Find research datasets worth reusing

opencc-by-sa-4.0Jan 2018View details →

Dataset supplementing Schütz, I. & Einhäuser, W. (2018) Visual awareness in binocular rivalry modulates induced pupil fluctuations.

This dataset supplements the publication: Schütz, I. & Einhäuser, W. (2018). Visual awareness in binocular rivalry modulates induced pupil fluctuations. Raw data are available in two formats: the actual raw EDF data files as returned by the eyetracking device (*.edf) for reference, and as MATLAB files into which all relevant information has been extracted (*.mat) for analysis. Variables in the pft_*.mat files include - raw eye position in the variable scan (t,x,y,p), where t is the timestamp of the eyetracker, x/y the position on the screen and p the pupil diameter in arbitrary units - fixation, saccade and blink events in variables fix, sac and blink - raw button presses in cell arrays buttonDn and buttonUp (6 - left button, 7 - right button) including timestamps - stimulus presentation cycle timestamps in the variable stimperiod - timestamps for auditory attentional instruction in the variable attends For analysis, data from all participants and sessions is imported into pftdata.mat, where it is stored in cell arrays of the format "samples{subject_no, condition}". Data Files ========== - rawdata.zip     - rawdata/*.edf: raw EyeLink 2000 EDF data files     - rawdata/*.mat: EyeLink data converted to MATLAB data file - analysis.zip     - pftdata.mat: preprocessed eye tracking and response data for analysis     - face.png, house.png: stimulus images used for the experiment     - resp_anova.csv: response data for ANOVA (generated by preprocessing.m)     - fig4_anova.csv: complex plane data for R T-Test (generated by figure4_complex_plane.m)     - analysis code files, see below Analysis Functions ================== Run the following functions in the listed order to reproduce figures and data in results/. - preprocessing.m:     - convert EDF data files to ASCII using SR-Research edf2asc, import into MATLAB     - remove EyeLink detected blinks and interpolate (cubic spline)     - z-score pupil data within each experimental block     - add button press / reported percept to sample data     - save response data for RM-ANOVA in R - figure1_methods.m:     - recreates Figure 1 (stimulus figure from images) - figure2_example_plot.m:     - recreate Figure 2 (example data from one participant) - figure3_averaged_response.m     - recreates Figure 2 (averaged F1 FFT component by condition) - figure4_complex_plane.m:     - recreates Figure 4 (complex plane analysis of pupil response) - stats_auc_decoding.m:     - moment-by-moment decoding analysis using AUC     - recreates stats_AUC.txt - pft_statistics.R:     - R statistics, recreates stats_responses.txt and stats_Zvalues.txt Output Files ============ results/     - Paper Figures (not layouted): figure1.tif, figure2.png, figure3.png, figure4.png     - stats_responses.txt: behavioral analyses results,     - stats_Zvalues.txt: complex plane analysis results     - stats_AUC.txt: moment-by-moment AUC decoding results

opencc-by-4.0Mar 2018View details →

PARN and TOE1 constitute a 3′ end maturation module for nuclear non-coding RNAs

HeLa cells were cultured in DMEM (Welgene) supplemented with 9% fetal bovine serum (Welgene). HeLa cells were transfected with 20 nM of siRNAs for four days using Lipofectamine 3000 (Thermo Fisher Scientific). Equal amounts of four different siRNAs were used for each knockdown. In the combinatorial knockdown, we mixed multiple siRNA pools to have a final concentration of 20 nM per siRNA pool. Total RNAs were extracted from siRNA-transfected HeLa cells using TRIzol reagent (Thermo Fisher Scientific) according to the manufacturer’s protocol and treated with DNase I (Takara). mTAIL-seq libraries were prepared as previously described (Lim et al., 2016). Amplified cDNA libraries were sequenced on an Illumina MiSeq platform with 50% of the PhiX control library (Illumina). The uploaded file includes both intensity and sequence information for spike-ins and libraries used in the mTAIL-seq analysis. These data can be processed with Tailseeker 3.1.7 (Chang, 2017) according to the standard workflow of the software. The source codes and container images are available from Zenodo (https://zenodo.org/record/887547; doi:10.5281/zenodo.887546).

opencc-by-4.0May 2019View details →

Outdoor monitoring data of an Insolight B-series module - CPV sub-module

Dataset from the outdoor characterization of a B Series module from Insolight at the rooftop of the Instituto de Energía Solar - Universidad Politécnica de Madrid. It was the basis of its power rating at CSTC and has informed several scientific and technical articles like the oral presentation by Gaël Nardin et al. "Towards Industrialization of Planar Microtracking Photovoltaic Panels" at the 15th International Conference on Concentrator Photovoltaics (CPV-15), held between 25 and 27 March of 2019 in Fes, Morocco.  Monitoring campaign: <ul> <li>Location: 40.453°N, -3.727°E. <a href="https://www.google.com/maps/place/40%C2%B027'11.6%22N+3%C2%B043'37.3%22W/@40.453215,-3.7275722,142m/data=!3m2!1e3!4b1!4m13!1m6!3m5!1s0x0:0xc636231f90c3bbeb!2sInstituto+de+Energ%C3%ADa+Solar!8m2!3d40.4531766!4d-3.7269107!3m5!1s0x0:0x0!7e2!8m2!3d40.4532142!4d-3.7270248">Instituto de Energía Solar</a>, Universidad Politécnica de Madrid. 28040 Madrid, Spain.</li> <li>Starting date: 21 November 2018</li> <li>End date: 14 December 2018</li> </ul> Description of data files: <ul> <li>Data files format: tab-separated text file; headers in first row.</li> <li>I-V parameters: single file "Insolight Preseries outdoor monitoring - IES rooftop - UPM.txt". Headers: <ul> <li>Date (DD/MM/YYYY)    </li> <li>Time (HH:MM:SS): time in CET / UTC+1</li> <li>Pmp (W): peak power</li> <li>Vmp (V): voltage at maximum power point</li> <li>Imp (A): current at maximum power point</li> <li>Isc (A): short-circuit current</li> <li>Voc (V): open-circuit voltage</li> <li>FF: fill factor</li> <li>Tair (°C): ambient temperature    </li> <li>Tlens (°C): temperature at the aperture plane</li> <li>GNI (W/m2): global normal irradiance at the aperture plane as measured with a pyranometer. Spectral range: 305 – 2800 nm.</li> </ul> </li> <li>Weather data: daily files "geonica2018_**_**.txt". Headers: <ul> <li>yyyy/mm/dd: date</li> <li>hh:mm: time in GMT/UTC</li> <li>V_Viento (m/s): wind speed</li> <li>D_Viento (°N): wind direction</li> <li>Temp_Air(°C): ambient temperature</li> <li>Rad_Dir(W/m2): direct normal irradiance as measured by a Normal Incidence Pyrheliometer from Eppley. Spectral Range: 250-3000 nm. Field of view: 5°</li> <li>Ele_Sol (°): solar tilt</li> <li>Ori_Sol (°N): solar position azimuth</li> <li>Top (W/m2): direct normal irradiance as measured by a top component cell of a lattice-matched III-V triple-junction cell in the  <a href="http://solaraddedvalue.com/en/category/products/spectro-heliometer/">ICU-3J35</a> spectroheliometer from Solar Added Value. Spectral range: 300 - 680 nm. Field of view: 5.7º</li> <li>Mid (W/m2): direct normal irradiance as measured by a middle component cell of a lattice-matched III-V triple-junction cell in the  <a href="http://solaraddedvalue.com/en/category/products/spectro-heliometer/">ICU-3J35</a> spectroheliometer from Solar Added Value. Spectral range: 680 - 900 nm. Field of view: 5.7º</li> <li>Bot (W/m2): direct normal irradiance as measured by a bottom component cell of a lattice-matched III-V triple-junction cell in the  <a href="http://solaraddedvalue.com/en/category/products/spectro-heliometer/">ICU-3J35</a> spectroheliometer from Solar Added Value. Spectral range: 900 - 1800 nm. Field of view: 5.7º</li> <li>Cal_Top: n/a</li> <li>Cal_Mid: n/a</li> <li>Cal_Bot: n/a</li> <li>Pres_Aire: n/a</li> </ul> </li> </ul>

opencc-by-4.0Jul 2021View details →

Modulation of bioelectric cues in the evolution of flying fishes [Data set]

Assembled reference contigs for protein-coding exons and conserved non-coding regions from targeted sequence enrichment of beloniform fishes.  Current citation: Daane JM, Blum N, Lanni J, Boldt H, Iovine MK, Johnson SL, Lovejoy NR, and MP Harris. (2021). Novel regulators of growth identified in the evolution of fin proportion in flying fish. bioRxiv. doi: 10.1101/2021.03.05.434157 -contigs.tar.gz contains the assembled contigs for each species. Each contig represents a targeted region with the addition of flanking DNA sequence -cnes.tar.gz contains the targeted conserved non-coding regions isolated from the larger contigs in contigs.tar.gz -exons.tar.gz contains the targeted protein coding exons isolated from the larger contigs in contigs.tar.gz -translated_exons.tar.gz contains the translated protein coding exons from exons.tar.gz -Beloniformes.tre is the species tree  -medaka_cne_great.txt contains the associations between the assembled CNEs and neighboring protein-coding genes based on the GREAT approach

opencc-by-4.0Dec 2022View details →

PnP module: multi-material components manufacturing by Automated Tape Laying process

Introduction The Automated Tape Laying (ATL) process is an automated technique used for composites manufacturing based on fiber placement processes. This module is part of AIMEN Technology Centre Open Pilot Line focusing on manufacturing of multi-material components. This module is composed by a movement system (robot) and heating system (ATL head), which can be composed by IR system or laser source.  Asset Administration Shell The Asset Administration Shell (AAS) modelling follows the Product, Process and Resources (PPR) model. The relation between the assets allows the traceability of the Product by demonstrating a Digital Thread based on AAS and how the active AAS modelling allows the Plug and Produce capabilities in a modular production scheme. In this repository some examples of AAS modeling (.aasx files) for a subset of assets in the shop floor (Resources), Product and Process can be found, as well as the architecture of the whole module. Architecture The information gathered by the central unit/industrial PC (Operational Technology) will be available in DIMOFAC platform (Information Technology) as well as the Product information related to the design and/or simulation (Engineering Technology). In the central unit the software in charge of taking the decision and allowing Plung and Produce capabilities is named “Orchestrator”, and in the product side, the software in charge of register all the information related with a specific software “Digital Thread”.   AAS Demonstration A demonstration video is available: <a href="https://www.youtube.com/watch?v=aOP6QWiF5FE&t=7s">PnP module: multi-material components manufacturing by Automated Tape Laying process - YouTube</a>

opencc-by-4.0Mar 2023View details →

Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems

Dataset used in the publication "Modulation Engineering: Stimulation Design for Enhanced Kinetic Information from Modulation-Excitation Experiments on Catalytic Systems" (<a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1021%2Facscatal.3c00646&data=05%7C01%7CValentijn.DeCoster%40UGent.be%7C2a7a2c81f646405654d308db2f58f8ec%7Cd7811cdeecef496c8f91a1786241b99c%7C1%7C0%7C638155831400735344%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=e%2Fyp50KsegsMtKcY9ijwh3AqUbrsxFLo%2BTXyGmzOLps%3D&reserved=0">https://doi.org/10.1021/acscatal.3c00646</a>). A description document ("Data overview.docx") is included and provides an overview of the dataset.

opencc-by-4.0Mar 2023View details →

Non-invasive modulation of human corticostriatal activity [Dataset]

This dataset contains resting-state functional MRI data used in the study "Non-invasive modulation of human corticostriatal activity" (Caballero-Insaurriaga et al, PNAS, 2023). In this study two datasets were used: one from a transcranial static-magnetic-field stimulation (tSMS) experiment (tSMS20) and another one from the Human Connectome Project (HCP100). The tSMS20 dataset was originally acquired for a previous study tSMS over the Supplementary Motor Area (Pineda-Pardo et al, Commun Biol, 2019). The regions used in the study are also provided. As for the tSMS20 dataset, the stimulation protocol consisted of 30-minute tSMS using a single magnet placed over the supplementary motor area (SMA). Each subject underwent two stimulation sessions (real and sham) in two separate days, whose order was randomized. In each session, structural MRI was acquired before tSMS, and resting-state fMRI before and after. Structural images were T1-weighted (T1w), with 1 mm isotropic voxel. Functional data was acquired in 10 minutes-long sessions, TR/TE 2400/30 ms (250 volumes per session), with 3mm isotropic voxel. The preprocessed resting-state fMRI data are included in this repository (see dataset_description.txt file and Pineda-Pardo et al, Commun Biol, 2019 for more details) As for the HCP100 dataset, only the subject list is included, as data are already publicly available from the HCP initiative. If you use this data in a publication, please cite: Pineda-Pardo, J. A., Obeso, I., Guida, P., Dileone, M., Strange, B. A., Obeso, J. A., Oliviero, A. & Foffani, G. Static magnetic field stimulation of the supplementary motor area modulates resting-state activity and motor behavior. Communications Biology 2, (2019) Caballero-Insaurriaga, J., Pineda-Pardo, J. A., Obeso, I., Oliviero, A. & Foffani, G. Non-invasive modulation of human corticostriatal activity. Proceedings of the National Academy of Sciences of the United States of America (2023)

opencc-by-4.0Apr 2023View details →

Ergolide Mediates Anti-Cancer Effects on Metastatic Uveal Melanoma Cells and Modulates their Cellular and Extracellular Vesicle proteomes

Underlying dataset and extended dataset of the results described in the article "Ergolide Mediates Anti-Cancer Effects on Metastatic Uveal Melanoma Cells and Modulates their Cellular and Extracellular Vesicle proteomes".

openCC0Apr 2017View details →

LAGOS-NE-LOCUS v1.01: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013

This data package, LAGOS-NE-LOCUS v1.01, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes. (2) LAGOS-NEGEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO v1.087.1: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NE-GEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE-LOCUS v1.01 module includes information on the physical location and features of all lakes > 4 ha. The information provided for this population of lakes includes: lake unique identifiers, lake area, perimeter, latitude and longitude, and the zone IDs that the lake is located within (e.g., state, county, the hydrologic unit at each level (4, 8, and 12). Citation for

openCC (other)Oct 2024View details →

LAGOS-US LANDSAT: Data module of remotely-sensed water quality estimates for U.S. lakes over 4 ha from 1984 to 2020

This data package, LAGOS-US LANDSAT, is one of the extension data modules of the LAGOS-US platform that provides six water quality estimates (chlorophyll, Secchi depth, dissolved organic carbon, total suspended solids, turbidity, and true water color) from remote sensing for lakes ≥ 4 ha in the conterminous U.S. (48 states plus the District of Columbia) for the years 1984-2020. These estimates are generated through machine learning models on in-lake water quality matchups from LAGOS-US LIMNO with Landsat 5, 7, and 8 whole lake median reflectance values and pixel-wise band ratios that are subsequently used to make predictions across the U.S. The LANDSAT module contains remotely sensed reflectance values for 136,977 of the 137,465 lakes ≥ 4 ha from the LAGOS-US research platform. Within the module are a total of 45,867,023 sets of reflectance values, a matchup dataset with a window of up to 7 calendar days with in situ data, and associated water quality parameter predictions for each reflectance set. Additional quality control flags are provided for predictions indicating whether reflectance extractions included negative values, the percent of the maximum pixels ever retrieved for that lake that the predictions are based on, and whether there are shared calendar day predictions due to scene overlap.

openCC (other)Jul 2021View details →

LAGOS-US NETWORKS v1.0: Data module of surface water networks characterizing connections among lakes, streams, and rivers in the conterminous U.S

Knowing the degree of surface water connectivity among aquatic ecosystems can help scientists better understand and predict the movement of materials and biota across ecosystems. Methods to quantify surface water networks that include lake and stream connections at broad spatial scales are rare because it is difficult to balance accurate estimates of surface water connectivity and computational challenges. The LAGOS-US NETWORKS (NETS) module contains surface connectivity metrics for lake networks across the conterminous United States. We applied a graph theory approach to identify lake networks (i.e. a set of lakes connected by streams either upstream, downstream, or both) created from the medium resolution NHD lakes, streams, and rivers and subsequently derive surface water connectivity metrics for lakes and networks. Using this approach, we created a total of 898 networks that include 86,511 lakes. The NETS module includes a table with metrics for connections between lakes (both upstream and downstream), dams, network position, and whole networks. NETS also includes a flow table and bidirectional and unidirectional distance tables that provide the distances between every pair of connected lakes.

openCC0May 2017View details →

LAGOS-NE-GEO v1.05: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013

This data package, LAGOS-NE-GEO v1.05, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS: lake location and physical characteristics for all lakes. (2) LAGOS-NE-GEO: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NEGEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE-GEO v1.05 module includes information on the ecological context of the census lakes, all lakes > 4 ha in the study extent, their watersheds, and their regions. The information provided in the data tables for this module is organized into three main themes: CHAG - climate, hydrology, atmospheric deposition of nitrogen and sulfur, and surficial geology; LULC - land use/cover, impervious co

openCC0Jan 2023View details →

ESM01 Fire and grazing modulate the structure and resistance of plant-floral visitor networks in a tallgrass prairie

Data from the study: Welti, E.A.R. and Joern, A. 2017. Fire and Grazing modulate the structure and resistance of plant-floral visitor networks in a tallgrass prairie. Oecologia 186: 447-458. EMS011 dataset contains counts of blooming inflorescences of plant species on 12 Konza watersheds in June-July of 2014; ESM012 dataset contains associations between flower-visiting insects and insect-pollinated flowering plants on 12 Konza watersheds collected in May-July of 2014; ESM013 dataset describes insects belonging to the orders of Coleoptera, Diptera, Lepidoptera and Hymenoptera collected in pantrap transects on 12 Konza watersheds collected in June - July of 2014.

OpenNeuro44/100

Multiple-object tracking as atool for parametrically modulating memory reactivation

Open the record for dataset details and reuse information.

openCC0Jan 2019View details →

opencc-by-4.0Dec 2020View details →

Nodal Modulation of Tidal Constituents in the North Sea

Harmonic analysis of sea surface elevation is commonly performed using the f-u correction procedure, which alters the analyzed tidal constituents, based on the longitude of the lunar ascending node at a 18.61 year frequency. Measurement analysis has led us to conclude, that common nodal modulation factors are inaccurate in the shallow regions of the North Sea, due to the friction-induced generation of overtides. For this reason we applied a numerical model to quantify the nodal modulation spatially. The hereby presented data set is therefore derived from model results and includes the nodal amplitude modulation and phase lag for the North Sea on a 7,500m raster as supplemental material to Hagen, et al. (2021, to appear). This data set may be used for the manual correction of nodal modulation in modeling applications, MSL analysis and any other application regarding harmonic analysis in the North Sea region.

opencc-by-4.0Dec 2014View details →

Data set to article "Rapid serial processing of natural scenes: Color modulates detection but neither recognition nor the attentional blink"

The file Data_Marxetal2014_AB.csv contains the data to the paper Marx, S., Hansen-Goos, O., Thrun, M., & Einhäuser, W. (2014). Rapid serial processing of natural scenes: Color modulates detection but neither recognition nor the attentional blink. Journal of Vision, 14(14):4, 1-18, http://www.journalofvision.org/content/14/14/4, doi:10.1167/14.14.4. as comma-separated value (csv) file Each row contains the data of one trial, represented by the following columns 1 - number of the line 2 - subject ID 3 - experiment number 4 - color condition (1: gray inverted, 2: gray original, 3: color inverted, 4: color original) 5 - number of targets 6 - SOA in ms 7 - serial position of first target (0 if absent) 8 - serial position of second target (0 if absent) 9 - category of first target (1: feline, 2: avian, 3: ungulate, 4: canine) 10 - category of second target (1: feline, 2: avian, 3: ungulate, 4: canine) 11 - response to "How many animals?" (detection) 12 - response to first category (recognition, 1: feline, 2: avian, 3: ungulate, 4: canine) 13 - response to second category (recognition, 1: feline, 2: avian, 3: ungulate, 4: canine)

opencc-by-4.0Oct 2023View details →

Multi-GeV Wakefield Acceleration in a Plasma-Modulated Plasma Accelerator

Input decks for the particle-in-cell code WarpX used in a new study to simulate the accelerator stage of a recently proposed laser-plasma accelerator scheme [Phys. Rev. Lett. 127, 184801 (2021)], dubbed the Plasma-Modulated Plasma Accelerator (P-MoPA).

opencc-by-4.0Nov 2023View details →

Data, codes for the study "Programmable access to microresonator solitons with modulational sideband heating"

This archive contains the data for figure 2/3/4, codes for simulation in figure 1 and colds for soliton addressing program in figure 3, in the paper "Programmable access to microresonator solitons with modulational sideband heating".

opencc-by-4.0Mar 2024View details →

Amino Acids Modulate Liquid-Liquid Phase Separation in vitro and in vivo by Regulating Protein-Protein Interactions

The metadata, plots and microscopy images for the manuscript "Amino Acids Modulate Liquid-Liquid Phase Separation in vitro and in vivo by Regulating Protein-Protein Interactions".