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Introduction: Muscle fatigue is often experienced by athletes and in work settings. Excessive fatigue can lead to injury and musculoskeletal disorders. Surface electromyography (EMG) is typically used to detect and ultimately prevent fatigue during isometric movement. The application of EMG to fatigue detection in dynamic movement requires, however, a secondary confirmation of fatigue based on physiological measures. Our objective was to determine if muscle oxygenation derived via near-infrared spectroscopy (NIRS) was correlated with relevant EMG indicators of neuromuscular fatigue and whether observed correlations were related to the fatigue process. Methods: Bilateral electromyograms from three upper leg muscles and the tissue oxygenation index (TOI) of the vastus lateralis muscle were recorded in sixteen non-disabled individuals during cycle ergometry to volitional exhaustion. Six EMG activity features were extracted and the Pearson correlation coefficient between each feature and TOI was determined. Results: The EMG root mean square, spectral standard deviation, second spectral moment, and zero-crossing rate (ZC) were strongly correlated with TOI. The time course of ZC and the correlation of this feature with TOI suggest that there could be a relation between muscle oxygenation and fatigue. Conclusion: Future work should use the knowledge gained in this study to investigate whether NIRS can be used to verify the onset of fatigue as detected by EMG.

The Compressed Baryonic Matter (CBM) experiment is one of the major scientific pillars of the Facility for Antiproton and Ion Research (FAIR). The physics programme of CBM is centred around the exploration of the QCD phase diagram and nuclear matter equation-of-state in the region of high baryon densities. The respective rare probes will be accessed by using nucleus-nucleus collisions in the energy range √sNN = 2.9 - 4.9 GeV at peak interaction rates of up to 10 MHz and a trigger-less data acquisition scheme. This article reviews CBM physics goals with the experimental observables. The progress and current status of the comprising detector sub-systems, including their performance in FAIR Phase-0 experiments will also be presented.

Image segmentation is a common use case of image processing. It enables a wide variety of activities, from self-driving cars to traffic systems that are capable of governing them. Most state of the art models like Mask R-CNN and other transformer-based models perform well but have very high inference times. Therefore in this paper, a novel model architecture is proposed that can run on consumer grade hardware while giving near real time image segmentation. This is done by creating masks on regions of interest proposed by a lightweight object detection algorithm that is the YOLOv4. Such an algorithm allows for image segmentation in near-real time for resource constrained environments as compared to other state of the art models that have high inference times are unsuitable for deployment in said environments.

The CBM experiment at the Facility for Antiproton and Ion Research (FAIR) aims to explore the QCD phase diagram in the region of high net-baryon densities using nucleus-nucleus collisions ($\sqrt{s_{NN}}$ = 2.9 - 4.9 GeV). CBM will be utilizing peak interaction rates of up to 10 MHz and an advanced triggerless data acquisition scheme to provide it with an unique access to rare physics probes required to accomplish CBM's physics goals. This contribution will summarise CBM's progress in terms of its physics performance simulations and the status of the comprising detector sub-systems, including their involvement in FAIR Phase-0 activities., Comment: 6 pages, 4 figures, Quark Matter 2022, submitted to Acta Physica Polonica B