764 resultados para Cluster aggregation


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

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

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

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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

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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

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

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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.

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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.

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In the present study, different aerial parts from twelve Amazonian plant species found in the National Institute for Amazon Research's (INPA's) Adolpho Ducke Forest Reserve (in Manaus, Amazonas, Brazil) were collected. Separate portions of dried, ground plant materials were extracted with water (by infusion), methanol and chloroform (by continuous liquid-solid extraction) and solvents were removed first by rotary evaporation, and finally by freeze-drying which yielded a total of seventy-one freeze-dried extracts for evaluation. These extracts were evaluated initially at concentrations of 500 and 100 µg/mL for in vitro hemolytic activity and in vitro inhibition of platelet aggregation in human blood, respectively. Sixteen extracts (23 % of all extracts tested, 42 % of all plant species), representing the following plants: Chaunochiton kappleri (Olacaceae), Diclinanona calycina (Annonaceae), Paypayrola grandiflora (Violaceae), Pleurisanthes parviflora (Icacinaceae), Sarcaulus brasiliensis (Sapotaceae), exhibited significant inhibitory activity towards human platelet aggregation. A group of extracts with antiplatelet aggregation activity having no in vitro hemolytic activity has therefore been identified. Three extracts (4 %), all derived from Elaeoluma nuda (Sapotaceae), exhibited hemolytic activity. None of the plant species in this study has known use in traditional medicine. So, these data serve as a baseline or minimum of antiplatelet and hemolytic activities (and potential usefulness) of non-medicinal plants from the Amazon forest. Finally, in general, these are the first data on hemolytic and inhibitory activity on platelet aggregation for the genera which these plant species represent.

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Nanocomposite materials with an organic-inorganic urea-silicate (di-ureasil) based matrix containing gold nanoparticles (NPs) were synthesized and characterized by optical (UV/Vis) spectroscopy and indentation measurement. The urea silicate gels were obtained by reaction between silicon alkoxyde modified by isocyanate group and polyethylene glycol oligomer with amine terminal groups in presence of catalyst. The latter ensures the successful incorporation of citrate-stabilized gold NPs in the matrix. It is shown that using a convenient destabilizing agent (AgNO3) and governing the preparative conditions, the aggregation degree of gold NPs can be controlled. The developed synthesis procedure significantly simplifies the preparative procedure of gold/urea silicate nanocomposites, compared to the procedure using gold NPs, preliminary covered with silica shells. Mechanical properties of the prepared sample were characterised using depth sensing indentation methods (DSI) and an idea about the type of aggregation structures was suggested.

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Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.