Modelagem numérica de escoamento em padrão anular com transferência de calor e massa

Annular flow is the prevailing pattern in transport and energy conversion systems and therefore, one of the most important patterns in multiphase flow in ducts. The correct prediction of the pressure gradient and heat transfer coefficient is essential for optimizing the system s capacity. The objective of this work is to develop and implement a numerical algorithm capable of predicting hydrodynamic and thermal characteristics for upflow, vertical, annular flow. The numerical algorithm is then complemented with the physical modeling of phenomena that occurs in this flow pattern. These are, turbulence, entrainment and deposition and phase change. For the development of the numerical model, axial diffusion of heat and momentum is neglected. In this way the time-averaged equations are solved in their parabolic form obtaining the velocity and temperature profiles for each axial step at a time, together with the global parameters, namely, pressure gradient, mean film thickness and heat transfer coefficient, as well as their variation in the axial direction. The model is validated for the following conditions: fully-developed laminar flow with no entrainment; fully developed laminar flow with heat transfer, fully-developed turbulent flow with entrained drops, developing turbulent annular flow with entrained drops, and turbulent flow with heat transfer and phase change

An investigation of Hebbian phase sequences as assembly graphs

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition.

An investigation of Hebbian phase sequences as assembly graphs

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition.

Selective Coupling between Theta Phase and Neocortical Fast Gamma Oscillations during REM-Sleep in Mice

TORT, A. B. L. ; SCHEFFER-TEIXEIRA, R ; Souza, B.C. ; DRAGUHN, A. ; BRANKACK, J. . Theta-associated high-frequency oscillations (110-160 Hz) in the hippocampus and neocortex. Progress in Neurobiology , v. 100, p. 1-14, 2013.

Increased hippocampal excitability and impaired spatial memory function in mice lacking VGLUT2 selectively in neurons defined by tyrosine hydroxylase promoter activity

Three populations of neurons expressing the vesicular glutamate transporter 2 (Vglut2) were recently described in the A10 area of the mouse midbrain, of which two populations were shown to express the gene encoding, the rate-limiting enzyme for catecholamine synthesis, tyrosine hydroxylase (TH).One of these populations (‘‘TH– Vglut2 Class1’’) also expressed the dopamine transporter (DAT) gene while one did not ("TH–Vglut2 Class2"), and the remaining population did not express TH at all ("TH-Vglut2-only"). TH is known to be expressed by a promoter which shows two phases of activation, a transient one early during embryonal development, and a later one which gives rise to stable endogenous expression of the TH gene. The transient phase is, however, not specific to catecholaminergic neurons, a feature taken to advantage here as it enabled Vglut2 gene targeting within all three A10 populations expressing this gene, thus creating a new conditional knockout. These knockout mice showed impairment in spatial memory function. Electrophysiological analyses revealed a profound alteration of oscillatory activity in the CA3 region of the hippocampus. In addition to identifying a novel role for Vglut2 in hippocampus function, this study points to the need for improved genetic tools for targeting of the diversity of subpopulations of the A10 area

Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

Efeitos da interação dipolar na nucleação de vórtices em nano-cilindros magnéticos

The effect of confinement on the magnetic structure of vortices of dipolar coupled ferromagnetic nanoelements is an issue of current interest, not only for academic reasons, but also for the potential impact in a number of promising applications. Most applications, such as nano-oscillators for wireless data transmission, benefit from the possibility of tailoring the vortex core magnetic pattern. We report a theoretical study of vortex nucleation in pairs of coaxial iron and Permalloy cylinders, with diameters ranging from 21nm to 150nm, and 12nm and 21nm thicknesses, separated by a non-magnetic layer. 12nm thick iron and Permalloy isolated (single) cylinders do not hold a vortex, and 21nm isolated cylinders hold a vortex. Our results indicate that one may tailor the magnetic structure of the vortices, and the relative chirality, by selecting the thickness of the non-magnetic spacer and the values of the cylinders diameters and thicknesses. Also, the dipolar interaction may induce vortex formation in pairs of 12nm thick nanocylinders and inhibit the formation of vortices in pairs of 21nm thick nanocylinders. These new phases are formed according to the value of the distance between the cylinderes. Furthermore, we show that the preparation route may control relative chirality and polarity of the vortex pair. For instance: by saturating a pair of Fe 81nm diameter, 21nm thickness cylinders, along the crystalline anisotropy direction, a pair of 36nm core diameter vortices, with same chirality and polarity is prepared. By saturating along the perpendicular direction, one prepares a 30nm diameter core vortex pair, with opposite chirality and opposite polarity. We also present a theoretical discussion of the impact of vortices on the thermal hysteresis of a pair of interface biased elliptical iron nanoelements, separated by an ultrathin nonmagnetic insulating layer. We have found that iron nanoelements exchange coupled to a noncompensated NiO substrate, display thermal hysteresis at room temperature, well below the iron Curie temperature. The thermal hysteresis consists in different sequences of magnetic states in the heating and cooling branches of a thermal loop, and originates in the thermal reduction of the interface field, and on the rearrangements of the magnetic structure at high temperatures, 5 produce by the strong dipolar coupling. The width of the thermal hysteresis varies from 500 K to 100 K for lateral dimensions of 125 nm x 65 nm and 145 nm x 65 nm. We focus on the thermal effects on two particular states: the antiparallel state, which has, at low temperatures, the interface biased nanoelement with the magnetization aligned with the interface field and the second nanoelement aligned opposite to the interface field; and in the parallel state, which has both nanoelements with the magnetization aligned with the interface field at low temperatures. We show that the dipolar interaction leads to enhanced thermal stability of the antiparallel state, and reduces the thermal stability of the parallel state. These states are the key phases in the application of pairs of ferromagnetic nanoelements, separated by a thin insulating layer, for tunneling magnetic memory cells. We have found that for a pair of 125nm x 65nm nanoelements, separated by 1.1nm, and low temperature interface field strength of 5.88kOe, the low temperature state (T = 100K) consists of a pair of nearly parallel buckle-states. This low temperature phase is kept with minor changes up to T= 249 K when the magnetization is reduced to 50% of the low temperature value due to nucleation of a vortex centered around the middle of the free surface nanoelement. By further increasing the temperature, there is another small change in the magnetization due to vortex motion. Apart from minor changes in the vortex position, the high temperature vortex state remains stable, in the cooling branch, down to low temperatures. We note that wide loop thermal hysteresis may pose limits on the design of tunneling magnetic memory cells

Caracterização de células de lugar no hipocampo e de suas relações com oscilações do potencial de campo local

The main inputs to the hippocampus arise from the entorhinal cortex (EC) and form a loop involving the dentate gyrus, CA3 and CA1 hippocampal subfields and then back to EC. Since the discovery that the hippocampus is involved in memory formation in the 50's, this region and its circuitry have been extensively studied. Beyond memory, the hippocampus has also been found to play an important role in spatial navigation. In rats and mice, place cells show a close relation between firing rate and the animal position in a restricted area of the environment, the so-called place field. The firing of place cells peaks at the center of the place field and decreases when the animal moves away from it, suggesting the existence of a rate code for space. Nevertheless, many have described the emergence of hippocampal network oscillations of multiple frequencies depending on behavioral state, which are believed to be important for temporal coding. In particular, theta oscillations (5-12 Hz) exhibit a spatio-temporal relation with place cells known as phase precession, in which place cells consistently change the theta phase of spiking as the animal traverses the place field. Moreover, current theories state that CA1, the main output stream of the hippocampus, would interplay inputs from EC and CA3 through network oscillations of different frequencies, namely high gamma (60-100 Hz; HG) and low gamma (30-50 Hz; LG), respectively, which tend to be nested in different phases of the theta cycle. In the present dissertation we use a freely available online dataset to make extensive computational analyses aimed at reproducing classical and recent results about the activity of place cells in the hippocampus of freely moving rats. In particular, we revisit the debate of whether phase precession is due to changes in firing frequency or space alone, and conclude that the phenomenon cannot be explained by either factor independently but by their joint influence. We also perform novel analyses investigating further characteristics of place cells in relation to network oscillations. We show that the strength of theta modulation of spikes only marginally affects the spatial information content of place cells, while the mean spiking theta phase has no influence on spatial information. Further analyses reveal that place cells are also modulated by theta when they fire outside the place field. Moreover, we find that the firing of place cells within the theta cycle is modulated by HG and LG amplitude in both CA1 and EC, matching cross-frequency coupling results found at the local field potential level. Additionally, the phase-amplitude coupling in CA1 associated with spikes inside the place field is characterized by amplitude modulation in the 40-80 Hz range. We conclude that place cell firing is embedded in large network states reflected in local field potential oscillations and suggest that their activity might be seen as a dynamic state rather than a fixed property of the cell.

Medium change monitoring using ambient seismic noise and coda wave interferometry: examples from intraplate NE Brazil and the Mid-Atlantic Ridge

This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake’s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers’ amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault’s region induced by the earthquake.

Medium change monitoring using ambient seismic noise and coda wave interferometry: examples from intraplate NE Brazil and the Mid-Atlantic Ridge

This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake’s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers’ amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault’s region induced by the earthquake.

Selective Coupling between Theta Phase and Neocortical Fast Gamma Oscillations during REM-Sleep in Mice

TORT, A. B. L. ; SCHEFFER-TEIXEIRA, R ; Souza, B.C. ; DRAGUHN, A. ; BRANKACK, J. . Theta-associated high-frequency oscillations (110-160 Hz) in the hippocampus and neocortex. Progress in Neurobiology , v. 100, p. 1-14, 2013.

Increased hippocampal excitability and impaired spatial memory function in mice lacking VGLUT2 selectively in neurons defined by tyrosine hydroxylase promoter activity

Three populations of neurons expressing the vesicular glutamate transporter 2 (Vglut2) were recently described in the A10 area of the mouse midbrain, of which two populations were shown to express the gene encoding, the rate-limiting enzyme for catecholamine synthesis, tyrosine hydroxylase (TH).One of these populations (‘‘TH– Vglut2 Class1’’) also expressed the dopamine transporter (DAT) gene while one did not ("TH–Vglut2 Class2"), and the remaining population did not express TH at all ("TH-Vglut2-only"). TH is known to be expressed by a promoter which shows two phases of activation, a transient one early during embryonal development, and a later one which gives rise to stable endogenous expression of the TH gene. The transient phase is, however, not specific to catecholaminergic neurons, a feature taken to advantage here as it enabled Vglut2 gene targeting within all three A10 populations expressing this gene, thus creating a new conditional knockout. These knockout mice showed impairment in spatial memory function. Electrophysiological analyses revealed a profound alteration of oscillatory activity in the CA3 region of the hippocampus. In addition to identifying a novel role for Vglut2 in hippocampus function, this study points to the need for improved genetic tools for targeting of the diversity of subpopulations of the A10 area