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京都大学 / 新制・課程博士 / 博士(工学) / 甲第23889号 / 工博第4976号 / 新制||工||1777(附属図書館) / 京都大学大学院工学研究科原子核工学専攻 / (主査)教授 斉藤 学, 准教授 田﨑 誠司, 教授 宮寺 隆之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Violent crime has many long-lasting negative consequences for society. This thesis aims to explore the relationship between economic inequality and violent crime, represented by the level of intentional homicides in forty-nine countries over the period of nine years from 2010-2018. We delve into several theories and representative works in the fields of criminology, sociology, psychology, and economics that provide important perspectives on the subject and offer a theoretical foundation for the analysis. Previous research has usually pointed to a positive association between inequality and crime rates, albeit with some notable outliers. Our objective was to provide an updated view on the subject, employing recent data and statistical methods. We use fixed-effects estimators to account for time-invariant determinants, provide random-effects estimators for control and apply a generalized methods of moments model for possible inertia regarding the dependent variable. Economic inequality in the form of income inequality does seem to cause more harm than what might be suspected at first, influencing the intentional homicide levels in a society. It is the duty of public and private bodies to foster policies that aim to reduce this trend, and thus diminish the societal costs associated with it.

<p><strong>Background:</strong> Major adverse cardiac events, MACE – a composite endpoint of cardiac death and nonfatal myocardial infarction (MI) – are severe harmful outcomes that commonly arise after elective vascular surgeries. As current pre-operative risk prediction models are not as effective in predicting post-operative outcomes, this thesis will discuss the key results of an individual patient data meta-analysis that is based on data from six cohort studies of patients undergoing vascular surgery.</p> <p><strong>Objectives:</strong> The purpose of this thesis is to determine optimal thresholds of continuous covariates and create a prediction model for major adverse cardiac events (MACE), within 30 days after a vascular surgery. The goals include exploring the minimum p-value method to dichotomize cutpoints for continuous variables; employing logistic regression analysis to determine a prediction model for MACE; evaluating its validity against other samples; and assessing its sensitivity to clustering effects. The secondary objectives are to determine individual models for predicting all-cause mortality, cardiac death, and nonfatal MI within 30 days of a vascular surgery, using the final covariates assessed for MACE.<strong></strong></p> <p><strong>Methods: </strong>Both B-type naturietic peptide (BNP) and its N-terminal fragment (NTproBNP) are independently associated with cardiovascular complications after noncardiac surgeries, and particularly frequent after noncardiac vascular surgeries. In a previous study, these covariates were dichotomized using the receiver operating characteristic (ROC) curve approach and a simple logistic regression (SLR) model was created for MACE [1]. The first part of this thesis applies the minimum p-value method to determine a threshold for each natriuretic peptide (NP), BNP and NTproBNP. SLR is then used to model the prediction of MACE within 30 days after a patient’s vascular surgery. Comparisons were made with the ROC curve approach to determine the optimal thresholds and create a prediction model. The validity of this model was tested using bootstrap samples and its robustness was assessed using a mixed effects logistic regression (MELR) model and a generalized estimating equation (GEE). Finally, MELR was performed on each of the secondary outcomes.</p> <p><strong>Results:</strong>A variable, ROC_thrshld, was created to represent the cutpoints of Rodseth’s ROC curve approach, which identified 116pg/mL and 277.5pg/mL to be the optimal thresholds for BNP and NTproBNP, respectively [1]. The minimum p-value method dichotomized these NP thresholds as BNP: 115.57pg/mL (p</p> <p><strong>Discussion:</strong> One key limitation to this thesis is the small sample size received for NTproBNP. Also, determining only one cutpoint for each NP concentration may not be sufficient, since dichotomizing continuous factors can lead to loss of information along with other issues. Further research should be performed to explore other possible cutpoints along with performing reclassification to observe improvements in risk stratification. After validating our final model against other samples, we can conclude that MINP_thrshld, the type of surgery, and diabetes are significant covariates for the prediction of MACE. With the simplicity in only requiring a blood test to measure NP concentration levels and easily learning the status of the other two factors, minimal effort is needed in calculating the points and risk estimates for each patient. Further research should also be performed on the secondary outcomes to examine other factors that may be useful in prediction.</p> <p><strong>Conclusions: </strong>The minimum p-value method produced similar results to the ROC curve method in dichotomizing the NP concentration levels. The cutpoints for BNP and NTproBNP were 115.57pg/mL and 241.7 pg/mL, respectively. Further research needs to be performed to determine the optimality of the final prediction model of MACE, with covariates MINP_thrshld, type of surgery, and diabetes mellitus. <strong></strong></p> <p><strong><br /></strong></p> / Master of Science (MSc)

This thesis presents simple efficient algorithms to estimate distribution parameters and to construct prediction intervals for location-scale families. Specifically, we study two scenarios: one is a frequentist method for a general location--scale family and then extend to a 3-parameter distribution, another is a Bayesian method for the Gumbel distribution. At the end of the thesis, a generalized bootstrap resampling scheme is proposed to construct prediction intervals for data with an unknown distribution. Our estimator construction begins with the equivariance principle, and then makes use of unbiasedness principle. These two estimates have closed form and are functions of the sample mean, sample standard deviation, sample size, as well as the mean and variance of a corresponding standard distribution. Next, we extend the previous result to estimate a 3-parameter distribution which we call a mixed method. A central idea of the mixed method is to estimate the location and scale parameters as functions of the shape parameter. The sample mean is a popular estimator for the population mean. The mean squared error (MSE) of the sample mean is often large, however, when the sample size is small or the scale parameter is greater than the location parameter. To reduce the MSE of our location estimator, we introduce an adaptive estimator. We will illustrate this by the example of the power Gumbel distribution. The frequentist approach is often criticized as failing to take into account the uncertainty of an unknown parameter, whereas a Bayesian approach incorporates such uncertainty. The present Bayesian analysis for the Gumbel data is achieved numerically as it is hard to obtain an explicit form. We tackle the problem by providing an approximation to the exponential sum of Gumbel random variables. Next, we provide two efficient methods to construct prediction intervals. The first one is a Monte Carlo method for a general location-scale family, based on our previous parameter estimation. Another is the Gibbs sampler, a special case of Markov Chain Monte Carlo. We derive the predictive distribution by making use of an approximation to the exponential sum of Gumbel random variables . Finally, we present a new generalized bootstrap and show that Efron's bootstrap re-sampling is a special case of the new re-sampling scheme. Our result overcomes the issue of the bootstrap of its ``inability to draw samples outside the range of the original dataset.'' We give an applications for constructing prediction intervals, and simulation shows that generalized bootstrap is better than that of the bootstrap when the sample size is small. The last contribution in this thesis is an improved GRS method used in nuclear engineering for construction of non-parametric tolerance intervals for percentiles of an unknown distribution. Our result shows that the required sample size can be reduced by a factor of almost two when the distribution is symmetric. The confidence level is computed for a number of distributions and then compared with the results of applying the generalized bootstrap. We find that the generalized bootstrap approximates the confidence level very well. / Dissertation / Doctor of Philosophy (PhD)

A core feature of GAD, excessive and uncontrollable worry, may be indicative of poor attentional control and difficulty disengaging attention from threatening or emotional information (e.g., Fox, 2004; Mathews, Fox, Yiend, & Calder, 2003; Yiend & Mathews 2001). The current study examined the performance of college students with and without self-reported GAD (N = 63) on measures of attentional control and a spatial cueing task designed to assess engagement-disengagement processes from emotionally valenced (aversive, pleasant) and neutral picture stimuli. Attentional control abilities were examined using the Stroop Color-Word Association Test (SCW Test) and Trail-Making Test (TMT). Separate analyses of variance (ANOVAs) demonstrated that GAD participants performed more poorly on the Stroop Color subtest and the TMT: Part B than non-GAD participants. Mixed ANOVAs of response times measured during the spatial cueing task revealed significant main effects for Cue Valence and Cue Validity, as well as several significant interactions of these variables with GAD status. The significant Cue Valence x Cue Validity x GAD status interaction indicated that GAD participants were slower to disengage their attention from aversive stimuli, relative to pleasant or neutral stimuli, than non-GAD participants who did not exhibit this bias. This interaction effect, however, did not remain significant upon covarying for depression. Together, these findings suggest that individuals with GAD evidence poorer attentional control and demonstrate difficulties disengaging from threatening stimuli compared to persons without the disorder. Impairment in these attentional processes may, therefore, contribute to the etiology and maintenance of GAD. / Psychology