A base case modelling investigation was conducted to explore the chemical and physical behaviour of ground-level ozone (O3) and its precursor nitrogen dioxide (NO2) in Ontario using the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) model. Two related studies were completed to evaluate the performance of CMAQ in reproducing the behaviour of these species in both rural and urban environments by comparing to surface measurements collected by the Ontario Ministry of the Environment (MOE) network of air quality stations. The first study was a winter examination and the second study was conducted for a period during the summer of the same year. The municipality of North Bay was used to represent a rural setting given its smaller population relative to the city of Ottawa which was the base of the urban site. Statistical and graphical analyses were used to validate the model output. CMAQ was found to replicate the spatial variation of O3 and NO2 over the domain in both the winter and summer, but showed some difficulty in simulating the temporal allocation of the species. Validation statistics for North Bay and Ottawa showed overall O3 mean biases (MB) of 3.35 ppb and 2.25 ppb, respectively, and overall NO2 MB of -8.75 ppb and -4.37 ppb, respectively for the winter. Summer statistics generated O3 MB of 4.66 ppb (North Bay) and 10.05 ppb (Ottawa) while both MB for NO2 were between -2.20 ppb to -2.55 ppb. Graphical analysis showed that the model was not able to reproduce the lower levels of O3, especially at night, or the higher levels of NO2 during the day at the North Bay site for either season. This was expected since the comparisons were made between point measurements and 36 km grid-averaged model results. The presence of high amounts of NO2 emissions local to the monitoring sites compared to the levels represented in the emissions inventory may also be a contributing factor. The simulations for Ottawa demonstrated better agreement between model results and measurements as CMAQ provided a more accurate reproduction of both the higher and lower mixing ratios of O3 and NO2 during the winter and summer seasons. Results indicate that CMAQ is able to simulate urban environments better than rural ones.

A base case modelling investigation was conducted to explore the chemical and physical behaviour of ground-level ozone (O3) and its precursor nitrogen dioxide (NO2) in Ontario using the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) model. Two related studies were completed to evaluate the performance of CMAQ in reproducing the behaviour of these species in both rural and urban environments by comparing to surface measurements collected by the Ontario Ministry of the Environment (MOE) network of air quality stations. The first study was a winter examination and the second study was conducted for a period during the summer of the same year. The municipality of North Bay was used to represent a rural setting given its smaller population relative to the city of Ottawa which was the base of the urban site. Statistical and graphical analyses were used to validate the model output. CMAQ was found to replicate the spatial variation of O3 and NO2 over the domain in both the winter and summer, but showed some difficulty in simulating the temporal allocation of the species. Validation statistics for North Bay and Ottawa showed overall O3 mean biases (MB) of 3.35 ppb and 2.25 ppb, respectively, and overall NO2 MB of -8.75 ppb and -4.37 ppb, respectively for the winter. Summer statistics generated O3 MB of 4.66 ppb (North Bay) and 10.05 ppb (Ottawa) while both MB for NO2 were between -2.20 ppb to -2.55 ppb. Graphical analysis showed that the model was not able to reproduce the lower levels of O3, especially at night, or the higher levels of NO2 during the day at the North Bay site for either season. This was expected since the comparisons were made between point measurements and 36 km grid-averaged model results. The presence of high amounts of NO2 emissions local to the monitoring sites compared to the levels represented in the emissions inventory may also be a contributing factor. The simulations for Ottawa demonstrated better agreement between model results and measurements as CMAQ provided a more accurate reproduction of both the higher and lower mixing ratios of O3 and NO2 during the winter and summer seasons. Results indicate that CMAQ is able to simulate urban environments better than rural ones.

The goal of this diploma thesis entitled "The evaluation and rewarding systemof employees in a specific organization" was to analyze the evaluation a rewarding system of personal bankers in Moneta Money bank a.s. Based on these analyses, to propose changes, that would contribute to improving the quality and effectiveness of this area. This thesis has two parts. The first part contains a summary of theoretical information relevant to this issue. The practical part contains description of the organization Moneta Money Banks Inc., a description of the evaluation and rewarding system of personal bankers in this organization and an analysis of these systems. The analysis used survey. The survey showed that personal bankers don't have the means or opportunity to evaluate their superior. And personal bankers are missing personal approach by Moneta Money bank a.s. This diploma thesis proposes implementation of these "personal bonuses" into the rewarding system: gifts or bonuses for years of service, for instance at the occasion of eymployee's jubilee. The next proposed change was the introduction of 360-degree feedback.

Les changements globaux et l'évolution du contexte socio-économique renforcent les attentes vis-à-vis d'une gestion multifonctionnelle des forêts. En France, la communauté forestière s'est accordée sur la définition du double objectif de « produire plus de bois, tout en préservant mieux la biodiversité […]» (Grenelle de l'Environnement, 2007). Cet objectif s'accompagne d'une volonté de maintenir des attributs favorables à la biodiversité d'une part, et de « dynamiser » la sylviculture d'autre part. La comptabilité entre ces mesures est toutefois controversée et il est aujourd'hui nécessaire de mieux comprendre leurs effets sur les services écosystémiques, afin de pouvoir définir les conditions d'une gestion forestière multifonctionnelle et durable.L'objectif de la thèse est d'explorer de manière fine l'effet de la sylviculture sur la structure des peuplements, la production de bois et la préservation de la biodiversité. Le travail s'articule autour de deux hypothèses générales : (1) celle que les indicateurs de ces deux services répondent de manière différente à la gestion; (2) celle qu'une gamme intermédiaire d'intensités de sylviculture est favorable au compromis entre production et biodiversité. Le travail a porté sur le cas des sapinières-pessières irrégulières de montagne, qui présentent une longue tradition de gestion en futaie irrégulière et sont jugées favorables à la fourniture d'un certain nombre de services écosystémiques. Nous avons opté pour une approche par simulation s'appuyant sur le couplage d'un modèle de dynamique forestière, d'algorithmes de sylviculture et de modèles et indicateurs de production et de biodiversité. Le travail de thèse a nécessité la mise en place d'une démarche complète d'expérimentation par simulation impliquant les étapes (i) de formalisation des variables de contrôle et de réponse, (ii) de développement et d'évaluation de modèles, (iii) de définition de plans d'expérience, (iv) d'analyse de sensibilité et (v) d'analyse de la réponse des indicateurs à la gestion. Une analyse complète du modèle Samsara2 nous a permis de vérifier la cohérence des dynamiques forestières simulées et la fiabilité des prédictions. Un algorithme de sylviculture a été développé pour modéliser la gestion en futaie irrégulière de manière fine. Deux modèles de biodiversité ont été implémentés à partir de modèles issus de la littérature : un modèle de stockage et de décomposition du bois mort et un modèle de prédiction de la richesse spécifique de la strate herbacée. Une analyse de sensibilité du système nous a tout d'abord permis d'analyser l'influence des paramètres d'entrée (sylvicoles, démographiques ou état initial) sur un ensemble d'indicateurs de structure, production et biodiversité, puis d'identifier et de fixer les paramètres peu influents. Une approche par régression a ensuite permis d'établir la fonction de réponse (métamodèle) de chaque indicateur aux principaux leviers de gestion, en interaction avec la démographie et l'état initial. Nous avons ainsi observé un effet négatif de l'intensification de la gestion sur la biodiversité, bien que cet effet varie en fonction des indicateurs. Les mesures de conservation de la biodiversité peuvent toutefois servir de leviers de compensation dans certains cas, permettant ainsi de concilier les deux objectifs. Des situations de compromis entre indicateurs de production et/ou biodiversité ont été détectées, mais leur analyse fine nécessite désormais de se tourner vers les méthodes d'analyse multicritère.Ainsi, l'analyse couplée des de la réponse des indicateurs de services écosystémiques à la gestion et des scénarii de gestion situés sur la zone de compromis devrait permettre d'alimenter les échanges avec les gestionnaires forestiers et de discuter des recommandations de gestion à l'échelle de la parcelle ou du massif forestier. / Global change and the evolution of the socio-economic context reinforce the expectations for multifunctional forest management. In France, the forest community agreed on the definition of the double objective of “improving timber production while preserving biodiversity better” (Grenelle 2007). This objective goes along with a will of maintaining the natural attributes favoring biodiversity on one hand, and of increasing management intensity on the other hand. The compatibility between both objectives is however controversial and it seem nowadays necessary to better understand their effects on ecosystem services, so as to enable the definition of multifunctional and sustainable forest management. The objective of this PhD thesis is to explore the effect of silviculture on stand structure, timber production and biodiversity preservation. This works involves two main hypotheses: (1) the fact that ecosystem services indicators present different responses to silvicultural drivers, thus leading to trade-offs situations; (2) the fact that management scenarios of intermediate intensity may enable satisfactory production-biodiversity trade-offs to be reached. This work addressed the case of uneven-aged spruce-fir mountain forests, which present a long tradition of uneven-aged management (selection system) and are judged favorable to the provision of several ecosystem services. We used a simulation approach coupling a forest dynamics simulation model (Samsara2), a silviculture algorithm, and ecosystem services models and indicators (for timber production and biodiversity). This however required a complete simulation experiment approach to be set up, with several steps: (i) formalization of control and response variables, (ii) model development and evaluation, (iii) experiment designs definition, (iv) sensitivity analysis, and (v) study of indicators' response to management. A complete analysis of the Samsara2 model enabled the consistency of simulated forest dynamics and the reliability of predictions to be checked. A silviculture algorithm has been developed to accurately model uneven-aged management. Two biodiversity models have been implemented from the literature: a dead wood decay model and an understory diversity model.A sensitivity analysis of the system first enabled us to assess the influence of input parameters (silviculture, demographic and initial state) on structure, timber production and biodiversity indicators, and then to identify and fix those with low influence. Then, a regression approach enabled the establishment of the response function (metamodels) of each indicator to the main silvicultural factors, in interaction with demography and initial state. This revealed the negative effect of increased management intensity on biodiversity indicators, although its effect depended on the indicator. Biodiversity conservation measures could however be used as compensation drivers in some cases, therefore enabling both objectives to be concealed. Trade-offs situations have also been detected between timber production and/or biodiversity conservation indicators, but their analysis now require specific multi-criteria analysis to be used.The combined analysis of ecosystem services response to silvicultural drivers and of management scenarios located on the trade-offs area would then supply the discussion with forest managers with new elements and enable management recommendations to be discussed at the stand or landscape scale.

This master’s thesis is focused on evaluation of performance and current state of the company Diadex Ltd. With the help of specific analysis and tools, described in the theoretical part, this thesis describes the environment, in which the company operates, and reveals pros and cons, that significantly affect corporate activities. Based on the results of financial and non-financial indicators, this work exposes the strengths and weaknesses. In conclusion, the selected methods should refer to the areas, which require increased attention, and possibly propose a solution for change and improvement in particular area or overall situation.

Department of Advanced Nursing Science / DCur

The three-factor model of Fama and French has proved to be a seminal contribution to asset pricing theory, and was recently extended to include two more factors, yielding the Fama-French five-factor model. Other proposed augmentations of the three-factor model includes the introduction of a momentum factor by Carthart. The extensive use of such factors in asset pricing theory and investing motivates the study of the distributional properties of the returns of these factors. However, previous studies have focused on subsets of these six factors on the U.S. market. In this thesis, the distributional properties of daily log-returns of the five Fama-French factors and the Carthart momentum factor in European data from 2009 to 2019 are examined. The univariate distributional dynamics of the factor log-returns are modelled as ARMA-NGARCH processes with skewed t distributed driving noise sequences. The Gaussian and t copula are then used to model the joint distributions of these factor log-returns. The models developed are applied to estimate the one-day ahead Value-at-Risk (VaR) in testing data. The estimations of the VaR are backtested to check for correct unconditional coverage and exponentially distributed durations between exceedances. The results suggest that the ARMA-NGARCH processes are a valid approximation of the factor log-returns, and lead to good estimations of the VaR. The results of the multivariate analysis suggest that constant Gaussian and t copulas might be insufficient to model the dependence structure of the factors, and that there might be a need for more flexible copula models with dynamic correlations between factor log-returns. / Fama och Frenchs trefaktormodell har blivit en populär modell för aktieavkastning, och utvidgades nyligen av Fama och French genom att två ytterligare faktorer lades till för att skapa en femfaktormodell. Carthart föreslår en annan modell där trefaktormodellen kompletteras med en momentumfaktor. Då dessa faktorer används inom både akademiska sammanhang och kapitalförvaltning finns det ett tydligt behov av att undersöka vilka egenskaper fördelningen av faktorernas avkastning har. Dock har tidigare sådan forskning inte undersökt detta för alla sex faktorer, och endast använt data från USA:s marknad. I detta examensarbete undersökt därför sannolikhetsfördelningen för den logaritmiska dagliga avkastningen av de fem Fama-French-faktorerna och Cartharts momentumfaktor i europeisk data från åren 2009 till 2019. De endimensionella sannolikhetsfördelningarna modelleras som dynamiska med hjälp av ARMA-NGARCH-processer med feltermer som är fördelade enligt en generaliserad t-fördelning som tillåter skevhet. För att modellera multivariata fördelningar används en Gaussisk copula och en t-copula. De erhållna modellerna används sedan för att uppskatta daglig Value-at-Risk (VaR) i testdata. Dessa uppskattningar av VaR genomgår sedan statistiska test för att undersöka om antalet överträdelser är korrekt och tiderna mellan varje överträdelse är exponentialfördelade. Resultaten i detta examensarbete tyder på att ARMA-NGARCH-processer är en bra approximation av faktorernas logaritmiska dagliga avkastning, och ger bra uppskattningar av VaR. Resultaten för den multivariata analysen tyder på att en konstant copula kan vara en otillräcklig modell för beroendestrukturen mellan faktorerna, och att det möjligen finns ett behov av att använda mer flexibla copula-modeller med en dynamisk korrelation mellan faktorernas logaritmiska avkastning.

No description available.

The concept of Shifting the Balance of Care was first introduced to NHS Scotland in 2005 through the Kerr Report. The key messages from the report were to: ensure sustainable and safe local services, which are supported by the right skills, change the emphasis of care into the community, provide preventative reactive care, and fully integrate the system to tackle the changes, use technology more effectively, and involve the public in finding solutions to change. Following the report, a framework was developed which highlighted and prioritised eight areas of improvement. These areas for improvement are the focus by which this research examines if Operational Research (OR), specifically OR models, can have a positive impact in Shifting the Balance of Care. The research utilises underlying OR methodologies and methods and provides evidence from the literature of the ability of nine selected models to facilitate the Shift in the Balance of Care. A contributing factor to the research is the barriers to implementation of OR models into the NHS. With reference to the literature, the common barriers to implementation of OR models are categorised and used to provide direction to modellers where implementation barriers are more prevalent in some models than in others. The research also provides empirical evidence of three selected models’ (the Lean Methodology, Process Mapping and Simulation, developed over two Case Studies) ability to address and influence the prioritised Improvement Areas, with the addition of a newly developed model: SoApt. The development of SoApt follows the Principles of Model Development derived as a guide to modellers who wish to develop a new model. SoApt is also empirically explored in a Case Study and provides some evidence of the models ability to aid Decision-makers, faced with limited budgets, to choose between options which will Shift the Balance of Care. OR methods and methodologies are examined to ascertain the Roles of Models for each model explored in the Case Studies. Examination of the Roles of Models against the Improvement Areas provided evidence of a models’ ability to address more than one of the priority areas and that models can be used together or sequentially. In addition, with reference to OR methods and methodologies, a theoretical Evaluation Framework is proposed which suggests the User and User Satisfaction is key to the evaluation of a model’s success; positive experiences of the User and Use of the model may help to eliminate some of the barriers to implementation.

<p>Population pharmacokinetic-pharmacodynamic (PK-PD) models can be fitted using nonlinear mixed effects modelling (NONMEM). This is an efficient way of learning about drugs and diseases from data collected in clinical trials. Identifying covariates which explain differences between patients is important to discover patient subpopulations at risk of sub-therapeutic or toxic effects and for treatment individualization. Stepwise covariate modelling (SCM) is commonly used to this end. The aim of the current thesis work was to evaluate SCM and to develop alternative approaches. A further aim was to develop a mechanistic PK-PD model describing fasting plasma glucose, fasting insulin, insulin sensitivity and beta-cell mass.</p><p>The lasso is a penalized estimation method performing covariate selection simultaneously to shrinkage estimation. The lasso was implemented within NONMEM as an alternative to SCM and is discussed in comparison with that method. Further, various ways of incorporating information and propagating knowledge from previous studies into an analysis were investigated. In order to compare the different approaches, investigations were made under varying, replicated conditions. In the course of the investigations, more than one million NONMEM analyses were performed on simulated data. Due to selection bias the use of SCM performed poorly when analysing small datasets or rare subgroups. In these situations, the lasso method in NONMEM performed better, was faster, and additionally validated the covariate model. Alternatively, the performance of SCM can be improved by propagating knowledge or incorporating information from previously analysed studies and by population optimal design.</p><p>A model was also developed on a physiological/mechanistic basis to fit data from three phase II/III studies on the investigational drug, tesaglitazar. This model described fasting glucose and insulin levels well, despite heterogeneous patient groups ranging from non-diabetic insulin resistant subjects to patients with advanced diabetes. The model predictions of beta-cell mass and insulin sensitivity were well in agreement with values in the literature.</p>