Comparative Enumeration Gene Expression

This paper is about differential gene expression measured by transcript counting methods such as SAGE or MPSS. It introduces two significance tests for detection of differential expressed tags: frequentist and Bayesian. Under the frequentist view, it is proposed a test that computes the critical level as a function of each tag total frequency. Under the Bayesian view the Full Bayesian Significance Test is used considering the logistic normal distribution. The two proposed significance levels, the frequentist and the Bayesian, are compared for a data set with four libraries. The linking function between them is a Beta distribution function with mean 0.39 and standard deviation 0.30

The Maize Seed Industries of Brazil and Mexico: Past Performance, Current Issues, and Future Prospects

This paper describes results of a study of the main factors affecting the development of the maize seed industries in Brazil and Mexico (and, by extension, other developing countries). The authors develop a framework that researchers and policy makers can use to evaluate seed industry performance in developing countries. This framework is used to analyze the seed industries of Brazil and Mexico, where very different sets of circumstances influence seed industry development, efficiency, and structure. The analysis gives special attention to the different maize breeding strategies pursued by the public and private sectors, measures of industry competitiveness and efficiency, and the trade-offs involved in developing and producing different kinds of maize seed, particularly improved open-pollinated maize varieties versus different types of hybrids. The authors identify key seed industry issues for researchers, administrators of national maize programs, and agricultural policy makers in developing countries, especially issues related to the appropriate roles for public and private organizations in maize seed industries in the developing world.Crop Production/Industries,

Bayesian Analysis of Simple Random Densities

A tractable nonparametric prior over densities is introduced which is closed under sampling and exhibits proper posterior asymptotics.Comment: 19 pages; 6 figure

Analysis of High-Order Element Types for Implicit Large Eddy Simulation

The use of high-order schemes continues to increase, with current methods becoming more robust and reliable. The resolution of complex turbulent flows using Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) can be computed more efficiently with high-order methods such as the Flux Reconstruction (FR) approach. We make use of the implicit form of LES, referred to as ILES, in which the numerical dissipation of the spatial scheme passively filters high-frequency modes and no subgrid scale turbulent model is explicitly implemented. Therefore, given the inherent three-dimensional behaviour of turbulent flows, it is important to understand the spectral characteristics of spatial discretizations in three dimensions. The dispersive and dissipative properties of hexahedra, prismatic and tetrahedral element types are compared using Fourier Analysis. This comparison is performed on a per degree of freedom basis to assess their suitability for ILES in terms of computational cost. We observe dispersion relations that display non-smooth behaviour for tetrahedral and prismatic elements, with the presence of jumps in the solution modes. Semilogarithmic plots of the numerical error are presented. We observe that the amount of numerical dissipation and dispersion added by hexahedral elements is the least, followed by prisms and finally tetrahedra. We validate our analysis comparing results obtained on computational domains with comparable computational cost against DNS data. Hexahedral elements have the best agreement with the reference data, followed by prismatic and finally tetrahedral elements, which is consistent with the spectral analysis

Sequential Allocation and Balancing Prognostic Factors in a Psychiatric Clinical Trial

In controlled clinical trials, each of several prognostic factors should be balanced across the trial arms. Traditional restricted randomization may be proved inadequate especially with small sample sizes. In psychiatric disorders such as obsessive compulsive disorder (OCD), small trials prevail. Therefore, procedures to minimize the chance of imbalance between treatment arms are advisable. This paper describes a minimization procedure specifically designed for a clinical trial that evaluates treatment efficacy for OCD patients. Aitchison's compositional distance was used to calculate vectors for each possibility of allocation in a covariate adaptive method. Two different procedures were designed to allocate patients in small blocks or sequentially one-by-one. Partial results of this allocation procedure as well as simulated ones are shown. In the clinical trial for which this procedure was developed, the balancing between treatment arms was achieved successfully. Simulations of results considering different arrival order of patients showed that most of the patients are allocated in a different treatment arm if arrival order is modified. Results show that a random factor is maintained with the random arrival order of patients. This specific procedure allows the use of a large number of prognostic factors for the allocation decision and was proved adequate for a psychiatric trial design