This archive contains the raw data material for the manuscript

"From Fabry-Pérot Interference to Coulomb Blockade at Fixed Hole Number"
D. R. Schmid, P. L. Stiller, A. Dirnaichner, A. K. Hüttel
arXiv:2005.01183

In particular, you will find here

* preparatory plots made with Gnuplot [1], and the corresponding Gnuplot scripts
* the raw data files in Gnuplot format, i.e., tab-separated columns

The raw data files (ending in .dat) contain comment lines at the start (beginning with #) where in each file the columns are explained. The data has been measured using Lab::Measurement [2,3].

[1] http://gnuplot.info/
[2] https://www.labmeasurement.de/
[3] Computer Physics Communications 234, 216–222 (2019)

This zip file contains the scripts, gnuplot and data files needed to generate the figures showing the numerical results presented in [1].

[1] S. Herrería-Alonso, A. Suárez-González, M. Rodríguez-Pérez and C. López-García, "Enhancing LoRaWAN scalability with Longest First Slotted CSMA," in Computer Networks, vol. 216, article number 109252, Oct. 2022, doi: 10.1016/j.comnet.2022.109252.

This dataset is associated to "A localization transition underlies the mode-coupling crossover of glasses" by D. Coslovich, A. Ninarello and L. Berthier [https://arxiv.org/abs/1811.03171].

It includes post-processed data and workflow to reproduce the analysis and the figures of the article and of the supplemental information.

Supplementary information is available in the Supplement section of the project document (project.pdf).

The easiest way to reproduce the analysis and figures, and then check the results, is to use the make script:

./make all

Alternatively, the analysis and figures can be reproduced in any of the following ways

• following the workflow described in the org-mode project file project.org
• using the individual bash and gnuplot scripts in src/ and plots/

Folders and files description:

• analysis/: post-processed data
• src/: bash, python and gnuplot scripts needed to reproduce the analysis
• plots/: eps figures that appear in the paper and supplemental information and associated gnuplot scripts
• make: convenience script to setup the python environment, analyze the data and reproduce the figures
• project.org: org-mode project file with workflow and supplemental information
• project.pdf: pdf project file with workflow and supplemental information
• project.bib: bibtex bibliography associated to the project

Dependencies:

• numpy (1.16.3)
• scipy (1.3.1)
• argh (0.26.2)
• atooms (1.9.1)
• gnuplot (5.0.0)

The analysis scripts have been tested with python versions 2.7 and 3.5. The org-mode project file has been tested with org version 9.1.13.

Note: this dataset does not contain (at least yet) the particle configurations associated to saddle points, only the post-processed files containing selected properties of their normal modes.

Changelog:

• 1.0.0
  • initial submission
• 1.1.0
  • add "all" target to ./make
  • fix ./make check
  • improve setup description
• 1.2.0
  • add analysis of eigenvector-following optimizations
  • small changes and fixes to analysis scripts
• 1.2.1
  • fix ./src/adiff.py
  • fix final check of ./make all
  • improve pdf layout
  • improve handling of org properties

1. Introduction

Welcome to the documentation for the code, data, and plotting scripts corresponding to the paper titled "Method Comparison for Simulating Non-Gaussian Beams and Diffraction for Precision Interferometry". This repository contains resources to replicate the simulation results presented in the paper. Please carefully review the instructions below to ensure the successful execution of the code, data generation, and plotting.

2. Dependencies

Before running the code, it is necessary to install IfoCAD (version 2022/10, git commit adf19a5b) in your environment. Please note, that IfoCAD is currently prepared for publication. However, because IfoCAD is not yet publically available, we provide here likewise the data generated by IfoCAD. Here is the introduction page of IfoCAD: https://www.aei.mpg.de/ifocad. Additionally, the plotting scripts require the installation of gnuplot.

3. Directory Structure

The code, data, and plotting scripts are organized according to the structure of the paper's sections. Each section corresponds to a specific folder. Here is a brief overview of the file structure: Section2/: Code, data, and plotting scripts for Section 2 Section3/: Code, data, and plotting scripts for Section 3 ...

4. Running the Code

Step 1:

Install Dependencies Ensure IfoCAD is installed. The open-source release is anticipated soon. Also, make sure gnuplot is installed for the plotting scripts.

Step 2:

Run the Code Navigate to the specific section folder and to run the code.

5. Generating Data

After running the code, the generated data will be stored in the file path configured in the code. Utilize this data for further analysis and visualization.

6. Plotting Scripts

Each section's plotting scripts are located in their respective folders. Run these scripts sequentially to generate plots consistent with those presented in the paper. Make sure to have gnuplot installed for proper execution.

For any issues or questions during usage, feel free to contact us.

Thank you for using our resources!

When referring to this dataset, please cite the corresponding research article (J. Chem. Phys. 156, 234109 (2022); https://doi.org/10.1063/5.0092063) instead of citing this dataset. This dataset includes the data and figure gnuplot-script files necessary to produce all figures for the article "Real-time non-adiabatic dynamics in the one-dimensional Holstein model: Trajectory-based vs exact methods", J. Chem. Phys. 156, 234109 (2022), with the exception of the "Data from Ref. 87"-lines in Fig. 33 and Fig. 34. These two figures include data from Ref. 87, for which we refer to the authors of that reference. The "data" folder includes the data obtained from our simulations with the various methods presented in the article. See the detailed README.txt within that folder for the structure of the data. The "figure_scripts" folder includes all gnuplot figure scripts to produce the figures of the paper (excluding the "Data from Ref. 87"-lines in Figs. 33 and 34). See the contained README.txt in that folder for more details.

The dataset consists of .txt files that contain the raw experimental or simulation data used to generate the figures in the manuscript. Each .txt file corresponds to a specific figure in the paper and contains the data points used to plot the figures. To generate the PDF figures directly from the data: 1. Download and install Gnuplot (if not already installed). 2. Run the script mainPRLhjh.plt in Gnuplot, which is configured to automatically read the .txt files and generate the corresponding plots. 3. The output will be in PDF format, matching the figures presented in the manuscript. This dataset allows other researchers to easily reproduce the figures from the manuscript or use the raw data for further analysis.

This dataset contains the numerical data accompanying the "Origin of the anomalous Hall effect in Cr-doped RuO2" paper.
Computations were performed using VASP 6.3.0, and the postprocessing necessary to obtain the band structures was done using the vaspkit package.

The Data directory contains the necessary input files to reproduce the computations and the output files produced by the computations.
The Plots directory contains the data and gnuplot scripts used to plot figures presented in the paper:

• Fig. 1: energies and weighted average of local magnetic moments of various magnetic phases of Cr-doped RuO2 in the VCA approximation
• Fig. 2: the absolute value of total magnetic moment with corresponding energy and local magnetic moment for a set of supercells of RuO2 with 20% Cr doping
• Fig. 3: magnetic moment distribution for the two lowest-energy structures
• Fig. 4: effective Curie-Weiss moments from Ref. [14] compared to a Cr-only model and anomalous Hall conductivity measured in Ref. [14] and its derivative with respect to the magnetic moment
• Fig. 5: band-structure plots for the lowest-energy structure among the set of studied supercells

To produce the figure one simply runs plot.sh script in the respective directory: the script will use gnuplot and pdflatex to produce the plots.
The data necessary to produce plots can be collected using the get.sh or get_data.sh scripts.
In the case of VASP computations, the total energy is reported in the OUTCAR file at the line containing the free energy TOTEN = token, the local magnetization in the block after the magnetization token, and the total magnetic moment in the OSZICAR file at the line containing the mag=token. The input parameters are specified in the INCAR file and the k-grid mesh in KPOINTS file. The pseudopotentials should be obtained from the VASP distribution and saved as a single file, named POTCAR.

The following POTCARs were used for VASP calculations:
md5sum name and location
b5c924befef4a180481bb6f65e4e516d potpaw_LDA.54/Ru_pv/POTCAR
6bfe8c9fc881319367b05c52d7f764ba potpaw_LDA.54/Cr_pv/POTCAR
dd29215744b63de40827d7952527f753 potpaw_LDA.54/POTCAR

Licenses

The data is licensed under CC-BY, the code (scripts) are licensed under MIT.

Thermal data measured by DSC for blends of PLLA with PLCL(70:30)-PEG or PLCL(80:20)-PEG, either before (Fig01) or after (Fig08) degradation. Contains Microsoft Excel files with Tg measurements and experimental details, as well as measured changes in enthalpy of relaxation after degradation. Example raw DSC curves are also given (.txt format), as well as script and data files for generating plots (.txt). Molecular weight distributions for blends of PLLA with PLCL(70:30)-PEG or PLCL(80:20)-PEG, measured by GPC, either before (Fig02) or after (Fig06) degradation. Contains Microsoft Excel files with raw GPC curves. Average molecular weights are also given in a Microsoft Excel file (Table01). Measured distributions for blends are compared with a calculated distribution based on a linear combination of individual blend components. Script and data files for generating plots (.txt) are also included. Mechanical testing data from tensile tests of blends of PLLA with PLCL(70:30)-PEG or PLCL(80:20)-PEG (Fig03). Tests were carried out before degradation in the dry state, before degradation in 37°C water, and after degradation in 37°C water. Contains Microsoft Excel files with measured properties and example stress-strain curves, as well as script and data files for generating plots (.txt). Degradation pH measurements from degradation of blends of PLLA with PLCL(70:30)-PEG or PLCL(80:20)-PEG in PBS at 37°C (Fig04 and Fig05). Contains Microsoft Excel files with raw pH measurements over time, as well as photographs of polymer samples during degradation. Script and data files for generating plots (.txt) are also included. Raw SEM images (.tif) of an 80:20 blend of PLLA and PLCL(70:30)-PEG before and after degradation are included (Fig07). Crystallinity data measured by XRD for blends of PLLA with PLCL(70:30)-PEG or PLCL(80:20)-PEG, either before (FigS1) or after (Fig09) degradation. Contains Microsoft Excel files experimental details, and sample codes. Example raw XRD patterns are also given (.uxd format), as well as script and data files for generating plots (.txt). Plots are generated using gnuplot (www.gnuplot.info),

The experimental dataset from Havlasek, Smilauer, and Nezerka's paper "Drying-Induced Deformation in Concrete: Insights from a 5-Year Study" is available in five archives. These archives contain the data organized according to the specified structure and accompanying Gnuplot source files for easier data visualization.

Full experimental description is given in the paper and in the preceding publication entitled "Shrinkage-induced deformations and creep of structural concrete: 1-year measurements and numerical prediction accessible from https://www.sciencedirect.com/science/article/pii/S000888462100051X

All Gnulot input files (*.gnu) generate a corresponding *.pdf file with the same base name. These PDFs are included, but they're not listed.Usage: $ gnuplot < plot_name_of_gnuplot_file.gnu

The full experimental dataset is reduced to 100 time points using resampling. Initially, geometric progression is applied, but once the time step reaches 30 days, it remains constant.

*** FILES STRUCTURE ***

|--- ambient_conditions| | # history of ambient humidity and temperature| || |--- plot_large_beams_ambient.gnu| | # time "0" corresponds to the onset of drying of the beams, i.e. concrete age 34.063 days| || |--- data| | # time "0" corresponds to concrete set| |--- humidity_function.dat| |--- temperature_function.dat ||--- creep_shrinkage_prisms| | # development of creep and shrinkage of beams 100x100x400 mm exposed to drying at the concrete age of 28 days; concrete specimens are drying from two lateral surfaces only| || |--- axial_shrinkage.gnu| | # total shrinkage| |--- eccentric_creep.gnu| | # total creep in axial direction and bending | || |--- data| |--- Jtot_ecc_axial_toi.csv| |--- Jtot_ecc_bending_toi.csv| |--- shrinkage_toi.csv||--- curvature_beams| # curvature of concrete beams with various sizes and sealing configurations, time "0" = installation time = onset of drying = concrete age of 34.063 days| | | |--- beam_1.gnu| | # 100 Top: breadth B = 0.10 m, height H = 0.10 m, span = 2.50 m, length = 2.70 m, drying from the top surface| |--- beam_2.gnu| | # 100 Sealed: breadth B = 0.10 m, height H = 0.10 m, span = 2.50 m, length = 2.70 m, sealed surface| |--- beam_3.gnu| | # 100 Bottom: breadth B = 0.10 m, height H = 0.10 m, span = 2.50 m, length = 2.70 m, drying from the bottom surface| |--- beam_4.gnu| | # 100 Both: breadth B = 0.10 m, height H = 0.10 m, span = 2.50 m, length = 2.70 m, drying from the top and bottom surfaces| |--- beam_5.gnu| | # 50 Top: breadth B = 0.10 m, height H = 0.05 m, span = 1.75 m, length = 1.95 m, drying from the top surface| |--- beam_6.gnu| | # 200 Top: breadth B = 0.10 m, height H = 0.20 m, span = 3.00 m, length = 3.20 m, drying from the top surface, loading with external weights 2 x 30 kg placed 0.6 m from the support| |--- beam_7.gnu| | # 150 Top: breadth B = 0.10 m, height H = 0.15 m, span = 3.00 m, length = 3.20 m, drying from the top surface| |--- beams_100_ABC.gnu| | # individual responses of the beams with height 100 and different sealing configurations| |--- beams_100_mean.gnu| | # mean responses of the beams with height 100 and different sealing configurations| |--- beams_sizes_ABC.gnu| | # individual responses of the beams with different height and drying from the top surface| |--- beams_sizes_mean.gnu| | # mean responses of the beams with different height and drying from the top surface| || |--- data| |--- automatic| | # measurement with post-mounted linear potentiometer installed at midspan of each specimen| | |--- 1_mean_curvature_toi.csv| | | # columns: time, mean curvature and standard deviation of curvature; the values are calculated from specimens A, B and C| | |--- 1A_curvature_toi.csv| | | # columns: time and curvature| | |--- 1B_curvature_toi.csv| | |--- 1C_curvature_toi.csv| | |--- 2_mean_curvature_toi.csv| | |--- 2A_curvature_toi.csv| | |--- 2B_curvature_toi.csv| | |--- 2C_curvature_toi.csv| | |--- 3_mean_curvature_toi.csv| | |--- 3A_curvature_toi.csv| | |--- 3B_curvature_toi.csv| | |--- 3C_curvature_toi.csv| | |--- 4_mean_curvature_toi.csv| | |--- 4A_curvature_toi.csv| | |--- 4B_curvature_toi.csv| | |--- 4C_curvature_toi.csv| | |--- 5_mean_curvature_toi.csv| | |--- 5A_curvature_toi.csv| | |--- 5B_curvature_toi.csv| | |--- 5C_curvature_toi.csv| | |--- 6_mean_curvature_toi.csv| | |--- 6A_curvature_toi.csv| | |--- 6B_curvature_toi.csv| | |--- 6C_curvature_toi.csv| | |--- 7_mean_curvature_toi.csv| | |--- 7A_curvature_toi.csv| | |--- 7B_curvature_toi.csv| | |--- 7C_curvature_toi.csv| |--- dial_gauge| | # measurement using a set of 5 digital indicators with a fixed position from the left support, only the front specimens (A) is measured using this technique| | # columns: time, curvature and standard devidation of curvature. Weights corresponding to theoretical normalized deflections are applied.| | |--- 1a_weighted_toi.csv| | |--- 2a_weighted_toi.csv| | |--- 3a_weighted_toi.csv| | |--- 4a_weighted_toi.csv| | |--- 5a_weighted_toi.csv| | |--- 6a_weighted_toi.csv| | |--- 7a_weighted_toi.csv| |--- DIC| | # measurement using digital image correlation, locations of the reference plates are above the support and at quarter-spans| |--- 1_stat_toi.csv| | # columns: time, mean curvature and standard deviation of curvature. The values are calculated from specimens A, B and C. The weights are given by the standard deviation of curvature of the individual specimens| |--- 1a_stat_toi.csv| | # columns: time, mean curvature and standard deviation of curvature.| |--- 1b_stat_toi.csv| |--- 1c_stat_toi.csv| |--- 2_stat_toi.csv| |--- 2a_stat_toi.csv| |--- 2b_stat_toi.csv| |--- 2c_stat_toi.csv| |--- 3_stat_toi.csv| |--- 3a_stat_toi.csv| |--- 3b_stat_toi.csv| |--- 3c_stat_toi.csv| |--- 4_stat_toi.csv| |--- 4a_stat_toi.csv| |--- 4b_stat_toi.csv| |--- 4c_stat_toi.csv| |--- 5_stat_toi.csv| |--- 5a_stat_toi.csv| |--- 5b_stat_toi.csv| |--- 5c_stat_toi.csv| |--- 6_stat_toi.csv| |--- 6a_stat_toi.csv| |--- 6b_stat_toi.csv| |--- 6c_stat_toi.csv| |--- 7_stat_toi.csv| |--- 7a_stat_toi.csv| |--- 7b_stat_toi.csv| |--- 7c_stat_toi.csv||--- drying_cylinders| # data of moisture loss measured on cylinders drying from the top and bottom surface and with a sealed circumference, onset of drying at concrete age 28 days| || |--- drying_cylinders_average.gnu| || |--- data| | # columns: duration of drying, average moisture loss [kg/m^3], standard deviation of moisture loss| |--- dwdV_25_toi.csv| |--- dwdV_50_toi.csv| |--- dwdV_100_toi.csv| |--- dwdV_150_toi.csv| |--- dwdV_200_toi.csv||---isotherm| # data for sorption isotherm expressed as a dependence of moisture content [kg/m^3] on relative humidity [-]| || |--- isotherm.gnu| | experimental data and a least-squares fit with a VanGenuchten expression| || |--- data| | # columns: relative humidity, average moisture content and standard deviation of moisture content| |--- isotherm_beam.dat| | # data measured on specimens cut from a spare concrete beam| |--- isotherm_cube.dat| | # data measured on specimens cut from a standard concrete cube

Data and gnuplot file to generate graph of submissions by category within computer science, by year. The data are whitespace separateed and for each category there is the count of submissions and then the fraction of all cs submissions that this represents for the year.

This is the data and code corresponding to Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation, Nature Comms. 13:3348.

Code

The file Surface_Evolver_script.txt is ... the Surface Evolver script, use with Ken Brakke's Surface Evolver

Data sources

The figure panels are based on the datafiles listed below, visualised either with Ken Brakke's Surface Evolver or with gnuplot 5. When the datafiles listed do not contain the primary data, they contain a commented last line which is the command line for the software datamerge to generate it from other datafiles found in the Data_sources subdirectory.

Figure 1

Fig. 1f : visualisation from Surface Evolver file Young100dixPoisson000Step013.dmp

Fig. 1g : myosin_profile_us_only.pdf generated with gnuplot script myosin_profile.plot

Figure 2

Fig. 2a : strain_profile_100_0_time_013.pdf generated with gnuplot script strain_profile.plot

Fig. 2b : visualisation from Surface Evolver file Young100dixPoisson000Step013.dmp

Fig. 2c : stress_profile_100_0_time_013.pdf gnuplot script stress_profile.plot

Fig. 2d : visualisation from Surface Evolver file Young100dixPoisson000Step063.dmp

Figure 3

Fig. 3a : myosin_area.pdf generated with gnuplot script area_AP_DV_paper.plot

Fig. 3b : area_stripes_t=-1.pdf generated with gnuplot script area_AP_DV_paper.plot

Fig. 3c : only_AP_stripes_t=-1.pdf generated with gnuplot script area_AP_DV_paper.plot

Fig. 3d : only_DV_stripes_t=-1.pdf generated with gnuplot script area_AP_DV_paper.plot

Fig. 3e : visualisation from Surface Evolver file Young100dixPoisson000Step013.dmp Young100dixPoisson000Step063.dmp Young100dixPoisson000Step163.dmp Young100dixPoisson000Step213.dmp

Figure 4

Fig. 4a : visualisation from Surface Evolver file Young100dixPoisson000Step213.dmp

Fig. 4b : furrow_propagation.pdf generated with gnuplot script furrow_propagation.plot

Fig. 4c : rate_of_furrowing_t=3.pdf generated with gnuplot script furrow_propagation.plot

Fig. 4f : curvature.pdf generated with gnuplot script curvature.plot

Figure 5

Fig. 5a : visualisation from Surface Evolver file Young100dixPoisson000Step013.dmp Young100dixPoisson000Step063.dmp Young100dixPoisson000Step113.dmp Young100dixPoisson000Step163.dmp Young100dixPoisson000Step213.dmp

Fig. 5b : visualisation from Surface Evolver file Young100dixPoisson000Step013.dmp Young100dixPoisson000Step140.dmp

Fig. 5d : stress_laserablations_profile_100_0_time_063.pdf generated with gnuplot script stress_profile_for_laser_ablations.plot

Fig. 5e : laser_ablation_recoil.pdf generated with gnuplot script laser_ablation_recoil.plot

Supp Figure 1

Fig. S1a : time_profile_FINI_100_0.pdf generated with gnuplot script time_profile_stress.plot

Fig. S1b : visualisation from Surface Evolver file Young100dixPoisson000Step013.dmp

Fig. S1d : visualisation from Surface Evolver file Young100dixPoisson000Step063.dmp

Fig. S1e : strain_profile_100_0_time_063.pdf gnuplot script strain_profile.plot

Fig. S1f : stress_profile_100_0_time_063.pdf gnuplot script stress_profile.plot

Supp Figure 1

Fig. S2a : area_stripes_time_evolution.pdf generated with gnuplot script area_AP_DV_paper.plot

Fig. S2b : area_stripes_time_evolution_SPIM.pdf generated with gnuplot script area_AP_DV_paper.plot

Supp Figure 3

Fig. S3a : visualisation from Surface Evolver file Young100dixPoisson000Step213.dmp

Fig. S3c : AP_binned_strain.pdf generated with gnuplot script AP_binned_strain.plot

Fig. S3d : furrow_propagation_experimental.pdf generated with gnuplot script plot_furrow.plot

Fig. S3e : curvature_DV_indiv.pdf generated with gnuplot script curvature.plot

Fig. S3f : depth_Gastrulation_ordi_Wild_Type_STITCHED_100_0.pdf generated with gnuplot script depth.plot

This dataset contains the numerical data accompanying the "Fragility of the magnetic order in the prototypical altermagnet RuO2" paper.
Computations were performed using VASP 6.3.2 and WIEN2k 21.1 packages.

It contains the data and gnuplot scripts used to plot Figures 2-6, i.e the dependence of the total energy and local magnetization at the Ru site as a function of the effective Hubbard U parameter for RuO2, the magnetic anisotropy as a function of angle, projected non-magnetic density of states onto Ru d-orbitals, spin-polarized total density of states for majority spin as a function of the effective U parameter and the dependence of local atomic magnetization on hole doping and the effective U parameter.

To produce the figure one simply runs gnuplot script.gnu command with script.gnu a placeholder for a relevant script name.
In the case of VASP computations, the total energy is reported in OUTCAR file at the line containing the free energy TOTEN = token, the local magnetization in the block after the magnetization token, the effective U parameter is Ueff = U - J, where U and J are defined by LDAUU and LDAUJ tokens in the INCAR file and the hole doping is defined by altering the number of electrons in the system using NELECT token in the INCAR file.

The density of states is calculated using WIEN2k and is stored in case.dos?ev* files with case being a filename, ? be replaced with a number and * be either empty, up or dn.

The following POTCARs were used for VASP calculations:
md5sum name and location
91f4c7aab413b97880dee28c8d363ff5 potpaw_PBE.52/Ru_sv/POTCAR
38ce74bba1194bccd788f22d688bfc65 potpaw_PBE.52/O/POTCAR

• "sl1.dat" : text file with data slip length vs number of gas atoms for k_gas = 1.0

• "sl5.dat" : text file with data slip length vs number of gas atoms for k_gas = 0.5

• "sl25.dat" : text file with data slip length vs number of gas atoms for k_gas = 0.25

• "sl125.dat" : text file with data slip length vs number of gas atoms for k_gas = 0.125

• "plotsl.plt": gnuplot script to plot slip lengths data and obtain figure 5a of the article

• "dg.dat": data for solubilities in kbT units from figure 3 of the article

• "3600gask0125.xyz": trajectory file in xyz format for the system with k_gas= 0.125 and 3600 gas atoms

• "3600.data": starting configuration for k_gas = 0.125 and 3600 gas atoms in restart.data format for lammps

• "in.shear": lammps input script to run the shear simulation for the system with k_gas = 0.125 and 3600 gas atoms starting from configuration store in "3600.data" file

Publication

arXiv preprint: https://arxiv.org/abs/2002.03032

journal version: [add link to journal]

Code

https://github.com/ComplexityBiosystems/metamech

https://github.com/complexitybiosystems/metamech_datasets

Datasets

Figure 2:

• antiparallel_{human,machine}_design.stl: STL files for human design and machine design configurations performing antiparallel movement.

Figure 3:

• crane_scaling_dataframe.csv: raw efficiency values and execution times used to generate Figure 3

Figure 4:

• eta_random.dat, eta_triang.dat, plot_distrib.gnupot: raw values of efficiency and gnuplot script used to generate Figure 4 panel d
• eta_vs_displ_random.dat, eta_vs_displ_triang.dat, eta_vs_displ.gnuplot: raw values of efficiency and gnuplot script used to generate Figure 4 panel c
• structures.tar.bz2: all the structures relative to Figure 4 panel d, in a format suitable for visualization with ovito software

Figure 5: data files for human and machine generated pairs of pliers in a format suitable for visualization with ovito software. "*.agr" and "*.data" files can be opened with any text editor to directly visualize the raw data.

• *_rest.data: rest configurations which are represented in grey in Fig. 5a and Fig. 5b.
• *_F0.01.data: displaced configurations with input force Fext = 0.01 and output spring stiffness kext = 0.01, also reported in Fig. 5a and Fig. 5b.
• *.agr: dataset for Figure 5c and 5d in xmgrace format.

Figure 6:

• Fig6/Fig6b/*.csv: raw values of efficiency used to generate Figure 6 panel b
• Fig6/Fig6c-training-data/*/*.png: a total of 1.163.733 PNG images, of size 192 x 168 pixels, as described in the methods section of the manuscript, organized in directories corresponding to different runs.
• Fig6/Fig6c-training-data/metadata.csv: maps each image path to its associated efficiency value
• Fig6/Fig6c-efficiency-data/eta_{CNN,DEM}.txt: raw values of efficiency used to generate Figure 6 panel c.

Figure 7:

• Fig7/transfer_learning_regression_values.csv: full raw data, including regression coefficients, p-values, slopes and intercepts corresponding to Figure 7 panels i and j

Figure S3:

• orthogonal_{human,machine}_design.stl: STL files for human design and machine design configurations performing orthogonal movement.

In this repository, we provide the data featured in our manuscript, which demonstrates the fluid dynamics mechanisms responsible for the formation of Earth’s basal magma ocean. The repository contains the input files and raw output files from the fluid dynamics simulations discussed in the manuscript. It also contains all GNUPlot script that can be used to generate figures from the raw files. In addition to the README file, the gnuplot script are a good place to understand how data are organized in the raw file.

This zip file contains the gnuplot and data files needed to generate the figures showing the experimental results presented in [1].

[1] S. Herrería-Alonso, M. Rodríguez-Pérez, R. F. Rodríguez-Rubio and F. Pérez-Fontán, "Improving Uplink Scalability of LoRa-Based Direct-to-Satellite IoT Networks," in IEEE Internet of Things Journal, vol. 11, no. 7, pp. 12526-12535, April 2024, doi: 10.1109/JIOT.2023.3333934.

Simulation data generated with the Dune model dune-ax1. Currently, there is data on which my 2013 Biophysical Journal paper is based on. Structure: The simulation data contains a main folder with mostly gnuplot data files and some debug/diagnostics information. The subfolder 'hdf5' contains values of alle the unknowns as well as domain information for each time step. Contact: If you have questions or if you are interested in data from different simulation setups, please contact me on Github: https://github.com/pederpansen/dune-ax1.

Dataset and scripts for reproducing the figures included in the paper "Short-range exposure to airborne virus transmission and current guidelines".DOI: https://doi.org/10.1101/2021.04.06.21255017 (medrxiv)DOI: https://doi.org/10.1073/pnas.2105279118 (PNAS)Instructions for reproducing the figures:-Figure 1 (manuscript): Run the gnuplot script "figure1.plt"-Figure 3 (manuscript): Run the python script "figure3.py"-Figure 4 (manuscript): Run the python script "figure4.py"-Figure S2 (supplementary): Run the gnuplot script "figureS2.plt"Each zip file contains all the raw data required to reproduce the respective image. The resulting plots are also provided in .png or .pdf formats.

This folder contains data necessary to reproduce figures contained in the manuscript, titled "Reconfigurable ferrimagnetic Tb/Co based substrates for magnetophoresis" by M. Urbaniak, D. Kiphart, M. Matczak, and P. Kuświk

Each folder corresponds to one figure containing data (we provide no additional content for schematic images).

The folders contain gnuplot source files, possibly edited to adjust paths and/or remove non-public content, and all the necessary files needed to produce an image (eps format) from the .gnu file, and possibly corresponding original images from the Kerr microscopy investigations.

To obtain eps file from gnu file open gnuplot in command line and execute: load "*.gnu"

Note that the field values on the images are irrelevant, and that in some of them the scale bar is not set properly.

The folders named FigX, where X is a single digit, contain the files of the images from the main text of the manuscript.

The folders named SFigX correspond to the images shown in a supplementary material.

On a reasonable request we can provide original recordings of the movies collected during magnetophoretic experiments (avi format, with about 18 MB/s data rate) that correspond to supplementary movies of the manuscript.