Recursive neuro fuzzy techniques for online identification and control

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Osmo- and thermo-adaptation in hyperthermophilic Archaea: identification of compatible solutes accumulation profiles, and biosynthetic routes in Archaeoglobus spp.

Dissertation presented to obtain the Ph.D degree in Biochemistry

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

Doctoral dissertation for Ph.D. degree in Sustainable Chemistry

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.

Going beyond duopoly: Connectivity breakdowns under receiving party pays

We show that the prediction of strategic connectivity breakdowns under a receiving-party-pays system and discrimination between on and off-net prices does not hold up once more than two mobile networks are considered. Indeed, if there are at least three competing networks and enough utility is obtained from receiving calls, only equilibria with finite call prices and receiving prices exist. Private negotiations over access charges then achieve the efficient outcome. Bill & keep (zero access charges) and free outgoing and incoming calls are efficient if and only marginal costs of calls are zero.

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.

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

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.

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.