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Optical measurement techniques have proven to be useful tools for studying combustion-related phenomenon. The fact that the techniques are optical facilitates performing the measurements without impinging upon the measurement object, such as the combustion event that can be involved. Such techniques can be species-specific and be performed in situ, i.e. in the setting in which the phenomena in que

Sudden cardiac arrest is a devastating event with high mortality and substantial morbidity among survivors. Early recognition and intervention to restore circulation is the primary goal; once that is achieved, the path toward a meaningful recovery starts. Initial in-hospital care is focused on emergency cardiac care, but soon there is a change to a more brain-oriented critical care including targe

We present a nonresonant circular polarization selective structure (CPSS) based on multiple layers of stacked meander line sheets arranged closely after each other. The structure has a total thickness of 13.5 mm (0.68 wavelengths at center frequency 15 GHz) and is realized by cascading printed circuit boards interspaced with a low-permittivity foam material, and the different layers are bonded tog

The increased impact from fluctuating energy sources like wind and photovoltaics significantly affects the operational regime of conventional power plants. In the near future, even former base load power plants such as the large-scale lignite plants in Germany will need to start and shut down to balance the electricity system. As frequent starts were not in the focus of optimisation in the past, a

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive technique to probe tissue microstructure. Conventional Stejskal–Tanner diffusion encoding (i.e., encoding along a single axis), is unable to disentangle different microstructural features within a voxel; If a voxel contains microcompartments that vary in more than one attribute (e.g., size, shape, orientation), it can be diff

With the vast amount of data available, and its increasing complexity in manufacturing processes, traditional statistical approaches have started to fall short. This is where machine learning plays a key role, addressing the challenges by bringing the ability to analyse large and complex datasets from multiple sources, finding non-linear and intricate patterns on data, relationships between severa

The early transition of knowledge from highly specialised and sophisticated proteomics research to a diverse community in need of know-how is a challenge that requires backing from advanced research centres and groups, and a coordinating body for the dissemination of this knowledge. The European Proteomics Association (EuPA) Education Committee signified this as a priority area when the EuPA was f