Surge Capacity Logistics

Successful management of a pandemic or disaster requires implementation of preexisting plans to minimize loss of life and maintain control. Managing the expected surges in intensive care capacity requires strategic planning from a systems perspective and includes focused intensive care abilities and requirements as well as all individuals and organizations involved in hospital and regional planning. The suggestions in this article are important for all involved in a large-scale disaster or pandemic, including front-line clinicians, hospital administrators, and public health or government officials. Specifically, this article focuses on surge logistics—those elements that provide the capability to deliver mass critical care.The Surge Capacity topic panel developed 23 key questions focused on the following domains: systems issues; equipment, supplies, and pharmaceuticals; staffing; and informatics. Literature searches were conducted to identify studies upon which evidence-based recommendations could be made.This article presents 22 suggestions pertaining to surge capacity mass critical care, including requirements for equipment, supplies, and pharmaceuticals; staff preparation and organization; methods of mitigating overwhelming patient loads; the role of deployable critical care services; and the use of transportation assets to support the surge response

Union renewal in historical perspective

This article revisits contemporary union renewal/revival debates through comparison with the late 1930s resurgence of trade unionism in the UK’s engineering industry. It is argued that the 1930s union renewal arose from more favourable contextual conditions than those currently obtaining. It was led by political activists, with better-articulated organisation and greater resonance in the working class than their contemporary counterparts, and who were assisted by state policy and pro-worker forces. Conclusions are drawn in relation to current debates

Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details

Mechanosensory interactions drive collective behaviour in Drosophila.

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can explain emergent group dynamics. These findings indicate the existence of neural circuits that support distributed behaviours, but the molecular and cellular identities of relevant sensory pathways are unknown. Here we show that Drosophila melanogaster exhibits collective responses to an aversive odour: individual flies weakly avoid the stimulus, but groups show enhanced escape reactions. Using high-resolution behavioural tracking, computational simulations, genetic perturbations, neural silencing and optogenetic activation we demonstrate that this collective odour avoidance arises from cascades of appendage touch interactions between pairs of flies. Inter-fly touch sensing and collective behaviour require the activity of distal leg mechanosensory sensilla neurons and the mechanosensory channel NOMPC. Remarkably, through these inter-fly encounters, wild-type flies can elicit avoidance behaviour in mutant animals that cannot sense the odour--a basic form of communication. Our data highlight the unexpected importance of social context in the sensory responses of a solitary species and open the door to a neural-circuit-level understanding of collective behaviour in animal groups

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior

Measurement of associated Z plus charm production in proton-proton collisions at root s=8TeV

A study of the associated production of a Z boson and a charm quark jet (Z + c), and a comparison to production with a b quark jet (Z + b), in pp collisions at a centre-of-mass energy of 8 TeV are presented. The analysis uses a data sample corresponding to an integrated luminosity of 19.7 fb(-1), collected with the CMS detector at the CERN LHC. The Z boson candidates are identified through their decays into pairs of electrons or muons. Jets originating from heavy flavour quarks are identified using semileptonic decays of c or b flavoured hadrons and hadronic decays of charm hadrons. The measurements are performed in the kinematic region with two leptons with pT(l) > 20 GeV, vertical bar eta(l)vertical bar 25 GeV and vertical bar eta(jet)vertical bar Z + c + X) B(Z -> l(+)l(-)) = 8.8 +/- 0.5 (stat)+/- 0.6 (syst) pb. The ratio of the Z+c and Z+b production cross sections is measured to be sigma(pp -> Z+c+X)/sigma (pp -> Z+b+X) = 2.0 +/- 0.2 (stat)+/- 0.2 (syst). The Z+c production cross section and the cross section ratio are also measured as a function of the transverse momentum of theZ boson and of the heavy flavour jet. The measurements are compared with theoretical predictions.Peer reviewe

Another Shipment of Six Short-Period Giant Planets from TESS

We present the discovery and characterization of six short-period, transiting giant planets from NASA's Transiting Exoplanet Survey Satellite (TESS) -- TOI-1811 (TIC 376524552), TOI-2025 (TIC 394050135), TOI-2145 (TIC 88992642), TOI-2152 (TIC 395393265), TOI-2154 (TIC 428787891), & TOI-2497 (TIC 97568467). All six planets orbit bright host stars (8.9 <G< 11.8, 7.7 <K< 10.1). Using a combination of time-series photometric and spectroscopic follow-up observations from the TESS Follow-up Observing Program (TFOP) Working Group, we have determined that the planets are Jovian-sized (R$_{P}$ = 1.00-1.45 R$_{J}$), have masses ranging from 0.92 to 5.35 M$_{J}$, and orbit F, G, and K stars (4753 $<$ T$_{eff}$ $<$ 7360 K). We detect a significant orbital eccentricity for the three longest-period systems in our sample: TOI-2025 b (P = 8.872 days, $e$ = $0.220\pm0.053$), TOI-2145 b (P = 10.261 days, $e$ = $0.182^{+0.039}_{-0.049}$), and TOI-2497 b (P = 10.656 days, $e$ = $0.196^{+0.059}_{-0.053}$). TOI-2145 b and TOI-2497 b both orbit subgiant host stars (3.8 $<$ $\log$ g $<$4.0), but these planets show no sign of inflation despite very high levels of irradiation. The lack of inflation may be explained by the high mass of the planets; $5.35^{+0.32}_{-0.35}$ M$_{\rm J}$ (TOI-2145 b) and $5.21\pm0.52$ M$_{\rm J}$ (TOI-2497 b). These six new discoveries contribute to the larger community effort to use {\it TESS} to create a magnitude-complete, self-consistent sample of giant planets with well-determined parameters for future detailed studies.Comment: 20 Pages, 6 Figures, 8 Tables, Accepted by MNRA

Measurement of differential cross sections in the kinematic angular variable phi* for inclusive Z boson production in pp collisions at root s=8 TeV

Measurements of differential cross sections d sigma/d phi* and double-differential cross sections d(2)sigma/ld phi*d/y/ for inclusive Z boson production are presented using the dielectron and dimuon final states. The kinematic observable phi* correlates with the dilepton transverse momentum but has better resolution, and y is the dilepton rapidity. The analysis is based on data collected with the CMS experiment at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 19.7 fb(-1). The normalised cross section (1/sigma) d sigma/d phi*, within the fiducial kinematic region, is measured with a precision of better than 0.5% for phi* <1. The measurements are compared to theoretical predictions and they agree, typically, within few percent.Peer reviewe