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.

Designing an undergraduate laboratory course in general chemistry

From an analysis of a learning model based on the theory of information processing four hypothesis were developed for improving the design of laboratory courses. Three of these hypotheses concerned specific procedures to minimise the load on students' working memories (or working spaces) and the fourth hypothesis was concerned with the value of mini-projects in enhancing meaningful learning of the knowledge and skills underpinning the set experiments. A three-year study of a first year undergraduate chemistry laboratory course at a Scottish university has been carried out to test these four hypotheses. This paper reports the results of the study relevant to the three hypotheses about the burden on students' working spaces. It was predicted from the learning model that the load on students working space should be reduced by appropriate changes to the written instructions and the laboratory organisation and by the introduction of prelab-work and prelab-training in laboratory techniques. It was concluded from research conducted over the three years period that all these hypothesised changes were effective both in reducing the load on students' working spaces and in improving their attitudes to the laboratory course.

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.

Experimental study applied to an industrial robot by using variable structure controllers and friction compensation

Control of an industrial robot is mainly a problem of dynamics. It includes non-linearities, uncertainties and external perturbations that should be considered in the design of control laws. In this work, two control strategies based on variable structure controllers (VSC) and a PD control algorithm are compared in relation to the tracking errors considering friction. The controller's performances are evaluated by adding an static friction model. Simulations and experimental results show it is possible to diminish tracking errors by using a model based friction compensation scheme. A SCARA robot is used to illustrate the conclusions of this paper.

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.