Yes / Bridge pier is a common feature in hydraulic structure. Its impact to the river usually occurs in group form rather than single pier, so this challenging piers-group influence towards river hydraulics and turbulence needs to be explored. In this paper, the measurements were conducted using an Acoustic doppler velocimeter (ADV) to study velocities in three dimensions (longitudinal, transversal, and vertical). Based on the experimental data, we have observed reversed depth-averaged velocity vector after each pier in the group of three-pier. The analysis has been conducted on the contribution of each bursting event to Reynolds shear stress (RSS) generation, in order to identify the critical events and turbulence structures around the piers. In the upstream near-wake flow in the bed-wall layer, strong sweep and ejection events have been observed; while at downstream, sweeps were more dominant. The pattern of burst changed in the outer layer of flow, where ejections were more dominant. Furthermore, the contribution fractional ratio to RSS variation at hole size H = 0 indicates that sweeps and ejections were significantly generated at the near wake-flow in upstream.

This study assesses the status of the teaching of contemporary issues in secondary social studies classrooms in four southwest Virginia school divisions. One hundred and sixteen secondary teachers in these school divisions were surveyed concerning their attitudes toward contemporary issues and the instruction of these issues in their social studies classrooms. Mean score results show that the issues that teachers perceived to be most significant to humankind were generally those issues that were given more extensive coverage in the curriculum. Teachers were divided when asked what issues would best be covered in each of the four major secondary subject areas. Each subject area was clearly noted for specific coverage of particular issues, with government classes providing the greatest amount of coverage and world history classes the least amount. A variety of teaching strategies, sources of information, and evaluation strategies were implemented in this instruction. Teachers also detailed what they considered to be major sources of support for the teaching of these issues. Finally, while teachers noted that contemporary issues were detailed in their curricula, they perceived limited coordination among teachers in this instruction. They also reported that more coordination among teachers of different secondary social studies courses should exist. / Doctor of Education

Climate change is impacting the intensity, duration, and frequency of climatic events. With climate change comes a multitude of adverse conditions, including extreme heat events, changes in disease patterns, and increased likelihood and frequency of natural disasters, including in places previously not exposed to such conditions. Human health has foundations in the environment; therefore, these adverse climatic conditions are directly linked to human health. Rural communities in Appalachia are likely to experience negative consequences of climate change more severely due to unique geomorphology and sociopolitical realities of the region. Non-governmental organizations (NGOs) throughout the Appalachian region are currently working to build resilience and prepare for potential adverse effects from climate change. To aid in this process, projections of future climate scenarios are needed to understand possible situations and adequately prepare. In partnership with Ohio University and West Virginia University, this study aims to characterize potential future climatic scenarios from publicly-available global climate models (GCMs) and prepare information to share with Appalachian communities. Climate model information for this analysis was obtained from NASA's Coupled Model Intercomparison Project (CMIP6). All code for data processing and analysis was prepared using the open-source R programming language to support reproducibility. To confirm that models can accurately simulate Appalachian climatic conditions, CMIP6 hindcast simulations for precipitation and maximum temperature were compared to observed weather records from NOAA. Climate models over and underestimated average precipitation values depending on location, while models consistently underestimated extreme precipitation values, simulated by total five-day precipitation. For temperature, climate models consistently underestimated average and extreme high temperature indicators. For Appalachian region projections, three towns of interest (one for each state involved in the study: Virginia, West Virginia, and Ohio) were selected based on current community resilience efforts. In these locations, mid-century (2040 – 2064) and end-of-century (2075 – 2099) projections for precipitation and temperature were summarized under a low emissions scenario and a high emissions scenario. Increases in precipitation and temperature were observed under average and extreme scenarios; these increases were noticeably more extreme under higher emissions scenarios. These trends are consistent with other studies and climate science consensus. When compared to hindcast values, observed average precipitation values were overestimated and underestimated, while observed extreme precipitation indices, average temperatures, and heat wave indices were underestimated by GCMs. Context with observed data is important to understanding model accuracy for the Appalachian region. GCMs are a useful tool to project potential future climate scenarios at specific locations in the Appalachian region, though model data is best used to communicate general trends rather than as inputs for other physical models. / Master of Science / Climate change is driving previously unseen changes in many aspects of the environment. Among these aspects, and of particular concern, are increased precipitation and increased high temperatures, which have direct negative outcomes on human health. Climate change can impact human health in a variety of ways, such as increasing instances of heat-related illnesses like heatstroke, changing insect-carried diseases patterns (i.e. Lyme disease, malaria), worsening preexisting conditions like asthma, and increasing the likelihood of natural disasters like flooding. Climate change also impacts mental health, especially increasing instances of anxiety and post-traumatic stress disorder from disasters. Rural communities like Appalachia are more likely to experience severe negative outcomes due to lack of resources, remote location, and economies historically based on resource extraction. Appalachia specifically also faces unique challenges with flooding, as many towns are situated in valleys with streams or rivers running through the center of town. To address and prepare for possible climate change outcomes, community-based planning is required to build resiliency. Throughout many areas, but specifically in Appalachia, many community-based organizations are already working to strengthen their communities by providing stable housing, addressing flooding, and preparing emergency response teams. To aid in these efforts, information about potential future climate is beneficial to these organizations to understand and prepare for potential conditions. This study aims to use publicly-available climate models to generate information about possible future climate conditions to be shared with community organizations. Additionally, this project's datasets and procedures are publicly available, so this analysis can be performed by communities anywhere in the world given they have adequate computing power. To check that models are a good indicator of previous climate conditions, and therefore would be useful for future projections, historic projected climate model outputs were compared to observed weather data. After confirming that the models used were fairly consistent with observed data, projected values for midcentury (2040 – 2064) and end-of-century (2075 – 2099) were gathered for Appalachian towns with interested community organizations. Projected values show increases in high temperatures and precipitation throughout the Appalachian region, including in short-term event scenarios, which is consistent with other climate science. Higher emissions scenarios result in greater increases in average and extreme temperature and precipitation values. Climate models can be a useful tool in understanding potential general climatic trends for a specific location and can support climate science communication.

The current study examined the nature and extent of endorsement of PMIEs, the nature and severity of MI symptoms related to endorsement of a PMIE, and the relations between extent of endorsement of PMIEs and MI symptoms. We hypothesized that (1) PMIEs perpetrated by others would be endorsed to a greater extent than PMIEs perpetrated by oneself; (2) medical professionals who endorsed a PMIE would report significantly greater severity on all MI symptoms compared to medical professionals who did not endorse a PMIE; (3) experiencing PMIEs (perpetrated by oneself and/or others) to a greater extent would predict higher levels of MI symptom severity, and MI symptom severity would specifically be most strongly predicted by PMIEs perpetrated by oneself. Hypotheses were examined using t-tests, Pearson's r correlations, and multiple multivariate regression analyses. First, the current study found that PMIEs perpetrated by others were endorsed to a greater extent than those perpetrated by themselves; second, greater exposure to PMIEs was associated with significantly greater severity of 10 of the 14 outcomes. Third, PMIEs perpetrated by oneself predicted more MI symptomatology than PMIEs perpetrated by others, indicating that while PMIEs perpetrated by others are more common, PMIEs perpetrated by oneself are more strongly associated with MI outcomes. This study highlights the widespread and harmful impact of PMIEs among medical professionals.

Planning is essential for an action-oriented, goal-driven software agent. In order to achieve a specific goal, an agent must first generate a plan. However, as the poet Robert Burns once noted, the best laid plans can often go awry. Each step of the plan is subject to the possibility of failure, a truth particularly relevant in the realworld or a realistic simulated environment. External influences not originally considered can often cause sudden, unanticipated consequences during the execution of the plan. When this happens, an intelligent software agent needs to answer the following important questions: What are the consequences of this event on its plan? How will the plan be affected? Can the plan be adjusted to accommodate the unanticipated effects? The research described in this thesis develops a model whereby intelligent agents can automatically determine consequences of unplanned events. Such a model provides agents with the ability to detect if and how events will affect the plan. This allows agents to subsequently modify the plan to mitigate unfavorable consequences or take advantage of favorable consequences.

<p dir="ltr">Tornadoes have caused billions of dollars in damage and are one of the leading causes of weather-related deaths in the United States each year. Recent studies have suggested spatial shifts in tornado activity, though the reason is unclear. Extratropical cyclones (ETCs), which are strongly associated with the jet stream, are known to produce an environment favorable for tornadoes in their warm sector. However, little recent research has been done on the spatiotemporal relationship between tornadoes and ETCs, so there is a poor understanding of whether or not the changes in tornado activity are affected by ETC patterns. ERA5 reanalysis, ETC tracking, and historical tornado data from 1980-2022 are used to analyze the climatology of tornadoes relative to ETCs. We found that 73% of F/EF1+ tornadoes occurred within 2000km of an ETC and are likely associated with the ETC. Most of those tornadoes occurred near the median position around 465km away from and to the southeast of the ETC center. Of those tornadoes, 68% occurred in large outbreaks of 6 or more tornadoes, where most tornadoes formed closer to and to the southeast of an ETC track as compared to small outbreak and isolated tornadoes. The spatial and relative distributions were similar across all intensity levels, though stronger tornadoes tended to have more tornadoes directly to the southeast of an ETC. Seasonal variances in tornadoes strongly corresponded with seasonal changes in the jet stream. Summer tornadoes occurred in northern portions of the US when the jet stream shifts poleward. The jet stream and ETCs are also weakest in the summer, and the weakest association was found in summer tornadoes based on their distribution relative to ETCs being more uniform towards the northeast and north-southeast directions. Winter tornadoes occurred in more southern portions of the US when the jet stream shifts equatorward, and they had a stronger association with most of the tornadoes occurring to the southeast and closer to the ETC center, aligning with a strong ETC and jet stream in the winter. Finally, tornadoes and ETCs had strong spatial covariance and showed similar linear trends, including a similar rate of change in the eastward shift, providing strong evidence that a shift in ETCs may be driving the shift in tornadoes. Furthering our understanding of the relationship between tornadoes and ETCs will help to better predict how tornadoes will change in the future based on changes in ETCs.</p>

Transarterial chemoembolization (TACE) and transarterial radioembolization (TARE) are recommended to treat patients with early or intermediate hepatocellular carcinoma (HCC). The liver maximum capacity test (LiMAx) has been supposed to predict the risk of post-interventional liver failure. We investigated the correlation of LiMAx with short term survival as primary endpoint and the occurrence of adverse events after therapy as secondary endpoint. Our study cohort prospectively included 69 patients receiving TACE (n = 57) or TARE (n = 12). LiMAx test and serological analyses were performed on the day before and 4 weeks after treatment. Hepatic and extrahepatic complications were monitored for 4 weeks. The LiMAx results were not associated with altered liver function and the occurrence of adverse events. The survival rates of patients with BCLC A with LiMAx ≤ 150 μg/kg/h were lower after 30 days (75.0 ± 15.3% vs. 100%, p = 0.011), 90 days (62.5 ± 17.7% vs. 95.8 ± 4.1%, p = 0.011) and 180 days (50.0 ± 17.7% vs. 95.8 ± 4.1%, p = 0.001) compared to those with higher LiMAx levels. The LiMAx test is not suitable to predict liver function abnormalities or the occurrence of complications 4 weeks after therapy but enables the identification of patients with early stage HCC and reduced short-term survival after treatment.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第25122号 / 理博第5029号 / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 西村 卓也, 教授 宮﨑 真一, 教授 大見 士朗 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Doctor of Philosophy / With the fast development of artificial intelligence (AI) technology, the reliability of AI needs to be investigated for confidently using AI products in our daily lives. This dissertation includes three projects introducing the statistical models and model estimation methods that can be used in the reliability analysis of AI systems. The first project analyzes the recurrent events data from autonomous vehicles (AVs). A nonparametric model is proposed to study the reliability of AI systems in AVs, and a statistical framework is introduced to evaluate the adequacy of using traditional parametric models in the analysis. The proposed model and framework are then applied to analyze AV data from four manufacturers that participated in an AV driving testing program overseen by the California Department of Motor Vehicles. The second project develops a survival model to investigate the failure times of graphics processing units (GPUs) used in supercomputers. The model considers several covariates, the spatial correlation, and the correlation among multiple types of failures. In addition, unique spatial correlation functions and a special distance function are introduced to quantify the spatial correlation inside supercomputers. The model is applied to explore the GPU failure times in the Titan supercomputer. The third project proposes a new Markov chain Monte Carlo sampler that can be used in the estimation and inference of spatial survival models. The sampler can generate a reasonable amount of samples within a shorter computing time compared with existing popular samplers. Important factors that can influence the performance of the proposed sampler are explored, and the sampler is used to analyze the Titan GPU failures to illustrate its usefulness in solving real-world problems.

This thesis Public Relations Effectiveness in the Czech Presidential Elections 2013 analyzes the effectiveness of public relations tools that have a key influence in building of positive image of candidates in political elections, and on the particular case of the Karel Schwarzenbergs election campaign in first ever presidential election in the Czech Republic. The first part deals with the theoretical definition of public relations in general and subsequently in the narrower sense in relation to politics, adaptation to the specific needs of political communication for example in endorsement or positive and negative campaigns in electoral contests. Attention is also paid to the possibilities of cooperation with the media, agenda setting and framing. In the second practical part is first introduced the background of the presidential election together with a detailed profile of Karel Schwarzenberg, followed by an analysis of his electoral campaign between August 2012 and January 2013, and in terms of effectiveness of various public relations tools that were used in the campaign and their success in projecting into the media content.