5 resultados para REAL-SPACE
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
We study a model of fast magnetic reconnection in the presence of weak turbulence proposed by Lazarian and Vishniac (1999) using three-dimensional direct numerical simulations. The model has been already successfully tested in Kowal et al. (2009) confirming the dependencies of the reconnection speed V-rec on the turbulence injection power P-inj and the injection scale l(inj) expressed by a constraint V-rec similar to P(inj)(1/2)l(inj)(3/4)and no observed dependency on Ohmic resistivity. In Kowal et al. (2009), in order to drive turbulence, we injected velocity fluctuations in Fourier space with frequencies concentrated around k(inj) = 1/l(inj), as described in Alvelius (1999). In this paper, we extend our previous studies by comparing fast magnetic reconnection under different mechanisms of turbulence injection by introducing a new way of turbulence driving. The new method injects velocity or magnetic eddies with a specified amplitude and scale in random locations directly in real space. We provide exact relations between the eddy parameters and turbulent power and injection scale. We performed simulations with new forcing in order to study turbulent power and injection scale dependencies. The results show no discrepancy between models with two different methods of turbulence driving exposing the same scalings in both cases. This is in agreement with the Lazarian and Vishniac (1999) predictions. In addition, we performed a series of models with varying viscosity nu. Although Lazarian and Vishniac (1999) do not provide any prediction for this dependence, we report a weak relation between the reconnection speed with viscosity, V-rec similar to nu(-1/4).
Resumo:
The magnetic properties of Mn nanostructures on the Fe(001) surface have been studied using the noncollinear first-principles real space-linear muffin-tin orbital-atomic sphere approximation method within density-functional theory. We have considered a variety of nanostructures such as adsorbed wires, pyramids, and flat and intermixed clusters of sizes varying from two to nine atoms. Our calculations of interatomic exchange interactions reveal the long-range nature of exchange interactions between Mn-Mn and Mn-Fe atoms. We have found that the strong dependence of these interactions on the local environment, the magnetic frustration, and the effect of spin-orbit coupling lead to the possibility of realizing complex noncollinear magnetic structures such as helical spin spiral and half-skyrmion.
Resumo:
In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.
Resumo:
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.
Resumo:
Abstract Introduction Pelvicalyceal cysts are common findings in autopsies and can manifest with a variety of patterns. These cystic lesions are usually a benign entity with no clinical significance unless they enlarge enough to cause compression of the adjacent collecting system and consequently obstructive uropathy. Few cases of the spontaneous rupture of pelvicalyceal renal cysts have been published and to the best of our knowledge there is no report of a combined rupture to collector system and retroperitoneal space documented during a multiphase computed tomography. Case presentation We report a case of a ‘real-time’ spontaneous rupture of a pelvicalyceal cyst into the collecting system with fistulization into the retroperitoneum. The patient was a 78-year-old Caucasian man with a previous history of renal stones and a large pelvicalyceal renal cyst who was admitted to our Emergency department with acute right flank pain. A multiphase computed tomography was performed and the pre-contrast images demonstrated a right pelvicalyceal renal cyst measuring 12.0 × 6.1cm in the lower pole causing moderate dilation of the upper right renal collection system. In addition, a partially obstructive stone on the left distal ureter with mild left hydronephrosis was noted. The nephrographic phase did not add any new information. The excretory phase (10-minute delay) demonstrated a spontaneous rupture of the cyst into the pelvicalyceal system with posterior fistulization into the retroperitoneal space. Conclusion In this case study we present time-related changes of a rare pelvicalyceal cyst complication, which to the best of our knowledge has fortunately not been previously documented. Analysis of the sequential images and comparison with an earlier scan allowed us to better understand the physiopathological process of the rupture, the clinical presentation and to elaborate hypotheses for its etiopathogenesis.