Functional and dynamic magnetic resonance imaging using vector adaptive weights smoothing

We consider the problem of statistical inference for functional and dynamic magnetic resonance imaging (MRI). A new approach is proposed which extends the adaptive weights smoothing procedure of Polzehl and Spokoiny that was originally designed for image denoising. We demonstrate how the adaptive weights smoothing method can be applied to time series of images, which typically occur in functional and dynamic MRI. It is shown how signal detection in functional MRI and the analysis of dynamic MRI can benefit from spatially adaptive smoothing. The performance of the procedure is illustrated by using real and simulated data.     

A new approach to investigating spatial variations of disease

Summary.  For rare diseases the observed disease count may exhibit extra Poisson variability, particularly in areas with low or sparse populations. Hence the variance of the estimates of disease risk, the standardized mortality ratios, may be highly unstable. This overdispersion must be taken into account otherwise subsequent maps based on standardized mortality ratios will be misleading and, rather than displaying the true spatial pattern of disease risk, the most extreme values will be highlighted. Neighbouring areas tend to exhibit spatial correlation as they may share more similarities than non-neighbouring areas. The need to address overdispersion and spatial correlation has led to the proposal of Bayesian approaches for smoothing estimates of disease risk. We propose a new model for investigating the spatial variation of disease risks in conjunction with an alternative specification for estimates of disease risk in geographical areas—the multivariate Poisson–gamma model. The main advantages of this new model lie in its simplicity and ability to account naturally for overdispersion and spatial auto-correlation. Exact expressions for important quantities such as expectations, variances and covariances can be easily derived.     

Tests based on weighted rankings in complete blocks: exact distribution and monte carlo simulation

Quade (1972, 1979) proposed a family of nonparametric tests based on weighted within-block rankings, for testing the hypothesis of no treatment effects in a complete randomized blocks layout. In this paper we give a table of the exact null distribution of these tests when the number of treatments is 3, the number of blocks is less than or equal to 14 and the block scores are linear. Moreover, a Monte Carlo study was performed to compare the powers of these tests with parametric and nonparametric competitors     

基于Panel Data和SEA的环境Kuznets曲线分析 ——与马树才、李国柱两位先生探讨

 针对当前学者研究中国环境Kuznets曲线存在的问题，本文使用了面板数据模型和空间计量模型，以克服使用时间序列模型时样本数量偏少和使用截面数据时易引起空间自相关性等问题。结果表明中国有部分环境指标满足环境Kuznets曲线的倒U型特征。     

DOUBLE LENGTH ARTIFICIAL REGRESSIONS FOR TESTING SPATIAL DEPENDENCE

This paper derives two simple artificial Double Length Regressions (DLR) to test for spatial dependence. The first DLR tests for spatial lag dependence while the second DLR tests for spatial error dependence. Both artificial regressions utilize only least squares residuals of the restricted model and are therefore easy to compute. These tests are illustrated using two simple examples. In addition, Monte Carlo experiments are performed to study the small sample performance of these tests. As expected, these DLR tests have similar performance to their corresponding LM counterparts.     

Procrustes shape analysis of triangulations of a two coloured point pattern

Consider a set of points in the plane with Gaussian perturbations about a regular mean configuration in which a Delaunay triangulation of the mean of the process is comprised of equilateral triangles of the same size. The points are labelled at random as black or white with variances of the perturbations possibly dependent on the colour. By investigating triangle subsets (with four sets of possible colour labels for the vertices) in detail we propose various test statistics based on a Procrustes shape analysis. A simulation study is carried out to investigate the relative merits and the adequacy of the approximations used in the distributional results, as well as a comparison with simulation methods based on nearest-neighbour distances. The methodology is applied to an investigation of regularity in human muscle fibre cross-sections.     

Governing the Circular Economy in the City: Local Planning Practice in London

ABSTRACT

There is interest in the circular economy as a framework for transition from a linear take-make-dispose model of production and consumption, to a circular model which decouples economic growth from resource consumption. However, there is limited understanding of how that applies to the city through governance lens. This paper examines evidence from 28 municipalities in London to unpack the ‘government’ and ‘governance’ of circular economy in the city. It examines the ‘governmentality’ of circular economy in planning practice and reflects on what austerity localism and scalar politics might mean for the planning and governance of circular economy in cities.     

论"代表最大多数人民利益"的创新内涵

江泽民在党的十六大报告中再次重申代表最大多数人民利益,具有深刻的社会内涵和哲学意蕴:其一,是把发展 看作代表大多数人民利益的前提和基础;其二,代表大多数人民必须正视当前利益格局的变化;其三,是坚持唯物史 观,回应各种错误思潮。     

A Novel Eigenvector Technique for Large Scale Combinatorial Problems in VLSI Layout

Modern integrated circuit design involves laying out circuits which consist of millions of switching elements or transistors. Due to the sheer complexity, optimizing the connectivity between transistors is a very difficult problem. How a circuit is interconnected is the single most important factor in performance criteria such as signal delay, power dissipation, circuit size and cost. These factors dictate that interconnections—wires, be made as short as possible. The wire–minimization problem is formulated as a sequence of discrete optimization subproblems. These problems are known to be NP-hard, hence they can only be solved approximately using meta-heuristics or linear programming techniques. Nevertheless, these methods are computationally expensive and the quality of solution depends to a great extent on an appropriate choice of starting configuration. A matrix reordering technique for solving very hard discrete optimization problems in Very Large Scale Integrated (VLSI) design which overcomes some of these shortcomings is proposed. In particular, the computational cost is reasonable—of the order of n ^1.4 running time.     

County child poverty rates in the US: a spatial regression approach

We apply methods of exploratory spatial data analysis (ESDA) and spatial regression analysis to examine intercounty variation in child poverty rates in the US. Such spatial analyses are important because regression models that exclude explicit specification of spatial effects, when they exist, can lead to inaccurate inferences about predictor variables. Using county-level data for 1990, we re-examine earlier published results [Friedman and Lichter (Popul Res Policy Rev 17:91–109, 1998)]. We find that formal tests for spatial autocorrelation among county child poverty rates confirm and quantify what is obvious from simple maps of such rates: the risk of a child living in poverty is not (spatially) a randomly distributed risk at the county level. Explicit acknowledgment of spatial effects in an explanatory regression model improves considerably the earlier published regression results, which did not take account of spatial autocorrelation. These improvements include: (1) the shifting of “wrong sign” parameters in the direction originally hypothesized by the authors, (2) a reduction of residual squared error, and (3) the elimination of any substantive residual spatial autocorrelation. While not without its own problems and some remaining ambiguities, this reanalysis is a convincing demonstration of the need for demographers and other social scientists to examine spatial autocorrelation in their data and to explicitly correct for spatial externalities, if indicated, when performing multiple regression analyses on variables that are spatially referenced. Substantively, the analysis improves the estimates of the joint effects of place-influences and family-influences on child poverty.