The decoupled direct method (DDM) has been implemented in a three-dimensional (3D) air quality model in order to calculate first-order sensitivities with respect to emissions and initial and boundary concentrations. This required deriving new equations for the sensitivities from the equations of the hybrid chemistry solver and the nonlinear advection algorithm in the model. The sensitivities for the chemistry and advection steps were tested in box-model and rotating-hill simulations, respectively. The complete model was then applied to an ozone episode of the Lake Michigan region during July 7-13, 1995. The DDM was found to be highly accurate for calculating the sensitivity of the 3D model. The sensitivities obtained by perturbing the inputs (brute-force method) converged toward the DDM sensitivities, as the brute-force perturbations became small. Ozone changes predicted with the DDM sensitivities were also compared to actual changes obtained from simulations with reduced inputs. For 40% reductions in volatile organic compound and/or NOx emissions,the predicted changes correlate highly with the actual changes and are directionally correct for nearly all grid cells in the modeling domain. However, the magnitude of the predicted changes is 10-20% smaller than the actual changes on average. Agreement between predicted and actual ozone changes is better for 40% reductions in initial or boundary concentrations. Calculating one sensitivity by the DDM is up to 2.5 times faster than calculating the concentrations alone.
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http://dx.doi.org/10.1021/es0112691 | DOI Listing |
Am J Emerg Med
January 2025
Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA; Center for Outcomes Research and Evaluation, Yale University, New Haven, CT, USA.
Background: This study aimed to examine how physician performance metrics are affected by the speed of other attendings (co-attendings) concurrently staffing the ED.
Methods: A retrospective study was conducted using patient data from two EDs between January-2018 and February-2020. Machine learning was used to predict patient length of stay (LOS) conditional on being assigned a physician of average speed, using patient- and departmental-level variables.
Eur Radiol
January 2025
Laboratory of Key Technology and Materials in Minimally Invasive Spine Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objectives: To investigate how studies determine the sample size when developing radiomics prediction models for binary outcomes, and whether the sample size meets the estimates obtained by using established criteria.
Methods: We identified radiomics studies that were published from 01 January 2023 to 31 December 2023 in seven leading peer-reviewed radiological journals. We reviewed the sample size justification methods, and actual sample size used.
Health Policy
December 2024
Department of Family Medicine and Population Health (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, Belgium; Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.
Introduction: Few integrated care studies elaborate how interventions are brought to wider scale. The SCUBY project developed interventions for scale-up of an Integrated Care Package (ICP) for two common diseases - type 2 diabetes and hypertension-, comprising evidence-based roadmaps and policy dialogues. This paper's aim is to report on the process evaluation of the ICP scale-up in Belgium.
View Article and Find Full Text PDFAm J Perinatol
January 2025
Ob-gyn, University of Minnesota System, Minneapolis, United States.
Background: Obesity is associated with an increased risk of stillbirth and neonatal death. Since the publication of A Randomized Trial of Induction Versus Expectant Management (ARRIVE) in 2018, there was an increase in 39 weeks deliveries. The objective of this study was to evaluate the trends in perinatal mortality by BMI category from 2015 to 2020.
View Article and Find Full Text PDFCortex
December 2024
Cognitive Neuroscience, Institute of Neuroscience & Medicine (INM-3), Forschungszentrum Jülich, Jülich, Germany; Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
The precise cognitive mechanisms underlying spatial neglect are not fully understood. Recent studies have provided the first evidence for aberrant behavioral and electrophysiological prediction and prediction error responses in patients with neglect, but also in right-hemispheric (RH) stroke patients without neglect. For prediction-dependent attention, as assessed with Posner-type cueing paradigms with volatile cue-target contingencies, studies in healthy volunteers point to a crucial role of the right temporo-parietal junction (rTPJ) - as part of a network commonly disrupted in neglect.
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