Numerous genome projects have produced a large and ever increasing amount of genomic sequence data. However, the biological functions of many proteins encoded by the sequences remain unknown. Protein function annotati...
详细信息
Lattice Boltzmann algorihms are a mesoscopic representation of nonlinear continuum physics (like Navier-Stokes, magnetohydro dynamics (MHD), Gross- Pitaevskii equations) which are ideal for parallel supercomputers bec...
详细信息
Lattice Boltzmann algorihms are a mesoscopic representation of nonlinear continuum physics (like Navier-Stokes, magnetohydro dynamics (MHD), Gross- Pitaevskii equations) which are ideal for parallel supercomputers because they transform the difficult nonlinear convective macroscopic derivatives into purely local moments of distribution functions. The macroscopic nonlinearities are recovered by relaxation distribution functions in the collision operator whose dependence on the macroscopic velocity is algebraically nonlinear and thus purely local. Unlike standard computational fluid dynamics codes, there is no loss in parallelization in handling arbitrary geometric boundaries, e.g., using bounce-back rules from kinetic theory. By encoding detailed balance into the collision operator through the introduction of discrete H-function, the lattice Boltzmann algorithm can be made unconditionally stable for arbitrary high Reynolds numbers. It is shown that this approach is a special case of a quantum lattice Boltzmann algorithm that entangles local qubits through unitary collision operators and which is ideally parallelized on quantum computer architectures. Here we consider turbulence simulations using 2,048 PEs on a 1,6003-spatial grid. A connection is found between the rate of change of enstrophy and the onset of laminar-to- turbulent flows.
A description of the so called "particles with coupled oscillator dynamics" (PCOD) is presented which is used to model, analyze and synthesize collective motion. An oscillator model with spatial dynamics is ...
详细信息
A description of the so called "particles with coupled oscillator dynamics" (PCOD) is presented which is used to model, analyze and synthesize collective motion. An oscillator model with spatial dynamics is presented to help describe how to design steering control laws while it is being used to study biological collectives. Lastly, both engineering and biological analysis were described.
Motivated by the desire to estimate the number of order-preserving self-maps of an ordered set, we compare three algorithms (Simple Sampling [4], Partial Backtracking [10] and Heuristic Sampling [1]) which predict how...
详细信息
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto-value functions, in which the underly...
详细信息
Fully Polarimetric radar systems are capable of simultaneously transmitting and receiving in two orthogonal polarizations. Instantaneous radar polarimetry exploits both polarization modes of a dually-polarized radar t...
详细信息
ISBN:
(纸本)1424407850
Fully Polarimetric radar systems are capable of simultaneously transmitting and receiving in two orthogonal polarizations. Instantaneous radar polarimetry exploits both polarization modes of a dually-polarized radar transmitter and receiver on a pulse by pulse basis, and can improve the radar detection performance and suppress range sidelobes. In this paper, we extend the use of instantaneous radar polarimetry for radar systems with multiple dually-polarized transmit and receive antennas. Alamouti signal processing is used to coordinate transmission of Golay pairs of phase codes waveforms across polarizations and multiple antennas. The integration of multi-antenna signal processing with instantaneous radar polarimetry can further improve the detection performance, at a computational cost comparable to single channel matched filtering.
With support from HBCU-UP (Historically Black College and University - Undergraduate program) at National science Foundation (NSF), the ACTION (Advanced Curriculum and Technology-Based Instructional Opportunities Netw...
详细信息
Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, the...
Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, there have been few attempts to analyze chemical signaling systems with the quantitative tools of information theory. Gradient sensing in the social amoeba Dictyostelium discoideum is a well characterized signal transduction system in which a cell estimates the direction of a source of diffusing chemoattractant molecules based on the spatiotemporal sequence of ligand-receptor binding events at the cell membrane. Using Monte Carlo techniques (MCell) we construct a simulation in which a collection of individual ligand particles undergoing Brownian diffusion in a three-dimensional volume interact with receptors on the surface of a static amoeboid cell. Adapting a method for estimation of spike train entropies described by Victor (originally due to Kozachenko and Leonenko), we estimate lower bounds on the mutual information between the transmitted signal (direction of ligand source) and the received signal (spatiotemporal pattern of receptor binding/unbinding events). Hence we provide a quantitative framework for addressing the question: how much could the cell know, and when could it know it? We show that the time course of the mutual information between the cell's surface receptors and the (unknown) gradient direction is consistent with experimentally measured cellular response times. We find that the acquisition of directional information depends strongly on the time constant at which the intracellular response is filtered.
暂无评论