Showing 261 - 280 results of 324 for search 'Last Train South', query time: 0.19s Refine Results
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    Prediction of thermal maturity by indirect methods using seismic attributes in the central part of the Persian Gulf by Elnaz Aliakbardoust, Mohammadhossein Adabi, Ali Kadkhodaie, Ali Chehrazi

    Published 2023-06-01
    “…The optimum number of attributes for MI prediction is four which shows the lowest prediction error, although the training error continuously decreases by adding more attributes. …”
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  10. 270

    Large, Persistent Epidemic of Adenovirus Type 4-Associated Acute Respiratory Disease in U.S. Army Trainees by K. Mills McNeill, Rose M. Hendrix, Jane L. Lindner, F. Ridgely Benton, Susan C. Monteith, Margaret A. Tuchscherer, Gregory C. Gray, Joel C. Gaydos

    Published 1999-12-01
    “…In May 1997, a large, persistent epidemic of adenovirus type 4-associated acute respiratory disease began at Fort Jackson, South Carolina, the largest army basic training center. …”
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  11. 271

    Veni, vidi, vici? Future spread and ecological impacts of a rapidly expanding invasive predator population by David R. Nelsen, Aaron G. Corbit, Angela Chuang, John F. Deitsch, Michael I. Sitvarin, David R. Coyle

    Published 2023-11-01
    “…Consistent with SDM predictions, T. clavata appears to be spreading faster to the north than to the south. Lastly, we conducted surveys to investigate potential ecological impacts of T. clavata on the diversity of native orb weaving spiders. …”
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    Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile by Santiago Yépez, Germán Velásquez, Daniel Torres, Rodrigo Saavedra-Passache, Martin Pincheira, Hayleen Cid, Lien Rodríguez-López, Angela Contreras, Frédéric Frappart, Jordi Cristóbal, Xavier Pons, Neftali Flores, Luc Bourrel

    Published 2024-01-01
    “…From this process the green chlorophyll index (GCI) was selected as the optimal choice for constructing the Chl-a retrieval model, reaching an R<sup>2</sup> of 0.88, while the red + NIR spectral index achieved the highest R<sup>2</sup> value (0.79) for turbidity analysis, although in the last case, it was necessary to incorporate data from several seasons for an adequate model training. …”
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