Wide localized solitons in systems with time- and space-modulated nonlinearities

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Numerical study of the spherically symmetric Gross-Pitaevskii equation in two space dimensions

The Gross-Pitaevskii equation for Bose-Einstein condensation (BEC) in two space dimensions under the action of a harmonic oscillator trap potential for bosonic atoms with attractive and repulsive interparticle interactions was numerically studied by using time-dependent and time-independent approaches. In both cases, numerical difficulty appeared for large nonlinearity. Nonetheless, the solution of the time-dependent approach exhibited intrinsic oscillation with time iteration which is independent of space and time steps used in discretization.

The effect of changing the mode of ventilation on the arterial-to-end-tidal CO2 difference and physiological dead space in laterally and dorsally recumbent horses during halothane anesthesia

Objective - To evaluate the effect of changing the mode of ventilation from spontaneous to controlled on the arterial-to-end-tidal CO2 difference [P(a-ET)CO2] and physiological dead space (VD(phys)/VT) in laterally and dorsally recumbent halothane-anesthetized horses. Study Design - Prospective, experimental, nonrandomized trial. Animals - Seven mixed breed adult horses (1 male and 6 female) weighing 320 ± 11 kg. Methods - Horses were anesthetized in 2 positions - right lateral and dorsal recumbency - with a minimum interval of 1 month. Anesthesia was maintained with halothane in oxygen for 180 minutes. Spontaneous ventilation (SV) was used for 90 minutes followed by 90 minutes of controlled ventilation (CV). The same ventilator settings were used for both laterally and dorsally recumbent horses. Arterial blood gas analysis was performed every 30 minutes during anesthesia. End-tidal CO2 (PETCO2) was measured continuously. P(a-ET)CO2 and VD(phys)/VT were calculated. Statistical analysis included analysis of variance for repeated measures over time, followed by Student-Newman-Keuls test. Comparison between groups was performed using a paired t test; P < .05 was considered significant. Results - P(a-ET)CO2 and VD(phys)/VT increased during SV, whereas CV reduced these variables. The variables did not change significantly throughout mechanical ventilation in either group. Dorsally recumbent horses showed greater P(a-ET)CO2 and VD(phys)/VT values throughout. PaCO2 was greater during CV in dorsally positioned horses. Conclusions and Clinical Relevance - Changing the mode of ventilation from spontaneous to controlled was effective in reducing P(a-ET)CO2 and physiological dead space in both laterally and dorsally recumbent halothane-anesthetized horses. Dorsal recumbency resulted in greater impairment of effective ventilation. Capnometry has a limited value for accurate estimation of PaCO, in anesthetized horses, although it may be used to evaluate pulmonary function when paired with arterial blood gas analysis. © Copyright 2000 by The American College of Veterinary Surgeons.

Using state-space techniques to represent frequency dependent single-phase lines directly in time domain

This paper proposes to use a state-space technique to represent a frequency dependent line for simulating electromagnetic transients directly in time domain. The distributed nature of the line is represented by a multiple 1t section network made up of the lumped parameters and the frequency dependence of the per unit longitudinal parameters is matched by using a rational function. The rational function is represented by its equivalent circuit with passive elements. This passive circuit is then inserted in each 1t circuit of the cascade that represents the line. Because the system is very sparse, it is possible to use a sparsity technique to store only nonzero elements of this matrix for saving space and running time. The model was used to simulate the energization process of a 10 km length single-phase line. ©2008 IEEE.

Role of the range of the dipole function in the classical dynamics of molecular dissociation

The dissociation dynamics of heteronuclear diatomic molecules induced by infrared laser pulses is investigated within the framework of the classical driven Morse oscillator. The interaction between the molecule and the laser field described in the dipole formulation is given by the product of a time-dependent external field with a position-dependent permanent dipole function. The effects of changing the spatial range of the dipole function in the classical dissociation dynamics of large ensembles of trajectories are studied. Numerical calculations have been performed for distinct amplitudes and carrier frequencies of the external pulses and also for ensembles with different initial energies. It is found that there exist a set of values of the dipole range for which the dissociation probability can be completely suppressed. The dependence of the dissociation on the dipole range is explained through the examination of the Fourier series coefficients of the dipole function in the angle variable of the free system. In particular, the suppression of dissociation corresponds to dipole ranges for which the Fourier coefficients associated with nonlinear resonances are null and the chaotic region in the phase space is reduced to thin layers. In this context, it is shown that the suppression of dissociation of heteronuclear molecules for certain frequencies of the external field is a consequence of the finite range of the corresponding permanent dipole. © 2013 American Physical Society.

The Linear Potential Propagator via Wave Function Expansion

ABSTRACT: We evaluate the quantum propagator for the motion of a particle in a linear potential via a recently developped formalism [A.B. Nassar et al., Phys. Rev. E56, 1230, (1997)]. In this formalism, the propagator comes about as a type of expansion of the wave function over the space of the initial velocities.

GABA and glutamate transporters: new events and function in the vertebrate retina

The neural retina is a highly complex tissue composed of excitatory and inhibitory neurons and glial cells. Glutamate, the main excitatory neurotransmitter, mediates information transfer from photoreceptors, bipolar cells, and ganglion cells, whereas interneurons, mainly amacrine and horizontal cells, use γ-aminobutyric acid (GABA), the main inhibitory neurotransmitter. In this review we place an emphasis on glutamate and GABA transporters as highly regulated molecules that play fundamental roles in neurotransmitter clearance, neurotransmitter release, and oxidative stress. We pharmacologically characterized glutamate transporters in chicken retina cells and identified two glutamate transporters: one Na+-dependent transporter and one Na+-independent transporter. The Na+-dependent uptake system presented characteristics related to the high-affinity xAG- system (EAAT1), and the Na+-independent uptake system presented characteristics related to the xCG- system, which highly contributes to glutamate transport in the retina. Glutamate shares the xCG- system with another amino acid, L-cysteine, suggesting the possible involvement of glutathione. Both transporter proteins are present mainly in Müller glial cells. GABA transporters (GATs) mediate high-affinity GABA uptake from the extracellular space and terminate the synaptic action of GABA in the central nervous system. GABA transporters can be modulated by molecules that act on specific sites to promote transporter phosphorylation and dephosphorylation. In addition to a role in the clearance of GABA, GATs may also release GABA through a reverse transport mechanism. In the chicken retina, a GAT-1 blocker, but not GAT2/3 blocker, was shown to inhibit GABA uptake, suggesting that GABA release from retina cells is mainly mediated by a GAT-1-like transporter.

Dynamics of Space Particles and Spacecrafts Passing by the Atmosphere of the Earth

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Large-scale analysis of the SDSS-III DR8 photometric luminous galaxies angular correlation function

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Anderson localization and momentum-space entanglement

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Cartan geometry of spacetimes with a nonconstant cosmological function Lambda

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Semiautomatic object-space road extraction combining a stereoscopic image pair and a TIN-Based DTM

In this letter, a semiautomatic method for road extraction in object space is proposed that combines a stereoscopic pair of low-resolution aerial images with a digital terrain model (DTM) structured as a triangulated irregular network (TIN). First, we formulate an objective function in the object space to allow the modeling of roads in 3-D. In this model, the TIN-based DTM allows the search for the optimal polyline to be restricted along a narrow band that is overlaid upon it. Finally, the optimal polyline for each road is obtained by optimizing the objective function using the dynamic programming optimization algorithm. A few seed points need to be supplied by an operator. To evaluate the performance of the proposed method, a set of experiments was designed using two stereoscopic pairs of low-resolution aerial images and a TIN-based DTM with an average resolution of 1 m. The experimental results showed that the proposed method worked properly, even when faced with anomalies along roads, such as obstructions caused by shadows and trees.

Pure spinor superstring partition function

Pós-graduação em Física - IFT

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

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.

Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.