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Quantifying spatial-temporal stability to drought in a semi-arid shortgrass prairie ecosystem
Get PDFDrought is known to cause negative ecological impacts in grasslands, with areas prone to drought expected to experience increases in both severity and frequency in the coming years. Cimarron County, Oklahoma is located at the westernmost extent of the Oklahoma panhandle and has a history of intense drought events, including those of the Dust Bowl era. Since 2005, there have been repeated droughts in the county, including a single event lasting from 2011-2015. We analyzed remote sensing data to understand the spatial and temporal stability of grassland structure (Enhanced Vegetation Index) and function (Gross Primary Productivity) within Cimarron County with reference to drought. Drought was quantified using the Standardized Precipitation Index, derived from a remotely sensed precipitation dataset. Stability was quantified by applying the BFAST (Breaks for Additive Season and Trend) algorithm to determine structural breaks within each metric’s time series, and by calculating the coefficient of variation for each pixel across the county. Temporal data show that while these grasslands display characteristics of low stability at the onset of drought, they exhibit consistent positive trends in EVI and GPP following each drought event, recovering, and sometimes eclipsing their pre-drought levels. Spatial data indicate high spatial heterogeneity in EVI and GPP variability across the county, and a relatively low but significant correlation with drought variability. These analyses suggest while drought has a significant effect on grassland stability, there are likely many other drivers, and while the onset of drought greatly effects grassland structure and function, they are consistently able to rebound and regain their pre-drought levels. Although these grasslands are impacted by drought, their ability to recover is rapid. Likely, plant composition or drought events are taking place during times of dormancy and mediating these responses, when plants may be less affected
Assessing Precipitation Delineation Capabilities of Spaceborne Radars
Get PDFSpaceborne radars uniquely measure, provide the finest depiction of, and give the most accurate estimate of precipitation globally from space. The Global Precipitation Measurement (GPM) mission dual-frequency precipitation radar (DPR) is the successor to the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR), expanding on its capabilities with a dual-frequency radar and coverage into the midlatitudes. The consistent ability to detect various precipitation magnitudes across satellite missions is critical to the study of global precipitation over various time periods. The precipitation delineation capabilities of spaceborne radars are characterized as functions of their reflectivity and the corresponding precipitation magnitude from the reference Ground Validation Multi-Radar/Multi-Sensor (GV-MRMS) over CONUS. The Heidke Skill Score, a measure of skill with respect to random chance, is computed to synthesize the capabilities of the spaceborne radars. This enables a finer depiction and interpretation of spaceborne radar capabilities than the bulk metrics widely used in the literature. Skill is more sensitive to changes in rain rate at lower rain rates and changes in reflectivity at higher rain rates. The TRMM-PR and GPM-DPR best delineate moderate precipitation while the GPM-KuPR detects precipitation with low to moderate skill. While both the TRMM-PR and GPM-DPR perform better than GPM-KuPR, the TRMM-PR performs better at lower reflectivity thresholds while the GPM-DPR performs better at higher reflectivity thresholds. Certain factors do not have a significant impact on the overall skill. Others have a significant impact, but the number of cases were small and did not greatly impact the overall skill. While the GPM-DPR struggles with the detection of precipitation, and the TRMM-PR performs the best overall, both the GPM-DPR and TRMM-PR have good delineation capabilities
Informed, Interactive, and Interpretable Machine Learning for Forward Kinematics of Robot Arms
Get PDFMachine learning (ML) is becoming increasingly sought after in diverse domains. Unfortunately for this objective, most ML research has focused too much on improving performance on evaluation metrics such as accuracy to the exclusion of other qualities like interpretability. However, to make important decisions, ML models need to be interpretable. The goal of interpretable machine learning (IML) is to build models that are understandable to users. One approach to IML is to have meaning to each of its components. Thus, IML aids in building models that are trustworthy and improve fairness in artificial intelligence. In informed ML, prior knowledge is explicitly integrated into the ML pipeline/training process. Interactive ML enables ML models to be interactively steered by people and is more advantageous for the tasks where human knowledge is needed in the analysis process. In this work, we proposed the I3 framework that brings together the ideas of being informed, interactive, and interpretable. In this work we reintroduced, highlighted, and established the larger picture to one approach in the context of being informative, interactive, and interpretable. Pei et al.’s work is a strong candidate and is one instantiation of I3 framework. In this work, Pei et al.’s work is used to approximate the kinematics of a robotic arm using interpretable artificial neural networks (ANNs). Pei et al.’s work is developed using applied mathematics for engineering mechanics and is based on approximating nonlinear functions where domain knowledge and visually observable features of the data are used to design ANNs. Pei et al.’s work is informed as scientific knowledge through applied mathematics, engineering and world knowledge through vision are represented in the form of algebraic equations, logic rules, and human feedback. The represented knowledge helps to narrow down the hypotheses for network architecture. Pei et al.’s work involve integrating prior knowledge obtained by examining the dominant features of the data. Then the interactive process involves choosing an appropriate basis function from the visualization of the function to be approximated; this helps in designing the ANN architecture and its initial values. Interpretability is the result of being informed and interactive. After analyzing Pei et al.’s work, we present a feasibility study approximating the kinematics of a simplified robotic arm. We extend Pei et al.’s work and its use for a different application, noting the challenges that arise while extending this work to more inputs and to multiple hidden layers. This approach leads to training success, good generalization, and interpretability
Sojourners’ Identity Transformation As A Function Of Cross-Cultural Adaptation: A Communication Model Of Multicultural Identity Development
Get PDFThis dissertation explored the multicultural identity(ies) development of sojourners as a function of their cross-cultural adaptation (CCA). Several theories of CCA, identity, and identity development are discussed and were used as a theoretical framework and explanatory mechanisms for investigating changes in sojourners’ identity. Three research questions were proposed to examine CCA experiences and the development of a multicultural identity. An interpretivist approach to qualitative research in the form of individual in-depth interviews with Davis-United World College students (N = 32) was employed. Data were analyzed via constant comparative analysis. Findings revealed that Davis-UWC students underwent multiple adaptation that shaped their multicultural identity(ies) development. Several communicative events that shaped the development of their multicultural identity(ies) were identified as were ways in which identity(ies) was/were enacted in communication practices. Based on these findings, the dissertation advanced a Communication Model of Multicultural Identity Development (CMMID) that is detailed along with a discussion of the findings and their implications for CCA and intercultural communication research
An Epistemology for Listening Across Religious, Cultural, and Political Divides
Get PDFThe rhetoric of cultural populism exploits and exacerbates the natural tendency for human communities to define their own identities by contrasting themselves with imagined Others. This heightens the already formidable epistemic challenge of understanding such Others. This chapter proposes an epistemology of intergroup understanding that is relational, recursive, eschatological, and sacrificial. It argues that coming to understand Others across group boundaries requires an ongoing process of listening and a willingness to sacrifice aspects of one’s own identity that prove to be grounded in self-serving misconstruals of the Other. Such listening requires open-mindedness, empathy, epistemic justice, epistemic charity, intellectual humility, and epistemic selflessness, which are therefore crucial to the functioning of a pluralistic society, especially one that is polarized along religious, cultural, or political lines.This is the author’s original preprint manuscript. Final published version in Engaging Populism: Democracy and the Intellectual Virtues, ed. Gregory R. Peterson, Michael C. Berhow, and George Tsakiridis, 185–214 (Palgrave, 2022). https://doi.org/10.1007/978-3-031-05785-4_10Ye
Japanese Americans at Heart Mountain: Networks, Power, and Everyday Life
No full textOn August 8, 1942, 302 people arrived by train at Vocation, Wyoming, to become the first Japanese American residents of what the U.S. government called the Relocation Center at Heart Mountain. In the following weeks and months, they would be joined by some 10,000 of the more than 120,000 people of Japanese descent, two-thirds of them U.S. citizens, incarcerated as “domestic enemy aliens” during World War II. Heart Mountain became a town with workplaces, social groups, and political alliances—in short, networks. These networks are the focus of Saara Kekki’s Japanese Americans at Heart Mountain.Interconnections between people are the foundation of human societies. Exploring the creation of networks at Heart Mountain, as well as movement to and from the camp between 1942 and 1945, this book offers an unusually detailed look at the formation of a society within the incarcerated community, specifically the manifestation of power, agency, and resistance. Kekki constructs a dynamic network model of all of Heart Mountain’s residents and their interconnections—family, political, employment, social, and geospatial networks—using historical “big data” drawn from the War Relocation Authority and narrative sources, including the camp newspaper Heart Mountain Sentinel. For all the inmates, life inevitably went on: people married, had children, worked, and engaged in politics. Because of the duration of the incarceration, many became institutionalized and unwilling to leave the camps when the time came. Yet most individuals, Kekki finds, took charge of their own destinies despite the injustice and looked forward to the day when Heart Mountain was behind them.Especially timely in its implications for debates over immigration and assimilation, Japanese Americans at Heart Mountain presents a remarkable opportunity to reconstruct a community created under duress within the larger American society, and to gain new insight into an American experience largely lost to official history.Saara Kekki is Post-doctoral Researcher at the University of Helsinki in Finland and coeditor of Bridging Cultural Concepts of Nature: Indigenous People and Protected Spaces of Nature.Funding provided by the Andrew W. Mellon Foundation as part of the Sustainable History Monograph Pilot
Pathways to Elevating Indigenous Voices in Anthropology
Get PDFAmerican Anthropology has a foundation of using Indigenous people, often Native Americans, as research objects. As a Navajo researcher and anthropologist in the 21st century, I believe that this foundation of literature and research presents an ideal landscape for Indigenous voices to be heard, both because of the longstanding history with and objectification of Indigenous people. The work I share with you in this dissertation aims to acknowledge unfortunate histories and move those discussions forward in productive ways that benefit Native American people. Anthropology, and knowledge in general, have been used to empower colonialism and displace Native communities; Scientists today must repair colonial relationships by producing knowledge in partnership with study communities
Contribution of exercise-onset hypotension to cerebrovascular hemodynamics during an exercise transition
Get PDFRecent evidence suggests cerebral blood flow (CBF) responds to moderate intensity exercise after ~ 40s when using a monoexponential model to characterize CBF kinetics. Considering the brain’s reliance on blood flow for O2 and substrate delivery during increased metabolic demands, this delay is concerning. Especially when other physiological systems that are less dependent on blood flow for immediate energy needs respond to exercise within 10s (e.g. VO2 kinetics, peripheral blood flow kinetics). Possibly this delay can be explained by a brief, transient exercise-onset-hypotension that occurs during a rest-to-exercise transition.
Purpose: The present study aimed to identify if CBF experiences an initial response not identified with a monoexponential model, and if that response is related to exercise-onset-hypotension at the start of exercise.
Methods: 23 total subjects (10 Females, 23.9 ± 3.3 yrs) completed a rest-to-exercise transition (2 minutes seated baseline followed by 3 minutes of 50W cycling) and an exercise-to-exercise transition (3 minutes of 50W cycling followed by 3 minutes of 75W cycling) on a recumbent cycle ergometer. Middle cerebral artery velocity (MCAv) was filtered and averaged into 3s bins and fit to a monoexponential model. Time delay (TD), tau (τ) and mean response time (MRT = TD + τ) were obtained from the model. Cerebral perfusion pressure (CPP = mean arterial pressure – Hydrostatic column) and cerebral vascular conductance index (CVCi = MCAv/CPP) were filtered and averaged into 3s bins as well for analysis. Several subjects (N=8) exhibited a rapid response to exercise (TD ≤ 1.5s; “Fast”) and were compared against subjects with longer TDs (TD > 3s; “Slow”). Comparisons were made using independent t-tests.
Results: All data are mean±SD. A light-intensity exercise transition (50W) elicited a TD = 19.7 ± 18.7s, τ = 29.7 ± 23.0s, and MRT = 49.1 ± 23.7s. The strongest correlation between variables was MCAv nadir (MCAvN) and TD (-0.560). MCAvN (-4.1 ± 5.5 Δcm/s) and CPP reached a nadir (CPPN = -13.5 ± 10.4 ΔmmHg) at similar times (16.5 ± 15.3 vs. 10.3 ± 4.5s, p = 0.07). CVCi reached a maximum (CVCiM) which occurred after MCAvN (46.9 ± 57.1s). CPP was able to describe the variance in MCAvN similarly to a more complicated model involving cardiac output (Q), total peripheral resistance (TPR), end-tidal CO2 (EtCO2), and CVCi (R2a = 0.36, AIC = 140.44 vs. R2a = 0.25, AIC 140.7, Full model vs. CPP only model). The Slow and Fast groups had differences in TD (30.4 ± 14.6 vs. 1.5 ± 0.0s, p < 0.001), MCAvN (-7.3 ± 3.4 vs. 2.0 ± 2.6 Δcm/s, p < 0.001), and CPP during MCAvN (-11.3 ± 11.8 vs. 3.7 ± 3.2 ΔmmHg, p < 0.001).
Discussion: Our data shows MCAvN occurred at the same time TD, and that TD is directly correlated with MCAvN (-0.560). From this data, CPP was able to explain a large portion of the variance in MCAvN. These data suggest that using a monoexponential model attributes the drop in MCAv at the start of exercise as a TD. This is further exemplified with the comparisons between Slow and Fast groups. The Slow group had a larger MCAvN and a predictable longer TD compared to the Fast group. If this type of analysis is to be used on disordered individuals, a better understanding of cerebrovascular mechanisms taking place at the start of exercise is needed to properly identify disordered CBFv responses to exercise onset