High resolution dynamic cardiac MRI using partial separability of spatiotemporal signals with a novel sampling scheme

The partial separability (PS) of spatiotemporal signals has been exploited to accelerate dynamic cardiac MRI by sampling two datasets (training and imaging datasets) without breath-holding or ECG triggering. According to the theory of partially separable functions, the wider the range of spatial frequency components covered by the training dataset, the more accurate the temporal constraint imposed by the PS model. Therefore, it is necessary to develop a new sampling scheme for the PS model in order to cover a wider range of spatial frequency components. In this paper, we propose the use of radial sampling trajectories for collecting the training dataset and Cartesian sampling trajectories for collecting the imaging dataset. In vivo high resolution cardiac MRI experiments demonstrate that the proposed data sampling scheme can significantly improve the image quality. The image quality using the PS model with the proposed sampling scheme is comparable to that of a commercial method using retrospective cardiac gating and breath-holding. The success of this study demonstrates great potential for high-quality, high resolution dynamic cardiac MRI without ECG gating or breath-holding through use of the PS model and the novel data sampling scheme.     

A low-temperature high-pressure apparatus with a temperature control system

Abstract

A low-temperature high-pressure apparatus was designed using commercial cryogenic equipment. Pressures up to 1 GPa and temperatures down to 40 K can be obtained in a volume of up to 30 cm³. The apparatus is of the piston-cylinder type with a piston diameter of 45 mm, and the pressure can be varied at all temperatures, An adaptive temperature control system keeps the temperature inside the pressure cylinder constant to within ±0.1 K.     

Parallel globally adaptive quadrature on the KSR-1

New algorithms for parallel one-dimensional globally adaptive quadrature are developed. The algorithms are implemented on a Kendall Square Research KSR-1 parallel computer and numerical results are presented. The most successful algorithm gives significant speedups on a range of hard problems, including ones with singular integrands. Both authors acknowledge the support of the EEC Esprit Basic Research Action Programme, Project 6634 (APPARC). The second author acknowledges the support of the NATO Collaborative Research Grant 920037.     

DQAINF: an algorithm for automatic integration of infinite oscillating tails

We describe an automatic quadrature routine which is specifically designed for real functions having a certain type of infinite oscillating tails. The algorithm is designed to integrate a vector function over an infinite interval. A FORTRAN implementation of the algorithm is included.The algorithm combines an adaptive subdivision strategy with extrapolation and requires that the decay of all the functions in the vector is the same. The algorithm is based on the assumption that the oscillating behavior is due to a periodic function with the property that it changes sign when evaluated at points of distance half a period. We assume that this period is known. The algorithm offers a choice of three different quasi-linear extrapolation procedures, namely the Euler transformation and two modifications of this transformation.This work was supported by The Norwegian Research Council for Science and the Humanities.     

Random sampling within the framework of a multivariate principal-agent approach

In this paper, we analyze a specific class of principal-agent models which seems to be sufficiently general to cover applications in environmental economics with upstream-downstream problems as an example. In our basic model, the observation outcome is ann-dimensional random vectorx and only the first and second moments ofx are common knowledge. We study the effects of random sampling in the presence of costly signals. For this purpose, we assume that the principal and the agent use a simple statistical procedure, i.e. their contract will be based on the mean of a random sample with sampling costs dependent on the sample size. It is shown that there exists an optimal sample size. We investigate the relationship between the optimal sample size, the marginal sampling costs, and the agent's risk aversion.     

定速风力发电机模型参考自适应控制

在对定速风力发电机建模的基础上,设计了模型参考自适应控制器,并进行了跟随性能和抗干扰性能仿真,仿真结果表明自适应控制器的自适应能力很好.     

大口径望远镜的高分辨成像技术

大口径望远镜的高分辨率成像观测技术是一项对天文学研究和空间目标探测都非常重要的技术,其中最核心的就是自适应光学。文章简要回顾了天文望远镜以及自适应光学技术的发展历程,围绕未来大口径望远镜发展需求,详细介绍了具有高空间分辨率特色的液晶自适应光学技术的发展历史及其现状。     

Rapprochement of artificial intelligence and dynamics

It is proposed that continuous time is in effect discretized in the brain by dynamic pattern recognition mechanisms in neurons. Time discretization is required to support formal computations in continuous time systems consisting of a large number of components. The ability to perform formal computations is necessary if the system is to execute high level algorithms of the type used in present day artificial intelligence. The weakness of such algorithms is that they work efficiently only when the forms of patterns and objects presented to them are highly constrained. The dynamic mechanisms which discretize the brain's time line also serve to code patterns into constrained forms suitable for high level processing.     

Time behavior of stressed nonhierarchical networks

In this paper it is shown, by means of simulation, that interesting time behavior is observed for damaged and overloaded networks, and that adaptive, decentralized intelligence can have a dramatic influence on the overall network performance. The time behavior of nonhierarchical networks is modeled by a system of nonlinear difference equations among global variables, and bistability is shown to exist. Using a simple adaptive control mechanism, it is shown that, depending upon the value of a certain network variable, either limit cycle or steady state behavior results. A few ideas are discussed for applications of nonhierarchical communications to cellular automata and to decision-making systems.     

动态波前误差的自适应光学实时校正

本文报道了在实验室里用由21元面阵变形反射镜、横向剪切干涉仪和平行控制系统构成的自适应光学系统实时校正动态波前误差的原理和实验结果.