Trypanosoma cruzi requires a triatomine insect vector for its life cycle, which can be complex in different enzootic scenarios, one of which is the unique transmission network in the Atlantic Forest of south-eastern Brazil. In Espírito Santo (ES) State, highly infected Triatoma vitticeps are frequently reported invading domiciles. However, triatomines were not found colonizing residences and mammals in the surrounding areas did not present T. cruzi infection. To date, the biotic and abiotic variables that modulate T. vitticeps occurrence and T. cruzi infection in ES State are still unknown. The aim of this study was to identify the environmental variables that modulate their occurrence. Local thematic maps were generated for two response variables: T. vitticeps occurrence and T. cruzi infection. The following explanatory variables were tested: climate (temperature, relative air humidity and rainfall), altitude elevation, mammalian species richness as well as soil and vegetation types. Spatiotemporal distribution patterns and correlation levels between response and explanatory variables were assessed through spatial statistics and map algebra modelling. The central and southern mesoregions presented higher T. vitticeps and T. cruzi distributions and can be considered transmission hotspots. The explanatory variables that can explain these phenomena were relative air humidity, average temperature, soil type, altitude elevation and mammalian species richness. Algebra map modelling demonstrated that central and southern mesoregions presented the environmental conditions needed for T. vitticeps occurrence and T. cruzi infection. The consideration of environmental variables is essential for understanding the T. cruzi transmission cycle. Cartographic and statistical methodologies used in parasitology have been demonstrated to be reliable and enlightening tools that should be incorporated routinely to expand the understanding of vector-borne parasite transmission.

This work presents an autonomous system for marine integrated physical-chemical and biological monitoring -the MarinEye system. It comprises a set of sensors providing diverse and relevant information for oceanic environment characterization and marine biology studies. It is constituted by a physical-chemical water properties sensor suite, a water filtration and sampling system for DNA collection, a plankton imaging system and biomass assessment acoustic system.The MarinEye system has onboard computational and logging capabilities allowing it either for autonomous operation or for integration in other marine observing systems (such as Observatories or robotic vehicles. It was designed in order to collect integrated multi-trophic monitoring data.The validation in operational environment on 3 marine observatories: RAIA, BerlengasWatch and Cascais on the coast of Portugal is also discussed.

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Este artigo busca verificar a relação entre as características das interseções, o uso do solo e o número de acidentes na zona sul do Rio de Janeiro. Para tal, utilizaram-se os coeficientes de Pearson para obter a correlação das variáveis independentes entre si e com o número de acidentes. Para avaliar o quão as mesmas explicariam a distribuição dos acidentes empregaram-se dois tipos de modelos estatísticos: modelos de regressão múltipla e modelos lineares generalizados. O número de interseções semaforizadas e a extensão das vias com áreas de lazer e de uso misto apresentaram os maiores valores de correlação com o número de acidentes. No entanto, a variável extensão das vias com uso misto não foi empregada na modelagem por ser correlacionada com o número de vias semaforizadas. O modelo de regressão múltipla apresentou resultado superior ao obtido pelo modelo linear generalizado com distribuição binomial negativa.

Despite the technological advances in sensors, landmine action still causes many deaths and mutilations in several countries worldwide, and the search for efficient methods to detect mines has become a relevant issue. Thus, this work proposes a landmine detection approach using multivariate analysis of infrared (IR) images. In addition, it is proposed to monitor these images through a control chart to help identify the mine. Experiments following this approach have indicated effectiveness in the detection of landmines, enabling their safe removal.

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