A Grid Supercomputing Enviroment for High Demand Computational Applications

Despite the huge increase in processor and interprocessor network performace, many computational problems remain unsolved due to lack of some critical resources such as floating point sustained performance, memory bandwidth, etc... Examples of these problems are found in areas of climate research, biology, astrophysics, high energy physics (montecarlo simulations) and artificial intelligence, among others. For some of these problems, computing resources of a single supercomputing facility can be 1 or 2 orders of magnitude apart from the resources needed to solve some them. Supercomputer centers have to face an increasing demand on processing performance, with the direct consequence of an increasing number of processors and systems, resulting in a more difficult administration of HPC resources and the need for more physical space, higher electrical power consumption and improved air conditioning, among other problems. Some of the previous problems can´t be easily solved, so grid computing, intended as a technology enabling the addition and consolidation of computing power, can help in solving large scale supercomputing problems. In this document, we describe how 2 supercomputing facilities in Spain joined their resources to solve a problem of this kind. The objectives of this experience were, among others, to demonstrate that such a cooperation can enable the solution of bigger dimension problems and to measure the efficiency that could be achieved. In this document we show some preliminary results of this experience and to what extend these objectives were achieved.

Computational explorations in Thompson's group F

Here we describe the results of some computational explorations in Thompson's group F. We describe experiments to estimate the cogrowth of F with respect to its standard finite generating set, designed to address the subtle and difficult question whether or not Thompson's group is amenable. We also describe experiments to estimate the exponential growth rate of F and the rate of escape of symmetric random walks with respect to the standard generating set.

Structure-function relationships of the alpha1b-adrenergic receptor.

The alpha1b-adrenergic receptor (AR) is a member of the large superfamily of seven transmembrane domain (TMD) G protein-coupled receptors (GPCR). Combining site-directed mutagenesis of the alpha1b-AR with computational simulations of receptor dynamics, we have explored the conformational changes underlying the process of receptor activation, i.e. the transition between the inactive and active states. Our findings suggest that the structural constraint stabilizing the alpha1b-AR in the inactive form is a network of H-bonding interactions amongst conserved residues forming a polar pocket and R143 of the DRY sequence at the end of TMDIII. We have recently reported that point mutations of D142, of the DRY sequence and of A293 in the distal portion of the third intracellular loop resulted in ligand-independent (constitutive) activation of the alpha1b-AR. These constitutively activating mutations could induce perturbations resulting in the shift of R143 out of the polar pocket. The main role of R143 may be to mediate receptor activation by triggering the exposure of several basic amino acids of the intracellular loops towards the G protein. Our investigation has been extended also to the biochemical events involved in the desensitization process of alpha1b-AR. Our results indicate that immediately following agonist-induced activation, the alpha1b-AR can undergo rapid agonist-induced phosphorylation and desensitization. Different members of the G protein coupled receptor kinase family can play a role in agonist-induced regulation of the alpha1b-AR. In addition, constitutively active alpha1b-AR mutants display different phosphorylation and internalization features. The future goal is to further elucidate the molecular mechanism underlying the complex equilibrium between activation and inactivation of the alpha1b-AR and its regulation by pharmacological substances. These findings can help to elucidate the mechanism of action of various agents displaying properties of agonists or inverse agonists at the adrenergic system.

Optimized venous return with a self-expanding cannula: from computational fluid dynamics to clinical application.

The Smart canula concept allows for collapsed cannula insertion, and self-expansion within a vein of the body. (A) Computational fluid dynamics, and (B) bovine experiments (76+/-3.8 kg) were performed for comparative analyses, prior to (C) the first clinical application. For an 18F access, a given flow of 4 l/min (A) resulted in a pressure drop of 49 mmHg for smart cannula versus 140 mmHg for control. The corresponding Reynolds numbers are 680 versus 1170, respectively. (B) For an access of 28F, the maximal flow for smart cannula was 5.8+/-0.5 l/min versus 4.0+/-0.1 l/min for standard (P<0.0001), for 24F 5.5+/-0.6 l/min versus 3.2+/-0.4 l/min (P<0.0001), and for 20F 4.1+/-0.3 l/min versus 1.6+/-0.3 l/min (P<0.0001). The flow obtained with the smart cannula was 270+/-45% (20F), 172+/-26% (24F), and 134+/-13% (28F) of standard (one-way ANOVA, P=0.014). (C) First clinical application (1.42 m2) with a smart cannula showed 3.55 l/min (100% predicted) without additional fluids. All three assessment steps confirm the superior performance of the smart cannula design.

A computational and geometric approach to phase resetting curves and surfaces

"Vegeu el resum a l'inici del document del fitxer adjunt."

Some progress on the chemistry of natural bioactive terpenoids form Chinese medicinal plants

(1) Pseudolaric acids - Novel diterpenes, Pseudolaric acid A, B, C and D were isolated from Pseudolarix kaempferi Gorden (pinaceae). Their structures were assigned by spectroscopic data and chemical correlations. In the contineous studies, the absolute configurations, the conformations in the solutions, the framentation mechanisms of MS and assigments of all NMR spectral signals were also reported. They showed the antifungal and cytotoxic activities. (2) Daphnane diterpenes - In the further studies on the plants of Thymelaeaceae, besides 10 known diterpenes, 16 new daphnane diterpenes were isolated from Daphne genkwa, D. tangutica, D. giraldii, Wikstroemie chamaedaphne. They showed the antifertilities activities. (3) Tripterygium diterpenes 14 new diterpenes were isolated from Triperygium wilfordii, T. regeli and T. hypoglaucum. Some of them showed the antitumor activities. The CD spectra showed that A/B ring of all compoundshave trans configuration as same as tripdiolide and triptolide determined by X-ray diffraction (4) Pregnane glycosides from Marsdenia koi - Two new pregnane glycosides marsdenikoiside A and marsdenikoiside B which can terminate the early pregnancy were isolated from Marsdeia koi. Their structures were elucidated by hydrolysis and spectroscopic methods.

Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

Investigation of Postmortem Gases: A Forensic Imaging and Analytical Chemistry Approach

Background: Distinguishing postmortem gas accumulations in the body due to natural decomposition and other phenomena such as gas embolism can prove a difficult task using purely Multi-Detector Computed Tomography (MDCT). The Radiological Alteration Index (RAI) was created with the intention to be able to identify bodies undergoing the putrefaction process based on the quantity of gas detected within the body. The flaw in this approach is the inability to absolutely determine putrefaction as the origin of gas volumes in cases of moderate alteration. The aim of the current study is to identify percentage compositions of O2, N2, CO2 and the presence of gases such as H2 and H2S within these sampling sites in order to resolve this complication. Materials and methods: All cases investigated in our University Center of Legal Medicine are undergoing a Post-Mortem Computed Tomography (PMCT)-scan before external examination or autopsy as a routine investigation. In the obtained images, areas of gas were characterized as 0, I, II or III based on the amount of gas present according to the RAI (1). The criteria for these characterizations were dependent of the site of gas, for example thoracic and abdominal cavities were graded as I (1 - 3cm gas), II (3 - 5cm gas) and III (>5cm gas). Cases showing gaseous sites with grade II or III were selected for this study. The sampling was performed under CT-guidance to target the regions to be punctured. Luer-lock PTFE syringes equipped with a three-way valve and needles were used to sample the gas directly (2). Gaseous samples were then analysed using gas chromatography coupled to a thermal conductivity detector (GC-TCD). The components present in the samples were expressed as a percentage of the overall gas present. Results: Up to now, we have investigated more than 40 cases using our standardized procedure for sampling and analysis of gas. O2, N2 and CO2 were present in most samples. The following distributions were found to correlate to gas origins of gas embolism/scuba diving accidents, trauma and putrefaction: ? Putrefaction → O2 = 1 - 5%; CO2 > 15%; N2 = 10 - 70%; H2 / H2S / CH4 variable presence ? Gas embolism/Scuba diving accidents → O2 and N2= varying percentages; CO2 > 20% ? Trauma → O2 = small percentage; CO2 < 15%; N2 > 65% H2 and H2S indicated levels of putrefaction along with methane which can also gauge environmental conditions or conditions of body storage/burial. Many cases showing large RAI values (advanced alteration) did reveal a radiological diagnosis which was in concordance with the interpretation of the gas composition. However, in certain cases (gas embolism, scuba divers) radiological interpretation was not possible and only chemical gas analysis was found to lead to the correct diagnosis, meaning that it provided complementary information to the radiological diagnosis. Conclusion: Investigation of postmortem gases is a useful tool to determine origin of gas generation which can aid the diagnosis of the cause of death. Levels of gas can provide information on stage of putrefaction and help to perform essential medico-legal diagnosis such as vital gas embolism.

A decision-making Fokker-Planck model in computational neuroscience

Minimal models for the explanation of decision-making in computational neuroscience are based on the analysis of the evolution for the average firing rates of two interacting neuron populations. While these models typically lead to multi-stable scenario for the basic derived dynamical systems, noise is an important feature of the model taking into account finite-size effects and robustness of the decisions. These stochastic dynamical systems can be analyzed by studying carefully their associated Fokker-Planck partial differential equation. In particular, we discuss the existence, positivity and uniqueness for the solution of the stationary equation, as well as for the time evolving problem. Moreover, we prove convergence of the solution to the the stationary state representing the probability distribution of finding the neuron families in each of the decision states characterized by their average firing rates. Finally, we propose a numerical scheme allowing for simulations performed on the Fokker-Planck equation which are in agreement with those obtained recently by a moment method applied to the stochastic differential system. Our approach leads to a more detailed analytical and numerical study of this decision-making model in computational neuroscience.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Paraphrasing : scope and typology : a computational approach

This PhD project aims to study paraphrasing, initially understood as the different ways in which the same content is expressed linguistically. We will go into that concept in depth trying to define and delimit its scope more accurately. In that sense, we also aim to discover which kind of structures and phenomena it covers. Although there exist some paraphrasing typologies, the great majority of them only apply to English, and focus on lexical and syntactic transformations. Our intention is to go further into this subject and propose a paraphrasing typology for Spanish and Catalan combining lexical, syntactic, semantic and pragmatic knowledge. We apply a bottom-up methodology trying to collect evidence of this phenomenon from the data. For this purpose, we are initially using the Spanish Wikipedia as our corpus. The internal structure of this encyclopedia makes it a good resource for extracting paraphrasing examples for our investigation. This empirical approach will be complemented with the use of linguistic knowledge, and by comparing and contrasting our results to previously proposed paraphrasing typologies in order to enlarge the possible paraphrasing forms found in our corpus. The fact that the same content can be expressed in many different ways presents a major challenge for Natural Language Processing (NLP) applications. Thus, research on paraphrasing has recently been attracting increasing attention in the fields of NLP and Computational Linguistics. The results obtained in this investigation would be of great interest in many of these applications.

Complementarities between mathematical and computational modeling: the case of the repeated Prisoners' Dilemma

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the mathematical model. Our main conclusion is that mathematical and computational models are good complements for research in social sciences. Indeed, while computational models are extremely useful to extend the scope of the analysis to complex scenarios hard to analyze mathematically, formal models can be useful to verify and to explain the outcomes of computational models.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flowcomputation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we develop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow computation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.