Bed nucleus of the stria terminalis alpha(1) and alpha(2) adrenoceptors differentially modulate the cardiovascular responses to exercise in rats

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On the development of a test-bed application for the ART-WiSe architecture

The ART-WiSe (Architecture for Real-Time communications in Wireless Sensor Networks) framework aims at the design of new communication architectures and mechanisms for time-sensitive Wireless Sensor Networks (WSNs). We adopted a two-tiered architecture where an overlay Wireless Local Area Network (Tier 2) serves as a backbone for a WSN (Tier 1), relying on existing standard communication protocols and commercial-off-the-shell (COTS) technologies – IEEE 802.15.4/ZigBee for Tier 1 and IEEE 802.11 for Tier 2. In this line, a test-bed application is being developed for assessing, validating and demonstrating the ART-WiSe architecture. A pursuit-evasion application was chosen since it fulfils a number of requirements, namely it is feasible and appealing and imposes some stress to the architecture in terms of timeliness. To develop the testbed based on the previously referred technologies, an implementation of the IEEE 8021.5.4/ZigBee protocols is being carried out, since there is no open source available to the community. This paper highlights some relevant aspects of the ART-WiSe architecture, provides some intuition on the protocol stack implementation and presents a general view over the envisaged test-bed application.

On a test-bed application for the ART-WiSe framework

This report describes the development of a Test-bed Application for the ART-WiSe Framework with the aim of providing a means of access, validate and demonstrate that architecture. The chosen application is a kind of pursuit-evasion game where a remote controlled robot, navigating through an area covered by wireless sensor network (WSN), is detected and continuously tracked by the WSN. Then a centralized control station takes the appropriate actions for a pursuit robot to chase and “capture” the intruder one. This kind of application imposes stringent timing requirements to the underlying communication infrastructure. It also involves interesting research problems in WSNs like tracking, localization, cooperation between nodes, energy concerns and mobility. Additionally, it can be easily ported into a real-world application. Surveillance or search and rescue operations are two examples where this kind of functionality can be applied. This is still a first approach on the test-bed application and this development effort will be continuously pushed forward until all the envisaged objectives for the Art-WiSe architecture become accomplished.

Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework

Aim The aim of this study was to test different modelling approaches, including a new framework, for predicting the spatial distribution of richness and composition of two insect groups. Location The western Swiss Alps. Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained fromindividual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly process in a unique modelling procedure. We used: (1) five methods to create bS-SDM predictions; (2) two approaches for predicting species richness, by summing individual SDM probabilities or by modelling the number of species (i.e. richness) directly; and (3) five different biotic rules based either on ranking probabilities from SDMs or on community co-occurrence patterns. Combining these various options resulted in 47 implementations for each taxon. Results Species richness of the two taxonomic groups was predicted with good accuracy overall, and in most cases bS-SDM did not produce a biased prediction exceeding the actual number of species in each unit. In the prediction of community composition bS-SDM often also yielded the best evaluation score. In the case of poor performance of bS-SDM (i.e. when bS-SDM overestimated the prediction of richness) the SESAM framework improved predictions of species composition. Main conclusions Our results differed from previous findings using community-level models. First, we show that overprediction of richness by bS-SDM is not a general rule, thus highlighting the relevance of producing good individual SDMs to capture the ecological filters that are important for the assembly process. Second, we confirm the potential of SESAM when richness is overpredicted by bS-SDM; limiting the number of species for each unit and applying biotic rules (here using the ranking of SDM probabilities) can improve predictions of species composition