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  1. ; ; ; ; ; ; ; ; ( , Journal of Geophysical Research: Space Physics)
    Free, publicly-accessible full text available May 1, 2023
  2. ; ; ; ( , Physical Review Research)
    Free, publicly-accessible full text available October 1, 2022
  3. ; ; ; ( , Weather and Forecasting)
    Abstract Previous studies have identified environmental characteristics that skillfully discriminate between severe and significant-severe weather events, but they have largely been limited by sample size and/or population of predictor variables. Given the heightened societal impacts of significant-severe weather, this topic was revisited using over 150 000 ERA5 reanalysis-derived vertical profiles extracted at the grid-point nearest—and just prior to—tornado and hail reports during the period 1996–2019. Profiles were quality-controlled and used to calculate 84 variables. Several machine learning classification algorithms were trained, tested, and cross-validated on these data to assess skill in predicting severe or significant-severe reports for tornadoes and hail.more »Random forest classification outperformed all tested methods as measured by cross-validated critical success index scores and area under the receiver operating characteristic curve values. In addition, random forest classification was found to be more reliable than other methods and exhibited negligible frequency bias. The top three most important random forest classification variables for tornadoes were wind speed at 500 hPa, wind speed at 850 hPa, and 0–500-m storm-relative helicity. For hail, storm-relative helicity in the 3–6 km and -10 to -30 °C layers, along with 0–6-km bulk wind shear, were found to be most important. A game theoretic approach was used to help explain the output of the random forest classifiers and establish critical feature thresholds for operational nowcasting and forecasting. A use case of spatial applicability of the random forest model is also presented, demonstrating the potential utility for operational forecasting. Overall, this research supports a growing number of weather and climate studies finding admirable skill in random forest classification applications.« less
    Free, publicly-accessible full text available October 7, 2022
  4. ; ; ; ; ; ; ; ; ; ; et al ( , Ecology and Evolution)
    Free, publicly-accessible full text available January 1, 2023
  5. ; ; ; ( , Physical Review A)
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  6. ; ; ; ( , Optics Letters)
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  7. ; ; ( , International Journal of Climatology)
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  8. ; ; ( , Geological Society of America Abstracts with Programs)
    NOTE: COVID CANCELLED THE SOUTHEASTERN MEETING AND THEY TOLD US TO SUBMIT OUR ABSTRACT AGAIN TO THE NATIONAL MEETING; THIS IS THE NATIONAL MEETING ABSTRACT WHERE KIRSTEN PRESENTED HER TALK. We studied the population and size distribution of the parasitic foraminifer Cibicides antarcticus living on the shell of the Antarctic scallop Adamussium colbecki within Explorers Cove, western McMurdo Sound, Antarctica. Previous work examined populations and parasite load between two distinct geographic locations, but our study focuses on the population and size distribution of C. antarcticus within one embayment, Explorers Cove. We hypothesize that if A. colbecki are living in themore »same embayment and has one recruitment event, then C. antarcticus populations and their size distributions should be similar; but, if they have differing populations and sizes, they likely are recruiting from very localized microhabitats with varying recruitment events. Live A. colbecki were collected from three sites in Explorers Cove: Jamesway (water depth 24.4 m), Smallberg (9.1 m), and Anoxic Pit (9.1 m). Five top valves from each site were examined for C. antarcticus under 75x magnification. The foraminifera were counted, their spatial distribution noted, and their largest diameter was measured using ImageJ. All data from each site was pooled to compare the sites. Results indicate that all the sites had different populations of parasitic C. antarcticus. Smallberg had the most parasitic foraminifera (n = 663), followed by Jamesway (n = 319) and the Anoxic Pit site had the fewest (n = 55). The largest size classes (0.70–1.30 mm) occurred at Anoxic Pit and Smallberg, while the smallest size classes (0.18–0.70 mm) were found at Jamesway, the deepest site. The average size of Cibicides was also smaller at Jamesway (0.73 mm) compared to Smallberg (0.89 mm) and Anoxic Pit (0.91 mm). In general, C. antarcticus recruits to the youngest part of the scallop shell while larger adults are found on the oldest part of the shell. The skewed size frequency distributions and differing population sizes suggest that C. antarcticus has localized microhabitat recruitment in Explorers Cove, rather than one synchronous recruitment event.« less
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  9. ; ; ( , Nature Climate Change)
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  10. ; ; ; ( , Physical review)
    Unraveling the mechanisms of packing of DNA inside viral capsids is of fundamental importance to understanding the spread of viruses. It could also help develop new applications to targeted drug delivery devices for a large range of therapies. In this article, we present a robust, predictive mathematical model and its numerical implementation to aid the study and design of bacteriophage viruses for application purposes. Exploiting the analogies between the columnar hexagonal chromonic phases of encapsidated viral DNA and chromonic aggregates formed by plank-shaped molecular compounds, we develop a first-principles effective mechanical model of DNA packing in a viral capsid. Themore »proposed expression of the packing energy, which combines relevant aspects of the liquid crystal theory, is developed from the model of hexagonal columnar phases, together with that describing configurations of polymeric liquid crystals. The method also outlines a parameter selection strategy that uses available data for a collection of viruses, aimed at applications to viral design. The outcome of the work is a mathematical model and its numerical algorithm, based on the method of finite elements, and computer simulations to identify and label the ordered and disordered regions of the capsid and calculate the inner pressure. It also presents the tools for the local reconstruction of the DNA “scaffolding” and the center curve of the filament within the capsid.« less
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