Power Secant Method applied to natural frequency extraction of Timoshenko beam structures

This work deals with an improved plane frame formulation whose exact dynamic stiffness matrix (DSM) presents, uniquely, null determinant for the natural frequencies. In comparison with the classical DSM, the formulation herein presented has some major advantages: local mode shapes are preserved in the formulation so that, for any positive frequency, the DSM will never be ill-conditioned; in the absence of poles, it is possible to employ the secant method in order to have a more computationally efficient eigenvalue extraction procedure. Applying the procedure to the more general case of Timoshenko beams, we introduce a new technique, named ""power deflation"", that makes the secant method suitable for the transcendental nonlinear eigenvalue problems based on the improved DSM. In order to avoid overflow occurrences that can hinder the secant method iterations, limiting frequencies are formulated, with scaling also applied to the eigenvalue problem. Comparisons with results available in the literature demonstrate the strength of the proposed method. Computational efficiency is compared with solutions obtained both by FEM and by the Wittrick-Williams algorithm.

Using the ultrasound and instrumented indentation techniques to measure the elastic modulus of engineering materials

Currently, the acoustic and nanoindentation techniques are two of the most used techniques for material elastic modulus measurement. In this article fundamental principles and limitations of both techniques are shown and discussed. Last advances in nanoindentation technique are also reviewed. An experimental study in ceramic, metallic, composite and single crystals was also done. Results shown that ultrasonic technique is capable to provide results in agreement with those reported in literature. However, ultrasonic technique does not allow measuring the elastic modulus of some small samples and single crystals. On the other hand, the nanoindentation technique estimates the elastic modulus values in reasonable agreement with those measured by acoustic methods, particularly in amorphous materials, while in some policristaline materials some deviation from expected values was obtained.

The Effect of Spatial Scale on Predicting Time Series: A Study on Epidemiological System Identification

A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Border figure detection using a phase oscillator network with dynamical coupling

Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.

System Identification and Prediction of Dengue Fever Incidence in Rio de Janeiro

Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.

Direct Computation of Operational Matrices for Polynomial Bases

Several numerical methods for boundary value problems use integral and differential operational matrices, expressed in polynomial bases in a Hilbert space of functions. This work presents a sequence of matrix operations allowing a direct computation of operational matrices for polynomial bases, orthogonal or not, starting with any previously known reference matrix. Furthermore, it shows how to obtain the reference matrix for a chosen polynomial base. The results presented here can be applied not only for integration and differentiation, but also for any linear operation.

Rumor Propagation Model: An Equilibrium Study

Compartmental epidemiological models have been developed since the 1920s and successfully applied to study the propagation of infectious diseases. Besides, due to their structure, in the 1960s an interesting version of these models was developed to clarify some aspects of rumor propagation, considering that spreading an infectious disease or disseminating information is analogous phenomena. Here, in an analogy with the SIR (Susceptible-Infected-Removed) epidemiological model, the ISS (Ignorant-Spreader-Stifler) rumor spreading model is studied. By using concepts from the Dynamical Systems Theory, stability of equilibrium points is established, according to propagation parameters and initial conditions. Some numerical experiments are conducted in order to validate the model.

Fully Connected PLL Networks: How Filter Determines the Number of Nodes

Synchronization plays an important role in telecommunication systems, integrated circuits, and automation systems. Formerly, the masterslave synchronization strategy was used in the great majority of cases due to its reliability and simplicity. Recently, with the wireless networks development, and with the increase of the operation frequency of integrated circuits, the decentralized clock distribution strategies are gaining importance. Consequently, fully connected clock distribution systems with nodes composed of phase-locked loops (PLLs) appear as a convenient engineering solution. In this work, the stability of the synchronous state of these networks is studied in two relevant situations: when the node filters are first-order lag-lead low-pass or when the node filters are second-order low-pass. For first-order filters, the synchronous state of the network shows to be stable for any number of nodes. For second-order filter, there is a superior limit for the number of nodes, depending on the PLL parameters. Copyright (C) 2009 Atila Madureira Bueno et al.

Synchronization of Discrete-Time Chaotic Systems in Bandlimited Channels

Over the last couple of decades, many methods for synchronizing chaotic systems have been proposed with communications applications in view. Yet their performance has proved disappointing in face of the nonideal character of usual channels linking transmitter and receiver, that is, due to both noise and signal propagation distortion. Here we consider a discrete-time master-slave system that synchronizes despite channel bandwidth limitations and an allied communication system. Synchronization is achieved introducing a digital filter that limits the spectral content of the feedback loop responsible for producing the transmitted signal. Copyright (C) 2009 Marcio Eisencraft et al.

Beam-energy and system-size dependence of dynamical net charge fluctuations

We present measurements of net charge fluctuations in Au+Au collisions at s(NN)=19.6, 62.4, 130, and 200 GeV, Cu+Cu collisions at s(NN)=62.4 and 200 GeV, and p+p collisions at s=200 GeV using the dynamical net charge fluctuations measure nu(+-,dyn). We observe that the dynamical fluctuations are nonzero at all energies and exhibit a modest dependence on beam energy. A weak system size dependence is also observed. We examine the collision centrality dependence of the net charge fluctuations and find that dynamical net charge fluctuations violate 1/N(ch) scaling but display approximate 1/N(part) scaling. We also study the azimuthal and rapidity dependence of the net charge correlation strength and observe strong dependence on the azimuthal angular range and pseudorapidity widths integrated to measure the correlation.

Survival and Neuronal Differentiation of Mesenchymal Stem Cells Transplanted into the Rodent Brain Are Dependent upon Microenvironment

Introduction: The successful integration of stem cells in adult brain has become a central issue in modern neuroscience. In this study we sought to test the hypothesis that survival and neurodifferentiation of mesenchymal stem cells (MSCs) may be dependent upon microenvironmental conditions according to the site of implant in the brain. Methods: MSCs were isolated from adult rats and labeled with enhanced-green fluorescent protein (eGFP) lentivirus. A cell suspension was implanted stereotactically into the brain of 50 young rats, into one neurogenic area (hippocampus), and into another nonneurogenic area (striatum). Animals were sacrificed 6 or 12 weeks after surgery, and brains were stained for mature neuronal markers. Cells coexpressing NeuN (neuronal specific nuclear protein) and GFP (green fluorescent protein) were counted stereologically at both targets. Results: The isolated cell population was able to generate neurons positive for microtubule-associated protein 2 (MAP2), neuronal-specific nuclear protein (NeuN), and neurofilament 200 (NF200) in vitro. Electrophysiology confirmed expression of voltage-gated ionic channels. Once implanted into the hippocampus, cells survived for up to 12 weeks, migrated away from the graft, and gave rise to mature neurons able to synthesize neurotransmitters. By contrast, massive cell degeneration was seen in the striatum, with no significant migration. Induction of neuronal differentiation with increased cyclic adenosine monophosphate in the culture medium before implantation favored differentiation in vivo. Conclusions: Our data demonstrated that survival and differentiation of MSCs is strongly dependent upon a permissive microenvironment. Identification of the pro-neurogenic factors present in the hippocampus could subsequently allow for the integration of stem cells into nonpermissive areas of the central nervous system.

Adipose Tissue-Derived Stem Cells from Humans and Mice Differ in Proliferative Capacity and Genome Stability in Long-Term Cultures

Adipose tissue-derived stem cells (ASCs) are among the more attractive adult stem cell options for potential therapeutic applications. Here, we studied and compared the basic biological characteristics of ASCs isolated from humans (hASCs) and mice (mASCs) and maintained in identical culture conditions, which must be examined prior to considering further potential clinical applications. hASCs and mASCs were compared for immunophenotype, differentiation potential, cell growth characteristics, senescence, nuclear morphology, and DNA content. Although both strains of ASCs displayed a similar immunophenotype, the percentage of CD73(+) cells was markedly lower and CD31(+) was higher in mASC than in hASC cultures. The mean population doubling time was 98.08 +/- 6.15 h for hASCs and 52.58 +/- 3.74 h for mASCs. The frequency of nuclear aberrations was noticeably lower in hASCs than in mASCs regardless of the passage number. Moreover, as the cells went through several in vitro passages, mASCs showed changes in DNA content and cell cycle kinetics (frequency of hypodiploid, G0/G1, G2/M, and hyperdiploid cells), whereas all of these parameters remained constant in hASCs. Collectively, these results suggest that mASCs display higher proliferative capacity and are more unstable than hASCs in long-term cultures. These results underscore the need to consider specificities among model systems that may influence outcomes when designing potential human applications.

FBXO25-associated nuclear domains: A novel subnuclear structure

Skp1, Cul1, Rbx1, and the FBXO25 protein form a functional ubiquitin ligase complex. Here, we investigate the cellular distribution of FBXO25 and its colocalization with some nuclear proteins by using immunochemical and biochemical approaches. FBXO25 was monitored with affinity-purified antibodies raised against the recombinant fragment spanning residues 2-62 of the FBXO25 sequence. FBXO25 protein was expressed in all mouse tissues tested except striated muscle, as indicated by immunoblot analysis. Confocal analysis revealed that the endogenous FBXO25 was partially concentrated in a novel dot-like nuclear domain that is distinct from clastosomes and other well-characterized structures. These nuclear compartments contain a high concentration of ubiquitin conjugates and at least two other components of the ubiquitin-proteasome system: 20S proteasome and Skp1. We propose to name these compartments FBXO25-associated nuclear domains. Interestingly, inhibition of transcription by actinomycin D or heat-shock treatment drastically affected the nuclear organization of FBXO25-containing structures, indicating that they are dynamic compartments influenced by the transcriptional activity of the cell. Also, we present evidences that an FBXO25-dependent ubiquitin ligase activity prevents aggregation of recombinant polyglutamine-containing huntingtin protein in the nucleus of human embryonic kidney 293 cells, suggesting that this protein can be a target for the nuclear FBXO25 mediated ubiquitination.

Expression of eight genes of nuclear factor-kappa B pathway in multiple myeloma using bone marrow aspirates obtained at diagnosis

Purpose: To evaluate the expression of NF-kappa B pathway genes in total bone marrow samples obtained from MM at diagnosis using real-time quantitative PCR and to evaluate its possible correlation with disease clinical features and survival. Material and methods: Expression of eight genes related to NF-kappa B pathway (NFKB1, IKB, RANK, RANKL, OPG, IL6, VCAM1 and ICAM1) were studied in 53 bone marrow samples from newly diagnosed MM patients and in seven normal controls, using the Taqman system. Genes were considered overexpressed when tumor expression level was at least four times higher than that observed in normal samples. Results: The percentages of overexpression of the eight genes were: NFKB1 0%, IKB 22.6%, RANK 15.1%, RANKL 31.3%, OPG 7.5%, IL6 39.6%, VCAM1 10% and ICAM1 26%. We found association between IL6 expression level and International Staging System (ISS) (p = 0.01), meaning that MM patients with high ISS scores have more chance of overexpression of IL6. The mean value of ICAM1 relative expression was also associated with the ISS score (p = 0.02). Regarding OS, cases with IL6 overexpression present worse evolution than cases with IL6 normal expression (p = 0.04). Conclusion: We demonstrated that total bone marrow aspirates can be used as a source of material for gene expression studies in MM. In this context, we confirmed that IL6 overexpression was significantly associated with worse survival and we described that it is associated with high ISS scores. Also, ICAM1 was overexpressed in 26% of cases and its level was associated with ISS scores.