Structure adaptation of linear MMSE adaptive filters

The tap-length, or the number of the taps, is an important structural parameter of the linear MMSE adaptive filter. Although the optimum tap-length that balances performance and complexity varies with scenarios, most current adaptive filters fix the tap-length at some compromise value, making them inefficient to implement especially in time-varying scenarios. A novel gradient search based variable tap-length algorithm is proposed, using the concept of the pseudo-fractional tap-length, and it is shown that the new algorithm can converge to the optimum tap-length in the mean. Results of computer simulations are also provided to verify the analysis.

Self-assembly of Fmoc-tetrapeptides based on the RGDS cell adhesion motif

Self-assembly in aqueous solution has been investigated for two Fmoc [Fmoc ¼ N-(fluorenyl)-9-methoxycarbonyl] tetrapeptides comprising the RGDS cell adhesion motif from fibronectin or the scrambled sequence GRDS. The hydrophobic Fmoc unit confers amphiphilicity on the molecules, and introduces aromatic stacking interactions. Circular dichroism and FTIR spectroscopy show that the self-assembly of both peptides at low concentration is dominated by interactions among Fmoc units, although Fmoc-GRDS shows b-sheet features, at lower concentration than Fmoc-RGDS. Fibre X-ray diffraction indicates b-sheet formation by both peptides at sufficiently high concentration. Strong alignment effects are revealed by linear dichroism experiments for Fmoc-GRDS. Cryo-TEM and smallangle X-ray scattering (SAXS) reveal that both samples form fibrils with a diameter of approximately 10 nm. Both Fmoc-tetrapeptides form self-supporting hydrogels at sufficiently high concentration. Dynamic shear rheometry enabled measurements of the moduli for the Fmoc-GRDS hydrogel, however syneresis was observed for the Fmoc-RGDS hydrogel which was significantly less stable to shear. Molecular dynamics computer simulations were carried out considering parallel and antiparallel b-sheet configurations of systems containing 7 and 21 molecules of Fmoc-RGDS or Fmoc-GRDS, the results being analyzed in terms of both intermolecular structural parameters and energy contributions.

Three dimensional picture of the local structure of 1,4-Polybutadiene from a complete atomistic model and neutron scattering data

An efficient method of combining neutron diffraction data over an extended Q range with detailed atomistic models is presented. A quantitative and qualitative mapping of the organization of the chain conformation in both glass and liquid phase has been performed. The proposed structural refinement method is based on the exploitation of the intrachain features of the diffraction pattern by the use of internal coordinates for bond lengths, valence angles and torsion rotations. Models are built stochastically by assignment of these internal coordinates from probability distributions with limited variable parameters. Variation of these parameters is used in the construction of models that minimize the differences between the observed and calculated structure factors. A series of neutron scattering data of 1,4-polybutadiene at the region 20320 K is presented. Analysis of the experimental data yield bond lengths for C-C and C=C of 1.54 and 1.35 Å respectively. Valence angles of the backbone were found to be at 112 and 122.8 for the CCC and CC=C respectively. Three torsion angles corresponding to the double bond and the adjacent R and β bonds were found to occupy cis and trans, s(, trans and g( and trans states, respectively. We compare our results with theoretical predictions, computer simulations, RIS models, and previously reported experimental results.

Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Grid warehousing of molecular dynamics protein unfolding data

With the increasing awareness of protein folding disorders, the explosion of genomic information, and the need for efficient ways to predict protein structure, protein folding and unfolding has become a central issue in molecular sciences research. Molecular dynamics computer simulations are increasingly employed to understand the folding and unfolding of proteins. Running protein unfolding simulations is computationally expensive and finding ways to enhance performance is a grid issue on its own. However, more and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. This paper describes efforts to provide a grid-enabled data warehouse for protein unfolding data. We outline the challenge and present first results in the design and implementation of the data warehouse.

Terahertz pulse imaging of stratified architectural materials for cultural heritage studies

Terahertz pulse imaging (TPI) is a novel noncontact, nondestructive technique for the examination of cultural heritage artifacts. It has the advantage of broadband spectral range, time-of-flight depth resolution, and penetration through optically opaque materials. Fiber-coupled, portable, time-domain terahertz systems have enabled this technique to move out of the laboratory and into the field. Much like the rings of a tree, stratified architectural materials give the chronology of their environmental and aesthetic history. This work concentrates on laboratory models of stratified mosaics and fresco paintings, specimens extracted from a neolithic excavation site in Catalhoyuk, Turkey, and specimens measured at the medieval Eglise de Saint Jean-Baptiste in Vif, France. Preparatory spectroscopic studies of various composite materials, including lime, gypsum and clay plasters are presented to enhance the interpretation of results and with the intent to aid future computer simulations of the TPI of stratified architectural material. The breadth of the sample range is a demonstration of the cultural demand and public interest in the life history of buildings. The results are an illustration of the potential role of TPI in providing both a chronological history of buildings and in the visualization of obscured wall paintings and mosaics.

When long-range zero-lag synchronization is feasible in cortical networks

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP.

Educational simulation in construction: the virtual construction simulator

Students in the architecture, engineering, and construction disciplines are often challenged with visualizing and understanding the complex spatial and temporal relationships involved in designing and constructing three-dimensional (3D) structures. An evolving body of research traces the use of educational computer simulations to enhance student learning experiences through testing real-world scenarios and the development of student decision-making skills. Ongoing research at Pennsylvania State University aims to improve engineering education in construction through interactive construction project learning applications in an immersive virtual reality environment. This paper describes the first- and second-generation development of the Virtual Construction Simulator (VCS), a tool that enables students to simultaneously create and review construction schedules through 3D model interaction. The educational value and utility of VCS was assessed through surveys, focus group interviews, and a student exercise conducted in a construction management class. Results revealed VCS is a valuable and effective four-dimensional (4D) model creation and schedule review application that fosters collaborative work and greater student task focus. This paper concludes with a discussion of the findings and the future development steps of the VCS educational simulation

Experimentally driven atomistic model of 1,2 Polybutadiene

We present an efficient method of combining wide angle neutron scattering data with detailed atomistic models, allowing us to perform a quantitative and qualitative mapping of the organisation of the chain conformation in both glass and liquid phases. The structural refinement method presented in this work is based on the exploitation of the intrachain features of the diffraction pattern and its intimate linkage with atomistic models by the use of internal coordinates for bond lengths, valence angles and torsion rotations. Atomic connectivity is defined through these coordinates that are in turn assigned by pre-defined probability distributions, thus allowing for the models in question to be built stochastically. Incremental variation of these coordinates allows for the construction of models that minimise the differences between the observed and calculated structure factors. We present a series of neutron scattering data of 1,2 polybutadiene at the region 120-400K. Analysis of the experimental data yield bond lengths for C-C and C=C of 1.54Å and 1.35Å respectively. Valence angles of the backbone were found to be at 112° and the torsion distributions are characterised by five rotational states, a three-fold trans-skew± for the backbone and gauche± for the vinyl group. Rotational states of the vinyl group were found to be equally populated, indicating a largely atactic chan. The two backbone torsion angles exhibit different behaviour with respect to temperature of their trans population, with one of them adopting an almost all trans sequence. Consequently the resulting configuration leads to a rather persistent chain, something indicated by the value of the characteristic ratio extrapolated from the model. We compare our results with theoretical predictions, computer simulations, RIS models and previously reported experimental results.

Self-consistent wave-particle interactions in dispersive scale long-period field-line-resonances

Using 1D Vlasov drift-kinetic computer simulations, it is shown that electron trapping in long period standing shear Alfven waves (SAWs) provides an efficient energy sink for wave energy that is much more effective than Landau damping. It is also suggested that the plasma environment of low altitude auroral-zone geomagnetic field lines is more suited to electron acceleration by inertial or kinetic scale Alfven waves. This is due to the self-consistent response of the electron distribution function to SAWs, which must accommodate the low altitude large-scale current system in standing waves. We characterize these effects in terms of the relative magnitude of the wave phase and electron thermal velocities. While particle trapping is shown to be significant across a wide range of plasma temperatures and wave frequencies, we find that electron beam formation in long period waves is more effective in relatively cold plasma.

Boundary condition effects in the simulation study of equilibrium properties of magnetic dipolar fluids

In this paper we investigate the equilibrium properties of magnetic dipolar (ferro-) fluids and discuss finite-size effects originating from the use of different boundary conditions in computer simulations. Both periodic boundary conditions and a finite spherical box are studied. We demonstrate that periodic boundary conditions and subsequent use of Ewald sum to account for the long-range dipolar interactions lead to a much faster convergence (in terms of the number of investigated dipolar particles) of the magnetization curve and the initial susceptibility to their thermodynamic limits. Another unwanted effect of the simulations in a finite spherical box geometry is a considerable sensitivity to the container size. We further investigate the influence of the surface term in the Ewald sum-that is, due to the surrounding continuum with magnetic permeability mu(BC)-on the convergence properties of our observables and on the final results. The two different ways of evaluating the initial susceptibility, i.e., (1) by the magnetization response of the system to an applied field and (2) by the zero-field fluctuation of the mean-square dipole moment of the system, are compared in terms of speed and accuracy.

Mathematical model for NF-kappaB-driven proliferation of adult neural stem cells

Neural stem cells (NSCs) are early precursors of neuronal and glial cells. NSCs are capable of generating identical progeny through virtually unlimited numbers of cell divisions (cell proliferation), producing daughter cells committed to differentiation. Nuclear factor kappa B (NF-kappaB) is an inducible, ubiquitous transcription factor also expressed in neurones, glia and neural stem cells. Recently, several pieces of evidence have been provided for a central role of NF-kappaB in NSC proliferation control. Here, we propose a novel mathematical model for NF-kappaB-driven proliferation of NSCs. We have been able to reconstruct the molecular pathway of activation and inactivation of NF-kappaB and its influence on cell proliferation by a system of nonlinear ordinary differential equations. Then we use a combination of analytical and numerical techniques to study the model dynamics. The results obtained are illustrated by computer simulations and are, in general, in accordance with biological findings reported by several independent laboratories. The model is able to both explain and predict experimental data. Understanding of proliferation mechanisms in NSCs may provide a novel outlook in both potential use in therapeutic approaches, and basic research as well.

DIFFUSION OF MAGNETIC FIELD AND REMOVAL OF MAGNETIC FLUX FROM CLOUDS VIA TURBULENT RECONNECTION

The diffusion of astrophysical magnetic fields in conducting fluids in the presence of turbulence depends on whether magnetic fields can change their topology via reconnection in highly conducting media. Recent progress in understanding fast magnetic reconnection in the presence of turbulence reassures that the magnetic field behavior in computer simulations and turbulent astrophysical environments is similar, as far as magnetic reconnection is concerned. This makes it meaningful to perform MHD simulations of turbulent flows in order to understand the diffusion of magnetic field in astrophysical environments. Our studies of magnetic field diffusion in turbulent medium reveal interesting new phenomena. First of all, our three-dimensional MHD simulations initiated with anti-correlating magnetic field and gaseous density exhibit at later times a de-correlation of the magnetic field and density, which corresponds well to the observations of the interstellar media. While earlier studies stressed the role of either ambipolar diffusion or time-dependent turbulent fluctuations for de-correlating magnetic field and density, we get the effect of permanent de-correlation with one fluid code, i.e., without invoking ambipolar diffusion. In addition, in the presence of gravity and turbulence, our three-dimensional simulations show the decrease of the magnetic flux-to-mass ratio as the gaseous density at the center of the gravitational potential increases. We observe this effect both in the situations when we start with equilibrium distributions of gas and magnetic field and when we follow the evolution of collapsing dynamically unstable configurations. Thus, the process of turbulent magnetic field removal should be applicable both to quasi-static subcritical molecular clouds and cores and violently collapsing supercritical entities. The increase of the gravitational potential as well as the magnetization of the gas increases the segregation of the mass and magnetic flux in the saturated final state of the simulations, supporting the notion that the reconnection-enabled diffusivity relaxes the magnetic field + gas system in the gravitational field to its minimal energy state. This effect is expected to play an important role in star formation, from its initial stages of concentrating interstellar gas to the final stages of the accretion to the forming protostar. In addition, we benchmark our codes by studying the heat transfer in magnetized compressible fluids and confirm the high rates of turbulent advection of heat obtained in an earlier study.

Reduced gradient method combined with augmented Lagrangian and barrier for the optimal power flow problem

A new approach for solving the optimal power flow (OPF) problem is established by combining the reduced gradient method and the augmented Lagrangian method with barriers and exploring specific characteristics of the relations between the variables of the OPF problem. Computer simulations on IEEE 14-bus and IEEE 30-bus test systems illustrate the method. (c) 2007 Elsevier Inc. All rights reserved.

Chaotic phase synchronization and desynchronization in an oscillator network for object selection

Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial Visual systems. Chaotic phase synchronization takes place in cases involving almost identical dynamical systems and it means that the phase difference between the systems is kept bounded over the time, while their amplitudes remain chaotic and may be uncorrelated. Instead of complete synchronization, phase synchronization is believed to be a mechanism for neural integration in brain. In this paper, an object selection model is proposed. Oscillators in the network representing the salient object in a given scene are phase synchronized, while no phase synchronization occurs for background objects. In this way, the salient object can be extracted. In this model, a shift mechanism is also introduced to change attention from one object to another. Computer simulations show that the model produces some results similar to those observed in natural vision systems.