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Plasma Vortex Theory is the engineered application of known sciences to create efficient velocity during spaceflight using electricity and propellant gas. Oscillation of granulate and liquid reagents using simple harmonic motion has been shown to excite particles to form geometric patterns when using calibrated frequencies discovered by the late Dr. Hans Jenny. Calibration methods will be used to attain vortex formations in the reagents Lycopodium, Sulfur Hexafluoride, CO2 and Xenon. Frequencies which form vortex patterns in Lycopodium powder using known methods will be used to excite Sulfur Hexafluoride (density 6.17 kg/m3), at incremental partial pressures. Air-filled mass objects will be used to observe acceleration, force and velocity data for a dense gas during oscillation and vortex formation. Xenon gas (density 5.761 kg/m3) will be ionized by external electrode field before, during and after vortex formations are created using acoustic measures.
Data Types:
  • Software/Code
Plasma Vortex Theory is the engineered application of known sciences to create efficient velocity during spaceflight using electricity and propellant gas. Oscillation of granulate and liquid reagents using simple harmonic motion has been shown to excite particles to form geometric patterns when using calibrated frequencies discovered by the late Dr. Hans Jenny. Calibration methods will be used to attain vortex formations in the reagents Lycopodium, Sulfur Hexafluoride, CO2 and Xenon. Frequencies which form vortex patterns in Lycopodium powder using known methods will be used to excite Sulfur Hexafluoride (density 6.17 kg/m3), at incremental partial pressures. Air-filled mass objects will be used to observe acceleration, force and velocity data for a dense gas during oscillation and vortex formation. Xenon gas (density 5.761 kg/m3) will be ionized by external electrode field before, during and after vortex formations are created using acoustic measures.
Data Types:
  • Software/Code
Note: This application is currently designed to run on Windows and requires the 2016 LabVIEW runtime engine. It is available free to download in the references. Brachistochrone- An example of how a cycloid is the solution to the shortest path between two points in a particular potential.2-D Membrane Modes- The first few normal modes of a 2-D membrane.Coupled Harmonic Oscillators- Select up to 10 masses (and 11 springs) and examine their normal modes of oscillation ordered in ascending frequency with various spring constants.
Data Types:
  • Software/Code
Supplementary material for the paper: Taylor, M.H., Mildenberger, T.K., 2017. Extending electronic length frequency analysis in R. Fisheries Management and Ecology. https://doi.org/10.1111/fme.12232 Description: The R scripts demonstrate use of a recent implementation of extending electronic length frequency analysis (ELEFAN) (Pauly and David 1980, 1981) for estimating growth function parameters in the R package "TropFishR" (Mildenberger et al., 2017). In addition to the traditional ELEFAN methodology, TropFishR also includes two optimization approaches for growth curve fitting: 1. Generalized Simulated Annealing ('ELEFAN_SA'), and 2. Genetic Algorithm ('ELEFAN_GA'). The scripts contain a demonstration of both optimization methods using a generated length-frequency data set with known seasonally-oscillating von Bertalanffy growth function (soVBGF) parameters. References: Mildenberger, T.K., Taylor, M.H., Wolff, M., 2017. TropFishR: Tropical Fisheries Analysis with R. R package version 1.1.3, https://github.com/tokami/TropFishR. Pauly, D., David, N., 1980. An objective method for determining fish growth from length-frequency data. ICLARM Newsl. 3, 13–15. Pauly, D., David, N., 1981. ELEFAN I, a basic program for the objective extraction of growth parameters from length-frequency data. Berichte Dtsch. Wiss. Kommissuib Für Meeresforsch. 28, 205–211. Contents: Supplement_Taylor_Mildenberger.Rproj - RStudio project file. When opened in RStudio, script file paths should remain compatible across platforms. /figures - Graphical outputs. /results - Results of scripts (e.g. .Rdata and .csv files) /scripts - Scripts used in the analysis. Script names begin with a number indicating the required order: /scripts/01_create_LFQ_data.R - Not required, but shows the settings for LFQ data generation ("synLFQ4" data in TropFishR package) /scripts/02_basic_demonstration.R - Shows the basic setup of ELEFAN_GA and ELEFAN_SA fitting procedures. /scripts//03_sensitivity_analysis.R - Runs analyses used in the work. Warning: requires sufficient computation time (ca. 12 hours on modern personal computer with 4 processing cores). /scripts/04_stats_and_figures - Reproduces figures and statistical analysis using results objects. /scripts/05_make_supplementary_figures_doc.R - Runs the R Markdown document "supplementary_figures.Rmd" to create "supplementary_figures.pdf"
Data Types:
  • Software/Code
Supplementary material for the paper: Taylor, M.H., Mildenberger, T.K., 2017. Extending electronic length frequency analysis in R. Fisheries Management and Ecology. https://doi.org/10.1111/fme.12232 Description: The R scripts demonstrate use of a recent implementation of extending electronic length frequency analysis (ELEFAN) (Pauly and David 1980, 1981) for estimating growth function parameters in the R package "TropFishR" (Mildenberger et al., 2017). In addition to the traditional ELEFAN methodology, TropFishR also includes two optimization approaches for growth curve fitting: 1. Generalized Simulated Annealing ('ELEFAN_SA'), and 2. Genetic Algorithm ('ELEFAN_GA'). The scripts contain a demonstration of both optimization methods using a generated length-frequency data set with known seasonally-oscillating von Bertalanffy growth function (soVBGF) parameters. References: Mildenberger, T.K., Taylor, M.H., Wolff, M., 2017. TropFishR: Tropical Fisheries Analysis with R. R package version 1.1.3, https://github.com/tokami/TropFishR. Pauly, D., David, N., 1980. An objective method for determining fish growth from length-frequency data. ICLARM Newsl. 3, 13–15. Pauly, D., David, N., 1981. ELEFAN I, a basic program for the objective extraction of growth parameters from length-frequency data. Berichte Dtsch. Wiss. Kommissuib Für Meeresforsch. 28, 205–211. Contents: Supplement_Taylor_Mildenberger.Rproj - RStudio project file. When opened in RStudio, script file paths should remain compatible across platforms. /figures - Graphical outputs. /results - Results of scripts (e.g. .Rdata and .csv files) /scripts - Scripts used in the analysis. Script names begin with a number indicating the required order: /scripts/01_create_LFQ_data.R - Not required, but shows the settings for LFQ data generation ("synLFQ4" data in TropFishR package) /scripts/02_basic_demonstration.R - Shows the basic setup of ELEFAN_GA and ELEFAN_SA fitting procedures. /scripts//03_sensitivity_analysis.R - Runs analyses used in the work. Warning: requires sufficient computation time (ca. 12 hours on modern personal computer with 4 processing cores). /scripts/04_stats_and_figures - Reproduces figures and statistical analysis using results objects. /scripts/05_make_supplementary_figures_doc.R - Runs the R Markdown document "supplementary_figures.Rmd" to create "supplementary_figures.pdf"
Data Types:
  • Software/Code
Supplementary material for the paper: Taylor, M.H., Mildenberger, T.K., 2017. Extending electronic length frequency analysis in R. Fisheries Management and Ecology. https://doi.org/10.1111/fme.12232 Description: The R scripts demonstrate use of a recent implementation of ELEFAN I (Pauly and David 1980, 1981) in the R package TropFishR (Mildenberger et al., 2017). In addition to the traditional methodology, TropFishR also includes two optimization approaches for growth curve fitting: 1. Generalized Simulated Annealing ('ELEFAN_SA'), and 2. Genetic Algorithm ('ELEFAN_GA'). The scripts contain a demonstration of both optimization methods using a generated length-frequency data set with known seasonally-oscillating von Bertalanffy growth function (soVBGF) parameters. A more detailed test of parameter estimation performance is conducted using the ELEFAN_GA approach under variable settings. References: Mildenberger, T.K., Taylor, M.H., Wolff, M., 2017. TropFishR: Tropical Fisheries Analysis with R. R package version 1.1.3, https://github.com/tokami/TropFishR. Pauly, D., David, N., 1980. An objective method for determining fish growth from length-frequency data. ICLARM Newsl. 3, 13–15. Pauly, D., David, N., 1981. ELEFAN I, a basic program for the objective extraction of growth parameters from length-frequency data. Berichte Dtsch. Wiss. Kommissuib Für Meeresforsch. 28, 205–211. Contents: Supplement_Taylor_Mildenberger.Rproj - RStudio project file. When opened in RStudio, script file paths should remain compatible across platforms. /figures - Graphical outputs. /packages - R package versions used at the time of the study. /results - Results of scripts (e.g. .Rdata and .csv files) /scripts - Scripts used in the analysis. Script names begin with a number indicating the required order: /01_create_LFQ_data.R - Not required, but shows the settings for LFQ data generation ("synLFQ4" data in TropFishR package) /02_basic_demonstration.R - Shows the basic setup of ELEFAN_GA and ELEFAN_SA fitting procedures. /03_sensitivity_analysis.R - Runs analyses used in the work. Warning: requires sufficient computation time (ca. 12 hours on modern personal computer with 4 processing cores). /04_stats_and_figures - Reproduces figures and statistical analysis using results objects. /05_make_supplementary_figures_doc.R - Runs the R Markdown document "supplementary_figures.Rmd" to create "supplementary_figures.pdf"
Data Types:
  • Software/Code
Supplementary material for the paper: Taylor, M.H., Mildenberger, T.K., 2016. Extending ELEFAN in R. https://dx.doi.org/10.6084/m9.figshare.4206561 Description: The R scripts demonstrate use of a recent implementation of ELEFAN I (Pauly and David 1980, 1981) in the R package TropFishR (Mildenberger et al., 2016). In addition to the traditional methodology, TropFishR also includes two optimization approaches for growth curve fitting: 1. Generalized Simulated Annealing ('ELEFAN_SA'), and 2. Genetic Algorithm ('ELEFAN_GA'). The scripts contain a demonstration of both optimization methods using a generated length-frequency data set with known seasonally-oscillating von Bertalanffy growth function (soVBGF) parameters. A more detailed test of parameter estimation performance is conducted using the ELEFAN_GA approach under variable settings. References: Mildenberger, T.K., Taylor, M.H., Wolff, M., 2017. TropFishR: Tropical Fisheries Analysis with R. R package version 1.1.2, https://github.com/tokami/TropFishR. Pauly, D., David, N., 1980. An objective method for determining fish growth from length-frequency data. ICLARM Newsl. 3, 13–15. Pauly, D., David, N., 1981. ELEFAN I, a basic program for the objective extraction of growth parameters from length-frequency data. Berichte Dtsch. Wiss. Kommissuib Für Meeresforsch. 28, 205–211. Contents: Supplement_Taylor_Mildenberger.Rproj - RStudio project file. When opened in RStudio, script file paths should remain compatible across platforms. /figures - Graphical outputs. /packages - R package versions used at the time of the study. /results - Results of scripts (e.g. .Rdata and .csv files) /scripts - Scripts used in the analysis. Script names begin with a number indicating the required order: /01_create_LFQ_data.R - Not required, but shows the settings for LFQ data generation ("synLFQ4" data in TropFishR package) /02_basic_demonstration.R - Shows the basic setup of ELEFAN_GA and ELEFAN_SA fitting procedures. /03_sensitivity_analysis.R - Runs analyses used in the work. Warning: requires sufficient computation time (ca. 12 hours on modern personal computer with 4 processing cores). /04_stats_and_figures - Reproduces figures and statistical analysis using results objects. /05_make_supplementary_figures_doc.R - Runs the R Markdown document "supplementary_figures.Rmd" to create "supplementary_figures.pdf"
Data Types:
  • Software/Code
Supplementary material for the paper: Taylor, M.H., Mildenberger, T.K., 2016. Extending ELEFAN in R. doi:10.6084/m9.figshare.4206561 Description: The R scripts demonstrate use of a recent implementation of ELEFAN I (Pauly and David 1980, 1981) in the R package TropFishR (Mildenberger et al., 2016). In addition to the traditional methodology, TropFishR also includes two optimization approaches for growth curve fitting: 1. Generalized Simulated Annealing ('ELEFAN_SA'), and 2. Genetic Algorithm ('ELEFAN_GA'). The scripts contain a demonstration of both optimization methods using a generated length-frequency data set with known seasonally-oscillating von Bertalanffy growth function (soVBGF) parameters. A more detailed test of parameter estimation performance is conducted using the ELEFAN_GA approach under variable settings. References: Mildenberger, T.K., Taylor, M.H., Wolff, M., 2016. TropFishR: Tropical Fisheries Analysis with R. R package version 1.0.0, https://github.com/tokami/TropFishR. Pauly, D., David, N., 1980. An objective method for determining fish growth from length-frequency data. ICLARM Newsl. 3, 13–15. Pauly, D., David, N., 1981. ELEFAN I, a basic program for the objective extraction of growth parameters from length-frequency data. Berichte Dtsch. Wiss. Kommissuib Für Meeresforsch. 28, 205–211. Contents: Supplement_Taylor_Mildenberger.Rproj - RStudio project file. When opened in RStudio, script file paths should remain compatible across platforms. /figures - Graphical outputs. /packages - R package versions used at the time of the study. /results - Results of scripts (e.g. .Rdata and .csv files) /scripts - Scripts used in the analysis. Script names begin with a number indicating the required order: /01_create_LFQ_data.R - Not required, but shows the settings for LFQ data generation ("synLFQ4" data in TropFishR package) /02_analysis.R - Runs analyses used in the work. Warning: the section titled "GA and sensitivity of ELEFAN" requires sufficient computation time (ca. 12 hours on modern personal computer with 4 processing cores). /03_stats_and_figures - Reproduces figures and statistical analysis using results objects.
Data Types:
  • Software/Code