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Title: Dataset: Impact of salinization on lake stratification and spring mixing v1.0 L&O Letters

Scripts, model configurations and outputs to process the data and recreate the figures from Ladwig, R., Rock, L.A, Dugan, H.A. (-): Impact of salinization on lake stratification and spring mixing. This repository includes the setup and output from the lake model ensemble (GLM, GOTM, Simstrat) ran on the lakes Mendota and Monona. Scripts to run the models are located under /numerical and the scripts to process the results for the discussion of the paper are in the top main repository. The scripts to derive the theoretical solution are located under /analytical. Buoy monitoring data are located under /fieldmonitoring. The final figures are located under /figs_HD.

 
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Award ID(s):
1759865
NSF-PAR ID:
10439095
Author(s) / Creator(s):
; ;
Publisher / Repository:
Zenodo
Date Published:
Edition / Version:
v1.0
Subject(s) / Keyword(s):
["lake modeling","salinization","GLM","GOTM","Simstrat","chloride"]
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  2. Data files were used in support of the research paper titled “Mitigating RF Jamming Attacks at the Physical Layer with Machine Learning" which has been submitted to the IET Communications journal.

    ---------------------------------------------------------------------------------------------

    All data was collected using the SDR implementation shown here: https://github.com/mainland/dragonradio/tree/iet-paper. Particularly for antenna state selection, the files developed for this paper are located in 'dragonradio/scripts/:'

    • 'ModeSelect.py': class used to defined the antenna state selection algorithm
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    • 'standalone-radio-tuning.py': SDR implementation for hyperparameter tunning
    • 'standalone-radio-onmi.py': SDR implementation for omnidirectional mode only

    ---------------------------------------------------------------------------------------------

    Authors: Marko Jacovic, Xaime Rivas Rey, Geoffrey Mainland, Kapil R. Dandekar
    Contact: krd26@drexel.edu

    ---------------------------------------------------------------------------------------------

    Top-level directories and content will be described below. Detailed descriptions of experiments performed are provided in the paper.

    ---------------------------------------------------------------------------------------------

    classifier_training: files used for training classifiers that are integrated into SDR platform

    • 'logs-8-18' directory contains OTA SDR collected log files for each jammer type and under normal operation (including congested and weaklink states)
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    ray_tracing_emulation: contains files related to Drexel area, Art Museum, and UAV Drexel area validation RTE studies.

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  3. This data set for the manuscript entitled "Design of Peptides that Fold and Self-Assemble on Graphite" includes all files needed to run and analyze the simulations described in the this manuscript in the molecular dynamics software NAMD, as well as the output of the simulations. The files are organized into directories corresponding to the figures of the main text and supporting information. They include molecular model structure files (NAMD psf or Amber prmtop format), force field parameter files (in CHARMM format), initial atomic coordinates (pdb format), NAMD configuration files, Colvars configuration files, NAMD log files, and NAMD output including restart files (in binary NAMD format) and trajectories in dcd format (downsampled to 10 ns per frame). Analysis is controlled by shell scripts (Bash-compatible) that call VMD Tcl scripts or python scripts. These scripts and their output are also included.

    Version: 2.0

    Changes versus version 1.0 are the addition of the free energy of folding, adsorption, and pairing calculations (Sim_Figure-7) and shifting of the figure numbers to accommodate this addition.


    Conventions Used in These Files
    ===============================

    Structure Files
    ----------------
    - graph_*.psf or sol_*.psf (original NAMD (XPLOR?) format psf file including atom details (type, charge, mass), as well as definitions of bonds, angles, dihedrals, and impropers for each dipeptide.)

    - graph_*.pdb or sol_*.pdb (initial coordinates before equilibration)
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    Force Field Parameters
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    CHARMM format parameter files:
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    - par_all36_cgenff_no_nbfix.prm (CGenFF v4.4 for graphene) The NBFIX parameters are commented out since they are only needed for aromatic halogens and we use only the CG2R61 type for graphene.
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    These contain the most commonly used simulation parameters. They are called by the other NAMD configuration files (which are in the namd/ subdirectory):
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    - template_abf.namd (for adaptive biasing force)

    Minimization
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    - namd/min_*.0.namd

    Equilibration
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    - namd/eq_*.0.namd

    Adaptive biasing force calculations
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    - namd/eabfZRest7_graph_chp1404.0.namd
    - namd/eabfZRest7_graph_chp1404.1.namd (continuation of eabfZRest7_graph_chp1404.0.namd)

    Log Files
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    For each NAMD configuration file given in the last two sections, there is a log file with the same prefix, which gives the text output of NAMD. For instance, the output of namd/eabfZRest7_graph_chp1404.0.namd is eabfZRest7_graph_chp1404.0.log.

    Simulation Output
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    Scripts
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    CONTENTS
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    The directory contents are as follows. The directories Sim_Figure-1 and Sim_Figure-8 include README.txt files that describe the files and naming conventions used throughout this data set.

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    Sim_Figure-4: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.

    Sim_Figure-5: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 295 K.

    Sim_Figure-5_replica: Temperature replica exchange molecular dynamics simulations for the peptide cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) with 20 replicas for temperatures from 295 to 454 K.

    Sim_Figure-6: Simulation of the peptide molecule cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) in free solution (no graphite).

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    Sim_Figure-9: Two replicates of a simulation of nine peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.

    Sim_Figure-9_scrambled: Two replicates of a simulation of nine peptide molecules with the control sequence cyc(GGTPTTGGGGGGSGGPSGTGGC) at the graphite–water interface at 370 K.

    Sim_Figure-10: Adaptive biasing for calculation of the free energy of the folded peptide as a function of the angle between its long axis and the zigzag directions of the underlying graphene sheet.

     

    This material is based upon work supported by the US National Science Foundation under grant no. DMR-1945589. A majority of the computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CHE-1726332, CNS-1006860, EPS-1006860, and EPS-0919443. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562, through allocation BIO200030. 
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