The Integrated Science of Movement is a concept of a new field of study emerging from two very similar, yet independently and parallelly developing research areas, human mobility and movement ecology. The resulting combination is very interdisciplinary, combining knowledge and methods from GIScience, computer science, physics, geography, transportation, and public health. Thanks to the fast...
The Zubarev approach of the non-equilibrium statistical operator [1] is used to account for the enhancement of the low-$p_T$ part of pion spectra by introducing an effective pion chemical potential [2]. This is an alternative to the explanation of the low-$p_T$ enhancement by resonance decays. We report on the first results obtained with a newly developed thermal particle generator that...
Deep learning (DL) techniques have become a crucial tool in various areas of physics, assisting in the acceleration and optimization of computational systems. DL algorithms enable the discovery of new relations and phenomenological laws. In my presentation, I will discuss two physics problems our team is working on. Firstly, we aim to develop an AI-supported version of NuWro, a Monte Carlo...
Freshwater fishes are among the most restricted species worldwide because they are fully contained within fragmented networks of water bodies surrounded by land. Given that the natural fragmentation and isolation of these networks have been identified as a generator of the greatest diversity in this group, we need a deeper understanding of their role as drivers of fish diversity. Hints that...
Tortuosity is the third parameter (after porosity and permeability) that is most often computed in investigation of transport through porous media. It characterizes the elongation of emergent paths of diffusive, hydrodynamic or electric transport.
In this poster we will present several ways of tortuosity computation. Initially, we spotlight the streamline-based approach. To facilitate...
PyRamanGUI[1, 2, 3] is a versatile tool to analyze Raman spectra, which combines state-of-the-art analysis methods like baseline correction, smoothing, cosmic spike removal, peak fitting and multivariate statistical methods like principal compound analysis with the organization of Raman data in projects and the plotting of spectra. The automated evaluation of batches of Raman spectra is also...
ML and DL are revolutionising our abilities to analyse biomedical images. Among other host-pathogen interactions may be readily deciphered from microscopy data using convolutional neural networks (CNN). We demonstrate in several studies how the definition of novel ML/DL tasks may aid in studying infection and disease phenotypes. Specifically, ML/DL algorithms may allow unambiguous scoring of...
Understanding the pathomechanism behind brain structure destruction is crucial for effective prevention and treatment strategies. The aHEAD project addresses this by continually enhancing diagnostic techniques and simulating the impact on brain structures resulting from road accidents, sports injuries, and head protection device efficacy, such as ski, bicycle, and motorcycle helmets. Through...
The GNSS signal is an important data source for weather applications: ground-based stations produce point-like observations of water vapor with unprecedented stability and a fast update rate. Space-based receivers mounted on the LEO satellites deliver reliable profiles of the troposphere, regardless of weather conditions. Both data types, so far with two different operators, are used by...
The GNSS signal is an important data source for weather applications: ground-based stations produce point-like observations of water vapor with unprecedented stability and a fast update rate. Space-based receivers mounted on the LEO satellites deliver reliable profiles of the troposphere, regardless of weather conditions. Both data types, so far with two different operators, are used by global...
