Athena: A New Code for Astrophysical MHD

A new code for astrophysical magnetohydrodynamics (MHD) is described. The code has been designed to be easily extensible for use with static and adaptive mesh refinement. It combines higher-order Godunov methods with the constrained transport (CT) technique to enforce the divergence-free constraint on the magnetic field. Discretization is based on cell-centered volume-averages for mass, momentum, and energy, and face-centered area-averages for the magnetic field. Novel features of the algorithm include (1) a consistent framework for computing the time- and edge-averaged electric fields used by CT to evolve the magnetic field from the time- and area-averaged Godunov fluxes, (2) the extension to MHD of spatial reconstruction schemes that involve a dimensionally-split time advance, and (3) the extension to MHD of two different dimensionally-unsplit integration methods. Implementation of the algorithm in both C and Fortran95 is detailed, including strategies for parallelization using domain decomposition. Results from a test suite which includes problems in one-, two-, and three-dimensions for both hydrodynamics and MHD are given, not only to demonstrate the fidelity of the algorithms, but also to enable comparisons to other methods. The source code is freely available for download on the web.Comment: 61 pages, 36 figures. accepted by ApJ

Design of an experimental platform for gait analysis with ActiSense and StereoPi

Gait analysis is a systematic study of human movement. Combining wearable foot pressure sensors and machine learning (ML) solutions for a high-fidelity body pose tracking from RGB video frames could reveal more insights into gait abnormalities. However, accurate detection of heel strike (HS) and toe-off (TO) events is crucial to compute interpretable gait parameters. In this work, we present an experimental platform to study the timing of gait events using a new wearable foot pressure sensor (ActiSense System, IEE S.A., Luxembourg), and Google’s open-source ML solution MediaPipe Pose. For this purpose, two StereoPi systems were built to capture stereoscopic videos and images in real time. MediaPipe Pose was applied to the synchronized StereoPi cameras, and two algorithms (ALs) were developed to detect HS and TO events for gait and analysis. Preliminary results from a healthy subject walking on a treadmill show a mean relative deviation across all time spans of less than 4% for the ActiSense device and less than 16% for AL2 (33% for AL1) employing MediaPipe Pose on StereoPi videos. Finally, this work offers a platform for the development of sensor- and video-based ALs to automatically identify the timing of gait events in healthy individuals and those with gait disorders

Viral load dynamics in intubated patients with COVID-19 admitted to the intensive care unit

Background: Prolonged viral RNA detection in respiratory samples from patients with COVID-19 has been described, but the clinical relevance remains unclear. We studied the dynamics of SARS-CoV-2 on a group and individual level in intubated ICU patients. Methods: In a cohort of 86 patients, we analysed SARS-CoV-2 RT-PCR results on nasopharyngeal and sputum samples (obtained as part of clinical care twice a week) according to time after intubation. Subsequently, we performed survival analyses. Results: 870 samples were tested by RT-PCR. Overall viral load was highest in the first week (median nasopharynx 3.5. IQR 1.5-4.3; median sputum 4.3. IQR 3.3-5.6) and decreased over time. In 20% of patients a relapsing pattern was observed. Nasopharyngeal and sputum PCR status on day 14 was not significantly associated with survival up to day 60 in this small cohort. Conclusion: In general SARS-CoV-2 RNA levels in respiratory samples in patients with severe COVID-19 decease alter the first week after intubation, but individual SARS-CoV-2 RNA levels can show a relapsing pattern. Larger studies are needed to address the association of clearance of SARS-CoV-2 RNA from respiratory samples with survival, because we observed a trend towards better survival in patients with early clearance from sputum. (C) 2021 The Authors. Published by Elsevier Inc

Origins of the Ambient Solar Wind: Implications for Space Weather

The Sun's outer atmosphere is heated to temperatures of millions of degrees, and solar plasma flows out into interplanetary space at supersonic speeds. This paper reviews our current understanding of these interrelated problems: coronal heating and the acceleration of the ambient solar wind. We also discuss where the community stands in its ability to forecast how variations in the solar wind (i.e., fast and slow wind streams) impact the Earth. Although the last few decades have seen significant progress in observations and modeling, we still do not have a complete understanding of the relevant physical processes, nor do we have a quantitatively precise census of which coronal structures contribute to specific types of solar wind. Fast streams are known to be connected to the central regions of large coronal holes. Slow streams, however, appear to come from a wide range of sources, including streamers, pseudostreamers, coronal loops, active regions, and coronal hole boundaries. Complicating our understanding even more is the fact that processes such as turbulence, stream-stream interactions, and Coulomb collisions can make it difficult to unambiguously map a parcel measured at 1 AU back down to its coronal source. We also review recent progress -- in theoretical modeling, observational data analysis, and forecasting techniques that sit at the interface between data and theory -- that gives us hope that the above problems are indeed solvable.Comment: Accepted for publication in Space Science Reviews. Special issue connected with a 2016 ISSI workshop on "The Scientific Foundations of Space Weather." 44 pages, 9 figure

Application of a buoyancy-modified k-ω SST turbulence model to simulate wave run-up around a monopile subjected to regular waves using OpenFOAM ®

© 2017 Elsevier B.V. The objective of the present work is to investigate wave run-up around a monopile subjected to regular waves inside a numerical wave flume using the Computational Fluid Dynamics (CFD) toolbox OpenFOAM®. Reynolds-Averaged Navier-Stokes (RANS) turbulence modelling is performed by applying the k-ω SST model. Boundary conditions for wave generation and absorption are adopted from the IHFOAM toolbox. Simulations of propagating water waves show sometimes excessive wave damping (i.e. a significant decrease in wave height over the length of the numerical wave flume) based on RANS turbulence modelling. This anomaly is prevented by implementing a buoyancy term in the turbulent kinetic energy equation. The additional term suppresses the turbulence level at the interface between water and air. The proposed buoyancy-modified k-ω SST turbulence model results in an overall stable wave propagation model without significant wave damping over the length of the flume. Firstly, the necessity of a buoyancy-modified k-ω SST turbulence model is demonstrated for the case of propagating water waves in an empty wave flume. Secondly, numerical results of wave run-up around a monopile under regular waves using the buoyancy-modified k-ω SST turbulence model are validated by using experimental data measured in a wave flume by De Vos et al. (2007). Furthermore, time-dependent high spatial resolutions of the numerically obtained wave run-up around the monopile are presented. These results are in line with the experimental data and available analytical formulations.keywords: CFD,OpenFOAM (R)/IHFOAM,Buoyancy-modified turbulence model,Monopile,Wave run-upstatus: publishe

Possible physical and thermodynamical evidence for liquid water at the Phoenix landing site

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95444/1/jgre2665.pd

Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopic observations: 2. Using isotopic diagnostics to understand the mid and upper tropospheric moist bias in the tropics and subtropics

Evaluating the representation of processes controlling tropical and subtropical tropospheric relative humidity (RH) in atmospheric general circulation models (GCMs) is crucial to assess the credibility of predicted climate changes. GCMs have long exhibited a moist bias in the tropical and subtropical mid and upper troposphere, which could be due to the mis-representation of cloud processes or of the large-scale circulation, or to excessive diffusion during water vapor transport. The goal of this study is to use observations of the water vapor isotopic ratio to understand the cause of this bias. We compare the three-dimensional distribution of the water vapor isotopic ratio measured from space and ground to that simulated by several versions of the isotopic GCM LMDZ. We show that the combined evaluation of RH and of the water vapor isotopic composition makes it possible to discriminate the most likely cause of RH biases. Models characterized either by an excessive vertical diffusion, an excessive convective detrainment or an underestimated in situ cloud condensation will all produce a moist bias in the free troposphere. However, only an excessive vertical diffusion can lead to a reversed seasonality of the free tropospheric isotopic composition in the subtropics compared to observations. Comparing seven isotopic GCMs suggests that the moist bias found in many GCMs in the mid and upper troposphere most frequently results from an excessive diffusion during vertical water vapor transport. This study demonstrates the added value of water vapor isotopic measurements for interpreting shortcomings in the simulation of RH by climate models

Recommendations for enterovirus diagnostics and characterisation within and beyond Europe.

Enteroviruses (EV) can cause severe neurological and respiratory infections, and occasionally lead to devastating outbreaks as previously demonstrated with EV-A71 and EV-D68 in Europe. However, these infections are still often underdiagnosed and EV typing data is not currently collected at European level. In order to improve EV diagnostics, collate data on severe EV infections and monitor the circulation of EV types, we have established European non-polio enterovirus network (ENPEN). First task of this cross-border network has been to ensure prompt and adequate diagnosis of these infections in Europe, and hence we present recommendations for non-polio EV detection and typing based on the consensus view of this multidisciplinary team including experts from over 20 European countries. We recommend that respiratory and stool samples in addition to cerebrospinal fluid (CSF) and blood samples are submitted for EV testing from patients with suspected neurological infections. This is vital since viruses like EV-D68 are rarely detectable in CSF or stool samples. Furthermore, reverse transcriptase PCR (RT-PCR) targeting the 5'noncoding regions (5'NCR) should be used for diagnosis of EVs due to their sensitivity, specificity and short turnaround time. Sequencing of the VP1 capsid protein gene is recommended for EV typing; EV typing cannot be based on the 5'NCR sequences due to frequent recombination events and should not rely on virus isolation. Effective and standardized laboratory diagnostics and characterisation of circulating virus strains are the first step towards effective and continuous surveillance activities, which in turn will be used to provide better estimation on EV disease burden

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability