A Step-up mu-Power Converter for Solar Energy Harvesting Applications, using Hill Climbing Maximum Power Point Tracking

This paper presents a step-up micro-power converter for solar energy harvesting applications. The circuit uses a SC voltage tripler architecture, controlled by an MPPT circuit based on the Hill Climbing algorithm. This circuit was designed in a 0.13 mu m CMOS technology in order to work with an a-Si PV cell. The circuit has a local power supply voltage, created using a scaled down SC voltage tripler, controlled by the same MPPT circuit, to make the circuit robust to load and illumination variations. The SC circuits use a combination of PMOS and NMOS transistors to reduce the occupied area. A charge re-use scheme is used to compensate the large parasitic capacitors associated to the MOS transistors. The simulation results show that the circuit can deliver a power of 1266 mu W to the load using 1712 mu W of power from the PV cell, corresponding to an efficiency as high as 73.91%. The simulations also show that the circuit is capable of starting up with only 19% of the maximum illumination level.

Damage detection and quantification using transmissibility

Structures experience various types of loads along their lifetime, which can be either static or dynamic and may be associated to phenomena of corrosion and chemical attack, among others. As a consequence, different types of structural damage can be produced; the deteriorated structure may have its capacity affected, leading to excessive vibration problems or even possible failure. It is very important to develop methods that are able to simultaneously detect the existence of damage and to quantify its extent. In this paper the authors propose a method to detect and quantify structural damage, using response transmissibilities measured along the structure. Some numerical simulations are presented and a comparison is made with results using frequency response functions. Experimental tests are also undertaken to validate the proposed technique. (C) 2011 Elsevier Ltd. All rights reserved.

Detection of Change in Fluorescence Between Reactive Cyan and the Yellow Fluorophores Usinga-SiC:H Multilayer Transducers

Optical colour sensors based on multilayered a-SiC:H heterostructures can act as voltage controlled optical filters in the visible range. In this article we investigate the application of these structures for Fluorescence Resonance Energy Transfer (FRET) detection, The characteristics of a-SiC:H multilayered structure are studied both theoretically and experimentally in several wavelengths corresponding to different fluorophores. The tunable optical p-i'(a-SiC:H)-n/p-i(a-Si:H)-n heterostructures were produced by PECVD and tested for a proper fine tuning in the violet, cyan and yellow wavelengths. The devices were characterized through transmittance and spectral response measurements, under different electrical bias and frequencies. Violet, cyan and yellow signals were applied in simultaneous and results have shown that they can be recovered under suitable applied bias. A theoretical analysis supported by numerical simulation is presented.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Detection of pathogens from periodontal lesions

OBJECTIVE: To comparatively detect A. actinomycetemcomitans and F. nucleatum from periodontal and healthy sites. METHODS: Subgingival clinical samples from 50 periodontitis adult patients and 50 healthy subjects were analyzed. Both organisms were isolated using a trypticase soy agar-bacitracin-vancomycin (TSBV) medium and detected by PCR. Conventional biochemical tests were used for bacteria identification. RESULTS: A. actinomycetemcomitans and F. nucleatum were isolated in 18% and 20% of the patients, respectively, and in 2% and 24% of healthy subjects. Among A. actinomycetemcomitans isolates, biotype II was the most prevalent. Primer pair AA was 100% sensitive in the detection of A. actinomycetemcomitans from both subject groups. Primers ASH and FU were also 100% sensitive to detect this organism in healthy subject samples. Primer pair FN5047 was more sensitive to detect F. nucleatum in patients or in healthy samples than primer 5059S. Primers ASH and 5059S were more specific in the detection of A. actinomycetemcomitans and F. nucleatum, respectively, in patients and in healthy subject samples. CONCLUSIONS: PCR is an effective tool for detecting periodontal pathogens in subgingival samples, providing a faster and safer diagnostic tool of periodontal diseases. The method's sensitivity and specificity is conditioned by the choice of the set of primers used.

Caminhamento fotogramétrico com arranjo triangular de câmaras fotográficas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Novel method using a laser scanning cytometer for detection of Mycobacteria in clinical samples

In order to evaluate the capacity of laser scanning cytometry (LSC) to detect acid-fast bacilli directly on clinical samples, a comparison between Kinyoun-stained smears analyzed under light microscopy and propidium iodide-auramine-stained smears analyzed by LSC was performed. The results were compared with those for culture on BACTEC MGIT 960. LSC is a new, reliable methodology to detect Mycobacteria.

Identificação e análise de movimento humano com ultrassons

Faz-se nesta dissertação a análise do movimento humano utilizando sinais de ultrassons refletidos pelos diversos membros do corpo humano, designados por assinaturas de ultrassons. Estas assinaturas são confrontadas com os sinais gerados pelo contato dos membros inferiores do ser humano com o chão, recolhidos de forma passiva. O método seguido teve por base o estudo das assinaturas de Doppler e micro-Doppler. Estas assinaturas são obtidas através do processamento dos ecos de ultrassons recolhidos, com recurso à Short-Time Fourier Transform e apresentadas sobre a forma de espectrograma, onde se podem identificar os desvios de frequência causados pelo movimento das diferentes partes do corpo humano. É proposto um algoritmo inovador que, embora possua algumas limitações, é capaz de isolar e extrair de forma automática algumas das curvas e parâmetros característicos dos membros envolvidos no movimento humano. O algoritmo desenvolvido consegue analisar as assinaturas de micro-Doppler do movimento humano, estimando diversos parâmetros tais como o número de passadas realizadas, a cadência da passada, o comprimento da passada, a velocidade a que o ser humano se desloca e a distância percorrida. Por forma a desenvolver, no futuro, um classificador capaz de distinguir entre humanos e outros animais, são também recolhidas e analisadas assinaturas de ultrassons refletidas por dois animais quadrúpedes, um canino e um equídeo. São ainda estudadas as principais características que permitem classificar o tipo de animal que originou a assinatura de ultrassons. Com este estudo mostra-se ser possível a análise de movimento humano por ultrassons, havendo características nas assinaturas recolhidas que permitem a classificação do movimento como humano ou não humano. Do trabalho desenvolvido resultou ainda uma base de dados de assinaturas de ultrassons de humanos e animais que permitirá suportar trabalho de investigação e desenvolvimento futuro.

Sensing Cloud Optimization to Solve ED of Units with Valve-Point Effects and Multi-fuels

In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors "to fill" the search space and "guide" the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.

Detection of Change in Fluorescence Between Reactive Cyan and the Yellow Fluorophores Using a-SiC:H Multilayer Transducers

The transducer consists of a semiconductor device based on two stacked -i-n heterostructures that were designed to detect the emissions of the fluorescence resonance energy transfer between fluorophores in the cyan (470 nm) and yellow (588 nm) range of the spectrum. This research represents a preliminary study on the use of such wavelength-sensitive devices as photodetectors for this kind of application. The device was characterized through optoelectronic measurements concerning spectral response measurements under different electrical and optical biasing conditions. To simulate the fluorescence resonance energy transfer (FRET) pairs, a chromatic time-dependent combination of cyan and yellow wavelengths was applied to the device. The generated photocurrent was measured under reverse and forward bias to read out the output photocurrent signal. A different wavelength-biasing light was also superimposed. Results show that under reverse bias, the photocurrent signal presents four separate levels, each one assigned to the different wavelength combinations of the FRET pairs. If a blue background is superimposed, the yellow channel is enhanced and the cyan suppressed, while under red irradiation, the opposite behavior occurs. So, under suitable biasing light, the transducer is able to detect separately the cyan and yellow fluorescence pairs. An electrical model, supported by a numerical simulation, supports the transduction mechanism of the device.

Detection of FRET signals with a wavelength sensitive device based on a-SiC:H

Glucose sensing is an issue with great interest in medical and biological applications. One possible approach to glucose detection takes advantage of measuring changes in fluorescence resonance energy transfer (FRET) between a fluorescent donor and an acceptor within a protein which undergoes glucose-induced changes in conformation. This demands the detection of fluorescent signals in the visible spectrum. In this paper we analyzed the emission spectrum obtained from fluorescent labels attached to a protein which changes its conformation in the presence of glucose using a commercial spectrofluorometer. Different glucose nanosensors were used to measure the output spectra with fluorescent signals located at the cyan and yellow bands of the spectrum. A new device is presented based on multilayered a-SiC:H heterostructures to detect identical transient visible signals. The transducer consists of a p-i'(a-SiC:H)-n/p-i(a-Si:H)-n heterostructure optimized for the detection of the fluorescence resonance energy transfer between fluorophores with excitation in the violet (400 nm) and emissions in the cyan (470 nm) and yellow (588 nm) range of the spectrum. Results show that the device photocurrent signal measured under reverse bias and using appropriate steady state optical bias, allows the separate detection of the cyan and yellow fluorescence signals. (C) 2013 Elsevier B.V. All rights reserved.

Implementação, validação e análise técnico-económico de alguns parâmetros analíticos no controlo de águas

Mestrado em Engenharia Química

Celiac disease detection using a transglutaminase electrochemical immunosensor fabricated on nanohybrid screen-printed carbon electrodes

Celiac disease is a gluten-induced autoimmune enteropathy characterized by the presence of tissue tranglutaminase (tTG) autoantibodies. A disposable electrochemical immunosensor (EI) for the detection of IgA and IgG type anti-tTG autoantibodies in real patient’s samples is presented. Screen-printed carbon electrodes (SPCE) nanostructurized with carbon nanotubes and gold nanoparticles were used as the transducer surface. This transducer exhibits the excellent characteristics of carbon–metal nanoparticle hybrid conjugation and led to the amplification of the immunological interaction. The immunosensing strategy consisted of the immobilization of tTG on the nanostructured electrode surface followed by the electrochemical detection of the autoantibodies present in the samples using an alkaline phosphatase (AP) labelled anti-human IgA or IgG antibody. The analytical signal was based on the anodic redissolution of enzymatically generated silver by cyclic voltammetry. The results obtained were corroborated with a commercial ELISA kit indicating that the electrochemical immunosensor is a trustful analytical screening tool.

Molecular imprinted nanoelectrodes for ultra sensitive detection of ovarian cancer marker

The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.

Voltammetric immunosensor for the diagnosis of celiac disease based on the quantification of anti-gliadin antibodies

Antibodies against gliadin are used to detect celiac disease (CD) in patients. An electrochemical immunosensor for the voltammetric detection of human anti-gliadin antibodies (AGA) IgA and AGA IgG in real serum samples is proposed. The transducer surface consists of screen-printed carbon electrodes modified with a carbon nanotube/gold nanoparticle hybrid system, which provides a very useful surface for the amplification of the immunological interactions. The immunosensing strategy is based on the immobilization of gliadin, the antigen for the autoantibodies of interest, onto the nanostructured surface. The antigen–antibody interaction is recorded using alkaline phosphatase labeled anti-human antibodies and a mixture of 3-indoxyl phosphate with silver ions (3-IP/Ag+) was used as the substrate. The analytical signal is based on the anodic redissolution of the enzymatically generated silver by cyclic voltammetry. The electrochemical behavior of this immunosensor was carefully evaluated assessing aspects as sensitivity, non-specific binding and matrix effects, and repeatability and reproducibility. The results were supported with a commercial ELISA test.