Enabling Workflows in GridSolve: Request Sequencing and Service Trading

International audienceGridSolve employs a RPC-based client-agent-server model for solving computational problems. There are two deficiencies associated with GridSolve when a computational problem essentially forms a workflow consisting of a sequence of tasks with data dependencies between them. First, intermediate results are always passed through the client, resulting in unnecessary data transport. Second, since the execution of each individual task is a separate RPC session, it is difficult to enable any potential parallelism among tasks. This paper presents a request sequencing technique that addresses these deficiencies and enables workflow executions. Building on the request sequencing work, one way to generate workflows is by taking higher level service requests and decomposing them into a sequence of simpler service requests using a technique called service trading. A service trading component is added to GridSolve to take advantage of the new dynamic request sequencing. The features described here include automatic DAG construction and data dependency analysis, direct interserver data transfer, parallel task execution capabilities, and a service trading component

Attraction Basins as Gauges of Robustness against Boundary Conditions in Biological Complex Systems

One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally

A view of Neural Networks as dynamical systems

We consider neural networks from the point of view of dynamical systems theory. In this spirit we review recent results dealing with the following questions, adressed in the context of specific models. 1. Characterizing the collective dynamics; 2. Statistical analysis of spikes trains; 3. Interplay between dynamics and network structure; 4. Effects of synaptic plasticity.Comment: Review paper, 51 pages, 10 figures. submitte

Spontaneous vertebral artery dissection presenting as symptomatic spinal subarachnoid haemorrhage

Spontaneous vertebral artery dissection presenting as symptomatic spinal subarachnoid haemorrhag

Whole brain quantitative CBF, CBV, and MTT measurements using MRI bolus tracking: implementation and application to data acquired from hyperacute stroke patients.

A robust whole brain magnetic resonance (MR) bolus tracking technique based on indicator dilution theory, which could quantitatively calculate cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) on a regional basis, was developed and tested. T2*-weighted gradient-echo echoplanar imaging (EPI) volumes were acquired on 40 hyperacute stroke patients after gadolinium diethylene triamine pentaacetic acid (Gd-DTPA) bolus injection. The thalamus, white matter (WM), infarcted area, penumbra, and mirror infarcted and penumbra regions were analyzed. The calculation of the arterial input function (AIF) needed for absolute quantification of CBF, CBV, and MTT was shown to be user independent. The CBF values (ml/min/100 g units) and CBV values (% units, in parentheses) for the thalamus, WM, infarct, mirror infarct, penumbra, and mirror penumbra (averaged over all patients) were 69.8 +/- 22.2 (9.0 +/- 3.0 SD); 28.1 +/- 6.9 (3.9 +/- 1.2); 34.4 +/- 22.4 (7.1 +/- 2.7); 60.3 +/- 20.7 (8.2 +/- 2.3); 50.2 +/- 17.5 (10.4 +/- 2.4); and 64.2 +/- 17.0 (9.5 +/- 2.3), respectively, and the corresponding MTT values (in seconds) were 8.0 +/- 2.1; 8.6 +/- 3.0; 16.1 +/- 8.9; 8.6 +/- 2.9; 13.3 +/- 3.5; and 9.4 +/- 3.2. The infarct and penumbra CBV values were not significantly different from their corresponding mirror values, whereas the CBF and MTT values were (P < 0.01). Quantitative measurements of CBF, CBV, and MTT were calculated on a regional basis on data acquired from hyperacute stroke patients, and the CBF and MTT values showed greater sensitivity to areas with perfusion defects than the CBV values. J. Magn. Reson. Imaging 2000;12:400-410

Whole brain quantitative CBF and CBV measurements using MRI bolus tracking: comparison of methodologies.

Three different deconvolution techniques for quantifying cerebral blood flow (CBF) from whole brain T*(2)-weighted bolus tracking images were implemented (parametric Fourier transform P-FT, parametric single value decomposition P-SVD and nonparametric single value decomposition NP-SVD). The techniques were tested on 206 regions from 38 hyperacute stroke patients. In the P-FT and P-SVD techniques, the tissue and arterial concentration time curves were fit to a gamma variate function and the resulting CBF values correlated very well (CBF(P-FT) = 1.02 x CBF(P-SVD), r(2) = 0.96). The NP-SVD CBF values (i.e., original unfitted curves were used) correlated well with the P-FT CBF values only when a sufficient number of time series volumes were acquired to minimize tracer time curve truncation (CBF(P-FT) x 0.92 x CBF(NP-SVD), r(2) = 0.88). The correlation between the fitted CBV and the unfitted CBV values was also maximized in regions with minimal tracer time curve truncation (CBV(fit) = 1.00 x CBV(unfit), r(2) = 0.89). When a sufficient number of time series volumes could not be acquired (due to scanner limitations) to avoid tracer time curve truncation, the P-FT and P-SVD techniques gave more reliable estimates of CBF than the NP-SVD technique

Imageries de diffusion et de perfusion en IRM à la phase hyperaiguë d'un accident vasculaire cérébral ischémique.

The sensitivity of diffusion-weighted MR imaging to detect a lesion within 6 hours of stroke onset was approximately 90%. The false negative results were usually small lesions (1 ml), were seen early, and were usually located in the brain stem. The specificity of this technique was nearly 100% when it was used correctly. The volume and the value of the apparent diffusion coefficient of the detected lesions provided prognostic information. After injection of a contrast agent (perfusion imaging), a time series of volumes were obtained using a T2* sensitive gradient echo EPI sequence. Hemodynamic perturbations of the cerebral parenchyma could be detected as well as the type of perturbation in the lesion. A map representing the mean transit time for each voxel was used to define the maximum volume of the perturbation. A hemodynamic penumbra was defined to be when this volume was larger than the volume detected on the diffusion images. The quantitative measure of cerebral blood flow could predict the irreversibility of the lesions when the value was below 18 ml/min/100g, and the extension of the ischemia in the penumbra zone when the value was below a threshold of 30 ml/min/100g

[Diffusion- and perfusion-weighted MR imaging during the hyperacute phase of stroke.]

The sensitivity of diffusion-weighted MR imaging to detect a lesion within 6 hours of stroke onset was approximately 90%. The false negative results were usually small lesions (less than or equal to 1 ml), were seen early, and were usually located in the brain stem. The specificity of this technique was nearly 100% when it was used correctly. The volume and the value of the apparent diffusion coefficient of the detected lesions provided prognostic information. After injection of a contrast agent (perfusion imaging), a time series of volumes were obtained using a T2* sensitive gradient echo EPI sequence. Hemodynamic perturbations of the cerebral parenchyma could be detected as well as the type of perturbation in the lesion. A map representing the mean transit time for each voxel was used to define the maximum volume of the perturbation. A hemodynamic penumbra was defined to be when this volume was larger than the volume detected on the diffusion images. The quantitative measure of cerebral blood flow could predict the irreversibility of the lesions when the value was below 18ml/min/100g, and the extension of the ischemia in the penumbra zone when the value was below a threshold of 30ml/min/100g