Time series morphological analysis applied to biomedical signals events detection

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

Bacterial peptidoglycan biosynthesis and recognition by the innate immune system

Dissertation presented to obtain the Ph.D degree in Biology

Gold nanoprobes for the detection of mutations associated with antibiotic resistance in Mycobacterium tuberculosis complex

Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

Production of polyhydroxyalkanoates from cheese whey - pH effect on the acidogenic fermentation stage and nutrient needs of the culture selection stage

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Studies on the wine spoilage yeast Brettanomyces bruxellensis: 4-ethylphenol production and improved detection

Dissertação para obtenção do Grau de Mestre em Biotecnologia

A low-voltage RF-CMOS receiver front-end for a wireless fall detection microsystem

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores, pela Universidade Nova de Ciências e Tecnologia

The Biotransformation of Pentachlorophenol by Mucor plumbeus: Mechanistic Insights

Dissertation presented to obtain the Ph.D degree in Biochemistry

A volumetric hybrid representation for obstacle detection in all-terrain robots

This dissertation presents an approach aimed at three-dimensional perception’s obstacle detection on all-terrain robots. Given the huge amount of acquired information, the adversities such environments present to an autonomous system and the swiftness, thus required, from each of its navigation decisions, it becomes imperative that the 3-D perceptional system to be able to map obstacles and passageways in the most swift and detailed manner. In this document, a hybrid approach is presented bringing the best of several methods together, combining the lightness of lesser meticulous analyses with the detail brought by more thorough ones. Realizing the former, a terrain’s slope mapping system upon a low resolute volumetric representation of the surrounding occupancy. For the latter’s detailed evaluation, two novel metrics were conceived to discriminate the little depth discrepancies found in between range scanner’s beam distance measurements. The hybrid solution resulting from the conjunction of these two representations provides a reliable answer to traversability mapping and a robust discrimination of penetrable vegetation from that constituting real obstructions. Two distinct robotic platforms offered the possibility to test the hybrid approach on very different applications: a boat, under an European project, the ECHORD Riverwatch, and a terrestrial four-wheeled robot for a national project, the Introsys Robot.

A semi-automatic approach to code smells detection

Eradication of code smells is often pointed out as a way to improve readability, extensibility and design in existing software. However, code smell detection remains time consuming and error-prone, partly due to the inherent subjectivity of the detection processes presently available. In view of mitigating the subjectivity problem, this dissertation presents a tool that automates a technique for the detection and assessment of code smells in Java source code, developed as an Eclipse plugin. The technique is based upon a Binary Logistic Regression model that uses complexity metrics as independent variables and is calibrated by expert‟s knowledge. An overview of the technique is provided, the tool is described and validated by an example case study.

Transimpedance amplifier for early detection of breast cancer

Breast cancer is the most common type of cancer worldwide. The effectiveness of its treatment depends on early stage detection, as well as on the accuracy of its diagnosis. Recently, diagnosis techniques have been submitted to relevant breakthroughs with the upcoming of Magnetic Resonance Imaging, Ultrasound Sonograms and Positron Emission Tomography (PET) scans, among others. The work presented here is focused on studying the application of a PET system to a Positron Emission Mammography (PEM) system. A PET/PEM system works under the principle that a scintillating crystal will detect a gamma-ray pulse, originated at the cancerous cells, converting it into a correspondent visible light pulse. The latter must then be converted into an electrical current pulse by means of a Photo- -Sensitive Device (PSD). After the PSD there must be a Transimpedance Amplifier (TIA) in order to convert the current pulse into a suitable output voltage, in a time period lower than 40 ns. In this Thesis, the PSD considered is a Silicon Photo-Multiplier (SiPM). The usage of this recently developed type of PSD is impracticable with the conventional TIA topologies, as it will be proven. Therefore, the usage of the Regulated Common-Gate (RCG) topology will be studied in the design of the amplifier. There will be also presented two RCG variations, comprising a noise response improvement and differential operation of the circuit. The mentioned topology will also be tested in a Radio-Frequency front-end, showing the versatility of the RCG. A study comprising a low-voltage self-biasing feedback TIA will also be shown. The proposed circuits will be simulated with standard CMOS technology (UMC 130 nm), using a 1.2 V power supply. A power consumption of 0.34 mW with a signal-to-noise ratio of 43 dB was achieved.

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Immunohistochemistry detection of putative miR-200c and miR-203 targets in breast cancer patients

Part of this thesis will be published in the following: Gomes, B.C., Santos, B. 2015. Methods for studying microRNAs expression and their targets in formalin-fixed, paraffin-embedded (FFPE) breast cancer tissues. In Methods in Molecular Biology: Cancer Drug Resistance (Rueff, J. & Rodrigues, A.S. eds), Springer Protocols.

Gold nanoparticles for the detection of DNA adducts as biomarkers of exposure to acrylamide

The main objective of this thesis was the development of a gold nanoparticle-based methodology for detection of DNA adducts as biomarkers, to try and overcome existing drawbacks in currently employed techniques. For this objective to be achieved, the experimental work was divided in three components: sample preparation, method of detection and development of a model for exposure to acrylamide. Different techniques were employed and combined for de-complexation and purification of DNA samples (including ultrasonic energy, nuclease digestion and chromatography), resulting in a complete protocol for sample treatment, prior to detection. The detection of alkylated nucleotides using gold nanoparticles was performed by two distinct methodologies: mass spectrometry and colorimetric detection. In mass spectrometry, gold nanoparticles were employed for laser desorption/ionisation instead of the organic matrix. Identification of nucleotides was possible by fingerprint, however no specific mass signals were denoted when using gold nanoparticles to analyse biological samples. An alternate method using the colorimetric properties of gold nanoparticles was employed for detection. This method inspired in the non-cross-linking assay allowed the identification of glycidamide-guanine adducts and DNA adducts generated in vitro. For the development of a model of exposure, two different aquatic organisms were studies: a goldfish and a mussel. Organisms were exposed to waterborne acrylamide, after which mortality was recorded and effect concentrations were estimated. In goldfish, both genotoxicity and metabolic alterations were assessed and revealed dose-effect relationships of acrylamide. Histopathological alterations were verified primarily in pancreatic cells, but also in hepatocytes. Mussels showed higher effect concentrations than goldfish. Biomarkers of oxidative stress, biotransformation and neurotoxicity were analysed after prolonged exposure, showing mild oxidative stress in mussel cells, and induction of enzymes involved in detoxification of oxygen radicals. A qualitative histopathological screening revealed gonadotoxicity in female mussels, which may present some risk to population equilibrium.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

Design of a CMOS amplifier for breast cancer detection

A transimpedance amplifier (TIA) is used, in radiation detectors like the positron emission tomography(PET), to transform the current pulse produced by a photo-sensitive device into an output voltage pulse with a desired amplitude and shape. The TIA must have the lowest noise possible to maximize the output. To achieve a low noise, a circuit topology is proposed where an auxiliary path is added to the feedback TIA input, In this auxiliary path a differential transconductance block is used to transform the node voltage in to a current, this current is then converted to a voltage pulse by a second feedback TIA complementary to the first one, with the same amplitude but 180º out of phase with the first feedback TIA. With this circuit the input signal of the TIA appears differential at the output, this is used to try an reduced the circuit noise. The circuit is tested with two different devices, the Avalanche photodiodes (APD) and the Silicon photomultiplier (SIPMs). From the simulations we find that when using s SIPM with Rx=20kΩ and Cx=50fF the signal to noise ratio is increased from 59 when using only one feedback TIA to 68.3 when we use an auxiliary path in conjunction with the feedback TIA. This values where achieved with a total power consumption of 4.82mv. While the signal to noise ratio in the case of the SIPM is increased with some penalty in power consumption.