879 resultados para Computation time delay
Resumo:
We consider scalar perturbations in the time dependent Horava-Witten model in order to probe its stability. We show that during the nonsingular epoque the model evolves without instabilities until it encounters the curvature singularity where a big crunch is supposed to occur. We compute the frequencies of the scalar field oscillation during the stable period and show how the oscillations can be used to prove the presence of such a singularity.
Resumo:
We present a scheme for quasiperfect transfer of polariton states from a sender to a spatially separated receiver, both composed of high-quality cavities filled by atomic samples. The sender and the receiver are connected by a nonideal transmission channel -the data bus- modelled by a network of lossy empty cavities. In particular, we analyze the influence of a large class of data-bus topologies on the fidelity and transfer time of the polariton state. Moreover, we also assume dispersive couplings between the polariton fields and the data-bus normal modes in order to achieve a tunneling-like state transfer. Such a tunneling-transfer mechanism, by which the excitation energy of the polariton effectively does not populate the data-bus cavities, is capable of attenuating appreciably the dissipative effects of the data-bus cavities. After deriving a Hamiltonian for the effective coupling between the sender and the receiver, we show that the decay rate of the fidelity is proportional to a cooperativity parameter that weighs the cost of the dissipation rate against the benefit of the effective coupling strength. The increase of the fidelity of the transfer process can be achieved at the expense of longer transfer times. We also show that the dependence of both the fidelity and the transfer time on the network topology is analyzed in detail for distinct regimes of parameters. It follows that the data-bus topology can be explored to control the time of the state-transfer process.
Resumo:
In this paper we detail some results advanced in a recent letter [Prado et al., Phys. Rev. Lett. 102, 073008 (2009).] showing how to engineer reservoirs for two-level systems at absolute zero by means of a time-dependent master equation leading to a nonstationary superposition equilibrium state. We also present a general recipe showing how to build nonadiabatic coherent evolutions of a fermionic system interacting with a bosonic mode and investigate the influence of thermal reservoirs at finite temperature on the fidelity of the protected superposition state. Our analytical results are supported by numerical analysis of the full Hamiltonian model.
Resumo:
Background data: Technology and physical exercise can enhance physical performance during aging. Objective: The purpose of this study was to investigate the effects of infrared-light-emitting diode (LED) illumination (850 nm) applied during treadmill training. Materials and methods: Twenty postmenopausal women participated in this study. They were randomly divided into two groups. The LED group performed treadmill training associated with infrared-LED illumination (n = 10) and the control group performed only treadmill training (n = 10). The training was performed during 3 months, twice a week during 30 min at intensities between 85 and 90% of maximal heart rate. The irradiation parameters were 31 mW/cm(2), treatment time 30 min, 14,400 J of total energy and 55.8 J/cm(2) of fluence. Physiological, biomechanical, and body composition parameters were measured at the baseline and after 3 months. Results: Both groups improved the time of tolerance limit (Tlim) (p < 0.05) during submaximal constant-speed testing. The peak torque did not differ between groups. However, the results showed significantly higher values of power [from 56 +/- 10 to 73 +/- 8W (p = 0.002)] and total work [from 1,537 +/- 295 to 1,760 +/- 262 J (p = 0.006)] for the LED group when compared to the control group [power: from 58 +/- 14 to 60 +/- 15W (p >= 0.05) and total work: from 1,504 +/- 404 to 1,622 +/- 418 J (p >= 0.05)]. The fatigue significantly increased for the control group [from 51 +/- 6 to 58 +/- 5 % (p = 0.04)], but not for the LED group [from 60 +/- 10 to 60 +/- 4 % (p >= 0.05)]. No significant differences in body composition were observed for either group. Conclusions: Infrared-LED illumination associated with treadmill training can improve muscle power and delay leg fatigue in postmenopausal women.
Resumo:
We show that measurements of finite duration performed on an open two-state system can protect the initial state from a phase-noisy environment, provided the measured observable does not commute with the perturbing interaction. When the measured observable commutes with the environmental interaction, the finite-duration measurement accelerates the rate of decoherence induced by the phase noise. For the description of the measurement of an observable that is incompatible with the interaction between system and environment, we have found an approximate analytical expression, valid at zero temperature and weak coupling with the measuring device. We have tested the validity of the analytical predictions against an exact numerical approach, based on the superoperator-splitting method, that confirms the protection of the initial state of the system. When the coupling between the system and the measuring apparatus increases beyond the range of validity of the analytical approximation, the initial state is still protected by the finite-time measurement, according with the exact numerical calculations.
Resumo:
The existence of quantum correlation (as revealed by quantum discord), other than entanglement and its role in quantum-information processing (QIP), is a current subject for discussion. In particular, it has been suggested that this nonclassical correlation may provide computational speedup for some quantum algorithms. In this regard, bulk nuclear magnetic resonance (NMR) has been successfully used as a test bench for many QIP implementations, although it has also been continuously criticized for not presenting entanglement in most of the systems used so far. In this paper, we report a theoretical and experimental study on the dynamics of quantum and classical correlations in an NMR quadrupolar system. We present a method for computing the correlations from experimental NMR deviation-density matrices and show that, given the action of the nuclear-spin environment, the relaxation produces a monotonic time decay in the correlations. Although the experimental realizations were performed in a specific quadrupolar system, the main results presented here can be applied to whichever system uses a deviation-density matrix formalism.
Resumo:
The exact exchange-correlation (XC) potential in time-dependent density-functional theory (TDDFT) is known to develop steps and discontinuities upon change of the particle number in spatially confined regions or isolated subsystems. We demonstrate that the self-interaction corrected adiabatic local-density approximation for the XC potential has this property, using the example of electron loss of a model quantum well system. We then study the influence of the XC potential discontinuity in a real-time simulation of a dissociation process of an asymmetric double quantum well system, and show that it dramatically affects the population of the resulting isolated single quantum wells. This indicates the importance of a proper account of the discontinuities in TDDFT descriptions of ionization, dissociation or charge transfer processes.
Resumo:
Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.
Resumo:
Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.
Resumo:
We consider a Random Walk in Random Environment (RWRE) moving in an i.i.d. random field of obstacles. When the particle hits an obstacle, it disappears with a positive probability. We obtain quenched and annealed bounds on the tails of the survival time in the general d-dimensional case. We then consider a simplified one-dimensional model (where transition probabilities and obstacles are independent and the RWRE only moves to neighbour sites), and obtain finer results for the tail of the survival time. In addition, we study also the ""mixed"" probability measures (quenched with respect to the obstacles and annealed with respect to the transition probabilities and vice-versa) and give results for tails of the survival time with respect to these probability measures. Further, we apply the same methods to obtain bounds for the tails of hitting times of Branching Random Walks in Random Environment (BRWRE).
Resumo:
Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.
Resumo:
Aims: To investigate the expression of sboA and ituD genes among strains of Bacillus spp. at different pH and temperature. Methods and Results: Different Bacillus strains from the Amazon basin and Bacillus subtilis ATCC 19659 were investigated for the production of subtilosin A and iturin A by qRT-PCR, analysing sboA and ituD gene expression under different culture conditions. Amazonian strains presented a general gene expression level lower than B. subtilis ATCC 19659 for sboA. In contrast, when analysing the expression of ituD gene, the strains from the Amazon, particularly P40 and P45B, exhibited higher levels of expression. Changes in pH (6 and 8) and temperature (37 and 42 degrees C) caused a decrease in sboA expression, but increased ituD expression among strains from Amazonian environment. Conclusions: Temperature and pH have an important influence on the expression of genes sboA (subtilosin A) and ituD (iturin A) among Bacillus spp. The strains P40 and P45B can be useful for the production of antimicrobial peptide iturin A. Significance and Impact of the Study: Monitoring the expression of essential biosynthetic genes by qRT-PCR is a valuable tool for optimization of the production of antimicrobial peptides.
Resumo:
It has been demonstrated that laser induced breakdown spectrometry (LIBS) can be used as an alternative method for the determination of macro (P, K. Ca, Mg) and micronutrients (B, Fe, Cu, Mn, Zn) in pellets of plant materials. However, information is required regarding the sample preparation for plant analysis by LIBS. In this work, methods involving cryogenic grinding and planetary ball milling were evaluated for leaves comminution before pellets preparation. The particle sizes were associated to chemical sample properties such as fiber and cellulose contents, as well as to pellets porosity and density. The pellets were ablated at 30 different sites by applying 25 laser pulses per site (Nd:YAG@1064 nm, 5 ns, 10 Hz, 25J cm(-2)). The plasma emission collected by lenses was directed through an optical fiber towards a high resolution echelle spectrometer equipped with an ICCD. Delay time and integration time gate were fixed at 2.0 and 4.5 mu s, respectively. Experiments carried out with pellets of sugarcane, orange tree and soy leaves showed a significant effect of the plant species for choosing the most appropriate grinding conditions. By using ball milling with agate materials, 20 min grinding for orange tree and soy, and 60 min for sugarcane leaves led to particle size distributions generally lower than 75 mu m. Cryogenic grinding yielded similar particle size distributions after 10 min for orange tree, 20 min for soy and 30 min for sugarcane leaves. There was up to 50% emission signal enhancement on LIBS measurements for most elements by improving particle size distribution and consequently the pellet porosity. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
The aim of this work is to demonstrate the feasibility of laser induced breakdown spectrometry (LIBS) for the determination of macro and micronutrients in multielement tablets. The experimental setup was designed by using a laser Q-switch (Nd:YAG, 10 Hz, lambda = 1064 nm) and the emission signals were collected by lenses into an optical fiber coupled to an echelle spectrometer equipped with a high-resolution intensified charge coupled device (ICCD). Tablets were cryogenically ground and thereafter pelletized before LIBS analysis. Calibration curves were made by employing samples and mixtures of commercial multielement tablets with binders at different ratios. Best results were achieved by using the following experimental conditions: 29 J cm(-2) laser fluence, 165 mm lens to sample distance (f = 200 mm), 2.0 mu s delay time, 5.0 mu s integration time and 5 accumulated laser pulses. In general, the results obtained by the proposed LIBS procedure were in agreement with those obtained by ICP OES from the corresponding acid digests and coefficients variation of LIBS measurements varied from 2 to 16%. The metrological figures of merit indicate that LIBS fits for the intended purposes, and can be recommended for the analysis of multielement tablets and similar matrices aiming the determination of Ca, Cu, Fe, Mg, Mn, P and Zn.
Resumo:
A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.