Towards a comprehensive green infrastructure typology: a systematic review of approaches,methods and typologies

There is no consensus on a comprehensive classification for green infrastructure (GI). This is a consequence of the diversity of disciplines, application contexts, methods, terminologies, purposes and valuation criteria for which a GI typology is required. The aim of this systematic literature review is to evaluate the existing evidence on how GI is being categorised and characterised worldwide. We reviewed a total of 85 studies from 15 countries that were analysed for contextual trends, methods, parameters and typologies. Results show that relevant literature lacks a common terminology and that a universal typology for all scenarios is impractical. Analysis reveals that GI can be organised into four main GI categories: (a) tree canopy, (b) green open spaces, (c) green roofs and (d) vertical greenery systems (facades/walls). Green open spaces and tree canopy attracted the attention of researchers due to their complexity, variability and important roles in GI planning. Evidence suggests that a ternary approach in terms of the functional (purpose, use, services), structural (morphology) and configurational (spatial arrangements) attributes of GI should be applied for a more comprehensive classification. Although this approximation is inherently generic, since it can be used across different research disciplines, it is also sufficiently specific to be implemented for individual scopes, scenarios and settings. Further research is needed to develop a typology capable of responding to particular research aims and performance analyses based upon the findings discussed in this paper.     

Relations of Temperament to Maladjustment and Ego Resiliency in At‐risk Children

The relations of control/regulation‐related temperamentally based dispositions (effortful control (EC), impulsivity, and approach/avoidance) to externalizing problems and personality ego resiliency were examined in a sample of 467 children (M age = 7.46 years), some of whom were children of alcoholics (COAs). In addition, we examined if the relations of temperamental regulation/control to maladjustment/ego resiliency were moderated by COA status or sex of the child. In general, regulated, controlled temperament was negatively related to externalizing problems and EC was positively related to ego resiliency. Relations between a problematic temperament and externalizing problems were stronger and sometimes only found for COAs, especially male COAs. Ego resiliency was positively related to high father‐reported approach for boys who were not sons of alcoholics. In addition, COA status was related to high impulsivity, approach behavior, and externalizing problems and low EC.     

Learning to learn and productivity growth: Evidence from a new car-assembly plant

This paper models learning by experience beyond the experience curve, including the possibility of “learning to learn”: the pace of learning increases over time by building on what has already been learned. We compare the extended deterministic learning model with Jovanovic and Nyarkos' [26] stochastic learning. The theoretical models are tested with data on the total factor productivity of a car-assembly plant in its first months of operation. We find that the deterministic “mixed learning model”, where the speed of learning is equal to a constant plus a learning to learn effect, is the one that best fits the empirical data. The mixed learning model results in a time pattern of total factor productivity growth, first increasing and later decreasing, different from the always decreasing rate of growth of the learning curve, opening new perspectives on the study of learning by experience.     

Cointegrated VARIMA Models: Specification and Simulation

In this note, we show how specify cointegrated vector autoregressive-moving average models and how they can be used to generate cointegrated time series.     

Risk-Management and Risk-Analysis-Based Decision Tools for Attacks on Electric Power

Incident data about disruptions to the electric power grid provide useful information that can be used as inputs into risk management policies in the energy sector for disruptions from a variety of origins, including terrorist attacks. This article uses data from the Disturbance Analysis Working Group (DAWG) database, which is maintained by the North American Electric Reliability Council (NERC), to look at incidents over time in the United States and Canada for the period 1990-2004. Negative binomial regression, logistic regression, and weighted least squares regression are used to gain a better understanding of how these disturbances varied over time and by season during this period, and to analyze how characteristics such as number of customers lost and outage duration are related to different characteristics of the outages. The results of the models can be used as inputs to construct various scenarios to estimate potential outcomes of electric power outages, encompassing the risks, consequences, and costs of such outages.     

Properties of systems with two exchangeable Pareto components

The life lengths of the units in a system can be modelled by a bivariate distribution. In this paper, we suppose that the joint distribution of the units is a symmetric bivariate Pareto (Lomax) distribution. For this model, we obtain basic reliability properties for series and parallel systems. J. M. Ruiz Partially Supported by Ministerio de Ciencia y Tecnologia under grant BFM2003-02947 and Fundacion Seneca under grant 00698/PI/04.     

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator.