Sarma phase in relativistic and non-relativistic systems

We investigate the stability of the Sarma phase in two-component fermion systems in three spatial dimensions. For this purpose we compare strongly-correlated systems with either relativistic or non-relativistic dispersion relation: relativistic quarks and mesons at finite isospin density and spin-imbalanced ultracold Fermi gases. Using a Functional Renormalization Group approach, we resolve fluctuation effects onto the corresponding phase diagrams beyond the mean-field approximation. We find that fluctuations induce a second order phase transition at zero temperature, and thus a Sarma phase, in the relativistic setup for large isospin chemical potential. This motivates the investigation of the cold atoms setup with comparable mean-field phase structure, where the Sarma phase could then be realized in experiment. However, for the non-relativistic system we find the stability region of the Sarma phase to be smaller than the one predicted from mean-field theory. It is limited to the BEC side of the phase diagram, and the unitary Fermi gas does not support a Sarma phase at zero temperature. Finally, we propose an ultracold quantum gas with four fermion species that has a good chance to realize a zero-temperature Sarma phase.Comment: version published in Phys.Lett.B; 10 pages, 5 figure

Multi-Class ECG Feature Importance Rankings: Cardiologists vs. Algorithms

Cardiologists have been using electrocardiogram features to diagnose a wide variety of heart conditions for many decades. There are also numerous algorithms that rank feature importance for a particular classification task. However, different algorithms often give quite different feature rankings. Therefore, we compared the feature importance rankings obtained by various algorithms with the features that cardiologists use for diagnosis

PTB-XL+, a comprehensive electrocardiographic feature dataset

Machine learning (ML) methods for the analysis of electrocardiography (ECG) data are gaining importance, substantially supported by the release of large public datasets. However, these current datasets miss important derived descriptors such as ECG features that have been devised in the past hundred years and still form the basis of most automatic ECG analysis algorithms and are critical for cardiologists’ decision processes. ECG features are available from sophisticated commercial software but are not accessible to the general public. To alleviate this issue, we add ECG features from two leading commercial algorithms and an open-source implementation supplemented by a set of automatic diagnostic statements from a commercial ECG analysis software in preprocessed format. This allows the comparison of ML models trained on clinically versus automatically generated label sets. We provide an extensive technical validation of features and diagnostic statements for ML applications. We believe this release crucially enhances the usability of the PTB-XL dataset as a reference dataset for ML methods in the context of ECG data

New trends in globalization of science and engineering education

Three decades ago most research and design were conducted in each country independently. But the world has become quite different since then. Global changes in technology and society changed the concept of an engineer. There is the need for engineers who can work effectively in changing global and technical environments. Less interest has been paid to the globalization of science and technology. This article reviews the stimulus, that impact the engineering profession and gives the recommendations concerning the profession of engineering, the technology and innovation

The nonperturbative functional renormalization group and its applications

The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for viable ultraviolet completions in fundamental physics. It provides us with a natural framework to study theoretical models where degrees of freedom are correlated over long distances and that may exhibit very distinct behavior on different energy scales. The nonperturbative functional renormalization-group (FRG) approach is a modern implementation of Wilson's RG, which allows one to set up nonperturbative approximation schemes that go beyond the standard perturbative RG approaches. The FRG is based on an exact functional flow equation of a coarse-grained effective action (or Gibbs free energy in the language of statistical mechanics). We review the main approximation schemes that are commonly used to solve this flow equation and discuss applications in equilibrium and out-of-equilibrium statistical physics, quantum many-particle systems, high-energy physics and quantum gravity.Comment: v2) Review article, 93 pages + bibliography, 35 figure

Performance of extensive cattle stocking on a reclaimed minerotrophic wet grassland

Extensive stocking with cattle is a common type of grassland management in reclaimed fen sites. However, due to the high productivity of grassland on organic soil with a history of intensive management, stocking at low rates may not allow an adequate balance of herbage production and utilisation. In the present study we examined the agronomic performance of an established (6-year) extensive cattle grazing system on a reclaimed fen grassland site in north-western Germany during the course of the grazing season. We regularly quantified the amount and energy content of herbage on offer based on compressed sward height (CSH), the spatial extent of patches of various degrees of grazing intensity (heavily or moderately grazed, non-grazed), and the chemical composition of the herbage, and assessed energy uptake and livestock performance in terms of live weight gain of the cattle. We deduced herbage utilisation from these data and quantified functional relationships between cattle grazing and the properties of the sward. Our data show that there was an inadequate balance between quantity and quality of forage on offer on the one hand, and demand and forage consumption by livestock on the other. As a result, live weight gains showed a seasonal pattern with a minimum in summer. The amount of energy on offer per animal unit had a significant effect on the sward structure, i.e. on both the area proportion of heavily grazed patches and the heterogeneity of CSH. These findings may be of interest in the context of conservation management of reclaimed fen grasslands, as they may contribute to the design of grazing regimes aiming to create particular sward structures, e.g., to provide habitat for individual target species