specific genotype

The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer

Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., ~140–160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual’s CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with CRC before the question of the potential utility of germline genomic profiling can be definitively answered

Analiza wypadków lotniczych zaistniałych w jednostkach Wyższej Oficerskiej Szkoły Lotniczej w latach 1970–1994

The article was written on basis of Flight safety brochures published by the Polish Air Force Academy from 1975 to 1998. The first part is dedicated for actual training process of the Polish military pilots. The second component focuses on the main causes of the occurrence of aircraft accidents in units of the Polish Air Force Academy in concerned period of time. The further part of the article is dedicated to analysis of aircraft accidents occurred in military aviation training units in years 1970–1994.Poniższy artykuł został napisany w oparciu o Informatory bezpieczeństwa lotów, wydane w Wyższej Szkole Oficerskiej Sił Powietrznych w latach 1975–1998. W części pierwszej opisano aktualny proces szkolenia pilotów wojskowych w Polsce. Następnie scharakteryzowano główne przyczyny wypadków lotniczych w jednostkach Wyższej Szkoły Oficerskiej Sił Powietrznych w rozpatrywanym okresie. W ostatniej części artykułu poddano analizie wypadki zaistniałe w jednostkach szkolnych w latach 1970– 1994

Surface and curve skeletonization of large 3D models on the GPU

We present a GPU-based framework for extracting surface and curve skeletons of 3D shapes represented as large polygonal meshes. We use an efficient parallel search strategy to compute point-cloud skeletons and their distance and feature transforms with user-defined precision. We regularize skeletons by a new GPU-based geodesic tracing technique which is orders of magnitude faster and more accurate than comparable techniques. We reconstruct the input surface from skeleton clouds using a fast and accurate image-based method. We also show how to reconstruct the skeletal manifold structure as a polygon mesh and the curve skeleton as a polyline. Compared to recent skeletonization methods, our approach offers two orders of magnitude speed-up, high precision, and low memory footprints. We demonstrate our framework on several complex 3D models. Keywords: Medial axes, geodesics, skeleton regularizatio