No abstract

As part of a plethora of global efforts to minimize the negative effects of the SARS-CoV2 (COVID-19) pandemic, we developed two different mechanisms that, after further development, could potentially be of use in the future in order to increase the capacity of ventilators with low-cost devices based on single-use-bag-valve mask systems. We describe the concept behind the devices and report a characterization of them. Finally, we make a description of the solved and unsolved challenges and propose a series of measures in order to better cope with future contingencies.

No abstract

A quantitative understanding of the worldwide plastics distribution is required not only to assess the extent and possible impact of plastic litter on the environment but also to identify possible counter measures. A systematic collection of data characterizing amount and composition of plastics has to be based on two crucial components: (i) An experimental approach that is simple enough to be accessible worldwide and sensible enough to capture the diversity of plastics; (ii) An analysis pipeline that is able to extract the relevant parameters from the vast amount of experimental data. In this study, we demonstrate that such an approach could be realized by a combination of photoluminescence spectroscopy and a machine learning-based theoretical analysis. We show that appropriate combinations of classifiers with dimensional reduction algorithms are able to identify specific material properties from the spectroscopic data. The best combination is based on an unsupervised learning technique making our approach robust to alternations of the input data.

As part of a plethora of global efforts to minimize the negative effects of the SARS-CoV2 (COVID-19) pandemic, we developed two different mechanisms that, after further development, could potentially be of use in the future in order to increase the capacity of ventilators with low-cost devices based on single-use-bag-valve mask systems. We describe the concept behind the devices and report a characterization of them. Finally, we make a description of the solved and unsolved challenges and propose a series of measures in order to better cope with future contingencies.