An adaptive minimum spanning tree multielement method for uncertainty quantification of smooth and discontinuous responses

A novel approach for nonintrusive uncertainty propagation is proposed. Our approach overcomes the limitation of many traditional methods, such as generalized polynomial chaos methods, which may lack sufficient accuracy when the quantity of interest depends discontinuously on the input parameters. As a remedy we propose an adaptive sampling algorithm based on minimum spanning trees combined with a domain d

Machine learning for closure models in multiphase flow applications

Multiphase flows are described by the multiphase Navier-Stokes equations. Numerically solving these equations is computationally expensive, and performing many simulations for the purpose of design, optimization and uncertainty quantification is often prohibitively expensive. A simplified model, the so-called two-fluid model, can be derived from a spatial averaging process. The averaging process introduces a closure problem, which is represented by unknown friction terms in the two-fluid model. Correctly modeling these friction terms is a long-standing problem in two-fluid model development. In this work we take a new approach, and learn the closure terms in the two-fluid model from a set of unsteady high-fidelity simulations conducted with the open source code Gerris. These form the training data for a neural network. The neural network provides a functional relation between the two-fluid mo

Intrusive deconvolutional neural networks for enhancing PIC/FLIP solutions

Traditional fluid flow predictions require large computational resources. Despite recent progress in parallel and GPU computing, the ability to run fluid flow predictions in real-time is often infeasible. Recently developed machine learning approaches, which are trained on high-fidelity data, perform unsatisfactorily outside the training set and remove the ability of utilising legacy codes after training. We propose a novel methodolog

Multi-level neural networks for PDEs with uncertain parameters

A novel multi-level method for partial differential equations with uncertain parameters is proposed. The principle behind the method is that the error between grid levels in multi-level methods has a spatial structure that is by good approximation independent of the actual grid level. Our method learns this structure by employing a sequence of convolutional neural networks, that are well-suited to automatically detect local error features as latent quantities of the solution. Furthermore, by using the concept of transfer learning, the information of coarse grid levels is reused on fine grid levels in order to minimize the required number of samples on fine levels. The method outperforms state-of-the-art multi-level methods, especially in the case when complex PDEs (such as single-phase and free-surface flow problems) are concerned, or when high accuracy is required

XFEL structures of the human MT2 melatonin receptor reveal the basis of subtype selectivity

The human MT1 and MT2 melatonin receptors1,2 are G-protein-coupled receptors (GPCRs) that help to regulate circadian rhythm and sleep patterns3. Drug development efforts have targeted both receptors for the treatment of insomnia, circadian rhythm and mood disorders, and cancer3, and MT2 has also been implicated in type 2 diabetes4,5. Here we report X-ray free electron laser (XFEL) structures of the human MT2 receptor in complex with the agonists 2-phenylmelatonin (2-PMT) and ramelteon6 at resolutions of 2.8 Å and 3.3 Å, respectively, along with two structures of function-related mutants: H2085.46A (superscripts represent the Ballesteros–Weinstein residue numbering nomenclature7) and N862.50D, obtained in complex with 2-PMT. Comparison of the structures of MT2 with a published structure8 of MT1 reveals that, despite conservation of the orthosteric ligand-binding site residues, there are notable conformational variations as well as differences in [3H]melatonin dissociation kinetics that provide insights into the selectivity between melatonin receptor subtypes. A membrane-buried lateral ligand entry channel is observed in both MT1 and MT2, but in addition the MT2 structures reveal a narrow opening towards the solvent in the extracellular part of the receptor. We provide functional and kinetic data that support a prominent role for intramembrane ligand entry in both receptors, and suggest that there might also be an extracellular entry path in MT2. Our findings contribute to a molecular understanding of melatonin receptor subtype selectivity and ligand access modes, which are essential for the design of highly selective melatonin tool compounds and therapeutic agents. © 2019, The Author(s), under exclusive licence to Springer Nature Limited

Structural basis of ligand recognition at the human MT1 melatonin receptor

Melatonin (N-acetyl-5-methoxytryptamine) is a neurohormone that maintains circadian rhythms1 by synchronization to environmental cues and is involved in diverse physiological processes2 such as the regulation of blood pressure and core body temperature, oncogenesis, and immune function3. Melatonin is formed in the pineal gland in a light-regulated manner4 by enzymatic conversion from 5-hydroxytryptamine (5-HT or serotonin), and modulates sleep and wakefulness5 by activating two high-affinity G-protein-coupled receptors, type 1A (MT1) and type 1B (MT2)3,6. Shift work, travel, and ubiquitous artificial lighting can disrupt natural circadian rhythms; as a result, sleep disorders affect a substantial population in modern society and pose a considerable economic burden7. Over-the-counter melatonin is widely used to alleviate jet lag and as a safer alternative to benzodiazepines and other sleeping aids8,9, and is one of the most popular supplements in the United States10. Here, we present high-resolution room-temperature X-ray free electron laser (XFEL) structures of MT1 in complex with four agonists: the insomnia drug ramelteon11, two melatonin analogues, and the mixed melatonin–serotonin antidepressant agomelatine12,13. The structure of MT2 is described in an accompanying paper14. Although the MT1 and 5-HT receptors have similar endogenous ligands, and agomelatine acts on both receptors, the receptors differ markedly in the structure and composition of their ligand pockets; in MT1, access to the ligand pocket is tightly sealed from solvent by extracellular loop 2, leaving only a narrow channel between transmembrane helices IV and V that connects it to the lipid bilayer. The binding site is extremely compact, and ligands interact with MT1 mainly by strong aromatic stacking with Phe179 and auxiliary hydrogen bonds with Asn162 and Gln181. Our structures provide an unexpected example of atypical ligand entry for a non-lipid receptor, lay the molecular foundation of ligand recognition by melatonin receptors, and will facilitate the design of future tool compounds and therapeutic agents, while their comparison to 5-HT receptors yields insights into the evolution and polypharmacology of G-protein-coupled receptors

Publisher Correction: Structural basis of ligand recognition at the human MT1 melatonin receptor (Nature, (2019), 569, 7755, (284-288), 10.1038/s41586-019-1141-3)

Change history: In this Letter, the rotation signs around 90°, 135° and 15° were missing and in the HTML, Extended Data Tables 2 and 3 were the wrong tables; these errors have been corrected online. © 2019, The Author(s), under exclusive licence to Springer Nature Limited

REFLECTIVITE HEMISPHERIQUE ET DIFFUSE DE COUCHES MINCES DE TUNGSTENE PREPAREES PAR DECOMPOSITION EN PHASE VAPEUR

Sur supports de quartz fondu, par décomposition en phase vapeur (CVD) de l'hexacarbonyle de tungstène W(CO)6, en présence ou non d'oxygène, sont obtenus deux types de matériau en couches minces, appelés respectivement "tungstène noir" (constitué principalement d'oxydes de tungstène) ou "tungstène réflecteur" (composé essentiellement de carbures de tungstène). A partir des mesures, à température ambiante, des pouvoirs réflecteurs hémisphérique, spéculaire et diffus, effectuées entre 0,25 et 15 µm immédiatement après la préparation ou après le recuit dans différentes atmosphères, sont déterminées les caractéristiques de sélectivité des couches. L'évolution de l'état de cristallisation, de la composition et de la rugosité de surface, en fonction des conditions de préparation et de recuit dans les différentes atmosphères, est mise en évidence par des mesures de diffraction de rayons X et de microscopie électronique à balayage.Two kinds of thin films were prepared on fused quartz substrates by chemical vapor decomposition (CVD) of tungsten hexacarbonyle W(CO)6 in the presence or absence of oxygen. One, called "black tungsten", is mainly composed by tungsten oxides, the other, "reflective tungsten", is constituted by tungsten carbide. The caracteristics of selectivity were determined from measurements of hemispherical, diffuse and specular reflectances in the spectral range of 0.25 to 15 µm, immediately after preparation or after annealing in argon, hydrogen or air. The evolution of the crystallinity, composition and surface texture as function of preparation conditions and annealings was shown by XR diffraction patterns and scanning electron micrographs