Modelagem matemática para a dispersão de fungos fitopatogênicos via autômatos celulares

Brazil is a major world producer and exporter of agricultural products like soybeans, sugar, coffee, orange and tobacoo. However, the action of phytopathogenic fungi has been one of the largest challenges encountered in the field as they are responsible for approximately 25 to 50 per cent of losses in crops of fruits and vegetables. The presence of these pathogens is always a problem, because the damage on the tissues and organs promote lesions which decreses growth vegetation and often leads the individual (host) to death. Therefore, it is crucial to understand the process of spreading of these pathogens in the field to develop strategies which prevent the epidemics caused by them. In this study, the dispersal of fungi phytopathogenic in the field was modeled using the automata cellular formalism. The growth rate of infected plants population was measured by the radius of gyration and the influence of host different susceptibility degrees into the disease spread was assessed. The spatial anisotropy related to the plant-to-plant space and the system’s response to distinct seasonal patterns were also evaluated. The results obtained by a mean field model (spatially implicit models) emphasized the importance of the spatial structure on the spreading process, and dispersal patterns obtained by simulation (using a cellular automata) were in agreement with thse observed in data. All computational implementation was held in language Cl

Spontaneous symmetry breaking in a spin-orbit-coupled f=2 spinor condensate

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

Mobile vector soliton in a spin-orbit coupled spin-1 condensate

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

Vector solitons in a spin-orbit-coupled spin-2 Bose-Einstein condensate

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

Reaction norms for the study of genotype-environment interaction for growth and indicator traits of sexual precocity in Nellore cattle

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

Aplicação de modelos de regressão aleatória utilizando diferentes estruturas de dados

A total of 3.035 lactations of Holstein cows from four farms in the Southeast, to check the influence of data structure of milk yield on the genetic parameters. Four dataset with different structures were tested, weekly controls (CW) with 122.842 controls, monthly controls (CM) 30.883, bimonthly controls (CB) with 15,837 and quarterly controls (CQ) with 12,702. The random regression model was used and was considered as random additive genetic and permanent environment effects, fixed effects of the contemporary groups (herd-year-month of test-day) and age of cow (linear and quadratic effects). Heritability estimates showed similar trends among the data files analyzed, with the greatest similarity between dataset CS, CM and CB. The dataset submitted all the CB estimates of genetic parameters analyzed with the same trend and similar magnitude to the CS and CM dataset, allowing the claim that there was no influence of the data structure on estimates of covariance components for the dataset CS, CM and CB. Thus, milk recording could be accomplished in a CB structure.

Antibioticoterapia para o tratamento de periotonite em diálise peritoneal: redicão sostemática de estudo clínicos controlados e série de casos

Pós-graduação em Fisiopatologia em Clínica Médica - FMB

Revisão sistemática do perfil de risco e profilaxia de tromboembolismo venoso no Brasil e no mundo

Pós-graduação em Bases Gerais da Cirurgia - FMB

Análise genética de escores visuais e sua relação com características reprodutivas de animais da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Modeling spatial distribution of cancer incidence in Cordoba, Argentina

Background: Cancer is the second leading cause of death in Argentina, and there is little knowledge about its incidence. The first study based on population-based cancer registry described spatial incidence and indicated that there existed at least county-level aggregation. The aim of the present work is to model the incidence patterns for the most incidence cancer in Córdoba Province, Argentina, using information from the Córdoba Cancer Registry by performing multilevel mixed model approach to deal with dependence and unobserved heterogeneity coming from the geo-reference cancer occurrence. Methods: Standardized incidence rates (world standard population) (SIR) by sex based on 5-year age groups were calculated for 109 districts nested on 26 counties for the most incidence cancers in Cordoba using 2004 database. A Poisson twolevel random effect model representing unobserved heterogeneity between first level-districts and second level-counties was fitted to assess the spatial distribution of the overall and site specific cancer incidence rates. Results: SIR cancer at Córdoba province shown an average of 263.53±138.34 and 200.45±98.30 for men and women, respectively. Considering the ratio site specific mean SIR to the total mean, breast cancer ratio was 0.25±0.19, prostate cancer ratio was 0.12±0.10 and lower values for lung and colon cancer for both sexes. The Poisson two-level random intercepts model fitted for SIR data distributed with overdispersion shown significant hierarchical structure for the cancer incidence distribution. Conclusions: a strong spatial-nested effect for the cancer incidence in Córdoba was observed and will help to begin the study of the factors associated with it.

Seleção genômica para características longitudinais de bovinos da raça Holandesa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analog Model for Quantum Gravity Effects: Phonons in Random Fluids

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

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

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The hierarchical model of branch planning with random coefficients

We consider the management branch model where the random resources of the subsystem are given by the exponential distributions. The determinate equivalent is a block structure problem of quadratic programming. It is solved effectively by means of the decomposition method, which is based on iterative aggregation. The aggregation problem of the upper level is resolved analytically. This overcomes all difficulties concerning the large dimension of the main problem.