Análise da influência de variantes do método de solução de escoamentos utilizando os métodos de elementos finitos com compressibilidade artificial e pseudo-características

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Perda de matéria seca em grãos de milho submetidos a sistemas de secagem natural e artificial.

The permanence of the corn grain in the field, after physiological maturity, is an important cause of crop losses, both in quantitative and qualitative aspect. By ceasing the supply of assimilated substances to grains, due to physiological maturity, the synthesis reactions are overcome by breathing, responsible for the maintenance of the living tissues of the grains, which occur at the expense of reserves accumulated during grain formation. In addition, there are losses from fungus and insects attack due to adverse weather conditions. Technological advances in recent decades, the develop of grain dryers with different capacities and efficiencies, has led to the early withdrawal of the product from the field, still damp, reducing spoilage. Moreover, the use of artificial drying systems can represent a significant cost to the producer. Thus, the present work aimed to study the effect of natural and artificial methods of drying on maize dry matter losses, for Botucatu, city of Sao Paulo state, Brazil. The cornfield production was conducted at the Experimental Farm “Lageado” and the experimental treatments were conducted in the Laboratory of Agricultural Products Processing, in the Department of Rural Engineering, where the drying systems were tested. The treatments were: shade (control), artificial with heated air, artificial unheated air and, drying attached to the plant. The following analyzes for quality monitoring were performed: weight test, thousand-grain weight test and, grain dry weight. The results showed significant loss in quality of drying beans attached to the plant, by assessing the dry matter loss and by the variation of the grain weight. The weight test showed that the worst performance was the artificial with heated air treatment. We used mathematical modeling techniques to describe the dry matter loss and adjusted the mathematical model to the experimental data analyzed. From the experimental data obtained during drying the grain attached to the plant, it was still possible to fit a regression model that estimates the loss of grain dry matter under the climate from Botucatu during the 2011/2012 harvest period.

Artificial Equations, Artificial Distinctions: Language that Poisons the Waters of Ethnic Relations

“It is my contention at this point that when race relations on campuses get better, it is in spite of, not because of, the proliferation of jargon-based rhetoric about diversity.”

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Effect of nAellore cows ciclicity on conception and pregnant rates after synchronization protocols for fixed timed artificial insemination

Palhano H.B., Jesus V.L.T., Abidu-Figueiredo M., Baldrighi J.M. & Mello M.R.B. [Effect of nAellore cows ciclicity on conception and pregnant rates after synchronization protocols for fixed timed artificial insemination]. Efeito da ciclicidade de vacas Nelore sobre as taxas de concepcao e de prenhez apos protocolos de sincronizacao para inseminacao artificial em tempo fixo. Revista Brasileira de Medicina Veterinaria, 34(1):63-68, 2012. Departamento de Biologia Animal, Universidade Federal Rural do Rio de Janeiro, BR 465 km 7, Seropedica, RJ 23890-000, Brasil. Email: hbpalhano@gmail.com The present study evaluated the effect on conception and pregnancy rates of Nellore cows selected for Fixed Timed Artificial Insemination (FTAI) program, submitted to four synchronization protocols. Four hundred and ninety lactating females were used and assigned to eight groups: I-OvSynch, n=68, with selection of cycling cows; II-OvSynch + progesterone (P-4), n=67, after selection of non-cycling animals; III-OvSynch, without selection, n=68; IV-OvSynch + P-4, without selection, n=67; V-Co-Synch, n=55, with selection of cycling cows; VI-Co-Synch + P-4, n=55, with selection non-cycling cows; VII- Co-Synch without selection, n=55; VIII- Co-Synch + P-4, without selection, n=55. The conception and pregnancy rates were, respectively, 45.6%, 27.9% and 82.4%, 48.5% for groups I and III; 61.2%, 37.3% and 85.1%, 58.2% for groups II and IV; 43.6%, 25.5% and 80%, 41.8% for groups V and VII; 52.7%, 32.7% and 83.6%, 50.9% for groups VI and VIII. When compared these rates, the results after chi-square test showed significant difference (P < 0.05) among protocols with or without selection. There was no significant difference (P > 0.05) between OvSynch and Co-Synch protocols, with or without P-4 and with selection, considering Co-Synch a viable option for optimization of FTAI. In conclusion, the selection of cows before FTAI program contributed significantly to improve the conception and pregnancy rates.

Sensitivity of Eisenia andrei (Annelida, Oligochaeta) to a commercial formulation of abamectin in avoidance tests with artificial substrate and natural soil under tropical conditions

Obtaining ecotoxicological data on pesticides in tropical regions is imperative for performing more realistic risk analysis, and avoidance tests have been proposed as a useful, fast and cost-effective tool. Therefore, the present study aimed to evaluate the avoidance behavior of Eisenia andrei to a formulated product, Vertimec(A (R)) 18 EC (a.i abamectin), in tests performed on a reference tropical artificial soil (TAS), to derive ecotoxicological data on tropical conditions, and a natural soil (NS), simulating crop field conditions. In TAS tests an adaptation of the substrate recommended by OECD and ISO protocols was used, with residues of coconut fiber as a source of organic matter. Concentrations of the pesticide on TAS test ranged from 0 to 7 mg abamectin/kg (dry weight-d.w.). In NS tests, earthworms were exposed to samples of soils sprayed in situ with: 0.9 L of Vertimec(A (R)) 18 EC/ha (RD); twice as much this dosage (2RD); and distilled water (Control), respectively, and to 2RD: control dilutions (12.5, 25, 50, 75%). All tests were performed under 25 +/- A 2A degrees C, to simulate tropical conditions, and a 12hL:12hD photoperiod. The organisms avoided contaminated TAS for an EC50,48h = 3.918 mg/kg soil d.w., LOEC = 1.75 mg/kg soil d.w. and NOEC = 0.85 mg/kg soil d.w. No significant avoidance response occurred for any NS test. Abamectin concentrations in NS were rather lower than EC50, 48h and LOEC determined in TAS tests. The results obtained contribute to overcome a lack of ecotoxicological data on pesticides under tropical conditions, but more tests with different soil invertebrates are needed to improve pesticides risk analysis.

Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Xylitol concentrations in artificial saliva after application of different xylitol dental varnishes

Objective: The present study analyzed xylitol concentrations in artificial saliva over time after application of varnishes containing 10% and 20% xylitol. Material and Methods: Fifteen bovine enamel specimens (8x4 mm) were randomly allocated to 3 groups (n=5/group), according to the type of varnish used: 10% xylitol, 20% xylitol and no xylitol (control). After varnish application (4 mg), specimens were immersed in vials containing 500 mu L of artificial saliva. Saliva samples were collected in different times (1, 8, 12, 16, 24, 48 and 72 h) and xylitol concentrations were analyzed. Data were assessed by two-way repeated-measures ANOVA (p<0.05). Results: Colorimetric analysis was not able to detect xylitol in saliva samples of the control group. Salivary xylitol concentrations were significantly higher up to 8 h after application of the 20% xylitol varnish. Thereafter, the 10% xylitol varnish released larger amounts of that polyol in artificial saliva. Conclusions: Despite the results in short-term, sustained xylitol releases could be obtained when the 10% xylitol varnish was used. These varnishes seem to be viable alternatives to increase salivary xylitol levels, and therefore, should be clinically tested to confirm their effectiveness.

Artificial and natural radioactivity in edible mushrooms from Sao Paulo, Brazil

Environmental biomonitoring has demonstrated that organisms such as crustaceans, fish and mushrooms are useful to evaluate and monitor both ecosystem contamination and quality. Particularly, some mushroom species have a high capacity to retain radionuclides and some toxic elements from the soil and the air. The potential of mushrooms to accumulate radionuclides in their fruit-bodies has been well documented. However, there are no studies that determine natural and artificial radionuclide composition in edible mushrooms, in Brazil. Artificial (Cs-137) and natural radioactivity (K-40. Ra-226. Ra-228) were determined in 17 mushroom samples from 3 commercialized edible mushroom species. The edible mushrooms collected were Agaricus sp., Pleurotus sp. and Lentinula sp. species. The activity measurements were carried out by gamma spectrometry. The levels of Cs-137 varied from 1.45 +/- 0.04 to 10.6 +/- 0.3 Bq kg(-1), K-40 levels varied from 461 +/- 2 to 1535 +/- 10 Bq kg(-1), Ra-226 levels varied from 14 +/- 3 to 66 +/- 12 Bq kg(-1) and Ra-228 levels varied from 6.2 +/- 0.2 to 54.2 +/- 1.7 Bq kg(-1). Cs-137 levels in Brazilian mushrooms are in accordance with the radioactive fallout in the Southern Hemisphere. The artificial and natural activities determined in this study were found to be below the maximum permissible levels as established by national legislation. Thus, these mushroom species can be normally consumed by the population without any apparent risks to human health.

Influence of artificial accelerated ageing on the colour stability of paints used for ocular prosthesis iris painting

Objectives: To evaluate the colour stability of paints used for ocular prosthesis iris painting submitted for accelerated artificial ageing (AAA). Materials and methods: Forty specimens of acrylic resin for sclera (16 x 2 mm) were made and separated into eight groups (n = 10) according to the type of paint (gouache, GP; oil, OP; acrylic AP; and composite resin for characterisation, CR) and the colours used (blue/brown). After drying (72 h), a new layer of colourless acrylic resin was applied and the initial colour readout was performed (Spectrophotometer PCB 6807). New colour readouts were performed after AAA, and Delta E was calculated. Results: Statistical analysis (two-way ANOVA-Bonferroni, p < 0.05) demonstrated that the brown colour showed lower Delta E means in comparison with the blue colour, with statistically significant difference for AP only. Blue colour showed no statistically significant difference with regard to the type of paint used. Brown AP showed lower Delta E than the other groups, with significant difference for OP and GP. GP showed greater alteration in Delta E for the brown colour, being statistically similar only to OP. Conclusions: Only the AP group for brown pigment shows clinically acceptable values for colour stability after AAA.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Effects of Natural Radiation, Photosynthetically Active Radiation and Artificial Ultraviolet Radiation-B on the Chloroplast Organization and Metabolism of Porphyra acanthophora var. brasiliensis (Rhodophyta, Bangiales)

We undertook a study of Porphyra acanthophora var. brasiliensis to determine its responses under ambient conditions, photosynthetically active radiation (PAR), and PAR+UVBR (ultraviolet radiation-B) treatment, focusing on changes in ultrastructure, and cytochemistry. Accordingly, control ambient samples were collected in the field, and two different treatments were performed in the laboratory. Plants were exposed to PAR at 60 mu mol photons m(-2) s(-1) and PAR+UVBR at 0.35 W m(-2) for 3 h per day during 21 days of in vitro cultivation. Confocal laser scanning microscopy analysis of the vegetative cells showed single stellate chloroplast in ambient and PAR samples, but in PAR+UVBR-exposed plants, the chloroplast showed alterations in the number and form of arms. Under PAR+UVBR treatment, the thylakoids of the chloroplasts were disrupted, and an increase in the number of plastoglobuli was observed, in addition to mitochondria, which appeared with irregular, disrupted morphology compared to ambient and PAR samples. After UVBR exposure, the formation of carpospores was also observed. Plants under ambient conditions, as well as those treated with PAR and PAR+UVBR, all showed different concentrations of enzymatic response, including glutathione peroxidase and reductase activity. In summary, the present study demonstrates that P. acanthophora var. brasiliensis shows the activation of distinct mechanisms against natural radiation, PAR and PAR+UVBR.

Expanding the horizontal capabilities of CRT monitors using artificial inter-pixel steps for neuroscience experiments

This article describes the development of a visual stimulus generator to be used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of a fixed image that is displaced horizontally according to the stimulus data. The system is capable of displaying 640 x 480 pixels with 256 intensity levels at 200 frames per second (FPS) on conventional raster monitors. To double the possible horizontal positioning possibilities from 640 to 1280, a novel technique is presented introducing artificial inter-pixel steps. The implementation consists in using two video frame buffers containing each a distinct view of the desired image pattern. This implementation generates a visual effect capable of doubling the horizontal positioning capabilities of the visual stimulus generator allowing more precise and movements more contiguous. (C) 2011 Elsevier Inc. All rights reserved.