Biocatalysis has gained a reputation as sustainable alternative to conventional catalysis over the past years. Still, several limitations need to be addressed in order to make this method a competitive candidate for industrial applications. The catalytic activity of unspecific peroxygenases has been investigated in several experimental studies already, with promising results in terms of turn...
Understanding and modeling the nonequilibrium dynamics of many-body
quantum systems is a crucial goal for many fields in physics and
chemistry. Examples include scattering of molecules off metal surfaces,
charge transport through molecular nanojunctions, spintronics, and
molecular photophysics. This motivates the development of sophisticated
theories capable of treating not only the...
In recent years, phenomic prediction has emerged as a new method in the plant breeding community. The method can be compared to genomic prediction, except that instead of marker data, NIR spectra are used to predict various traits. Phenomic prediction has been shown to have great potential. However, there are still many open questions regarding its practical application. For example, in the...
Artificial Intelligence (AI) has become indispensable for analyzing large-scale datasets, particularly in the realm of 3D image volumes.
However, effectively harnessing AI for such tasks often requires advanced algorithms and high-performance computing (HPC) resources, presenting significant challenges for non-technical users.
To overcome these barriers, we present KI-Morph, a novel software...
Traditional analysis techniques in data-intensive disciplines like high energy physics and cosmology have been restricted to hand-crafted low dimensional summary statistics. Modern machine learning allows for new methods that attempt to make optimal use of the full high-dimensional data. However the significant computational cost of these methods requires the use of dedicated GPU clusters,...
Computing resources play a crucial role in modern particle physics research, covering a wide range of different use
cases. These range from the enormous data processing demands of large experimental collaborations, like ATLAS, CMS or Belle II, over theory calculations and Monte Carlo simulations producing huge amounts of data, to analysis code of PhD or Master's students. These workflows...
