7 resultados para IN-CELL SIMULATION

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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We report in this paper the recent advances we obtained in optimizing a color image sensor based on the laser-scanned-photodiode (LSP) technique. A novel device structure based on a a-SiC:H/a-Si:H pin/pin tandem structure has been tested for a proper color separation process that takes advantage on the different filtering properties due to the different light penetration depth at different wavelengths a-SM and a-SiC:H. While the green and the red images give, in comparison with previous tested structures, a weak response, this structure shows a very good recognition of blue color under reverse bias, leaving a good margin for future device optimization in order to achieve a complete and satisfactory RGB image mapping. Experimental results about the spectral collection efficiency are presented and discussed from the point of view of the color sensor applications. The physics behind the device functioning is explained by recurring to a numerical simulation of the internal electrical configuration of the device.

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Microtubules are polymers of alpha/beta-tubulin participating in essential cell functions. A multistep process involving distinct molecular chaperones and cofactors produces new tubulin heterodimers competent to polymerise. In vitro cofactor A (TBCA) interacts with beta-tubulin in a quasi-native state behaving as a molecular chaperone. We have used siRNA to silence TBCA expression in HeLa and MCF-7 mammalian cell lines. TBCA is essential for cell viability and its knockdown produces a decrease in the amount of soluble tubulin, modifications in microtubules and G1 cell cycle arrest. In MCF-7 cells, cell death was preceded by a change in cell shape resembling differentiation.

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We propose a low complexity technique to generate amplitude correlated time-series with Nakagami-m distribution and phase correlated Gaussian-distributed time-series, which is useful in the simulation of ionospheric scintillation effects during the transmission of GNSS signals. The method requires only the knowledge of parameters S4 (scintillation index) and σΦ (phase standard deviation) besides the definition of models for the amplitude and phase power spectra. The Zhang algorithm is used to produce Nakagami-distributed signals from a set of Gaussian autoregressive processes.

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Objective: To evaluate the influence of Everolimus (RAD001) on chemically induced urothelial lesions in mice and its influence on in vitro human bladder cancer cell lines. Methods: ICR male mice were given N-butyl-N-(4-hydroxybutyl) nitrosamine in drinking water for a period of 12 weeks. Subsequently, RAD001 was administered via oral gavage, for 6 weeks. At the end of the experiment, all the animals were sacrificed and tumor development was determined by means of histopathologic evaluation; mammalian target of rapamycin (mTOR) expressivity was evaluated by immunohistochemistry. Three human bladder cancer cell lines (T24, HT1376, and 5637) were treated using a range of RAD001 concentrations. MTT assay, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), and flow cytometry were used to assess cell proliferation, apoptosis index, and cell cycle analysis, respectively. Immunoblotting analysis of 3 cell line extracts using mTOR and Akt antibodies was performed in order to study the expression of Akt and mTOR proteins and their phosphorylated forms. Results: The incidence of urothelial lesions in animals treated with RAD001 was similar to those animals not treated. RAD001 did not block T24 and HT1376 cell proliferation or induce apoptosis. A reduction in cell proliferation rate and therefore G0/G1 phase arrest, as well as a statistically significant induction of apoptosis (P 0.001), was only observed in the 5637 cell line. Conclusion: RAD001 seems not to have a significant effect on chemically induced murine bladder tumors. The effect of RAD001 on tumor proliferation and apoptosis was achieved only in superficial derived bladder cancer cell line, no effect was observed in invasive cell lines.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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A new data set of daily gridded observations of precipitation, computed from over 400 stations in Portugal, is used to assess the performance of 12 regional climate models at 25 km resolution, from the ENSEMBLES set, all forced by ERA-40 boundary conditions, for the 1961-2000 period. Standard point error statistics, calculated from grid point and basin aggregated data, and precipitation related climate indices are used to analyze the performance of the different models in representing the main spatial and temporal features of the regional climate, and its extreme events. As a whole, the ENSEMBLES models are found to achieve a good representation of those features, with good spatial correlations with observations. There is a small but relevant negative bias in precipitation, especially in the driest months, leading to systematic errors in related climate indices. The underprediction of precipitation occurs in most percentiles, although this deficiency is partially corrected at the basin level. Interestingly, some of the conclusions concerning the performance of the models are different of what has been found for the contiguous territory of Spain; in particular, ENSEMBLES models appear too dry over Portugal and too wet over Spain. Finally, models behave quite differently in the simulation of some important aspects of local climate, from the mean climatology to high precipitation regimes in localized mountain ranges and in the subsequent drier regions.

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The iterative simulation of the Brownian bridge is well known. In this article, we present a vectorial simulation alternative based on Gaussian processes for machine learning regression that is suitable for interpreted programming languages implementations. We extend the vectorial simulation of path-dependent trajectories to other Gaussian processes, namely, sequences of Brownian bridges, geometric Brownian motion, fractional Brownian motion, and Ornstein-Ulenbeck mean reversion process.