Ublished. Nonetheless, towards the very best of our expertise, we achieved the very best identification

Ublished. Nonetheless, towards the very best of our expertise, we achieved the very best identification price of COVID-19 among other sorts of pneumonia making use of segmented CXR pictures in a much less biased configuration. As future perform, we aim to help keep enhancing our database to raise our classification overall performance and present much more robust estimates by using more CNN architectures for segmentation and classification. Moreover, we desire to apply extra sophisticated segmentation methods to isolate specific lung opacities caused by COVID-19. Likewise, we also would like to discover more approaches to evaluate the model predictions, like SHAP [48].Author Contributions: Conceptualization, L.O.T. and Y.M.G.C.; methodology, L.O.T., L.N. and Y.M.G.C.; validation, D.B., L.S.O. and G.D.C.C.; investigation, L.O.T. and R.M.P.; writing–original draft preparation, L.O.T.; writing–review and editing, R.M.P., D.B., L.S.O., L.N. and Y.M.G.C.; supervision, L.S.O., G.D.C.C. and Y.M.G.C.; project administration, Y.M.G.C.; All authors have study and agreed to the published version from the manuscript. Funding: This study has been partly supported by the National Council for Scientific and Technological Development (CNPq) and Coordena o de Aperfei amento de Pessoal de N el SuperiorBrasil (CAPES). Institutional Critique Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study is openly available on GitHub at https://github.com/lucasxteixeira/covid19-segmentation-paper (accessed on 19 August 2021). Acknowledgments: We appreciate the work of Joseph Paul Cohen in the University of Montreal for keeping a repository of COVID-19 pictures for the analysis neighborhood. Conflicts of Interest: The authors declare no conflict of interest.
sensorsArticleA Versatile Multiple-Pass Raman Technique for Industrial Trace Gas DetectionChunlei Shen, Chengwei Wen, Xin Huang and Xinggui Long Combretastatin A-1 Description Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics, Mianyang 621900, China; [email protected] (C.S.); [email protected] (C.W.); [email protected] (X.H.) Correspondence: [email protected]: Shen, C.; Wen, C.; Huang, X.; Long, X. A Versatile Multiple-Pass Raman Technique for Industrial Trace Gas Detection. Sensors 2021, 21, 7173. https://doi.org/10.3390/s21217173 Academic Editor: Anna Chiara De Luca Received: 28 September 2021 PF-05105679 Autophagy Accepted: 26 October 2021 Published: 28 OctoberAbstract: The quickly and in-line multigas detection is essential to get a selection of industrial applications. Inside the present operate, we demonstrate the utility of multiple-pass-enhanced Raman spectroscopy as a distinctive tool for sensitive industrial multigas detection. In place of applying spherical mirrors, D-shaped mirrors are chosen as cavity mirrors in our design, and 26 total passes are accomplished in a basic and compact multiple-pass optical program. Due to the big quantity of passes achieved inside the multiple-pass cavity, experiments with ambient air show that the noise equivalent detection limit (3) of 7.6 Pa (N2 ), eight.four Pa (O2 ) and 2.eight Pa (H2 O), which correspond to relative abundance by volume at 1 bar total pressure of 76 ppm, 84 ppm and 28 ppm, is usually achieved in one particular second having a 1.5 W red laser. Furthermore, this multiple-pass Raman method could be simply upgraded to a multiple-channel detection technique, along with a two-channel detection method is demonstrated and characterized. High utilization ratio of laser power (defined because the ratio of laser.