Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.

Discursos e a construção do "real": um estudo do processo de formação e institucionalização do campo da biotecnologia

Comprehension of the processes of formation of new organizational fields is the main objective that stimulated the theoretical reflection and empirical research that I present in this paper. My intention here is to uphold the potential for the application of seemingly dichotomous perspectives in terms of the objectivity/subjectivity dimension in the comprehension of the objective in question. The contribution of Foucault, with his concept of discourse, is linked to the proposal of critical constructivism represented by Latour and studies of science and technology. Juxtaposing these perspectives, I examined the dynamics of the biotechnological field on the basis of the dialectic of movements of demarcation/circularity, which is basically a simultaneous movement of (dis)construction of the boundaries of a field. The dialectic of demarcation/circularity is made up of the set of relations established between heterogeneous elements ¿ institutions, economic and social processes, behavioral patterns, systems of norms, techniques, types of classification, forms of characterization, in other words it finds ways of emerging in the course of discursive formations. This theoretical proposal ¿ which incorporates an overlooked dimension in institutional analysis, especially in organization studies (power) ¿ has the advantage of contributing to enhancing comprehension of the dynamics of institutionalization. By proposing that the institutional processes arise within discursive fields, the argument put forward is that such processes contribute to the productivity of the power relations in these fields. In empirical terms, I conducted a descriptive and exploratory research directed at the biotechnology sector. The research was based on a historical perspective, since the analysis spans the period from the origins of genetic science (beginning of the 20th century) through to recent developments in biotechnology in the USA (beginning of the 21st century). The USA was chosen as the locus of research, principally due to the fact that structuring of the field of biotechnology originated in that country, subsequently spreading to other countries around the world. Starting from this theoretical and methodological framework, three discursive formations are highlighted: organization, information and network. Each of the discursive formations is characterized by a dominant set of discourses that prepare the ground for the appearance and (trans)formation of the focus-objects under analysis. In this process, organizations appear in at least two ways: as boundary-organizations ¿ which are important for understanding the movement of the approximation of different discursive domains ¿ and as new organizations, which accompany the (trans)formation of new fields, whereby prevailing discourses materialize at a given historical moment and contribute to breathe life into new discourses, which in turn spark off new power relations. Among the conclusions of this work, I would highlight the following: questioning the 'organizational' dimension of the fields; the relationship revealed not only between the discourses and the institutionalized practices, but also with the process of construction of legitimacy; and the redefinition of the concept of organizations, based on new conceptions relating to the limits of the topic, the objectivity/subjectivity, and space/time dichotomy.

Inexpensive solution for real-time video and image stitching

Image stitching is the process of joining several images to obtain a bigger view of a scene. It is used, for example, in tourism to transmit to the viewer the sensation of being in another place. I am presenting an inexpensive solution for automatic real time video and image stitching with two web cameras as the video/image sources. The proposed solution relies on the usage of several markers in the scene as reference points for the stitching algorithm. The implemented algorithm is divided in four main steps, the marker detection, camera pose determination (in reference to the markers), video/image size and 3d transformation, and image translation. Wii remote controllers are used to support several steps in the process. The built‐in IR camera provides clean marker detection, which facilitates the camera pose determination. The only restriction in the algorithm is that markers have to be in the field of view when capturing the scene. Several tests where made to evaluate the final algorithm. The algorithm is able to perform video stitching with a frame rate between 8 and 13 fps. The joining of the two videos/images is good with minor misalignments in objects at the same depth of the marker,misalignments in the background and foreground are bigger. The capture process is simple enough so anyone can perform a stitching with a very short explanation. Although real‐time video stitching can be achieved by this affordable approach, there are few shortcomings in current version. For example, contrast inconsistency along the stitching line could be reduced by applying a color correction algorithm to every source videos. In addition, the misalignments in stitched images due to camera lens distortion could be eased by optical correction algorithm. The work was developed in Apple’s Quartz Composer, a visual programming environment. A library of extended functions was developed using Xcode tools also from Apple.

Comparative validation using quantitative real-time PCR (qPCR) and conventional PCR of bovine semen centrifuged in continuous density gradient

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Phenotypic and genetic parameters compared during repeated measures of longissimus muscle area and subcutaneous fat thickness in Nelore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic and environmental factors affecting ultrasound measures of longissimus muscle area and backfat thickness in Nelore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Group Sequential Communication (GSC): Especificação e Análise de Desempenho de umMecanismo de Comunicação de Tempo Real Compatível ao Padrão IEEE 802.11/11e Aplicado à Automação Industrial

This thesis proposes the specification and performance analysis of a real-time communication mechanism for IEEE 802.11/11e standard. This approach is called Group Sequential Communication (GSC). The GSC has a better performance for dealing with small data packets when compared to the HCCA mechanism by adopting a decentralized medium access control using a publish/subscribe communication scheme. The main objective of the thesis is the HCCA overhead reduction of the Polling, ACK and QoS Null frames exchanged between the Hybrid Coordinator and the polled stations. The GSC eliminates the polling scheme used by HCCA scheduling algorithm by using a Virtual Token Passing procedure among members of the real-time group to whom a high-priority and sequential access to communication medium is granted. In order to improve the reliability of the mechanism proposed into a noisy channel, it is presented an error recovery scheme called second chance algorithm. This scheme is based on block acknowledgment strategy where there is a possibility of retransmitting when missing real-time messages. Thus, the GSC mechanism maintains the real-time traffic across many IEEE 802.11/11e devices, optimized bandwidth usage and minimal delay variation for data packets in the wireless network. For validation purpose of the communication scheme, the GSC and HCCA mechanisms have been implemented in network simulation software developed in C/C++ and their performance results were compared. The experiments show the efficiency of the GSC mechanism, especially in industrial communication scenarios.