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.

     

The gene encoding ganglioside-induced differentiation-associated protein 1 is mutated in axonal Charcot-Marie-Tooth type 4A disease.

We identified three distinct mutations and six mutant alleles in GDAP1 in three families with axonal Charcot-Marie-Tooth (CMT) neuropathy and vocal cord paresis, which were previously linked to the CMT4A locus on chromosome 8q21.1. These results establish the molecular etiology of CMT4A (MIM 214400) and suggest that it may be associated with both axonal and demyelinating phenotypes.     

Global Optimization in Any Minkowski Metric: A Permutation-Translation Simulated Annealing Algorithm for Multidimensional Scaling

It is well known that considering a non-Euclidean Minkowski metric in Multidimensional Scaling, either for the distance model or for the loss function, increases the computational problem of local minima considerably. In this paper, we propose an algorithm in which both the loss function and the composition rule can be considered in any Minkowski metric, using a multivariate randomly alternating Simulated Annealing procedure with permutation and translation phases. The algorithm has been implemented in Fortran and tested over classical and simulated data matrices with sizes up to 200 objects. A study has been carried out with some of the common loss functions to determine the most suitable values for the main parameters. The experimental results confirm the theoretical expectation that Simulated Annealing is a suitable strategy to deal by itself with the optimization problems in Multidimensional Scaling, in particular for City-Block, Euclidean and Infinity metrics.     

Systems Thinking and Scenario Planning: Application in the Clothing Sector

Industrial sectors that operate in uncertain environments - with demand variability, product seasonality and different industrialisation structures - need studies that enable identification and forecast trends. Therefore, the development of competitiveness extends beyond a company’s individual performance. Collective action, whether toward consumer markets, supplier markets, competitors and substitutes, can reinforce or help reformulate the current practices of an organisation, besides providing better results in the development of strategies and competitive positioning. Thus, clothing, the sector addressed in this work, is characterised by a long, fragmented, heterogeneous production chain, the competitiveness of which is linked to product differentiation. Therefore, the use of systemic approaches to study this sector is effective. In this sense, this research aims at adapting Systems Thinking and Scenario Planning (STSP) so that it supports the development and planning process in a given sector. Thus, this research applies STSP adapted to an analysis of the clothing sector in the northern region of Rio Grande do Sul State, Brazil. As a result, in academic terms, this research proposed and validated a method for analysing industrial sectors of the clothing industry. In the sectoral context, this research identified elements that leverage the sector’s competitiveness, besides generating knowledge and learning aimed at strengthening the sectoral structure identified, and fostering the formation of a new clothing cluster.     

Improving moving average trading rules with boosting and statistical learning methods

We present a system for combining the different types of predictions given by a wide category of mechanical trading rules through statistical learning methods (boosting, and several model averaging methods like Bayesian or simple averaging methods). Statistical learning methods supply better out‐of‐sample results than most of the single moving average rules in the NYSE Composite Index from January 1993 to December 2002. Moreover, using a filter to reduce trading frequency, the filtered boosting model produces a technical strategy which, although it is not able to overcome the returns of the buy‐and‐hold (B&H) strategy during rising periods, it does overcome the B&H during falling periods and is able to absorb a considerable part of falls in the market. Copyright © 2008 John Wiley & Sons, Ltd.     

PYY modulation of cortical and hypothalamic brain areas predicts feeding behaviour in humans

The ability to maintain adequate nutrient intake is critical for survival. Complex interrelated neuronal circuits have developed in the mammalian brain to regulate many aspects of feeding behaviour, from food-seeking to meal termination. The hypothalamus and brainstem are thought to be the principal homeostatic brain areas responsible for regulating body weight. However, in the current 'obesogenic' human environment food intake is largely determined by non-homeostatic factors including cognition, emotion and reward, which are primarily processed in corticolimbic and higher cortical brain regions. Although the pleasure of eating is modulated by satiety and food deprivation increases the reward value of food, there is currently no adequate neurobiological account of this interaction between homeostatic and higher centres in the regulation of food intake in humans. Here we show, using functional magnetic resonance imaging, that peptide YY3-36 (PYY), a physiological gut-derived satiety signal, modulates neural activity within both corticolimbic and higher-cortical areas as well as homeostatic brain regions. Under conditions of high plasma PYY concentrations, mimicking the fed state, changes in neural activity within the caudolateral orbital frontal cortex predict feeding behaviour independently of meal-related sensory experiences. In contrast, in conditions of low levels of PYY, hypothalamic activation predicts food intake. Thus, the presence of a postprandial satiety factor switches food intake regulation from a homeostatic to a hedonic, corticolimbic area. Our studies give insights into the neural networks in humans that respond to a specific satiety signal to regulate food intake. An increased understanding of how such homeostatic and higher brain functions are integrated may pave the way for the development of new treatment strategies for obesity.     

Metagenomic and functional analysis of hindgut microbiota of a wood-feeding higher termite

From the standpoints of both basic research and biotechnology, there is considerable interest in reaching a clearer understanding of the diversity of biological mechanisms employed during lignocellulose degradation. Globally, termites are an extremely successful group of wood-degrading organisms and are therefore important both for their roles in carbon turnover in the environment and as potential sources of biochemical catalysts for efforts aimed at converting wood into biofuels. Only recently have data supported any direct role for the symbiotic bacteria in the gut of the termite in cellulose and xylan hydrolysis. Here we use a metagenomic analysis of the bacterial community resident in the hindgut paunch of a wood-feeding 'higher' Nasutitermes species (which do not contain cellulose-fermenting protozoa) to show the presence of a large, diverse set of bacterial genes for cellulose and xylan hydrolysis. Many of these genes were expressed in vivo or had cellulase activity in vitro, and further analyses implicate spirochete and fibrobacter species in gut lignocellulose degradation. New insights into other important symbiotic functions including H2 metabolism, CO2-reductive acetogenesis and N2 fixation are also provided by this first system-wide gene analysis of a microbial community specialized towards plant lignocellulose degradation. Our results underscore how complex even a 1-microl environment can be.