Inference on inspiral signals using LISA MLDC data

In this paper we describe a Bayesian inference framework for analysis of data obtained by LISA. We set up a model for binary inspiral signals as defined for the Mock LISA Data Challenge 1.2 (MLDC), and implemented a Markov chain Monte Carlo (MCMC) algorithm to facilitate exploration and integration of the posterior distribution over the 9-dimensional parameter space. Here we present intermediate results showing how, using this method, information about the 9 parameters can be extracted from the data.Comment: Accepted for publication in Classical and Quantum Gravity, GWDAW-11 special issu

Association of red blood cells and plasma transfusion versus red blood cell transfusion only with survival for treatment of major traumatic hemorrhage in prehospital setting in England: a multicenter study

Background In-hospital acute resuscitation in trauma has evolved toward early and balanced transfusion resuscitation with red blood cells (RBC) and plasma being transfused in equal ratios. Being able to deliver this ratio in prehospital environments is a challenge. A combined component, like leukocyte-depleted red cell and plasma (RCP), could facilitate early prehospital resuscitation with RBC and plasma, while at the same time improving logistics for the team. However, there is limited evidence on the clinical benefits of RCP. Objective To compare prehospital transfusion of combined RCP versus RBC alone or RBC and plasma separately (RBC + P) on mortality in trauma bleeding patients. Methods Data were collected prospectively on patients who received prehospital transfusion (RBC + thawed plasma/Lyoplas or RCP) for traumatic hemorrhage from six prehospital services in England (2018–2020). Retrospective data on patients who transfused RBC from 2015 to 2018 were included for comparison. The association between transfusion arms and 24-h and 30-day mortality, adjusting for age, injury mechanism, age, prehospital heart rate and blood pressure, was evaluated using generalized estimating equations. Results Out of 970 recruited patients, 909 fulfilled the study criteria (RBC + P = 391, RCP = 295, RBC = 223). RBC + P patients were older (mean age 42 vs 35 years for RCP and RBC), and 80% had a blunt injury (RCP = 52%, RBC = 56%). RCP and RBC + P were associated with lower odds of death at 24-h, compared to RBC alone (adjusted odds ratio [aOR] 0.69 [95%CI: 0.52; 0.92] and 0.60 [95%CI: 0.32; 1.13], respectively). The lower odds of death for RBC + P and RCP vs RBC were driven by penetrating injury (aOR 0.22 [95%CI: 0.10; 0.53] and 0.39 [95%CI: 0.20; 0.76], respectively). There was no association between RCP or RBC + P with 30-day survival vs RBC. Conclusion Prehospital plasma transfusion for penetrating injury was associated with lower odds of death at 24-h compared to RBC alone. Large trials are needed to confirm these findings

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Volcanoes of the Diamante cross-chain: evidence for a mid-crustal felsic magma body beneath the Southern Izu–Bonin–Mariana arc

http://www.godac.jamstec.go.jp/darwin/cruise/natsushima/nt09-08/

Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets

We report on the analysis of selected single source data sets from the first round of the mock LISA data challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pipeline consisting of a grid-based coherent pre-processing unit for signal detection and an automatic Markov Chain Monte Carlo (MCMC) post-processing unit for signal evaluation. We demonstrate that signal detection with our coherent approach is secure and accurate, and is increased in accuracy and supplemented with additional information on the signal parameters by our Markov Chain Monte Carlo approach. We also demonstrate that the Markov Chain Monte Carlo routine is additionally able to determine accurately the noise level in the frequency window of interest