The Open Global Glacier Model (OGGM) v1.1 Maussion, Fabien; Butenko, Anton; Champollion, Nicolas ...
Geoscientific Model Development,
03/2019, Letnik:
12, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Despite their importance for sea-level rise, seasonal water availability, and
as a source of geohazards, mountain glaciers are one of the few remaining
subsystems of the global climate system for ...which no globally applicable,
open source, community-driven model exists. Here we present the Open Global
Glacier Model (OGGM), developed to provide a modular and open-source
numerical model framework for simulating past and future change of any
glacier in the world. The modeling chain comprises data downloading tools
(glacier outlines, topography, climate, validation data), a preprocessing
module, a mass-balance model, a distributed ice thickness estimation model,
and an ice-flow model. The monthly mass balance is obtained from gridded
climate data and a temperature index melt model. To our knowledge, OGGM is
the first global model to explicitly simulate glacier dynamics: the model
relies on the shallow-ice approximation to compute the depth-integrated flux
of ice along multiple connected flow lines. In this paper, we describe and
illustrate each processing step by applying the model to a selection of
glaciers before running global simulations under idealized climate forcings.
Even without an in-depth calibration, the model shows very realistic
behavior. We are able to reproduce earlier estimates of global glacier volume
by varying the ice dynamical parameters within a range of plausible values.
At the same time, the increased complexity of OGGM compared to other
prevalent global glacier models comes at a reasonable computational cost:
several dozen glaciers can be simulated on a personal computer, whereas
global simulations realized in a supercomputing environment take up to a few
hours per century. Thanks to the modular framework, modules of various
complexity can be added to the code base, which allows for new kinds of model
intercomparison studies in a controlled environment. Future developments will
add new physical processes to the model as well as automated calibration
tools. Extensions or alternative parameterizations can be easily added by the
community thanks to comprehensive documentation. OGGM spans a wide range of
applications, from ice–climate interaction studies at millennial timescales
to estimates of the contribution of glaciers to past and future sea-level
change. It has the potential to become a self-sustained community-driven
model for global and regional glacier evolution.
This work introduces a model for all-sky-image-based cloud and direct irradiance nowcasting (MACIN), which predicts direct normal irradiance (DNI) for solar energy applications based on hemispheric ...sky images from two all-sky imagers (ASIs).
With a synthetic setup based on simulated cloud scenes, the model and its components are validated in depth.
We train a convolutional neural network on real ASI images to identify clouds.
Cloud masks are generated for the synthetic ASI images with this network.
Cloud height and motion are derived using sparse matching.
In contrast to other studies, all derived cloud information, from both ASIs and multiple time steps, is combined into an optimal model state using techniques from data assimilation.
This state is advected to predict future cloud positions and compute DNI for lead times of up to 20 min.
For the cloud masks derived from the ASI images, we found a pixel accuracy of 94.66 % compared to the references available in the synthetic setup. The relative error of derived cloud-base heights is 4 % and cloud motion error is in the range of ±0.1ms-1.
For the DNI nowcasts, we found an improvement over persistence for lead times larger than 1 min.
Using the synthetic setup, we computed a DNI reference for a point and also an area of 500 m×500 m.
Errors for area nowcasts as required, e.g., for photovoltaic plants, are smaller compared with errors for point nowcasts.
Overall, the novel ASI nowcasting model and its components proved to work within the synthetic setup.
The Open Global Glacier Model (Author abstract) Maussion, Fabien; Butenko, Anton; Champollion, Nicolas ...
Geoscientific model development,
03/2019, Letnik:
12, Številka:
3
Journal Article
Leisure (otium) is an unfettered lingering in time set loose from instrumental rationality and utilitarianism. It aims to be free from regimes of time and pressures to perform, that is, it aims at ...freedom set in time yet not subjected to time's dominion. Leisure may hence at first glance appear to be an individual experience and remove individuals from societal constraints, but it is also an eminently social phenomenon. Capacities for successfully claiming spaces of leisure for oneself are distributed in an extremely unequal manner. Freedom for leisure often becomes a defining and fiercely contested feature of specific social roles. This volume, which contains seventeen essays from ten different disciplines, illuminates leisure's societal dimension in varying historical and cultural contexts, while illustrating its symbolic capital in its respective manifestations.
Abstract Innovative materials for phosphor converted white light-emitting diodes are in high demand owing to the huge potential of the light-emitting diode technology to reduce energy consumption ...worldwide. As the primary blue diode is already highly optimized, the conversion phosphors are of crucial importance for any further improvements. We report on the discovery of the high performance red phosphor SrLi 2 Al 2 O 2 N 2 :Eu 2+ meeting all requirements for a phosphor’s optical properties. It combines the optimal spectral position for a red phosphor, as defined in the 2016 Research & Development-plan of the United States government, with an exceptionally small spectral full width at half maximum and excellent thermal stability. A white mid-power phosphor-converted light-emitting diode prototype utilising SrLi 2 Al 2 O 2 N 2 :Eu 2+ shows an increase of 16% in luminous efficacy compared to currently available commercial high colour-rendering phosphor-converted light-emitting diodes, while retaining excellent high colour rendition. This phosphor enables a big leap in energy efficiency of white emitting phosphor-converted light-emitting-diodes.
We sought to evaluate the frequency of early hypo-attenuated leaflet thickening (HALT) of the SAPIEN 3 transcatheter aortic valve (S3).
Of 249 patients who had undergone S3 implantation, we studied ...156 consecutive patients (85 women, median age 82.2 ± 5.5 years) by electrocardiogram (ECG)-triggered dual-source computed tomography angiography (CTA) after a median of 5 days post-transcatheter aortic valve implantation. The prosthesis was assessed for HALT. Apart from heparin, peri-interventional antithrombotic therapy consisted of single- (aspirin 29%) or dual- (aspirin plus clopidogrel 71%) antiplatelet therapy. Hypo-attenuated leaflet thickening was found in 16 patients 10.3% (95% confidence interval (CI) 5.5-15.0%) of the patients. None of the baseline and procedural variables were significantly associated with HALT, nor did we find a significant association with the antithrombotic regimen, either peri-interventionally or at the time of CTA. Hypo-attenuated leaflet thickening was found in 6 of 45 patients with peri-interventional single-antiplatelet therapy and in 10 of 111 patients with dual-antiplatelet therapy at the time of intervention 13.3% (95% CI 3.4-23.3%) vs. 9% (95% CI 3.7-14.3%), P = 0.42. Hypo-attenuated leaflet thickening was not associated with clinical symptoms, but a small, albeit significant difference in mean pressure gradient at the time of CTA (11.6 ± 3.4 vs. 14.9 ± 5.3 mmHg, P = 0.026). Full anticoagulation led to almost complete resolution of HALT in 13 patients with follow-up CTA.
Irrespective of the antiplatelet regimen, early HALT occurred in 10% of our patients undergoing transcatheter aortic S3 implantation. Early HALT is clinically inapparent and reversible by full anticoagulation.
Retinal fluid as the major biomarker in exudative macular disease is accurately visualized by high-resolution three-dimensional optical coherence tomography (OCT), which is used world-wide as a ...diagnostic gold standard largely replacing clinical examination. Artificial intelligence (AI) with its capability to objectively identify, localize and quantify fluid introduces fully automated tools into OCT imaging for personalized disease management. Deep learning performance has already proven superior to human experts, including physicians and certified readers, in terms of accuracy and speed. Reproducible measurement of retinal fluid relies on precise AI-based segmentation methods that assign a label to each OCT voxel denoting its fluid type such as intraretinal fluid (IRF) and subretinal fluid (SRF) or pigment epithelial detachment (PED) and its location within the central 1-, 3- and 6-mm macular area. Such reliable analysis is most relevant to reflect differences in pathophysiological mechanisms and impacts on retinal function, and the dynamics of fluid resolution during therapy with different regimens and substances. Yet, an in-depth understanding of the mode of action of supervised and unsupervised learning, the functionality of a convolutional neural net (CNN) and various network architectures is needed. Greater insight regarding adequate methods for performance, validation assessment, and device- and scanning-pattern-dependent variations is necessary to empower ophthalmologists to become qualified AI users. Fluid/function correlation can lead to a better definition of valid fluid variables relevant for optimal outcomes on an individual and a population level. AI-based fluid analysis opens the way for precision medicine in real-world practice of the leading retinal diseases of modern times.
•The current assessment of optical coherence tomography images in clinical practice is unsatisfactory.•Artificial intelligence offers objective and precise localization and quantification of fluid.•Automated algorithms provide identification of different types and dynamics of fluid resolution.•The performance of advanced AI tools is superior to human experts in terms of accuracy and speed.•AI in retinal fluid analysis introduces precision medicine into real-world patient management.
Abstract
Childhood acute lymphoblastic leukemia (ALL) genomes show that relapses often arise from subclonal outgrowths. However, the impact of clonal evolution on the actionable proteome and response ...to targeted therapy is not known. Here, we present a comprehensive retrospective analysis of paired ALL diagnosis and relapsed specimen. Targeted next generation sequencing and proteome analysis indicate persistence of actionable genome variants and stable proteomes through disease progression. Paired viably-frozen biopsies show high correlation of drug response to variant-targeted therapies but in vitro selectivity is low. Proteome analysis prioritizes PARP1 as a pan-ALL target candidate needed for survival following cellular stress; diagnostic and relapsed ALL samples demonstrate robust sensitivity to treatment with two PARP1/2 inhibitors. Together, these findings support initiating prospective precision oncology approaches at ALL diagnosis and emphasize the need to incorporate proteome analysis to prospectively determine tumor sensitivities, which are likely to be retained at disease relapse.
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