Exploring the potential energy landscape over a large parameter-space

Solving large polynomial systems with coefficient parameters are ubiquitous and constitute an important class of problems. We demonstrate the computational power of two methods - a symbolic one called the Comprehensive Grobner basis and a numerical one called the cheater's homotopy - applied to studying both potential energy landscapes and a variety of questions arising from geometry and phenomenology. Particular attention is paid to an example in flux compactification where important physical quantities such as the gravitino and moduli masses and the string coupling can be efficiently extracted

The main concerns of European anaesthesiology postgraduate trainees: A European survey

This is the first study intended to identify the European anaesthesiology trainees' main concerns, to initiate a process of improvement of the training in anaesthesiology by the European Society of Anaesthesiology (ESA). The authors developed an electronic survey which addressed seven different concerns: autonomy transition, technical skills, exchange programs, residency costs, residency workload, employment prospects and educational contents/preparation for the European Diploma in Anaesthesiology and Intensive Care (EDAIC). The survey was disseminated by email to all anaesthesiology trainees registered in ESA and all European National Societies were asked to distribute the survey to their graduating trainees. 665 trainees initiated the survey with a completion rate of 54.6%. The trainees' main concerns were in descending order: educational contents, residency costs, employment prospects, residency workload, exchange programs, technical skills and autonomy transition. This report analyzes the three main concerns in more detail. 68% of respondents were unaware of the existence of the ESA e-learning platform. Other means to improve the preparation for the EDAIC such as a multiple-choice questions book should be developed. The main reason for not becoming an ESA Trainee member was the associated cost and 68% of respondents gave up activities or opportunities during their residency due to economic constraints; 56% of respondents considered emigrating for economic reasons and 28% elected Northern/Central Europe. The results of the present survey may provide additional background information for the development of specific improvements in strategies for training in anaesthesiology. (c) 2018 Elsevier Ltd. All rights reserved

MACDA II: A New Reanalysis for the Martian Atmosphere Using Vertically-Resolved Dust Opacity Observations.

The dust cycle is a key component of the Martian climate, and is extremely important for understanding the interannual, seasonal and synoptic evolution of the Martian environment. (e.g., Kahre et al., 2017; Newman et al., 2002a, and references therein). Intensive measurements of atmospheric temperature and dust extending over more than eleven Mars years (MY) now exist with unprecedented spatial coverage, thanks to various orbital spacecraft. Such observations have already helped to improve our understanding of Mars' weather and climate. However, the incomplete coverage of these measurements across the planet constrains our ability to study the general circulation in full detail, particularly those aspects related to dust opacity. On the other hand, numerical models provide four-dimensional simulated data with moderate to high temporal and spatial resolution and complete coverage in space and time, but often fail to reproduce the dust cycle's full range of variability. Even the most sophisticated free-running GCMs still struggle to capture realistic interannual variability associated with dust lifting and transport. To aid in this task, data assimilation has become an optimal approach to provide a solution that is consistent with both observations and modeled physical constraints. Data assimilation corrects model-predicted variables toward observations such that the resulting solution can represent the full observed variability of the climate. Such an assimilated record is often termed a “reanalysis” by analogy with the practice in Earth weather and climate forecasting. Several publicly available reanalyses of observations of the Martian atmosphere have been produced in recent years, based mainly on remote sounding measurements of atmospheric temperature, dust and ice opacity and chemical constituents from various orbital platforms (e.g. Montabone et al. 2014; Greybush et al. 2019; Holmes et al. 2020). However, almost all of these have so far mainly used measurements of column dust opacity without information on the vertical distribution of dust. Such products provide much useful information on how dust evolves during the Martian year, but may misrepresent some important features, such as elevated layers of dust (Heavens et al. 2011), and give no information on the vertical extent of dust loading in the atmosphere. In the present work, we have extended the Analysis Correction assimilation scheme (Lorenc et al. 1991), as used for the MACDA and OPENMARS reanalyses, to make use of both column-integrated (CIDO) and layer-integrated dust opacity (LIDO), such as obtained from Mars Climate Sounder limb observations. Here we outline the new assimilation scheme and present some results (a) that validate the reanalysis with independent observations and (b) that demonstrate significant improvements in the representation of the 3D distribution of dust opacity in the Martian atmosphere, even when this distribution differs markedly from the long term climatology

Assimilation of both column‐ and layer‐integrated dust opacity observations in the Martian atmosphere

A new dust data assimilation scheme has been developed for the UK version of the Laboratoire de Météorologie Dynamique (LMD) Martian General Circulation Model. The Analysis Correction scheme (adapted from the UK Met Office) is applied with active dust lifting and transport to analyze measurements of temperature, and both column-integrated dust optical depth (CIDO), τref (rescaled to a reference level), and layer-integrated dust opacity (LIDO). The results are shown to converge to the assimilated observations, but assimilating either of the dust observation types separately does not produce the best analysis. The most effective dust assimilation is found to require both CIDO (from Mars Odyssey/THEMIS) and LIDO observations, especially for Mars Climate Sounder data that does not access levels close to the surface. The resulting full reanalysis improves the agreement with both in-sample assimilated CIDO and LIDO data and independent observations from outside the assimilated dataset. It is thus able to capture previously elusive details of the dust vertical distribution, including elevated detached dust layers that have not been captured in previous reanalyses. Verification of this reanalysis has been carried out under both clear and dusty atmospheric conditions during Mars Years 28 and 29, using both in-sample and out of sample observations from orbital remote sensing and contemporaneous surface measurements of dust opacity from the Spirit and Opportunity landers. The reanalysis was also compared with a recent version of the Mars Climate Database (MCD v5), demonstrating generally good agreement though with some systematic differences in both time mean fields and day-to-day variability

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Visualization of Multivariate Athlete Performance Data

We present a set of visualization methods for the analysis of multivariate data recorded from the measurement of the performance of athletes during training. We use a modified training device to measure the force, acceleration, displacement, and speed of the athlete’s feet and arms while performing a certain training exercise. We are interested in visually measuring and comparing the performance over several training sessions of the same and/or different athletes. For this, we adapt and extend several visualization methods for multivariate data. First, we use an enhanced signal plot and statistics plot to visualize the regularity of repetitions within a given exercise. Second, we use a novel texture-based signal plot to eliminate signal noise and emphasize the average repetitive pattern of the exercise. Finally, we use a signal clustering technique, visualized with a matrix plot, to detect similar exercises over long periods of time. We demonstrate our approaches with actual data from training sessions of several athletes.