Redefining Sports: Esports, Environments, Signals and Functions

The sports landscape is constantly changing due to innovation and entrepreneurship. The availability of technology led to the emergence of esports and augmented sports. Biofeedback and sensing technologies can be used for athlete monitoring and training purposes. Research on motor control deals with planning and execution of bodily movements and provides some insights towards formal presentation of sports.Previous research provided many sports categorization models. On many occasions, published articles failed to distinguish recreational/leisure competitive gameplay activity (gaming) from athletic performance (esports). Our goal was to define esports by extending existing universal sport definitions and propose a novel modular computational framework for categorizing sports through environments and signals.We have fulfilled our goals by illustrating how signals flow within competitive (sports) environments. Our esports definition introduces esports as a group of sports similar to motorsports. Moreover, we have defined mathematical foundations for signal processing by various actors (athletes, referees, environments, intermediate processing steps). We have demonstrated that representing sports as a multidimensional signal can lead to the categorization of sports through computation. We claim that our approach could be applied to transfer training methods from similar sports, analysis of the training process, and referee error measurement.Our study was not without limitations. Further research is required to validate our theoretical model by embedding available variables in latent space to calculate similarity measures between sports

Selected Advances of Quantum Biophotonics – a Short Review

This article discusses four fields of study with the potential to revolutionize our understanding and interaction with biological systems: quantum biophotonics, molecular and supramolecular bioelectronics, quantum-based approaches in gaming, and nano-biophotonics. Quantum biophotonics uses photonics, biochemistry, biophysics, and quantum information technologies to study biological systems at the sub-nanoscale level. Molecular and supramolecular bioelectronics aim to develop biosensors for medical diagnosis, environmental monitoring, and food safety by designing materials and devices that interface with biological systems at the molecular level. Quantum-based approaches in gaming improve modeling of complex systems, while nanomedicine enhances disease diagnosis, treatment, and prevention using nanoscale devices and sensors developed with quantum biophotonics. Lastly, nano-biophotonics studies cellular structures and functions with unprecedented resolution

TACAM: Topic And Context Aware Argument Mining

In this work we address the problem of argument search. The purpose of argument search is the distillation of pro and contra arguments for requested topics from large text corpora. In previous works, the usual approach is to use a standard search engine to extract text parts which are relevant to the given topic and subsequently use an argument recognition algorithm to select arguments from them. The main challenge in the argument recognition task, which is also known as argument mining, is that often sentences containing arguments are structurally similar to purely informative sentences without any stance about the topic. In fact, they only differ semantically. Most approaches use topic or search term information only for the first search step and therefore assume that arguments can be classified independently of a topic. We argue that topic information is crucial for argument mining, since the topic defines the semantic context of an argument. Precisely, we propose different models for the classification of arguments, which take information about a topic of an argument into account. Moreover, to enrich the context of a topic and to let models understand the context of the potential argument better, we integrate information from different external sources such as Knowledge Graphs or pre-trained NLP models. Our evaluation shows that considering topic information, especially in connection with external information, provides a significant performance boost for the argument mining task

Selected Advances of Quantum Biophotonics – a Short Review

This article discusses four fields of study with the potential to revolutionize our understanding and interaction with biological systems: quantum biophotonics, molecular and supramolecular bioelectronics, quantum-based approaches in gaming, and nano-biophotonics. Quantum biophotonics uses photonics, biochemistry, biophysics, and quantum information technologies to study biological systems at the sub-nanoscale level. Molecular and supramolecular bioelectronics aim to develop biosensors for medical diagnosis, environmental monitoring, and food safety by designing materials and devices that interface with biological systems at the molecular level. Quantum-based approaches in gaming improve modeling of complex systems, while nanomedicine enhances disease diagnosis, treatment, and prevention using nanoscale devices and sensors developed with quantum biophotonics. Lastly, nano-biophotonics studies cellular structures and functions with unprecedented resolution

MIaS: Math-Aware Retrieval in Digital Mathematical Libraries

Digital mathematical libraries (DMLs) such as arXiv, Numdam, and EuDML contain mainly documents from STEM fields, where mathematical formulae are often more important than text for understanding. Conventional information retrieval (IR) systems are unable to represent formulae and they are therefore ill-suited for math information retrieval (MIR). To fill the gap, we have developed, and open-sourced the MIaS MIR system. MIaS is based on the full-text search engine Apache Lucene. On top of text retrieval, MIaS also incorporates a set of tools for preprocessing mathematical formulae. We describe the design of the system and present speed, and quality evaluation results. We show that MIaS is both efficient, and effective, as evidenced by our victory in the NTCIR-11 Math-2 task

Coupling of conductive, convective and radiative heat transfer in Czochralski crystal growth process

Abstract This paper studies the conjugate problems of fluid flow and energy transport (involving conduction, convection and radiation heat transfer) within a material changing its phase. The analysis focuses on the Czochralski crystal growth process. The solidifying material is treated as a pure substance with constant material properties. The solution of the resulting 3-D, axisymmetric, non-linear problem is obtained iteratively using the commercial CFD package Fluent. The algorithm employed here treats each subdomain of the system separately, i.e. the liquid and solid phases of the solidified material, as well as the inertial gas surrounding both phases. Results of a test case shows the velocity field and temperature distribution within a simple system employed for the growth of a single silicon crystal

SC2EGSet: StarCraft II Esport Replay and Game-state Dataset

As a relatively new form of sport, esports offers unparalleled data availability. Despite the vast amounts of data that are generated by game engines, it can be challenging to extract them and verify their integrity for the purposes of practical and scientific use. Our work aims to open esports to a broader scientific community by supplying raw and pre-processed files from StarCraft II esports tournaments. These files can be used in statistical and machine learning modeling tasks and related to various laboratory-based measurements (e.g., behavioral tests, brain imaging). We have gathered publicly available game-engine generated "replays" of tournament matches and performed data extraction and cleanup using a low-level application programming interface (API) parser library. Additionally, we open-sourced and published all the custom tools that were developed in the process of creating our dataset. These tools include PyTorch and PyTorch Lightning API abstractions to load and model the data. Our dataset contains replays from major and premiere StarCraft II tournaments since 2016. To prepare the dataset, we processed 55 tournament "replaypacks" that contained 17930 files with game-state information. Based on initial investigation of available StarCraft II datasets, we observed that our dataset is the largest publicly available source of StarCraft II esports data upon its publication. Analysis of the extracted data holds promise for further Artificial Intelligence (AI), Machine Learning (ML), psychological, Human-Computer Interaction (HCI), and sports-related studies in a variety of supervised and self-supervised tasks

Reactivity Model as a Tool to Compare the Combustion Process in Aviation Turbine Engines Powered by Synthetic Fuels

The paper aims to verify the thesis that the reactivity model, developed in earlier research, can be used to compare the fuels combustion processes in turbine engines, which is important for predicting the behavior of different alternative fuels in combustion process. Synthetic blending components from alcohol to jet and hydroprocessed esters and fatty acids technologies and their blends with conventional jet fuel were used in tests. The undertaken laboratory tests reveal the differences between the properties of the tested fuels. Bench tests were carried out on a test rig with a miniature turbojet engine, according to authorial methodology. For each blend, on selected points of rotational speed the carbon oxide concentration in the exhaust gases was recorded. The obtained results allowed the formulation of empirical power functions describing relations between carbon oxide concentration and fuel mass flow rate. Based on general assumptions, the reactivity model was adopted to compare the combustion processes of the different fuels in turbine engines. The directions of further research on the development of the proposed model were indicated

Thermal Degradation Process of Semi-Synthetic Fuels for Gas Turbine Engines in Non-Aeronautical Applications

This article concerns the issue of thermal degradation process of fuels, important from the perspective of the operation of turbine engines, especially in the context of new fuels/bio-fuels and their implementation. The studies of the kerosene-based jet fuel (Jet A-1) and its blends with synthetic components manufactured according to HEFA and ATJ technology, were presented. Both technologies are currently approved by ASTM D7566 to produce components to be added to turbine fuels. Test rig investigations were carried out according to specific methodology which reflects the phenomena taking place in fuel systems of turbine engines. The mechanism of thermal degradation process was assessed on the basis of test results for selected properties, IR spectroscopy and calculation of activation energy. The results show that with the increase of the applied temperature there is an increment of the content of solid contaminants, water and acid for all tested fuels. Thermal degradation process is different for conventional jet fuel when compared to blends, but also semi-synthetic fuels distinguished by different thermal stability depending on a given manufacturing technology