Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts

Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in using satellites to detect fire locations further provides the opportunity to use measurements to improve fire spread forecasts from numerical models through data assimilation. This work develops a method for inferring the history of a wildfire from satellite measurements, providing the necessary information to initialize coupled atmosphere-wildfire models from a measured wildfire state in a physics-informed approach. The fire arrival time, which is the time the fire reaches a given spatial location, acts as a succinct representation of the history of a wildfire. In this work, a conditional Wasserstein Generative Adversarial Network (cWGAN), trained with WRF-SFIRE simulations, is used to infer the fire arrival time from satellite active fire data. The cWGAN is used to produce samples of likely fire arrival times from the conditional distribution of arrival times given satellite active fire detections. Samples produced by the cWGAN are further used to assess the uncertainty of predictions. The cWGAN is tested on four California wildfires occurring between 2020 and 2022, and predictions for fire extent are compared against high resolution airborne infrared measurements. Further, the predicted ignition times are compared with reported ignition times. An average Sorensen's coefficient of 0.81 for the fire perimeters and an average ignition time error of 32 minutes suggest that the method is highly accurate

Effects of steroids and angiotensin converting enzyme inhibition on circumferential strain in boys with Duchenne muscular dystrophy: a cross-sectional and longitudinal study utilizing cardiovascular magnetic resonance

<p>Abstract</p> <p>Background</p> <p>Steroid use has prolonged ambulation in Duchenne muscular dystrophy (DMD) and combined with advances in respiratory care overall management has improved such that cardiac manifestations have become the major cause of death. Unfortunately, there is no consensus for DMD-associated cardiac disease management. Our purpose was to assess effects of steroid use alone or in combination with angiotensin converting enzyme inhibitors (ACEI) or angiotension receptor blocker (ARB) on cardiovascular magnetic resonance (CMR) derived circumferential strain (ε_cc).</p> <p>Methods</p> <p>We used CMR to assess effects of corticosteroids alone (Group A) or in combination with ACEI or ARB (Group B) on heart rate (HR), left ventricular ejection fraction (LVEF), mass (LVM), end diastolic volume (LVEDV) and circumferential strain (ε_cc) in a cohort of 171 DMD patients >5 years of age. Treatment decisions were made independently by physicians at both our institution and referral centers and not based on CMR results.</p> <p>Results</p> <p>Patients in Group A (114 studies) were younger than those in Group B (92 studies)(10 ± 2.4 vs. 12.4 ± 3.2 years, p < 0.0001), but HR, LVEF, LVEDV and LVM were not different. Although ε_ccmagnitude was lower in Group B than Group A (-13.8 ± 1.9 vs. -12.8 ± 2.0, p = 0.0004), age correction using covariance analysis eliminated this effect. In a subset of patients who underwent serial CMR exams with an inter-study time of ~15 months, ε_ccworsened regardless of treatment group.</p> <p>Conclusions</p> <p>These results support the need for prospective clinical trials to identify more effective treatment regimens for DMD associated cardiac disease.</p

A systematic review of the reporting of Data Monitoring Committees' roles, interim analysis and early termination in pediatric clinical trials

<p>Abstract</p> <p>Background</p> <p>Decisions about interim analysis and early stopping of clinical trials, as based on recommendations of Data Monitoring Committees (DMCs), have far reaching consequences for the scientific validity and clinical impact of a trial. Our aim was to evaluate the frequency and quality of the reporting on DMC composition and roles, interim analysis and early termination in pediatric trials.</p> <p>Methods</p> <p>We conducted a systematic review of randomized controlled clinical trials published from 2005 to 2007 in a sample of four general and four pediatric journals. We used full-text databases to identify trials which reported on DMCs, interim analysis or early termination, and included children or adolescents. Information was extracted on general trial characteristics, risk of bias, and a set of parameters regarding DMC composition and roles, interim analysis and early termination.</p> <p>Results</p> <p>110 of the 648 pediatric trials in this sample (17%) reported on DMC or interim analysis or early stopping, and were included; 68 from general and 42 from pediatric journals. The presence of DMCs was reported in 89 of the 110 included trials (81%); 62 papers, including 46 of the 89 that reported on DMCs (52%), also presented information about interim analysis. No paper adequately reported all DMC parameters, and nine (15%) reported all interim analysis details. Of 32 trials which terminated early, 22 (69%) did not report predefined stopping guidelines and 15 (47%) did not provide information on statistical monitoring methods.</p> <p>Conclusions</p> <p>Reporting on DMC composition and roles, on interim analysis results and on early termination of pediatric trials is incomplete and heterogeneous. We propose a minimal set of reporting parameters that will allow the reader to assess the validity of trial results.</p

Immersion in ESL culture: Oral output through acting

BACKGROUND: To reduce study start-up time, increase data sharing, and assist investigators conducting clinical studies, the National Institute of Neurological Disorders and Stroke embarked on an initiative to create common data elements for neuroscience clinical research. The Common Data Element Team developed general common data elements which are commonly collected in clinical studies regardless of therapeutic area, such as demographics. In the present project, we applied such approaches to data collection in Friedreich ataxia, a neurological disorder that involves multiple organ systems. METHODS: To develop Friedreich’s ataxia common data elements, Friedreich’s ataxia experts formed a working group and subgroups to define elements in: Ataxia and Performance Measures; Biomarkers; Cardiac and Other Clinical Outcomes; and Demographics, Laboratory Tests and Medical History. The basic development process included: Identification of international experts in Friedreich’s ataxia clinical research; Meeting via teleconference to develop a draft of standardized common data elements recommendations; Vetting of recommendations across the subgroups; Dissemination of recommendations to the research community for public comment. RESULTS: The full recommendations were published online in September 2011 at http://www.commondataelements.ninds.nih.gov/FA.aspx. The Subgroups’ recommendations are classified as core, supplemental or exploratory. Template case report forms were created for many of the core tests. CONCLUSIONS: The present set of data elements should ideally lead to decreased initiation time for clinical research studies and greater ability to compare and analyze data across studies. Their incorporation into new and ongoing studies will be assessed in an ongoing fashion to define their utility in Friedreich’s ataxia