Numerical simulation of plasmonic effects in amorphous silicon induced by embedded aluminium nanoparticles

This work reports a theoretical study aimed to identify the plasmonic resonance condition for a system formed by metallic nanoparticles embedded in an a-Si: H matrix. The study is based on a Tauc-Lorentz model for the electrical permittivity of a-Si: H and a Drude model for the metallic nanoparticles. It is calculated the The polarizability of an sphere and ellipsoidal shaped metal nanoparticles with radius of 20 nm. We also performed FDTD simulations of light propagation inside this structure reporting a comparison among the effects caused by a single nanoparticles of Aluminium, Silver and, as a comparison, an ideally perfectly conductor. The simulation results shows that is possible to obtain a plasmonic resonance in the red part of the spectrum (600-700 nm) when 20-30 nm radius Aluminium ellipsoids are embedded into a-Si: H.

An economical model for dumping by dumping in a Cournot model

We consider an international trade economical model where two firms of different countries compete in quantities and can use three different strategies: (i) repeated collusion, (ii) deviation from the foreigner firm followed by punishment by the home country and then followed by repeated Cournot, or (iii) repeated deviation followed by punishment. In some cases (ii) and (iii) can be interpreted as dumping.We compute the profits of both firms for each strategy and we characterize the economical parameters where each strategy is adopted by the firms.

Evolutionary branching in deme-structured populations.

Adaptive dynamics shows that a continuous trait under frequency dependent selection may first converge to a singular point followed by spontaneous transition from a unimodal trait distribution into a bimodal one, which is called "evolutionary branching". Here, we study evolutionary branching in a deme-structured population by constructing a quantitative genetic model for the trait variance dynamics, which allows us to obtain an analytic condition for evolutionary branching. This is first shown to agree with previous conditions for branching expressed in terms of relatedness between interacting individuals within demes and obtained from mutant-resident systems. We then show this branching condition can be markedly simplified when the evolving trait affect fecundity and/or survival, as opposed to affecting population structure, which would occur in the case of the evolution of dispersal. As an application of our model, we evaluate the threshold migration rate below which evolutionary branching cannot occur in a pairwise interaction game. This agrees very well with the individual-based simulation results.

'Heures' a bio-economic model for Mediterranean fisheries, towards the evaluation of management strategies

The bio-economic model "Heures" is a first attempt to develop a simulation procedure to understand the Northwestern Mediterranean fisheries, to evaluate management strategies and to analyze the feasibility of implementing an adaptative management. The model is built on the interaction among three boxes simulating the dynamics of each of the basic actors of a fishery: the stock, the market and the fishermen. A fourth actor, the manager, imposes or modifies the rules, or, in terms of the model, modifies some particular parameters. Thus, the model allows us to simulate and evaluate the mid-term biologic and economic effects of particular management measures. The bio-economic nature of the model is given by the interaction among the three boxes, by the market simulation and, particularly, by the fishermen behaviour. This last element confers to the model its Mediterranean"selfregulated" character. The fishermen allocate their investments to maximize fishing mortality but, having a legal effort limit, they invest in maintenance and technology in order to increase the catchability, which, as a consequence. will be function of the invested capital.

CSP-A Model for In Vivo Presentation of Plasmodium berghei Sporozoite Antigens by Hepatocytes.

One target of protective immunity against the Plasmodium liver stage in BALB/c mice is represented by the circumsporozoite protein (CSP), and mainly involves its recognition by IFN-γ producing specific CD8+T-cells. In a previous in vitro study we showed that primary hepatocytes from BALB/c mice process Plasmodium berghei (Pb) CSP (PbCSP) and present CSP-derived peptides to specific H-2k(d) restricted CD8+T-cells with subsequent killing of the presenting cells. We now extend these observations to an in vivo infection model in which infected hepatocytes and antigen specific T-cell clones are transferred into recipient mice inducing protection from sporozoite (SPZ) challenge. In addition, using a similar protocol, we suggest the capacity of hepatocytes in priming of naïve T-cells to provide protection, as further confirmed by induction of protection after depletion of cross-presenting dendritic cells (DCs) by cytochrome c (cyt c) treatment or using traversal deficient parasites. Our results clearly show that hepatocytes present Plasmodium CSP to specific-primed CD8+T-cells, and could also prime naïve T-cells, leading to protection from infection. These results could contribute to a better understanding of liver stage immune response and design of malaria vaccines.

E-tailer business model creation: an information technology perspective

This research analyzes e-tailer business model formulation and the role of information technology in enabling value creation from the point of view of an e-tailer. The thesis explains the value creation dynamics and the components of an e-tailer business model and further illustrates how information technology enables value creation throughout the different components of e-tailer business models. The theoretical part of the thesis describes the sources of value creation in virtual markets through evaluating the explanatory value of traditional strategic management theories. The theoretical part advances to present an integrated model of the value creation mechanisms in the virtual markets and further describes the components of an e-tailer business model. The role of information technology in e-tailer business models are represented by illustrating how it is able to add value throughout the activities and processes of the e-tailer business model. The empirical descriptive qualitative single-case research focuses on demonstrating how a global retailer of consumer goods operates the different components in its business model. The findings indicate that information technology plays a considerable role in all the components of an e-tailer business model and should not be treated solely as a supporting business function, but rather as one of the most valuable assets in enabling successful e-tailing operations.

A Business continuity management maturity model : the search for an ISO 22301 Compliant BCM Maturity model

BCM (business continuity Management) is a holistic management process aiming at ensuring business continuity and building organizational resilience. Maturity models offer organizations a tool for evaluating their current maturity in a certain process. In the recent years BCM has been subject to international ISO standardization, while the interest of organizations to bechmark their state of BCM agains standards and the use of maturity models for these asessments has increased. However, although new standards have been introduced, very little attention has been paid to reviewing the existing BCM maturity models in research - especially in the light of the new ISO 22301 standard for BCM. In this thesis the existing BCM maturily models are carefully evaluated to determine whetherthey could be improved. In order to accomplish this, the compliance of the existing models to the ISO 22301 standard is measured and a framework for assessing a maturitymodel´s quality is defined. After carefully evaluating the existing frameworks for maturity model development and evaluation, an approach suggested by Becker et al. (2009) was chosen as the basis for the research. An additionto the procedural model a set of seven research guidelines proposed by the same authors was applied, drawing on the design-science research guidelines as suggested by Hevner et al. (2004). Furthermore, the existing models´ form and function was evaluated to address their usability. Based on the evaluation of the existing BCM maturity models, the existing models were found to have shortcomings in each dimension of the evaluation. Utilizing the best of the existing models, a draft version for an enhanced model was developed. This draft model was then iteratively developed by conducting six semi-structured interviews with BCM professionals in finland with the aim of validating and improving it. As a Result, a final version of the enhanced BCM maturity model was developed, conforming to the seven key clauses in the ISO 22301 standard and the maturity model development guidelines suggested by Becker et al. (2009).

Dynamics and Thermodynamics of the Arabian Sea Warm Pool

The present study examines the importance of low saline waters and resulting barrier layer in the dynamics of the ASWP using observational data.The oceanic general circulation models (OGCM) are very useful for exploring the processes responsible for the ASWP and their variability. The circulation and thermohaline structure stimulated by an OGCM changes a lot when the resolution is increased from mesoscale to macro scale. For a reasonable simulation of the ASWP, we must include the mesoscale turbulence in numerical models. Especially the SEAS is an eddy prominent region with a horizontal dimension of 100 to 500 km and vertical extent of hundred meters. These eddies may have an important role on the evolution of ASWP, which has not been explored so far.Most of the earlier studies in the SEAS showed that the heat buildup in the mixed layer during the pre-monsoon (March-May) is primarily driven by the surface heat flux through the ocean-atmosphere interface, while the 3-dimensional heat budget of the ML physical processes that are responsible for the formation of the ASWP are unknown. With this background the present thesis also examines the relative importance of mixed layer processes that lead to the formation of warm pool in the SEAS.

Climate response to basin-scale warming and cooling of the North Atlantic Ocean

Using experiments with an atmospheric general circulation model, the climate impacts of a basin-scale warming or cooling of the North Atlantic Ocean are investigated. Multidecadal fluctuations with this pattern were observed during the twentieth century, and similar variations--but with larger amplitude--are believed to have occurred in the more distant past. It is found that in all seasons the response to warming the North Atlantic is strongest, in the sense of highest signal-to-noise ratio, in the Tropics. However there is a large seasonal cycle in the climate impacts. The strongest response is found in boreal summer and is associated with suppressed precipitation and elevated temperatures over the lower-latitude parts of North and South America. In August­-September-­October there is a significant reduction in the vertical shear in the main development region for Atlantic hurricanes. In winter and spring, temperature anomalies over land in the extratropics are governed by dynamical changes in circulation rather than simply reflecting a thermodynamic response to the warming or cooling of the ocean. The tropical climate response is primarily forced by the tropical SST anomalies, and the major features are in line with simple models of the tropical circulation response to diabatic heating anomalies. The extratropical climate response is influenced both by tropical and higher-latitude SST anomalies and exhibits nonlinear sensitivity to the sign of the SST forcing. Comparisons with multidecadal changes in sea level pressure observed in the twentieth century support the conclusion that the impact of North Atlantic SST change is most important in summer, but also suggest a significant influence in lower latitudes in autumn and winter. Significant climate impacts are not restricted to the Atlantic basin, implying that the Atlantic Ocean could be an important driver of global decadal variability. The strongest remote impacts are found to occur in the tropical Pacific region in June­-August and September­-November. Surface anomalies in this region have the potential to excite coupled ocean­atmosphere feedbacks, which are likely to play an important role in shaping the ultimate climate response.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

Impact of Resolution on the Tropical Pacific Circulation in a Matrix of Coupled Models

Results are presented from a matrix of coupled model integrations, using atmosphere resolutions of 135 and 90 km, and ocean resolutions of 1° and 1/3°, to study the impact of resolution on simulated climate. The mean state of the tropical Pacific is found to be improved in the models with a higher ocean resolution. Such an improved mean state arises from the development of tropical instability waves, which are poorly resolved at low resolution; these waves reduce the equatorial cold tongue bias. The improved ocean state also allows for a better simulation of the atmospheric Walker circulation. Several sensitivity studies have been performed to further understand the processes involved in the different component models. Significantly decreasing the horizontal momentum dissipation in the coupled model with the lower-resolution ocean has benefits for the mean tropical Pacific climate, but decreases model stability. Increasing the momentum dissipation in the coupled model with the higher-resolution ocean degrades the simulation toward that of the lower-resolution ocean. These results suggest that enhanced ocean model resolution can have important benefits for the climatology of both the atmosphere and ocean components of the coupled model, and that some of these benefits may be achievable at lower ocean resolution, if the model formulation allows.

U.K. HiGEM: The New U.K. High-Resolution Global Environment Model—Model Description and Basic Evaluation

This article describes the development and evaluation of the U.K.’s new High-Resolution Global Environmental Model (HiGEM), which is based on the latest climate configuration of the Met Office Unified Model, known as the Hadley Centre Global Environmental Model, version 1 (HadGEM1). In HiGEM, the horizontal resolution has been increased to 0.83° latitude × 1.25° longitude for the atmosphere, and 1/3° × 1/3° globally for the ocean. Multidecadal integrations of HiGEM, and the lower-resolution HadGEM, are used to explore the impact of resolution on the fidelity of climate simulations. Generally, SST errors are reduced in HiGEM. Cold SST errors associated with the path of the North Atlantic drift improve, and warm SST errors are reduced in upwelling stratocumulus regions where the simulation of low-level cloud is better at higher resolution. The ocean model in HiGEM allows ocean eddies to be partially resolved, which dramatically improves the representation of sea surface height variability. In the Southern Ocean, most of the heat transports in HiGEM is achieved by resolved eddy motions, which replaces the parameterized eddy heat transport in the lower-resolution model. HiGEM is also able to more realistically simulate small-scale features in the wind stress curl around islands and oceanic SST fronts, which may have implications for oceanic upwelling and ocean biology. Higher resolution in both the atmosphere and the ocean allows coupling to occur on small spatial scales. In particular, the small-scale interaction recently seen in satellite imagery between the atmosphere and tropical instability waves in the tropical Pacific Ocean is realistically captured in HiGEM. Tropical instability waves play a role in improving the simulation of the mean state of the tropical Pacific, which has important implications for climate variability. In particular, all aspects of the simulation of ENSO (spatial patterns, the time scales at which ENSO occurs, and global teleconnections) are much improved in HiGEM.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Use of a crop model ensemble to quantify CO2 stimulation of water-stressed and well-watered crops

Increased atmospheric concentrations of carbon dioxide (CO2) will benefit the yield of most crops. Two free air CO2 enrichment (FACE) meta-analyses have shown increases in yield of between 0 and 73% for C3 crops. Despite this large range, few crop modelling studies quantify the uncertainty inherent in the parameterisation of crop growth and development. We present a novel perturbed-parameter method of crop model simulation, which uses some constraints from observations, that does this. The model used is the groundnut (i.e. peanut; Arachis hypogaea L.) version of the general large-area model for annual crops (GLAM). The conclusions are of relevance to C3 crops in general. The increases in yield simulated by GLAM for doubled CO2 were between 16 and 62%. The difference in mean percentage increase between well-watered and water-stressed simulations was 6.8. These results were compared to FACE and controlled environment studies, and to sensitivity tests on two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., Bell, M.J., 1995. A peanut simulation model. I. Model development and testing. Agron. J. 87, 1085-1093]. The relationship between CO2 and water stress in the experiments and in the models was examined. From a physiological perspective, water-stressed crops are expected to show greater CO2 stimulation than well-watered crops. This expectation has been cited in literature. However, this result is not seen consistently in either the FACE studies or in the crop models. In contrast, leaf-level models of assimilation do consistently show this result. An analysis of the evidence from these models and from the data suggests that scale (canopy versus leaf), model calibration, and model complexity are factors in determining the sign and magnitude of the interaction between CO2 and water stress. We conclude from our study that the statement that 'water-stressed crops show greater CO2 stimulation than well-watered crops' cannot be held to be universally true. We also conclude, preliminarily, that the relationship between water stress and assimilation varies with scale. Accordingly, we provide some suggestions on how studies of a similar nature, using crop models of a range of complexity, could contribute further to understanding the roles of model calibration, model complexity and scale. (C) 2008 Elsevier B.V. All rights reserved.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.