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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Automating Data Analysis For Two-Dimensional Gas Chromatography/Time-Of-Flight Mass Spectrometry Non-Targeted Analysis Of Comparative Samples, Ivan A. Titaley, O. Maduka Ogba, Leah Chibwe, Eunha Hoh, Paul H.-Y. Cheong, Staci L. Massey Simonich
Automating Data Analysis For Two-Dimensional Gas Chromatography/Time-Of-Flight Mass Spectrometry Non-Targeted Analysis Of Comparative Samples, Ivan A. Titaley, O. Maduka Ogba, Leah Chibwe, Eunha Hoh, Paul H.-Y. Cheong, Staci L. Massey Simonich
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Non-targeted analysis of environmental samples, using comprehensive two‐dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC/ToF-MS), poses significant data analysis challenges due to the large number of possible analytes. Non-targeted data analysis of complex mixtures is prone to human bias and is laborious, particularly for comparative environmental samples such as contaminated soil pre- and post-bioremediation. To address this research bottleneck, we developed OCTpy, a Python™ script that acts as a data reduction filter to automate GC × GC/ToF-MS data analysis from LECO® ChromaTOF® software and facilitates selection of analytes of interest based on peak area …
Generating Species Assemblages For Restoration And Experimentation: A New Method That Can Simultaneously Converge On Average Trait Values And Maximize Functional Diversity, David C. Laughlin, Loïc Chalmandrier, Chaitanya Joshi, Michael Renton, John M. Dwyer, Jennifer L. Funk
Generating Species Assemblages For Restoration And Experimentation: A New Method That Can Simultaneously Converge On Average Trait Values And Maximize Functional Diversity, David C. Laughlin, Loïc Chalmandrier, Chaitanya Joshi, Michael Renton, John M. Dwyer, Jennifer L. Funk
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
1.Restoring resilient ecosystems in an era of rapid environmental change requires a flexible framework for selecting assemblages of species based on functional traits. However, current trait‐based models have been limited to algorithms that select species assemblages that only converge on specified average trait values, and could not accommodate the common desire among restoration ecologists to generate functionally diverse assemblages.
2.We have solved this problem by applying a nonlinear optimization algorithm to solve for the species relative abundances that maximize Rao's quadratic entropy (Q) subject to other linear constraints. Rao's Q is a closed‐form algebraic expression of functional diversity …