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1702 Publications visible to you, out of a total of 1702
Using CutFEM for solving the linearized Poisson-Boltzmann equation: Introductory application in HiFlow3

Abstract (Expand)

The Poisson-Boltzmann equation(PBE) is a fundamental equation for accurate description of electrostatics in ionic solutions or plasma. Hence, it finds application in a wide variety of fields including … plasma physics, computational biology, colloidal and interface science and chemistry. In this preprint, we describe a first approach for solving it in a linearized setup using the CutFEM method in the software framework HiFlow3. The considered methods are easy to use, but not oriented towards extracting optimal computing time. Forthis purpose,the weak form of the linear PBE is first derived. Then, the CutFEM based numerical method is proposed. Finally, the most important code sections in HiFlow 3 are explained in more details. The electrostatic potential for ubiquitin and the adenovirus virion molecules are calculated and presented in a numerical example at the end of the paper.

Authors: Jonas Roller, Valentin Schmid, Philipp Gerstner, Jakob Nießner, Vincent Heuveline

Date Published: 18th Jul 2024

Publication Type: Journal

Redesign of astrophysical codes for exascale computing: the SPACE experience

Abstract

Not specified

Authors: Giuliano Taffoni, Andrea Mignone, Luca Tornatore, Eva Sciacca, Massimiliano Guarrasi, Giovanni Lapenta, Lubomir Riha, Radim Vavrik, Ondrej Vysocky, Kristian Kadlubiak, Petr Strakos, Milan Jaros, Klaus Dolag, Benoit Commercon, Luciano Rezzolla, Khalil Pierre, Georgios Doulis, Sijing Shen, Manolis Marazakis, Daniele Gregori, Elisabetta Boella, Gino Perna, Marisa Zanotti, Erwan Raffin, Kai Polsterer, Sebastian Trujillo Gomez, Guillermo Marin

Date Published: 18th Jul 2024

Publication Type: Journal

Towards an Interoperability Landscape for a National Research Data Infrastructure for Personal Health Data.

Abstract (Expand)

The German initiative "National Research Data Infrastructure for Personal Health Data" (NFDI4Health) focuses on research data management in health research. It aims to foster and develop … harmonized informatics standards for public health, epidemiological studies, and clinical trials, facilitating access to relevant data and metadata standards. This publication lists syntactic and semantic data standards of potential use for NFDI4Health and beyond, based on interdisciplinary meetings and workshops, mappings of study questionnaires and the NFDI4Health metadata schema, and literature search. Included are 7 syntactic, 32 semantic and 9 combined syntactic and semantic standards. In addition, 101 ISO Standards from ISO/TC 215 Health Informatics and ISO/TC 276 Biotechnology could be identified as being potentially relevant. The work emphasizes the utilization of standards for epidemiological and health research data ensuring interoperability as well as the compatibility to NFDI4Health, its use cases, and to (inter-)national efforts within these sectors. The goal is to foster collaborative and inter-sectoral work in health research and initiate a debate around the potential of using common standards.

Authors: C. N. Vorisek, S. A. I. Klopfenstein, M. Lobe, C. O. Schmidt, P. J. Mayer, M. Golebiewski, S. Thun

Date Published: 13th Jul 2024

Publication Type: Journal

Non-adiabatic molecular dynamics simulations provide new insights into the exciton transfer in the Fenna–Matthews–Olson complex

Abstract (Expand)

A trajectory surface hopping approach, which uses machine learning to speed up the most time-consuming steps, has been adopted to investigate the exciton transfer in light-harvesting systems. The present … neural networks achieve high accuracy in predicting both Coulomb couplings and excitation energies. The latter are predicted taking into account the environment of the pigments. Direct simulation of exciton dynamics through light-harvesting complexes on significant time scales is usually challenging due to the coupled motion of nuclear and electronic degrees of freedom in these rather large systems containing several relatively large pigments. In the present approach, however, we are able to evaluate a statistically significant number of non-adiabatic molecular dynamics trajectories with respect to exciton delocalization and exciton paths. The formalism is applied to the Fenna–Matthews–Olson complex of green sulfur bacteria, which transfers energy from the light-harvesting chlorosome to the reaction center with astonishing efficiency. The system has been studied experimentally and theoretically for decades. In total, we were able to simulate non-adiabatically more than 30 ns, sampling also the relevant space of parameters within their uncertainty. Our simulations show that the driving force supplied by the energy landscape resulting from electrostatic tuning is sufficient to funnel the energy towards site 3, from where it can be transferred to the reaction center. However, the high efficiency of transfer within a picosecond timescale can be attributed to the rather unusual properties of the BChl a molecules, resulting in very low inner and outer-sphere reorganization energies, not matched by any other organic molecule, e.g., used in organic electronics. A comparison with electron and exciton transfer in organic materials is particularly illuminating, suggesting a mechanism to explain the comparably high transfer efficiency.

Authors: Monja Sokolov, David S. Hoffmann, Philipp M. Dohmen, Mila Krämer, Sebastian Höfener, Ulrich Kleinekathöfer, Marcus Elstner

Date Published: 9th Jul 2024

Publication Type: Journal

Nonadiabatic Simulation of Exciton Dynamics in Organic Semiconductors Using Neural Network-Based Frenkel Hamiltonian and Gradients

Abstract

Not specified

Authors: Farhad Ghalami, Philipp M. Dohmen, Mila Krämer, Marcus Elstner, Weiwei Xie

Date Published: 8th Jul 2024

Publication Type: Journal

Much Ado About Nothing: Accelerating Maximum Likelihood Phylogenetic Inference via Early Stopping to evade (Over-)optimization

Abstract (Expand)

Maximum Likelihood (ML) based phylogenetic inference constitutes a challenging optimization problem. Given a set of aligned input sequences, phylogenetic inference tools strive to determine the tree …rive to determine the tree topology, the branch-lengths, and the evolutionary parameters that maximize the phylogenetic likelihood function. However, there exist compelling reasons to not push optimization to its limits, by means of early, yet adequate stopping criteria. Since input sequences are typically subject to stochastic and systematic noise, one should exhibit caution regarding (over-)optimization and the inherent risk of overfitting the model to noisy input data. To this end, we propose, implement, and evaluate four statistical early stopping criteria in RAxML-NG that evade excessive and compute-intensive (over-)optimization. These generic criteria can seamlessly be integrated into other phylo-genetic inference tools while not decreasing tree accuracy. The first two criteria quantify input data-specific sampling noise to derive a stopping threshold. The third, employs the Kishino-Hasegawa (KH) test to statistically assess the significance of differences between intermediate trees before , and after major optimization steps in RAxML-NG. The optimization terminates early when improvements are insignificant. The fourth method utilizes multiple testing correction in the KH test. We show that all early stopping criteria infer trees that are statistically equivalent compared to inferences without early stopping. In conjunction with a necessary simplification of the standard RAxML-NG tree search heuristic, the average inference times on empirical and simulated datasets are ∼3.5 and ∼1.8 times faster, respectively, than for standard RAxML-NG v.1.2. The four stopping criteria have been implemented in RAxML-NG and are available as open source code under GNU GPL at https://github.com/togkousa/raxml-ng .

Authors: Anastasis Togkousidis, Alexandros Stamatakis, Olivier Gascuel

Date Published: 8th Jul 2024

Publication Type: Journal

Making Epidemiological and Clinical Studies FAIR Using the Example of COVID-19

Abstract (Expand)

Abstract FAIRification of personal health data is of utmost importance to improve health research and political as well as medical decision-making, which ultimately contributes to a better health of …utes to a better health of the general population. Despite the many advances in information technology, several obstacles such as interoperability problems remain and relevant research on the health topic of interest is likely to be missed out due to time-consuming search and access processes. A recent example is the COVID-19 pandemic, where a better understanding of the virus’ transmission dynamics as well as preventive and therapeutic options would have improved public health and medical decision-making. Consequently, the NFDI4Health Task Force COVID-19 was established to foster the FAIRification of German COVID-19 studies. This paper describes the various steps that have been taken to create low barrier workflows for scientists in finding and accessing German COVID-19 research. It provides an overview on the building blocks for FAIR health research within the Task Force COVID-19 and how this initial work was subsequently expanded by the German consortium National Research Data Infrastructure for Personal Health Data (NFDI4Health) to cover a wider range of studies and research areas in epidemiological, public health and clinical research. Lessons learned from the Task Force helped to improve the respective tasks of NFDI4Health.

Authors: Iris Pigeot, Wolfgang Ahrens, Johannes Darms, Juliane Fluck, Martin Golebiewski, Horst K. Hahn, Xiaoming Hu, Timm Intemann, Elisa Kasbohm, Toralf Kirsten, Sebastian Klammt, Sophie Anne Ines Klopfenstein, Bianca Lassen-Schmidt, Manuela Peters, Ulrich Sax, Dagmar Waltemath, Carsten Oliver Schmidt

Date Published: 1st Jul 2024

Publication Type: Journal

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