Carbon nanotubes as reinforcement of cellulose liquid crystalline responsive networks

The incorporation of small amount of highly anisotropic nanoparticles into liquid crystalline hydroxypropylcellulose (LC-HPC) matrix improves its response when is exposed to humidity gradients due to an anisotropic increment of order in the structure. Dispersed nanoparticles give rise to faster order/disorder transitions when exposed to moisture as it is qualitatively observed and quantified by stress-time measurements. The presence of carbon nanotubes derives in a improvement of the mechanical properties of LC-HPC thin films.

Sparse matrix multiplication on a reconfigurable many-core architecture

Sparse matrix-vector multiplication (SMVM) is a fundamental operation in many scientific and engineering applications. In many cases sparse matrices have thousands of rows and columns where most of the entries are zero, while non-zero data is spread over the matrix. This sparsity of data locality reduces the effectiveness of data cache in general-purpose processors quite reducing their performance efficiency when compared to what is achieved with dense matrix multiplication. In this paper, we propose a parallel processing solution for SMVM in a many-core architecture. The architecture is tested with known benchmarks using a ZYNQ-7020 FPGA. The architecture is scalable in the number of core elements and limited only by the available memory bandwidth. It achieves performance efficiencies up to almost 70% and better performances than previous FPGA designs.

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Mucosal leishmaniasis ("espundia") responsive to low dose of N-methyl glucamine (Glucantime ®) in Rio de Janeiro, Brazil

Response to treatment with antimonial drugs varies considerably depending on the parasite strain involved, immune status of the patient and clinical form of the disease. Therapeutic regimens with this first line drug have been frequently modified both, in dose and duration of therapy. A regimen of 20 mg/kg/day of pentavalent antimony (Sb5+) during four weeks without an upper limit on the daily dose is currently recommended for mucosal disease ("espundia"). Side-effects with this dose are more marked in elderly patients, more commonly affected by this form of leishmaniasis. According to our experience, leishmaniasis in Rio de Janeiro responds well to antimony and, in cutaneous disease, high cure rates are obtained with 5 mg/kg/day of Sb5+ during 30 to 45-days. In this study a high rate of cure (91.4%) employing this dose was achieved in 36 patients with mild disease in this same geographic region. Side-effects were reduced and no antimony refractoriness was noted with subsequent use of larger dose in patients that failed to respond to initial schedule.

TEA: Timing and Energy Aware compression architecture for Efficient Configuration in CGRAs

Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

Protein-responsive polymers for point-of-care detection of cardiac biomarker

This work describes a novel use for the polymeric film, poly(o-aminophenol) (PAP) that was made responsive to a specific protein. This was achieved through templated electropolymerization of aminophenol (AP) in the presence of protein. The procedure involved adsorbing protein on the electrode surface and thereafter electroploymerizing the aminophenol. Proteins embedded at the outer surface of the polymeric film were digested by proteinase K and then washed away thereby creating vacant sites. The capacity of the template film to specifically rebind protein was tested with myoglobin (Myo), a cardiac biomarker for ischemia. The films acted as biomimetic artificial antibodies and were produced on a gold (Au) screen printed electrode (SPE), as a step towards disposable sensors to enable point-of-care applications. Raman spectroscopy was used to follow the surface modification of the Au-SPE. The ability of the material to rebind Myo was measured by electrochemical techniques, namely electrochemical impedance spectroscopy (EIS) and square wave voltammetry (SWV). The devices displayed linear responses to Myo in EIS and SWV assays down to 4.0 and 3.5 μg/mL, respectively, with detection limits of 1.5 and 0.8 μg/mL. Good selectivity was observed in the presence of troponin T (TnT) and creatine kinase (CKMB) in SWV assays, and accurate results were obtained in applications to spiked serum. The sensor described in this work is a potential tool for screening Myo in point-of-care due to the simplicity of fabrication, disposability, short time response, low cost, good sensitivity and selectivity.

A Novel Run-Time Monitoring Architecture for Safe and Efficient Inline Monitoring

20th International Conference on Reliable Software Technologies - Ada-Europe 2015 (Ada-Europe 2015), Madrid, Spain.

A module for the XDense architecture in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.

A Novel Runtime Monitoring Architecture

Poster presented in 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 25 to 28, Mar, 2015, Poster Session. Porto, Portugal.

Treatment of chronic hepatitis C in non-responsive patients with pegylated interferon associated with ribavirin and thalidomide: report of six cases of total remission

Hepatitis C virus (HCV) infection is an important public health issue worldwide. It is estimated that over 170 million people are infected with the virus. The present study reports six cases in which patients did not respond to combination therapy with pegylated interferon and ribavirin. However, after the addition of thalidomide to the therapy, the patients presented negative RNA PCR. The use of thalidomide combined with pegylated interferon and ribavirin for the treatment of hepatitis C is described here for the first time in the related literature.

Architecture to Support Quality of Service in Arrowhead Systems

Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Covilhã, Portugal.

Run-time Monitoring Architecture for RealTime Systems

Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Portugal.

Regulation of autoimmune neuroinflammation by stress-responsive genes

Dissertation presented to obtain the Ph.D degree in Biology