Teaching computers to fold proteins

A new general algorithm for optimization of potential functions for protein folding is introduced. It is based upon gradient optimization of the thermodynamic stability of native folds of a training set of proteins with known structure. The iterative update rule contains two thermodynamic averages which are estimated by (generalized ensemble) Monte Carlo. We test the learning algorithm on a Lennard-Jones (LJ) force field with a torsional angle degrees-of-freedom and a single-atom side-chain. In a test with 24 peptides of known structure, none folded correctly with the initial potential functions, but two-thirds came within 3{\AA} to their native fold after optimizing the potential functions.Comment: 4 pages, 3 figure

Das Luchsprojekt Harz : ein Zwischenbericht

Ende 1999 beschlossen das Niedersächsische Ministerium für den ländlichen Raum, Ernährung, Landwirtschaft und Verbraucherschutz, das Niedersächsische Umweltministerium und die Landesjägerschaft Niedersachsen e. V. im Harz ein gemeinsames Projekt zur Wiederansiedlung des Eurasischen Luchses (Lynx lynx) zu beginnen. Luchse existieren allerdings aufgrund einer Wiederansiedlung bereits im Böhmerwald im deutsch-tschechischen Grenzgebiet und können zudem auch im Pfälzerwald und im Schwarzwald mehr oder weniger regelmäßig bestätigt werden. Letztere Nachweise könnten auf Wiederansiedlungsprojekte der 1970er und 1980er Jahre in der Schweiz und Frankreich zurück zu führen sein. Einzelnachweise von Luchsen unklarer Herkunft, wie zuletzt in Hessen und Nordrhein-Westfalen, treten gelegentlich auch in anderen Gebieten auf

Autoencoding beyond pixels using a learned similarity metric

We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a variational autoencoder with a generative adversarial network we can use learned feature representations in the GAN discriminator as basis for the VAE reconstruction objective. Thereby, we replace element-wise errors with feature-wise errors to better capture the data distribution while offering invariance towards e.g. translation. We apply our method to images of faces and show that it outperforms VAEs with element-wise similarity measures in terms of visual fidelity. Moreover, we show that the method learns an embedding in which high-level abstract visual features (e.g. wearing glasses) can be modified using simple arithmetic

Using Computational Essays to Scaffold Professional Physics Practice

This article describes a curricular innovation designed to help students experience authentic physics inquiry with an emphasis on computational modeling and scientific communication. The educational design centers on a new type of assignment called a computational essay, which was developed and implemented over the course of two semesters of an intermediate electricity and magnetism course at the University of Oslo, Norway. We describe the motivation, learning goals, and scaffolds used in the computational essay project, with the intention that other educators will be able to replicate and adapt our design. We also report on initial findings from this implementation, including key features of student-written computational essays, student reflections on the inquiry process, and self-reported conceptual and attitudinal development. Based on these findings, we argue that computational essays can serve a key role in introducing students to open-ended, inquiry-based work and setting the foundation for future computational research and studies.Comment: Submitted to the European Journal of Physic

The large-scale time-mean ocean circulation in the Nordic Seas and Arctic Ocean estimated from simplified dynamics

A simplified diagnostic model of the time-mean, large-scale ocean circulation in the Nordic Seas and Arctic Ocean is presented. Divergences in the surface Ekman layer are extracted from observed climatological wind stress fields. Similarly, divergences caused by the meridional thermal wind transport (relative to the bottom) are calculated from an observed climatological density field. These known quantities are then used to force the model\u27s bottom geostrophic velocities. Both scaling arguments and direct observations show that for long time scales the bottom currents are closely aligned with contours of f/H, (where f is the Coriolis parameter and H is the depth of the seabed). Due to the weak planetary vorticity gradient at high latitudes, the f/H field is dominated by topography and is characterized by multiple regions of closed isolines. The only frictional effect included in the model is bottom stress. By then integrating the depth-integrated vorticity equation over the area spanned by a closed f/H contour, and assuming that the same contour is a streamline of the bottom geostrophic flow, we derive an analytical expression for the bottom geostrophic velocity on this f/H contour. For the few contours that are not closed, current measurements are used as boundary conditions. Model results are compared with near-bottom current measurements in both the Nordic Seas and the Arctic Ocean. In addition comparison is made with observations from surface drifters in the Nordic Seas by adding the observed thermal wind shear to the modeled bottom flow. The agreement is surprisingly good, suggesting that the simple model is capturing some of the most important processes responsible for the large-scale circulation field. Features like the subgyre recirculations in the Nordic Seas, the gyres in the Canadian and Eurasian Basins, the East Greenland Current, the Norwegian Atlantic Current and the Arctic Circumpolar Boundary Current are all well reproduced by the model. The simplicity of the model makes it well suited as a dynamical framework for interpreting the large-scale circulation pattern in the Nordic Seas and Arctic Ocean