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1,582 results for “manuscript”
Digital publishing of Indic manuscripts and inscriptions using the READ Workbench corpus development, research and publishing framework
<p>Paper presented on Friday 11 June 2021 at the Digital Medievalist Global Symposium <em>The past, present, and future of Digital Medieval Studies</em> for the Asia & Oceania Panel, in the session Reading Indic and Japanese scripts.</p> <p> </p>
Supporting data for the manuscript "Nerpa: a tool for discovering biosynthetic gene clusters of nonribosomal peptides"
<p>Preprocessed structures of nonribosomal peptides [NRPs] and genomic sequences (reference and representative genomes, biosynthetic gene clusters [BGCs]) used in the benchmark experiments in the Nerpa paper.</p> <p><strong>Files description</strong></p> <ul> <li><strong>mibig_nrp_bacteria_preprocessed.tar.gz</strong> contains the preprocessed dataset of 194 bacterial NRP BGCs from the MIBiG database.</li> <li><strong>mibig_nrp_bacteria_summary.tsv</strong> contains metadata for the MIBiG-NRP dataset.</li> <li><strong>bacterial_ref_and_repr_genomes_20210604_preprocessed.tar.gz</strong> contains the preprocessed dataset of 13,399 reference and representative bacterial genomes from the NCBI RefSeq database (retrieved on 2021/06/04).</li> <li><strong>bacterial_ref_and_repr_genomes_20210604_summary.txt</strong> contains metadata for the RefSeq dataset.</li> <li><strong>pnrpdb_preprocessed.info</strong> contains the Nerpa-preprocessed pNRPdb database, a database of 8,368 known and putative NRP structures.</li> <li><strong>pnrpdb_summary.tsv</strong> contains the pNRPdb database metadata.<br> </li> </ul>
Data and script for analyses from the manuscript titled: Contaminant metal concentrations in three species of aquatic macrophytes from the Coeur d'Alene Lake basin, USA..
<p>These files include R statistical software script, an archived "project" file, and a "ReadMe.rtf" file. See the "ReadMe.rtf" file for further instructions. Also, please see the full article for more detail at: </p> <p>Scofield, B.D., Torso, K., Fields, S.F., & D.W. Chess<em>.</em> Contaminant metal concentrations in three species of aquatic macrophytes from the Coeur d’Alene Lake basin, USA. <em>Environ Monit Assess</em> <strong>193, </strong>683 (2021). <a href="https://doi.org/10.1007/s10661-021-09488-y">https://doi.org/10.1007/s10661-021-09488-y</a> </p>
Manuscript V - Supplementary material
<p><strong>Supplementary material for manuscript V in dissertation:</strong></p> <p>Selection of rye (<em>Secale cereale</em> L.) for powdery mildew and leaf rust resistance through phenotyping, target sequencing, and association genetics</p>
Manuscript V - Supplementary material
<p><strong>Supplementary material for manuscript V in dissertation:</strong></p> <p>Selection of rye (<em>Secale cereale</em> L.) for powdery mildew and leaf rust resistance through phenotyping, target sequencing, and association genetics</p>
Manuscript II - Supplementary material
<p><strong>Supplementary material for manuscript II in dissertation:</strong></p> <p>Selection of rye (<em>Secale cereale</em> L.) for powdery mildew and leaf rust resistance through phenotyping, target sequencing, and association genetics</p>
Manuscript III - Supplementary material
<p><strong>Supplementary material for manuscript III in dissertation:</strong></p> <p>Selection of rye (<em>Secale cereale</em> L.) for powdery mildew and leaf rust resistance through phenotyping, target sequencing, and association genetics</p>
Manuscript I - Supplementary material
<p><strong>Supplementary material for manuscript I in Thesis</strong>:</p> <p>Selection of rye (<em>Secale cereale</em> L.) for powdery mildew and leaf rust resistance through phenotyping, target sequencing, and association genetics</p> <p> </p>
DeepSTARR manuscript data
<p>This repository holds the trained DeepSTARR model and the data used to train and evaluate the model.</p> <p><strong>Files:</strong></p> <ul> <li><strong><set>.fa</strong> <ul> <li>FASTA files with DNA sequences of genomic regions from train/val/test sets.</li> </ul> </li> <li><strong><set>*.txt</strong> <ul> <li>Files with developmental and housekeeping activity of genomic regions from train/val/test sets.</li> </ul> </li> <li><strong>DeepSTARR.model.h5 </strong>and<strong> DeepSTARR.model.json</strong> <ul> <li>DeepSTARR Keras model</li> </ul> </li> </ul>
Supporting dataset for manuscript "Direct viscosity measurement of peridotite melt under lower-mantle conditions supports a fractional magma ocean solidification at top lower mantle conditions"
<p>Supporting material for manuscript "<strong>Direct viscosity measurement of peridotite melt under lower-mantle conditions supports a fractional magma ocean solidification at top lower mantle conditions"</strong></p>
Data from "Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR" manuscript
<p>Data from "Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR" manuscript. Full results for applications 1 and 2.</p>
Scripts for post-processing Delft3d output data and figures for manuscript 'Longitudinal scour-bar pattern in estuaries'
<p>The 7z file contains two folders, one named 'mat' contains the matlab scripts for post-processing Delft3D output data and plotting, the other named 'Figures' contains main outputs for the manuscript 'Longitudinal scour-bar pattern in estuaries'. </p>
Dataset for the Manuscript: Surfactants Control Optical Trapping Near a Glass Wall
<p>This repository includes datasets supporting our manuscript that will be transferred to <em>the Journal of Physical Chemistry C</em>. This Version 2 includes extensive new results conducted during the revision process. </p> <ul> <li><strong>'Videos.zip'</strong>: Recordings of trapped particles, estimated trajectories, and calculated MSDs<strong>.</strong></li> <li><strong>'Dynamic Light Scattering.zip'</strong>: Measurement data using dynamic light scattering (DLS). It includes the conductivity, zeta potentials, and hydrodynamic size measurements.</li> <li><strong>'Raw data manual.html'</strong>: A data manual explaining the data details and visualizing the results.</li> </ul> <p>Notes:</p> <p>For finding particle trajectories, we used a Python package, <a href="http://soft-matter.github.io/trackpy/v0.4.2/index.html">Trackpy</a>, developed by Allan et al. We simply followed <a href="http://soft-matter.github.io/trackpy/v0.4.2/tutorial/walkthrough.html">their walkthrough</a> to find particle locations in a video recording and link them to a particle trajectory. The details of our trajectory outputs (_traj.csv files) can be found in <a href="http://soft-matter.github.io/trackpy/v0.4.2/generated/trackpy.locate.html#trackpy.locate">their API reference</a>. </p>
Data set related to the manuscript "Carbon-carbon supercapacitors: Beyond the average pore size or how electrolyte confinement and inaccessible pores affect the capacitance"
<p>Graphical files in the agr format and xyz files for the figures in the manuscript entitled "Carbon-carbon supercapacitors: Beyond the average pore size or how electrolyte confinement and inaccessible pores affect the capacitance". Examples of input files for the two systems simulated.</p>
Data for manuscript "Prominent Role of Sulfate Reduction in Robust Sulfur Retention in Subtropical Soil"
<p>Data for manuscript "Prominent Role of Sulfate Reduction in Robust Sulfur Retention in Subtropical Soil" submitted to Geophysical Research Letters</p>
Data and code for the manuscript Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration
<p>Data and code for the manuscript <em>Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration</em> accepted for publication to<em> </em> <em>Earth and Space Science</em> in October 2021.</p> <p>The dataset contains 7 month of total losses (transmitted - received power levels) and retrieved water vapor density from a 4.87 km long full-duplex E-band commercial microwave link (CML) operating at 73.5 and 83.5 GHz in Prague, CZ. The CML was operated as a part of a mobile phone backhaul. Furthermore, observations of air temperature, and air relative humidity from sites close to the CML end nodes are provided. Finally, theoretical gaseous attenuation calculated from the air temperature and relative humidity is included as a part of the dataset.</p> <p>Data are stored in semicolon-delimited csv files. Time stamps are in UTC time in the format yyyy-mm-dd HH:MM:SS. All time series are regular and have 5-min temporal resolution. Metadata are stored in text files.</p> <p>The code is in a form of R Markdown files and html notebooks. Results presented in the manuscript Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration and in its Supporting information are fully reproducible using this dataset.</p>
Dataset and R code for the manuscript:Interspecific facilitation drives coexistence by favouring rare sensitive species and reducing performance disparities
<p>The following directory contains the data necessary to replicate the results obtained in the manuscript entitled: <strong>Interspecific facilitation drives coexistence by favouring rare sensitive species and reducing performance disparities </strong></p> <p>We provided an R workspace containing the data "Dataset1.RData", a "ReadMe.txt" archive with detailed information of the variables included in "Dataset1.RData", and the R code necessary to replicate the results and figures ("Rcode1.txt")</p>
The dataset of the manuscript: A Sub-Grid Parameterization Scheme for Topographic Vertical Motion in CAM5-SE
<p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/figure_code.zip?versionId=83ff16db-ce42-4c35-80cc-f8f8cee2c7d5">figure_code.zip</a>: code of drawing figures.</p> <p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/modification_code.zip?versionId=6f6e777a-8c5c-4134-b4e2-34985ff6c595">modification_code.zip</a>: add the code of topographic vertical montion and sub-grid topographic parameterization scheme in CAM5-SE.</p> <p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/output_data.rar">output_data.rar</a>: the results of sensitivity experiments for CAM5-SE.</p> <p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/draw_data.rar">draw_data.rar</a>: interpolated data according to output results and inputdata of drawing figures.</p> <p> </p>
Data in support to the manuscript: Testing a novel sensor design to jointly measure cosmic-ray neutrons, muons and gamma rays for non-invasive soil moisture estimation by Gianessi et al. (2024)
<p>The files contain data presented and discussed in the manuscript: Testing a novel sensor design to jointly measure cosmic-ray neutrons, muons and gamma rays for non-invasive soil moisture estimation by Gianessi et al. (2024).</p> <div> <div>Gianessi, Stefano, Matteo Polo, Luca Stevanato, Marcello Lunardon, Till Francke, Sascha E. Oswald, Hami Said Ahmed, et al. “Testing a Novel Sensor Design to Jointly Measure Cosmic-Ray Neutrons, Muons and Gamma Rays for Non-Invasive Soil Moisture Estimation.” <em>Geoscientific Instrumentation, Methods and Data Systems</em> 13, no. 1 (January 16, 2024): 9–25. <a href="https://doi.org/10.5194/gi-13-9-2024">https://doi.org/10.5194/gi-13-9-2024</a>.</div> </div> <p> </p>
Simulation data associated to the manuscript "Controlling the Hydrophilicity of the Electrochemical Interface to Modulate the Oxygen-Atom Transfer in Electrocatalytic Epoxidation Reactions"
<p>Contains input files used to perform the simulations of the article:</p> <p>Controlling the Hydrophilicity of the Electrochemical Interface to Modulate the Oxygen-Atom Transfer in Electrocatalytic Epoxidation Reactions</p> <p>Florian Dorchies, Alessandra Serva, Dorian Crevel, Jérémy de Freitas, Nikolaos Kostopoulos, Marc Robert, Ozlem Sel, Mathieu Salanne and Alexis Grimaud<br> *ChemRxiv*, 2022</p> <p>https://doi.org/ 10.26434/chemrxiv-2022-wjsbs-v2</p> <p>Each folder contains 2 input files for MetalWalls, which is available [here](https://gitlab.com/ampere2/metalwalls). The corresponding systems are the following:</p> <ul> <li>Bulk liquids: <ul> <li>Acetonitrile - water - LiClO4</li> <li>Acetonitrile - water - LiClO4 with cyclooctene</li> <li>Acetonitrile - water - TBAClO4</li> <li>Acetonitrile - water - TBAClO4 with cyclooctene</li> </ul> </li> <li>Liquids in contact with gold electrodes: <ul> <li>Acetonitrile - water - LiClO4</li> <li>Acetonitrile - water - LiClO4 with cyclooctene</li> <li>Acetonitrile - water - TBAClO4</li> <li>Acetonitrile - water - TBAClO4 with cyclooctene</li> </ul> </li> </ul>
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.