Molybdenum Induces the expression of a protein containing a new heterometallic Mo-Fe cluster in desulfoVibrio alaskensis

Biochemistry. 2009 Feb 10;48(5):873-82. doi: 10.1021/bi801773t.

NMR assignment of the apo-form of a Desulfovibrio gigas protein containing a novel Mo–Cu cluster

Biomol NMR Assign (2007) 1:81–83 DOI 10.1007/s12104-007-9022-3

Desulfovibrio gigas ferredoxin II: redox structural modulation of the [3Fe–4S] cluster

J Biol Inorg Chem (2006) 11: 307–315 DOI 10.1007/s00775-005-0077-2

Formation of a stable cyano-bridged dinuclear iron cluster following oxidation of the superoxide reductases from Treponema pallidum and Desulfovibrio vulgaris with K(3)Fe(CN)(6)

Inorg. Chem., 2003, 42 (4), pp 938–940 DOI: 10.1021/ic0262886

Incorporation of either molybdenum or tungsten into formate dehydrogenase from Desulfovibrio alaskensis NCIMB 13491; EPR assignment of the proximal iron-sulfur cluster to the pterin cofactor in formate dehydrogenases from sulfate-reducing bacteria

J Biol Inorg Chem (2004) 9: 145–151 DOI 10.1007/s00775-003-0506-z

Activation of N2O reduction by the fully reduced micro4-sulfide bridged tetranuclear Cu Z cluster in nitrous oxide reductase

J. Am. Chem. Soc., 2003, 125 (51), pp 15708–15709 DOI: 10.1021/ja038344n

Cluster analysis and segmentation of Global M&A transactions

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

Brain-computer interface (BCI): a methodological proposal to assess the impacts of medical applications in 2022

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Armin Grunwald (Karlsruhe Institute of Technology-ITAS, Germany). Other members of the thesis committee are Mário Forjaz Secca (FCT-UNL) and Femke Nijboer (University of Twente, Netherlands).

O e-Planning como Instrumento na Construção do Cluster do Mar em Portugal - Quantificação, Participação e Envolvimento dos Setores Socioeconómicos Nacionais

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em e-Planeamento

Purification of complex biopharmaceuticals with new processes, advanced analytics and computer-aided process design tools

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Genetic and functional analysis of the bacillus subtilis BSP1 gam cluster

Mannans (linear mannan, glucomannan, galactomannan and galactoglucomannan) are the major constituents of the hemicellulose fraction in softwoods and show great importance as a renewable resource for fuel or feedstock applications. As complex polysaccharides, mannans can only be degraded through a synergistic action of different mannan-degrading enzymes, mannanases. Microbial mannanases are mainly extracellular enzymes that can act in wide range of pH and temperature, contributing to pulp and paper, pharmaceutical, food and feed, oil and textile successful industrial applications. Knowing and controlling these microbial mannan-degrading enzymes are essential to take advantage of their great biotechnological potential. The genome of the laboratory 168 strain of Bacillus subtilis carries genes gmuA-G dedicated to the degradation and utilization of glucomannan, including an extracellular -mannanase. Recently, the genome sequence of an undomesticated strain of B. subtilis, BSP1, was determined. In BSP1, the gmuA-G operon is maintained, interestingly, however, a second cluster of genes was found (gam cluster), which comprise a second putative extracellular β-mannanase, and most likely specify a system for the degradation and utilization of a different mannan polymer, galactoglucomannan. The genetic organization and function of the gam cluster, and whether its presence in BSP1 strain results in new hemicellulolytic capabilities, compared to those of the laboratory strain, was address in this work. In silico and in vivo mRNA analyses performed in this study revealed that the gam cluster, comprising nine genes, is organized and expressed in at least six different transcriptional units. Furthermore, cloning, expression, and production of Bbsp2923 in Escherichia coli was achieved and preliminary characterization shows that the enzyme is indeed a β-mannanase. Finally, the high hemicellulolytic capacity of the undomesticated B. subtilis BSP1, demonstrated in this work by qualitative analyses, suggests potential to be used in the food and feed industries.

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.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.