981 resultados para annealing time
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Wireless sensor network (WSN) Is a technology that can be used to monitor and actuate on environments in a non-intrusive way. The main difference from WSN and traditional sensor networks is the low dependability of WSN nodes. In this way, WSN solutions are based on a huge number of cheap tiny nodes that can present faults in hardware, software and wireless communication. The deployment of hundreds of nodes can overcome the low dependability of individual nodes, however this strategy introduces a lot of challenges regarding network management, real-time requirements and self-optimization. In this paper we present a simulated annealing approach that self-optimize large scale WSN. Simulation results indicate that our approach can achieve self-optimization characteristics in a dynamic WSN. © 2012 IEEE.
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One of the purposes of this study is to give further constraints on the temperature range of the zircon partial annealing zone over a geological time scale using data from borehole zircon samples, which have experienced stable temperatures for ∼1 Ma. In this way, the extrapolation problem is explicitly addressed by fitting the zircon annealing models with geological timescale data. Several empirical model formulations have been proposed to perform these calibrations and have been compared in this work. The basic form proposed for annealing models is the Arrhenius-type model. There are other annealing models, that are based on the same general formulation. These empirical model equations have been preferred due to the great number of phenomena from track formation to chemical etching that are not well understood. However, there are two other models, which try to establish a direct correlation between their parameters and the related phenomena. To compare the response of the different annealing models, thermal indexes, such as closure temperature, total annealing temperature and the partial annealing zone, have been calculated and compared with field evidence. After comparing the different models, it was concluded that the fanning curvilinear models yield the best agreement between predicted index temperatures and field evidence. © 2012 Elsevier Ltd. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A self-learning simulated annealing algorithm is developed by combining the characteristics of simulated annealing and domain elimination methods. The algorithm is validated by using a standard mathematical function and by optimizing the end region of a practical power transformer. The numerical results show that the CPU time required by the proposed method is about one third of that using conventional simulated annealing algorithm.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.
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This work reports evidence of the induced migration of Mn2+ ions in Cd(1-x)MnxS nanocrystals (NCs) by selecting a specific thermal treatment for each sample. The growth and characterization of these magnetic dots were investigated by atomic force microscopy (AFM), optical absorption (OA), and electronic paramagnetic resonance (EPR) techniques. The comparison of experimental and simulated EPR spectra confirms the incorporation of Mn2+ ions both in the core and at the dot surface regions. The thermal treatment of a magnetic sample, via selected annealing temperature and/or time, affects the fine and hyperfine interaction constants which modify the shape and the intensity of the EPR transition spectrum. The identification of these changes has allowed tracing the magnetic ion migration from core to surface regions of a dot as well as inferring the local density of the magnetic impurity ions. (C) 2011 Elsevier Ltd. All rights reserved.
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Real-time quantitative polymerase chain reaction (qPCR) depends on precise temperature control of the sample during cycling. In the current study, we investigated how temperature variation in plate-based qPCR instruments influences qPCR results. Temperature variation was measured by amplicon melting analysis as a convenient means to assess well-to-well differences. Multiple technical replicates of several SYBR Green I-based qPCR assays allowed correlation of relative well temperature to quantification cycle. We found that inadequate template denaturation results in an inverse correlation and requires increasing the denaturation temperature, adding a DNA destabilizing agent, or pretreating with a restriction enzyme. In contrast, inadequate primer annealing results in a direct correlation and requires lowering the annealing temperature. Significant correlations were found in 18 of 25 assays. The critical nature of temperature-dependent effects was shown in a blinded study of 29 patients for the diagnosis of Prader-Willy and Angelman syndromes, where eight diagnoses were incorrect unless temperature-dependent effects were controlled. A method to detect temperature-dependent effects by pairwise comparisons of replicates in routine experiments is presented and applied. Systematic temperature errors in qPCR instruments can be recognized and their effects eliminated when high precision is required in quantitative genetic diagnostics and critical complementary DNA analyses.
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The introduction of a low-temperature (LT) tail after P emitter diffusion was shown to lead to considerable improvements in electron lifetime and solar cell performance by different researchers. So far, the drawback of the investigated extended gettering treatments has been the lack of knowledge about optimum annealing times and temperatures and the important increase in processing time. In this manuscript, we calculate optimum annealing temperatures of Fe-contaminated Si wafers for different annealing durations. Subsequently, it is shown theoretically and experimentally that a relatively short LT tail of 15 min can lead to a significant reduction of interstitial Fe and an increase in electron lifetime. Finally, we calculate the potential improvement of solar cell efficiency when such a short-tail extended P diffusion gettering is included in an industrial fabrication process.
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The conformational space annealing (CSA) method for global optimization has been applied to the 10-55 fragment of the B-domain of staphylococcal protein A (protein A) and to a 75-residue protein, apo calbindin D9K (PDB ID code 1CLB), by using the UNRES off-lattice united-residue force field. Although the potential was not calibrated with these two proteins, the native-like structures were found among the low-energy conformations, without the use of threading or secondary-structure predictions. This is because the CSA method can find many distinct families of low-energy conformations. Starting from random conformations, the CSA method found that there are two families of low-energy conformations for each of the two proteins, the native-like fold and its mirror image. The CSA method converged to the same low-energy folds in all cases studied, as opposed to other optimization methods. It appears that the CSA method with the UNRES force field, which is based on the thermodynamic hypothesis, can be used in prediction of protein structures in real time.
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This is a study of heat transfer in a lift-off furnace which is employed in the batch annealing of a stack of coils of steel strip. The objective of the project is to investigate the various factors which govern the furnace design and the heat transfer resistances, so as to reduce the time of the annealing cycle, and hence minimize the operating costs. The work involved mathematical modelling of patterns of gas flow and modes of heat transfer. These models are: Heat conduction and its conjectures in the steel coils;Convective heat transfer in the plates separating the coils in the stack and in other parts of the furnace; and Radiative and convective heat transfer in the furnace by using the long furnace model. An important part of the project is the development of numerical methods and computations to solve the transient models. A limited number of temperature measurements was available from experiments on a test coil in an industrial furnace. The mathematical model agreed well with these data. The model has been used to show the following characteristics of annealing furnaces, and to suggest further developments which would lead to significant savings: - The location of the limiting temperature in a coil is nearer to the hollow core than to the outer periphery. - Thermal expansion of the steel tends to open the coils, reduces their thermal conductivity in the radial direction, and hence prolongs the annealing cycle. Increasing the tension in the coils and/or heating from the core would overcome this heat transfer resistance. - The shape and dimensions of the convective channels in the plates have significant effect on heat convection in the stack. An optimal design of a channel is shown to be of a width-to-height ratio equal to 9. - Increasing the cooling rate, by using a fluidized bed instead of the normal shell and tube exchanger, would shorten the cooling time by about 15%, but increase the temperature differential in the stack. - For a specific charge weight, a stack of different-sized coils will have a shorter annealing cycle than one of equally-sized coils, provided that production constraints allow the stacking order to be optimal. - Recycle of hot flue gases to the firing zone of the furnace would produce a. decrease in the thermal efficiency up to 30% but decreases the heating time by about 26%.
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Fabrication of nanoscale patterns through the bottom-up approach of self-assembly of phase-separated block copolymers (BCP) holds promise for nanoelectronics applications. For lithographic applications, it is useful to vary the morphology of BCPs by monitoring various parameters to make “from lab to fab” a reality. Here I report on the solvent annealing studies of lamellae forming polystyrene-blockpoly( 4-vinylpyridine) (PS-b-P4VP). The high Flory-Huggins parameter (χ = 0.34) of PS-b-P4VP makes it an ideal BCP system for self-assembly and template fabrication in comparison to other BCPs. Different molecular weights of symmetric PS-b-P4VP BCPs forming lamellae patterns were used to produce nanostructured thin films by spin-coating from mixture of toluene and tetrahydrofuran(THF). In particular, the morphology change from micellar structures to well-defined microphase separated arrangements is observed. Solvent annealing provides a better alternative to thermal treatment which often requires long annealing periods. The choice of solvent (single and dual solvent exposure) and the solvent annealing conditions have significant effects on the morphology of films and it was found that a block neutral solvent was required to realize vertically aligned PS and P4VP lamellae. Here, we have followed the formation of microdomain structures with time development at different temperatures by atomic force microscopy (AFM). The highly mobilized chains phase separate quickly due to high Flory-Huggins (χ) parameter. Ultra-small feature size (~10 nm pitch size) nanopatterns were fabricated by using low molecular weight PSb- P4VP (PS and P4VP blocks of 3.3 and 3.1 kg mol-1 respectively). However, due to the low etch contrast between the blocks, pattern transfer of the BCP mask is very challenging. To overcome the etch contrast problem, a novel and simple in-situ hard mask technology is used to fabricate the high aspect ratio silicon nanowires. The lamellar structures formed after self-assembly of phase separated PS-b-P4VP BCPs were used to fabricate iron oxide nanowires which acted as hard mask material to facilitate the pattern transfer into silicon and forming silicon nanostructures. The semiconductor and optical industries have shown significant interest in two dimensional (2D) molybdenum disulphide (MoS2) as a potential device material due to its low band gap and high mobility. However, current methods for its synthesis are not ‘fab’ friendly and require harsh environments and processes. Here, I also report a novel method to prepare MoS2 layered structures via self-assembly of a PS-b-P4VP block copolymer system. The formation of the layered MoS2 was confirmed by XPS, Raman spectroscopy and high resolution transmission electron microscopy.
O problema de alocação de berços: um estudo das heurísticas simulated annealing e algoritmo genético
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Este trabalho apresenta um estudo de caso das heurísticas Simulated Annealing e Algoritmo Genético para um problema de grande relevância encontrado no sistema portuário, o Problema de Alocação em Berços. Esse problema aborda a programação e a alocação de navios às áreas de atracação ao longo de um cais. A modelagem utilizada nesta pesquisa é apresentada por Mauri (2008) [28] que trata do problema como uma Problema de Roteamento de Veículos com Múltiplas Garagens e sem Janelas de Tempo. Foi desenvolvido um ambiente apropriado para testes de simulação, onde o cenário de análise foi constituido a partir de situações reais encontradas na programação de navios de um terminal de contêineres. Os testes computacionais realizados mostram a performance das heurísticas em relação a função objetivo e o tempo computacional, a m de avaliar qual das técnicas apresenta melhores resultados.
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For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.