Systemic Indicators for Rural Communities in Developing Economies: Bringing the Shared Vision into Being

Community indicators have been a frequent focus of the scholarly literature. There has been little exploration, however, in relation to rural communities, especially in developing countries. This reflects the special challenges associated with the complexity of rural systems, and the difficulties involved in developing appropriate and systemic indicators for rural communities. Identifying indicators that help the community to monitor progress towards sustainable outcomes requires a framework that is both practical and holistic. This paper introduces a participatory systemic framework for identifying community indicators, which respects the principles of complexity and honours the sense of ownership present in the communities. This framework is an iterative, sharing, co-learning engagement process that extends from creating a shared vision and extracting its core messages, to identifying indicators of progress and determining what actions to try. Importantly, this framework enables us to rank the indicators identified by communities with reference to ‘leverage points’, the best places to intervene in the social-environmental system for transformational change. This framework provides a potential pathway for sustainable rural development and perhaps also for organisations and urban communities.     

Tritium analyses of groundwater from the Gort Lowland of Western Ireland

Zusammenfassung Grundwasserproben aus der Gort-Ebene (West-Irland) wurden auf Tritium-Gehalt analysiert und die Ergebnisse mit dem bereits bekannten Tritium-Einstrom dieser Gegend verglichen. Registrierungen des «World Precipitation Network» in Wien ergaben den Nachweis eines offenbar langsamen Durchflusses in das Grundwasser-Aquifer-System.

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Acknowledgments. The authors are indebted to the Nuclear Physics Division, Atomic Energy Research Establishment, Harwell (England) for tritium analyses and to Mr.B. R. Payne, Section of Isotope Hydrology, IAEA, Wien (Austria) for providing unpublished tritium data from Valentia for the period 1966 to 1971.     

铜镜表面“黑漆古”中“痕像”的研究

采用矿相薄片制备方法暴露出“黑漆古”矿化层。矿相显微镜下偏光现察，此矿化层透光、且具有原金属的α与δ痕像及较多圆形颗粒，说明此矿化层是铜镜自身的组成部分而不是附加在镜面上的沉积物或镀锡层腐蚀产物。此矿化层的ＳＥＭ能谱分析显示，ａ与ａ痕像以及圆形颗粒在成分上是十分相近的，是高Ｓｎ、低Ｃｕ并含有一定量的Ｐｂ、Ｓｉ、Ｆｅ。ＸＰＳ及ＸＲＤ分析结果显示铜镜“黑漆古”表面以ＳｎＯ２。细晶为主要组成。以上研究结果对探讨“黑漆古”形成机理提供直接证据。进一步表明矿化层的形成是在铜镜埋葬环境下腐蚀作用的结果，发生了氧化－络合－凝胶析出及脱水等一系列化学变化。     

Recognizing Treelike k-Dissimilarities

A k-dissimilarity D on a finite set X, |X|????k, is a map from the set of size k subsets of X to the real numbers. Such maps naturally arise from edgeweighted trees T with leaf-set X: Given a subset Y of X of size k, D(Y ) is defined to be the total length of the smallest subtree of T with leaf-set Y . In case k?=?2, it is well-known that 2-dissimilarities arising in this way can be characterized by the so-called ??4-point condition??. However, in case k?>?2 Pachter and Speyer (2004) recently posed the following question: Given an arbitrary k-dissimilarity, how do we test whether this map comes from a tree? In this paper, we provide an answer to this question, showing that for k????3 a k-dissimilarity on a set X arises from a tree if and only if its restriction to every 2?k-element subset of X arises from some tree, and that 2?k is the least possible subset size to ensure that this is the case. As a corollary, we show that there exists a polynomial-time algorithm to determine when a k-dissimilarity arises from a tree. We also give a 6-point condition for determining when a 3-dissimilarity arises from a tree, that is similar to the aforementioned 4-point condition.     

Mixtures of Autoregressions with an Improper Component for Panel Data

An EM algorithm for fitting mixtures of autoregressions of low order is constructed and the properties of the estimators are explored on simulated and real datasets. The mixture model incorporates a component with an improper density, which is intended for outliers. The model is proposed as an alternative to the search for the order of a single-component autoregression. The methods can be adapted to other patterns of dependence in panel data. An application to the monthly records of income of the outlets of a retail company is presented.