Numerical enclosures of the optimal cost of the Kantorovitch’s mass transportation problem

International audience

Genome-Wiide estimates of coancestry, in breeding and effective population size in the Spanish Holstein population

Estimates of effective population size in the Holstein cattle breed have usually been low despite the large number of animals that constitute this breed. Effective population size is inversely related to the rates at which coancestry and inbreeding increase and these rates have been high as a consequence of intense and accurate selection. Traditionally, coancestry and inbreeding coefficients have been calculated from pedigree data. However, the development of genome-wide single nucleotide polymorphisms has increased the interest of calculating these coefficients from molecular data in order to improve their accuracy. In this study, genomic estimates of coancestry, inbreeding and effective population size were obtained in the Spanish Holstein population and then compared with pedigree-based estimates. A total of 11,135 animals genotyped with the Illumina BovineSNP50 BeadChip were available for the study. After applying filtering criteria, the final genomic dataset included 36,693 autosomal SNPs and 10,569 animals. Pedigree data from those genotyped animals included 31,203 animals. These individuals represented only the last five generations in order to homogenise the amount of pedigree information across animals. Genomic estimates of coancestry and inbreeding were obtained from identity by descent segments (coancestry) or runs of homozygosity (inbreeding). The results indicate that the percentage of variance of pedigree-based coancestry estimates explained by genomic coancestry estimates was higher than that for inbreeding. Estimates of effective population size obtained from genome-wide and pedigree information were consistent and ranged from about 66 to 79. These low values emphasize the need of controlling the rate of increase of coancestry and inbreeding in Holstein selection programmes.

AN ENERGY BASED MINIMUM-TIME OPTIMAL CONTROL OF DC-DC CONVERTERS

Time-optimal response is an important and sometimes necessary characteristic of dynamic systems for specific applications. Power converters are widely used in different electrical systems and their dynamic response will affect the whole system. In many electrical systems like microgrids or voltage regulators which supplies sensitive loads fast dynamic response is a must. Minimum time is the fastest converter to compensate the step output reference or load change. Boost converters as one of the wildly used power converters in the electrical systems are aimed to be controlled in optimal time in this study. Linear controllers are not able to provide the optimal response for a boost converter however they are still useful and functional for other applications like reference tracking or stabilization. To obtain the fastest possible response from boost converters, a nonlinear control approach based on the total energy of the system is studied in this research. Total energy of the system considers as the basis for developing the presented method, since it is easy and accurate to measure besides that the total energy of the system represents the actual operating condition of the boost converter. The detailed model of a boost converter is simulated in MATLAB/Simulink to achieve the time optimal response of the boost converter by applying the developed method. The simulation results confirmed the ability of the presented method to secure the time optimal response of the boost converter under four different scenarios.

Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Innovation and Territorial Development: An Analysis of the Region of São José dos Campos - Brazil

This study aimed to identify and analyze the interrelations between companies, research centers, universities, government and other relevant players in the micro region of São José dos Campos, focusing on the creation and diffusion of innovations as a strategy for regional development. To this end, we made an interview with 12 regional players Involved in this process. It is hoped the results expand the knowledge of regional development in technologyoriented areas, as well as the dynamics of territorial development in the micro region studied. It is an academic contribution in developing strategies for expanding competitive regions through incentives for innovation and technology transfer.

Estimates of genetic parameters using RELM/BLUP for intrapopulational genetic breeding of Platonia insignis Mart.

The aim of this study was to estimate genetic parameters to support the selection of bacuri progenies for a first cycle of recurrent selection, using the REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure to estimate the variance components and genotypic values. Were evaluated twelve variables in a total of 210 fruits from 39 different seed trees, from a field trial with an experimental design of incomplete blocks with clonal replies among subplots. The three variables related with the fruit development (weight, diameter, length) showed strong correlation, and where fruit length showed higher heritability and potential to be used for indirect selection. Among the 39 progenies evaluated in this study, five present potential to compose the next cycle of recurrent selection, due they hold good selection differential either to agrotechnological variables as to development of bacuri fruit.

Bayesian estimates of genetic parameters for reproductive traits in Nellore cows raised on pasture in tropical regions.

2016

Development of a numerical platform for the modeling and optimal control of liquid metal flows

The main purpose of this work is to develop a numerical platform for the turbulence modeling and optimal control of liquid metal flows. Thanks to their interesting thermal properties, liquid metals are widely studied as coolants for heat transfer applications in the nuclear context. However, due to their low Prandtl numbers, the standard turbulence models commonly used for coolants as air or water are inadequate. Advanced turbulence models able to capture the anisotropy in the flow and heat transfer are then necessary. In this thesis, a new anisotropic four-parameter turbulence model is presented and validated. The proposed model is based on explicit algebraic models and solves four additional transport equations for dynamical and thermal turbulent variables. For the validation of the model, several flow configurations are considered for different Reynolds and Prandtl numbers, namely fully developed flows in a plane channel and cylindrical pipe, and forced and mixed convection in a backward-facing step geometry. Since buoyancy effects cannot be neglected in liquid metals-cooled fast reactors, the second aim of this work is to provide mathematical and numerical tools for the simulation and optimization of liquid metals in mixed and natural convection. Optimal control problems for turbulent buoyant flows are studied and analyzed with the Lagrange multipliers method. Numerical algorithms for optimal control problems are integrated into the numerical platform and several simulations are performed to show the robustness, consistency, and feasibility of the method.

2D PCA-Based localization for mobile robots in unstructured environments

In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.

Global alcohol exposure estimates by country, territory and region for 2005--a contribution to the Comparative Risk Assessment for the 2010 Global Burden of Disease Study.

AIMS: This study aimed to estimate the prevalence of life-time abstainers, former drinkers and current drinkers, adult per-capita consumption of alcohol and pattern of drinking scores, by country and Global Burden of Disease region for 2005, and to forecast these indicators for 2010. DESIGN: Statistical modelling based on survey data and routine statistics. SETTING AND PARTICIPANTS: A total of 241 countries and territories. MEASUREMENTS: Per-capita consumption data were obtained with the help of the World Health Organization's Global Information System on Alcohol and Health. Drinking status data were obtained from Gender, Alcohol and Culture: An International Study, the STEPwise approach to Surveillance study, the World Health Survey/Multi-Country Study and other surveys. Consumption and drinking status data were triangulated to estimate alcohol consumption across multiple categories. FINDINGS: In 2005 adult per-capita annual consumption of alcohol was 6.1 litres, with 1.7 litres stemming from unrecorded consumption; 17.1 litres of alcohol were consumed per drinker, 45.8% of all adults were life-time abstainers, 13.6% were former drinkers and 40.6% were current drinkers. Life-time abstention was most prevalent in North Africa/Middle East and South Asia. Eastern Europe and Southern sub-Saharan Africa had the most detrimental pattern of drinking scores, while drinkers in Europe (Eastern and Central) and sub-Saharan Africa (Southern and West) consumed the most alcohol. CONCLUSIONS: Just over 40% of the world's adult population consumes alcohol and the average consumption per drinker is 17.1 litres per year. However, the prevalence of abstention, level of alcohol consumption and patterns of drinking vary widely across regions of the world.

Phenotypic stability and genetic gains in six-year girth growth of Hevea clones

Rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell. Arg.] budgrafts of seven clones were evaluated on five contrasting sites in the plateau region of the São Paulo State, Brazil. The objective of this work was to study the phenotypic stability for girth growth. The experimental design was a randomized block design with three replications and seven treatments. Analysis of variance of girth at six-year plant growth indicated a highly significant clone x site interaction. Only linear sites and clone x site components of clone x year interaction were significant, indicating that the performance of clones over sites for this trait could be predicted. The clones GT 1 and PB 235 showed the greatest stability in relation to girth growth, with foreseen responses to change, introduced in the sites. The clones PB 235 and IAN 873 showed significative difference in relation to regression coefficient, representing clones with specific adaptability on favorable and unfavorable sites respectively. The clone GT 1 became the most promissory one in the study of stability and adaptability even showing low girth growth. Expected genetic gains from planting sites, along with estimates of clonal variance and repeatability of clonal means are generally greatest or close to the greatest when selection is done at the same site.

Mean motion resonances and the stability of a circumbinary disk in a triple stellar system

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of a Human VPF/VEGF 3′ Untranslated Region Mediating Hypoxia-induced mRNA Stability

Hypoxia is a prominent feature of malignant tumors that are characterized by angiogenesis and vascular hyperpermeability. Vascular permeability factor/vascular endothelial growth factor (VPF/VEGF) has been shown to be up-regulated in the vicinity of necrotic tumor areas, and hypoxia potently induces VPF/VEGF expression in several tumor cell lines in vitro. Here we report that hypoxia-induced VPF/VEGF expression is mediated by increased transcription and mRNA stability in human M21 melanoma cells. RNA-binding/electrophoretic mobility shift assays identified a single 125-bp AU-rich element in the 3′ untranslated region that formed hypoxia-inducible RNA-protein complexes. Hypoxia-induced expression of chimeric luciferase reporter constructs containing this 125-bp AU-rich hypoxia stability region were significantly higher than constructs containing an adjacent 3′ untranslated region element without RNA-binding activity. Using UV-cross-linking studies, we have identified a series of hypoxia-induced proteins of 90/88 kDa, 72 kDa, 60 kDa, 56 kDa, and 46 kDa that bound to the hypoxia stability region element. The 90/88-kDa and 60-kDa species were specifically competed by excess hypoxia stability region RNA. Thus, increased VPF/VEGF mRNA stability induced by hypoxia is mediated, at least in part, by specific interactions between a defined mRNA stability sequence in the 3′ untranslated region and distinct mRNA-binding proteins in human tumor cells.

Stability of an Optimal Schedule for a Job-Shop Problem with Two Jobs

The usual assumption that the processing times of the operations are known in advance is the strictest one in scheduling theory. This assumption essentially restricts practical aspects of deterministic scheduling theory since it is not valid for the most processes arising in practice. The paper is devoted to a stability analysis of an optimal schedule, which may help to extend the significance of scheduling theory for decision-making in the real-world applications. The term stability is generally used for the phase of an algorithm, at which an optimal solution of a problem has already been found, and additional calculations are performed in order to study how solution optimality depends on variation of the numerical input data.

Neurons in the hilus region of the rat hippocampus are depleted in number by exposure to alcohol during early postnatal life

We have previously shown that exposing rats to a relatively high dose of ethanol during early postnatal life resulted in a deficit in spatial learning ability. This ability is controlled, at least in part, by the hippocampal formation. The purpose of the present study was to determine whether exposure of rats to ethanol during early postnatal life affected the number of specific neurons in the hippocampus. Wistar rats were exposed to a relatively high daily dose of ethanol between postnatal days 10 and 15 by placing them for 3 h each day in a chamber containing ethanol vapor. The blood ethanol concentration was about 430 mg/dl at the end of the exposure period. Groups of ethanol-treated (ET) rats, separation controls (SC), and mother-reared controls (MRC) were anesthetized and killed at 16 days of age by perfusion with phosphate-buffered glutaraldehyde (2.5%). The Cavalieri principle was used to determine the volume of various subdivisions of the hippocampal formation (CA1, CA2+CA3, hilus, and granule cell layer), and the physical disector method was used to estimate the numerical densities of neurons within each subdivision. The total number of neurons was calculated by multiplying estimates of the numerical density with the volume. There were, on average, about 441,000 granule cells in the granule cell layer and 153,000 to 177,000 pyramidal cells in both the CA1 and CA2+CA3 regions in all three treatment groups. In the hilus region, ET rats had about 27,000 neuronal cells. This was significantly fewer than the average of 38,000 such neurons estimated to be present in both MRC and SC animals. Thus, neurons in the hilus region may be particularly vulnerable to the effects of a high dose of ethanol exposure during early postnatal life. (C) 2000 Wiley-Liss, Inc.