Background: Thanks to a simplified special approval process that was valid until October 1st, 2020, a large number of particle-filtering half masks have come onto the German market. When caring for SARS-CoV-2 infected patients, the RKI recommends wearing particle-filtering half masks with a filter performance of at least 94 %, which corresponds to FFP class 2 according to EN 149:2001+A1:2009. We have examined 15 particle-filtering half masks with different specifications for their filter performance METHOD: The masks were clamped in a jig in an airtight test box. Radioactive particles with a size of 0.6 ± 0.4 µm were nebulized into the box and sucked into a filter through the port of the jig and an unfiltered reference port using an artificial lung. The activity deposited on the filter was measured by means of a gamma camera. The filter performance was calculated from this.
Results: Five of the 15 masks tested had a filter performance of less than 94 % and therefore do not meet the FFP2 standard. The filter performance of these masks was 71.8 ± 2.3 %, 73.2 ± 2.3 %, 78.2 ± 6.7 %, 92.2 ± 0.5 % and 85.9 ± 1.6 %.
Conclusion: One third of the examined masks did not meet the recommended FFP2 standard, which is recommended for the care of SARS-CoV-2 infected patients. A comprehensive review of already approved products by the supervisory authorities is advisable.
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http://dx.doi.org/10.1055/a-1364-0061 | DOI Listing |
Biomed Phys Eng Express
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Children's Hospital of Eastern Switzerland, Claudiusstrasse 6, St.Gallen, 9006, SWITZERLAND.
Mapping the myomagnetic field of a straight and easily accessible muscle after electrical stimulation using triaxial optically pumped magnetometers (OPMs) to assess potential benefits for magnetomyography (MMG). Approach: Six triaxial OPMs were arranged in two rows with three sensors each along the abductor digiti minimi (ADM) muscle. The upper row of sensors was inclined by 45° with respect to the lower row and all sensors were aligned closely to the skin surface without direct contact.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
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View Article and Find Full Text PDFPLoS One
January 2025
School of Business Economics, European Union University, Montreux, Switzerland.
As people's material living standards continue to improve, the types and quantities of household garbage they generate rapidly increase. Therefore, it is urgent to develop a reasonable and effective method for garbage classification. This is important for resource recycling and environmental improvement and contributes to the sustainable development of production and the economy.
View Article and Find Full Text PDFComput Stat
September 2024
Department of Statistics, Purdue University, West Lafayette, IN 47907.
State estimation for large-scale non-Gaussian dynamic systems remains an unresolved issue, given nonscalability of the existing particle filter algorithms. To address this issue, this paper extends the Langevinized ensemble Kalman filter (LEnKF) algorithm to non-Gaussian dynamic systems by introducing a latent Gaussian measurement variable to the dynamic system. The extended LEnKF algorithm can converge to the right filtering distribution as the number of stages become large, while inheriting the scalability of the LEnKF algorithm with respect to the sample size and state dimension.
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