A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

Development of Collaborative Product Structure Management

The purpose of this thesis is to develop an environment or network that enables effective collaborative product structure management among stakeholders in each unit, throughout the entire product lifecycle and product data management. This thesis uses framework models as an approach to the problem. Framework model methods for development of collaborative product structure management are proposed in this study, there are three unique models depicted to support collaborative product structure management: organization model, process model and product model. In the organization model, the formation of product data management system (eDSTAT) key user network is specified. In the process model, development is based on the case company’s product development matrix. In the product model framework, product model management, product knowledge management and design knowledge management are defined as development tools and collaboration is based on web-based product structure management. Collaborative management is executed using all these approaches. A case study from an actual project at the case company is presented as an implementation; this is to verify the models’ applicability. A computer assisted design tool and the web-based product structure manager, have been used as tools of this collaboration with the support of the key user. The current PDM system, eDSTAT, is used as a piloting case for key user role. The result of this development is that the role of key user as a collaboration channel is defined and established. The key user is able to provide one on one support for the elevator projects. Also the management activities are improved through the application of process workflow by following criteria for each project milestone. The development shows effectiveness of product structure management in product lifecycle, improved production process by eliminating barriers (e.g. improvement of two-way communication) during design phase and production phase. The key user role is applicable on a global scale in the company.

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).

Innovation process development and business process integration - a multiple case study

The main objective of this study was to find out the bases for innovation model formulation in an existing organization based on cases. Innovation processes can be analyzed based on their needs and based on their emphasis on the business model development or R&D. The research was conducted in energy sector within one company by utilizing its projects as cases for the study. It is typical for the field of business that development is slow, although the case company has put emphasis on its innovation efforts. Analysis was done by identifying the cases’ needs and comparing them. The results were that because of the variances in the needs of the cases, the applicability of innovation process models varies. It was discovered that by dividing the process into two phases, a uniform model could be composed. This model would fulfill the needs of the cases and potential future projects as well.

Healthcare Information System Selection Model for Medical Clinics

The issue of selecting an appropriate healthcare information system is a very essential one. If implemented healthcare information system doesn’t fit particular healthcare institution, for example there are unnecessary functions; healthcare institution wastes its resources and its efficiency decreases. The purpose of this research is to develop a healthcare information system selection model to assist the decision-making process of choosing healthcare information system. Appropriate healthcare information system helps healthcare institutions to become more effective and efficient and keep up with the times. The research is based on comparison analysis of 50 healthcare information systems and 6 interviews with experts from St-Petersburg healthcare institutions that already have experience in healthcare information system utilization. 13 characteristics of healthcare information systems: 5 key and 7 additional features are identified and considered in the selection model development. Variables are used in the selection model in order to narrow the decision algorithm and to avoid duplication of brunches. The questions in the healthcare information systems selection model are designed to be easy-to-understand for common a decision-maker in healthcare institution without permanent establishment.

A description of the FAMOUS (version XDBUA) climate model and control run

FAMOUS is an ocean-atmosphere general circulation model of low resolution, capable of simulating approximately 120 years of model climate per wallclock day using current high performance computing facilities. It uses most of the same code as HadCM3, a widely used climate model of higher resolution and computational cost, and has been tuned to reproduce the same climate reasonably well. FAMOUS is useful for climate simulations where the computational cost makes the application of HadCM3 unfeasible, either because of the length of simulation or the size of the ensemble desired. We document a number of scientific and technical improvements to the original version of FAMOUS. These improvements include changes to the parameterisations of ozone and sea-ice which alleviate a significant cold bias from high northern latitudes and the upper troposphere, and the elimination of volume-averaged drifts in ocean tracers. A simple model of the marine carbon cycle has also been included. A particular goal of FAMOUS is to conduct millennial-scale paleoclimate simulations of Quaternary ice ages; to this end, a number of useful changes to the model infrastructure have been made.

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

Constraining a North Atlantic Ocean general circulation model with chlorofluorocarbon observations

Measurements of anthropogenic tracers such as chlorofluorocarbons and tritium must be quantitatively combined with ocean general circulation models as a component of systematic model development. The authors have developed and tested an inverse method, using a Green's function, to constrain general circulation models with transient tracer data. Using this method chlorofluorocarbon-11 and -12 (CFC-11 and -12) observations are combined with a North Atlantic configuration of the Miami Isopycnic Coordinate Ocean Model with 4/3 degrees resolution. Systematic differences can be seen between the observed CFC concentrations and prior CFC fields simulated by the model. These differences are reduced by the inversion, which determines the optimal gas transfer across the air-sea interface, accounting for uncertainties in the tracer observations. After including the effects of unresolved variability in the CFC fields, the model is found to be inconsistent with the observations because the model/data misfit slightly exceeds the error estimates. By excluding observations in waters ventilated north of the Greenland-Scotland ridge (sigma (0) < 27.82 kg m(-3); shallower than about 2000 m), the fit is improved, indicating that the Nordic overflows are poorly represented in the model. Some systematic differences in the model/data residuals remain and are related, in part, to excessively deep model ventilation near Rockall and deficient ventilation in the main thermocline of the eastern subtropical gyre. Nevertheless, there do not appear to be gross errors in the basin-scale model circulation. Analysis of the CFC inventory using the constrained model suggests that the North Atlantic Ocean shallower than about 2000 m was near 20% saturated in the mid-1990s. Overall, this basin is a sink to 22% of the total atmosphere-to-ocean CFC-11 flux-twice the global average value. The average water mass formation rates over the CFC transient are 7.0 and 6.0 Sv (Sv = 10(6) m(3) s(-1)) for subtropical mode water and subpolar mode water, respectively.

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.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Model inter-comparison between statistical and dynamic model assessments of the long-term stability of blanket peat in Great Britain (1940-2099)

We compared output from 3 dynamic process-based models (DMs: ECOSSE, MILLENNIA and the Durham Carbon Model) and 9 bioclimatic envelope models (BCEMs; including BBOG ensemble and PEATSTASH) ranging from simple threshold to semi-process-based models. Model simulations were run at 4 British peatland sites using historical climate data and climate projections under a medium (A1B) emissions scenario from the 11-RCM (regional climate model) ensemble underpinning UKCP09. The models showed that blanket peatlands are vulnerable to projected climate change; however, predictions varied between models as well as between sites. All BCEMs predicted a shift from presence to absence of a climate associated with blanket peat, where the sites with the lowest total annual precipitation were closest to the presence/absence threshold. DMs showed a more variable response. ECOSSE predicted a decline in net C sink and shift to net C source by the end of this century. The Durham Carbon Model predicted a smaller decline in the net C sink strength, but no shift to net C source. MILLENNIA predicted a slight overall increase in the net C sink. In contrast to the BCEM projections, the DMs predicted that the sites with coolest temperatures and greatest total annual precipitation showed the largest change in carbon sinks. In this model inter-comparison, the greatest variation in model output in response to climate change projections was not between the BCEMs and DMs but between the DMs themselves, because of different approaches to modelling soil organic matter pools and decomposition amongst other processes. The difference in the sign of the response has major implications for future climate feedbacks, climate policy and peatland management. Enhanced data collection, in particular monitoring peatland response to current change, would significantly improve model development and projections of future change.

Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases

The Arabian Sea is an important moisture source for Indian monsoon rainfall. The skill of climate models in simulating the monsoon and its variability varies widely, while Arabian Sea cold sea surface temperature (SST) biases are common in coupled models and may therefore influence the monsoon and its sensitivity to climate change. We examine the relationship between monsoon rainfall, moisture fluxes and Arabian Sea SST in observations and climate model simulations. Observational analysis shows strong monsoons depend on moisture fluxes across the Arabian Sea, however detecting consistent signals with contemporaneous summer SST anomalies is complicated in the observed system by air/sea coupling and large-scale induced variability such as the El Niño-Southern Oscillation feeding back onto the monsoon through development of the Somali Jet. Comparison of HadGEM3 coupled and atmosphere-only configurations suggests coupled model cold SST biases significantly reduce monsoon rainfall. Idealised atmosphere-only experiments show that the weakened monsoon can be mainly attributed to systematic Arabian Sea cold SST biases during summer and their impact on the monsoon-moisture relationship. The impact of large cold SST biases on atmospheric moisture content over the Arabian Sea, and also the subsequent reduced latent heat release over India, dominates over any enhancement in the land-sea temperature gradient and results in changes to the mean state. We hypothesize that a cold base state will result in underestimation of the impact of larger projected Arabian Sea SST changes in future climate, suggesting that Arabian Sea biases should be a clear target for model development.

The HadGEM2 family of Met Office Unified Model climate configurations

We describe the HadGEM2 family of climate configurations of the Met Office Unified Model, MetUM. The concept of a model "family" comprises a range of specific model configurations incorporating different levels of complexity but with a common physical framework. The HadGEM2 family of configurations includes atmosphere and ocean components, with and without a vertical extension to include a well-resolved stratosphere, and an Earth-System (ES) component which includes dynamic vegetation, ocean biology and atmospheric chemistry. The HadGEM2 physical model includes improvements designed to address specific systematic errors encountered in the previous climate configuration, HadGEM1, namely Northern Hemisphere continental temperature biases and tropical sea surface temperature biases and poor variability. Targeting these biases was crucial in order that the ES configuration could represent important biogeochemical climate feedbacks. Detailed descriptions and evaluations of particular HadGEM2 family members are included in a number of other publications, and the discussion here is limited to a summary of the overall performance using a set of model metrics which compare the way in which the various configurations simulate present-day climate and its variability.

The FAMOUS climate model (versions XFXWB and XFHCC): description update to version XDBUA

FAMOUS is an ocean-atmosphere general circulation model of low resolution, based on version 4.5 of the UK MetOffice Unified Model. Here we update the model description to account for changes in the model as it is used in the CMIP5 EMIC model intercomparison project (EMICmip) and a number of other studies. Most of these changes correct errors found in the code. The EMICmip version of the model (XFXWB) has a better-conserved water budget and additional cooling in some high latitude areas, but otherwise has a similar climatology to previous versions of FAMOUS. A variant of XFXWB is also described, with changes to the dynamics at the top of the model which improve the model climatology (XFHCC).