To determine accurately the number of serious injuries at EU level and to compare serious injury rates between different countries it is essential to use a common definition. In January 2013, the High Level Group on Road Safety established the definition of serious injuries as patients with an injury level of MAIS3+(Maximum Abbreviated Injury Scale). Whatever the method used for estimating the number or serious injuries, at some point it is always necessary to use hospital records. The aim of this paper is to understand the implications for (1) in/exclusion criteria applied to case selection and (2) a methodological approach for converting ICD (International Classification of Diseases/Injuries) to MAIS codes, when estimating the number of road traffic serious injuries from hospital data. A descriptive analysis with hospital data from Spain and the Netherlands was carried out to examine the effect of certain choices concerning in- and exclusion criteria based on codes of the ICD9-CM and ICD10. The main parameters explored were: deaths before and after 30 days, readmissions, and external injury causes. Additionally, an analysis was done to explore the impact of using different conversion tools to derive MAIS3 + using data from Austria, Belgium, France, Germany, Netherlands, and Spain. Recommendations are given regarding the in/exclusion criteria and when there is incomplete data to ascertain a road injury, weighting factors could be used to correct data deviations and make more real estimations.

The development, use, and understanding of severity of illness scoring systems has advanced rapidly in the last decade; their weaknesses and limitations have also become apparent. This work follows some of this development and explores some of these aspects. It was undertaken in three stages and in two countries. The first study investigated three severity of illness scoring systems in a general Intensive Care Unit (ICU) in Cape Town, namely the Acute Physiology and Chronic Health Evaluation (APACHE II) score, the Therapeutic Intervention Scoring System (TISS), and a locally developed organ failure score. All of these showed a good relationship with mortality, with the organ failure score the best predictor of outcome. The TISS score was felt to be more likely to be representative of intensiveness of medical and nursing management than severity of illness. The APACHE II score was already becoming widely used world-wide and although it performed less well in some diagnostic categories (for example Adult Respiratory Distress Syndrome) than had been hoped, it clearly warranted further investigation. Some of the diagnosis-specific problems were eliminated in the next study which concentrated on the application of the APACHE II score in a cardiothoracic surgical ICU in London. Although group predictive ability was statistically impressive, the predictive ability of APACHE II in the individual patient was limited as only very high APACHE II scores confidently predicted death and then only in a small number of patients. However, there were no deaths associated with an APACHE II score of less than 5 and the mortality was less than 1 % when the APACHE II score was less than 10. Finally, having recognised the inadequacies in mortality prediction of the APACHE II score in this scenario, a study was undertaken to evaluate a novel concept: a combination of preoperative, intraoperative, and postoperative (including APACHE II and III) variables in cardiac surgery patients admitted to the same ICU. The aim was to develop a more precise method of predicting length of stay, incidence of complications, and ICU and hospital outcome for these patients. There were 1008 patients entered into the study. There was a statistically significant relationship between increasing Parsonnet (a cardiac surgery risk prediction score), APACHE II, and APACHE III scores and mortality. By forward stepwise logistic regression a model was developed for the probability of hospital death. This model included bypass time, need for inotropes, mean arterial pressure, urea, and Glasgow Coma Scale. Predictive performance was evaluated by calculating the area under the receiver operating characteristic (ROC) curve. The derived model had an area under the ROC curve 0.87, while the Parsonnet score had an area of 0.82 and the APACHE II risk of dying 0.84. It was concluded that a combination of intraoperative and postoperative variables can improve predictive ability.

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The going concern warning and its consequences for auditors and companies have been studied from many different angles. However, the results are conflicting. A going concern warning is issued by an auditor when there is substantial doubt on the company’s ability to continue as a going concern. Studies have shown that most companies survive despite a going concern warning. There are also signs of short-term consequences for the companies. How the consequences unfold in the long run for companies that have received a going concern warning is not well studied. The purpose of this study is to investigate how companies are affected in the long run by the consequences that can arise due to a going concern warning. For this study, a quantitative method has been used. Legitimacy theory, Interest theory and Institutional theory, have the common factor that they all explain how organizations survive in the long run. The theories, together with scientific articles and other relevant literature, have been used to develop the hypotheses. Companies with a going concern warning have been compared with companies that have not received a going concern warning. Empirical data have been collected for 2010-2015 and by using multiple linear regressions the hypotheses of the study have been tested. The result of the study showed that a going concern warning did not adversely affect the company on a long-term basis. On the contrary, the study indicates that companies with a going concern warning improve compared to equivalent companies which did not receive a going concern warning.

This paper investigates the impact of the 2008's financial crisis on local crime rates in Sweden. I deploy a difference-in-differences approach that contrasts the changes in reported crimes between municipalities that are more or less crisis-exposed. The results show no significant effect on any crime category nor the aggregate crime rate. However, there are indications of more densely populated municipalities experiencing an increase in crimes with underlying financial incentives, although not robust. The results are similar when the effect of the Great Recession is compared to the major financial crisis that hit Sweden in the early 90s, suggesting that economic crises do not cause any reactions in crimes. One explanation could be the increase in social grants recipients and the participation in labour market programmes. Both of which cushions the fall in income and reduces criminal motivation. The results appear robust for a variety of alternative severity measures. Potential spillovers between adjacent municipalities do not seem to be a threat as the results are similar for county-level regressions. Overall, the findings in this paper point towards the number of reported crimes being unaffected by the crisis exposure measured as the employment change and change in retail sales.

In conducting this research, I wanted to explore whether political incentives have a significant effect on wildfire management in the United States. I attempt to answer this question by proving a theoretical justification for why wildfires may become more expensive to fight and severe to manage because of political institutions. I then attempt to provide some hard evidence to support this theory by using regression analysis. My analysis suggests that political factors do matter for wildfire suppression funding, although I was unable to find strong enough evidence to suggest that these political factors are actually driving more severe wildfires. This research contributes to the literature on public choice theory, a branch of political economy that looks at government from the individual decision makers’ level. Additionally, this research contributes to the literature on what affects wildfire suppression effectiveness and funding. This research may contribute to future analyses of the institutions that make U.S. wildland firefighters more or less capable of effectively managing wildfires to protect human lives, property, and forests.

Fire is a natural and essential component of forests in western North America. Fire maintains biodiversity through the creation of different habitat types, and regular fire rotations reduce the accumulation of woody fuels and thick understory plant densities that give rise to catastrophic fire. The practice of fire exclusion has altered western forests and increased the risk of widespread change under rising temperatures projected for the 21st century. To manage for the reintroduction of fire it is critical that we understand the interactions between fire and forest biota in recently fire-suppressed forests. In Chapter 2, I studied the formation and impact of small-scale fire refugia. Fire refugia are areas within burned forest that experienced relatively little change, and are recognized as important places that offer protection for forest biota (vegetation, wildlife) during and after the fire. Very few studies, however, have examined small-scale fire refugia despite their importance to many organisms (e.g., small mammals, understory plants). In a long-term forest monitoring plot in Yosemite National Park, I mapped all unburned areas ≥ 1 m2 the first year after fire. I found small fire refugia were abundant, somewhat predictable, and fostered increased survival and diversity of nearby plant life. My results suggest that small fire refugia are an important component of burned forests that should be included in management considerations. In Chapter 3, I examined possible fisher habitat in burned areas. Fishers are forest carnivores of high conservation concern due to widespread declines since European settlement and the risk of habitat loss due to fire. An isolated population remains in the Sierra National Forest, where managers are weighing the need to reintroduce fire against possible detrimental impacts to current habitat. My research examined the forest structural characteristics (vegetative cover, heights of different forest layers) surrounding fisher dens. I found suitable thresholds of these structural characteristics in recently burned areas in Yosemite, particularly after low-severity fire. My results suggest that burned areas may offer suitable denning habitat for fishers, though more research is needed to determine if this conclusion holds for all fisher activities (e.g., foraging, resting) and scales of selection.

A new mathematical model has been developed along with a new parameter estimation routine using surface temperature and heat flux measurements to estimate blood perfusion and thermal resistance in living tissue. Dynamic thermal measurements collected at the surface of the sensor before and after imposing a dynamic thermal cooling event are used with the model to estimate the blood perfusion, thermal resistance and core temperature. The Green\'s function based analytical solution does not require calculation of the whole tissue temperature distribution, which was not the case for the previous models. The result from the new model was proved to have better and more consistent results than previous models. The new model was validated to solve one of the unsolved biomedical problems which is the ability of detecting burn severity. The method was tested with a phantom perfusion system. The results matched known blood perfusion and thermal resistance values. The method was also tested with burns on animal models. Inflammation effects associated with the burns were studied using a newly developed term called the Burn Factor. This correlated with the severity of imposed burns. This work consists of three journal papers. The first paper introduces the mathematical model and its validation with finite-difference solutions. The second paper validates the physical aspects of the usage of the model with thermal measurement in detecting simulated burned layers and the associated perfusion. The third paper demonstrates the ability of the model to use thermal measurements to detect different burn severity of an animal model and to study the healing process. / Ph. D.

京都大学 / 0048 / 新制・論文博士 / 博士(農学) / 乙第13066号 / 論農博第2841号 / 新制||農||1046(附属図書館) / 学位論文||H28||N5020(農学部図書室) / (主査)教授 安達 修二, 教授 谷 史人, 教授 保川 清 / 学位規則第4条第2項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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