Changes induced in Biomphalaria glabrata (Say, 1818) following trials for artificial stimulation of its internal defense system

Biomphalaria glabrata can react through different pathways to Schistosoma mansoni miracidium penetration, according to the degree of resistance/susceptibility presented by different snail strains, which is a genetically determined character, resistance being the dominant feature. However, it has been observed that previous susceptible snail strain may change its reactive behavior along the course of infection, exhibiting later a pattern of cercarial shedding and histopatopathological picture compatible with high resistance. Such observation suggests the possibility of B. glabrata to develop a sort of adaptative immunity face a schistosome infection. To explore on this aspect, the present investigation looked for the behavior of S. mansoni infection in B. glabrata previously subjected to different means of artificial stimulation of its internal defense system. Snails previously inoculated with irradiated miracídia (Group I); treated with S. mansoni antigens (Group II) or with a non-related parasite antigen (Group III) were challenged with 20 viable S. mansoni miracidia, and later looked for cercarial shedding and histopathologic changes at different times from exposition. Nodules of hemocyte accumulations were found at the site of antigen injection. These nodules resembled solid granulomas, and were larger and more frequent in snails injected with S. mansoni products as compared to those injected with Capillaria hepatica. However, the presence of such granulomas did not avoid the S. mansoni challenge infection from developing in a similar way as that seen in controls. The data are indicative that hemocytes are able to proliferate locally when stimulated, such capacity also remaining localized, not being shared by the population of hemocytes located elsewhere within the snail body.

Attraction of Chagas disease vectors (Triatominae) to artificial light sources in the canopy of primary Amazon rainforest

Adult triatomines occasionally fly into artificially lit premises in Amazonia. This can result in Trypanosoma cruzi transmission to humans either by direct contact or via foodstuff contamination, but the frequency of such behaviour has not been quantified. To address this issue, a light-trap was set 45 m above ground in primary rainforest near Manaus, state of Amazonas, Brazil and operated monthly for three consecutive nights over the course of one year (432 trap-hours). The most commonly caught reduviids were triatomines, including 38 Panstrongylus geniculatus, nine Panstrongylus lignarius, three Panstrongylus rufotuberculatus, five Rhodnius robustus, two Rhodnius pictipes, one Rhodnius amazonicus and 17 Eratyrus mucronatus. Males were collected more frequently than females. The only month without any catches was May. Attraction of most of the known local T. cruzi vectors to artificial light sources is common and year-round in the Amazon rainforest, implying that they may often invade premises built near forest edges and thus become involved in disease transmission. Consequently, effective Chagas disease prevention in Amazonia will require integrating entomological surveillance with the currently used epidemiological surveillance.

Resfriamento artificial para o controle de Coleoptera em arroz armazenado em silo metálico

Resfriamento artificial para o controle de Coleoptera em arroz armazenado em silo metálico. O objetivo desta pesquisa foi avaliar o efeito do resfriamento artificial de grãos de arroz para o controle de coleópteros-praga. O ar frio foi insuflado pelo sistema de aeração em um silo metálico com arroz-em-casca. A avaliação do tratamento foi feita quinzenalmente usando armadilhas caladores. As espécies de Coleoptera capturadas foram: Oryzaephilus surinamensis (60%); Cryptolestes ferrugineus (9%); Rhyzopertha dominica (16,5%) e Sitophilus spp. (0,5%). Aos 28 dias, a temperatura média da massa de grãos era de 15ºC, e o número médio de insetos havia diminuído 76,8%. A aplicação de ar frio manteve as populações sob controle por aproximadamente 60 dias. Os resultados do monitoramento dos insetos e da temperatura indicaram que um novo ciclo de ar frio deveria ser aplicado nesse período para manter as populações sob controle. Também o manejo adequado da massa de grãos faz-se necessário para garantir resultados satisfatórios do resfriamento artificial.

Records of Anopheles (Nyssorhynchus) (Diptera, Culicidae) in artificial containers in Ribeirão Preto City, State of São Paulo, Brazil

Thirty immatures of Anopheles darlingi Root, Anopheles argyritarsis Robineau-Desvoidy and Anopheles rondoni (Neiva & Pinto) (were found in an artificial lagoon situated near Pardo River, in Ribeirão Preto City, State of São Paulo, Brazil. The presence of immatures of Anopheles darlingi breeding in a lagoon is suggestive of the potential capacity of that species to adapt and occupy new habitats and to invade urban areas along the species distribution range and also disperse to new localities.

Nymph developmental time and survivorship, adult longevity, reproduction and body weight of Dichelops melacanthus (Dallas) feeding on natural and artificial diets

The biology of nymphs and adults of the neotropical pentatomid, Dichelops melacanthus (Dallas), feeding on the natural foods, soybean, Glycine max (L.) Merrill immature pods, and corn, Zea mays L. immature seeds, and on an artificial dry diet, was studied in the laboratory. Nymph developmental time was shorter on the natural foods (ca. 21-22 days) than on the artificial diet (28 days), and most nymphs reached adulthood on the food plants (55% on soybean and 73% on corn) than on the artificial diet (40%). Fresh body weight at adult emergence was similar and higher for females raised as nymphs on the natural foods, compared to females from nymphs raised on the artificial diet; for males, weights were similar on all foods. Mean (female and male) survivorship up to day 20, decreased from 55% on soybean to 40% on corn, down to 0% on the artificial diet. Total longevity for females was higher on soybean, while for males was similar on all foods. About three times more females oviposited on soybean than on corn, but fecundity/female was similar on both foods. On the artificial diet, only one out of 30 females oviposited. Fresh body weight of adults increased significantly during the first week of adult life, and at the end of the 3rd week, weight gain was similar on all foods.

The adequacy of artificial oviposition substrates for laboratory rearing of Piezodorus guildinii (Westwood) (Heteroptera, Pentatomidae)

Studies in the laboratory tested the suitability of synthetic wool string, cotton string, cheesecloth, and commercial cotton ball as artificial oviposition substrates for the small green stink bug, Piezodorus guildinii (Westwood) (Heteroptera, Pentatomidae). In confined cages, 54% of total egg masses was laid on synthetic wool string, 31% on cotton string, and only 15% on cheesecloth. In an additional test, the best substrate selected, synthetic wool string, received 92% of egg masses compared to 8% on the commonly used substrate, cotton ball. Synthetic wool string received the most egg masses of any size, in particular those in the range 11-20 eggs/mass. Because the eggs of P. guildinii are laid in two parallel double rows, the egg masses fit the wool string perfectly.

Selection of artificial hosts for oviposition by wild Anastrepha obliqua (Macquart) (Diptera, Tephritidae): influence of adult food and effect of experience

Several factors influence the selection of oviposition substrates by insects. The aim of the present work was to find answers to the following questions related to the oviposition behavior of Anastrepha obliqua. Can carbohydrates (glucose or sucrose) present in the adult diet have influence on the female preference for an oviposition substrate with similar composition? Can the previous experience with a host containing one of mentioned carbohydrates interfere in further selection of oviposition substrates? The results showed that the kind of carbohydrate present in the adult diet did not affect the female preference for an artificial oviposition substrate, neither when it was presented by itself nor in combination with brewer's yeast. The effect of experience in the oviposition behavior was observed when there was a previous contact with artificial oviposition substrates containing yeast and sucrose. The data are discussed in terms of the behavioral plasticity presented by this species in relation to feeding and oviposition behaviors.

Use of artificial substrates of different colors for oviposition by the brown stink bug Euschistus heros (Hemiptera, Pentatomidae)

Aiming to contribute to a rearing methodology for the brown stink bug, Euschistus heros, in the laboratory, we evaluated oviposition on artificial substrates of different colors. During six days, oviposition was evaluated daily, by counting the total number of eggs, number of clutches, and eggs/clutch. Females laid 12,463 eggs, in 1,677 clutches, resulting in an average of 7.28 ± 0.44 eggs/clutch. Black, brown, and green felt had the most eggs and clutches. The results demonstrated that many colors are suitable as oviposition substrate for E. heros, providing information for the mass rearing of this insect.

Desenvolvimento e análise de uma rede neural artificial para estimativa da erosividade da chuva para o Estado de São Paulo

O conhecimento do valor da erosividade da chuva (R) de determinada localidade é fundamental para a estimativa das perdas de solo feitas a partir da Equação Universal de Perdas de Solo, sendo, portanto, de grande importância no planejamento conservacionista. A fim de obter estimativas do valor de R para localidades onde este é desconhecido, desenvolveu-se uma rede neural artificial (RNA) e analisou-se a acurácia desta com o método de interpolação "Inverso de uma Potência da Distância" (ID). Comparando a RNA desenvolvida com o método de interpolação ID, verificou-se que a primeira apresentou menor erro relativo médio na estimativa de R e melhor índice de confiança, classificado como "Ótimo", podendo, portanto, ser utilizada no planejamento de uso, manejo e conservação do solo no Estado de São Paulo.

Rugosidade da superfície do solo sob diferentes sistemas de manejo e influenciada por chuva artificial

A rugosidade da superfície do solo é influenciada pelo manejo, formada em especial pelo tipo de preparo e reduzida pela ação da chuva, principalmente. O objetivo deste estudo foi avaliar a influência de diferentes sistemas de manejo do solo e da aplicação de chuva artificial na rugosidade da superfície do solo. Os tratamentos estudados resultaram da combinação de três sistemas de manejo do solo, semeadura direta (SD), preparo convencional (PC) e cultivo mínimo (CM), com três doses de resíduo vegetal seco de soja (Glycine max L. Merrill): 0, 2 e 4 Mg ha-1. Nas unidades experimentais foram aplicadas sete chuvas, com intensidade de precipitação pluvial de 60 mm h-1 e duração de 60 min cada, totalizando 420 mm de lâmina de chuva. A rugosidade foi avaliada imediatamente antes e após o preparo do solo e imediatamente após a aplicação de cada uma das sete chuvas artificiais. Obtiveram-se valores do índice de rugosidade ao acaso entre 1,88 e 5,41 mm na semeadura direta; entre 3,88 e 8,30 mm no preparo convencional; e entre 8,99 e 17,45 mm no cultivo mínimo. Concluiu-se que: as operações de preparo do solo aumentaram a rugosidade da sua superfície, em geral; o cultivo mínimo foi o sistema de preparo do solo que proporcionou os maiores valores de rugosidade ao acaso; e nos tratamentos semeadura direta com cobertura do solo a ação da chuva não promoveu decaimento do microrrelevo do solo.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

INTELIGÊNCIA ARTIFICIAL: SISTEMAS ESPECIALISTAS NO GERENCIAMENTO DA INFORMAÇÃO

O principal objetivo deste artigo é propor um modelo para sistemas de gerenciamento da informação baseado em técnicas de inteligência artificial. O modelo propõe uma arquitetura de sistema especialista para gerenciamento da informação, sugerindo a utilização de um analisador semântico embutido na interface do usuário final. A abordagem enfatiza a dificuldade em se obter informações com precisão e qualidade, para apoiar tomadores de decisões, e a necessidade de prover os usuários finais com mecanismos, poderosos, capazes de analisar, selecionar e direcionar-lhes informações, de acordo com as necessidades e urgências de cada um

Comportamento de fungos e de sementes de feijoeiro durante o teste de envelhecimento artificial

O teste de envelhecimento artificial, recomendado para avaliar o vigor de lotes de sementes, apresenta variabilidade em seus resultados; a ação dos fungos é considerada uma das causas dessa variabilidade. Este trabalho objetivou verificar os efeitos de diferentes períodos de envelhecimento artificial, no comportamento fisiológico de sementes do feijoeiro e dos fungos Aspergillus spp., Penicillium spp., Fusarium oxysporum e Colletotrichum lindemuthianum, inoculados artificialmente. Foram conduzidos testes de sanidade, germinação, tetrazólio, emergência, condutividade elétrica e lixiviação de potássio. As respostas obtidas, dependentes da duração do período de envelhecimento, indicaram efeitos da espécie fúngica presente. Concluiu-se que o teste de envelhecimento artificial associa a expressão de causas fisiológicas e sanitárias, o que prejudica a interpretação dos dados obtidos; a presença de fungos, principalmente de Aspergillus spp., pode ser considerada como capaz de interferir de modo negativo no desempenho das sementes envelhecidas artificialmente.