Using deep learning to correct theoretically-derived models

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Generating samples of extreme winters to support climate adaptation

Recent extreme weather across the globe highlights the need to understand the potential for more extreme events in the present-day, and how such events may change with global warming. We present a methodology for more efficiently sampling extremes in future climate projections. As a proof-of-concept, we examine the UK’s most recent set of national Climate Projections (UKCP18). UKCP18 includes a 15-member perturbed parameter ensemble (PPE) of coupled global simulations, providing a range of climate projections incorporating uncertainty in both internal variability and forced response. However, this ensemble is too small to adequately sample extremes with very high return periods, which are of interest to policy-makers and adaptation planners. To better understand the statistics of these events, we use distributed computing to run three 1000-member initial-condition ensembles with the atmosphere-only HadAM4 model at 60km resolution on volunteers’ computers, taking boundary conditions from three distinct future extreme winters within the UKCP18 ensemble. We find that the magnitude of each winter extreme is captured within our ensembles, and that two of the three ensembles are conditioned towards producing extremes by the boundary conditions. Our ensembles contain several extremes that would only be expected to be sampled by a UKCP18 PPE of over 500 members, which would be prohibitively expensive with current supercomputing resource. The most extreme winters we simulate exceed those within UKCP18 by 0.85 K and 37% of the present-day average for UK winter means of daily maximum temperature and precipitation respectively. As such, our ensembles contain a rich set of multivariate, spatio-temporally and physically coherent samples of extreme winters with wide-ranging potential applications

Five-year outcome after laparoscopic anterior partial versus Nissen fundoplication: four randomized trials

Author version made available in accordance with the publisher's policy.Objective: To compare longer term (5-year) outcomes for reflux control and post-surgery side effects following laparoscopic anterior (90˚ and 180˚) partial vs. Nissen fundoplication for gastroesophageal reflux. Summary Background Data: Laparoscopic Nissen fundoplication is the most frequently performed surgical procedure for gastroesophageal reflux. It achieves excellent control of reflux, but in some patients is followed by troublesome side effects. To reduce the risk of side effects laparoscopic anterior partial fundoplication variants have been advocated, although some studies suggest poorer reflux control. Methods: From 1995 to 2003, 461 patients with gastroesophageal reflux were enrolled in 4 randomized controlled trials comparing anterior partial vs. Nissen fundoplication. Two trials evaluated anterior 180˚, and 2 anterior 90˚ partial fundoplication. The original trial data were combined and a re-analysis from original data was undertaken to determine outcomes at 5-years follow-up. Reflux symptom control and side effects were evaluated in a blinded fashion using standardized questionnaires, including 0-10 analog scores (0=no symptoms, 10=severe symptoms). Results: At 5 years, patients who underwent an anterior 90˚ or 180˚ partial fundoplication had less side effects compared with Nissen fundoplication and were equally satisfied with the overall outcome. Reflux control, measured by heartburn scores and antisecretory medication use, was similar for anterior 180˚ partial vs. Nissen fundoplication, but inferior after anterior 90˚ partial vs. Nissen fundoplication. Conclusions: Anterior 180˚ partial fundoplication achieves durable control of reflux symptoms and less side effects compared with Nissen fundoplication. Although reflux control following anterior 90˚ partial fundoplication appears less effective than after Nissen fundoplication. This data supports the use of anterior 180˚ partial fundoplication for the surgical treatment of gastroesophageal reflux

Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction

Dynamical weather and climate prediction models underpin many studies of the Earth system and hold the promise of being able to make robust projections of future climate change based on physical laws. However, simulations from these models still show many differences compared with observations. Machine learning has been applied to solve certain prediction problems with great success, and recently it's been proposed that this could replace the role of physically-derived dynamical weather and climate models to give better quality simulations. Here, instead, a framework using machine learning together with physically-derived models is tested, in which it is learnt how to correct the errors of the latter from timestep to timestep. This maintains the physical understanding built into the models, whilst allowing performance improvements, and also requires much simpler algorithms and less training data. This is tested in the context of simulating the chaotic Lorenz '96 system, and it is shown that the approach yields models that are stable and that give both improved skill in initialised predictions and better long-term climate statistics. Improvements in long-term statistics are smaller than for single time-step tendencies, however, indicating that it would be valuable to develop methods that target improvements on longer time scales. Future strategies for the development of this approach and possible applications to making progress on important scientific problems are discussed.Comment: 26p, 7 figures To be published in Journal of Advances in Modeling Earth System

Transition temperature of a dilute homogeneous imperfect Bose gas

The leading-order effect of interactions on a homogeneous Bose gas is theoretically predicted to shift the critical temperature by an amount \Delta\Tc = # a_{scatt} n^{1/3} T_0 from the ideal gas result T_0, where a_{scatt} is the scattering length and n is the density. There have been several different theoretical estimates for the numerical coefficient #. We claim to settle the issue by measuring the numerical coefficient in a lattice simulation of O(2) phi^4 field theory in three dimensions---an effective theory which, as observed previously in the literature, can be systematically matched to the dilute Bose gas problem to reproduce non-universal quantities such as the critical temperature. We find # = 1.32 +- 0.02.Comment: 4 pages, submitted to Phys. Rev. Lett; minor changes due to improvement of analysis in the longer companion pape

Identification of target-specific bioisosteric fragments from ligand-protein crystallographic data

Bioisosteres are functional groups or atoms that are structurally different but that can form similar intermolecular interactions. Potential bioisosteres were identified here from analysing the X-ray crystallographic structures for sets of different ligands complexed with a fixed protein. The protein was used to align the ligands with each other, and then pairs of ligands compared to identify substructural features with high volume overlap that occurred in approximately the same region of geometric space. The resulting pairs of substructural features can suggest potential bioisosteric replacements for use in lead-optimisation studies. Experiments with 12 sets of ligand-protein complexes from the Protein Data Bank demonstrate the effectiveness of the procedure

Correlation between Compact Radio Quasars and Ultra-High Energy Cosmic Rays

Some proposals to account for the highest energy cosmic rays predict that they should point to their sources. We study the five highest energy events (E>10^20 eV) and find they are all aligned with compact, radio-loud quasars. The probability that these alignments are coincidental is 0.005, given the accuracy of the position measurements and the rarity of such sources. The source quasars have redshifts between 0.3 and 2.2. If the correlation pointed out here is confirmed by further data, the primary must be a new hadron or one produced by a novel mechanism.Comment: 8 pages, 3 tables, revtex. with some versions of latex it's necessary to break out the tables and latex them separately using article.sty rather than revtex.st

Laparoscopic repair of very large hiatus hernia with sutures versus absorbable mesh versus nonabsorbable mesh a randomized controlled trial

Author version made available in accordance with pubilsher policy. 12 month embargo applies from the date of publication (1 Feb 2015).Objective: Determine whether absorbable or non-absorbable mesh in repair of large hiatus hernias reduces the risk of recurrence, compared to suture repair. Summary Background Data: Repair of large hiatus hernia is associated with radiological recurrence rates of up to 30%, and to improve outcomes mesh repair has been recommended. Previous trials have shown less short term recurrence with mesh, but adverse outcomes limit mesh use. Methods: Multicentre prospective double blind randomized controlled trial of 3 methods of repair; sutures vs. absorbable mesh vs. non-absorbable mesh. Primary outcome - hernia recurrence assessed by barium meal X-ray and endoscopy at 6 months. Secondary outcomes - clinical symptom scores at 1, 3, 6 and 12 months. Results: 126 patients enrolled - 43 sutures, 41 absorbable mesh and 42 non-absorbable mesh. 96.0% were followed to 12 months, with objective follow-up data in 92.9%. A recurrent hernia (any size) was identified in 23.1% following suture repair, 30.8% - absorbable mesh, and 12.8% - non-absorbable mesh (p=0.161). Clinical outcomes were similar, except less heartburn at 3 & 6 months and less bloating at 12 months with non-absorbable mesh, and more heartburn at 3 months, odynophagia at 1 month, nausea at 3 & 12 months, wheezing at 6 months, and inability to belch at 12 months following absorbable mesh. The magnitude of the clinical differences were small. Conclusions: No significant differences were seen for recurrent hiatus hernia, and the clinical differences were unlikely to be clinically significant. Overall outcomes following sutured repair were similar to mesh repair

Reversed argininosuccinate lyase activity in fumarate hydratase-deficient cancer cells.

BACKGROUND: Loss of function of fumarate hydratase (FH), the mitochondrial tumor suppressor and tricarboxylic acid (TCA) cycle enzyme, is associated with a highly malignant form of papillary and collecting duct renal cell cancer. The accumulation of fumarate in these cells has been linked to the tumorigenic process. However, little is known about the overall effects of the loss of FH on cellular metabolism. METHODS: We performed comprehensive metabolomic analyses of urine from Fh1-deficient mice and stable isotopologue tracing from human and mouse FH-deficient cell lines to investigate the biochemical signature of the loss of FH. RESULTS: The metabolomics analysis revealed that the urea cycle metabolite argininosuccinate is a common metabolic biomarker of FH deficiency. Argininosuccinate was found to be produced from arginine and fumarate by the reverse activity of the urea cycle enzyme argininosuccinate lyase (ASL), making these cells auxotrophic for arginine. Depleting arginine from the growth media by the addition of pegylated arginine deiminase (ADI-PEG 20) decreased the production of argininosuccinate in FH-deficient cells and reduced cell survival and proliferation. CONCLUSIONS: These results unravel a previously unidentified correlation between fumarate accumulation and the urea cycle enzyme ASL in FH-deficient cells. The finding that FH-deficient cells become auxotrophic for arginine opens a new therapeutic perspective for the cure of hereditary leiomyomatosis and renal cell cancer (HLRCC).RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Ensemble of global climate simulations for temperature in historical, 1.5 °C and 2.0 °C scenarios from HadAM4

Large ensembles of global temperature are provided for three climate scenarios: historical (2006–16), 1.5 °C and 2.0 °C above pre-industrial levels. Each scenario has 700 members (70 simulations per year for ten years) of 6-hourly mean temperatures at a resolution of 0.833° ´ 0.556° (longitude ´ latitude) over the land surface. The data was generated using the climateprediction.net (CPDN) climate simulation environment, to run HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Biases in simulated temperature were identified and corrected using quantile mapping with reference temperature data from ERA5. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository as NetCDF V4 files