Shear viscosity from thermal fluctuations in relativistic conformal fluid dynamics

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

Supercritical fluid extraction from fennel (Foeniculum vulgare): global yield, composition and kinetic data

Supercritical fluid extraction (SFE) from solids has proven to be technically feasible for almost any system; nonetheless, its economical viability has been proven for a restricted number of systems. A common practice is to compare the cost of manufacturing of vegetable extracts by a variety of techniques without deeply considering the huge differences in composition and functional properties among the various types of extracts obtained; under this circumstance, the cost of manufacturing do not favor SFE. Additionally, the influence of external parameters such as the agronomic conditions and the SFE system geometry are not considered. In the present work, these factors were studied for the system fennel seeds + CO2. The effects of the harvesting season and the degree of maturation on the global yields for the system fennel seeds + CO2 were analyzed at 300 bar and 40 degrees C. The effects of the pressure on the global yields were determined for the temperatures of 30 and 40 degrees C. Kinetics experiments were done for various ratios of bed height to bed diameter. Fennel extracts were also obtained by hydrodistillation and low-pressure solvent extraction. The chemical composition of the fennel extracts were determined by gas chromatography. The SFE maximum global yield (12.5%, dry basis) was obtained with dry harvested fennel seeds. Anethole and fenchone were the major constituents of the extract; the following fat acids palmitic (C16H32O2), palmitoleic stearic (C18H36O2), oleic (C18H34O2), linoleic (C18H32O2) and linolenic (C18H30O2) were also detected in the extracts. A relation between amounts of feed and solvent, bed height and diameter, and solvent flow rate was proposed. The models of Sovova, Goto et al. and Tan and Lion were capable of describing the mass transfer kinetics. (c) 2005 Elsevier B.V. All rights reserved.

Antagonism of clonidine injected intracerebroventricularly in different models of salt intake

Clonidine, an alpha 2-adrenergic agonist, injected into the brain inhibits salt intake of animals treated by the diuretic model of sodium depletion. In the present study, we address the question of whether central injection of clonidine also inhibits salt intake in animals deprived of water or in the need-free state. Saline or clonidine (30 nmol) was injected into the anterior third ventricle of 24-h sodium-depleted (furosemide + removal of ambient sodium), of 24-h water-deprived and of normovolemic (need-free state) adult male rats, Clonidine injected intracerebroventricularly (icv) inhibited the 1.5% NaCl intake for 120 min by 50 to 90% in every model tested. Therefore, different models of salt intake are inhibited by icv injection of clonidine, Idazoxan, an alpha 2-adrenergic antagonist, injected icy at a dose of 160 nmol, inhibited the effect of clonidine only in the furosemide + removal of ambient sodium model of salt intake. This indicates that the antagonism of this effect by idazoxan is dependent on the body fluid/sodium status of the animal.

Rheological properties and fluid dynamics of coffee extract

The rheological behavior of coffee extract with different water contents (49 to 90%) was studied at a wide range of temperatures (274 to 365 K) using a concentric cylinder rheometer. The flow curves followed different models depending on the concentration and temperature level. Newtonian behavior was observed at high values of water content and temperature, changing to power law as these values were decreased. The Newtonian viscosity as well as the consistency and behavior index could be well correlated by functions simultaneously dependent on temperature and water content. The rheological parameters, together with experimental values of pressure loss in tube flow, were used to calculate friction factors. These showed to be in good agreement with those resulting from classical theoretical and empirical equations, thus confirming the reliability of the rheological measurements.

Fuzzy control embedded in microcontroller and applied to an experimental apparatus using magnetorheological fluid damper

This work focuses on applying fuzzy control embedded in microcontrollers in an experimental apparatus using magnetorheological fluid damper. The non-linear behavior of the magnetorheological dampers associated with the parametric variations on vehicle suspension models corroborate the use of the fuzzy controllers. The fundamental formulation of this controller is discussed and its performance is shown through numeric simulations. An experimental apparatus representing a two degree of freedom system containing a magnetorheological damper is used to identify the main parameters and to evaluate the performance of the closed-loop system with the embedded low-cost microcontroller-based fuzzy controller. © 2013 Brazilian Society for Automatics - SBA.

Antidiarrheal and intestinal antiinflammatory activities of a methanolic extract of Qualea parviflora Mart. in experimental models

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

MMP-2 and MMP-9 activities and TIMP-1 and TIMP-2 expression in the prostatic tissue of two ethanol-preferring rat models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analysis of energy dissipation in stirred suspension polymerisation reactors using computational fluid dynamics

This work evaluates the spatial distribution of normalised rates of droplet breakage and droplet coalescence in liquidliquid dispersions maintained in agitated tanks at operation conditions normally used to perform suspension polymerisation reactions. Particularly, simulations are performed with multiphase computational fluid dynamics (CFD) models to represent the flow field in liquidliquid styrene suspension polymerisation reactors for the first time. CFD tools are used first to compute the spatial distribution of the turbulent energy dissipation rates (e) inside the reaction vessel; afterwards, normalised rates of droplet breakage and particle coalescence are computed as functions of e. Surprisingly, multiphase simulations showed that the rates of energy dissipation can be very high near the free vortex surfaces, which has been completely neglected in previous works. The obtained results indicate the existence of extremely large energy dissipation gradients inside the vessel, so that particle breakage occurs primarily in very small regions that surround the impeller and the free vortex surface, while particle coalescence takes place in the liquid bulk. As a consequence, particle breakage should be regarded as an independent source term or a boundary phenomenon. Based on the obtained results, it can be very difficult to justify the use of isotropic assumptions to formulate particle population balances in similar systems, even when multiple compartment models are used to describe the fluid dynamic behaviour of the agitated vessel. (C) 2011 Canadian Society for Chemical Engineering

Exponential stability for a plate equation with p-Laplacian and memory terms

This paper is concerned with the energy decay for a class of plate equations with memory and lower order perturbation of p-Laplacian type, utt+?2u-?pu+?0tg(t-s)?u(s)ds-?ut+f(u)=0inOXR+, with simply supported boundary condition, where O is a bounded domain of RN, g?>?0 is a memory kernel that decays exponentially and f(u) is a nonlinear perturbation. This kind of problem without the memory term models elastoplastic flows.

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e. g., fractional Brownian motion, Levy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation sigma t which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

B cells Can Modulate the CD8 Memory T Cell after DNA Vaccination Against Experimental Tuberculosis

Abstract Background Although B cells are important as antigen presenting cells (APC) during the immune response, their role in DNA vaccination models is unknown. Methods In this study in vitro and in vivo experiments were performed to evaluate the ability of B cells to protect mice against Mycobacterium tuberculosis challenge. Results In vitro and in vivo studies showed that B cells efficiently present antigens after naked plasmid pcDNA3 encoding M. leprae 65-kDa heat shock protein (pcDNA3-Hsp65) internalization and protect B knock-out (BKO) mice against Mycobacterium tuberculosis infection. pcDNA3-Hsp65-transfected B cells adoptively transferred into BKO mice rescued the memory phenotypes and reduced the number of CFU compared to wild-type mice. Conclusions These data not only suggest that B cells play an important role in the induction of CD8 T cells but also that they improve bacterial clearance in DNA vaccine model.

What ethologically based models have taught us about the neural systems underlying fear and anxiety

Classical Pavlovian fear conditioning to painful stimuli has provided the generally accepted view of a core system centered in the central amygdala to organize fear responses. Ethologically based models using other sources of threat likely to be expected in a natural environment, such as predators or aggressive dominant conspecifics, have challenged this concept of a unitary core circuit for fear processing. We discuss here what the ethologically based models have told us about the neural systems organizing fear responses. We explored the concept that parallel paths process different classes of threats, and that these different paths influence distinct regions in the periaqueductal gray - a critical element for the organization of all kinds of fear responses. Despite this parallel processing of different kinds of threats, we have discussed an interesting emerging view that common cortical-hippocampal-amygdalar paths seem to be engaged in fear conditioning to painful stimuli, to predators and, perhaps, to aggressive dominant conspecifics as well. Overall, the aim of this review is to bring into focus a more global and comprehensive view of the systems organizing fear responses.

The growth of glioblastoma orthotopic xenografts in nude mice is directly correlated with impaired object recognition memory

Cognitive dysfunction is found in patients with brain tumors and there is a need to determine whether it can be replicated in an experimental model. In the present study, the object recognition (OR) paradigm was used to investigate cognitive performance in nude mice, which represent one of the most important animal models available to study human tumors in vivo. Mice with orthotopic xenografts of the human U87MG glioblastoma cell line were trained at 9, 14, and 18days (D9, D14, and D18, respectively) after implantation of 5×10(5) cells. At D9, the mice showed normal behavior when tested 90min or 24h after training and compared to control nude mice. Animals at D14 were still able to discriminate between familiar and novel objects, but exhibited a lower performance than animals at D9. Total impairment in the OR memory was observed when animals were evaluated on D18. These alterations were detected earlier than any other clinical symptoms, which were observed only 22-24days after tumor implantation. There was a significant correlation between the discrimination index (d2) and time after tumor implantation as well as between d2 and tumor volume. These data indicate that the OR task is a robust test to identify early behavior alterations caused by glioblastoma in nude mice. In addition, these results suggest that OR task can be a reliable tool to test the efficacy of new therapies against these tumors.

Models and methods for power monolithic microwave integrated circuits

Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.

Design of wireless sensor networks for fluid dynamic applications

In fluid dynamics research, pressure measurements are of great importance to define the flow field acting on aerodynamic surfaces. In fact the experimental approach is fundamental to avoid the complexity of the mathematical models for predicting the fluid phenomena. It’s important to note that, using in-situ sensor to monitor pressure on large domains with highly unsteady flows, several problems are encountered working with the classical techniques due to the transducer cost, the intrusiveness, the time response and the operating range. An interesting approach for satisfying the previously reported sensor requirements is to implement a sensor network capable of acquiring pressure data on aerodynamic surface using a wireless communication system able to collect the pressure data with the lowest environmental–invasion level possible. In this thesis a wireless sensor network for fluid fields pressure has been designed, built and tested. To develop the system, a capacitive pressure sensor, based on polymeric membrane, and read out circuitry, based on microcontroller, have been designed, built and tested. The wireless communication has been performed using the Zensys Z-WAVE platform, and network and data management have been implemented. Finally, the full embedded system with antenna has been created. As a proof of concept, the monitoring of pressure on the top of the mainsail in a sailboat has been chosen as working example.