Enhanced force-field calibration via machine learning

The influence of microscopic force fields on the motion of Brownian particles plays a fundamental role in a broad range of fields, including soft matter, biophysics, and active matter. Often, the experimental calibration of these force fields relies on the analysis of the trajectories of the Brownian particles. However, such an analysis is not always straightforward, especially if the underlying force fields are non-conservative or time-varying, driving the system out of thermodynamic equilibrium. Here, we introduce a toolbox to calibrate microscopic force fields by analyzing the trajectories of a Brownian particle using machine learning, namely, recurrent neural networks. We demonstrate that this machine-learning approach outperforms standard methods when characterizing the force fields generated by harmonic potentials if the available data are limited. More importantly, it provides a tool to calibrate force fields in situations for which there are no standard methods, such as non-conservative and time-varying force fields. In order to make this method readily available for other users, we provide a Python software package named DeepCalib, which can be easily personalized and optimized for specific force fields and applications. This package is ideal to calibrate complex and non-standard force fields from short trajectories, for which advanced specific methods would need to be developed on a case-by-case basis

Brain health: time matters in multiple sclerosis

publisher: Elsevier articletitle: Brain health: time matters in multiple sclerosis journaltitle: Multiple Sclerosis and Related Disorders articlelink: http://dx.doi.org/10.1016/j.msard.2016.07.003 content_type: article copyright: © 2016 Oxford PharmaGenesis Ltd. Published by Elsevier B.V

Theories in Business and Information Systems Engineering

Even though the idea of science enjoys an impressive reputation, there seems to be no precise conception of science. On the one hand, there is no unified definition of the extension of activities subsumed under the notion of science. According to the narrow conception that is common in Anglo-Saxon countries, science is restricted to those disciplines that investigate nature and aim at explanation and prediction of natural phenomena. A wider conception that can be found in various European countries includes social sciences, the humanities and engineering. On the other hand and related to the first aspect, there is still no general consensus on the specific characteristics of scientific discoveries and scientific knowledge

Multiple sclerosis registries in Europe – An updated mapping survey

Highlights Nineteen questionnaires from European MS registries were analysed. Aim and focus as well as number of patients and inclusion criteria vary considerably. Most of the MS registries collect data within common general categories. There are more pronounced differences regarding specific subcategories

Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated