Journal: Scientific Reports

Article Title: Data-driven analysis of amino acid change dynamics timely reveals SARS-CoV-2 variant emergence

doi: 10.1038/s41598-021-00496-z

Figure Lengend Snippet: Data-driven identification of variants in Japan. ( a–c ), left panels: Four hits in Japan (two of which occurring in the same week), corresponding to clusters JP_008 (Jun-wk4-20), JP_025 (Aug-wk3-20), JP_093, and JP_098 (both observed in Mar-wk1-21). Central panels: Cluster-dictionary similarity ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$J_{cd}$$\end{document} J cd ) for the four early hits showing, at time of detection, to strongly match ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$J_{cd} = 1$$\end{document} J cd = 1 in all cases) the four lineages B.1.1.284 (JP2), B.1.1.214 (JP1), R.1 (JP3), and B.1.1.7 (Alpha); values \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$J_{cd} < 0.1$$\end{document} J cd < 0.1 are not shown. Right panels: Community detection applied to the within-cluster change co-occurrence matrix evaluated over the period of time between the emergence of two subsequent variants. The resulting interaction network is plotted using a force-directed layout , with edge lengths inversely proportional to link weights. Colors indicate nodes belonging to communities that strongly match known lineages, other communities are in gray-scale shades. ( d–g ): Temporal dynamics of the four identified variants. In each scatter plot, the left y-axis value represents the average prevalence of the changes in the cluster-dictionary intersection, circle size represents the cluster-dictionary similarity ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$J_{cd} < 0.1$$\end{document} J cd < 0.1 not shown), while circle color is proportional to the log-ratio between the number of changes in the cluster and in the dictionary. Warnings are marked with a labeled arrow. In the background, the number of reported COVID-19 infections (thousand cases, right axis) in Japan . Plots were created using MATLAB R2021a ( http://www.mathworks.com ). All graphics were further processed using Adobe Illustrator 2021 ( http://www.adobe.com ).

Article Snippet: The map was created using https://mapchart.net/ on 4 July 2021 and plots were created using MATLAB R2021a ( http://www.mathworks.com ).

Techniques: Labeling

Journal: Scientific Reports

Article Title: Data-driven analysis of amino acid change dynamics timely reveals SARS-CoV-2 variant emergence

doi: 10.1038/s41598-021-00496-z

Figure Lengend Snippet: Emergence of variants in their country of origin. Details of the variant dynamics plots shown within insets as in panels (d–g) of Fig. . The vertical dashed lines indicate the dates of hits using our method. Estimates of reported cases are taken from Johns Hopkins/Our World in Data , except for the US, for which data comes from the Centers for Disease Control and Prevention . The map was created using https://mapchart.net/ on 4 July 2021 and plots were created using MATLAB R2021a ( http://www.mathworks.com ). All graphics were further processed using Adobe Illustrator 2021 ( http://www.adobe.com ).

Article Snippet: The map was created using https://mapchart.net/ on 4 July 2021 and plots were created using MATLAB R2021a ( http://www.mathworks.com ).

Techniques: Variant Assay

Journal: Scientific Reports

Article Title: Data-driven analysis of amino acid change dynamics timely reveals SARS-CoV-2 variant emergence

doi: 10.1038/s41598-021-00496-z

Figure Lengend Snippet: Temporal dynamics of notable variants in European countries ( a ) and in the US ( b ). Color shading for European countries indicates the timing of emergence of the Alpha variant (the lighter, the later). Different colors code instead the couple/triple of variants (Epsilon, Iota, Alpha, and US1/US2 as aliases of B.1.2 and B.1.596—only US2 is shown here) that were detected and tracked in the US using our method. Inset details as in panels (d–g) of Fig. . The blank maps of Europe and US were retrieved from https://commons.wikimedia.org/wiki/File:Europe_political_chart_complete_blank.svg and https://commons.wikimedia.org/wiki/File:USA_blank.svg on 4 July 2021 and plots were created using MATLAB R2021a ( http://www.mathworks.com ). All graphics were further processed using Adobe Illustrator 2021 ( https://www.adobe.com ).

Article Snippet: The map was created using https://mapchart.net/ on 4 July 2021 and plots were created using MATLAB R2021a ( http://www.mathworks.com ).

Techniques: Variant Assay

Journal: Scientific Reports

Article Title: Smartphones enabled up to 58 s strong-shaking warning in the M7.8 Türkiye earthquake

doi: 10.1038/s41598-024-55279-z

Figure Lengend Snippet: Relevant information regarding the EQN detection of the M7.8 Pazarcik earthquake on 6 February 2023. ( A ) State of the EQN smartphone network at the time of the earthquake detection, including: smartphones that detected the earthquake (filled circles), active monitoring smartphones (transparent circles) and smartphones with the EQN app installed but not monitoring (red circles). Map generated by authors using the MATLAB R2023a software. ( B ) Smartphone triggering delay (s) from origin time versus epicentral distance (km).

Article Snippet: Map generated by authors using the MATLAB R2023a software.

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: Smartphones enabled up to 58 s strong-shaking warning in the M7.8 Türkiye earthquake

doi: 10.1038/s41598-024-55279-z

Figure Lengend Snippet: Spatial distribution of the warning time (s), with respect to the exceedance of the 12%g PGA threshold, provided by the EQN system during the M7.8 Pazarcik earthquake. Map generated by authors using the MATLAB R2023a software.

Article Snippet: Map generated by authors using the MATLAB R2023a software.

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: Smartphones enabled up to 58 s strong-shaking warning in the M7.8 Türkiye earthquake

doi: 10.1038/s41598-024-55279-z

Figure Lengend Snippet: ( A ) Spatial distribution of macroseismic intensity . ( B ) Spatial distribution of the population. The Fault rupture is taken from Reitman et al. (2023), while macroseismic intensity is taken from Hancilar et al. . Legend in Fig. . Maps generated by authors using the MATLAB R2023a software.

Article Snippet: Map generated by authors using the MATLAB R2023a software.

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: First top-down diurnal adjustment to NO x emissions inventory in Asia informed by the Geostationary Environment Monitoring Spectrometer (GEMS) tropospheric NO 2 columns

doi: 10.1038/s41598-024-76223-1

Figure Lengend Snippet: Monthly averages of hourly daytime tropospheric NO 2 columns (molecules/cm 2 ) observed and modeled during MAM 2022. (a) GEMS NO 2 columns during daylight hours, (b) CMAQ-simulated NO 2 columns during daylight hours, (c) differences (b - a), (d) LEO proxy NO 2 columns at 04:45 UTC, (e) CMAQ-simulated NO 2 columns at 04:45 UTC, (f) differences (e - d). The maps were created using MATLAB R2024a by MathWorks, Inc. ( https://www.mathworks.com/products/matlab.html ).

Article Snippet: The maps were created using MATLAB R2024a by MathWorks, Inc. ( https://www.mathworks.com/products/matlab.html ).

Techniques:

Journal: Scientific Reports

Article Title: First top-down diurnal adjustment to NO x emissions inventory in Asia informed by the Geostationary Environment Monitoring Spectrometer (GEMS) tropospheric NO 2 columns

doi: 10.1038/s41598-024-76223-1

Figure Lengend Snippet: Monthly averages of hourly daytime NO x emissions (moles/s) during MAM 2022. (a) the a priori emissions, (b) the a posteriori emissions adjusted using GEMS tropospheric NO 2 columns, (c) differences (b - a), (d) the a posteriori emissions adjusted using LEO proxy NO 2 columns, and (e) differences (d - a), (f) differences (d - b). The maps were created using MATLAB R2024a by MathWorks, Inc. ( https://www.mathworks.com/products/matlab.html ).

Article Snippet: The maps were created using MATLAB R2024a by MathWorks, Inc. ( https://www.mathworks.com/products/matlab.html ).

Techniques:

Journal: Scientific Reports

Article Title: First top-down diurnal adjustment to NO x emissions inventory in Asia informed by the Geostationary Environment Monitoring Spectrometer (GEMS) tropospheric NO 2 columns

doi: 10.1038/s41598-024-76223-1

Figure Lengend Snippet: Monthly averages of hourly daytime tropospheric NO 2 columns (molecules/cm 2 ) modeled during MAM 2022. (a) modeled using the a priori emissions, (b) modeled after the GEMS-informed adjustment, (c) modeled after the LEO-informed adjustment. The maps were created using MATLAB R2024a by MathWorks, Inc. ( https://www.mathworks.com/products/matlab.html ).

Article Snippet: The maps were created using MATLAB R2024a by MathWorks, Inc. ( https://www.mathworks.com/products/matlab.html ).

Techniques: