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Visual displays in the news media become critical during escalating events such as the COVID-19 pandemic, as they facilitate the communication of complex information to the public. This article investigates the use of graphs in Korea's news media during the COVID-19 outbreak. We selected 12 dates that represent turning points in the outbreak of the disease and collected news stories including graphs from seven Korean daily newspapers issued on those dates. First, we analyzed the usage of graphs in COVID-19 news stories. Quantitative analysis of the types and frequency of graphs used in COVID-19 news stories and qualitative analysis of the content of news stories containing graphs were conducted. Second, we identified cases in which readers may be biased by the mathematical misuse of graphs in the news stories covering COVID-19. The implications of these findings for future teaching and learning of graph literacy in school mathematics courses are discussed.

This study proposes an improved approach for monitoring the spatial concentrations of hourly particulate matter less than 2.5 μm in diameter (PM2.5) via a deep neural network (DNN) using geostationary ocean color imager (GOCI) images and unified model (UM) reanalysis data over the Korean Peninsula. The DNN performance was optimized to determine the appropriate training model structures, incorporating hyperparameter tuning, regularization, early stopping, and input and output variable normalization to prevent training dataset overfitting. Near-surface atmospheric information from the UM was also used as an input variable to spatially generalize the DNN model. The retrieved PM2.5 from the DNN was compared with estimates from random forest, multiple linear regression, and the Community Multiscale Air Quality model. The DNN demonstrated the highest accuracy compared to that of the conventional methods for the hold-out validation (root mean square error (RMSE) = 7.042 μg/m3, mean bias error (MBE) = −0.340 μg/m3, and coefficient of determination (R2) = 0.698) and the cross-validation (RMSE = 9.166 μg/m3, MBE = 0.293 μg/m3, and R2 = 0.49). Although the R2 was low due to underestimated high PM2.5 concentration patterns, the RMSE and MBE demonstrated reliable accuracy values (<10 μg/m3 and 1 μg/m3, respectively) for the hold-out validation and cross-validation. [ABSTRACT FROM AUTHOR]

The first total synthesis of the marine toxin (-)-gymnodimine (1) has been accomplished in a convergent manner. A highly diastereo- and enantioselective exo-Diels-Alder reaction catalyzed by a bis-oxazoline Cu(II) catalyst enabled rapid assembly of the spirocyclic core of gymnodimine. The preparation of the tetrahydrofuran fragment utilized a chiral auxiliary based anti-aldol reaction. Two major fragments, spirolactam 56 and tetrahydrofuran 55, were then coupled through an efficient Nozaki-Hiyama-Kishi reaction. An unconventional, ambient temperature t-BuLi-initiated intramolecular Barbier reaction of alkyl iodide 64 was employed to form the macrocycle. A late stage vinylogous Mukaiyama aldol addition of a silyloxyfuran to a complex cyclohexanone 83 appended the butenolide, and a few additional steps provided (-)-gymnodimine (1). A diastereomer of the natural product was also synthesized, C4-epi-gymnodimine (90), derived from the vinylogous Mukaiyama aldol addition., (© 2011 American Chemical Society)

A highly diastereoselective, nucleophile-promoted bis-cyclization process, employing readily available and tractable keto acid substrates, is described. This methodology provides concise access to bicyclic- and tricyclic-beta-lactones bearing tertiary carbinol centers and quaternary carbons, greatly extending the scope of previous routes to bicyclic-beta-lactones from aldehyde acid substrates. The utility of the method was demonstrated by application to an enantioselective synthesis of (+)-dihydroplakevulin A. This and related processes may be revealing a subtle interplay between [2+2] cycloaddition and nucleophile-catalyzed aldol lactonization (NCAL) reaction manifolds.