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Background: Cognitively impaired older adults living in the community have been vulnerable to the effects of COVID-19 confinement. The current study’s objectives were to examine the prevalence of loneliness in such adults along with impact of COVID-19 on neuropsychiatric symptoms and functional status. Methods: A cross-sectional study was conducted in community dwelling cognitively impaired older Veterans (N=41). Demographic data such as age, gender, race, and rurality were collected. Loneliness data were collected with the 3-item Loneliness Questionnaire. Cognition was assessed with the Tele-Montreal Cognitive Assessment (T-MoCA) and functional status of instrumental activities of daily living was assessed with the Functional Activities Questionnaire (FAQ). Neuropsychiatry symptoms including severity and distress were collected using the Neuropsychiatric Inventory (NPI), and change during COVID was also recorded for each symptom. Results: Demographic characteristics included: mean age of 71.9 (±8.6) years, 95.1% male, 46.3% rural, 75.6% Caucasian, and 19.5% African American. Loneliness was prevalent in most participants (62.5%). T-MoCA and FAQ mean scores were 15.1 (±4.5) and 10.0 (±8.6), respectively. Mean NPI total severity and total distress were 8.4 (±5.9) and 11.4 (±8.5), respectively. Irritability was most frequently reported symptom (65%), followed by agitation (57.5%), anxiety (55%), depression (50%), and night-time behavior (50%). A majority of the participants reported worsening of neuropsychiatric symptoms during COVID (71.1%). Among those that reported worsening neuropsychiatric symptoms, 70.4% noted an increase in ≥ two symptoms. Conclusion: Older adults with pre-existent cognitive impairment may be at high risk for loneliness and worsening of neuropsychiatric symptoms during the COVID pandemic.

Many distinct combinations of three-dimensional shape, surface material, illumination, and optical focus can induce similar patterns of luminance gradients on the retina. The present thesis examines several conditions in which the visual system fails to correctly disentangle these physical sources of image structure, and uses these cases of misperception to assess how the visual system distinguishes diffuse shaded shape from specular reflections and defocus blur. Chapter 2 investigated how physical variations in surface reflectance can transform our perception of 3D shape, and vice versa. Increments in the specularity of a deformed planar terrain led to exaggerated percepts of its relief, particularly for surfaces with low curvature. Increments in physical relief conversely led to greater percepts of gloss for the same surfaces. Chapter 3 assessed similar misperceptions in the domain of optical defocus blur. Foreground blur induced by lens defocus was misattributed to a change in material and 3D shape when level cut contours in the background remained sharp. Conversely, fully focused images of a shaded terrain with no level cut contours were perceived as defocused. Chapter 4 tested whether the focus cues generated by level cut contours depend on their resemblance to the convex self-occluding rims of shaded surfaces. Masks that produced stronger rim-like correlations between contour orientation and shading luminance led to greater percepts of image focus and more reliable percepts of illumination direction and 3D shape, particularly when that shape appeared convex. Finally, Chapter 5 investigated how other sources of high spatial frequencies provide cues to gradient focus. Deformed shaded terrains with sharper specular reflections were perceived as more focused, but surfaces with mesostructural relief were only perceived as coherent and focused in the presence of intermediate relief scales that bridged the smooth surface deformations and fine mesostructure.

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives.

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives.

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives. Fil: Morrison, Kathleen D.. University of Pennsylvania; Estados Unidos Fil: Hammer, Emily. University of Pennsylvania; Estados Unidos Fil: Boles, Oliver. University of Pennsylvania; Estados Unidos Fil: Madella, Marco. University of the Witwatersrand; Sudáfrica. Universitat Pompeu Fabra; España Fil: Whitehouse, Nicola. University of Glasgow; Reino Unido Fil: Gaillard, Marie-Jose. Linnaeus University; Suecia Fil: Bates, Jennifer. University of Pennsylvania; Estados Unidos Fil: Linden, Marc Vander. Bournemouth University; Sudáfrica Fil: Merlo, Stefania. University of the Witwatersrand; Sudáfrica Fil: Yao, Alice. University of Chicago; Estados Unidos Fil: Popova, Laura. Arizona State University; Estados Unidos Fil: Hill, Austin Chad. University of Pennsylvania; Estados Unidos Fil: Antolin, Ferran. Universiat Basel; Suiza Fil: Bauer, Andrew. University of Stanford; Estados Unidos Fil: Biagetti, Stefano. University of the Witwatersrand; Sudáfrica. Universitat Pompeu Fabra; España Fil: Bishop, Rosie R.. University of Stavanger; Noruega Fil: Buckland, Phillip. Universidad de Umea; Suecia Fil: Cruz, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Unidad Ejecutora en Ciencias Sociales Regionales y Humanidades. Universidad Nacional de Jujuy. Unidad Ejecutora en Ciencias Sociales Regionales y Humanidades; Argentina Fil: Dreslerová, Dagmar. Institute Of Archaeology Of The Academy Of Sciences Of The Czech Republic; Hungría Fil: Dusseldorp, Gerrit. Leiden University; Países Bajos Fil: Ellis, Erle C.. University of Maryland; Estados Unidos. University Of Johannesburg; Sudáfrica Fil: Filipovich, Ruben Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Bio y Geociencias del NOA. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Museo de Ciencias Naturales. Instituto de Bio y Geociencias del NOA; Argentina Fil: Foster, Thomas. University of Tulsa; Estados Unidos Fil: Hannaford, Matthew J.. Lincoln University.; Nueva Zelanda Fil: Harrison, Sandy P.. University of Reading; Reino Unido Fil: Hazarika, Manjil. Cotton University; India Fil: Herold, Hajnalka. University of Exeter; Reino Unido Fil: Hilpert, Johanna. Universitat zu Köln; Alemania Fil: Kaplan, Jed O.. The University Of Hong Kong; Hong Kong Fil: Kay, Andrea. Max Planck Institute For The Science Of Human History; Alemania Fil: Goldewijk, Kees Klein. Utrecht University; Países Bajos Fil: Kolár, Jan. Masaryk University; República Checa Fil: Kyazike, Elizabeth. Kyambogo University; Uganda Fil: Laabs, Julian. University of Bern; Suiza Fil: Lancelotti, Carla. Universitat Pompeu Fabra; España Fil: Lane, Paul. University of the Witwatersrand; Sudáfrica. University of Cambridge; Estados Unidos Fil: Lawrence, Dan. University of Durham; Reino Unido Fil: Lewis, Krista. University of Arkansas; Estados Unidos Fil: Lombardo, Umberto. University of Bern; Suiza Fil: Lucarini, Giulio. Consiglio Nazionale delle Ricerche; Italia. University of Naples; Italia Fil: Arroyo Kalin, Manuel. Colegio Universitario de Londres; Reino Unido Fil: Marchant, Rob. University of York; Reino Unido Fil: Mayle, Francis. University of Reading; Reino Unido Fil: McClatchie, Meriel. University College; Irlanda Fil: McLeester, Madeleine. Dartmouth College; Estados Unidos Fil: Mooney, Scott. Unsw Sydney; Australia Fil: Moskal-Del Hoyo, Magdalena. Wladyslaw Szafer Institute Of Botany Of The Polish Academy Of Sciences; Polonia Fil: Navarrete, Vanessa. Universitat Autònoma de Barcelona; España Fil: Ndiema, Emmanuel. National Museums Of Kenya; Kenia Fil: Neves, Eduardo Góes. Universidade de Sao Paulo; Brasil Fil: Nowak, Marek. Jagiellonian University; Polonia Fil: Out, Welmoed A.. Moesgaard Museum; Dinamarca Fil: Petrie, Cameron. Universitat Pompeu Fabra; España. University of Cambridge; Estados Unidos Fil: Phelps, Leanne N.. Royal Botanic Gardens; Reino Unido. University of Edinburgh; Reino Unido Fil: Szakonyi, Zsolt. Eötvös University; Hungría Fil: Rostain, Stéphen. Centre National de la Recherche Scientifique; Francia Fil: Russell, Thembi. University of the Witwatersrand; Sudáfrica Fil: Sluyter, Andrew. Louisiana State University; Estados Unidos Fil: Styring, Amy K.. University of Oxford; Reino Unido Fil: Tamanaha, Eduardo. The Mamirauá Sustainable Development Institute; Brasil Fil: Thomas, Evert. The Alliance of Bioversity International and CIAT; Perú Fil: Veerasamy, Selvakumar. Tamil University; India Fil: Welton, Lynn. University of the Witwatersrand; Sudáfrica Fil: Zanon, Marco. Institute of Pre- and Protohistoric Archaeology; Alemania

Realistically, organizational and/or system efficiency performance is dynamic, non-linear, and a function of multiple interactions in production. However, in the efficiency literature, system performance is frequently evaluated considering linear combinations of the input/output variables, without explicitly taking into account the interactions and feedback mechanisms that explain the causes of efficiency behavior, the dynamic nature of production, and non-linear combinations of the input/output variables. Consequently, policy decisions based on these results may be sub-optimized because the non-linear relationships among variables, causal relationships, and feedback mechanisms are ignored. This research takes the initial steps of evaluating system efficiency performance in a dynamic environment, by relating the factors that effect system efficiency performance to the policies that govern it. First, this research extends the concepts of the static production axioms into a dynamic realm, where inputs are not instantaneously converted into outputs. The relationships of these new dynamic production axioms to the basic behaviors associated with system dynamics structures are explored. Second, this research introduces a methodological approach that combines system dynamics modeling with the measurement of productive efficiency. System dynamics is a modeling paradigm that evaluates system policies by exploring the causal relationships of the important elements within the system. This paradigm is coupled with the fundamental assumptions of production theory in order to evaluate the productive efficiency of a production system operating within a dynamic and non-linear environment. As a result, a subsystem within the system dynamics model is introduced that computes efficiency scores based on the fundamental notions of productive efficiency. The framework's ability to combine prescriptive and descriptive modeling characteristics, as well as dynamic and combinatorial complexity, can potentially have a greater impact on policy decisions and how they affect system efficiency performance. Finally, the utility of these concepts is demonstrated in an implementation case study. This methodology generates a prescriptive dynamical production frontier which defines the optimal production resources required to satisfy system requirements. Additionally, the dynamical production frontier allows for analysis for comparisons between options during a transient period, insight into possible unintended consequences, and the ability to forecast optimal times for introducing system or process improvements. Ph. D.