James M.R.,Lancaster University |
Robson S.,Environmental and Geomatic Engineering
Journal of Geophysical Research: Earth Surface | Year: 2012
Topographic measurements for detailed studies of processes such as erosion or mass movement are usually acquired by expensive laser scanners or rigorous photogrammetry. Here, we test and use an alternative technique based on freely available computer vision software which allows general geoscientists to easily create accurate 3D models from field photographs taken with a consumer-grade camera. The approach integrates structure-from-motion (SfM) and multiview-stereo (MVS) algorithms and, in contrast to traditional photogrammetry techniques, it requires little expertise and few control measurements, and processing is automated. To assess the precision of the results, we compare SfM-MVS models spanning spatial scales of centimeters (a hand sample) to kilometers (the summit craters of Piton de la Fournaise volcano) with data acquired from laser scanning and formal close-range photogrammetry. The relative precision ratio achieved by SfM-MVS (measurement precision: observation distance) is limited by the straightforward camera calibration model used in the software, but generally exceeds 1:1000 (i.e., centimeter-level precision over measurement distances of 10s of meters). We apply SfM-MVS at an intermediate scale, to determine erosion rates along a ∼50-m-long coastal cliff. Seven surveys carried out over a year indicate an average retreat rate of 0.70 0.05m a-1. Sequential erosion maps (at ∼0.05m grid resolution) highlight the spatiotemporal variability in the retreat, with semivariogram analysis indicating a correlation between volume loss and length scale. Compared with a laser scanner survey of the same site, SfM-MVS produced comparable data and reduced data collection time by ∼80%. © 2012. American Geophysical Union. All Rights Reserved.
Taylor J.,Environmental and Geomatic Engineering |
Lai K.M.,Environmental and Geomatic Engineering |
Clifton D.,Polygon UK Ltd
Environment International | Year: 2011
With a changing climate and increased urbanisation, the occurrence and the impact of flooding is expected to increase significantly. Floods can bring pathogens into homes and cause lingering damp and microbial growth in buildings, with the level of growth and persistence dependent on the volume and chemical and biological content of the flood water, the properties of the contaminating microbes, and the surrounding environmental conditions, including the restoration time and methods, the heat and moisture transport properties of the envelope design, and the ability of the construction material to sustain the microbial growth. The public health risk will depend on the interaction of these complex processes and the vulnerability and susceptibility of occupants in the affected areas. After the 2007 floods in the UK, the Pitt review noted that there is lack of relevant scientific evidence and consistency with regard to the management and treatment of flooded homes, which not only put the local population at risk but also caused unnecessary delays in the restoration effort. Understanding the drying behaviour of flooded buildings in the UK building stock under different scenarios, and the ability of microbial contaminants to grow, persist, and produce toxins within these buildings can help inform recovery efforts. To contribute to future flood management, this paper proposes the use of building simulations and biological models to predict the risk of microbial contamination in typical UK buildings. We review the state of the art with regard to biological contamination following flooding, relevant building simulation, simulation-linked microbial modelling, and current practical considerations in flood remediation. Using the city of London as an example, a methodology is proposed that uses GIS as a platform to integrate drying models and microbial risk models with the local building stock and flood models. The integrated tool will help local governments, health authorities, insurance companies and residents to better understand, prepare for and manage a large-scale flood in urban environments. © 2011 Elsevier Ltd.
Schobi R.,Environmental and Geomatic Engineering |
Chatzi E.N.,Environmental and Geomatic Engineering
Structure and Infrastructure Engineering | Year: 2015
The signs of deterioration in worldwide infrastructure and the associated socio-economic and environmental losses call for sustainable resource management and policy-making. To this end, this work presents an enhanced variant of partially observable Markov decision processes (POMDPs) for the life cycle assessment and maintenance planning of infrastructure. POMDPs comprise a method, commonly employed in the field of robotics, for decision-making on the basis of uncertain observations. In the work presented herein, a continuous-state POMDP formulation is presented which is adapted to the problem of decision-making for optimal management of civil structures. The aforementioned problem may comprise non-linear and non-deterministic action and observation models. The continuous-state POMDP is herein coupled with a normalised unscented transform (NUT) in order to deliver a framework able to tackle non-linearities that likely characterise action models. The capabilities of this enhanced framework and its applicability to the maintenance planning problem are presented via two applications. In a first illustrative example, the use of the NUT is demonstrated within the framework of the value iteration algorithm. Next, the proposed continuous-state framework is compared against a discrete-state formulation for implementation on a life cycle assessment problem. © 2015 Taylor & Francis
Walbridge S.,University of Waterloo |
Fernando D.,Environmental and Geomatic Engineering |
Adey B.T.,Environmental and Geomatic Engineering |
Raimbault J.,University of Waterloo
Proceedings, Annual Conference - Canadian Society for Civil Engineering | Year: 2013
In order for bridge managers to evaluate the consequences of adopting new fatigue retrofitting techniques and management strategies on the cost of maintaining their bridge infrastructure, simple predictive models are needed, which can be easily integrated with the analytical tools that are already being using to model other deterioration processes (e.g. corrosion, road surface wear). These models must be capable of predicting the effects of inspection and retrofitting events with a sufficient degree of accuracy to ensure that optimal management strategies are correctly identified. Considering the large number of fatigue-prone welds and structures that may be present in a road network, minimizing computational effort is also critical. In this paper, a simple Markov chain deterioration model, similar to those currently used in bridge management systems (BMSs) to model deterioration due to other processes, is used to determine critical cost ratios for selecting optimal fatigue management strategies for steel highway bridge welds, First, the model is briefly described. A study is then presented, wherein the long term costs associated with different management strategies are related to parameters such as the equivalent stress range, traffic volume, and intervention costs for a generic weld detail. The results of this study are used to establish critical cost ratio contour plots, which can be used for the selection of the optimal management strategy. A limited number of strategies are investigated, in order to demonstrate an application of the presented methodology. They are composed of different intervention types, including: inspection, repair, replacement, and the use of post-weld 'peening' treatments. Copyright © (2013) by the Canadian Society for Civil Engineering.
Bainbridge J.W.B.,University College London |
Mehat M.S.,University College London |
Sundaram V.,University College London |
Robbie S.J.,University College London |
And 30 more authors.
New England Journal of Medicine | Year: 2015
BACKGROUND: Mutations in RPE65 cause Leber's congenital amaurosis, a progressive retinal degenerative disease that severely impairs sight in children. Gene therapy can result in modest improvements in night vision, but knowledge of its efficacy in humans is limited. METHODS: We performed a phase 1-2 open-label trial involving 12 participants to evaluate the safety and efficacy of gene therapy with a recombinant adeno-associated virus 2/2 (rAAV2/2) vector carrying the RPE65 complementary DNA, and measured visual function over the course of 3 years. Four participants were administered a lower dose of the vector, and 8 were administered a higher dose. In a parallel study in dogs, we investigated the relationship among vector dose, visual function, and electroretinography (ERG) findings. RESULTS: Improvements in retinal sensitivity were evident, to varying extents, in six participants for up to 3 years, peaking at 6 to 12 months after treatment and then declining. No associated improvement in retinal function was detected by means of ERG. Three participants had intraocular inflammation, and two had clinically significant deterioration of visual acuity. The reduction in central retinal thickness varied among participants. In dogs, RPE65 gene therapy with the same vector at lower doses improved vision-guided behavior, but only higher doses resulted in improvements in retinal function that were detectable with the use of ERG. CONCLUSIONS: Gene therapy with rAAV2/2 RPE65 vector improved retinal sensitivity, albeit modestly and temporarily. Comparison with the results obtained in the dog model indicates that there is a species difference in the amount of RPE65 required to drive the visual cycle and that the demand for RPE65 in affected persons was not met to the extent required for a durable, robust effect. (Funded by the National Institute for Health Research and others; ClinicalTrials.gov number, NCT00643747.) Copyright © 2015 Massachusetts Medical Society.