906 resultados para loss of electricity


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Charge changing processes of MeV ions penetrating through liquid spray is confirmed to be abundant source of various energetic negative ion and neutral atom beams its generic nature is demonstrated.

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Several forest species are severely affected by Phytophthora cinnamomi. The contribution of this oomycete to forest decline and dieback has been broadly reported. In particular, it is consensual that it is the causal agent of ink disease in Castanea sativa. It has been associated with the severe decline of Quercus species, namely the Q. suber and Q. ilex dieback in Portugal and Spain, and has been responsible for the infection of numerous native species and crops. This pathogen persists in the soil or on plant material in the form of chlamydospores allowing the infection of living root tissues when environmental conditions are favorable. © Microscopy Society of America 2012.

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Dissertação de Mestrado, Oncobiologia: Mecanismos Moleculares do Cancro, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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Tese de mestrado, Neurociências, Faculdade de Medicina, Universidade de Lisboa, 2016

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We trace the diachronic development of the preposition se in inner Asia Minor Greek from its use to mark a range of spatial functions to its ultimate loss and replacement by zero. We propose that, before spreading to all syntactic and semantic contexts, zero marking was contextually-dependent on the presence/absence of a prenominal genitive modifying the head noun of Ground-encoding NPs and on the presence/absence of Region-encoding postpositions. We attribute these developments to an informational load relief strategy aimed at producing more economical utterances as well as to language contact with Turkish, which favoured structural convergence on the adpositional level between the two languages.

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Spinal cord regenerative ability is lost with development, but the mechanisms underlying this loss are still poorly understood. In chick embryos, effective regeneration does not occur after E13, when spinal cord injury induces extensive apoptotic response and tissue damage. As initial experiments showed that treatment with a calcium chelator after spinal cord injury reduced apoptosis and cavitation, we hypothesized that developmentally regulated mediators of calcium-dependent processes in secondary injury response may contribute to loss of regenerative ability. To this purpose we screened for such changes in chick spinal cords at stages of development permissive (E11) and non-permissive (E15) for regeneration. Among the developmentally regulated calcium-dependent proteins identified was PAD3, a member of the peptidylarginine deiminase (PAD) enzyme family that converts protein arginine residues to citrulline, a process known as deimination or citrullination. This post-translational modification has not been previously associated with response to injury. Following injury, PAD3 up-regulation was greater in spinal cords injured at E15 than at E11. Consistent with these differences in gene expression, deimination was more extensive at the non-regenerating stage, E15, both in the gray and white matter. As deimination paralleled the extent of apoptosis, we investigated the effect of blocking PAD activity on cell death and deiminated-histone 3, one of the PAD targets we identified by mass-spectrometry analysis of spinal cord deiminated proteins. Treatment with the PAD inhibitor, Cl-amidine, reduced the abundance of deiminated-histone 3, consistent with inhibition of PAD activity, and significantly reduced apoptosis and tissue loss following injury at E15. Altogether, our findings identify PADs and deimination as developmentally regulated modulators of secondary injury response, and suggest that PADs might be valuable therapeutic targets for spinal cord injury.

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With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

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This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.

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This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

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This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

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This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

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

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Inflammation can promote or inhibit cancer progression. In this study we have addressed the role of the proinflammatory cytokine thymic stromal lymphopoietin (TSLP) during skin carcinogenesis. Using conditional loss- and gain-of-function mouse models for Notch and Wnt signaling, respectively, we demonstrate that TSLP-mediated inflammation protects against cutaneous carcinogenesis by acting directly on CD4 and CD8 T cells. Genetic ablation of TSLP receptor (TSLPR) perturbs T-cell-mediated protection and results in the accumulation of CD11b(+)Gr1(+) myeloid cells. These promote tumor growth by secreting Wnt ligands and augmenting β-catenin signaling in the neighboring epithelium. Epithelial specific ablation of β-catenin prevents both carcinogenesis and the accumulation of CD11b(+)Gr1(+) myeloid cells, suggesting tumor cells initiate a feed-forward loop that induces protumorigenic inflammation.