"Monstruoso systema (...) intrusa e abusiva jurisdicção": O Diretório dos Índios no discurso dos agentes administrativos coloniais (1777-1798)

O trabalho visa demonstrar, por meio de relatórios e correspondências dos agentes administrativos coloniais no vale amazônico, o discurso acerca do Diretório dos Índios (1757-1798). Nosso propósito foi indicar que as críticas formuladas pelos representantes da Coroa, mais que denunciar desvios dos diretores, indicavam a emergência de poderes que colocavam em risco o projeto metropolitano para o vale amazônico.

Sôbre a glândula abdominal da fêmea de Citheronia laocoon (Cr., 1777) (Lepidoptera, Adelocephalidae)

Macho e fêmea de Citheronia laocoon emitem um cheiro repugnante. Esta substância é um componente da hemolinfa que, no momento de perigo, é expulsa através da cutícula, desconhecendo-se, porém, ainda o local da exsudação, que, entretanto deve ser procurado nas membranas intersegmentais do abdômen. A fêmea possui uma glândula atraente de organização simples, situada entre os 8.º e 9.º segmentos abdominais.

Taxorchis caviae sp. n. (Trematoda, Paramphistomidae), parasito intestinal de Cavia aperea Erxleben, 1777 (Rodentia, Caviidae)

Descreve-se uma nova espécie de trematóide paranfistomídeo, encontrado no intestino grosso de preá, Cavia aperea aperea Erxleben, 1777, roedor silvestre muito freqüente no Estado de São Paulo de outras regiões do país. Para o trematóide em apreço é proposto o nome de Taxorchis caviae sp. n. São discutidas as diferenças entre T. caviae e as espécies próximas,dos gêneros Chiorchis, Taxorchis e Stichorchis. São propostas alterações na diagnose clássica do gênero Taxorchis, de modo a nele ser incluído T. caviae.

Physa acuta Draparnaud, 1805 (Gastropoda: Physidae): a study of topotypic specimens

A description is given of Physa acuta Draparnaud, 1805, based on topotypic specimens from the Garonne river basin, and additional samples from the environs of the French cities of Montpellier and Perpignan. It proved indistinguishable, in shell and anatomy, from topotypic Physa cubensis Pfeiffer, 1839, thus leading the authors to admit the synonymy of the two nominal species under the older name, P. acuta.

Hemilucilia segmentaria (Fabricius, 1805) (Diptera: Calliphoridae) as new biological vector of eggs of Dermatobia hominis (Linnaeus Jr., 1781) (Diptera: Oestridae) in Reserva Biológica do Tinguá, Rio de Janeiro, Brazil

The aim of this note was to record for the first time the finding of Hemilucilia segmentaria acting as biological vector of Dermatobia hominis, during a study of the diversity of Calliphoridae at Reserva Biológica do Tinguá, Rio de Janeiro, Brazil. The insects were captured using traps baited with chicken vicera, for a period of 28-30 h twice per month. In the period of one year, 1987 insects were collected, 7.5% of which belonged to the H. segmentaria; of these a female was captured in May 2001, carrying a mass of 20 eggs on the left side of its abdomen.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.