Labour pain: the hidden influences of anxiety and social deprivation

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Tracer Studies of Catalysed Chemical Reactions

The reaction of cyclopropane with hydrogen has been studied over evaporated and pumice-supported nickel catalysts. It has been found that reproducibility of reaction behaviour on a particular catalyst is controlled by a number of factors. In cases where reproducibility has been obtained poisoning of the hydrogenation reaction by mercury has been studied using a radiotracer technique. The results of this study indicate that, when allowance has been made for differences in film weight, a particular amount of mercury does not produce a comparable effect on different films, although, when only relative effects are considered, reproducibility between films is obtained. A comparison of the poisoning curve so derived with those in the literature confirms that on evaporated nickel films the mechanism of the poisoning process is the prevention by mercury of hydrogen adsorption; a process necessary for hydrogenation of cyclopropane

Using earth observation satellites to explore forest dynamics across large areas

A third of the land on earth is covered by forests. Forests provide valuable resources and essential ecosystem services, including filtering air and water, harbouring biodiversity and managing the carbon cycle. Regular monitoring and reporting across various indicators is necessary to manage forests sustainably. Due to the vastness of forests, satellite Earth observation is one of the most practical and cost-effective ways to monitor forests. The regular and consistent measurements provided from space enable time series analysis, which can reveal trends over time. The temporal, spatial and radiometric depth of the Landsat archive, which extends back to 1972 in some cases, is one of the most useful resources for monitoring forest dynamics across large areas. Analysing forest disturbance and recovery trends using Landsat has recently become widespread, particularly since the opening of the image archive in 2008. However, deriving useful information from the data is challenging on many fronts, including overcoming cloud-cover, differentiating true changes from noise and relating spectral measurements to meaningful outputs. In addition, large data volumes create hurdles for processing and storage. This study presents new techniques for exploiting the Landsat archive in relation to monitoring and measuring forest disturbance and recovery across large areas. Landsat data were processed through a series of steps, analysed in time series, and combined with other data sources to produce mapped outputs and statistical summaries, which can be interpreted by non-experts. The spatial extent of the analysis expands across multiple scales - from local and regional to global (temperate and boreal forests). Firstly, eight Landsat spectral indices were assessed to determine their sensitivity to forest disturbance (caused by wildfire) and recovery in southeast Australian forests. Results indicated that indices making use of the shortwave infrared wavelengths were more reliable indicators of forest disturbance and recovery than indices using only the red and near-infrared wavelengths. Following this exploratory analysis, three indices and two change detection algorithms were evaluated in terms of their ability to detect forest disturbance. Results showed that the LandTrendr algorithm with the Normalised Burn Ratio (NBR) was the most accurate single algorithm/index combination (overall error 21%). However, results were greatly improved by using an ensemble approach. A Random Forests model combining several Landsat-derived metrics with multiple indices, trained with human interpreted reference data, had an overall error of 7%. A notable finding was that priming the training data with confusing cases (commission errors from the change detection algorithms) led to increased accuracy. One Random Forests model was used to create annual forest disturbance maps (1989-2017) across the state of Victoria, Australia. These maps, in conjunction with each pixel's temporal trajectory, were used to extract metrics for spectral disturbance magnitude and recovery length across 2 million ha of burned forest in southeast Australia. The association between disturbance magnitude and forest recovery length, as measured spectrally, was then explored. A novel patch-based technique was used to isolate the disturbance-recovery relationship from confounding factors such as climate, elevation and soil type. The results showed statistically significant differences across bioregions and forest types. The patch-based method demonstrated how Landsat time series can be harnessed to explore ecological changes. The methods developed above were then employed over a much larger area, to investigate trends in fire disturbance and forest recovery in temperate and boreal forests worldwide. This work used both MODIS and Landsat data, through the Google Earth Engine platform, to look at trends in burned area, fire severity and forest recovery across almost 2 billion ha of forests, over the last 18 years. Burned area results showed significant increasing trends in two cases: coniferous forests in Canada and Mediterranean forests in Chile. A significant decreasing trend was found in temperate mixed forests in China. An assessment of fire severity, as measured by Landsat spectral change, highlighted possible trends in a few cases; most notably, the Russian taiga, where increasing severity was observed. An analysis of forest recovery, based on Landsat time series, indicated recovery times were accelerating in many regions. However, given the relatively short time-period analysed, these results should be interpreted with caution. The results presented in this thesis demonstrate the power of Earth observation satellites in monitoring forests at the landscape scale. Although forests are complex systems that are influenced by a myriad of factors, the regular and consistent measurements provided by satellites can be analysed in time series to provide inter-comparable results across large areas. This can broaden our understanding of the dynamic nature of forests, and in doing so, help progress towards their sustainable management

Convergence of resonances on thin branched quantum wave guides

We prove an abstract criterion stating resolvent convergence in the case of operators acting in different Hilbert spaces. This result is then applied to the case of Laplacians on a family X_\eps of branched quantum waveguides. Combining it with an exterior complex scaling we show, in particular, that the resonances on X_\eps approximate those of the Laplacian with ``free'' boundary conditions on $X_0$, the skeleton graph of X_\eps.Comment: 48 pages, 1 figur

Solving the Coulomb scattering problem using the complex scaling method

Based on the work of Nuttall and Cohen [Phys. Rev. {\bf 188} (1969) 1542] and Resigno et al{} [Phys. Rev. A {\bf 55} (1997) 4253] we present a rigorous formalism for solving the scattering problem for long-range interactions without using exact asymptotic boundary conditions. The long-range interaction may contain both Coulomb and short-range potentials. The exterior complex scaling method, applied to a specially constructed inhomogeneous Schr\"odinger equation, transforms the scattering problem into a boundary problem with zero boundary conditions. The local and integral representations for the scattering amplitudes have been derived. The formalism is illustrated with numerical examples.Comment: 3 pages, 3 figure

Twisted duality of the CAR-Algebra

We give a complete proof of the twisted duality property M(q)'= Z M(q^\perp) Z* of the (self-dual) CAR-Algebra in any Fock representation. The proof is based on the natural Halmos decomposition of the (reference) Hilbert space when two suitable closed subspaces have been distinguished. We use modular theory and techniques developed by Kato concerning pairs of projections in some essential steps of the proof. As a byproduct of the proof we obtain an explicit and simple formula for the graph of the modular operator. This formula can be also applied to fermionic free nets, hence giving a formula of the modular operator for any double cone.Comment: 32 pages, Latex2e, to appear in Journal of Mathematical Physic

Intra- and inter-firm dynamics in combinatorial knowledge bases

[EN] Research on innovation has often concentrated on a narrow set of sectors and activities, and on the experiences of the most advanced regions in the world. However, innovation, when defined in a broad sense, incorporates a variety of processes and outputs that cut across organisational, sectoral, territorial and knowledge boundaries. This paper seeks to make a contribution to this literature by focusing on the experiences of less developed regions, and by examining how different knowledge bases contribute to technological upgrading and higher added value for firms. It argues that in regions where access to advanced knowledge and technology is restricted, or where firms do not have the absorptive capacity to access, absorb and exploit such knowledge, combining existing knowledge in innovative ways may be the best strategy for firms to become more innovative and competitive. It also argues that this combination can happen through vertical integration within the firm, or by the creation and maintenance of inter-firm mechanisms that stimulate knowledge dissemination. These themes are discussed by drawing on the evolution of the wine industry in three Portuguese regions. These regions have all experienced different trajectories, in terms of the renewal of their wine industry, and it is argued that this is in part the result of endogenous regional characteristics.This work was supported by an Early Career Grant by the Regional Studies Association and by the German Research Foundation/European Science Foundation [grant number 10-ECRP-007].Marques, P. (2019). Intra- and inter-firm dynamics in combinatorial knowledge bases. European Urban and Regional Studies. 26(2):186-204. https://doi.org/10.1177/0969776418779116S186204262Asheim, B. T., Boschma, R., & Cooke, P. (2011). 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Economic Geography, 89(3), 261-284. doi:10.1111/ecge.12009Helfat, C. E. (2015). Vertical firm structure and industry evolution. Industrial and Corporate Change, 24(4), 803-818. doi:10.1093/icc/dtv027Malerba, F., Nelson, R., Orsenigo, L., & Winter, S. (2008). Vertical integration and disintegration of computer firms: a history-friendly model of the coevolution of the computer and semiconductor industries. Industrial and Corporate Change, 17(2), 197-231. doi:10.1093/icc/dtn001Manniche, J. (2012). Combinatorial Knowledge Dynamics: On the Usefulness of the Differentiated Knowledge Bases Model. European Planning Studies, 20(11), 1823-1841. doi:10.1080/09654313.2012.723423Manniche, J., Moodysson, J., & Testa, S. (2016). Combinatorial Knowledge Bases: An Integrative and Dynamic Approach to Innovation Studies. Economic Geography, 93(5), 480-499. doi:10.1080/00130095.2016.1205948Marques, P. (2017). From toys to automobiles: foreign investment, firm heterogeneity and intermediaries in a Portuguese industry. European Planning Studies, 25(8), 1375-1393. doi:10.1080/09654313.2017.1303822Marques, P. (2017). Human capital and university–business interactions: an example from the wine industry. Regional Studies, Regional Science, 4(1), 154-160. doi:10.1080/21681376.2017.1341818Martin, R., & Moodysson, J. (2011). Comparing knowledge bases: on the geography and organization of knowledge sourcing in the regional innovation system of Scania, Sweden. European Urban and Regional Studies, 20(2), 170-187. doi:10.1177/0969776411427326Martin, R., & Sunley, P. (2003). Deconstructing clusters: chaotic concept or policy panacea? Journal of Economic Geography, 3(1), 5-35. doi:10.1093/jeg/3.1.5Moulaert, F., & Sekia, F. (2003). Territorial Innovation Models: A Critical Survey. Regional Studies, 37(3), 289-302. doi:10.1080/0034340032000065442Pina, K., & Tether, B. S. (2016). 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