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    Patient and Hospital Characteristics Associated with Admission Among Patients With Minor Isolated Extremity Firearm Injuries: A Propensity-Matched Analysis by Arielle C. Thomas, MD, MPH, MS, Regina Royan, MD, MPH, Avery B. Nathens, MD, PhD, Brendan T. Campbell, MD, MPH, Susheel Reddy, MPH, Sarabeth Spitzer, MD, Doulia Hamad, MD, Angie Jang, BA, Anne M. Stey, MD, MSc

    Published 2024-06-01
    “…This was an observational retrospective cohort study of minor isolated extremity firearm injury captured in the Healthcare Cost and Utilization Project State Inpatient and Emergency Department Databases in 6 states (New York, Arkansas, Wisconsin, Massachusetts, Florida, and Maryland) from 2016 to 2017 among patients aged 16 years or older. …”
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  3. 18603
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    Using Hyperspectral Imaging and Principal Component Analysis to Detect and Monitor Water Stress in Ornamental Plants by Van Patiluna, James Owen, Joe Mari Maja, Jyoti Neupane, Jan Behmann, David Bohnenkamp, Irene Borra-Serrano, José M. Peña, James Robbins, Ana de Castro

    Published 2025-01-01
    “…This study aims to investigate the spectral responses of four ornamental plant taxa—<i>Rosa</i> hybrid (rose), <i>Itea virginica</i> (itea), <i>Spiraea nipponica</i> (spirea), and <i>Weigela florida</i> (weigela)—under varying levels of water stress using hyperspectral imaging and principal component analysis (PCA). …”
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    Machine Learning-Based Prediction of Ecosystem-Scale CO<sub>2</sub> Flux Measurements by Jeffrey Uyekawa, John Leland, Darby Bergl, Yujie Liu, Andrew D. Richardson, Benjamin Lucas

    Published 2025-01-01
    “…The model showed excellent performance testing on sites that are ecologically similar to other sites (the Mid Atlantic, New England, and the Rocky Mountains), but poorer performance at sites with fewer ecological similarities to other sites in the data (Pacific Northwest, Florida, and Puerto Rico). The results show strong potential for machine learning-based models to make more skillful predictions than state-of-the-art process-based models, being able to estimate the multi-year mean carbon balance to within an error ±50 gCm<sup>−2</sup>y<sup>−1</sup> for 29 of our 44 test sites. …”
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    Síndrome de Sheehan: marcador de subdesarrollo by Alfredo Jácome Roca

    Published 2024-12-01
    “…Al momento del diagnóstico, la clínica suele ser florida. Solo hubo un estudio en la India que exploró la prevalencia; además, hubo series menos grandes, pero con casos bien estudiados y con tecnología actual. …”
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