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Parent Population (parent + population)
Selected AbstractsFast computation evolutionary programming algorithm for the economic dispatch problemEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 1 2006P. Somasundaram Abstract This paper essentially aims to propose a new EP based algorithm for solving the ED problem. The ED problem is solved using EP with system lambda as decision variable and power mismatch as fitness function. The algorithm is made fast through judicious modifications in initialization of the parent population, offspring generation and selection of the normal distribution curve. The proposed modifications reduce the search region progressively and generate only effective offsprings. The proposed algorithm is tested on a number of sample systems with quadratic cost function and also on a 10-unit system with piecewise quadratic cost function. The computational results reveal that the proposed algorithm has an excellent convergence characteristic and is superior to other EP based methods in many respects. Copyright © 2005 John Wiley & Sons, Ltd. [source] AN EXACT FORM OF THE BREEDER'S EQUATION FOR THE EVOLUTION OF A QUANTITATIVE TRAIT UNDER NATURAL SELECTIONEVOLUTION, Issue 11 2005John S. Heywood Abstract Starting with the Price equation, I show that the total evolutionary change in mean phenotype that occurs in the presence of fitness variation can be partitioned exactly into five components representing logically distinct processes. One component is the linear response to selection, as represented by the breeder's equation of quantitative genetics, but with heritability defined as the linear regression coefficient of mean offspring phenotype on parent phenotype. The other components are identified as constitutive transmission bias, two types of induced transmission bias, and a spurious response to selection caused by a covariance between parental fitness and offspring phenotype that cannot be predicted from parental phenotypes. The partitioning can be accomplished in two ways, one with heritability measured before (in the absence of) selection, and the other with heritability measured after (in the presence of) selection. Measuring heritability after selection, though unconventional, yields a representation for the linear response to selection that is most consistent with Darwinian evolution by natural selection because the response to selection is determined by the reproductive features of the selected group, not of the parent population as a whole. The analysis of an explicitly Mendelian model shows that the relative contributions of the five terms to the total evolutionary change depends on the level of organization (gene, individual, or mated pair) at which the parent population is divided into phenotypes, with each frame of reference providing unique insight. It is shown that all five components of phenotypic evolution will generally have nonzero values as a result of various combinations of the normal features of Mendelian populations, including biparental sex, allelic dominance, inbreeding, epistasis, linkage disequilibrium, and environmental covariances between traits. Additive genetic variance can be a poor predictor of the adaptive response to selection in these models. The narrow-sense heritability s,2A/s,2P should be viewed as an approximation to the offspring-parent linear regression rather than the other way around. [source] Population Synthesis: Comparing the Major Techniques Using a Small, Complete Population of FirmsGEOGRAPHICAL ANALYSIS, Issue 2 2009Justin Ryan Recently, disaggregate modeling efforts that rely on microdata have received wide attention by scholars and practitioners. Synthetic population techniques have been devised and are used as a viable alternative to the collection of microdata that normally are inaccessible because of confidentiality concerns or incomplete because of high acquisition costs. The two most widely discussed synthetic techniques are the synthetic reconstruction method (IPFSR), which makes use of iterative proportional fitting (IPF) techniques, and the combinatorial optimization (CO) method. Both methods are described in this article and then evaluated in terms of their ability to recreate a known population of firms, using limited data extracted from the parent population of the firms. Testing a synthetic population against a known population is seldom done, because obtaining an entire population usually is too difficult. The case presented here uses a small, complete population of firms for the City of Hamilton, Ontario, for the year 1990; firm attributes compiled are number of employees, 3-digit standard industrial classification, and geographic location. Results are summarized for experiments based upon various combinations of sample size and tabulation detail designed to maximize the accuracy of resulting synthetic populations while holding input data costs to a minimum. The output from both methods indicates that increases in sample size and tabulation detail result in higher quality synthetic populations, although the quality of the generated population is more sensitive to increases in tabular detail. Finally, most tests conducted with the created synthetic populations suggest that the CO method is superior to the IPFSR method. Los modelos desagregados basados en micro data han recibido la atención relativamente reciente de los círculos académicos y de aplicación. La colección de dicha data es una tarea difícil por cuestiones de accesibilidad, confidencialidad, datos incompletos o altos costos de adquisición. Por esta razón se han creado indicadores sintéticos como a alternativa a la recolección directa de datos. Los dos indicadores sintéticos mas discutidos/conocidos son el método de Reconstrucción Sintética (Sytnthetic Reconstruction method) (IPFSR) que hace uso de técnicas de Ajuste Proporcional Iterativo (IPF); y el método Optimización Combinatoria (CO). Ambos métodos son descritos en este artículo y luego evaluados en base a su habilidad de recrear una población de empresas ya conocidas o preestablecidas. Contrastar una población sintética versus una población conocida es una operación poco frecuente porque la obtención de una población entera es por lo general bastante difícil. El caso presentado en este estudio utiliza una población pequeña y completa de empresas en la ciudad de Hamilton, Ontario (Canadá) para el año 1990. Las variables recopiladas son el número de empleados, SIC (código estandarizado de clasificación industrial), y ubicación geográfica. Los resultados que se reportan en el presente estudio son producto de varios experimentos basados en varias combinaciones del tamaño de la muestra, y del detalle en la tabulación diseñados, los mismos que fueron diseñados para maximizar la exactitud de las poblaciones sintéticas calculadas y al mismo tiempo minimizar los costos de datos necesarios. Los resultados obtenidos por ambos métodos indica que los incrementos en el tamaño de la muestra y en el detalle de la tabulación resultan en un estimado de poblaciones mejor, aunque este estimado es particularmente sensible a incrementos en el detalle de las tabulaciones. Finalmente, la mayoría de pruebas realizadas con las poblaciones sintéticas generadas para este estudio sugieren que el método CO es superior al método IPFSR. [source] Methods for metabolic evaluation of prostate cancer cells using proton and 13C HR-MAS spectroscopy and [3- 13C] pyruvate as a metabolic substrateMAGNETIC RESONANCE IN MEDICINE, Issue 5 2009Yakir S. Levin Abstract Prostate cancer has been shown to undergo unique metabolic changes associated with neoplastic transformation, with associated changes in citrate, alanine, and lactate concentrations. 13C high resolution-magic angle spinning (HR-MAS) spectroscopy provides an opportunity to simultaneously investigate the metabolic pathways implicated in these changes by using 13C-labeled substrates as metabolic probes. In this work, a method to reproducibly interrogate metabolism in prostate cancer cells in primary culture was developed using HR-MAS spectroscopy. Optimization of cell culture protocols, labeling parameters, harvesting, storage, and transfer was performed. Using [3- 13C] pyruvate as a metabolic probe, 1H and 13C HR-MAS spectroscopy was used to quantify the net amount and fractional enrichment of several labeled metabolites that evolved in multiple cell samples from each of five different prostate cancers. Average enrichment across all cancers was 32.4 ± 5.4% for [3- 13C] alanine, 24.5 ± 5.4% for [4- 13C] glutamate, 9.1 ± 2.5% for [3- 13C] glutamate, 25.2 ± 5.7% for [3- 13C] aspartate, and 4.2 ± 1.0% for [3- 13C] lactate. Cell samples from the same parent population demonstrated reproducible fractional enrichments of alanine, glutamate, and aspartate to within 12%, 10%, and 10%, respectively. Furthermore, the cells produced a significant amount of [4- 13C] glutamate, which supports the bioenergetic theory for prostate cancer. These methods will allow further characterization of metabolic properties of prostate cancer cells in the future. Magn Reson Med, 2009. © 2009 Wiley-Liss, Inc. [source] Genetic analysis of larval survival and larval growth of two populations of Leptinotarsa decemlineata on tomatoENTOMOLOGIA EXPERIMENTALIS ET APPLICATA, Issue 2 2001Wenhua Lu Abstract The genetics of adaptation to tomato in Leptinotarsa decemlineata (Say) were investigated in reciprocal F1, F2, and backcross populations generated from crosses between beetles from a tomato adapted population and from a population that was poorly adapted to tomato. Larvae from the parent and test populations were reared on tomato for four days, after which survivorship and larval weights were recorded. Most results indicate that differences in larval growth and survival on tomato between the parent populations are largely determined by autosomal, polygenic mechanisms, the inheritance of which involves a significant dominance component. However, results from F2 crosses are not consistent with this conclusion. A significant difference in larval weights, but not in survival, between reciprocal F1 populations in an analysis of combined data from four separate experiments suggests that maternal cytoplasmic effects may contribute to differences in larval performance on tomato between the adapted and unadapted populations. The unusual results obtained from F2 crosses in this study are not atypical of results from previous studies of the genetics of adaptation to host plants by the Colorado potato beetle. Host plant adaptation by Colorado potato beetles may therefore involve unusual genetic mechanisms that are not easily assessed by classical Mendelian analysis. [source] | ||||||||||