4 resultados para Influence of the temperature

em Instituto Politécnico do Porto, Portugal


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Ball rotating micro-abrasion tribometers are commonly used to carry out wear tests on thin hard coatings. In these tests, different kinds of abrasives were used, as alumina (Al2O3), silicon carbide (SiC) or diamond. In each kind of abrasive, several particle sizes can be used. Some studies were developed in order to evaluate the influence of the abrasive particle shape in the micro-abrasion process. Nevertheless, the particle size was not well correlated with the material removed amount and wear mechanisms. In this work, slurry of SiC abrasive in distilled water was used, with three different particles size. Initial surface topography was accessed by atomic force microscopy (AFM). Coating hardness measurements were performed with a micro-hardness tester. In order to evaluate the wear behaviour, a TiAlSiN thin hard film was used. The micro-abrasion tests were carried out with some different durations. The abrasive effect of the SiC particles was observed by scanning electron microscopy (SEM) both in the films (hard material) as in the substrate (soft material), after coating perforation. Wear grooves and removed material rate were compared and discussed.

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Glioma is the most frequent form of malignant brain tumor in the adults and childhood. There is a global tendency toward a higher incidence of gliomas in highly developed and industrialized countries. Simultaneously obesity is reaching epidemic proportions in such developed countries. It has been highly accepted that obesity may play an important role in the biology of several types of cancer. We have developed an in vitro method for the understanding of the influence of obesity on glioma mouse cells (Gl261). 3T3-L1 mouse pre-adipocytes were induced to the maturity. The conditioned medium was harvested and used into the Gl261 cultures. Using two-dimension electrophoresis it was analyzed the proteome content of Gl261 in the presence of conditioned medium (CGl) and in its absence (NCGl). The differently expressed spots were collected and analyzed by means of mass spectroscopy (MALDI-TOF-MS). Significantly expression pattern changes were observed in eleven proteins and enzymes. RFC1, KIF5C, ANXA2, N-RAP, RACK1 and citrate synthase were overexpressed or only present in the CGl. Contrariwise, STI1, hnRNPs and phosphoglycerate kinase 1 were significantly underexpressed in CGl. Aldose reductase and carbonic anhydrase were expressed only in NCGl. Our results show that obesity remodels the physiological and metabolic behavior of glioma cancer cells. Also, proteins found differently expressed are implicated in several signaling pathways that control matrix remodeling, proliferation, progression, migration and invasion. In general our results support the idea that obesity may increase glioma malignancy, however, some interesting paradox finding were also reported and discussed.

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Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

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The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.