Propagation front of correlations in an interacting Bose gas

We analyze the quench dynamics of a one-dimensional bosonic Mott insulator and focus on the time evolution of density correlations. For these we identify a pronounced propagation front, the velocity of which, once correctly extrapolated at large distances, can serve as a quantitative characteristic of the many-body Hamiltonian. In particular, the velocity allows the weakly interacting regime, which is qualitatively well described by free bosons, to be distinguished from the strongly interacting one, in which pairs of distinct quasiparticles dominate the dynamics. In order to describe the latter case analytically, we introduce a general approximation to solve the Bose-Hubbard Hamiltonian based on the Jordan-Wigner fermionization of auxiliary particles. This approach can also be used to determine the ground-state properties. As a complement to the fermionization approach, we derive explicitly the time-dependent many-body state in the noninteracting limit and compare our results to numerical simulations in the whole range of interactions of the Bose-Hubbard model.Comment: 16 pages, 7 figure

Telementoring for remote simulation instructor training and faculty development using telesimulation

Publisher Copyright: © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Introduction: Simulation-based training is essential for high-quality medical care, but it requires access to equipment and expertise. Technology can facilitate connecting educators to training in simulation. We aimed to explore the use of remote simulation faculty development in Latvia using telesimulation and telementoring with an experienced debriefer located in the USA. Methods: This was a prospective, simulation-based longitudinal study. Over the course of 16 months, a remote simulation instructor (RI) from the USA and a local instructor (LI) in Latvia cofacilitated with teleconferencing. Responsibility gradually transitioned from the RI to the LI. At the end of each session, students completed the Debriefing Assessment for Simulation in Healthcare (DASH) student version form (DASH-SV) and a general feedback form, and the LI completed the instructor version of the DASH form (DASH-IV). Outcome measures were the changes in DASH scores over time. Results: A total of eight simulation sessions were cofacilitated of 16 months. As the role of the LI increased over time, the debrief quality measured with the DASH-IV did not change significantly (from 89 to 87), although the DASH-SV score decreased from a total median score of 89 (IQR 86-98) to 80 (IQR 78-85) (p=0.005). Conclusion: In this study, telementoring with telesimulations resulted in high-quality debriefing. The quality - perceived by the students - was higher with the involvement of the remote instructor and declined during the transition to the LI. This concept requires further investigation and could potentially build local simulation expertise promoting sustainability of high-quality simulation.Peer reviewe

Insights into Rock-Ice Avalanche Dynamics by Combined Analysis of Seismic Recordings and a Numerical Avalanche Mode

Rock‐ice avalanches larger than 1 × 106 m3 are high‐magnitude, low‐frequency events that may occur in all ice‐covered, high mountain areas around the world and can cause extensive damage if they reach populated regions. The temporal and spatial evolution of the seismic signature from two events was analyzed, and recordings at selected stations were compared to numerical model results of avalanche propagation. The first event is a rock‐ice avalanche from Iliamna volcano in Alaska which serves as a “natural laboratory” with simple geometric conditions. The second one originated on Aoraki/Mt. Cook, New Zealand Southern Alps, and is characterized by a much more complex topography. A dynamic numerical model was used to calculate total avalanche momentum, total kinetic energy, and total frictional work rate, among other parameters. These three parameters correlate with characteristics of the seismic signature such as duration and signal envelopes, while other parameters such as flow depths, flow path and deposition geometry are well in agreement with observations. The total frictional work rate shows the best correlation with the absolute seismic amplitude, suggesting that it may be used as an independent model evaluation criterion and in certain cases as model calibration parameter. The good fit is likely because the total frictional work rate represents the avalanche ’s energy loss rate, part of which is captured by the seismometer. Deviations between corresponding calculated and measured parameters result from site and path effects which affect the recorded seismic signal or indicate deficiencies of the numerical model. The seismic recordings contain additional information about when an avalanche reaches changes in topography along the runout path and enable more accurate velocity calculations. The new concept of direct comparison of seismic and avalanche modeling data helps to constrain the numerical model input parameters and to improve the understanding of (rock‐ice) avalanche dynamics

A Collaborative In Situ Simulation-based Pediatric Readiness Improvement Program for Community Emergency Departments

Background More than 30 million children are cared for across 5,000 U.S. emergency departments (EDs) each year. Most of these EDs are not facilities designed and operated solely for children. A Web-based survey provided a national and state-by-state assessment of pediatric readiness and noted a national average score was 69 on a 100-point scale. This survey noted wide variations in ED readiness with scores ranging from 61 in low-pediatric-volume EDs to 90 in the high-pediatric-volume EDs. Additionally, the mean score at the state level ranged from 57 (Wyoming) to 83 (Florida) and for individual EDs ranged from 22 to 100. The majority of prior efforts made to improve pediatric readiness have involved providing Web-based resources and online toolkits. This article reports on the first year of a program that aimed to improve pediatric readiness across community hospitals in our state through in situ simulation-based assessment facilitated by our academic medical center. The primary aim was to improve the pediatric readiness scores in the 10 participating hospitals. The secondary aim was to explore the correlation of simulation-based performance of hospital teams with pediatric readiness scores. Methods This interventional study measured the Pediatric Readiness Survey (PRS) prior to and after implementation of an improvement program. This program consisted of three components: 1) in situ simulations, 2) report-outs, and 3) access to online pediatric readiness resources and content experts. The simulations were conducted in situ (in the ED resuscitation bay) by multiprofessional teams of doctors, nurses, respiratory therapists, and technicians. Simulations and debriefings were facilitated by an expert team from a pediatric academic medical center. Three scenarios were conducted for all teams and include: a 6-month-old with respiratory failure, an 8-year-old with diabetic ketoacidosis (DKA), and a 6-month-old with supraventricular tachycardia (SVT). A performance score was calculated for each scenario. The improvement of PRS was compared before and after the simulation program. The correlation of the simulation performance of each hospital and the PRS was calculated. Results Forty-one multiprofessional teams from 10 EDs in Indiana participated in the study, five were of medium pediatric volume and five were medium- to high-volume EDs. The PRS significantly improved from the first to the second on-site verification assessment (58.4 ± 4.8 to 74.7 ± 2.9, p = 0.009). Total adherence scores to scenario guidelines were 54.7, 56.4, and 62.4% in the respiratory failure, DKA, and SVT scenarios, respectively. We found no correlation between simulation performance and PRS scores. Medium ED pediatric volume significantly predicted higher PRS scores compared to medium-high pediatric ED volume (β = 8.7; confidence interval = 0.72–16.8, p = 0.034). Conclusions Our collaborative improvement program that involved simulation was associated with improvement in pediatric readiness scores in 10 EDs participating statewide. Future work will focus on further expanding of the network and establishing a national model for pediatric readiness improvement

Infectious Complications of Ventricular Assist Device Use in Children in the US: Data from the Pediatric Interagency Registry for Mechanical Circulatory Support (Pedimacs)

Background Infections are frequent in pediatric ventricular assist device (VAD) patients. In this study we aimed to describe infections in durable VAD patients reported to Pedimacs. Methods Durable VAD data from the Pedimacs registry (September 19, 2012 to December 31, 2015) were analyzed. Infections were described with standard descriptive statistics, Kaplan–Meier analysis and competing outcomes analysis. Results There were 248 implants in 222 patients, with a mean age and a median follow-up of 11 ± 6.4 years and 2.4 patient-months (<1 day to 2.6 years), respectively. Device types were pulsatile flow (PF) in 91 (41%) patients and continuous flow (CF) in 131 (59%) patients. PF patients were younger (4 ± 4 vs 14 ± 4 years; p < 0.0001) and were more likely to have congenital heart disease (25% vs 12%; p = 0.03), prior surgery (53% vs 26%; p < 0.0001) and prior extracorporeal membrane oxygenation (24% vs 7%; p = 0.0003). Infection accounted for 17% (96 of 564) of the reported adverse events (AEs). A non-device infection was most common (51%), followed by sepsis (24%), external pump component infection (20%) and internal pump component infection (5%). Most infections were bacterial (73%) and required intravenous therapy only (77%). The risk of infection in the constant phase was higher in patients with a history of prior infection and in patients with a history of a non-infectious major AEs. Survival was lower after infection only in CF patients (p = 0.008). Conclusions Infection was the most common AE after pediatric VAD implantation. Non-device infections were most common. The best predictor of a future infection was a past infection. CF patients have higher risk of death after an infection

Keeping Up With the Kids: Diffusion of Innovation in Pediatric Emergency Medicine Among Emergency Physicians

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137273/1/acem13185.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137273/2/acem13185_am.pd

Using Simulation to Measure and Improve Pediatric Primary Care Offices Emergency Readiness

Introduction Emergencies in the pediatric primary care office are high-risk, low-frequency events that offices may be ill-prepared to manage. We developed an intervention to improve pediatric primary care office emergency preparedness involving a baseline measurement, a customized report out with action plans for improvement (based on baseline measures), and a plan to repeat measurement at 6 months. This article reports on the baseline measurement. Methods This baseline measurement consisted of 2 components: preparedness checklists and in situ simulations. The preparedness checklists were completed in person to measure compliance with the American Academy of Pediatrics Policy Statement: preparation for emergencies in the offices of pediatricians and pediatric primary care providers, in the domains of equipment, supplies, medication, and guidelines. Two in situ simulations, a child in respiratory distress and a child with a seizure, were conducted with the offices' interprofessional teams; performance was scored using checklists. Results Baseline measurements were conducted in 12 pediatric offices from October to December 2018. Wide variability was noted for compliance with the American Academy of Pediatrics recommendations (range = 47%–87%) and performance during in situ simulations (range = 43%–100%). Conclusions Pediatric primary care office emergency preparedness was found to be variable. Simulation can be used to augment existing measures of emergency preparedness, such as checklists. By using simulation to measure office emergency preparedness, areas of knowledge deficit and latent safety threats were identified and are being addressed through ongoing collaboration