A Network model of systemic risk : identifying the sources of dependence across institutions

We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.

Teaching art and design : addressing issues and identifying directions.

Promueve el desarrollo profesional de los profesores especialistas en arte y diseño, tanto de los que se preparan para enseñar, como de los recién titulados o los más experimentados. Así, este recurso surge como respuesta a los debates sobre dos iniciativas de gran alcance promovidas por el gobierno: la introducción del National Currículo y la reforma de la educación y formación del profesorado. Estas medidas llevaron a los profesores de arte y diseño a aplicar, de forma rápida, el plan de estudios para Arte y a prepararse para su nuevo papel en la escuela, a través de cursos iniciales de formación. También, aborda el libro los problemas actuales en la enseñanza del arte y el diseño, e identifica las direcciones que han de seguir el desarrollo de sus futuros programas de estudios, con especial referencia a la fase de secundaria.

Unlocking learning and teaching with ICT : identifying and overcoming barriers.

En primer lugar, identifica las barreras que aún existen para la integración con éxito de las tecnologías de la información y la comunicación (TIC) en las escuelas, así como propone métodos y estrategias para su superación. También, muestra cómo la utilización de estas tecnologías ayuda a los niños a aprender y a mejorar sus capacidades.

Identifying stakeholders in a Portuguese university : a case study

Resumen basado en el de la publicación.

Trace elements biogeochemistry in high mountain lake catchments: identifying anthropogenic versus natural components from the atmospheric contamination legacy in remote natural areas

Human activities have been interfering with the natural biogeochemical cycles of trace elements since the ancient civilizations. Although they are inaccessible and remote, high mountain lake catchments are irrefutably trace-element contaminated by anthropogenic emissions, which can travel by long-range atmospheric transport before they are deposited. This has been revealed by several natural archives. High mountain lake catchments are thus excellent sentinels of long-range contamination. Continuous accumulation can lead to a build up of potentially toxic trace elements in these remote, or relatively remote, ecosystems. The thesis focuses on the biogeochemistry of a suite of trace elements of environmental concern (Ni, Cu, Zn, As, Se, Cd and Pb) in Pyrenean lake catchments, with special emphasis on discerning the “natural” components from the “anthropogenic” contributions. Five other metallic elements (Al, Fe, Ti, Mn and Zr) have also been studied to trace natural fluxes and biogeochemical processes within the lake catchment systems.

Convectively coupled equatorial waves: A new methodology for identifying wave structures in observational data

Convectively coupled equatorial waves are fundamental components of the interaction between the physics and dynamics of the tropical atmosphere. A new methodology, which isolates individual equatorial wave modes, has been developed and applied to observational data. The methodology assumes that the horizontal structures given by equatorial wave theory can be used to project upper- and lower-tropospheric data onto equatorial wave modes. The dynamical fields are first separated into eastward- and westward-moving components with a specified domain of frequency–zonal wavenumber. Each of the components for each field is then projected onto the different equatorial modes using the y structures of these modes given by the theory. The latitudinal scale yo of the modes is predetermined by data to fit the equatorial trapping in a suitable latitude belt y = ±Y. The extent to which the different dynamical fields are consistent with one another in their depiction of each equatorial wave structure determines the confidence in the reality of that structure. Comparison of the analyzed modes with the eastward- and westward-moving components in the convection field enables the identification of the dynamical structure and nature of convectively coupled equatorial waves. In a case study, the methodology is applied to two independent data sources, ECMWF Reanalysis and satellite-observed window brightness temperature (Tb) data for the summer of 1992. Various convectively coupled equatorial Kelvin, mixed Rossby–gravity, and Rossby waves have been detected. The results indicate a robust consistency between the two independent data sources. Different vertical structures for different wave modes and a significant Doppler shifting effect of the background zonal winds on wave structures are found and discussed. It is found that in addition to low-level convergence, anomalous fluxes induced by strong equatorial zonal winds associated with equatorial waves are important for inducing equatorial convection. There is evidence that equatorial convection associated with Rossby waves leads to a change in structure involving a horizontal structure similar to that of a Kelvin wave moving westward with it. The vertical structure may also be radically changed. The analysis method should make a very powerful diagnostic tool for investigating convectively coupled equatorial waves and the interaction of equatorial dynamics and physics in the real atmosphere. The results from application of the analysis method for a reanalysis dataset should provide a benchmark against which model studies can be compared.

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

Identifying the environments of construction projects

A systematic technique for identifying the environments of construction projects is described. It provides a method for isolating the major variables surrounding construction projects, and is briefly applied to the industries of Britain and Jamaica to illustrate its application. From this, it is inferred that the environment of a Jamaican construction project in systems terms is broadly similar to the environment of a construction project in Britain.

Identifying appropriate construction procurement strategies

The origins of the various procurement methods in construction are considered, followed by a discussion of the circumstances for which each procurement system is best suited. The likely future development sin management-based methods are discussed in the context of current research, showing that co-ordination of trade and specialist contractors , more flexible contracting, constructive conflict management and a potential polarization of views about project management in the industry are likely.

Calibrating flood inundation models: identifying and addressing uncertainty in satellite observed flood extents

Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at the margins of the flood. Comparison between modelled and observed water surface elevations provides a new means for calibrating and validating flood inundation models, however the uncertainty in this observed data has yet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data. A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the River Dee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline are selected, and the water surface elevation recorded as the LiDAR DEM elevation at each point. With a planar water surface from the gauged upstream to downstream water elevations as an approximation, the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. The pattern of errors between the two show a roughly normal distribution, however when plotted against coordinates there is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errors to the slope gradient and aspect of the LiDAR DEM. A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertainty on the calibration of flood inundation models. Multiple simulations are run using different combinations of friction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used to quantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-test are selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice of optimum parameter set to uncertainty in the observed data. This work explores the observed data in detail and highlights possible causes of error. The identification of significant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotely sensed data emphasises the limitations of using this data in a deterministic manner within the calibration process. These limitations are addressed by developing a new probabilistic approach to using the observed data.

Enhanced aglycone production of fermented soybean products by Bacillus species

This study evaluated the effect of starter culture and fermentation period on the isoflavone content of protein-rich soybeans variety TG145. Initially, soybeans were washed, soaked in water for 16 h and autoclaved at 121°C for 40min. Three different bacterial starter cultures (~104 CFU/g) namely Bacillus subtilis BEST195, B. subtilis Asaichiban and B. subtilis TN51 were then added and the fermentation was allowed to proceed at 42°C for 24 h (natto-style) and 72 h (thua nao-style). The quantities of six major isoflavones (daidzin, genistin, glycitin, daidzein, genistein, and glycitein) were then determined in these fermented soybean products using reverse phase HPLC technique. Generally, our results clearly showed that the content of total isoflavones in the fermented products prepared by Bacillus starter cultures greatly increased ranging from 43 to 99% compared to that of the unfermented autoclaved soybeans. In addition, a dramatic increase of aglycones was also observed (> 400%) in the soybean products fermented by Bacillus subtilis strain TN51. This present study suggests a promising use of Bacillus starter cultures in improving isoflavone compounds especially the aglycones which would benefit for novel functional food development.