Action learning as an enabler for successful technology transfer with construction SMEs

There is an increasing demand for construction companies to adopt and use new technologies. At the same time universities are increasingly being called upon to assist with ‘technology transfer’ through positive engagement with industry. However, there is little literature investigating technology transfer from the perspective of small construction companies which make up the overwhelming majority of firms in the sector. This paper contributes to this developing area by providing a literature review of technology transfer and proposing a holistic system required for success. Building upon this review it assesses the potential use of action learning as a means of providing this holistic solution and, in so doing, promoting technology transfer and improving the links between higher education institutions (HEIs) and the construction industry. The assessment is made through a literature review of action learning in construction and an analysis of results from the national Construction Knowledge Exchange (CKE) initiative which uses an action learning methodology to assist HEIs in supporting local construction small and medium-sized enterprises (SMEs). The initial results show that this innovative approach, has been successful in creating synergies between academic and business worlds, helping HEIs to communicate more effectively with businesses and vice versa. However, the results indicate that innovations which small construction companies tend to more successfully adopt are those which can contribute to the business in a quick, tangible fashion, and which can be dovetailed into existing rganisational capabilities. This is found to be in marked contrast to the relevant literature which depict large companies operating in more complex networks, drawing upon them for new tacit and explicit technologies which support more long term, formal technology strategies, and which often complement some form of specialised internal research and development capability. The implication for policy is that any technology transfer initiatives need to appreciate and actively manage the different motivations and capabilities of small and large construction companies to absorb and use new technology

A system for gaze-contingent image analysis and multi-sensorial image display

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A physically based parameterization of gravity drainage for sea-ice modeling

We incorporate a physically derived parameterization of gravity drainage, in terms of a convective upwelling velocity, into a one-dimensional, thermodynamic sea- ice model of the kind currently used in coupled climate models. Our parameterization uses a local Rayleigh number to represent the important feedback between ice salinity, porosity, permeability and desalination rate. It allows us to determine salt fluxes from sea ice and the corresponding evolution of the bulk salinity of the ice, in contrast to older, established models that prescribe the ice salinity. This improves the predictive power of climate models in terms of buoyancy fluxes to the polar oceans, and also the thermal properties of sea ice, which depend on its salinity. We analyze the behaviour of exist- ing fixed-salinity models, elucidate the physics by which changing salinity affects ice growth and compare against our dynamic-salinity model, both in terms of laboratory experiments and also deep-ocean calculations. These comparisons explain why the direct effect of ice salinity on growth is relatively small (though not always negligible, and sometimes dif- ferent from previous studies), and also highlight substantial differences in the qualita- tive pattern and quantitative magnitude of salt fluxes into the polar oceans. Our study is particularly relevant to growing first-year ice, when gravity drainage is the dominant mechanism by which ice desalinates. We expect that our dynamic model, which respects the underlying physics of brine drainage, should be more robust to changes in polar cli- mate and more responsive to rapid changes in oceanic and atmospheric forcing.This is the accepted manuscript. The final version is available from Wiley/American Geophysical Union at http://onlinelibrary.wiley.com/doi/10.1002/2013JC009296/abstract

Historical trends and variability in heat waves in the United Kingdom

This is the final version of the article. Available from MDPI via the DOI in this record.Increases in numbers and lengths of heat waves have previously been identified in global temperature records, including locations within Europe. However, studies of changes in UK heat wave characteristics are limited. Historic daily maximum temperatures from 29 weather stations with records exceeding 85 years in length across the country were examined. Heat waves were defined as periods with unusually high temperatures for each station, even if the temperatures would not be considered warm in an absolute sense. Positive trends in numbers and lengths of heat waves were identified at some stations. However, for some stations in the south east of England, lengths of very long heat waves (over 10 days) had declined since the 1970s, whereas the lengths of shorter heat waves had increased slightly. Considerable multidecadal variability in heat wave numbers and lengths was apparent at all stations. Logistic regression, using a subset of eight stations with records beginning in the nineteenth century, suggested an association between the Atlantic Multidecadal Oscillation and the variability in heat wave numbers and lengths, with the summertime North Atlantic Oscillation playing a smaller role. The results were robust against different temperature thresholds.This work was funded under the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in environmental change and health, led by the London School of Hygiene and Tropical Medicine in partnership with Public Health England (PHE), the University of Exeter and the Met Office

A patient's experience of a new post-operative patient-controlled analgesic technique

A patient underwent major spinal surgery, twice within a 3 week period. On the first occasion his post-operative pain was managed by conventional morphine patient-controlled analgesia (PCA). After the second procedure his pain was managed by a patient-controlled computer-assisted titration of alfentanil. This provided the opportunity to compare the efficacy of these two drug regimens in the same subject. The results showed comparable quality of analgesia and sedation and similar effects on respiration. However, the patient expressed a preference for morphine PCA.published_or_final_versio

Exclusive J/φ and γ photoproduction and the low x gluon

We discuss the potential to constrain the small-x PDFs using the exclusive production of heavy vector mesons. The calculation of J/φ and γ photoproduction at NLO in collinear factorisation is described. The different behaviour of the NLO corrections for J/φ and → is highlighted and we outline what might be expected from the inclusion of these processes in a PDF fit

Quasi-diffusion magnetic resonance imaging (QDI): A fast, high b-value diffusion imaging technique.

To enable application of non-Gaussian diffusion magnetic resonance imaging (dMRI) techniques in large-scale clinical trials and facilitate translation to clinical practice there is a requirement for fast, high contrast, techniques that are sensitive to changes in tissue structure which provide diagnostic signatures at the early stages of disease. Here we describe a new way to compress the acquisition of multi-shell b-value diffusion data, Quasi-Diffusion MRI (QDI), which provides a probe of subvoxel tissue complexity using short acquisition times (1-4 min). We also describe a coherent framework for multi-directional diffusion gradient acquisition and data processing that allows computation of rotationally invariant quasi-diffusion tensor imaging (QDTI) maps. QDI is a quantitative technique that is based on a special case of the Continuous Time Random Walk model of diffusion dynamics and assumes the presence of non-Gaussian diffusion properties within tissue microstructure. QDI parameterises the diffusion signal attenuation according to the rate of decay (i.e. diffusion coefficient, D in mm2 s-1) and the shape of the power law tail (i.e. the fractional exponent, α). QDI provides analogous tissue contrast to Diffusional Kurtosis Imaging (DKI) by calculation of normalised entropy of the parameterised diffusion signal decay curve, Hn, but does so without the limitations of a maximum b-value. We show that QDI generates images with superior tissue contrast to conventional diffusion imaging within clinically acceptable acquisition times of between 84 and 228 s. We show that QDI provides clinically meaningful images in cerebral small vessel disease and brain tumour case studies. Our initial findings suggest that QDI may be added to routine conventional dMRI acquisitions allowing simple application in clinical trials and translation to the clinical arena