597 research outputs found

    Decarbonising the critical sectors of aviation, shipping, road freight and industry to limit warming to 1.5–2°C

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    Limiting warming to well below 2°C requires rapid and complete decarbonisation of energy systems. We compare economy-wide modelling of 1.5°C and 2°C scenarios with sector-focused analyses of four critical sectors that are difficult to decarbonise: aviation, shipping, road freight transport, and industry. We develop and apply a novel framework to analyse and track mitigation progress in these sectors. We find that emission reductions in the 1.5°C and 2°C scenarios of the IMAGE model come from deep cuts in CO2 intensities and lower energy intensities, with minimal demand reductions in these sectors’ activity. We identify a range of additional measures and policy levers that are not explicitly captured in modelled scenarios but could contribute significant emission reductions. These are demand reduction options, and include less air travel (aviation), reduced transportation of fossil fuels (shipping), more locally produced goods combined with high load factors (road freight), and a shift to a circular economy (industry). We discuss the challenges of reducing demand both for economy-wide modelling and for policy. Based on our sectoral analysis framework, we suggest modelling improvements and policy recommendations, calling on the relevant UN agencies to start tracking mitigation progress through monitoring key elements of the framework (CO2 intensity, energy efficiency, and demand for sectoral activity, as well as the underlying drivers), as a matter of urgency

    What drives the 'August effect'?: an observational study of the effect of junior doctor changeover on out of hours work

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    Objective: To investigate whether measurements of junior doctor on-call workload and performance can clarify the mechanisms underlying the increase in morbidity and mortality seen after junior doctor changeover: the ‘August effect’. Design: Quantitative retrospective observational study of routinely collected data on junior doctor workload. Setting: Two large teaching hospitals in England. Participants: Task level data from a wireless out of hours system (n = 29,885 requests) used by medical staff, nurses, and allied health professionals. Main outcome measures: Number and type of tasks requested by nurses, time to completion of tasks by junior doctors. Results: There was no overall change in the number of tasks requested by nurses out of hours around the August changeover (median requests per hour 15 before and 14 after, p = 0.46). However, the number of tasks classified as urgent was greater (p = 0.016) equating to five more urgent tasks per day. After changeover, doctors took less time to complete tasks overall due to a reduction in time taken for routine tasks (median 74 vs. 66 min; p = 3.9 × 10−9). Conclusion: This study suggests that the ‘August effect’ is not due to new junior doctors completing tasks more slowly or having a greater workload. Further studies are required to investigate the causes of the increased number of urgent tasks seen, but likely factors are errors, omissions, and poor prioritization. Thus, improved training and quality control has the potential to address this increased duration of unresolved patient risk. The study also highlights the potential of newer technologies to facilitate quantitative study of clinical activity

    Aviation effects on already-existing cirrus clouds.

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    Determining the effects of the formation of contrails within natural cirrus clouds has proven to be challenging. Quantifying any such effects is necessary if we are to properly account for the influence of aviation on climate. Here we quantify the effect of aircraft on the optical thickness of already-existing cirrus clouds by matching actual aircraft flight tracks to satellite lidar measurements. We show that there is a systematic, statistically significant increase in normalized cirrus cloud optical thickness inside mid-latitude flight tracks compared with adjacent areas immediately outside the tracks

    The structures of a naturally empty cowpea mosaic virus particle and its genome-containing counterpart by cryo-electron microscopy

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    Cowpea mosaic virus (CPMV) is a picorna-like plant virus. As well as an intrinsic interest in CPMV as a plant pathogen, CPMV is of major interest in biotechnology applications such as nanotechnology. Here, we report high resolution cryo electron microscopy (cryo-EM) maps of wild type CPMV containing RNA-2, and of naturally-formed empty CPMV capsids. The resolution of these structures is sufficient to visualise large amino acids. We have refined an atomic model for each map and identified an essential amino acid involved in genome encapsidation. This work has furthered our knowledge of Picornavirales genome encapsidation and will assist further work in the development of CPMV as a biotechnological tool

    When Does Reward Maximization Lead to Matching Law?

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    What kind of strategies subjects follow in various behavioral circumstances has been a central issue in decision making. In particular, which behavioral strategy, maximizing or matching, is more fundamental to animal's decision behavior has been a matter of debate. Here, we prove that any algorithm to achieve the stationary condition for maximizing the average reward should lead to matching when it ignores the dependence of the expected outcome on subject's past choices. We may term this strategy of partial reward maximization “matching strategy”. Then, this strategy is applied to the case where the subject's decision system updates the information for making a decision. Such information includes subject's past actions or sensory stimuli, and the internal storage of this information is often called “state variables”. We demonstrate that the matching strategy provides an easy way to maximize reward when combined with the exploration of the state variables that correctly represent the crucial information for reward maximization. Our results reveal for the first time how a strategy to achieve matching behavior is beneficial to reward maximization, achieving a novel insight into the relationship between maximizing and matching

    ParaVR: A Virtual Reality Training Simulator for Paramedic Skills maintenance

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    This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Paramedic Practice, copyright © MA Healthcare, after peer review and technical editing by the publisher. To access the final edited and published work see https://www.paramedicpractice.com/features/article/paravr-a-virtual-reality-training-simulator-for-paramedic-skills-maintenance.Background, Virtual Reality (VR) technology is emerging as a powerful educational tool which is used in medical training and has potential benefits for paramedic practice education. Aim The aim of this paper is to report development of ParaVR, which utilises VR to address skills maintenance for paramedics. Methods Computer scientists at the University of Chester and the Welsh Ambulance Services NHS Trust (WAST) developed ParaVR in four stages: 1. Identifying requirements and specifications 2. Alpha version development, 3. Beta version development 4. Management: Development of software, further funding and commercialisation. Results Needle Cricothyrotomy and Needle Thoracostomy emerged as candidates for the prototype ParaVR. The Oculus Rift head mounted display (HMD) combined with Novint Falcon haptic device was used, and a virtual environment crafted using 3D modelling software, ported (a computing term meaning transfer (software) from one system or machine to another) onto Oculus Go and Google cardboard VR platform. Conclusion VR is an emerging educational tool with the potential to enhance paramedic skills development and maintenance. The ParaVR program is the first step in our development, testing, and scaling up of this technology

    Personalized Drug Dosage – Closing the Loop

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    A brief account is given of various approaches to the individualization of drug dosage, including the use of pharmacodynamic markers, therapeutic monitoring of plasma drug concentrations, genotyping, computer-guided dosage using ‘dashboards’, and automatic closed-loop control of pharmacological action. The potential for linking the real patient to his or her ‘virtual twin’ through the application of physiologically-based pharmacokinetic modeling is also discussed
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