Is cognitive science interdisciplinary or multidisciplinary? We contribute to this debate by examining the authorship structure and topic similarity of contributions Cognitive Science Society from 2000 2019. Our analysis focuses on graph theoretic features co-authorship network—edge density, transitivity, maximum subgraph size—as well as clustering within space scientific topics. also combine s...

Objectives: This paper reviews the current literature on acquired brain injury (ABI) with a focus on ABI burden, importance of community integration, and community integration definitions suggested by the literature. Methods: Literature review Results: Acquired brain injury (ABI) is referred to a diverse range of disabilities resulted of injury in different parts of the brain. People with AB...

--The evaluation of convolution can be cumbersome and unpleasant for most students. In this paper, a novel and much simpler technique is presented. The intent is to convolve two signals given their start and end times. The technique was beneficial as it could easily be explained when it was introduced to undergraduate students in Signals and Systems class. Additionally, a simplistic method on i...

Integration by parts reduction is a standard component of most modern multi-loop calculations in quantum field theory. We present a novel strategy constructed to overcome the limitations of currently available reduction programs based on Laporta’s algorithm. The key idea is to construct algebraic identities from numerical samples obtained from reductions over finite fields. We expect the method...

We establish an integration by parts formula in an abstract framework in order to study the regularity of the law for processes solution of stochastic differential equations with jumps, including equations with discontinuous coefficients for which the Malliavin calculus developed by Bismut and Bichteler, Gravereaux and Jacod fails. 2000 MSC. Primary: 60H07, Secondary 60G51

We develop an integration by parts technique for point processes, with application to the computation of sensitivities via Monte Carlo simulations in stochastic models with jumps. The method is applied to density estimation and to the construction of a modified kernel estimator which is less sensitive to variations of the bandwidth parameter than standard kernel estimators. Simulations are pres...