Aquilegia, Vol. 29 No. 1, January-February 2005: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1104/thumbnail.jp

Aquilegia, Vol. 27 No. 3, August 2003: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1098/thumbnail.jp

Investigating the Perspectives of Social Value for a UK Flood Alleviation Scheme

The argument presented in this paper calls for an approach to flood infrastructure that considers not only the need for a technical perspective in design and construction but also a social perspective. As a result of climate change and changing weather patterns, it is predicted that more intense rainfall will be experienced, as well as rising sea levels, resulting in a greater number of people across the world becoming vulnerable to flood events. The need for flood alleviation infrastructure is therefore highly likely to increase. However industry professionals responsible for design and construction have often neglected to see flooding as a social problem; consequently they focus only on the technical and cost-effective, rather than the social end user orientated, aspects of their design solutions. This paper presents the preliminary findings from research that seeks to understand how the social value of flood alleviation schemes is interpreted and discussed. The results are derived from an examination of the Didsbury Flood Storage Basin Improvements scheme between April and August 2013 in Manchester, UK. A series of semi-structured interviews were conducted with both the community and those responsible for the design, delivery and construction of the scheme. The findings presented demonstrate how social value is articulated by both groups, and where a difference in interpretation and perspectives exists. These findings reinforce the argument that adopting a socially, as well as technically, considerate approach for future flood infrastructure design and construction is a necessity, as more communities around the world are exposed to the very real risk of flood events.This research was carried out with the aid of funding from an Engineering and Physical Sciences Research Council (EPSRC) iCase doctoral award.This is the final version. It was first published by the Research Division of Social Sciences of ATINER in Athens Journal of Social Sciences at http://www.athensjournals.gr/social/Cover-2014-04social.pdf

Aquilegia, Vol. 29 No. 2, March-April 2005: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1112/thumbnail.jp

Aquilegia, Vol. 28 No. 1, January-February 2004: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1101/thumbnail.jp

Aquilegia, Vol. 30 No. 2, April-May 2006: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1107/thumbnail.jp

Breeding for Increased Protein in Winter Wheat

Crop Scienc

Aquilegia, Vol. 30 No. 3, June-July 2006, Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1116/thumbnail.jp

Applying Bayesian model averaging to characterise urban residential stock turnover dynamics

Building stock is a key determinant in building energy modelling and policy analysis. However, official statistics on total floor area of urban residential stock in China only exist up to 2006. Previous studies estimating Chinese urban residential stock size and energy use made various questionable methodological assumptions and only produced deterministic results. This paper presents a Bayesian approach to characterise the stock turnover dynamics and estimate stock size uncertainties. Firstly, a probabilistic dynamic model is developed to describe the building aging and demolition process governed by a hazard function specified by a parametric survival model. Secondly, with each of five candidate parametric survival models, the dynamic model is simulated through Markov Chain Monte Carlo (MCMC) to obtain posterior distributions of model-specific parameters, estimate marginal likelihood, and make predictions on stock size. Finally, Bayesian Model Averaging (BMA) is applied to create a model ensemble that combines the model-specific posterior predictive distributions of the stock evolution pathway in proportion to posterior model probabilities. This Bayesian modelling framework, and its results in the form of probability distributions of annual total stock and age-specific substocks, can provide a solid basis for further modelling and analysis of policy trade-offs across embodied-versus-operational energy consumption and carbon emissions of buildings in the context of sectorwide transition towards decarbonising buildings

Aquilegia, Vol. 28 No. 3, May-June-July 2004: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1102/thumbnail.jp