Development of a weather-based model for Botrytis leaf blight of onion

ABSTRACT In the present study, onion plants were tested under controlled conditions for the development of a climate model based on the influence of temperature (10, 15, 20 and 25°C) and leaf wetness duration (6, 12, 24 and 48 hours) on the severity of Botrytis leaf blight of onion caused by Botrytis squamosa. The relative lesion density was influenced by temperature and leaf wetness duration (P <0.05). The disease was most severe at 20°C. Data were subjected to nonlinear regression analysis. Beta generalized function was used to adjust severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Botrytis leaf blight. The response surface obtained by the product of two functions was expressed as ES = 0.008192 * (((x-5)1.01089) * ((30-x)1.19052)) * (0.33859/(1+3.77989 * exp (-0.10923*y))), where ES represents the estimated severity value (0.1); x, the temperature (°C); and y, the leaf wetness (in hours). This climate model should be validated under field conditions to verify its use as a computational system for the forecasting of Botrytis leaf blight in onion.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

A network society communicative model for optimizing the Refugee Status Determination (RSD) procedures

This article recommends a new way to improve Refugee Status Determination (RSD) procedures by proposing a network society communicative model based on active involvement and dialogue among all implementing partners. This model, named after proposals from Castells, Habermas, Apel, Chimni, and Betts, would be mediated by the United Nations High Commissioner for Refugees (UNHCR), whose role would be modeled after that of the International Committee of the Red Cross (ICRC) practice.

A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil

INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. METHODS: The forecasting model for dengue incidence was performed with R software using the seasonal autoregressive integrated moving average (SARIMA) model. We fitted a model based on the reported monthly incidence of dengue from 1998 to 2008, and we validated the model using the data collected between January and December of 2009. RESULTS: SARIMA (2,1,2) (1,1,1)12 was the model with the best fit for data. This model indicated that the number of dengue cases in a given month can be estimated by the number of dengue cases occurring one, two and twelve months prior. The predicted values for 2009 are relatively close to the observed values. CONCLUSIONS: The results of this article indicate that SARIMA models are useful tools for monitoring dengue incidence. We also observe that the SARIMA model is capable of representing with relative precision the number of cases in a next year.

Prospects for a nonliving vaccine against Schistosomiasis based on cell-mediated immune resistance mechanisms

We have designed a vaccine model based on induction of cell-mediated immunity and shown that it protects mice against Schistosoma mansoni infection. Mice are immunized by intradermal injection with schistosome antigens plus BCG. Resistance is dependent on the route of antigen presentation and the adjuvant chosen. The pattern of resistance correlates with sensitization of T lymphocytes for production of gamma interferon, a macrophage activating lymphokine that stimulates the cellular effector mechanism of protection. Purified schistosome paramyosin, a muscle cell component present in soluble parasite antigenic preparations, is immunogenic for T lymphocytes and induces resistance when given intradermally with BCG. It is likely that this protein, and possibly other soluble molecules that are released by the parasites of a challenge infection, induce a cellular inflammatory response resulting in larval trapping and/or killing by activated macrophages. These results verify the feasibility of a vaccine against schistosomiasis based on induction of cell-mediated immune resistance mechanisms.

An oligonucleotide probe derived from kDNA minirepeats is specific for Leishmania (Viannia)

Sequence analysis of Leishmania (Viannia) kDNA minicircles and analysis of multiple sequence alignments of the conserved region (minirepeats) of five distinct minicircles from L. (V.) braziliensis species with corresponding sequences derived from other dermotropic leishmanias indicated the presence of a sub-genus specific sequence. An oligonucleotide bearing this sequence was designed and used as a molecular probe, being able to recognize solely the sub-genus Viannia species in hybridization experiments. A dendrogram reflecting the homologies among the minirepeat sequences was constructed. Sequence clustering was obtained corresponding to the traditional classification based on similarity of biochemical, biological and parasitological characteristics of these Leishmania species, distinguishing the Old World dermotropic leishmanias, the New World dermotropic leishmanias of the sub-genus Leishmania and of the sub-genus Viannia.

Genetic associations in the detection of QTLs for wheat spike-related traits

The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.

Temporal variability of soil CO2 emission after conventional and reduced tillage described by an exponential decay in time model

To study Assessing the impact of tillage practices on soil carbon losses dependents it is necessary to describe the temporal variability of soil CO2 emission after tillage. It has been argued that large amounts of CO2 emitted after tillage may serve as an indicator for longer-term changes in soil carbon stocks. Here we present a two-step function model based on soil temperature and soil moisture including an exponential decay in time component that is efficient in fitting intermediate-term emission after disk plow followed by a leveling harrow (conventional), and chisel plow coupled with a roller for clod breaking (reduced) tillage. Emission after reduced tillage was described using a non-linear estimator with determination coefficient (R²) as high as 0.98. Results indicate that when emission after tillage is addressed it is important to consider an exponential decay in time in order to predict the impact of tillage in short-term emissions.

Assessing the dynamics of terms of trade in a model of cumulative causation and structural change

ABSTRACT The motivation for this paper stems from the steady decline in the share of consumer expenditures on goods produced in the global south, coupled with the (empirically ambiguous) Singer/Prebisch hypothesis that this can be explained by a secular decline in the southern terms of trade. Drawing on these sources of inspiration, the paper sets out to study the dynamics of the terms of trade using a multi-sector growth model based on the principle of cumulative causation. The upshot is a North-South model of growth and trade in which the evolution of the terms of trade depends on differential rates of productivity growth in different sectors of the economy - and in which terms of trade dynamics may not be the best guide as to whether or not there is an uneven development problem.

Molecular Epidemiology of Human Polyomavirus JC in the Biaka Pygmies and Bantu of Central Africa

Polyomavirus JC (JCV) is ubiquitous in humans and causes a chronic demyelinating disease of the central nervous system , progressive multifocal leukoencephalopathy which is common in AIDS. JCV is excreted in urine of 30-70% of adults worldwide. Based on sequence analysis of JCV complete genomes or fragments thereof, JCV can be classified into geographically derived genotypes. Types 1 and 2 are of European and Asian origin respectively while Types 3 and 6 are African in origin. Type 4, a possible recombinant of European and African genotypes (1 and 3) is common in the USA. To delineate the JCV genotypes in an aboriginal African population, random urine samples were collected from the Biaka Pygmies and Bantu from the Central African Republic. There were 43 males and 25 females aged 4-55 years, with an average age of 26 years. After PCR amplification of JCV in urine, products were directly cycle sequenced. Five of 23 Pygmy adults (22%) and four of 20 Bantu adults (20%) were positive for JC viruria. DNA sequence analysis revealed JCV Type 3 (two), Type 6 (two) and one Type 1 variant in Biaka Pygmies. All the Bantu strains were Type 6. Type 3 and 6 strains of JCV are the predominant strains in central Africa. The presence of multiple subtypes of JCV in Biaka Pygmies may be a result of extensive interactions of Pygmies with their African tribal neighbors during their itinerant movements in the equatorial forest.

The impact of two education methods on knowledge of schistosomiasis transmission and prevention among schoolchildren in a rural community in northern Minas Gerais, Brazil

The objective of this study was to analyse the effect of using two health education approaches on knowledge of transmission and prevention of schistosomiasis of school children living in a rural endemic area in the state of Minas Gerais, Brazil. The 87 children participating in the study were divided into three groups based on gender, age and presence or absence of Schistosoma mansoni infection. In the first group the social representation model and illness experience was used. In the second group, we used the cognitive model based on the transmission of information. The third group, the control group, did not receive any information related to schistosomiasis. Ten meetings were held with all three groups that received a pre-test prior to the beginning of the educational intervention and a post-test after the completion of the program. The results showed that knowledge levels in Group 1 increased significantly during the program in regard to transmission (p = 0.038) and prevention (p = 0.001) of schistosomiasis. Groups 2 and 3 did not show significant increase in knowledge between the two tests. These results indicate that health education models need to consider social representation and illness experience besides scientific knowledge in order to increase knowledge of schistosomiasis transmission and prevention.

Polymerase chain reaction genotyping of Epstein-Barr virus in scraping samples of the tongue lateral border in HIV-1 seropositive patients

The Epstein-Barr virus (EBV) is the etiological agent of oral hairy leukoplakia (OHL), an oral lesion with important diagnostic and prognostic value in acquired immunodeficiency disease syndrome. The two EBV genotypes, EBV-1 and EBV-2, can be distinguished by divergent gene sequences encoding the EBNA-2, 3A, 3B, and 3C proteins. The purpose of this study was to identify the EBV genotype prevalent in 53 samples of scrapings from the lateral border of the tongue of HIV-1 seropositive patients, with and without OHL, and to correlate the genotypes with presence of clinical or subclinical OHL with the clinic data collected. EBV-1 and EBV-2 were identified through PCR and Nested-PCR based on sequence differences of the EBNA-2 gene. EBV-1 was identified in the 31 samples (15 without OHL, 7 with clinical OHL and 9 with subclinical OHL), EBV-2 in 12 samples (10 without OHL, 1 with clinical and 1 subclinical OHL), and a mixed infection in 10 samples (2 without OHL, 3 with clinical and 5 with subclinical OHL). The presence of EBV-1 was higher in women, but a significant statistical result relating one the EBV genotypes to the development of OHL was not found. We conclude that the oral epithelium in HIV-1 seropositive patients can be infected by EBV-1, EBV-2 or by a mixed viral population.

Trypanosoma cruzi: ancestral genomes and population structure

Although the genome of Trypanosoma cruzi has been completely sequenced, little is known about its population structure and evolution. Since 1999, two major evolutionary lineages presenting distinct epidemiological characteristics have been recognised: T. cruzi I and T. cruzi II. We describe new and important aspects of the population structure of the parasite, and unequivocally characterise a third ancestral lineage that we propose to name T. cruzi III. Through a careful analysis of haplotypes (blocks of genes that are stably transmitted from generation to generation of the parasite), we inferred at least two hybridisation events between the parental lineages T. cruzi II and T. cruzi III. The strain CL Brener, whose genome was sequenced, is one such hybrid. Based on these results, we propose a simple evolutionary model based on three ancestral genomes, T. cruzi I, T. cruzi II and T. cruzi III. At least two hybridisation events produced evolutionarily viable progeny, and T. cruzi III was the cytoplasmic donor for the resulting offspring (as identified by the mitochondrial clade of the hybrid strains) in both events. This model should be useful to inform evolutionary and pathogenetic hypotheses regarding T. cruzi.

Modelling of soil penetration resistance for an oxisol under no-tillage

Soil penetration resistance is an important property that affects root growth and elongation and water movement in the soil. Since no-till systems tend to increase organic matter in the soil, the purpose of this study was to evaluate the efficiency with which soil penetration resistance is estimated using a proposed model based on moisture content, density and organic matter content in an Oxisol containing 665, 221 and 114 g kg-1 of clay, silt and sand respectively under annual no-till cropping, located in Londrina, Paraná State, Brazil. Penetration resistance was evaluated at random locations continually from May 2008 to February 2011, using an impact penetrometer to obtain a total of 960 replications. For the measurements, soil was sampled at depths of 0 to 20 cm to determine gravimetric moisture (G), bulk density (D) and organic matter content (M). The penetration resistance curve (PR) was adjusted using two non-linear models (PR = a Db Gc and PR' = a Db Gc Md), where a, b, c and d are coefficients of the adjusted model. It was found that the model that included M was the most efficient for estimating PR, explaining 91 % of PR variability, compared to 82 % of the other model.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.