Structural real time control using fluid magnetorheologic damper

In the last decades there was a great development in the study of control systems to attenuate the harmful effect of natural events in great structures, as buildings and bridges. Magnetorheological fluid (MR), that is an intelligent material, has been considered in many proposals of project for these controllers. This work presents the controller design using feedback of states through LMI (Linear Matrix Inequalities) approach. The experimental test were carried out in a structure with two degrees of freedom with a connected shock absorber MR. Experimental tests were realized in order to specify the features of this semi-active controller. In this case, there exist states that are not measurable, so the feedback of the states involves the project of an estimator. The coupling of the MR damper causes a variation in dynamics properties, so an identification methods, based on experimental input/output signal was used to compare with the numerical application. The identification method of Prediction Error Methods - (PEM) was used to find the physical characteristics of the system through realization in modal space of states. This proposal allows the project of a semi-active control, where the main characteristic is the possibility of the variation of the damping coefficient.

Entropy variation in isothermal fluid flow considering real gas effects

The present paper concerns on the estimative of the pressure loss and entropy variation in an isothermal fluid flow, considering real gas effects. The 1D formulation is based on the isothermal compressibility module and on the thermal expansion coefficient in order to be applicable for both gas and liquid as pure substances. It is emphasized on the simple methodology description, which establishes a relationship between the formulation adopted for ideal gas and another considering real gas effects. A computational procedure has been developed, which can be used to determine the flow properties in duct with a variable area, where real gas behavior is significant. In order to obtain quantitative results, three virial coefficients for Helium equation of state are employed to determine the percentage difference in pressure and entropy obtained from different formulations. Results are presented graphically in the form of real gas correction factors, which can be applied to perfect gas calculations.

Assembling a xylanase-lichenase chimera through all-atom molecular dynamics simulations

Multifunctional enzyme engineering can improve enzyme cocktails for emerging biofuel technology. Molecular dynamics through structure-based models (SB) is an effective tool for assessing the tridimensional arrangement of chimeric enzymes as well as for inferring the functional practicability before experimental validation. This study describes the computational design of a bifunctional xylanase-lichenase chimera (XylLich) using the xynA and bglS genes from Bacillus subtilis. In silico analysis of the average solvent accessible surface area (SAS) and the root mean square fluctuation (RMSF) predicted a fully functional chimera, with minor fluctuations and variations along the polypeptide chains. Afterwards, the chimeric enzyme was built by fusing the xynA and bglS genes. XylLich was evaluated through small-angle X-ray scattering (SAXS) experiments, resulting in scattering curves with a very accurate fit to the theoretical protein model. The chimera preserved the biochemical characteristics of the parental enzymes, with the exception of a slight variation in the temperature of operation and the catalytic efficiency (k cat/Km). The absence of substantial shifts in the catalytic mode of operation was also verified. Furthermore, the production of chimeric enzymes could be more profitable than producing a single enzyme separately, based on comparing the recombinant protein production yield and the hydrolytic activity achieved for XylLich with that of the parental enzymes. © 2013 Elsevier B.V. All rights reserved.

Dynamics of cell and tissue genesis in the male reproductive system of ticks (Acari: Ixodidae) Amblyomma cajennese (Fabricius, 1787) and Amblyomma aureolatum (Pallas, 1772): a comparative analysis

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

A two-fluid model for refrigerant flow through adiabatic capillary tubes

This work presents a numerical model to simulate refrigerant flow through capillary tubes, commonly used as expansion devices in refrigeration systems. The flow is divided in a single-phase region, where the refrigerant is in the subcooled liquid state, and a region of two-phase flow. The capillary tube is considered straight and horizontal. The flow is taken as one-dimensional and adiabatic. Steady-state condition is also assumed and the metastable flow phenomena are neglected. The two-fluid model, considering the hydrodynamic and thermal non-equilibrium between the liquid and vapor phases, is applied to the two-phase flow region. Comparisons are made with experimental measurements of the mass flow rate and pressure distribution along two capillary tubes working with refrigerant R-134a in different operating conditions. The results indicate that the present model provides a better estimation than the commonly employed homogeneous model. Some computational results referring to the quality, void fraction, velocities, and temperatures of each phase are presented and discussed.

Combined active and semi-supervised learning using particle walking temporal dynamicscombined active and semi-supervised learning using particle walking temporal dynamics

Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Análise dinâmica não-linear de um sistema não-ideal, utilizando amortecedor magneto-reológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

MOLECULAR DYNAMICS STUDIES OF SIMPLE MODEL FLUIDS AND WATER CONFINED IN CARBON NANOTUBE

Molecular Dynamics (MD) simulation is one of the most important computational techniques with broad applications in physics, chemistry, chemical engineering, materials design and biological science. Traditional computational chemistry refers to quantum calculations based on solving Schrodinger equations. Later developed Density Functional Theory (DFT) based on solving Kohn-Sham equations became the more popular ab initio calculation technique which could deal with ~1000 atoms by explicitly considering electron interactions. In contrast, MD simulation based on solving classical mechanics equations of motion is a totally different technique in the field of computational chemistry. Electron interactions were implicitly included in the empirical atom-based potential functions and the system size to be investigated can be extended to ~106 atoms. The thermodynamic properties of model fluids are mainly determined by macroscopic quantities, like temperature, pressure, density. The quantum effects on thermodynamic properties like melting point, surface tension are not dominant. In this work, we mainly investigated the melting point, surface tension (liquid-vapor and liquid-solid) of model fluids including Lennard-Jones model, Stockmayer model and a couple of water models (TIP4P/Ew, TIP5P/Ew) by means of MD simulation. In addition, some new structures of water confined in carbon nanotube were discovered and transport behaviors of water and ions through nano-channels were also revealed.

A general framework for multi-compartmental analysis of drug chemotherapy dynamics in human immunodeficiency virus type-1 infected individuals

An optimal control strategy for the highly active antiretroviral therapy associated to the acquired immunodeficiency syndrome should be designed regarding a comprehensive analysis of the drug chemotherapy behavior in the host tissues, from major viral replication sites to viral sanctuary compartments. Such approach is critical in order to efficiently explore synergistic, competitive and prohibitive relationships among drugs and, hence, therapy costs and side-effect minimization. In this paper, a novel mathematical model for HIV-1 drug chemotherapy dynamics in distinct host anatomic compartments is proposed and theoretically evaluated on fifteen conventional anti-retroviral drugs. Rather than interdependence between drug type and its concentration profile in a host tissue, simulated results suggest that such profile is importantly correlated with the host tissue under consideration. Furthermore, the drug accumulative dynamics are drastically affected by low patient compliance with pharmacotherapy, even when a single dose lacks. (C) 2012 Elsevier Inc. All rights reserved.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

Computational and experimental characterization of a low-cost piezoelectric valveless diaphragm pump

Flow pumps act as important devices in areas such as Bioengineering, Medicine, and Pharmacy, among other areas of Engineering, mainly for delivering liquids or gases at small-scale and precision flow rate quantities. Principles for pumping fluids based on piezoelectric actuators have been widely studied, since they allow the construction of pump systems for displacement of small fluid volumes with low power consumption. This work studies valveless piezoelectric diaphragm pumps for flow generation, which uses a piezoelectric ceramic (PZT) as actuator to move a membrane (diaphragm) up and down as a piston. The direction of the flow is guaranteed by valveless configuration based on a nozzle-diffuser system that privileges the flow in just one pumping direction. Most research efforts on development of valveless flow pump deal either with computational simulations based on simplified models or with simplified physical approaches based on analytical models. The main objective of this work is the study of a methodology to develop a low-cost valveless piezoelectric diaphragm flow pump using computational simulations, parametric study, prototype manufacturing, and experimental characterization. The parametric study has shown that the eccentricity of PZT layer and metal layer plays a key role in the performance of the pump.

An in-depth analysis of the HIV-1/AIDS dynamics by comprehensive mathematical modeling

This work presents major results from a novel dynamic model intended to deterministically represent the complex relation between HIV-1 and the human immune system. The novel structure of the model extends previous work by representing different host anatomic compartments under a more in-depth cellular and molecular immunological phenomenology. Recently identified mechanisms related to HIV-1 infection as well as other well known relevant mechanisms typically ignored in mathematical models of HIV-1 pathogenesis and immunology, such as cell-cell transmission, are also addressed. (C) 2011 Elsevier Ltd. All rights reserved.

Molecular Dynamics Investigations of PRODAN in a DLPC Bilayer

Molecular dynamics computer simulations have been performed to identify preferred positions of the fluorescent probe PRODAN in a fully hydrated DLPC bilayer in the fluid phase. In addition to the intramolecular charge-transfer first vertical excited state, we considered different charge distributions for the electronic ground state of the PRODAN molecule by distinct atomic charge models corresponding to the probe molecule in vacuum as well as polarized in a weak and a strong dielectric solvent (cyclohexane and water). Independent on the charge distribution model of PRODAN, we observed a preferential orientation of this molecule in the bilayer with the dimethylamino group pointing toward the membrane's center and the carbonyl oxygen toward the membrane's interface. However, changing the charge distribution model of PRODAN, independent of its initial position in the equilibrated DLPC membrane, we observed different preferential positions. For the ground state representation without polarization and the in-cyclohexane polarization, the probe maintains its position close to the membrane's center. Considering the in-water polarization model, the probe approaches more of the polar headgroup region of the bilayer, with a strong structural correlation with the choline group, exposing its oxygen atom to water molecules. PRODAN's representation of the first vertical excited state with the in-water polarization also approaches the polar region of the membrane with the oxygen atom exposed to the bilayer's hydration shell. However, this model presents a stronger structural correlation with the phosphate groups than the ground state. Therefore, we conclude that the orientation of the PRODAN molecule inside the DLPC membrane is well-defined, but its position is very sensitive to the effect of the medium polarization included here by different models for the atomic charge distribution of the probe.

Exact dynamics of single-qubit-gate fidelities under the measurement-based quantum computation scheme

Measurement-based quantum computation is an efficient model to perform universal computation. Nevertheless, theoretical questions have been raised, mainly with respect to realistic noise conditions. In order to shed some light on this issue, we evaluate the exact dynamics of some single-qubit-gate fidelities using the measurement-based quantum computation scheme when the qubits which are used as a resource interact with a common dephasing environment. We report a necessary condition for the fidelity dynamics of a general pure N-qubit state, interacting with this type of error channel, to present an oscillatory behavior, and we show that for the initial canonical cluster state, the fidelity oscillates as a function of time. This state fidelity oscillatory behavior brings significant variations to the values of the computational results of a generic gate acting on that state depending on the instants we choose to apply our set of projective measurements. As we shall see, considering some specific gates that are frequently found in the literature, the fast application of the set of projective measurements does not necessarily imply high gate fidelity, and likewise the slow application thereof does not necessarily imply low gate fidelity. Our condition for the occurrence of the fidelity oscillatory behavior shows that the oscillation presented by the cluster state is due exclusively to its initial geometry. Other states that can be used as resources for measurement-based quantum computation can present the same initial geometrical condition. Therefore, it is very important for the present scheme to know when the fidelity of a particular resource state will oscillate in time and, if this is the case, what are the best times to perform the measurements.