Seleção de linhagens de soja quanto a resistência de Corynespora cassiicola safra 2009/2010.

Avaliou-se 28 genótipos de soja convencional e soja RR, quanto a reação de Corynespora cassiicola, nos municípios de São Gabriel do Oeste (MS), Chapadão do Sul (MS) e Sorriso (MT), na safra 2009/2010

Substructure lensing in galaxy clusters as a constraint on low-mass sterile neutrinos in tensor-vector-scalar theory: The straight arc of Abell 2390

Certain covariant theories of the modified Newtonian dynamics paradigm seem to require an additional hot dark matter (HDM) component - in the form of either heavy ordinary neutrinos or more recently light sterile neutrinos (SNs) with a mass around 11eV - to be relieved of problems ranging from cosmological scales down to intermediate ones relevant for galaxy clusters. Here we suggest using gravitational lensing by galaxy clusters to test such a marriage of neutrino HDM and modified gravity, adopting the framework of tensor-vector-scalar theory (TeVeS). Unlike conventional cold dark matter (CDM), such HDM is subject to strong phase-space constraints, which allows one to check cluster lens models inferred within the modified framework for consistency. Since the considered HDM particles cannot collapse into arbitrarily dense clumps and only form structures well above the galactic scale, systems which indicate the need for dark substructure are of particular interest. As a first example, we study the cluster lens Abell 2390 and its impressive straight arc with the help of numerical simulations. Based on our results, we outline a general and systematic approach to model cluster lenses in TeVeS which significantly reduces the calculation complexity. We further consider a simple bimodal lens configuration, capable of producing the straight arc, to demonstrate our approach. We find that such a model is marginally consistent with the hypothesis of 11eV SNs. Future work including more detailed and realistic lens models may further constrain the necessary SN distribution and help to conclusively assess this point. Cluster lenses could therefore provide an interesting discriminator between CDM and such modified gravity scenarios supplemented by SNs or other choices of HDM.Comment: 22 pages, 14 figures, 2 tables; minor changes to match accepted versio

Infering Air Quality from Traffic Data using Transferable Neural Network Models

This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy requirements. Measurement equipment tends to be expensive to purchase and maintain. Therefore, a model based approach capable of accurate determination of pollution levels is highly beneficial. The objective of this study was to develop a neural network model to accurately infer pollution levels from existing data sources in Leicester, UK. Neural Networks are models made of several highly interconnected processing elements. These elements process information by their dynamic state response to inputs. Problems which were not solvable by traditional algorithmic approaches frequently can be solved using neural networks. This paper shows that using a simple neural network with traffic and meteorological data as inputs, the air quality can be estimated with a good level of generalisation and in near real-time. By applying these models to links rather than nodes, this methodology can directly be used to inform traffic engineers and direct traffic management decisions towards enhancing local air quality and traffic management simultaneously.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

BRSGO 7460RR: cultivar de soja transgênica.

bitstream/item/57492/1/BRSGO7460RR.pdf1 folder

Nematic liquid crystal reorientation around multi-walled carbon nanotubes mapped via Raman microscopy

We have studied the formation of topological defects in liquid crystal (LC) matrices induced by multiwalled carbon nanotubes (MWCNTs) and external electric fields. The defects are ascribable to a distortion of the LC molecular director in proximity of the MWCNT surface. The system is analyzed macroscopically using spectroscopic variable angle ellipsometry. Concurrently, confocal micro-Raman spectroscopy is used to study the system state at the microscale. This allows to acquire a three-dimensional, spatially-resolved map of the topological defect, determining scale length variations and orientation topography of the LC molecules around the MWCNT

Cultivares de soja: macrorregiões 3, 4 e 5 Goiás e Região Central do Brasil.

Grupo de maturidade relativa. Indicação de cultivares por região edafoclimática. Mancha olho-de-rã. Cancro da haste. Oídio. Nematóides de galhas. Manejo de mofo-branco em soja. Soja Louca II. Peso médio de sementes. Cultivares de soja convencional. Cultivares de soja transgênica (RR).bitstream/item/76085/1/catalogo-SojaGO-2012-FINAL.pdfCatálogo 02/2012

Adaptabilidade e estabilidade produtiva de linhagens de soja na Macrorregião sojícola 3, Brasil.

O objetivo deste trabalho foi avaliar a adaptabilidade e estabilidade de 25 genótipos de soja (21 linhagens experimentais e 4 cultivares testemunhas), de ciclo precoce, avaliados em oito locais dentro da Macrorregião sojícola 3 (301, 302, 303 e 304), na safra 2010/2011. Para isso, utilizou-se a análise AMMI (modelo de efeitos principais aditivos e interação multiplicativa), aplicada a dados de rendimento de grãos de ensaios delineados em blocos casualizados, com quatro repetições. Todos os sete eixos principais da análise (IPCAs) estiveram relacionados ao padrão da interação de genótipos com ambientes (GxA), segundo a significância das respectivas somas de quadrados. Com isso, não houve descarte de ruído adicional, além daquele associado ao erro experimental médio, no ajuste das médias de tratamentos (genótipos) e das estimativas de interação GxA. As linhagens G20, G8, G21 e as testemunha G23 e G24 foram as mais estáveis e com boas médias de produtividade (adaptabilidade geral). O ambiente A2 (Rio Verde) foi o mais favorável à manifestação da produtividade dos genótipos, e o ambiente A6 (Itumbiara), aquele com as piores produtividades

Vertex Cover Kernelization Revisited: Upper and Lower Bounds for a Refined Parameter

An important result in the study of polynomial-time preprocessing shows that there is an algorithm which given an instance (G,k) of Vertex Cover outputs an equivalent instance (G',k') in polynomial time with the guarantee that G' has at most 2k' vertices (and thus O((k')^2) edges) with k' <= k. Using the terminology of parameterized complexity we say that k-Vertex Cover has a kernel with 2k vertices. There is complexity-theoretic evidence that both 2k vertices and Theta(k^2) edges are optimal for the kernel size. In this paper we consider the Vertex Cover problem with a different parameter, the size fvs(G) of a minimum feedback vertex set for G. This refined parameter is structurally smaller than the parameter k associated to the vertex covering number vc(G) since fvs(G) <= vc(G) and the difference can be arbitrarily large. We give a kernel for Vertex Cover with a number of vertices that is cubic in fvs(G): an instance (G,X,k) of Vertex Cover, where X is a feedback vertex set for G, can be transformed in polynomial time into an equivalent instance (G',X',k') such that |V(G')| <= 2k and |V(G')| <= O(|X'|^3). A similar result holds when the feedback vertex set X is not given along with the input. In sharp contrast we show that the Weighted Vertex Cover problem does not have a polynomial kernel when parameterized by the cardinality of a given vertex cover of the graph unless NP is in coNP/poly and the polynomial hierarchy collapses to the third level.Comment: Published in "Theory of Computing Systems" as an Open Access publicatio