9,776 research outputs found

    Nonlinear Eigenvalue Approach to Differential Riccati Equations for Contraction Analysis

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    In this paper, we extend the eigenvalue method of the algebraic Riccati equation to the differential Riccati equation (DRE) in contraction analysis. One of the main results is showing that solutions to the DRE can be expressed as functions of nonlinear eigenvectors of the differential Hamiltonian matrix. Moreover, under an assumption for the differential Hamiltonian matrix, real symmetricity, regularity, and positive semidefiniteness of solutions are characterized by nonlinear eigenvalues and eigenvectors

    Story structure and reader affect in American and Hungarian short stories

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    Running title: Story structure and reader affectBibliography: leaves 31-32Supported in part by the National Institute of Education under contract no. NIE-C-400-81-003

    Japanese activities in refrigeration technology

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    Recent activities in refrigeration technology in Japan are discussed. Stirling cycle refrigerators and magnetic refrigerators are discussed. The development of units for use on trains is discussed

    Insertion of sequences at the original provirus integration site of mouse ROSA26 locus using the CRISPR/Cas9 system.

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    Targeted transgenic mouse models, where an exogenous gene is inserted into a specified genomic locus to achieve its stable and reliable expression, have been widely used in biomedical research. However, the available methodologies for targeted insertion of sequences require many laborious steps that involve the use of embryonic stem (ES) cells. We recently developed Pronuclear Injection-based Targeted Transgenesis (PITT), a method that uses a recombinase-mediated cassette exchange (RMCE) to enable insertion of sequences at a predetermined genomic locus, such as ROSA26. The PITT technique uses fertilized eggs (instead of ES cells) collected from \u27seed mice\u27 that contain the RMCE landing pad. The PITT method can rapidly generate reliable targeted transgenic mice; it requires a seed mouse, which in our previous study was generated using ES cell targeting approaches. Here, we demonstrate that seed mice containing the RMCE landing pad can be developed rapidly by using the CRISPR/Cas9 system. One of the CRISPR targets tested in this study enabled the insertion of sequences precisely at the original ROSA26 provirus integration site. We anticipate that using a similar approach, PITT landing pad sequences can be rapidly and precisely inserted at other genomic loci to develop an array of PITT tools. This two-step strategy combines the best features of the two newer technologies-rapid creation of PITT landing pads using the CRISPR/Cas9 system and efficient and precise insertion of larger cassettes at the landing pads using PITT. This study also revealed that anomalous and mosaic sequence insertions can occur with the CRISPR/Cas9 system

    Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces

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    © 2007 EUCA.A novel online-computation approach to optimal control of nonlinear, noise-affected systems with continuous state and control spaces is presented. In the proposed algorithm, system noise is explicitly incorporated into the control decision. This leads to superior results compared to state-of-the-art nonlinear controllers that neglect this influence. The solution of an optimal nonlinear controller for a corresponding deterministic system is employed to find a meaningful state space restriction. This restriction is obtained by means of approximate state prediction using the noisy system equation. Within this constrained state space, an optimal closed-loop solution for a finite decision-making horizon (prediction horizon) is determined within an adaptively restricted optimization space. Interleaving stochastic dynamic programming and value function approximation yields a solution to the considered optimal control problem. The enhanced performance of the proposed discrete-time controller is illustrated by means of a scalar example system. Nonlinear model predictive control is applied to address approximate treatment of infinite-horizon problems by the finite-horizon controller
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