Promoting Entrepreneurship through a Community Learning Model – Case Study: Green Businesses

This article presents a community learning model formulated by Engineers Without Borders Colombia with the aim of providing communities with tools to create sustainable productive solutions which have relevancy for members and for potential customers. The goal of this formulation is to promote learning processes that are guided by decisions made by community members to propose sustainable and replicable initiatives. The model applicability is evidenced through a case study devoted to strengthening community-led green businesses in the Guavio Province, Colombia by collecting lessons and conclusions. Ultimately, this collection will prove useful in replicating the learning model in other similar rural communities.

     

Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms

In agglomerative hierarchical clustering, pair-group methods suffer from a problem of non-uniqueness when two or more distances between different clusters coincide during the amalgamation process. The traditional approach for solving this drawback has been to take any arbitrary criterion in order to break ties between distances, which results in different hierarchical classifications depending on the criterion followed. In this article we propose a variable-group algorithm that consists in grouping more than two clusters at the same time when ties occur. We give a tree representation for the results of the algorithm, which we call a multidendrogram, as well as a generalization of the Lance andWilliams’ formula which enables the implementation of the algorithm in a recursive way. The authors thank A. Arenas for discussion and helpful comments. This work was partially supported by DGES of the Spanish Government Project No. FIS2006–13321–C02–02 and by a grant of Universitat Rovira i Virgili.     

Chemical basis of pupal cannibalism in a caterpillar (Utetheisa ornatrix).

The moth Utetheisa ornatrix derives protection against predation from systemic pyrrolizidine alkaloids (PAs) that it sequesters as a larva from its foodplants (Leguminosae, Crotalaria spp.). We here show, in laboratory tests, that Utetheisa deficient in body PA can make up for the chemical shortfall by cannibalizing pupae. We present evidence indicating that cannibalism in larvae is elicited not by hunger, but possibly by PA deficiency itself, and that in making cannibalistic choices larvae prefer PA-containing over PA-free pupae. PAs themselves, either in crystalline form or as additives to food items, proved phagostimulatory to larvae. In nature Utetheisa tend to pupate away from their foodplant, essentially out of reach of larval attack. The threat of cannibalism may have contributed to the evolution of this pupation behavior.     

Overcompensation and population cycles in an ungulate.

Although theoretical studies show that overcompensatory density-dependent mechanisms can potentially generate regular or chaotic fluctuations in animal numbers, the majority of realistic single-species models of invertebrate populations are not overcompensatory enough to cause sustained population cycles. The possibility that overcompensation may generate cycles or chaos in vertebrate populations has seldom been considered. Here we show that highly overcompensatng density-dependent mortality can generate recurrent population crashes consistent with those observed in a naturally limited population of Soay sheep. The observed interval of three or more years between crashes points to sharp 'focusing' of mortality over a narrow range of population density.     

On the limitations of comparing mean square forecast errors

Linear models are invariant under non-singular, scale-preserving linear transformations, whereas mean square forecast errors (MSFEs) are not. Different rankings may result across models or methods from choosing alternative yet isomorphic representations of a process. One approach can dominate others for comparisons in levels, yet lose to another for differences, to a second for cointegrating vectors and to a third for combinations of variables. The potential for switches in ranking is related to criticisms of the inadequacy of MSFE against encompassing criteria, which are invariant under linear transforms and entail MSFE dominance. An invariant evaluation criterion which avoids misleading outcomes is examined in a Monte Carlo study of forecasting methods.