Identification of atmospheric pollutants control mechanisms during co-combustion of coal and non-toxic wastes

Doctoral dissertation for Ph.D. degree in Sustainable Chemistry

Automatic information retrieval through text-mining

The dissertation presented for obtaining the Master’s Degree in Electrical Engineering and Computer Science, at Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Credit cycle identification: A Markov-switching application

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

In-School CSR and its impact on brand image, brand identification and brand reputation: The moderator effect of brand familiarity, product involvement and cause-brand fit

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Identification of Leishmania chagasi from skin in Leishmania/HIV co-infection: a case report

A case of HIV/Leishmania co-infection presenting both visceral and cutaneous manifestations is reported. Leishmania infection was confirmed by conventional methods (parasitological approach and serology) and by PCR. Leishmania chagasi isolated from the skin lesion was characterized by enzyme electrophoresis and by restriction fragment length polymorphism of the internal transcribed spacer of the ribosomal gene.

Identification of CNVs on the genome of Brazilian chicken lines.

2016

Identification and purification of immunogenic proteins from nonliving promastigote polyvalent Leishmania vaccine (Leishvacin®)

Immunogenic proteins from nonliving promastigote polyvalent Leishmania vaccine against American tegumentary leishmaniasis (Leishvacin®), produced by Biobrás (Biochemistry of Brazil ), Montes Claros, State of Minas Gerais, Brazil, were identified and purified by polyacrylamide electrophoresis gel and electroelution. C57BL/10 mice were vaccinated with proteins with estimated molecular weights of 42, 46, 63, 66, 73, 87, 97, and 160kDa in three doses of 30µg of each protein at 15-day intervals combined with 250µg of Corynebacterium parvum followed by a challenge infection with 10(5) infective promastigotes from Leishmania (Leishmania) amazonensis. The ability of these proteins to induce immune response and protection was analyzed. No statistical difference was observed in the level of IFN-g induced by proteins in vaccinated groups in comparison with control groups. Six months after challenge infection, protection levels of 28.57; 42.86; 57.14; 42.86; 42.86, 57.14; 42.86 and 57.14% were demonstrated for each purified protein.

A clustering approach for vehicle routing problems with hard time windows

Dissertação para obtenção do Grau de Mestre em Logica Computicional

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.

Spectroscopic characterization of natural dyes by their non-invasive identification on pre-Columbian codices: the Maya yellow

Mesoamerican cultures had a strong tradition of written and pictorial manuscripts, called the codices. In studies already performed it was found the use of Maya Blue, made from a mixture of indigo and a clay called palygorskite, forming an incredibly stable material where the dye is trapped inside the nanotubes of the clay, after heating. However, a bigger challenge lies in the study of the yellows used, for these civilizations might have used this clay-dye mixture to produce their yellow colorants. As a first step, it was possible to provide identification, by non-invasive methods, of two colorants (a flavonoid and a carotenoid). While the flavonoid absorbed between 368-379 nm, the carotenoid would absorb around 455 nm. A temperature study also conducted allowed to set 140ºC as the desirable temperature to heat the samples without degrading them. FT-IR, conventional Raman and SERS allowed us to understand the existence of a reaction between the dyes and the clays (palygorskite and kaolinite), however it is difficult to understand it in a molecular point of view. As a second step, five species of Mexican dyes were selected on the basis of historical sources. The Maya yellow samples were produced adapting the recipe proposed by Reyes-Valerio, supporting the yellow dyes extracted from the dried plants on the clays, with addition of water, and then heated at 140ºC. It was found that the addition of water in palygorskite would increase the pH, hence deprotonating the molecules having a clear negative effect in the color. A second recipe was developed, without the addition of water; however, it was found that the use of water based binders would still alter the color of the samples with palygorskite. In this case, kaolinite without heating yield better results as a Maya yellow hybrid. It was found that the Maya chemistry might not have been the same for all the colors. The Mesoamericans might have found that different dyes could work better to their desires if matched with different clays. It was noticeable that for a clear distinction between flavonoids and carotenoids the reflectance and emission studies suffice, but when clay is added, Raman techniques will perform better. For this reason, conventional Raman and SERS were employed in order to create a database for the Mesoamerican dyestuffs for a future identification.

Identification and differentiation of Candida species from pediatric patients by random amplified polymorphic DNA

Thirty-four Candida isolates were analyzed by random amplified polymorphic DNA using the primer OPG-10:24 Candida albicans; 4 Candida tropicalis; 2 Candida parapsilosis; 2 Candida dubliniensis; 1 Candida glabrata and 1 Candida krusei. The UPGMA-Pearson correlation coefficient was used to calculate the genetic distance between the different Candida groupings. Samples were classified as identical (correlation of 100%); highly related samples (90%); moderately related samples (80%) and unrelated samples (< 70%). The results showed that the RAPD proposed was capable of classifying the isolates coherently (such that same species were in the same dendrogram), except for two isolates of Candida parapsilosis and the positive control (Netherlands, 1973), probably because they are now recognized as three different species. Concerning the only fluconazole-resistant Candida tropicalis isolate with a genotype that was different to the others, the data were insufficient to affirm that the only difference was the sensitivity to fluconazole. We concluded that the Random Amplified Polymorphic DNA proposed might be used to confirm Candida species identified by microbiological methods.

Botnet cluster identification

Botnets are a group of computers infected with a specific sub-set of a malware family and controlled by one individual, called botmaster. This kind of networks are used not only, but also for virtual extorsion, spam campaigns and identity theft. They implement different types of evasion techniques that make it harder for one to group and detect botnet traffic. This thesis introduces one methodology, called CONDENSER, that outputs clusters through a self-organizing map and that identify domain names generated by an unknown pseudo-random seed that is known by the botnet herder(s). Aditionally DNS Crawler is proposed, this system saves historic DNS data for fast-flux and double fastflux detection, and is used to identify live C&Cs IPs used by real botnets. A program, called CHEWER, was developed to automate the calculation of the SVM parameters and features that better perform against the available domain names associated with DGAs. CONDENSER and DNS Crawler were developed with scalability in mind so the detection of fast-flux and double fast-flux networks become faster. We used a SVM for the DGA classififer, selecting a total of 11 attributes and achieving a Precision of 77,9% and a F-Measure of 83,2%. The feature selection method identified the 3 most significant attributes of the total set of attributes. For clustering, a Self-Organizing Map was used on a total of 81 attributes. The conclusions of this thesis were accepted in Botconf through a submited article. Botconf is known conferênce for research, mitigation and discovery of botnets tailled for the industry, where is presented current work and research. This conference is known for having security and anti-virus companies, law enforcement agencies and researchers.

Automatic delimitation of the clinical region of interest in ultra-wide field of view images of the retina

Retinal ultra-wide field of view images (fundus images) provides the visu-alization of a large part of the retina though, artifacts may appear in those images. Eyelashes and eyelids often cover the clinical region of interest and worse, eye-lashes can be mistaken with arteries and/or veins when those images are put through automatic diagnosis or segmentation software creating, in those cases, the appearance of false positives results. Correcting this problem, the first step in the development of qualified auto-matic diseases diagnosis programs can be done and in that way the development of an objective tool to assess diseases eradicating the human error from those processes can also be achieved. In this work the development of a tool that automatically delimitates the clinical region of interest is proposed by retrieving features from the images that will be analyzed by an automatic classifier. This automatic classifier will evaluate the information and will decide which part of the image is of interest and which part contains artifacts. The results were validated by implementing a software in C# language and validated through a statistical analysis. From those results it was confirmed that the methodology presented is capable of detecting artifacts and selecting the clin-ical region of interest in fundus images of the retina.

Automatic extraction of concepts from texts and applications

The extraction of relevant terms from texts is an extensively researched task in Text- Mining. Relevant terms have been applied in areas such as Information Retrieval or document clustering and classification. However, relevance has a rather fuzzy nature since the classification of some terms as relevant or not relevant is not consensual. For instance, while words such as "president" and "republic" are generally considered relevant by human evaluators, and words like "the" and "or" are not, terms such as "read" and "finish" gather no consensus about their semantic and informativeness. Concepts, on the other hand, have a less fuzzy nature. Therefore, instead of deciding on the relevance of a term during the extraction phase, as most extractors do, I propose to first extract, from texts, what I have called generic concepts (all concepts) and postpone the decision about relevance for downstream applications, accordingly to their needs. For instance, a keyword extractor may assume that the most relevant keywords are the most frequent concepts on the documents. Moreover, most statistical extractors are incapable of extracting single-word and multi-word expressions using the same methodology. These factors led to the development of the ConceptExtractor, a statistical and language-independent methodology which is explained in Part I of this thesis. In Part II, I will show that the automatic extraction of concepts has great applicability. For instance, for the extraction of keywords from documents, using the Tf-Idf metric only on concepts yields better results than using Tf-Idf without concepts, specially for multi-words. In addition, since concepts can be semantically related to other concepts, this allows us to build implicit document descriptors. These applications led to published work. Finally, I will present some work that, although not published yet, is briefly discussed in this document.

PCR-RFLP of 16S ribosomal DNA to confirm the identification of Enterococcus gallinarum and Enterococcus casseliflavus isolated from clinical and food samples

INTRODUCTION: This study aimed to confirm the identification of Enterococcus gallinarum and Enterococcus casseliflavus isolated from clinical and food samples by PCR-RFLP. METHODS: Fifty-two strains identified by conventional biochemical exams were submitted to PCR amplification and digested with HinfI. Only 20 (38.5%) of the 52 strains showed a DNA pattern expected for E. gallinarum and E. casseliflavus. RESULTS: Analysis of the results of this study showed that E. gallinarum and E. casseliflavus are occasionally erroneously identified and confirmed the potential application of 16S rDNA analysis for accurate identification of these species. CONCLUSIONS: A correct identification is important to distinguish between intrinsic and acquired vancomycin resistance.