Genetic selection strategies: computer modeling

There are four primary factors to consider in genetic selection strategies: 1) accuracy of selection, 2) selection intensity, 3) effective population size, and 4) mating system. Current theory indicates that optimum response to selection is achieved by maximizing the first three factors and using a mating systems that allows optimization of reproductive characteristics in dam lines and production characteristics in sire lines. However, with limited resources, compromises among the first three factors are needed. Simulations are useful for examining those compromises. Unrealistic simplifying assumptions are necessary for analytic theoretical results and thus do not address real world breeding problems. Using simulations, the relationship between selection accuracy, which is increased by use of family selection indices or Best Linear Unbiased Prediction (BLUP), and response to selection was examined. Results show that those procedures place a great restriction on effective population size, which offsets most of their advantage, i.e., there is too little emphasis on effective population size. A revision of the methodology and a reappraisal of the results of selection theory for optimization of genetic response is required. Another relationship that is of fundamental importance in breeding programs is that between selection intensity and effective population size. Analytical results for the additive case have been developed but have never been extended to heterotic traits. A gene level simulation program was developed to examine that relationship. Results show that the optimal selection strategy depends on the trait being selected. For additive traits and in the short term (20 generations), one should maximize selection intensity. For heterotic traits, an intermediate proportion (25% of each sex) gives optimal response. In all breeding strategies, primary attention must be given to the rate of inbreeding, which is increased by increasing either accuracy of selection or selection intensity. Inbreeding reduces response to selection in two ways. First, for both additive and nonadditive traits, inbreeding is a measure of the amount of random genetic drift that has occurred. Genetic drift causes loss of favorable alleles. Once lost, those alleles can never be recovered and thus genetic drift lowers the selection limit. Second, for heterotic traits, inbreeding results in a depression of the mean caused by directional dominance.     

Bronchoalveolar lavage. Quantitation of intraalveolar fluid?

A precise calculation of the amount of intraalveolar fluid is the basis of a quantitative analysis of intraalveolar compounds. Different approaches have been made to cover this important problem. Here, we report a comparative study with five markers: 99mTc-DTPA, 51Cr-EDTA, inulin, urea, and methylene blue in animal experiments as well as in human experiments. The marker substances were added to the lavage fluid, and the "dilution" of the markers, i.e., the alveolar fluid, was calculated. The results showed that in animals with healthy lungs the tracer methods are able to calculate amounts of intraalveolar fluid that are comparable to morphologic findings. In animals as well as in humans, methylene blue and inulin were shown to be useless in determining alveolar fluid volume compared with the tracer methods. In humans, the calculations with the urea method and with Tc-DTPA were in the same magnitude, but there was no individual correlation. We conclude that, at present, the methods to quantitate alveolar fluid volume lack precision and add nothing to a deeper understanding of alveolar biology.     

Application-Oriented Low-Side Gate Drivers

This paper presents three types of low-side gate drivers to drive n-channel power metal-oxide-semiconductor field-effect transistors (MOSFETs). Most important of all, each gate driver has a single positive-voltage source fed, and any one of these three types is used according to applications. In addition, the main purpose of the proposed gate drivers is to reduce the losses created from power MOSFETs. In this paper, the detailed operating principles of the proposed gate drivers are illustrated, along with some experimental results provided to verify the feasibility of the proposed topologies.     

Hot-carrier degradation of submicrometer p-MOSFETs withthermal/LPCVD composite oxide

It is shown that while gate oxides containing thermal/LPCVD composite oxide have lower defect densities than gates using only thermal oxides, they are more susceptible to hot-carrier degradation. The hot-carrier-induced degradation of composite oxides is worse in p-channel MOSFETs than in n-channel MOSFETs. This sensitivity of p-channel MOSFETs is caused by higher electron trapping levels in LPCVD oxides. For 150-Å gate technology, the hot-carrier-degradation resistance of thermal/LPCVD composite gate oxides with a 70-Å or thicker thermal oxide layer approaches that of high-quality pure thermal oxide     

An efficient algorithm for superresolution in medium field imaging

In this paper, we study the problem of reconstruction of a high-resolution (HR) image from several blurred low-resolution (LR) image frames in medium field. The image frames consist of blurred, decimated, and noisy versions of a HR image. The HR image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a HR image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore HR images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach. This research was conducted with support from the Army Research Office Grant DAAD 19-03-1-0261 and the National Science Foundation Grant CCF-0429481. Research supported in part by RGC Grant Nos. 7130/02P, 7046/03P, 7035/04P and 7035/04P and FRG/04-05/II-51.     

On the robustness of parameter estimation of superimposed signalsby dynamic programming

We analyze a recently proposed dynamic programming algorithm (REDP) for maximum likelihood (ML) parameter estimation of superimposed signals in noise. We show that it degrades gracefully with deviations from the key assumption of a limited interaction signal model (LISMO), providing exact estimates when the LISMO assumption holds exactly. In particular, we show that the deviations of the REDP estimates from the exact ML are continuous in the deviation of the signal model from the LISMO assumption. These deviations of the REDP estimates from the MLE are further quantified by a comparison to an ML algorithm with an exhaustive multidimensional search on a lattice in parameter space. We derive an explicit expression for the lattice spacing for which the two algorithms have equivalent optimization performance, which can be used to assess the robustness of REDP to deviations from the LISMO assumption. The values of this equivalent lattice spacing are found to be small for a classical example of superimposed complex exponentials in noise, confirming the robustness of REDP for this application