17 resultados para Sugar plants


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Dissertation presented to obtain the Ph.D degree in Molecular Biology

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XX Symposium of Brazilian Medicinal Plants & X International Congress of Ethnopharmacology. S. Paulo, Brasil.

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Journal of Bacteriology (Out 2010) 5312-5318

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The section at Cristo Rei shows sandy beds with intercalated clayey lenses (IVb division from the Lisbon Miocene series) that correspond to a major regression event dated from between ca. 17.6 and 17 Ma. They also correspond to a distal position (relatively to the typical fluviatile facies in Lisbon), nearer the basin's axis. Geologic data and paleontological analysis (plant fossils, fishes, crocodilians, land mammals) allow the reconstruction of environments that were represented in the concerned area: estuary with channels and ox-bows; upstream, areas occupied by brackish waters where Gryphaea griphoides banks developped; still farther upstream, freshwaters sided by humid forests and low mountain subtropical forests under warm temperate and rainy conditions, as well as not far away, seasonally dry environments (low density tree or shrub cover, or steppe).

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Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Dissertation presented to obtain the degree of Doctorate in Biochemistry by Instituto de Tecnologia Química e Biológica of Universidade Nova de Lisboa

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A thesis submitted in fulfilment of the requirements for the Degree of Doctor of Philosophy in Sanitary Engineering in the Faculty of Sciences and Technology of the New University of Lisbon

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FEBS journal, Volume 278, Issue 14, pages 2511-2524, July 2011

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Dissertação para obtenção do Grau de Mestre em Biotecnologia

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

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Dissertation presented to obtain the Ph.D degree in Biochemistry

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Thesis submitted to obtain the Doctoral degree in Energy and Bioenergy

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Dissertation toobtaina Master of Science degree in Bioorganics

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AraL from Bacillus subtilis is a member of the ubiquitous haloalkanoate dehalogenase, HAD, superfamily. The araL gene has been cloned, over-expressed in Escherichia coli and its product purified to homogeneity. The enzyme displays phosphatase activity, which is optimal at neutral pH (7.0) and 65 °C. Substrate screening and kinetic analysis showed AraL to have low specificity and catalytic activity towards several sugar phosphates, which are metabolic intermediates of the glycolytic and pentose phosphate pathways. Based on substrate specificity and gene context within the arabinose metabolic operon, a putative physiological role of AraL in detoxification of accidental accumulation of phosphorylated metabolites has been proposed. The ability of AraL to catabolise several related secondary metabolites requires regulation at the genetic level. Here, by site- directed mutagenesis, we show that AraL production is regulated by a structure in the translation initiation region of the mRNA, which most probably blocks access to the ribosome-binding site, preventing protein synthesis. Members of HAD subfamily IIA and IIB are characterised by a broad-range and overlapping specificity that anticipated the need for regulation at the genetic level. In this study we provide evidence for the existence of a genetic regulatory mechanism controlling AraL production.

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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.