Swarms of computational resources and swarms of tasks for building reliable systems

Space applications demand the need for building reliable systems. Autonomic computing defines such reliable systems as self-managing systems. The work reported in this paper combines agent based and swarm robotic approaches leading to swarm-array computing, a novel technique to achieve autonomy for distributed parallel computing systems. Two swarm-array computing approaches based on swarms of computational resources and swarms of tasks are explored. FPGA is considered as the computing system. The feasibility of the two proposed approaches that binds the computing system and the task together is simulated on the SeSAm multi-agent simulator.

Computational complexity of weighted splitting schemes on parallel computers

In models of complicated physical-chemical processes operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The recently rediscovered weighted splitting schemes have the great advantage of being parallelizable on operator level, which allows us to reduce the computational time if parallel computers are used. In this paper, the computational times needed for the weighted splitting methods are studied in comparison with the sequential (S) splitting and the Marchuk-Strang (MSt) splitting and are illustrated by numerical experiments performed by use of simplified versions of the Danish Eulerian model (DEM).

Comparison of the computational cost of a Monte Carlo and deterministic algorithm for computing bilinear forms of matrix powers

In this paper we consider bilinear forms of matrix polynomials and show that these polynomials can be used to construct solutions for the problems of solving systems of linear algebraic equations, matrix inversion and finding extremal eigenvalues. An almost Optimal Monte Carlo (MAO) algorithm for computing bilinear forms of matrix polynomials is presented. Results for the computational costs of a balanced algorithm for computing the bilinear form of a matrix power is presented, i.e., an algorithm for which probability and systematic errors are of the same order, and this is compared with the computational cost for a corresponding deterministic method.

Computational chemistry for elucidating protein function: energetics and dynamics of myoglobin-ligand systems

State-of-the-art computational methodologies are used to investigate the energetics and dynamics of photodissociated CO and NO in myoglobin (Mb···CO and Mb···NO). This includes the combination of molecular dynamics, ab initio MD, free energy sampling, and effective dynamics methods to compare the results with studies using X-ray crystallography and ultrafast spectroscopy metho ds. It is shown that modern simulation techniques along with careful description of the intermolecular interactions can give quantitative agreement with experiments on complex molecular systems. Based on this agreement predictions for as yet uncharacterized species can be made.

Coming of age: a review of embodiment and the neuroscience of semantics

Over the last decade, there has been an increasing body of work that explores whether sensory and motor information is a necessary part of semantic representation and processing. This is the embodiment hypothesis. This paper presents a theoretical review of this work that is intended to be useful for researchers in the neurosciences and neuropsychology. Beginning with a historical perspective, relevant theories are placed on a continuum from strongly embodied to completely unembodied representations. Predictions are derived and neuroscientific and neuropsychological evidence that could support different theories is reviewed; finally, criticisms of embodiment are discussed. We conclude that strongly embodied and completely disembodied theories are not supported, and that the remaining theories agree that semantic representation involves some form of Convergence Zones (Damasio, 1989) and the activation of modal content. For the future, research must carefully define the boundaries of semantic processing and tackle the representation of abstract entities.

Electronic properties of 4,4 ',5,5 '-tetramethyl-2,2 '-biphosphinine (tmbp) in the redox series fac-[Mn(Br)(CO)(3)(tmbp)], [Mn(CO)(3)(tmbp)](2), and [Mn(CO)(3)(tmbp)](-): crystallographic, spectroelectrochemical, and DFT computational study

Stepwise electrochemical reduction of the complex fac-[Mn(Br)(CO)(3)(tmbp)] (tmbp = 4,4',5,5'-tetramethyl-2,2'-biphosphinine) produces the dimer [Mn(CO)(3)(tmbp)](2) and the five-coordinate anion [Mn(CO)(3)(tmbp)](-). All three members of the redox series have been characterized by single-crystal X-ray diffraction. The crystallographic data provide valuable insight into the localization of the added electrons on the (carbonyl)manganese and tmbp centers. In particular, the formulation of the two-electron-reduced anion as [Mn-0(CO)(3)(tmbp(-))](-) also agrees with the analysis of its IR nu(CO) wavenumbers and with the results of density functional theoretical (DFT) MO calculations on this compound. The strongly delocalized pi-bonding in the anion stabilizes its five-coordinate geometry and results in the appearance of several mixed Mn-to-tmbp charge-transfer/IL(tmbp) transitions in the near-UV-vis spectral region. A thorough voltammetric and UV-vis/IR spectroelectrochemical study of the reduction path provided evidence for a direct formation of [Mn(CO)(3)(tmbp)](-) via a two-electron ECE mechanism involving the [Mn(CO)(3)(tmbp)](.) radical transient. At ambient temperature [Mn(CO)(3)(tmbp)](-) reacts rapidly with nonreduced fac-[Mn(Br)(CO)(3)(tmbp)] to produce [Mn(CO)(3)(tmbp)](2). Comparison with the analogous 2,2'-bipyridine complexes has revealed striking similarity in the bonding properties and reactivity, despite the stronger pi-acceptor character of the tmbp ligand.

Titanocene anticancer complexes and their binding mode of action to human serum albumin: a computational study

Due to the pivotal role played by human serum albumin (HSA) in the transport and cytotoxicity of titanocene complexes, a docking study has been performed on a selected set of titanocene complexes to aid in the current understanding of the potential mode of action of these titanocenes upon binding HSA. Analysis of the docking results has revealed potential binding at the known drug binding sites in HSA and has provided some explanation for the specificity and subsequent cytotoxicity of these titanocenes. Additionally, a new alternative binding site for these titanocenes has been postulated.

Generation, description and storage of dendritic morphology data

It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.