cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7445990
title: Mechanical behavior of C45 steel at high temperatures and high strain rates—experimental data set and numerical approach

description: In this publication we provide experimental data of dynamic compression tests of four microstructural variants of the C45 steel alloy performed at high temperatures and high strain rates. The presented data evidences the presence of Dynamic Strain Aging (DSA) in the material. Moreover, we provided the MATLAB codes of a calibration approach to estimate the material parameters of a plasticity model that accounts for DSA. The file "Mechanical behavior of C45" contains: 1) Folder EXP_DATA contains experimental data of dynamic compression tests of the C45 steel variants in .mat format. The data is organized in cell arrays, and every cell in the arrays contains the data of one experiment. The data of each experiment is arranged as four columns arrays, as: column 1: Plastic strain, column 2: Flow stress, column 3: absolute temperature, column 4: strain rate 2) Matlab code named CALIBRATION.m which executes a calibration approach of a modified Johnson-Cook that accounts for DSA. The form of the model is the following: \(\sigma(\varepsilon ,T,\dot{\varepsilon}) = (A+B\varepsilon^n)\left(1+Cln\left(\frac{\dot{\varepsilon}}{\dot{\varepsilon}^{ref}}\right)\right)\left( 1-\left(\frac{T-T^{ref}}{T^{melt}-T^{ref}}\right)^m\right) +\sigma^{dsa}(\varepsilon ,T,\dot{\varepsilon}) \) with, \(σ^{dsa} (ε,T,\dotε )=\frac{B_1}{ν} \left(\frac{ε^β}{ ε ̇T} exp⁡(-\frac{Q_m}{KT}) \right)^{\frac{2}{3}}\), \(\frac{B_1}{\nu} = \frac{\psi \dot{\varepsilon}}{exp(\eta \frac{T}{\dot{\varepsilon}^\alpha})} \) The code CALIBRATION contains a data presentation section that can be used to generate plots to compare calibrated models with the experimental data. Further instructions are commented in the code CALIBRATION.m.
DOI: 10.5281/zenodo.7445989
title: Mechanical behavior of C45 steel at high temperatures and high strain rates—experimental data set and numerical approach

description: In this publication we provide experimental data of dynamic compression tests of four microstructural variants of the C45 steel alloy performed at high temperatures and high strain rates. The presented data evidences the presence of Dynamic Strain Aging (DSA) in the material. Moreover, we provided the MATLAB codes of a calibration approach to estimate the material parameters of a plasticity model that accounts for DSA. The file "Mechanical behavior of C45" contains: 1) Folder EXP_DATA contains experimental data of dynamic compression tests of the C45 steel variants in .mat format. The data is organized in cell arrays, and every cell in the arrays contains the data of one experiment. The data of each experiment is arranged as four columns arrays, as: column 1: Plastic strain, column 2: Flow stress, column 3: absolute temperature, column 4: strain rate 2) Matlab code named CALIBRATION.m which executes a calibration approach of a modified Johnson-Cook that accounts for DSA. The form of the model is the following: \(\sigma(\varepsilon ,T,\dot{\varepsilon}) = (A+B\varepsilon^n)\left(1+Cln\left(\frac{\dot{\varepsilon}}{\dot{\varepsilon}^{ref}}\right)\right)\left( 1-\left(\frac{T-T^{ref}}{T^{melt}-T^{ref}}\right)^m\right) +\sigma^{dsa}(\varepsilon ,T,\dot{\varepsilon}) \) with, \(σ^{dsa} (ε,T,\dotε )=\frac{B_1}{ν} \left(\frac{ε^β}{ ε ̇T} exp⁡(-\frac{Q_m}{KT}) \right)^{\frac{2}{3}}\), \(\frac{B_1}{\nu} = \frac{\psi \dot{\varepsilon}}{exp(\eta \frac{T}{\dot{\varepsilon}^\alpha})} \) The code CALIBRATION contains a data presentation section that can be used to generate plots to compare calibrated models with the experimental data. Further instructions are commented in the code CALIBRATION.m.
DOI: 10.34740/kaggle/dsv/4833843
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5517/ccdc.csd.cc2cwpml
title: CCDC 2201360: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Belaj, Carina Vidovic, Nadia C. Mösch-Zanetti|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cwppn
title: CCDC 2201362: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Belaj, Natascha Stock, Nadia C. Mösch-Zanetti|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d0rsz
title: CCDC 2205271: Experimental Crystal Structure Determination

description: Related Article: Akira Okumura, Thomas P. Spaniol, Jun Okuda|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d12dy
title: CCDC 2205569: Experimental Crystal Structure Determination

description: Related Article: Shagufi Naz Ansari, Anju Ajayan Kongasseri|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d13bx
title: CCDC 2205598: Experimental Crystal Structure Determination

description: Related Article: T.A.Antonenko, V.A.Tafeenko, M.A.Vorobyev, D.B.Shpakovsky, E.R.Milaeva|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d0wv5
title: CCDC 2205397: Experimental Crystal Structure Determination

description: Related Article: Rui SHANG|2022|CSD Communication|||
description: Related Article: Takahiro Doba, Rui Shang, Eiichi Nakamura|2022|J.Am.Chem.Soc.|144|21692|doi:10.1021/jacs.2c09470
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cb0f5
title: CCDC 2184366: Experimental Crystal Structure Determination

description: Related Article: Changkun Li |2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzst0
title: CCDC 2234133: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, R.W. Harrington|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzsw2
title: CCDC 2234135: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, R.W. Harrington|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzsx3
title: CCDC 2234136: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, R.W. Harrington|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dzsy4
title: CCDC 2234137: Experimental Crystal Structure Determination

description: Related Article: W. Clegg, R.W. Harrington|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21857484
title: AGILE 2023: Data and Software Availability

description: There are two datasets as follows, 1) This original dataset of ICT patent applications includes the date of application and addresses of applicants during 2007-2021. <br> 2) District administrative Boundaries at Three Levels in China
DOI: 10.6084/m9.figshare.21834801
title: Mesocarnivore occurrence modeling

description: Data associated with the paper "Monitoring mesocarnivores with tracks and technology using multi-method modeling" by Moll et al. <br> Files include detection histories for cameras ("cam") and scent stations ("track") as well as associated covariates. <br> Model code is provided in the supplemental file associated with the manuscript.
DOI: 10.6084/m9.figshare.21834801.v1
title: Mesocarnivore occurrence modeling

description: Data associated with the paper "Monitoring mesocarnivores with tracks and technology using multi-method modeling" by Moll et al. <br> Files include detection histories for cameras ("cam") and scent stations ("track") as well as associated covariates. <br> Model code is provided in the supplemental file associated with the manuscript.
DOI: 10.34740/kaggle/dsv/4833865
title: PyAFBF textures - set 002
DOI: 10.5258/soton/d2455
title: Dataset for "Mechanisms of mass transfer to small spheres sinking in turbulence"

description: Dataset for: Lawson, J., & Ganapathisubramani, B. (2023). Mechanisms of mass transfer to small spheres sinking in turbulence. Journal of Fluid Mechanics, 954, A15. doi:10.1017/jfm.2022.998 The accompanying MATLAB HDF5 files, MATLAB scripts and Excel spreadsheets contain all necessary data and code to reproduce figures 5-16 from the paper. Nomenclature used is (mostly) consistent with the paper.
DOI: 10.5281/zenodo.7515511
title: WaterKit: thermodynamic profiling of protein hydration sites (1/3)

description: <strong>Overview</strong> This archive (1/3) contains the results (fabp4, fkb1a, hivpr, hs90a, ital) for the following study: WaterKit: thermodynamic profiling of protein hydration sites (https://doi.org/10.26434/chemrxiv-2022-grlsr) Each zip archive contains the following files: charmm-gui: output from CHARMM-gui xx_amber: GIST output from MD simulations figures: convergence, predictions per waterkit model plots, etc... pdbbind_ligands: contains all the ligands used to define the ligand binding site waterkit: contains all the results from the WaterKit calculations All the WaterKit parameters tested: ad : acceptor/donor anchor points all : used all hydrogen atoms as anchor points vina : used O_DA vina probe for the spherical model (otherwise TIP3P model) 300 : temperature 3 : number of hydration layers placed during the calculations min_100_2.5 : 100 steps of minimization with 2.5 kcal/mol/A**2 constraints Each directory contains: output from the GIST analysis (gist-*.dx) cluster.pdb: All the hydration sites identified protein.nc : WaterKit "trajectory" protein_system.prmtop : Amber top file pymol_*.pse : PyMol session with all the results (WK, MD) results_*.png : Comparison plots between WaterKit predictions and MD simulations per hydration sites analysis_xxx.ipynb: Jupyter notebook containing all the analysis (needs utils.py file) protein_prepared.pdbqt: structure used for the WK calculations results_md.csv : contains all the raw results from the MD simulations results_wk.csv : contains all the raw results from the WK calculations results_md_md_comp_energy_*.csv : comparison results between MD simulations (energy) results_md_md_comp_placement_*.csv : comparison results between MD simulations (placement) results_md_wk_comp_energy_*.csv : comparison results between MD simulations and WK (energy) results_md_wk_comp_placement_*.csv : comparison results between MD simulations and WK (placement) results_wk_wk_comp_energy_*.csv : comparison results between WK calculations (energy) results_wk_wk_comp_placement_*.csv : comparison results between WK calculations (placement)
DOI: 10.5281/zenodo.7515510
title: WaterKit: thermodynamic profiling of protein hydration sites (1/3)

description: <strong>Overview</strong> This archive (1/3) contains the results (fabp4, fkb1a, hivpr, hs90a, ital) for the following study: WaterKit: thermodynamic profiling of protein hydration sites (https://doi.org/10.26434/chemrxiv-2022-grlsr) Each zip archive contains the following files: charmm-gui: output from CHARMM-gui xx_amber: GIST output from MD simulations figures: convergence, predictions per waterkit model plots, etc... pdbbind_ligands: contains all the ligands used to define the ligand binding site waterkit: contains all the results from the WaterKit calculations All the WaterKit parameters tested: ad : acceptor/donor anchor points all : used all hydrogen atoms as anchor points vina : used O_DA vina probe for the spherical model (otherwise TIP3P model) 300 : temperature 3 : number of hydration layers placed during the calculations min_100_2.5 : 100 steps of minimization with 2.5 kcal/mol/A**2 constraints Each directory contains: output from the GIST analysis (gist-*.dx) cluster.pdb: All the hydration sites identified protein.nc : WaterKit "trajectory" protein_system.prmtop : Amber top file pymol_*.pse : PyMol session with all the results (WK, MD) results_*.png : Comparison plots between WaterKit predictions and MD simulations per hydration sites analysis_xxx.ipynb: Jupyter notebook containing all the analysis (needs utils.py file) protein_prepared.pdbqt: structure used for the WK calculations results_md.csv : contains all the raw results from the MD simulations results_wk.csv : contains all the raw results from the WK calculations results_md_md_comp_energy_*.csv : comparison results between MD simulations (energy) results_md_md_comp_placement_*.csv : comparison results between MD simulations (placement) results_md_wk_comp_energy_*.csv : comparison results between MD simulations and WK (energy) results_md_wk_comp_placement_*.csv : comparison results between MD simulations and WK (placement) results_wk_wk_comp_energy_*.csv : comparison results between WK calculations (energy) results_wk_wk_comp_placement_*.csv : comparison results between WK calculations (placement)
DOI: 10.5281/zenodo.7520008
title: WaterKit: thermodynamic profiling of protein hydration sites (2/3)

description: <strong>Overview</strong> This archive (2/3) contains the results (fa10 and pgh2) for the following study: WaterKit: thermodynamic profiling of protein hydration sites (https://doi.org/10.26434/chemrxiv-2022-grlsr) Each zip archive contains the following files: charmm-gui: output from CHARMM-gui xx_amber: GIST output from MD simulations figures: convergence, predictions per waterkit model plots, etc... pdbbind_ligands: contains all the ligands used to define the ligand binding site waterkit: contains all the results from the WaterKit calculations All the WaterKit parameters tested: ad : acceptor/donor anchor points all : used all hydrogen atoms as anchor points vina : used O_DA vina probe for the spherical model (otherwise TIP3P model) 300 : temperature 3 : number of hydration layers placed during the calculations min_100_2.5 : 100 steps of minimization with 2.5 kcal/mol/A**2 constraints Each directory contains: output from the GIST analysis (gist-*.dx) cluster.pdb: All the hydration sites identified protein.nc : WaterKit "trajectory" protein_system.prmtop : Amber top file pymol_*.pse : PyMol session with all the results (WK, MD) results_*.png : Comparison plots between WaterKit predictions and MD simulations per hydration sites analysis_xxx.ipynb: Jupyter notebook containing all the analysis (needs utils.py file) protein_prepared.pdbqt: structure used for the WK calculations results_md.csv : contains all the raw results from the MD simulations results_wk.csv : contains all the raw results from the WK calculations results_md_md_comp_energy_*.csv : comparison results between MD simulations (energy) results_md_md_comp_placement_*.csv : comparison results between MD simulations (placement) results_md_wk_comp_energy_*.csv : comparison results between MD simulations and WK (energy) results_md_wk_comp_placement_*.csv : comparison results between MD simulations and WK (placement) results_wk_wk_comp_energy_*.csv : comparison results between WK calculations (energy) results_wk_wk_comp_placement_*.csv : comparison results between WK calculations (placement)
DOI: 10.5281/zenodo.7520007
title: WaterKit: thermodynamic profiling of protein hydration sites (2/3)

description: <strong>Overview</strong> This archive (2/3) contains the results (fa10 and pgh2) for the following study: WaterKit: thermodynamic profiling of protein hydration sites (https://doi.org/10.26434/chemrxiv-2022-grlsr) Each zip archive contains the following files: charmm-gui: output from CHARMM-gui xx_amber: GIST output from MD simulations figures: convergence, predictions per waterkit model plots, etc... pdbbind_ligands: contains all the ligands used to define the ligand binding site waterkit: contains all the results from the WaterKit calculations All the WaterKit parameters tested: ad : acceptor/donor anchor points all : used all hydrogen atoms as anchor points vina : used O_DA vina probe for the spherical model (otherwise TIP3P model) 300 : temperature 3 : number of hydration layers placed during the calculations min_100_2.5 : 100 steps of minimization with 2.5 kcal/mol/A**2 constraints Each directory contains: output from the GIST analysis (gist-*.dx) cluster.pdb: All the hydration sites identified protein.nc : WaterKit "trajectory" protein_system.prmtop : Amber top file pymol_*.pse : PyMol session with all the results (WK, MD) results_*.png : Comparison plots between WaterKit predictions and MD simulations per hydration sites analysis_xxx.ipynb: Jupyter notebook containing all the analysis (needs utils.py file) protein_prepared.pdbqt: structure used for the WK calculations results_md.csv : contains all the raw results from the MD simulations results_wk.csv : contains all the raw results from the WK calculations results_md_md_comp_energy_*.csv : comparison results between MD simulations (energy) results_md_md_comp_placement_*.csv : comparison results between MD simulations (placement) results_md_wk_comp_energy_*.csv : comparison results between MD simulations and WK (energy) results_md_wk_comp_placement_*.csv : comparison results between MD simulations and WK (placement) results_wk_wk_comp_energy_*.csv : comparison results between WK calculations (energy) results_wk_wk_comp_placement_*.csv : comparison results between WK calculations (placement)
DOI: 10.5281/zenodo.7520012
title: WaterKit: thermodynamic profiling of protein hydration sites (3/3)

description: <strong>Overview</strong> This archive (3/3) contains the results (kith, nram and streptavidin) for the following study: WaterKit: thermodynamic profiling of protein hydration sites (https://doi.org/10.26434/chemrxiv-2022-grlsr) Each zip archive contains the following files: charmm-gui: output from CHARMM-gui xx_amber: GIST output from MD simulations figures: convergence, predictions per waterkit model plots, etc... pdbbind_ligands: contains all the ligands used to define the ligand binding site waterkit: contains all the results from the WaterKit calculations All the WaterKit parameters tested: ad : acceptor/donor anchor points all : used all hydrogen atoms as anchor points vina : used O_DA vina probe for the spherical model (otherwise TIP3P model) 300 : temperature 3 : number of hydration layers placed during the calculations min_100_2.5 : 100 steps of minimization with 2.5 kcal/mol/A**2 constraints Each directory contains: output from the GIST analysis (gist-*.dx) cluster.pdb: All the hydration sites identified protein.nc : WaterKit "trajectory" protein_system.prmtop : Amber top file pymol_*.pse : PyMol session with all the results (WK, MD) results_*.png : Comparison plots between WaterKit predictions and MD simulations per hydration sites analysis_xxx.ipynb: Jupyter notebook containing all the analysis (needs utils.py file) protein_prepared.pdbqt: structure used for the WK calculations results_md.csv : contains all the raw results from the MD simulations results_wk.csv : contains all the raw results from the WK calculations results_md_md_comp_energy_*.csv : comparison results between MD simulations (energy) results_md_md_comp_placement_*.csv : comparison results between MD simulations (placement) results_md_wk_comp_energy_*.csv : comparison results between MD simulations and WK (energy) results_md_wk_comp_placement_*.csv : comparison results between MD simulations and WK (placement) results_wk_wk_comp_energy_*.csv : comparison results between WK calculations (energy) results_wk_wk_comp_placement_*.csv : comparison results between WK calculations (placement)