145 research outputs found

    A choice function hyper-heuristic framework for the allocation of maintenance tasks in Danish railways

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    This work has been partially funded by the DAASE project, EPSRC programme grant EP/J017515/1

    Expression quantitative trait loci as possible biomarkers on depression

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    Expression quantitative trait loci as possible biomarkers on depression

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    Molecular and cellular neuroplasticity in animal models of depression

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    Smit, A.B. [Promotor]Hoogendijk, W.J.G. [Promotor]Spijker, S. [Copromotor

    2018 Symposium Brochure

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    This dissertation explores the mean field Heisenberg spin system and its evolution in time. We first study the system in equilibrium, where we explore the tool known as Stein's method, used for determining convergence rates to thermodynamic limits, both in an example proof for a mean field Ising system and in tightening a previous result for the equilibrium mean field Heisenberg system. We then model the evolution of the mean field Heisenberg model using Glauber dynamics and use this method to test the equilibrium results of two previous papers, uncovering a typographical error in one. Agreement in other aspects between theory and our simulations validates our approach in the equilibrium case. Next, we compare the evolution of the Heisenberg system under Glauber dynamics to a number of forms of Brownian motion and determine that Brownian motion is a poor match in most situations. Turning back to Stein's method, we consider what sort of proof regarding the behavior of the mean field Heisenberg model over time is obtainable and look at several possible routes to that path. We finish up by offering a Stein's method approach to understanding the evolution of the mean field Heisenberg model and offer some insight into its convergence in time to a thermodynamic limit. This demonstrates the potential usefulness of Stein's method in understanding the finite time behavior of evolving systems. In our efforts, we encounter several holes in current mathematical and physical knowledge. In particular, we suggest the development of tools for Markov chains currently unavailable and the development of a more physically based algorithm for the evolution of Heisenberg systems. These projects lie beyond the scope of this dissertation but it is our hope that these ideas may be useful to future research

    2018 Symposium Brochure

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    Complexity, Emergent Systems and Complex Biological Systems:\ud Complex Systems Theory and Biodynamics. [Edited book by I.C. Baianu, with listed contributors (2011)]

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    An overview is presented of System dynamics, the study of the behaviour of complex systems, Dynamical system in mathematics Dynamic programming in computer science and control theory, Complex systems biology, Neurodynamics and Psychodynamics.\u

    The 7th Conference of PhD Students in Computer Science

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