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

Desenvolvimento de dispositivos microfluídicos 3D em papel para utilização em biossensores

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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

Produção de espumas 3D porosas por auto-organização de nanofibras de policaprolactona

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Cancer theranostics: multifunctional gold nanoparticles for diagnostics and therapy

Doctorate in Biology, Specialty in Biotechnology

Evaluation of chemotherapeutic potential of natural extracts using 3D models of colon cancer

Dissertation to obtain master degree in Biotechnology

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

Modelação 3D de teores de depósitos minerais condicionados por tipos de mineralização. O caso de estudo do depósito mineral do Zambujal, Minas de Neves-Corvo

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

Estruturas 3D porosas com gradiente de funcionalidade produzidas por Freeze-casting

Dissertação para obtenção do Grau de Mestre em Engenharia de Materiais

A nanopore-based stochastic detection method: Single molecule characterisation of nanoparticles using ()- hemolysin

Dissertation presented to obtain the Ph.D degree in Chemistry.

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.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

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.

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.