Some Comments on Gerechte Designs

In a companion paper we derived the correct analysis for gerechte designs with uncorrected errors. Here we show that this correct analysis cannot be justified by the usual randomization argument. However, when the regions are rectangular there is a randomization procedure which validates an analysis with three separate error terms. We also outline other developments in design and analysis that may be more satisfactory.     

两相邻边固定两相邻边简支弹性薄板的两类变量广义变分原理

按照广义力和广义位移之间的对应关系,将弹性薄板的平衡方程和几何方程乘上相应的虚量,然后积分,代数相加,代入本构关系,进而建立两相邻边固定两相邻边简支弹性薄板的两类变量广义势能原理。通过代入另一类本构关系,再应用类似如上的方法,建立两相邻边固定两相邻边简支弹性薄板的两类变量广义余能原理。再将这两种两类变量的广义变分原理分别退化到弹性薄板的势能原理和余能原理。最后,应用两类变量广义余能原理求解弹性薄板的挠度。     

How geographically concentrated is poverty in Fiji?

In this paper, we present highly disaggregated estimates of expenditure‐based poverty in Fiji using data from the 2007 national census and 2008–2009 Household Income and Expenditure Survey. Predicted poverty is estimated at provincial and tikina levels. Poverty in Fiji is marked by considerable spatial heterogeneity that cannot be gauged by the division level household survey estimates revealing pockets of poverty even within relatively well‐off regions. Predicted poverty is highest in Cakaudrove province in Northern Division. Most strikingly, we find that 50% of all the poor in Fiji are concentrated in just 6 out of 85 tikinas, namely Suva, Labasa, Ba, Naitasiri, Vuda and Nadi. This finding has important implications for efficiency of targeted poverty alleviation programmes. We also focus on squatter settlements for which poverty headcount estimates using the Household Income and Expenditure Survey are not feasible. We find these settlements have rates of poverty headcount ratio that range from 38–55% depending on the Division the squatter settlement is located in; this range is significantly higher compared with the average urban poverty estimated at 26% and raises important social policy issues for addressing urban poverty.     

MapX在空间数据绑定与林业专题图制作中的应用探讨

从空间地图数据与属性数据的关联、专题图的生成各方法,就MapX在林业地理信息系统开发中空间数据绑定与专题图制作中的技术等作了简要探讨。     

茶梢蛾幼虫空间分布及其抽样技术

对茶梢蛾幼虫的空间分布型及抽样技术的研究结果表明,幼虫为普通聚集分布,其基本成分是面积为一株油茶大小的个体群,个体间相互吸引。调查时以棋盘式取样为佳。根据空间分布型分析,计算出序贯抽样模型为:最适理论抽样数模型为:     

Spatial distribution of weeds in arable crops: are current sampling and analytical methods appropriate?

This paper reviews the literature concerning the spatial distribution of weeds; highlighting the limitations of our current sampling and analytical methodologies, and suggesting how these inadequacies can be addressed. Most research studies have used discrete sampling, i.e. weeds are counted within a quadrat, on a grid basis. Few have mapped weeds at a whole-field scale, either with a resolution appropriate to spraying operations or key ecological processes. Statistical analyses used to describe the data can be divided into two main types, spatially implicit (also at the scale of the sampling unit) or spatially explicit, in which the location of individuals is included in the analyses. Spatially implicit methods can be strongly affected by quadrat size and mean density and are of doubtful benefit. More attention is required to address sampling resolution issues for spatially explicit methods. Our understanding of the formation and dynamics of spatial pattern, as well as predicting the consequences of site-specific management, can be improved with models. Unfortunately, most models consider only newly expanding patches and appear incapable of predicting spatial distributions when an area has been fully invaded. More detailed biological information is required if models are to become more realistic and informative. We also need to ensure that we understand the spatial processes in the context of the whole field environment, to optimize the success of site-specific weed management in the longer term.