4,297 research outputs found

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Graduate Catalog of Studies, 2023-2024

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    Acceptability of speed limits and other policy measures in German cities

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    An increasing number of German cities currently demand the Federal Government to empower cities to implement 30 kph speed limits at their own discretion. Setting area-wide 30 kph as the maximum speed, as already installed in many other European cities, could therefore soon become a viable policy option in Germany. This thesis conducts a stated choice (SC) experiment to determine the acceptability of such area-wide standard 30 kph speed limits compared to the acceptability of the expansion of shared space zones, costs for inner-city on-street car parking and public transport ticket fares. Combining the policies as attributes in an unlabeled experiment allows to juxtapose the policies in terms of their relative importance for the respondents’ choice decision. 129 adults from German cities with more than 100,000 inhabitants participated in an online survey during September 2022. The results show that respondents evaluate the introduction of standard 30 kph speed limit in the city center as utility increasing compared to the prevalent status quo with standard 50 kph. Setting a standard 30 kph speed limit in the whole city also has a positive parameter in the base model, but does not significantly influence the respondents’ utility. The expansion of shared space seems to have no relevant effect on the choice decision of respondents. Higher ticket fares for public transport show to be utility decreasing for respondents of this study, whereas an increase in car parking costs is assessed positively. Clear differences in the policy assessment of different subgroups of respondents can be observed. In line with literature, city-wide implementation of a standard 30 kph speed limit shows low acceptability among the group of frequent car users. In turn, voters of mayoral candidates for the Green Party (BĂŒndnis 90/Die GrĂŒnen) or Left Party (Die Linke) expect a positive effect on their personal utility when a standard 30 kph speed limit is established in the whole city or in the city center only. Respondents’ gender does not seem to affect the assessment of 30 kph speed limit policy

    Disinterested or discouraged? : the gender gap in political interest.

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    Defence date: 28 June 2019Examining Board: Prof. Alexander Trechsel, University of Luzern, former European university Institute (Supervisor); Prof. Marta Fraile, Instituto de Bienes y PolĂ­ticas PĂșblicas – Consejo Superior de Investigaciones CientĂ­ficas, former European University Institute (Co-Supervisor); Prof. Susan Banducci, University of Exeter; Prof. Hilde CoffĂ©, University of BathThis dissertation examines gender differences in political interest. It draws from scholarship in political science, sociology and communication, amongst other disciplines, to explore the drivers of such pervading differences. The key argument of this thesis is that gender differences (or gender gaps), both regarding political orientations and political participation, are the product of gendered social norms and differences in men and women’s socio-economic status. Despite advances in gender equality in Western societies in the last decades, women remain the primary care-providers while men focus on the provision of resources. The thesis consists of three empirical chapters, each addressing a distinct puzzle regarding the object of difference, their development over the lifespan and the context in which they develop. In the first paper (chapter 2), I argue that men and women relate differently to politics, and this is reflected in their interest not as a matter of level (how interested they are) but of the object of interest (women are interested in other issues). In the second paper (chapter 3) I argue that socialization is at the heart of the existence of a substantial gender gap in political interest from an early age. These gender differences in the political realm are further amplified during the transition to adulthood. The third paper (chapter 4) turns to contextual factors, precisely that the absence of women in media as agents of the news contributes to hindering women’s interest in politics as they lack figures to identify with. Despite the limited attention of the scholarship to media, it is a relevant contextual factor that vehiculates many citizens’ interactions with the political realm (but also with financial affairs or other social events), so the events reported and how they are framed are crucial for the political formation of citizens

    New party entry and political engagement : electoral turnout and satisfaction with democracy

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    Defence date: 15 June 2023Examining Board: Prof. Hanspeter Kriesi, (European University Institute, supervisor); Prof. Elias Dinas, (European University Institute); Prof. Ruth Dassonneville, (University of MontrĂšal); Prof. Chris Anderson, (London School of Economics and Political Science)The last two decades have seen a surge in the institutionalization of new political parties, yet low levels of political engagement are persistent in many Western democracies. This raises questions about whether new parties can effectively channel political discontent and promote participation. This thesis argues that new party entry has distinct implications for different forms of political engagement. While new parties can increase electoral participation, they can also reinforce democratic dissatisfaction in affectively polarized environments. The empirical chapters provide evidence to support these arguments. Chapter 2 demonstrates that obtaining parliamentary representation does not significantly increase satisfaction with democracy and even reinforces political discontent among anti-establishment radical party voters. Chapter 3 introduces the concept of disruptive elections and shows that rapid electoral shifts can hinder changes in democratic satisfaction by introducing uncertainty into the government formation process. Chapter 4 proposes that considering an in-group/out-group logic is critical to understanding post-electoral changes in satisfaction with democracy among affectively polarized voters. It provides evidence that the establishment party win fosters political discontent among radical party voters despite electoral success. Finally, chapter 5 offers causal evidence that new party entry increases electoral turnout. These findings contribute to the growing literature on the effects of electoral change on political attitudes and behavior and highlight concerning implications for normative democratic theory. While new political parties may bring new forms of engagement, they can also exacerbate polarizing competition patterns that put democracy at risk. Ultimately, their impact depends on the specific conditions that led to their entry, urging us to consider ways to incorporate new political demands while reducing partisan animosity

    Current Challenges in the Application of Algorithms in Multi-institutional Clinical Settings

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    The Coronavirus disease pandemic has highlighted the importance of artificial intelligence in multi-institutional clinical settings. Particularly in situations where the healthcare system is overloaded, and a lot of data is generated, artificial intelligence has great potential to provide automated solutions and to unlock the untapped potential of acquired data. This includes the areas of care, logistics, and diagnosis. For example, automated decision support applications could tremendously help physicians in their daily clinical routine. Especially in radiology and oncology, the exponential growth of imaging data, triggered by a rising number of patients, leads to a permanent overload of the healthcare system, making the use of artificial intelligence inevitable. However, the efficient and advantageous application of artificial intelligence in multi-institutional clinical settings faces several challenges, such as accountability and regulation hurdles, implementation challenges, and fairness considerations. This work focuses on the implementation challenges, which include the following questions: How to ensure well-curated and standardized data, how do algorithms from other domains perform on multi-institutional medical datasets, and how to train more robust and generalizable models? Also, questions of how to interpret results and whether there exist correlations between the performance of the models and the characteristics of the underlying data are part of the work. Therefore, besides presenting a technical solution for manual data annotation and tagging for medical images, a real-world federated learning implementation for image segmentation is introduced. Experiments on a multi-institutional prostate magnetic resonance imaging dataset showcase that models trained by federated learning can achieve similar performance to training on pooled data. Furthermore, Natural Language Processing algorithms with the tasks of semantic textual similarity, text classification, and text summarization are applied to multi-institutional, structured and free-text, oncology reports. The results show that performance gains are achieved by customizing state-of-the-art algorithms to the peculiarities of the medical datasets, such as the occurrence of medications, numbers, or dates. In addition, performance influences are observed depending on the characteristics of the data, such as lexical complexity. The generated results, human baselines, and retrospective human evaluations demonstrate that artificial intelligence algorithms have great potential for use in clinical settings. However, due to the difficulty of processing domain-specific data, there still exists a performance gap between the algorithms and the medical experts. In the future, it is therefore essential to improve the interoperability and standardization of data, as well as to continue working on algorithms to perform well on medical, possibly, domain-shifted data from multiple clinical centers

    Neighbourhood Socioeconomic Disparity in Exposure to Preterm Birth Risk During the Pandemic: Secondary Analysis of Pregnancy During the Pandemic Cohort

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    Background: Preterm birth (PTB) is defined as a live birth before 37 weeks of gestation and remains a major public health concern, affecting an estimated 15 million births annually with a global prevalence of 11%. Socioeconomic disparities play a crucial role in PTB rates, with both individual- and neighborhood-level factors contributing. Stress response pathway has been identified as a key mechanism in the relationship between neighborhood socioeconomic status (nSES) and PTB risk. As such, the new challenges added due to the COVID-19 pandemic, such as disruption to the support networks and increased psychosocial distress for pregnant individuals, were expected to increase PTB rates. However, studies found lack of change or even decrease in the incidence during this period. It is suggested that such counter intuitive findings are due to lack of consideration for the differential exposure to the pandemic-related hardships based on nSES. Therefore, the primary aim of the present study is to test whether a measure of objective pandemic hardship and psychological distress mediate the relationship between nSES and PTB. Methods: Present study is a secondary analysis of the data collected from a prospective longitudinal cohort study, Pregnancy during the Pandemic (PdP). Two serial mediation path models with a measure of baseline objective pandemic hardship and psychological distress included as mediators between nSES and PTB/gestational age (GA) were tested. Results: In both models, the main indirect pathway of interest from nSES to pandemic objective hardship, psychological distress, then PTB/GA was non-significant with minimal effect. Secondary indirect pathway of interest from pandemic objective hardship to psychological distress then PTB/GA was significant in both models while controlling for months into the pandemic at birth and baseline sociodemographic characteristics. Discussion: The present paper is the first to test a comprehensive model of the role of nSES on PTB risk with an explicit measure of pandemic objective hardship and psychological distress included as mediators. While the main indirect serial mediation pathway was non-significant, partial support for the proposed mechanism was observed where increase in pandemic-related hardship elevated psychological distress, which then heightened the risk of PTB risk and shortened gestational age at birth

    Model farm services centers in Khyber Pakhtunkhwa: Evaluation and the way forward

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    The sub-national Government of Khyber Pakhtunkhwa in Pakistan enacted Farm Services Centers Act, 2014, to establish Model Farm Services Centers (MFSCs) and Farm Services Centers as “one stop-shop” based on public-private partnership principle to strengthen extension system. The aim of these Centers is to empower small farmers at a platform to enhance their knowledge and skills and availability of quality agricultural inputs as stipulated in Section 4(g) of the Act, 2014, that each FSC shall “purchase certified seed, fertilizers, animal husbandry services, quality veterinary heath care services and medicines, farm machinery, expertise and technology for provision to the members who are registered with the Centre on affordable rates in comparison to open market rates”. The objective is to improve rural livelihoods, and development of the rural economy

    Development of an R package to learn supervised classification techniques

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    This TFG aims to develop a custom R package for teaching supervised classification algorithms, starting with the identification of requirements, including algorithms, data structures, and libraries. A strong theoretical foundation is essential for effective package design. Documentation will explain each function’s purpose, accompanied by necessary paperwork. The package will include R scripts and data files in organized directories, complemented by a user manual for easy installation and usage, even for beginners. Built entirely from scratch without external dependencies, it’s optimized for accuracy and performance. In conclusion, this TFG provides a roadmap for creating an R package to teach supervised classification algorithms, benefiting researchers and practitioners dealing with real-world challenges.Grado en Ingeniería Informátic
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