5,129 research outputs found

    UMSL Bulletin 2023-2024

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

    Reframing museum epistemology for the information age: a discursive design approach to revealing complexity

    Get PDF
    This practice-based research inquiry examines the impact of an epistemic shift, brought about by the dawning of the information age and advances in networked communication technologies, on physical knowledge institutions - focusing on museums. The research charts adapting knowledge schemas used in museum knowledge organisation and discusses the potential for a new knowledge schema, the network, to establish a new epistemology for museums that reflects contemporary hyperlinked and networked knowledge. The research investigates the potential for networked and shared virtual reality spaces to reveal new ā€˜knowledge monumentsā€™ reflecting the epistemic values of the network society and the space of flows. The central practice for this thesis focuses on two main elements. The first is applying networks and visual complexity to reveal multi-linearity and adapting perspectives in relational knowledge networks. This concept was explored through two discursive design projects, the Museum Collection Engine, which uses data visualisation, cloud data, and image recognition within an immersive projection dome to create a dynamic and searchable museum collection that returns new and interlinking constellations of museum objects and knowledge. The second discursive design project was Shared Pasts: Decoding Complexity, an AR app with a unique ā€˜anti-personalisationā€™ recommendation system designed to reveal complex narratives around historic objects and places. The second element is folksonomy and co-design in developing new community-focused archives using the community's language to build the dataset and socially tagged metadata. This was tested by developing two discursive prototypes, Women Reclaiming AI and Sanctuary Stories

    Reshaping Higher Education for a Post-COVID-19 World: Lessons Learned and Moving Forward

    Get PDF
    No abstract available

    Complexity Science in Human Change

    Get PDF
    This reprint encompasses fourteen contributions that offer avenues towards a better understanding of complex systems in human behavior. The phenomena studied here are generally pattern formation processes that originate in social interaction and psychotherapy. Several accounts are also given of the coordination in body movements and in physiological, neuronal and linguistic processes. A common denominator of such pattern formation is that complexity and entropy of the respective systems become reduced spontaneously, which is the hallmark of self-organization. The various methodological approaches of how to model such processes are presented in some detail. Results from the various methods are systematically compared and discussed. Among these approaches are algorithms for the quantification of synchrony by cross-correlational statistics, surrogate control procedures, recurrence mapping and network models.This volume offers an informative and sophisticated resource for scholars of human change, and as well for students at advanced levels, from graduate to post-doctoral. The reprint is multidisciplinary in nature, binding together the fields of medicine, psychology, physics, and neuroscience

    Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse

    Get PDF
    This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses. This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups. In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in usersā€™ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018ā€”6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena

    Quantifying the Impacts of Flash Flooding on Dominicaā€™s Material Stocks in Buildings: A GIS-based methodological framework for Small Island States

    Get PDF
    Economic growth is usually accompanied by extensive extraction of natural resources, especially in developing countries. From a ā€œmaterial-stock-flow-serviceā€ perspective, the substantial part (e.g., construction materials) of the extracted natural resources as inflows to a society get accumulated in the built environment as ā€œmaterial stocksā€ (MS). Depending on the end-use types of their containers, MS provide essential services to a society such as housing, education and transportation. When an environmental hazard strikes, MS lose their functionality due to the destruction of the physical structure of their carriers, resulting in extra construction waste that then must be cleared for recovery. To make a society more resilient to environmental hazards, which is especially important in small island states with limited natural and human resources, the knowledge of exposure of MS to hazard risk is critical. This research focuses on the quantity and spatial distribution of MS in buildings in the context of intense rainfall-triggered flash flooding in Dominica, a small island state in the Caribbean region. A Geographical Information System (GIS)-based stock-driven methodology is used to quantify four typical types of construction materials: concrete, aggregates, timber, and steel. To quantify exposed MS in buildings to flash flooding, an event-based flood model is used to generate flood inundation extents at the national scale. To investigate the degrees to which the exposed households are susceptible to the impacts of environmental hazards, this research also designs a resident survey to collect social factors contributing to household vulnerability to hazards. For 2020, the total MS in the building sector is estimated at 6,574 kt, equivalent to 91 t per capita, given Dominicaā€™s population of the year. In terms of the distributions of MS in different material categories, concrete accounts for 86% of the total MS in buildings, followed by aggregate at 7%, timber at 4% and steel at 3%. Examining the exposure of MS in buildings to flash flooding, it is found that flood events of larger magnitudes would result in more MS contained in the exposed buildings. For flash flood events with 5-year, 10-year, and 20-year return periods, the numbers of exposed buildings are 2,781, 3,030, and 3,274, respectively, which contain 17%, 18%, and 19% of the total MS in buildings in Dominica. This research demonstrates how to link the results of material stock accounting to flash flood modelling, approaching the concept of socio-economic metabolism from an environmental hazard risk perspective. Knowledge of the quantity and spatial distribution of the exposed MS in buildings can assist local governments in making cost-effective mitigation plans before a hazard event. Although the designed survey was not implemented due to travel restrictions, it is a valuable instrument to collect the information about household vulnerability to environmental hazards, which can help hazard response agencies with more-efficient rescue operations during a hazardous event

    2023-2024 Boise State University Undergraduate Catalog

    Get PDF
    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    ATR-FTIR Spectroscopy-Linked Chemometrics:A Novel Approach to the Analysis and Control of the Invasive Species Japanese Knotweed

    Get PDF
    Japanese knotweed (Reynoutria japonica), an invasive plant species, causes negative environmental and socio-economic impacts. A female clone in the United Kingdom, its extensive rhizome system enables rapid vegetative spread. Plasticity permits this species to occupy a broad geographic range and survive harsh abiotic conditions. It is notoriously difficult to control with traditional management strategies, which include repetitive herbicide application and costly carbon-intensive rhizome excavation. This problem is complicated by crossbreeding with the closely related species, Giant knotweed (Reynoutria sachalinensis), to give the more vigorous hybrid, Bohemian knotweed (Fallopia x Bohemica) which produces viable seed. These species, hybrids, and backcrosses form a morphologically similar complex known as Japanese knotweed ā€˜sensu latoā€™ and are often misidentified. The research herein explores the opportunities offered by advances in the application of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy-linked chemometrics within plant sciences, for the identification and control of knotweed, to enhance our understanding of knotweed biology, and the potential of this technique. ATR-FTIR spectral profiles of Japanese knotweed leaf material and xylem sap samples, which include important biological absorptions due to lipids, proteins, carbohydrates, and nucleic acids, were used to: identify plants from different growing regions highlighting the plasticity of this clonal species; differentiate between related species and hybrids; and predict key physiological characteristics such as hormone concentrations and root water potential. Technical advances were made for the application of ATR-FTIR spectroscopy to plant science, including definition of the environmental factors that exert the most significant influence on spectral profiles, evaluation of sample preparation techniques, and identification of key wavenumbers for prediction of hormone concentrations and abiotic stress. The presented results cement the position of concatenated mid-infrared spectroscopy and machine learning as a powerful approach for the study of plant biology, extending its reach beyond the field of crop science to demonstrate a potential for the discrimination between and control of invasive plant species
    • ā€¦
    corecore