Stepwise dissection and visualization of the catalytic mechanism of haloalkane dehalogenase LinB using molecular dynamics simulations and computer graphics

The different steps of the dehalogenation reaction carried out by LinB on three different substrates have been characterized using a combination of quantum mechanical calculations and molecular dynamics simulations. This has allowed us to obtain information in atomic detail about each step of the reaction mechanism, that is, substrate entrance and achievement of the near-attack conformation, transition state stabilization within the active site, halide stabilization, water molecule activation and subsequent hydrolytic attack on the ester intermediate with formation of alcohol, and finally product release. Importantly, no bias or external forces were applied during the whole procedure so that both intermediates and products were completely free to sample configuration space in order to adapt to the plasticity of the active site and/or search for an exit. Differences in substrate reactivity were found to be correlated with the ease of adopting the near-attack conformation and two different exit pathways were found for product release that do not interfere with substrate entrance. Additional support for the different entry and exit pathways was independently obtained from an examination of the enzyme's normal modes.     

Subacute proteome changes following traumatic injury of the developing brain: Implications for a dysregulation of neuronal migration and neurite arborization

Traumatic brain injury (TBI) is a major cause of morbidity and mortality among children and adolescents. To gain insight into developmental events influenced by TBI, we analyzed subacute mouse brain proteome changes in a percussion head trauma model at P7 ipsi- and contralateral to the site of injury. The comparison of brain proteomes of trauma mice and controls revealed reproducible changes in the intensity of 28 proteins (30 protein spots) in response to trauma. The changes detected suggest that TBI leads to apoptosis, inflammation, and oxidative stress. These changes were consistent with our results of histological and biochemical evaluation of the brains which revealed widespread apoptotic neurodegeneration, microglia activation, and increased levels of protein carbonyls. Furthermore, we detected changes in proteins involved in neuronal migration as well as axonal and dendritic growth and guidance, suggesting interference of trauma with these developmental events.     

A web-based e-learning system for increasing study efficiency by stimulating learner’s motivation

Due to the opportunities provided by the Internet, more and more people are taking advantage of distance learning courses and during the last few years enormous research efforts have been dedicated to the development of distance learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is about 30%. One of the reasons is the low study desire when the learner studies the learning materials. In this research, we propose an interactive Web-based e-learning system. The purpose of our system is to increase the e-learning completion rate by stimulating learner’s motivation. The proposed system has three subsystems: the learning subsystem, learner support subsystem, and teacher support subsystem. The learning subsystem improves the learner’s study desire. The learner support subsystem supports the learner during the study, and the teacher support subsystem supports the teacher to get the learner’s study state. To evaluate the proposed system, we developed several experiments and surveys. By using new features such as: display of learner’s study history, change of interface color, encourage function, ranking function, self-determination of the study materials, and grouping of learners, the proposed system can increase the learning efficiency.

Ambient occlusion and edge cueing to enhance real time molecular visualization

The paper presents a set of combined techniques to enhance the real-time visualization of simple or complex molecules (up to order of 106 atoms) space fill mode. The proposed approach includes an innovative technique for efficient computation and storage of ambient occlusion terms, a small set of GPU accelerated procedural impostors for space-fill and ball-and-stick rendering, and novel edge-cueing techniques. As a result, the user's understanding of the three-dimensional structure under inspection is strongly increased (even for still images), while the rendering still occurs in real time.     

‘Closed Interval Process Algebra’ versus ‘Interval Process Algebra’

Summary. In this paper we extend the theory of processes with durational actions that has been proposed in [1,2] to describe and reason about the performance of systems. We associate basic actions with lower and upper time bounds, that specify their possible different durations. Depending on how the lower and upper time bounds are fixed, eager actions (those which happen as soon as they can), lazy actions (those which can wait arbitrarily long before firing) as well as patient actions (those which can be delayed for a while) can be modelled. Processes are equipped with a (soft) operational semantics which is consistent with the original one and is well-timed (observation traces are ordered with respect to time). The bisimulation-based equivalence defined on top of the new operational semantics, timed equivalence, turns out to be a congruence and, within the lazy fragment of the algebra, refines untimed equivalences. Decidability and automatic checking of timed equivalence are also stated by resorting to a finite alternative characterization which is amenable to an automatic treatment by using standard algorithms. The relationships with other timed calculi and equivalences proposed in the literature are also established. Received: 22 May 1998 / 8 November 2000     

Reasoning about reasoning in a meta-level architecture

In this paper we discuss reasoning about reasoning in a multiple agent scenario. We consider agents that are perfect reasoners, loyal, and that can take advantage of both the knowledge and ignorance of other agents. The knowledge representation formalism we use is (full) first order predicate calculus, where different agents are represented by different theories, and reasoning about reasoning is realized via a meta-level representation of knowledge and reasoning. The framework we provide is pretty general: we illustrate it by showing a machine checked solution to the three wisemen puzzle. The agents' knowledge is organized into units: the agent's own knowledge about the world and its knowledge about other agents are units containing object-level knowledge; a unit containing meta-level knowledge embodies the reasoning about reasoning and realizes the link among units. In the paper we illustrate the meta-level architecture we propose for problem solving in a multi-agent scenario; we discuss our approach in relation to the modal one and we compare it with other meta-level architectures based on logic. Finally, we look at a class of applications that can be effectively modeled by exploiting the meta-level approach to reasoning about knowledge and reasoning.     

Bridging logic and kernel machines

We propose a general framework to incorporate first-order logic (FOL) clauses, that are thought of as an abstract and partial representation of the environment, into kernel machines that learn within a semi-supervised scheme. We rely on a multi-task learning scheme where each task is associated with a unary predicate defined on the feature space, while higher level abstract representations consist of FOL clauses made of those predicates. We re-use the kernel machine mathematical apparatus to solve the problem as primal optimization of a function composed of the loss on the supervised examples, the regularization term, and a penalty term deriving from forcing real-valued constraints deriving from the predicates. Unlike for classic kernel machines, however, depending on the logic clauses, the overall function to be optimized is not convex anymore. An important contribution is to show that while tackling the optimization by classic numerical schemes is likely to be hopeless, a stage-based learning scheme, in which we start learning the supervised examples until convergence is reached, and then continue by forcing the logic clauses is a viable direction to attack the problem. Some promising experimental results are given on artificial learning tasks and on the automatic tagging of bibtex entries to emphasize the comparison with plain kernel machines.     

Parallel option pricing on GPU: barrier options and realized variance options

This paper shows two examples of how the analysis of option pricing problems can lead to computational methods efficiently implemented in parallel. These computational methods outperform ??general purpose?? methods (i.e., for example, Monte Carlo, finite differences methods). The GPU implementation of two numerical algorithms to price two specific derivatives (continuous barrier options and realized variance options) is presented. These algorithms are implemented in CUDA subroutines ready to run on Graphics Processing Units (GPUs) and their performance is studied. The realization of these subroutines is motivated by the extensive use of the derivatives considered in the financial markets to hedge or to take risk and by the interest of financial institutions in the use of state of the art hardware and software to speed up the decision process. The performance of these algorithms is measured using the (CPU/GPU) speed up factor, that is using the ratio between the (wall clock) times required to execute the code on a CPU and on a GPU. The choice of the reference CPU and GPU used to evaluate the speed up factors presented is stated. The outstanding performance of the algorithms developed is due to the mathematical properties of the pricing formulae used and to the ad hoc software implementation. In the case of realized variance options when the computation is done in single precision the comparisons between CPU and GPU execution times gives speed up factors of the order of a few hundreds. For barrier options, the corresponding speed up factors are of about fifteen, twenty. The CUDA subroutines to price barrier options and realized variance options can be downloaded from the website http://www.econ.univpm.it/recchioni/finance/w13. A?more general reference to the work in mathematical finance of some of the authors and of their coauthors is the website http://www.econ.univpm.it/recchioni/finance/.     

Integration of virtual and real environments for engineering service-oriented manufacturing systems

Engineering frameworks are currently required to support the easy, low-cost, modular and integrated development of manufacturing systems addressing the emergent requirements of re-configurability, responsiveness and robustness. This paper discusses the integration of 2D/3D digital software tools with Petri net based service-oriented frameworks to allow the design, configuration, analysis, validation, simulation, monitoring and control of manufacturing systems in a virtual environment and its posterior smooth migration into the real ??physical?? environment. An experimental case study was implemented to validate the proposed concepts, using the Continuum platform to design, compose, analyze, validate and simulate the Petri nets based service-oriented manufacturing control system, and the Delmia Automation^TM software suite to support the rapid prototyping and the easy simulation of the designed control solution. The experimental results prove several aspects of the proposed approach, notably the smooth migration between the design and the operation phases, one of the main objectives of the work.