Energy-level statistics of interacting trapped bosons

It is a well-established fact that statistical properties of energy-level spectra are the most efficient tool to characterize nonintegrable quantum systems. The statistical behavior of different systems such as complex atoms, atomic nuclei, two-dimensional Hamiltonians, quantum billiards, and noninteracting many bosons has been studied. The study of statistical properties and spectral fluctuations in interacting many-boson systems has developed interest in this direction. We are especially interested in weakly interacting trapped bosons in the context of Bose-Einstein condensation (BEC) as the energy spectrum shows a transition from a collective nature to a single-particle nature with an increase in the number of levels. However this has received less attention as it is believed that the system may exhibit Poisson-like fluctuations due to the existence of an external harmonic trap. Here we compute numerically the energy levels of the zero-temperature many-boson systems which are weakly interacting through the van der Waals potential and are confined in the three-dimensional harmonic potential. We study the nearest-neighbor spacing distribution and the spectral rigidity by unfolding the spectrum. It is found that an increase in the number of energy levels for repulsive BEC induces a transition from a Wigner-like form displaying level repulsion to the Poisson distribution for P(s). It does not follow the Gaussian orthogonal ensemble prediction. For repulsive interaction, the lower levels are correlated and manifest level-repulsion. For intermediate levels P(s) shows mixed statistics, which clearly signifies the existence of two energy scales: external trap and interatomic interaction, whereas for very high levels the trapping potential dominates, generating a Poisson distribution. Comparison with mean-field results for lower levels are also presented. For attractive BEC near the critical point we observe the Shnirelman-like peak near s = 0, which signifies the presence of a large number of quasidegenerate states.

A stochastic spatially structured epidemic model with diffusive processes

We developed a stochastic lattice model to describe the vector-borne disease (like yellow fever or dengue). The model is spatially structured and its dynamical rules take into account the diffusion of vectors. We consider a bipartite lattice, forming a sub-lattice of human and another occupied by mosquitoes. At each site of lattice we associate a stochastic variable that describes the occupation and the health state of a single individual (mosquito or human). The process of disease transmission in the human population follows a similar dynamic of the Susceptible-Infected-Recovered model (SIR), while the disease transmission in the mosquito population has an analogous dynamic of the Susceptible-Infected-Susceptible model (SIS) with mosquitos diffusion. The occurrence of an epidemic is directly related to the conditional probability of occurrence of infected mosquitoes (human) in the presence of susceptible human (mosquitoes) on neighborhood. The probability of diffusion of mosquitoes can facilitate the formation of pairs Susceptible-Infected enabling an increase in the size of the epidemic. Using an asynchronous dynamic update, we study the disease transmission in a population initially formed by susceptible individuals due to the introduction of a single mosquito (human) infected. We find that this model exhibits a continuous phase transition related to the existence or non-existence of an epidemic. By means of mean field approximations and Monte Carlo simulations we investigate the epidemic threshold and the phase diagram in terms of the diffusion probability and the infection probability.

Irreversibility by competition on a Glauber-Ising model by means of the entropy production.

An out of equilibrium Ising model subjected to an irreversible dynamics is analyzed by means of a stochastic dynamics, on a effort that aims to understand the observed critical behavior as consequence of the intrinsic microscopic characteristics. The study focus on the kinetic phase transitions that take place by assuming a lattice model with inversion symmetry and under the influence of two competing Glauber dynamics, intended to describe the stationary states using the entropy production, which characterize the system behavior and clarifies its reversibility conditions. Thus, it is considered a square lattice formed by two sublattices interconnected, each one of which is in contact with a heat bath at different temperature from the other. Analytical and numerical treatments are faced, using mean-field approximations and Monte Carlo simulations. For the one dimensional model exact results for the entropy production were obtained, though in this case the phase transition that takes place in the two dimensional counterpart is not observed, fact which is in accordance with the behavior shared by lattice models presenting inversion symmetry. Results found for the stationary state show a critical behavior of the same class as the equilibrium Ising model with a phase transition of the second order, which is evidenced by a divergence with an exponent µ ¼ 0:003 of the entropy production derivative.

Structure-based drug design studies on a series of aldolase inhibitors

Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.

Use of recent geoid models to estimate mean dynamic topography and geostrophic currents in South Atlantic and Brazil Malvinas confluence

The use of geoid models to estimate the Mean Dynamic Topography was stimulated with the launching of the GRACE satellite system, since its models present unprecedented precision and space-time resolution. In the present study, besides the DNSC08 mean sea level model, the following geoid models were used with the objective of computing the MDTs: EGM96, EIGEN-5C and EGM2008. In the method adopted, geostrophic currents for the South Atlantic were computed based on the MDTs. In this study it was found that the degree and order of the geoid models affect the determination of TDM and currents directly. The presence of noise in the MDT requires the use of efficient filtering techniques, such as the filter based on Singular Spectrum Analysis, which presents significant advantages in relation to conventional filters. Geostrophic currents resulting from geoid models were compared with the HYCOM hydrodynamic numerical model. In conclusion, results show that MDTs and respective geostrophic currents calculated with EIGEN-5C and EGM2008 models are similar to the results of the numerical model, especially regarding the main large scale features such as boundary currents and the retroflection at the Brazil-Malvinas Confluence.

Using AMS combined with mineral shape preferred orientation analysis to understand the emplacement fabrics of the Apiai gabbro-norite (Ribeira Belt, SE Brazil)

The Apiai gabbro-norite is a massive fine-grained Neoproterozoic intrusion emplaced in a core of synformal structure that deforms low-grade marine metasedimentary rocks of the Ribeira Belt of south-eastern Brazil. The lack of visible magmatic layering or any internal fabric has been a major limitation in deciding whether the emplacement occurred before or after the regional folding. To assist in the tectonic interpretations, we combine low-field anisotropy of magnetic susceptibility (AMS) and silicate shape preferred orientation (SPO) to reveal the internal structure of the mafic intrusion. Magnetic data indicate a mean susceptibility of about 10(-2) SI and a mean anisotropy degree (P) of about 1.08, essentially yielded by titanomagnetite. The magnetic and silicate foliations for P >= 1.10 are parallel to each other, while the lineations tend to scatter on the foliation plane, in agreement with the dominant oblate symmetry of the AMS and SPO ellipsoids. For lower P values, the magnetic and silicate fabrics vary from coaxial to oblique, and for P <= 1.05, their shapes and orientations can be quite distinct. The crystal size distribution (CSD) of plagioclase for P > 1.05 is log linear, in agreement with a bulk simple crystallisation history. These results combined show that for a strong SPO, corresponding to a magnetic anisotropy above 1.10, AMS is a reliable indicator of the magmatic fabric. They indicate that the Apiai gabbro-norite consists of sill-like body that was inclined gently to the north by the regional folding.

Overview of the South American Biomass burning analysis (SAMBBA) field experiment.

Biomass burning represents one of the largest sources of particulate matter to the atmosphere, which results in a significant perturbation to the Earth’s radiative balance coupled with serious negative impacts on public health. Globally, biomass burning aerosols are thought to exert a small warming effect of 0.03 Wm-2, however the uncertainty is 4 times greater than the central estimate. On regional scales, the impact is substantially greater, particularly in areas such as the Amazon Basin where large, intense and frequent burning occurs on an annual basis for several months (usually from August-October). Furthermore, a growing number of people live within the Amazon region, which means that they are subject to the deleterious effects on their health from exposure to substantial volumes of polluted air. Initial results from the South American Biomass Burning Analysis (SAMBBA) field experiment, which took place during September and October 2012 over Brazil, are presented here. A suite of instrumentation was flown on-board the UK Facility for Airborne Atmospheric Measurement (FAAM) BAe-146 research aircraft and was supported by ground based measurements, with extensive measurements made in Porto Velho, Rondonia. The aircraft sampled a range of conditions with sampling of fresh biomass burning plumes, regional haze and elevated biomass burning layers within the free troposphere. The physical, chemical and optical properties of the aerosols across the region will be characterized in order to establish the impact of biomass burning on regional air quality, weather and climate.