Response Matrix Solution Using Boundary Condition Perturbation Theory for the Diffusion Approximation

A second-order response matrix method is developed for solving the diffusion equation in a coarse-mesh grid. In this method, the problem domain is divided into a grid of coarse meshes (nodes) of the size of a fuel assembly. Then, by using the fact that all nodes have the same eigenvalue, an equation is developed for the node interface current to flux ratio. The fine-mesh solution in the domain is then obtained by evaluating perturbation expressions for the core eigenvalue and the flux with the node interface current to flux ratios and the precomputed Green's functions for the unique assemblies in the system. The Green's functions and the perturbation expressions for the eigenvalue and flux are based on a high-order boundary condition perturbation method developed recently. Two example problems are used to assess the accuracy of the new method

ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but the reported results are largely incomparable due to different datasets and evaluation schemes. We approached this urgent problem of comparability with the Ischemic Stroke Lesion Segmentation (ISLES) challenge organized in conjunction with the MICCAI 2015 conference. In this paper we propose a common evaluation framework, describe the publicly available datasets, and present the results of the two sub-challenges: Sub-Acute Stroke Lesion Segmentation (SISS) and Stroke Perfusion Estimation (SPES). A total of 16 research groups participated with a wide range of state-of-the-art automatic segmentation algorithms. A thorough analysis of the obtained data enables a critical evaluation of the current state-of-the-art, recommendations for further developments, and the identification of remaining challenges. The segmentation of acute perfusion lesions addressed in SPES was found to be feasible. However, algorithms applied to sub-acute lesion segmentation in SISS still lack accuracy. Overall, no algorithmic characteristic of any method was found to perform superior to the others. Instead, the characteristics of stroke lesion appearances, their evolution, and the observed challenges should be studied in detail. The annotated ISLES image datasets continue to be publicly available through an online evaluation system to serve as an ongoing benchmarking resource (www.isles-challenge.org).Peer reviewe

Advances in HYDRA and its applications to simulations of inertial confinement fusion targets

A new set of capabilities has been implemented in the HYDRA 2D/3D multiphysics inertial confinement fusion simulation code. These include a Monte Carlo particle transport library. It models transport of neutrons, gamma rays and light ions, as well as products they generate from nuclear and coulomb collisions. It allows accurate simulations of nuclear diagnostic signatures from capsule implosions. We apply it to here in a 3D simulation of a National Ignition Facility (NIF) ignition capsule which models the full capsule solid angle. This simulation contains a severely rough ablator perturbation and provides diagnostics signatures of capsule failure due to excessive instability growth

Detection of temporal patterns in dog–human interaction

A new time structure model and pattern detection procedures developed by (Magnusson, M.S., 1996. Hidden real-time patterns in intra- and inter-individual behaviour description and detection. Eur.-J. Psychol. Assess. 12, 112-123; Magnusson, M.S., 2000. Discovering hidden time patterns in behaviour: T-patterns and their detection. Behav. Res. Methods, Instrum. Comput. 32, 93-110) enables us to detect complex temporal patterns in behaviour. This method has been used successfully in studying human and neuronal interactions (Anolli, L., Duncan, S. Magnusson, M.S., Riva G. (Eds.), 2005. The Hidden Structure of Interaction, IOS Press, Amsterdam). We assume that similarly to interactions between humans, cooperative and communicative interaction between dogs and humans also consist of patterns in time. We coded and analyzed a cooperative, situation when the owner instructs the dog to help build a tower and complete the task. In this situation, a cooperative interaction developed spontaneously, and occurrences of hidden time patterns in behaviour can be expected. We have found such complex temporal patterns (T-patterns) in each pair during the task that cannot be detected by "standard" behaviour analysis. During cooperative interactions the dogs' and humans' behaviour becomes organized into interactive temporal patterns and that dog-human interaction is much more regular than yet has been thought. We have found that communicative behaviour units and action units can be detected in the same T-pattern during cooperative interactions. Comparing the T-patterns detected in the dog-human dyads, we have found a typical sequence emerging during the task, which was the outline of the successfully completed task. Such temporal patterns were conspicuously missing from the "randomized data" that gives additional support to the claim that interactive T-patterns do not occur by chance or arbitrarily but play a functional role during the task