Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
203
datasets available to search
ShareScore release 0.9.0
Dataset results
203 results for “mechanical evaluation”
An Open-access Database for the Evaluation of Cardio-mechanical Signals from Patients with Valvular Heart Diseases
<p>This dataset is for the paper "An Open-access Database for the Evaluation of Cardio-mechanical Signals from Patients with Valvular Heart Diseases" published to Frontiers in Physiology. Please cite "Yang C, Fan F, Aranoff N, Green P, Li Y, Liu C and Tavassolian N (2021) An Open-Access Database for the Evaluation of Cardio-Mechanical Signals From Patients With Valvular Heart Diseases.<br> Front. Physiol. 12:750221. doi: 10.3389/fphys.2021.750221" when using this database.</p> <p>The archive comprises SCG and GCG recordings sourced from and processed at multiple sites worldwide, including Columbia University Medical Center and Stevens Institute of Technology in the USA, as well as Southeast University, Nanjing Medical University, and the first affiliated hospital of Nanjing Medical University in China. It includes electrocardiogram (ECG), SCG, and GCG recordings collected from 100 patients with various conditions of valvular heart diseases, such as aortic and mitral stenosis. The recordings were collected from clinical environments with the same types of wearable sensor patch. Besides the raw recordings of ECG, SCG and GCG signals, a set of hand-corrected fiducial point annotations is provided by manually checking the results of the annotated algorithm. The database also includes relevant echocardiogram parameters associated with each subject such as ejection fraction, valve area, and mean gradient pressure.</p>
Molecular geometries and energies from quantum mechanical calculations and small molecule force field evaluations.
<p>Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction.<br> The quality of these studies relies on the quality of the force fields used to represent the systems. <br> Focusing on small molecules of fewer than 50 heavy atoms, this data compares nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2.<br> On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data.<br> <br> The data was created using scripts of the <a href="https://github.com/MobleyLab/benchmarkff/commit/fa45247aa9867f504c02eb6f62d8459a94a0a936">benchmarkff github repository</a>.</p> <p>A corresponding manuscript is submitted, a preprint is available on ChemRxiv:<br> <a href="https://doi.org/10.26434/chemrxiv.12551867.v2 ">Lim, Victoria T.; Hahn, David F.; Tresadern, Gary; Bayly, Christopher I.; Mobley, David (2020): Benchmark Assessment of Molecular Geometries and Energies from Small Molecule Force Fields. ChemRxiv. Preprint</a></p> <p>Read below or the file README.md for further information and description of the content:</p> <pre><code class="language-markdown"># README Version: 04 Nov 2020 For Python scripts that are NOT found in these directories, please check the [BenchmarkFF Github repo](https://github.com/MobleyLab/benchmarkff/tree/master/tools). ## Procedure 1. Prep OPLS3e file for analysis: standardize format by OpenEye in case of differences and convert from kJ/mol to kcal/mol. ``` cd prep python convert_extension.py -i opls3e_minimized.sd -o opls3e.sdf ``` 2. Remove mols that couldn't parameterize by ALL FFs. ``` python get_by_tag.py -i opls3e.sdf -s "SMILES QCArchive" -list trim3.txt -o trim3_full_opls3e.sdf ``` 3. Run analysis. ``` conda activate parsley # calc ddE, RMSD, and TFD distributions python compare_ffs.py -i match.in -t 'SMILES QCArchive' --plot > metrics.out # match_minima, only in 01_analysis_all and 02_analysis_all_smaller_cutoff python match_minima.py -i match.in --plot --cutoff 1.0 --readpickle # look at specific subsets, only in 01_analysis_all python color_by_moiety.py -i match.in -p metrics.pickle -s N-N.dat azetidine.dat octahydrotetracene.dat -o scatter_tfd_3_ # look at outliers,only in 01_analysis_all and 02_analysis_all_smaller_cutoff python tailed_parameters.py -i refdata_trim_overlap_full_openff_unconstrained-1.2.0.sdf -f <offxml file> --metric 'TFD' --cutoff 0.12 --tag "TFD to trim_overlap_full_qcarchive.sdf" --tag_smiles "SMILES QCArchive" > output_tfd.dat ``` ## Brief description of contents * High level: ``` . ├── 00_prep │ ├── convert_extension.py │ ├── opls3e_minimized.sd OPLS3e minimized structures from Schrodinger Maestro │ ├── opls3e.sdf standardized through OpenEye tools │ ├── opt_openff*.sdf OpenFF minimized conformations ├── 01_analysis_all compare all ffs (qm, GAFF(2), MMFF94(S), Smirnoff, OpenFF-X.X, OPLS3e) ├── 02_analysis_all_smaller_cutoff compare all ffs (qm, GAFF(2), MMFF94(S), Smirnoff, OpenFF-X.X, OPLS3e) with a smaller cutoff of .3 for match_minima ├── 03_analysis_latest_ffs compare only the latest versions of ffs (qm, GAFF2, MMFF94S, OpenFF-1.2, OPLS3e) ├── 04_analysis_openff_only compare only OpenFF ffs (qm, Smirnoff, OpenFF-X.X) └── README.md ``` * Inside an output directory: ``` YY_analysis_* various output files of above mentioned scripts, some are listed and described below: ├── bar*.png parameter coverage bar plots ├── ddE.dat relative energies data ├── fig_density_*.png scatter plots of ddE vs (RMSD or TFD) for each force field ├── match.in input file for compare_ffs.py ├── metrics.out output file for compare_ffs.py ├── metrics.pickle pickle file for compare_ffs.py -- you can read this into compare_ffs instead of rerunning the full analysis ├── refdata_*.sdf output SDF files with stored RMSD / TFD scores with reference to QM for each structure ├── relene_*.dat relative energies of matched conformers ├── ridge_dde.png compared energies plot ├── ridge_rmsd.svg compared rmsds plot ├── ridge_tfd.svg compared tfds plot ├── fig_scatter_*.png scatter plots of ddE vs (RMSD or TFD). these are noisy; I don't use these ├── trim3_*.sdf input SDF files for compare_ffs.py listed in match.in file ├── violin*.* violin plot showing ddE distributions ``` </code></pre>
Data from: Evaluating mechanisms of diversification in a Guineo-Congolian tropical forest frog using demographic model selection
The accumulation of biodiversity in tropical forests can occur through multiple allopatric and parapatric models of diversification, including forest refugia, riverine barriers and ecological gradients. Considerable debate surrounds the major diversification process, particularly in the West African Lower Guinea forests, which contain a complex geographic arrangement of topographic features and historical refugia. We used genomic data to investigate alternative mechanisms of diversification in the Gaboon forest frog, Scotobleps gabonicus, by first identifying population structure and then performing demographic model selection and spatially explicit analyses. We found that a majority of population divergences are best explained by allopatric models consistent with the forest refugia hypothesis and involve divergence in isolation with subsequent expansion and gene flow. These population divergences occurred simultaneously and conform to predictions based on climatically stable regions inferred through ecological niche modelling. Although forest refugia played a prominent role in the intraspecific diversification of S. gabonicus, we also find evidence for potential interactions between landscape features and historical refugia, including major rivers and elevational barriers such as the Cameroonian Volcanic Line. We outline the advantages of using genomewide variation in a model-testing framework to distinguish between alternative allopatric hypotheses, and the pitfalls of limited geographic and molecular sampling. Although phylogeographic patterns are often species-specific and related to life-history traits, additional comparative studies incorporating genomic data are necessary for separating shared historical processes from idiosyncratic responses to environmental, climatic and geological influences on diversification.
Applying an Inconsistency Repair Mechanism for clone-and-own Code Smell Analysis: the Apo-games Case Study (Evaluation Data)
<p>This is a repository containing the artifacts and the results of the evaluation of the solution paper "Applying an Inconsistency Repair Mechanism for <em>clone-and-own</em> Code Smell Analysis: the Apo-games Case Study"</p>
The University of California, Riverside Environmental Chamber Data Base for Evaluating Oxidant Mechanism. Indoor Chamber Experiments through 1993
<strong><span>THE UNIVERSITY OF CALIFORNIA, RIVERSIDE ENVIRONMENTAL CHAMBER DATA BASE FOR EVALUATING OXIDANT MECHANISMS</span></strong> <p>William P. L. Carter, Dongmin Luo, Irina L. Malkina and Dennis Fitz</p> <p>Project Report for<br>Cooperative Agreement 815779, United States Environmental Protection Agency</p> <p>March 20, 1995</p> <p>This two report describes the data base of University of California, Riverside, environmental chamber experiments for use when evaluating photochemical mechanisms for urban and regional airshed models. This includes data obtained using the Statewide Air Pollution Research Center (SAPRC) Evacuable Chamber (EC), Indoor Teflon Chamber #1 (ITC), Indoor Teflon Chamber #2 (ETC), Dividable Teflon Chamber (DTC), and Xenon arc Teflon Chamber (XTC) between September of 1975 through November of 1993. This document provides backing information and data for that data set as well. This document lists and summarizes the experiments, summarizes the facility and procedures employed, documents the analytical and monitoring methods and their calibration data and associated uncertainties, assigns and documents the input data needed to conduct model simulations of the experiments in the present data base, and describes the format of the data sets which are distributed with this document on computer diskettes. Files are included in the distribution to permit modeling of the experiments in the present data base using the SAPRC-90 and the Carbon Bond IV chemical mechanisms, though a full mechanism evaluation procedure is beyond the scope of this report. Recommendations are made concerning the steps that need to be taken before using these data to evaluate chemical mechanisms.</p> <p>This report consists of two volumes. Volume 1 contains the main body of the text documenting the data base, and Volume 2 contains the three appendices. Appendix A contains printouts of spreadsheets containing summaries of the runs in the data base. Appendix B contains tabulations of the NOx and GC calibration data, which are too lengthy to include in the main body of the report. Appendix C describes how to install the distributed data files and software on a computer and how to conduct initial model simulations of the runs using the SAPRC modeling software and the SAPRC-90 and Carbon Bond IV mechanisms.</p>
Evaluation of the pKa's of Quinazoline Derivatives : Usage of Quantum Mechanical Based Descriptors
<p>In this study, several quantum mechanical-based computational approaches have been used in order to propose accurate protocols for predicting the p<em>K<sub>a</sub></em>’s of quinazoline derivatives, which constitute a very important class of natural and synthetic compounds in organic, pharmaceutical, agricultural and medicinal chemistry areas. Linear relationships between the experimental p<em>K<sub>a</sub></em>’s and nine different DFT descriptors (atomic charge on nitrogen atoms (<em>Q</em>(N), ionization energy (<em>I</em>), electron affinity (<em>A</em>), chemical potential (m), hardness (h), electrophilicity index (w), fukui functions (<em>f <sup>+</sup></em>, <em>f <sup>-</sup></em>), condensed dual descriptor (D<em>f</em>) and local hypersoftness (s<sup>(2)</sup>)) were considered. Several DFT methods (a combination of five DFT functionals and two basis sets) in conjunction with two different implicit solvent models were tested, and among them, M06L/6-311++G(d,p) level of theory employing the CPCM solvation model was found to give the strongest correlations between the DFT descriptors and the experimental p<em>K<sub>a</sub></em>’s of the quinazoline derivatives. The calculated atomic charge on N<sub>1</sub> atom (<em>Q</em>(N<sub>1</sub>)) was shown to be the best descriptor to reproduce the experimental p<em>K<sub>a</sub></em>’s (R<sup>2</sup>=0.927), whereas strong correlations were also derived for <em>A</em>, w, m, and Δ<em>f</em>. In the last part, the applicability of isodesmic reaction scheme to the p<em>K<sub>a</sub></em> prediction of quinazoline derivatives was tested, and the calculated <em>A</em> was shown to be a well-established method for the classification of molecules, and thus, for the identification of a suitable reference molecule for the calculations. The QM-based protocols presented in this study will enable fast and accurate high-throughput p<em>K<sub>a</sub></em> predictions of quinazoline derivatives and the relationships derived can be effectively used in data generation for successful machine learning models for p<em>K<sub>a</sub></em> predictions.</p>
Evaluation of Mechanical Thrombectomy in Acute Ischemic Stroke Related to a Distal Arterial Occlusion
ClinicalTrials.gov study NCT05030142. IPD Sharing: YES. Countries: 1. Publications: 1.
A Study To Evaluate The Mechanism Of Action Of CP-690,550 In Patients With Rheumatoid Arthritis
ClinicalTrials.gov study NCT00976599. IPD Sharing: Not stated. Countries: 1. Publications: 12.
Evaluation of Efficacy and Mechanisms of an Antiinflammatory Intervention for Chemotherapy Related Mucosal Injury
ClinicalTrials.gov study NCT00031551. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Evaluation of the Efficacy and Mechanisms of a Novel Intervention for Chronic Pain Tailored to People Living With HIV
ClinicalTrials.gov study NCT03692611. IPD Sharing: NO. Countries: 1. Publications: 93.
Evaluating Mechanically Engineered Stem Cell Exosomes for Treating Endometrial Injury: A Clinical Study
ClinicalTrials.gov study NCT06896747. IPD Sharing: YES. Countries: 1. Publications: 6.
Evaluation of the Mechanism of Action of Platelet Rich Fibrin Matrix (PRFM) in Producing Skin Volume Augmentation
ClinicalTrials.gov study NCT00956020. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Evaluating mechanisms of diversification in a Guineo-Congolian tropical forest frog using demographic model selection
Open the record for dataset details and reuse information.
The dataset for Evaluation of plume-induced continental crust growth rate in early Earth: Insight from integrated petrological-thermo-mechanical modeling
<p>All data of model results for the paper <em>Evaluation of plume-induced continental crust growth rate in early Earth: Insight from integrated petrological-thermo-mechanical modeling</em>.</p> <p>Contents of this dataset includes:</p> <p>A list for models and data of model results are provided in the zip file. </p> <p>The files suffixed *.grd are grid datas that can be draw by GMT.</p> <p>The files suffixed *.info are datas of the evolution of volume of the continental crust and TTGs in the model.</p> <p>The files suffixed *.prn are datas of P-T condtions of continental crust generation by partial melting.</p> <p>The files suffixed *.py are python codes for visualization of the volume of continental crust and P-T datas.</p>
Why do open-farmland specialist birds prefer small fields? The evaluation of mechanisms using a cross-border study
Open the record for dataset details and reuse information.
Data from: A re-evaluation of the effects of mechanical cockle dredging in the Dutch Wadden Sea
<p>The three datasets are obtained directly from the papers we discuss or from their authors. The first two datasets concern recruitment of cockles and Balthic tellins at seven sites in the Wadden Sea. The third dataset contains data on dredging and suitability for knots at 272 1 km<sup>2</sup> grid cells in the western Wadden Sea.</p>
Data for "A thermal-hydro-mechanical model for evaluating the stability of mountain glaciers"
<p>This dataset details the data produced in our study "A thermal-hydro-mechanical model for evaluating the stability of mountain glaciers".</p>
Study data of : Preparation and evaluation of in situ eye gel with a dual triggered mechanism for the delivery of gatifloxacin and betamethasone sodium phosphate
<p><strong>Preparation and evaluation of in situ eye gel with a dual triggered mechanism for the delivery of gatifloxacin and betamethasone sodium phosphate</strong></p>
Clinical Evaluation and Antimicrobial Effect of Papain Based Chemo-mechanical Caries Removal Agents
ClinicalTrials.gov study NCT05983900. IPD Sharing: YES. Countries: 1. Publications: 1.
Evaluating the Efficacy of the Sliding Mechanisms on Round-section Arch Wire
ClinicalTrials.gov study NCT07243509. IPD Sharing: NO. Countries: 1. Publications: 5.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.