Magnetic Properties of the Metamagnet Ising Model in a three-dimensional Lattice in a Random and Uniform Field

By employing the Monte Carlo technique we study the behavior of Metamagnet Ising Model in a random field. The phase diagram is obtained by using the algorithm of Glaubr in a cubic lattice of linear size $L$ with values ranging from 16 to 42 and with periodic boundary conditions.Comment: 4 pages, 6 figure

Origens, crescimento e progressos na cotonicultura do Brasil.

Origens e crescimento da cotonicultura; Progressos na cotonicultura.bitstream/item/130108/1/ORIGEM-CRESCIMENTO.pd

Melhoramento genético do feijão-caupi na Embrapa Semi-Árido.

Procedimentos para hibridações, avanços de gerações e competições; análises estatísticas dos ensaios avançados; análises para a qualidade tecnológica dos grãos; avaliações em macroparcelas em nível de propriedades rurais; seleção de linhagens avançadas nos cruzamentos com Epace 10 e BR 14 Gurguéia; análises para a qualidade tecnológica dos grãos; avaliações em macroparcelas em nível de propriedades rurais; seleção de linhagens de crescimento determinado e porte ereto; seleção de linhagens tipo ?Canapu? tolerantes às principais viroses; integração de melhoramento clássico e molecular; desenvolvimento de linhagens com propriedades de alimentos funcionaisbitstream/CPATSA/36702/1/SDC204.pd

A gomose da acácia-negra no Brasil.

A acácia-negra (Acacia mearnsii) é cultivada no Brasil, especialmente no Estado do Rio Grande do Sul, visando tanto à produção de tanino, a partir da casca, quanto o uso da madeira para papel, celulose, carvão, lenha e chapas de aglomerados. A gomose causada por Phytophthora nicotianae e P. boehmeriae, é o seu principal problema fitossanitário. Discute-se nesta revisão a existência de dois padrões distintos de sintomatologia da gomose de Phytophthora que têm sido observados nas plantações brasileiras: gomose basal, associada a P. nicotianae, e gomose generalizada, mais associada a P. boehmeriae. São discutidos aspectos relacionados à etiologia, à epidemiologia e às estratégias de controle

Doenças emergentes causadas por Phytophtora no Brasil.

Edição do 40º Congresso Brasileiro de Fitopatologia, 2007, Maringá

The Euler characteristic as a topological marker for outbreaks in vector-borne disease

Abstract. Epidemic outbreaks represent a significant concern for the current state of global health, particularly in Brazil, the epicentre of several vector-borne disease outbreaks and where epidemic control is still a challenge for the scientific community. Data science techniques applied to epidemics are usually made via standard statistical and modelling approaches, which do not always lead to reli- able predictions, especially when the data lacks a piece of reliable surveillance information needed for precise parameter estimation. In particular, dengue out- breaks reported over the past years raise concerns for global health care, and thus novel data-driven methods are necessary to predict the emergence of out- breaks. In this work, we propose a parameter-free approach based on geometric and topological techniques, which extracts geometrical and topological invariants as opposed to statistical summaries used in established methods. Specifically, our procedure generates a time-varying network from a time-series of new epidemic cases based on synthetic time-series and real dengue data across several dis- tricts of Recife, the fourth-largest urban area in Brazil. Subsequently, we use the Euler characteristic (EC) to extract key topological invariant of the epidemic time-varying network and we finally compared the results with the effective reproduction number (Rt) for each data set. Our results unveil a strong cor- relation between epidemic outbreaks and the EC. In fact, sudden changes in the EC curve preceding and/or during an epidemic period emerge as a warn- ing sign for an outbreak in the synthetic data, the EC transitions occur close to the periods of epidemic transitions, which is also corroborated. In the real dengue data, where data is intrinsically noise, the EC seems to show a better sign-to-noise ratio once compared to Rt. In analogy with later studies on noisy data by using EC in positron emission tomography scans, the EC estimates the number of regions with high connectivity in the epidemic network and thus has potential to be a signature of the emergence of an epidemic state. Our results open the door to the development of alternative/complementary topological and geometrical data-driven methods to characterise vector-borne disease outbreaks, specially when the conventional epidemic surveillance methods are not effective in a scenario of extreme noise and lack of robustness in the data