Find research datasets worth reusing

Spectroscopic data for the compounds and reactions published in "Vinyl-pyrazole as a biomimetic acetaldehyde surrogate"

<p>Here, the uploaded data are associated with the manuscript "Vinyl-pyrazole as a biomimetic acetaldehyde surrogate" published in Chem. Comm. under the following DOI: https://doi.org/10.1039/D4CC01305K</p> <p>The .dpt files represent IR spectra of the compounds published in the manuscript.</p> <p>The .scv files represent NMR spectra of the compounds published in the manuscript.</p> <p>HPLC-MS data is presented as .pdf files.</p> <p>The labeling of the compounds and reactions follows the one in the published manuscript.</p>

Dataset of Reaction Times for the Study of Differential Functional Changes in Visual Performance During Acute Exposure to Microgravity Analogue and their Potential Links with Spaceflight-Associated Neuro-Ocular Syndrome

<p><strong>Title</strong>: "Dataset of Reaction Times for the Study of Differential Functional Changes in Visual Performance During Acute Exposure to Microgravity Analogue and their Potential Links with Spaceflight-Associated Neuro-Ocular Syndrome"<br>Zenodo DOI: 10.5281/zenodo.11840654</p> <p><strong>Contains</strong>: simple-reaction-times-VBRHDT-data.csv<br>Dateset of SRT (simple reaction time) values to visual stimuli in different positions in visual field, binocularly observed, in a microgravity analogue study, in four body positions (vertical, horizontal, -6 deg tild, -15 deg tilt). <br>Total records contained: 3584.</p> <p><strong>Institutional Review Board Statement</strong>: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee “Carol Davila” University of Medicine and Pharmacy Bucharest, Romania, 14877/26.05.2023. Data was collected in SpaceMed Laboratory , CIeH (Center for Innovation and eHealth) of UMF Carol Davila Bucharest, Romania.</p> <p><strong>Citation and</strong> <strong>Detailed description:</strong>  see "<em>Differential functional changes in visual performance during acute exposure to microgravity analogue and their potential links with Spaceflight-Associated Neuro-Ocular Syndrome</em>", 2024, by Iftime A, Tofolean IT, Pintilie V, Călinescu O, Busnatu S, Papacocea IR, Diagnostics ,2024; 14(17):1918. doi: 10.3390/diagnostics14171918  <br>https://pubmed.ncbi.nlm.nih.gov/39272703/</p> <p><strong>Structure</strong>: Dataset is in CSV (Comma-Separated Values) format, UTF-8 encoded, text field delimited with quotation marks, in tidy format; one row is one record from the SRT task, variables values are in columns). The first row is the variable name. The variable are:</p> <p>1) "live_row"<br>- type:  integer numbers, sequential;<br>- values: the index (order) of each SRT measurement performed in a body position, by a participant (ID). The value is C-based (first measurement is "0", second measurement is "1", etc).</p> <p>2) "response_time"<br>- type: real numbers, continuous values;<br>- values: response time recorded from the participant; values in miliseconds.</p> <p>3) "target_position_x_deg"<br>- type: real numbers, categorical (4 values: +/- 18.478, +/- 0.75);<br>- values: horizontal visual angle, in visual degrees in the visual field, of the position of the stimulus. Screen coordinates are computed from "0" position, foveal fixation, positive values to the right, negative values to the left.</p> <p>4) "target_position_y_deg"<br>- type: real numbers, categorical (2 values:  -0.75, -7.654);<br>- values: vertical visual angle, in visual degrees in the visual field, of the position of the stimulus. Screen coordinates are computed from "0" position, foveal fixation, positive values downward, negative values upward.<br>-Note: For the equivalent polar coordinates (as in planimetry testing) see Figure 2 of the mentioned paper. </p> <p>5) "Contrast_Weber_calibrated"<br>- type: real numbers, categorical (2 values:  50.58, 99.3);<br>- values: Measured Weber contrast of the visual stimulus shown, values in percents.</p> <p>6) "hand"<br>- type: categorical, 1 value ("right");<br>- values: hand used by the participant during SRT task.</p> <p>7) "body_position"<br>- type: categorical (4 values: "vertical (90 deg)", "horizontal (0 deg)", "inclined (-6 deg)", "inclined (-15 deg)" );<br>- values: Body position during the SRT task.</p> <p>8) "ID(anon)"<br>- type: integer number, categorical, 8 values;<br>- values: anonymized ID of the participants in the study (8 persons).</p>

Spectroscopic data for the compounds and reactions published in "Nucleophiles Target the Tungsten Center Over Acetylene in Biomimetic Models"

<p>Here, the uploaded data are associated with the manuscript "Nucleophiles Target the Tungsten Center Over Acetylene in Biomimetic Models" published in Inorg. Chem. under the following https://doi.org/10.1021/acs.inorgchem.4c00286<br>The .dpt files represent IR spectra of the compounds published in the manuscript. Gas IR spectrum is reported as .scv file. The .scv files represent NMR spectra of the compounds and reactions published in the manuscript. Line Shape Analysis calculation is presented in the excel file.<br>The labeling of the compounds and reactions follows the one in the published manuscript.</p>

Research data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach"

<div><strong>Research Data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em></strong></div> <div> </div> <div>Dear reader,</div> <div> </div> <div>reasearch data are provided for the research article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em> (https://doi.org/10.1016/j.advwatres.2024.104763). The authors hope that the research data allows for a better understanding of the modeling workflow. The research data covers the following files:</div> <div> <ul> <li>Python scripts to create the models <ul> <li>Model scripts using FloPy (Bakker et al., 2016) are stored as .py files in './model_data/flopy_scripts/', named 'model_variant_vXYZ.py', where 'XYZ' is a wildcard for the model number. </li> <li>--> Note that model numbers correspond to the different model variants as referred to in the article, see overview below.</li> <li>The model scripts require postfix files, stored in './model_data/flopy_scripts/postfix/', a PHREEQC database file, stored in './model_data/flopy_scripts/template_database/', as well as spreadsheets that contain the initial concentrations as well as reaction rate parameters needed by PHT3D, stored as .xlsx files in './model_data/flopy_scripts/', to create the models.</li> <li>Note that the .xlsx files are used by PHT3D-FSP in the model scripts to generate relevant PHT3D input files (compare https://doi.org/10.5281/zenodo.7559750 for more details).</li> </ul> </li> <li>SEAWAT/PHT3D input files <ul> <li>Original SEAWAT and PHT3D input files, which were created with the corresponding model scripts previously (see step before).</li> <li>Input files are stored in './model_data/model_files/vXYZ/model_files/' for each model variant, where 'XYZ' is a wildcard for the model number.</li> <li>SEAWAT/PHT3D executables can directly run the model files files. Thus, the files don't need to be re-created via the previous step.</li> </ul> </li> <li>Model outputs <ul> <li>Model output data is stored as NumPy arrays in './model_data/model_files/vXYZ/npy_arrays/', where 'XYZ' is a wildcard for the model number.</li> <li>The script './model_data/flopy_scripts/template_output/pht3d_output_hpc_v006.py' was used to generate the output files.</li> <li>2-D species concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/species/', where 'XYZ' is a wildcard for the model number.</li> <li>Species min./max. concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/min_max/', where 'XYZ' is a wildcard for the model number.</li> <li>2-D water budget arrays (CH & WEL boundaries) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/budgets/', where 'XYZ' is a wildcard for the model number.</li> <li>Model discretization information (ncol, nrow, nlay etc.) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/discretization/', where 'XYZ' is a wildcard for the model number.</li> </ul> </li> <li>Figure files <ul> <li>Original figure files as well as the corresponding Python scripts to create the figures are stored in the subfolder'./figures'.</li> </ul> </li> </ul> <p>Numbering of the model variants is as follows:<br><br>v401 --> VAR-conservative<br>v402 --> VAR-OM<br>v403 --> VAR-C/I<br>v404 --> VAR-C/I/S<br>v405 --> VAR-C/I/P<br>v406 --> VAR-C/I/P/H<br>v407 --> VAR-C/I/P/V<br>v408 --> VAR-C/I/P-Co<br>v409 --> VAR-all<br>v410 --> VAR-all (no C)</p> </div> <div> </div> <div>Literature:</div> <div> </div> <div>Bakker, M., Post, V., Langevin, C.D., Hughes, J.D., White, J.T., Starn, J.J. and Fienen, M.N., 2016. Scripting MODFLOW model development using Python and FloPy. Groundwater, 54(5), pp.733-739. https://doi.org/10.1111/gwat.12413</div> <div> </div> <div>Seibert, S.L., Massmann, G., Meyer, R., Post, V.E.A., Greskowiak, J., 2024. Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2024.104763</div> <div> </div> <div><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Vincent E.A. Post (vincent@edinsi.nl), Rena Meyer (rena.meyer@uol.de) or Gudrun Massmann (gudrun.massmann@uol.de)</div>

Figure 5 in Quantitative phosphoproteomic analysis of chicken DF-1 cells infected with Eimeria tenella, using tandem mass tag (TMT) and parallel reaction monitoring (PRM) mass spectrometry

Figure 5. KEGG pathways of the differentially expressed phosphorylated proteins. The abscissa indicates the first 10 significantly enriched KEGG pathways and the ordinate indicates the significance of enriched KEGG pathways, the more left, the more significant.

Figure 4 in Quantitative phosphoproteomic analysis of chicken DF-1 cells infected with Eimeria tenella, using tandem mass tag (TMT) and parallel reaction monitoring (PRM) mass spectrometry

Figure 4. Gene ontology annotations of the differentially expressed phosphorylated proteins. The abscissa indicates the enriched GO functional classification, including biological process (A), cellular component (B), and molecular function (C). The ordinate indicates the size of the significance of corresponding to each entry, the more left, the more significant.

Figure 3 in Quantitative phosphoproteomic analysis of chicken DF-1 cells infected with Eimeria tenella, using tandem mass tag (TMT) and parallel reaction monitoring (PRM) mass spectrometry

Figure 3. Clustering heatmap of different expression phosphorylated peptides. Each row represents a phosphorylated peptide segment, each column represents a group of samples. The logarithmic value (logarithmic transformation based on 2) of the significantly differentially expressed phosphorylated peptides in different samples is displayed in the clustering heatmap in different colors. Red represents significant upregulation of phosphorylated peptides; blue represents significant down-regulation of phosphorylated peptides.

Figure 2 in Quantitative phosphoproteomic analysis of chicken DF-1 cells infected with Eimeria tenella, using tandem mass tag (TMT) and parallel reaction monitoring (PRM) mass spectrometry

Figure 2. Volcano plots from different group comparisons. The abscissa indicates difference multiple (logarithmic transformation based on 2), the ordinate indicates the significant of difference (logarithmic transformation based on 10). The red point is significantly upregulated phosphorylated peptide segment, the blue point is significantly downregulated phosphorylated peptide segment and the gray point is a phosphorylated peptide segment with no significant difference.

opencc-by-4.0Mar 2024View details →

Supplementary Material to "Exothermic reactions and 39Ar–40Ar thermochronology: Hydration leads to younger apparent ages"

<p>Here we briefly describe the supplementary materials for the publication "Exothermic reactions and 39Ar–40Ar thermochronology: Hydration leads to younger apparent ages" in Geology, 52(6), 458-462 by Schorn, S., Moulas, E., & Stüwe, K. (2024).</p>

opencc-by-4.0Oct 2023View details →

Combining Bayesian optimization and automation to simultaneously optimize reaction conditions and routes

<p>Yield and Conversion measurements for iodoalkylation reaction of four different terminal alkynes. The reaction conditions as well as the equivalent of the reactants and reagents for each of the three optimizers are listed in the corresponding JSON file. </p>

dryad40/100

Data from: A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation

<div> <p>Understanding how plant phenotypes are shaped by their environments is crucial for addressing questions about crop adaptation to new environments. This study investigated the interplay between developmental responses to temperature fluctuations and photoperiod perception in maize that contribute to genotype-by-environment variation in flowering time. We present a physiological reaction norm for flowering time plasticity (PRN-FTP) for studying large collections of genotypes tested in multi-environment trial (MET) networks. Using a new variable for computational envirotyping of sensed photoperiod, it was found that, at high latitudes, different genotypes in the same environment can experience hours-long differences in photoperiod. This emphasizes the importance of considering genotype-specific differences in the experienced environment when investigating plasticity. A statistical framework is introduced for modeling the PRN-FTP as a non-linear response function, with parameters putatively linked to different regulatory modules for flowering time. Applying the PRN-FTP to a sample of global breeding material for maize showed that tropical and temperate maize occupy distinct territories of the trait space for PRN-FTP parameters, supporting that the geographical spread and adaptation of maize was differentially mediated by exogenous and endogenous pathways for flowering time regulation. Our results have implications for understanding crop adaptation and for future crop improvement efforts.</p> </div>

opencc-zeroJul 2024View details →

opencc-by-4.0Mar 2024View details →

Dataset for "The Ithildin library for efficient numerical solution of anisotropic reaction-diffusion problems in excitable media"

<p>This archive contains the full source code of Ithildin as well as the data generated by the simulations used in the paper introducing the Ithildin software.</p>

opencc-by-4.0Nov 2018View details →

Improvements to stratospheric chemistry scheme in the UM-UKCA (v10.7) model: solar cycle and heterogeneous reactions

<p>These are the data and the Python notebooks required to create the figures from the paper.</p> <p> </p> <p>Abstract:</p> <p>Improvements are made to two areas of the United Kingdom Chemistry and Aerosol (UKCA) module, which forms part of the Met Office Unified Model (UM) used for weather and climate applications. Firstly, a solar cycle is added to the photolysis scheme. The effect on total column ozone of this addition was found to be around 1-2% in mid-latitude and equatorial regions in phase with the solar cycle. Secondly, reactions occurring on the surfaces of polar stratospheric clouds and sulfate aerosol are updated and extended by modification of the uptake coefficients of five existing reactions and the addition of a further eight reactions involving bromine species. These modifications are shown to reduce the overabundance of modeled total-column ozone in the Arctic during October to February, southern mid-latitudes during August, and the Antarctic during September. Antarctic springtime ozone depletion is shown to be enhanced by 25 DU on average, which now causes the ozone hole to be somewhat too deep compared to observations. We show that this is in part due to a cold bias of the Antarctic polar vortex in the model.</p>

opencc-by-4.0Mar 2019View details →

SN2 reactions

<p>This dataset probes chemical reactions of methyl halides with halide anions, i.e. <br> X- + CH3Y -> CH3X +  Y-, and contains structures for all possible combinations of <br> X,Y = F, Cl, Br, I. The dataset also includes various structures for several smaller <br> molecules that can be formed in fragmentation reactions, such as CH3X, HX, CHX or <br> CH2X- as well as geometries for H2, CH2, CH3+ and XY interhalogen compounds. In total, <br> the dataset provides reference energies, forces, and dipole moments for 452709 structures <br> calculated at the DSD-BLYP-D3(BJ)/def2-TZVP level of theory [1-4] using the ORCA 4.0.1 <br> code [5,6]. </p> <p>For more details, see https://arxiv.org/abs/1902.08408.</p> <p>[1] Grimme, S.; Antony, J.; Ehrlich, S. and Krieg, H. J. Chem. Phys. 132, 154104 (2010).<br> [2] Kozuch, S.; Gruzman, D. and Martin, J. M. J. Phys. Chem. C 114, 20801-20808 (2010).<br> [3] Grimme, S.; Ehrlich, S. and Goerigk, L. J. Comput. Chem. 32, 1456-1465 (2011).<br> [4] Weigend, F. and Ahlrichs, R. Phys. Chem. Chem. Phys. 7, 3297-3305 (2005).<br> [5] Neese, F. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2, 73-78 (2012).<br> [6] Neese, F. Wiley Interdiscip. Rev. Comput. Mol. Sci. 8, e1327 (2018).</p>

opencc-by-4.0Jul 2019View details →

Diels-Alder reactions dataset

<p>This is the dataset used for training the PhysNet model in "Reactive Atomistic Simulations of Diels-Alder Reactions: the Importance of Molecular Rotations". It contains energies, forces and dipole moments calculated at the M06-2X/6-31G* level of theory for structures of all 378 possible "amon" [1] structures of 2,3-dibromo-1,3-butadiene (DBB) and maleic anhydride (MA) at multiple geometries sampled by running Langevin dynamics at 1000 K at the PM7 level of theory. Additional geometries were generated by adaptive sampling [2,3]. In total, the dataset contains 224483 data points.</p> <p>For more details, see https://arxiv.org/abs/1906.07455.</p> <p>[1] Huang, B. and von Lilienfeld O. A., arXiv:1707.04146 (2017)<br> [2] Behler, J., Phys. Condens. Matter 26, 183001 (2014)<br> [3] Behler, J., Int. J. Quantum Chem. 115, 1032 (2015) </p>

Fig. 3 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)

Fig. 3. Phylogenetic tree of seven Trypanosome species and subsequent genotypes constructed with sequences of the amplicons generated by the HRMqPCR primers.

Fig. 4 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)

Fig. 4. Amplification plots, melt curves and standard curves of T. copemani, T. vegrandis G7 and T. noyesi G8 prepared from a plasmid containing trypanosome species.

Fig. 5. A-D in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)

Fig. 5. A-D: Derivative melt curves showing mock mixed infections generated from plasmid clones containing the following DNA: (A) T. noyesi G8 and T. copemani; (B) T. vegrandis G7 and T. copemani; (C) T. vegrandis G7 and T. noyesi G8; (D) T. vegrandis G7, T. noyesi G8 and T. copemani.

Fig. 1 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)

Fig. 1. Multiple sequence alignment of a portion of the 18S rDNA of seven Trypanosome species and subsequent genotypes used to design the HRM-qPCR assays.