Towards the design of efficient nonbeacon-enabled ZigBee networks

This paper presents experimental results of the communication performance evaluation of a prototype ZigBee-based patient monitoring system commissioned in an in-patient floor of a Portuguese hospital (HPG – Hospital Privado de Guimar~aes). Besides, it revisits relevant problems that affect the performance of nonbeacon-enabled ZigBee networks. Initially, the presence of hidden-nodes and the impact of sensor node mobility are discussed. It was observed, for instance, that the message delivery ratio in a star network consisting of six wireless electrocardiogram sensor devices may decrease from 100% when no hidden-nodes are present to 83.96% when half of the sensor devices are unable to detect the transmissions made by the other half. An additional aspect which affects the communication reliability is a deadlock condition that can occur if routers are unable to process incoming packets during the backoff part of the CSMA-CA mechanism. A simple approach to increase the message delivery ratio in this case is proposed and its effectiveness is verified. The discussion and results presented in this paper aim to contribute to the design of efficient networks,and are valid to other scenarios and environments rather than hospitals.

Stress affects theta activity in limbic networks and impairs novelty-induced exploration and familiarization

Exposure to a novel environment triggers the response of several brain areas that regulate emotional behaviors. Here, we studied theta oscillations within the hippocampus (HPC)-amygdala (AMY)-medial prefrontal cortex (mPFC) network in exploration of a novel environment and subsequent familiarization through repeated exposures to that same environment; in addition, we assessed how concomitant stress exposure could disrupt this activity and impair both behavioral processes. Local field potentials were simultaneously recorded from dorsal and ventral hippocampus (dHPC and vHPC respectively), basolateral amygdala (BLA) and mPFC in freely behaving rats while they were exposed to a novel environment, then repeatedly re-exposed over the course of 3 weeks to that same environment and, finally, on re-exposure to a novel unfamiliar environment. A longitudinal analysis of theta activity within this circuit revealed a reduction of vHPC and BLA theta power and vHPC-BLA theta coherence through familiarization which was correlated with a return to normal exploratory behavior in control rats. In contrast, a persistent over-activation of the same brain regions was observed in stressed rats that displayed impairments in novel exploration and familiarization processes. Importantly, we show that stress also affected intra-hippocampal synchrony and heightened the coherence between vHPC and BLA. In summary, we demonstrate that modulatory theta activity in the aforementioned circuit, namely in the vHPC and BLA, is correlated with the expression of anxiety in novelty-induced exploration and familiarization in both normal and pathological conditions.

Temperature dependence of the electrical conductivity of vapor grown carbon nanofiber/epoxy composites with different filler dispersion levels

The influence of the dispersion of vapor grown carbon nanofibers (VGCNF) on the electrical properties of VGCNF/epoxy composites has been studied. A homogeneous dispersion of the VGCNF does not imply better electrical properties. The presence of well distributed clusters appears to be a key factor for increasing composite conductivity. It is also shown that the main conduction mechanism has an ionic nature for concentrations below the percolation threshold, while above the percolation threshold it is dominated by hopping between the fillers. Finally, using the granular system theory it is possible to explain the origin of conduction at low temperatures.

The role of disorder on the AC and DC electrical conductivity of vapour grown carbon nanofibre/epoxy composites

Four dispersion methods were used for the preparation of vapour grown carbon nanofibre (VGCNF)/epoxy composites. It is shown that each method induces certain levels of VGCNF dispersion and distribution within the matrix, and that these have a strong influence on the composite electrical properties. A homogenous VGCNF dispersion does not necessarily imply higher electrical conductivity. In fact, it is concluded that the presence of well distributed clusters, rather than a fine dispersion, is more important for achieving larger conductivities for a given VGCNF concentration. It is also found that the conductivity can be described by a weak disorder regime.

A Platform to Emulate Ambient Assisted Living Environments

According to the opinion of clinicians, emerging medical conditions can be timely detected by observing changes in the activities of daily living and/or in the physiological signals of a person. To accomplish such purpose, it is necessary to properly monitor both the person’s physiological signals as well as the home environment with sensing technology. Wireless sensor networks (WSNs) are a promising technology for this support. After receiving the data from the sensor nodes, a computer processes the data and extracts information to detect any abnormality. The computer runs algorithms that should have been previously developed and tested in real homes or in living-labs. However, these installations (and volunteers) may not be easily available. In order to get around that difficulty, this paper suggests the making of a physical model to emulate basic actions of a user at home, thus giving autonomy to researchers wanting to test the performance of their algorithms. This paper also studies some data communication issues in mobile WSNs namely how the orientation of the sensor nodes in the body affects the received signal strength, as well as retransmission aspects of a TDMA-based MAC protocol in the data recovery process.

The need for standardized tests to evaluate the reliability of data transport in wireless medical systems

Wireless medical systems are comprised of four stages, namely the medical device, the data transport, the data collection and the data evaluation stages. Whereas the performance of the first stage is highly regulated, the others are not. This paper concentrates on the data transport stage and argues that it is necessary to establish standardized tests to be used by medical device manufacturers to provide comparable results concerning the communication performance of the wireless networks used to transport medical data. Besides, it suggests test parameters and procedures to be used to produce comparable communication performance results.

Applying complex network theory to the understanding of high-aspect-ratio carbon-filled composites

This work demonstrates that the theoretical framework of complex networks typically used to study systems such as social networks or the World Wide Web can be also applied to material science, allowing deeper understanding of fundamental physical relationships. In particular, through the application of the network theory to carbon nanotubes or vapour-grown carbon nanofiber composites, by mapping fillers to vertices and edges to the gap between fillers, the percolation threshold has been predicted and a formula that relates the composite conductance to the network disorder has been obtained. The theoretical arguments are validated by experimental results from the literature.

The influence of the dispersion method on the electrical properties of vapor-grown carbon nanofiber/epoxy composites

The influence of the dispersion of vapor-grown carbon nanofibers (VGCNF) on the electrical properties of VGCNF/ Epoxy composites has been studied. A homogenous dispersion of the VGCNF does not imply better electrical properties. In fact, it is demonstrated that the most simple of the tested dispersion methods results in higher conductivity, since the presence of well-distributed nanofiber clusters appears to be a key factor for increasing composite conductivity.

Chronic stress disrupts neural coherence between cortico-limbic structures

Chronic stress impairs cognitive function, namely on tasks that rely on the integrity of cortico-limbic networks. To unravel the functional impact of progressive stress in cortico-limbic networks we measured neural activity and spectral coherences between the ventral hippocampus (vHIP) and the medial prefrontal cortex (mPFC) in rats subjected to short term stress (STS) and chronic unpredictable stress (CUS). CUS exposure consistently disrupted the spectral coherence between both areas for a wide range of frequencies, whereas STS exposure failed to trigger such effect. The chronic stress-induced coherence decrease correlated inversely with the vHIP power spectrum, but not with the mPFC power spectrum, which supports the view that hippocampal dysfunction is the primary event after stress exposure. Importantly, we additionally show that the variations in vHIP-to-mPFC coherence and power spectrum in the vHIP correlated with stress-induced behavioral deficits in a spatial reference memory task. Altogether, these findings result in an innovative readout to measure, and follow, the functional events that underlie the stress-induced reference memory impairments.

PHB-PEO electrospun fiber membranes containing chlorhexidine for drug delivery applications

Fiber meshes of poly(hydroxybutyrate) (PHB) and poly(hydroxybutyrate)/ poly(ethylene oxide) (PHB/PEO) with different concentrations of chlorhexidine (CHX) were prepared by electrospinning, for assessment as a polymer based drug delivery system. The electrospun fibers were characterized at morphological, molecular and mechanical levels. The bactericidal potential of PHB and PHB/PEO electrospun fibers with and without CHX was investigated against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by disk diffusion susceptibility tests. Electrospun fibers containing CHX exhibited bactericidal activity. PHB/PEO-1%CHX displayed higher CHX release levels and equivalent antibacterial activity when compared to PHB/PEO with 5 and 10 wt% CHX. Bactericidal performance of samples with 1 wt% CHX was assessed by Colony Forming Units (CFU), where a reduction of 100 % and 99.69 % against E. coli and S. aureus were achieved, respectively.

Effect of neutralization and cross-linking on the thermal degradation of chitosan electrospun membranes

Thermal degradation of as electrospun chitosan membranes and samples subsequently treated with ethanol and cross-linked with glutaraldehyde (GA) have been studied by thermogravimetry (TG) coupled with an infrared spectrometer (FTIR). The influence of the electrospinning process and cross-linking in the electrospun chitosan thermal stability was evaluated. Up to three degradation steps were observed in the TG data, corresponding to water dehydration reaction at temperatures below 100 ºC, loss of side groups formed between the amine groups of chitosan and trifluoroacetic acid between 150 – 270 ºC and chitosan thermal degradation that starts around 250 ºC and goes up to 400 ºC. The Kissinger model was employed to evaluate the activation energies of the electrospun membranes during isothermal experiments and revealed that thermal degradation activation energy increases for the samples processed by electrospinning and subsequent neutralization and cross-linking treatments with respect to the neat chitosan powder.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Produto Aquaoli: projeto de design industrial em aquariofilia

Esta dissertação de mestrado, apresenta a elaboração de um projeto de design industrial em aquariofilia - Aquaoli. Pretende-se criar uma nova tipologia de aquários inovadora e distinta, projetando o produto com o intuito deste cumprir com todos os parâmetros exigidos pelo mercado e produção do mesmo. Definiu-se a criança entre os 7 e os 11 anos como público-alvo deste projeto. Assim, pretende-se um resultando promissor para a empresa AQUATLANTIS apostar e lucrar com o seu desenvolvimento. Para que este projeto obtivesse bons resultados, foi realizada uma pesquisa aprofundada, desde a aquariofilia (a sua história, biologia e mercado), do aquariófilo atual (psicologia do consumidor e as suas responsabilidades), até ao estado da arte (da AQUATLANTIS e dos produtos existentes no mercado). Este projeto foi desenvolvido em várias vertentes de design, procurando ser o mais completo possível. Isso foi viável com o desenvolvimento do produto e de todos os seus componentes em três dimensões, o desenvolvimento de maquetes e de protótipos do produto, o desenvolvimento do packaging e campanha promocional, a definição de preço custo e métodos de produção dos objetos, entre outros parâmetros. Obteve-se um projeto de design industrial bastante completo e com potencial para ser implementado no mercado, cativando a atenção do público-alvo e obtendo vendas elevadas. O aquário apresenta-se distinto dos existentes, principalmente no facto de ser modular, muito interativo, pedagógico e incorporar uma estrutura invulgar e particularmente cativante para as crianças. Este produto subdivide-se em dois conjuntos vendidos separadamente (Aquarium Pack e Kit-1 Pack), apresentando assim uma estratégia de marketing que pretende que a criança que o adquira pela primeira vez, venha a desejar adquirir mais produtos desta gama, procurando aumentar a sua estante e/ou o número de aquários e animais que incorpora na mesma.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.