Algoritmos construtivos para treino de redes neuronais b-spline

Dissertação de mest. em Engenharia de Sistemas e Computação - Área de Sistemas de Controlo, Faculdade de Ciências e Tecnologia, Univ.do Algarve, 2001

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Random regression models using different functions to model milk flow in dairy cows

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

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Otimização de forma aplicando B-splines sob critério integral de tensões

This work proposes a computational methodology to solve problems of optimization in structural design. The application develops, implements and integrates methods for structural analysis, geometric modeling, design sensitivity analysis and optimization. So, the optimum design problem is particularized for plane stress case, with the objective to minimize the structural mass subject to a stress criterion. Notice that, these constraints must be evaluated at a series of discrete points, whose distribution should be dense enough in order to minimize the chance of any significant constraint violation between specified points. Therefore, the local stress constraints are transformed into a global stress measure reducing the computational cost in deriving the optimal shape design. The problem is approximated by Finite Element Method using Lagrangian triangular elements with six nodes, and use a automatic mesh generation with a mesh quality criterion of geometric element. The geometric modeling, i.e., the contour is defined by parametric curves of type B-splines, these curves hold suitable characteristics to implement the Shape Optimization Method, that uses the key points like design variables to determine the solution of minimum problem. A reliable tool for design sensitivity analysis is a prerequisite for performing interactive structural design, synthesis and optimization. General expressions for design sensitivity analysis are derived with respect to key points of B-splines. The method of design sensitivity analysis used is the adjoin approach and the analytical method. The formulation of the optimization problem applies the Augmented Lagrangian Method, which convert an optimization problem constrained problem in an unconstrained. The solution of the Augmented Lagrangian function is achieved by determining the analysis of sensitivity. Therefore, the optimization problem reduces to the solution of a sequence of problems with lateral limits constraints, which is solved by the Memoryless Quasi-Newton Method It is demonstrated by several examples that this new approach of analytical design sensitivity analysis of integrated shape design optimization with a global stress criterion purpose is computationally efficient

Inhibin B and ovarian function after total abdominal hysterectomy in women of reproductive age

The aim of this prospective study was to assess ovarian function using clinical and endocrine parameters in women of reproductive age who underwent total abdominal hysterectomy. Sixty-one women, aged ≤ 40 years, were allocated into two groups: group 1, consisting of 31 patients who had hysterectomy, and group 2, consisting of 30 normal women. Inclusion criteria were normal ovarian function at baseline, normal body weight, no hormonal diseases and basal follicle stimulating hormone (FSH) level of < 15 mIU/ml. FSH, luteinizing hormone (LH), estradiol and inhibin B levels as well as maturation value (MV) were measured by vaginal cytology on three occasions: baseline, and 6 and 12 months after hysterectomy. Analysis of variance, the Friedman test, Mann-Whitney test and t-test statistics were employed to compare the two groups. At baseline the groups were homogeneous. At months 6 and 12, hysterectomized women showed decreased median values of inhibin B, increased median values of estradiol (p < 0.05), unchanged median values of FSH and LH, and decreased median values of MV (p < 0.05). In the hysterectomy group, 12.9% (4/31) of the patients had FSH levels of > 40 mIU/ml, estradiol of < 20 pg/ml and inhibin B of < 5 ng/ml, compatible with ovarian failure. In the control group, all the parameters studied remained unchanged. These results suggest that total abdominal hysterectomy accelerates the decline in ovarian function in women of reproductive age.

Urban air pollution and chronic obstructive pulmonary disease-related emergency department visits

Background: Patients with chronic obstructive pulmonary disease (COPD) can have recurrent disease exacerbations triggered by several factors, including air pollution. Visits to the emergency respiratory department can be a direct result of short-term exposure to air pollution. The aim of this study was to investigate the relationship between the daily number of COPD emergency department visits and the daily environmental air concentrations of PM(10), SO(2), NO(2), CO and O(3) in the City of Sao Paulo, Brazil. Methods: The sample data were collected between 2001 and 2003 and are categorised by gender and age. Generalised linear Poisson regression models were adopted to control for both short-and long-term seasonal changes as well as for temperature and relative humidity. The non-linear dependencies were controlled using a natural cubic spline function. Third-degree polynomial distributed lag models were adopted to estimate both lag structures and the cumulative effects of air pollutants. Results: PM(10) and SO(2) readings showed both acute and lagged effects on COPD emergency department visits. Interquartile range increases in their concentration (28.3 mg/m(3) and 7.8 mg/m(3), respectively) were associated with a cumulative 6-day increase of 19% and 16% in COPD admissions, respectively. An effect on women was observed at lag 0, and among the elderly the lag period was noted to be longer. Increases in CO concentration showed impacts in the female and elderly groups. NO(2) and O(3) presented mild effects on the elderly and in women, respectively. Conclusion: These results indicate that air pollution affects health in a gender-and age-specific manner and should be considered a relevant risk factor that exacerbates COPD in urban environments.

Cubic spline population density functions and subcentre delimitation. The case of Barcelona

The presence of subcentres cannot be captured by an exponential function. Cubic spline functions seem more appropriate to depict the polycentricity pattern of modern urban systems. Using data from Barcelona Metropolitan Region, two possible population subcentre delimitation procedures are discussed. One, taking an estimated derivative equal to zero, the other, a density gradient equal to zero. It is argued that, in using a cubic spline function, a delimitation strategy based on derivatives is more appropriate than one based on gradients because the estimated density can be negative in sections with very low densities and few observations, leading to sudden changes in estimated gradients. It is also argued that using as a criteria for subcentre delimitation a second derivative with value zero allow us to capture a more restricted subcentre area than using as a criteria a first derivative zero. This methodology can also be used for intermediate ring delimitation.

The C76R transmembrane activator and calcium modulator cyclophilin ligand interactor mutation disrupts antibody production and B-cell homeostasis in heterozygous and homozygous mice.

BackgroundMutations in TNFRSF13B, the gene encoding transmembrane activator and calcium modulator cyclophilin ligand interactor (TACI), are found in 10% of patients with common variable immunodeficiency. However, the most commonly detected mutation is the heterozygous change C104R, which is also found in 0.5% to 1% of healthy subjects. The contribution of the C104R mutation to the B-cell defects observed in patients with common variable immunodeficiency therefore remains unclear.ObjectiveWe sought to define the functional consequences of the C104R mutation on B-cell function.MethodsWe performed in vitro studies of TACI C104R expression and signaling. A knock-in mouse with the equivalent mutation murine TACI (mTACI) C76R was generated as a physiologically relevant model of human disease. We examined homozygous and heterozygous C76R mutant mice alongside wild-type littermates and studied specific B-cell lineages and antibody responses to T cell-independent and T cell-dependent challenge.ResultsC104R expression and ligand binding are significantly diminished when the mutant protein is expressed in 293T cells or in patients' cell lines. This leads to defective nuclear factor κB activation, which is proportionally restored by reintroduction of wild-type TACI. Mice heterozygous and homozygous for mTACI C76R exhibit significant B-cell dysfunction with splenomegaly, marginal zone B-cell expansion, diminished immunoglobulin production and serological responses to T cell-independent antigen, and abnormal immunoglobulin synthesis.ConclusionsThese data show that the C104R mutation and its murine equivalent, C76R, can significantly disrupt TACI function, probably through haploinsufficiency. Furthermore, the heterozygous C76R mutation alone is sufficient to disturb B-cell function with lymphoproliferation and immunoglobulin production defects.

Complex interplay between LPS and IL-10 in dendritic cells: uncoupling of inflammatory chemokine receptors and positive effects on B cell chemokines

Abstract: Protective immune responses against pathogen invasion and transformed cells requires the coordinated action of distinct leukocyte subsets and soluble factors, overall termed immunological network. Among antigen-presenting cells (APC), a crucial role is played by dendritic cells (DC), which initiate, amplify and determine the outcome of the immune response. Micro-environmental conditions profoundly influence DC in such ways that the resulting immune response ranges from successful immune stimulation to abortive response or immune suppression. For instance, the presence in the milieu of anti-inflammatory cytokine interleukin-10 (IL-10) reverts most of the effects mediated on DC by even strong pro-inflammatory agents such as bacterial Lipopolysaccharide (LPS), in terms of differentiation, activation and functions. In an environment containing both LPS and IL-10, uncoupling of receptors for inflammatory chemokines already occurs after a few hours and in a reversible manner on DC, allowing scavenging of chemokines and, consequently, attenuation of the inflammatory process which could be deleterious to the organism. By studying the effects on DC of concomitant stimulation by LPS and IL-10 from the gene expression point of view, we were able to define four distinct transcriptional programs: A. the inhibition of inflammation and immunity, B. the regulation of tissue remodeling, C. the tuning of cytokine/growth factor receptors and G protein-coupled receptors, D. the stimulation of B cell function and lymphoid tissue neogenesis. Among the latter genes, we further demonstrated that IL-10 synergizes with Toll-like receptor ligands for the production of functionally active B cell attracting chemokine CXCL13. Our data provide evidence that the combined exposure of APC to LPS and IL-10, via the production of CXCL13, involves humoral immunity by attracting antibody-producing cells. It is well known that the persistent release of CXCL13 leads to the development of ectopic lymphoid tissue aggregates and production of high levels of antibodies, thus favoring the induction of auto-immunity. Our findings suggest that the IL-10 produced in chronic inflammatory conditions may promote lymphoid tissue neogenesis through increased release of CXCL13. IL-10 is an anti-inflammatory cytokine inhibiting cellular-mediated TH 1-polarized immune responses. In this study we demonstrate that IL- 10 strongly supports the development of humoral immunity. IL-10 and CXCL13 can thus be targets for specific therapies in auto-immune diseases.

Validation des modèles statistiques tenant compte des variables dépendantes du temps en prévention primaire des maladies cérébrovasculaires

L’intérêt principal de cette recherche porte sur la validation d’une méthode statistique en pharmaco-épidémiologie. Plus précisément, nous allons comparer les résultats d’une étude précédente réalisée avec un devis cas-témoins niché dans la cohorte utilisé pour tenir compte de l’exposition moyenne au traitement : – aux résultats obtenus dans un devis cohorte, en utilisant la variable exposition variant dans le temps, sans faire d’ajustement pour le temps passé depuis l’exposition ; – aux résultats obtenus en utilisant l’exposition cumulative pondérée par le passé récent ; – aux résultats obtenus selon la méthode bayésienne. Les covariables seront estimées par l’approche classique ainsi qu’en utilisant l’approche non paramétrique bayésienne. Pour la deuxième le moyennage bayésien des modèles sera utilisé pour modéliser l’incertitude face au choix des modèles. La technique utilisée dans l’approche bayésienne a été proposée en 1997 mais selon notre connaissance elle n’a pas été utilisée avec une variable dépendante du temps. Afin de modéliser l’effet cumulatif de l’exposition variant dans le temps, dans l’approche classique la fonction assignant les poids selon le passé récent sera estimée en utilisant des splines de régression. Afin de pouvoir comparer les résultats avec une étude précédemment réalisée, une cohorte de personnes ayant un diagnostique d’hypertension sera construite en utilisant les bases des données de la RAMQ et de Med-Echo. Le modèle de Cox incluant deux variables qui varient dans le temps sera utilisé. Les variables qui varient dans le temps considérées dans ce mémoire sont iv la variable dépendante (premier évènement cérébrovasculaire) et une des variables indépendantes, notamment l’exposition

Neurokinin-B transcription in erythroid cells - Direct activation by the hematopoietic transcription factor GATA-1

The GATA family of transcription factors establishes genetic networks that control developmental processes including hematopoiesis, vasculogenesis, and cardiogenesis. We found that GATA-1 strongly activates transcription of the Tac-2 gene, which encodes proneurokinin-B, a precursor of neurokinin-B (NK-B). Neurokinins function through G protein-coupled transmembrane receptors to mediate diverse physiological responses including pain perception and the control of vascular tone. Whereas an elevated level of NK-B was implicated in pregnancy-associated pre-eclampsia ( Page, N. M., Woods, R. J., Gardiner, S. M., Lomthaisong, K., Gladwell, R. T., Butlin, D. J., Manyonda, I. T., and Lowry, P. J. ( 2000) Nature 405, 797 - 800), the regulation of NK-B synthesis and function are poorly understood. Tac-2 was expressed in normal murine erythroid cells and was induced upon ex vivo erythropoiesis. An estrogen receptor fusion to GATA-1 (ER-GATA-1) and endogenous GATA-1 both occupied a region of Tac-2 intron-7, which contains two conserved GATA motifs. Genetic complementation analysis in GATA-1-null G1E cells revealed that endogenous GATA-2 occupied the same region of intron-7, and expression of ER-GATA-1 displaced GATA-2 and activated Tac-2 transcription. Erythroid cells did not express neurokinin receptors, whereas aortic and yolk sac endothelial cells differentially expressed neurokinin receptor subtypes. Since NK-B induced cAMP accumulation in yolk sac endothelial cells, these results suggest a new mode of vascular regulation in which GATA-1 controls NK-B synthesis in erythroid cells.

Neurofuzzy network model construction using Bézier-Bernstein polynomial functions

Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Modelling and inverting complex-valued Wiener systems

We develop a complex-valued (CV) B-spline neural network approach for efficient identification and inversion of CV Wiener systems. The CV nonlinear static function in the Wiener system is represented using the tensor product of two univariate B-spline neural networks. With the aid of a least squares parameter initialisation, the Gauss-Newton algorithm effectively estimates the model parameters that include the CV linear dynamic model coefficients and B-spline neural network weights. The identification algorithm naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. An accurate inverse of the CV Wiener system is then obtained, in which the inverse of the CV nonlinear static function of the Wiener system is calculated efficiently using the Gaussian-Newton algorithm based on the estimated B-spline neural network model, with the aid of the De Boor recursions. The effectiveness of our approach for identification and inversion of CV Wiener systems is demonstrated using the application of digital predistorter design for high power amplifiers with memory