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.
1,457
datasets available to search
ShareScore release 0.9.0
Dataset results
1,457 results for “feedback”
Source code and data for aerosol emission and indirect feedback paper
<p>A physics suite under development at NOAA’s Global System Laboratory (GSL) includes the aerosol-aware double moment Thompson-Eidhammer microphysics scheme (TH-E MP). This microphysics scheme uses two aerosol variables (water friendly (WFA) and ice friendly (IFA) aerosol number concentrations) to include interaction with some of the physical processes. In the original implementation, WFA and IFA depend on emissions derived from climatologies. In our approach, using the Common Community Physics Package (CCPP), we embedded sea-salt, dust, and biomass burning emission modules as well as anthropogenic aerosol emissions into the Unified Forecast System (UFS) to provide realistic aerosol emissions for these two variables. This represents a very simple approach with no additional tracer variables and therefore very limited additional computing cost. We then evaluate a comparison of simulations using the original TH-E MP approach, which derives the two aerosol variables using empirical emission formulas from climatologies (CTL) and simulations that use the online emissions (EXP). Aerosol Optical Depth (AOD) is derived from the 2 variables and appears quite realistic in the runs with online emissions when compared to analyzed fields. We find less resolved precipitation over Europe and North America from the EXP run, which represents an improvement compared to observations. Also interesting are moderately increased aerosol concentrations over Southern Ocean from the EXP run invigorating the development of cloud water and enhances the resolved precipitation in those areas. This study shows that a more realistic representation of aerosol emission may be useful when using double moment microphysics schemes.</p>
Data from: Visual feedback influences the consistency of the locomotor pattern in Asian Elephants (Elephas maximus)
<p><span>Elephants are atypical of most quadrupeds in that they maintain the same lateral sequence footfall pattern across all locomotor speeds. It has been speculated that the preservation of the footfall patterns is necessary to maintain a statically stable support polygon. This should be a particularly important constraint in large, relatively slow animals. This suggests that elephants must rely on available sensory feedback mechanisms to actively control their massive pillar-like limbs for proper foot placement and sequencing. How the nervous system of elephants integrates the available sensory information for a stable gait is unknown. Here we explored the role that visual feedback plays in the control of the locomotor pattern in elephants. Four Asian elephants (</span><span><em>Elephas maximus</em>)</span><span> walked with and without a blindfold as we measured their stride time intervals. Coefficient of variation was used to assess changes in the overall variability of the stride time intervals, while approximate entropy was used to measure the stride-to-stride consistency of the time intervals. We show that visual feedback plays a role in the stride-to-stride consistency of the locomotor pattern in elephants. These results demonstrate that elephants likely use visual feedback to correct and maintain proper sequencing of the limbs during locomotion. </span></p>
Data and code for "Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak"
<p>This repository contains all scripts and data files to reproduce the analysis of the manuscript "Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak"</p> <p><strong>Abstract</strong></p> <p>Competitive hierarchies in diverse ecological communities have long been thought to lead to instability and prevent coexistence. However, system stability has never been tested and the relation between hierarchy and instability has never been explained in complex competition networks parameterised with data from direct observation. Here we test model stability of 30 multispecies bryozoan assemblages, using estimates of energy loss from observed interference competition to parameterise both the inter- and intraspecific interactions in the competition networks. We find that all competition networks are unstable. However, instability is mitigated considerably by asymmetries in the energy loss rates brought about by hierarchies of strong and weak competitors. This asymmetric organisation results in asymmetries in the interaction strengths, which reduces instability by keeping the weight of short (positive) and longer (positive and negative) feedback loops low. Our results support the idea that interference competition leads to instability and exclusion but demonstrate that this is not because of, but despite, competitive hierarchy.</p> <p><strong>Data</strong></p> <p>Our data set contains records of overgrowth competition in 30 high-latitude bryozoan assemblages. Rocks were collected by hand from shallow subtidal coastal locations at Rothera Island, West Antarctic Peninsula, Signy Island in the maritime Antarctic and Spitsbergen in the Arctic. For each assemblage, the data set contains one .csv file with abundance per species and one .csv file containing the species-contact-matrix. All bryozoans were identified to species and counted, giving abundance data in colonies per species. Then, all pairwise contests between colonies were classified as win, draw or loss and the results were compiled in the species-contact-matrices. For details, see the methods section of the paper.</p> <p><strong>Analysis </strong></p> <p>The analysis is subdivided into the following sections:</p> <ul> <li>0 <strong>Random matrices</strong>: Stability of random matrices with symmetric and asymmetric interactions.</li> <li>1 <strong>Preparation</strong>: Define functions to calculate asymmetry measures and set plotting parameters</li> <li>2 <strong>Read and process raw data</strong>: Converts raw data to Jacobian matrices</li> <li>3 <strong>Analysis of empirical matrices</strong>: Calculates stability, asymmetry measures, loop weights of empirical matrices.</li> <li>4 <strong>Analysis of randomised matrices:</strong> Randomises empirical matrices and analyses the effect on stability, asymmetry measures and loop weights.</li> <li>5<strong> Sensitivity</strong>: Effect of model assumptions (cost-values / replacement of missing values) on the results.</li> </ul> <p>Details on how to reproduce the full analysis, including all figures and tables in the manuscript can be found in the ReadMe file.</p>
On the importance of additional behavioral observation in behavioral psychopharmacology research: a case study on agomelatine's effects on feedback sensitivity in probabilistic reversal learning test in rats (data&code)
<p>Dataset to the manuscript entitled: On the importance of additional behavioral observation in behavioral psychopharmacology research: a case study on agomelatine's effects on feedback sensitivity in probabilistic reversal learning test in rats. Code in R used for analysis data from probabilistic reversal learning (PRL) test performed in operant conditioning boxes. Script analyzes data files from MED-PC IV software.</p>
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
<p>QA-Feedback used in the paper: Fine-Grained Human Feedback Gives Better Rewards for Language Model Training</p>
Data for "Multiple Equilibria and Soil Moisture-Precipitation Feedbacks in Idealized Convection-Permitting Simulations with an Open Hydrological Cycle"
<p>Code, simulation input files, and simulation output data supporting “Multiple Equilibria and Soil Moisture-Precipitation Feedbacks in Idealized Convection-Permitting Simulations with an Open Hydrological Cycle”, under review at JAMES. Enclosed README files provide detailed descriptions of the archive contents.</p>
Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners
<p>This data represents four artifacts from our research in studying how software organizations manage user feedback, particularly social media feedback, to help improve existing products. It includes our interview questions, information about the study participants, the codebook with example quotes, and table with the code to concept generation.</p> <p>This page includes supplementary materials associated with our paper entitled "Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners".</p>
Data from: Mycorrhizal driven feedbacks and forest resilience to reduced rainfall
<p>Forests can experience negative feedbacks in the growth of tree populations but positive feedbacks within the two dominant mycorrhizal types of trees: ectomycorrhizal (EM) and arbuscular mycorrhizal (AM). Positive feedbacks within mycorrhizal types may provide communities with resistance to climate change. We tested whether each mycorrhizal type led to positive feedbacks on seedling survival, while statistically controlling for the effect of congeneric trees in ambient versus rainfall reduced conditions. We explored two potential drivers; the variation in soil fungal community structure and soil chemistry. Seedlings benefited from growing in stands dominated by their own mycorrhizal type, and simultaneously, tree seedlings performed worse in the presence of adult trees of their own genus, but only in rainfall reduced conditions. We found that the composition of the EM fungal community differed between plots dominated by EM versus AM trees. These results indicated that mycorrhizal types may create positive feedbacks in dry conditions that should be considered when predicting future states.</p>
Data from: Active-feedback quantum control of an integrated, low-frequency mechanical resonator
<p>Source data for Figures.</p>
Accompanying data for: Local negative feedback of Rac activity at the leading edge underlies a pilot pseudopod-like program for amoeboid cell guidance
<p>This is the data underlying all of the figures in: Local negative feedback of Rac activity at the leading edge underlies a pilot pseudopod-like program for amoeboid cell guidance by Jason P. Town and Orion D. Weiner</p> <p>Paper Abstract: To migrate efficiently, neutrophils must polarize their cytoskeletal regulators along a single axis of motion. This polarization process is thought to be mediated through local positive feedback that amplifies leading edge signals and global negative feedback that enables sites of positive feedback to compete for dominance. Though this two-component model efficiently establishes cell polarity, it has potential limitations, including a tendency to “lock” onto a particular direction, limiting the ability of cells to reorient. We use spatially-defined optogenetic control of a leading edge organizer (PI3K) to probe how neutrophil-like HL-60 cells balance “decisiveness” needed to polarize in a single direction with the flexibility needed to respond to new cues. Underlying this balancing act is a local Rac inhibition process that destabilizes the leading edge to promote exploration. We show that this local inhibition enables cells to process input signal dynamics, linking front stability and orientation to local temporal increases in input signals. </p> <p>All data can be processed using standard scientific python packages using the Jupyter Notebooks located <a href="https://zenodo.org/badge/latestdoi/672328942">here</a>. To run the notebooks and reproduce the figures in the paper, download all of the zipped data files, unzip them, and arrange them into the following directory structure:</p> <ul> <li>projectfolder <ul> <li>data <ul> <li>fig03data</li> <li>fig04data</li> <li>fig05data</li> <li>figS01data</li> <li>figS08data</li> <li>figS10data</li> <li>simpleStimdata</li> </ul> </li> <li>figure01.ipynb</li> <li>figure02.ipynb</li> <li>...</li> </ul> </li> </ul> <p>Microscopy data was collected using an automated, Pycromanager-based pipeline. The most recent version of the pipeline can be found <a href="https://zenodo.org/badge/latestdoi/583790048">here</a>. </p> <p>This zipped folders contains microscopy data (images & metadata) in several directories:</p> <ul> <li>"simpleStimData" contains data used in several figures in the paper. It shows the dynamic behaviors of neutrophils as they are subjected to local optogenetic activation of optoPI3K. <ul> <li>File folders are not entirely standardized, but typically contain <ul> <li>The data of the experiment (YYMMDD format)</li> <li>The cell line used and the constructs expressed (35 is the optogenetic anchor, 52 is the optogenetic cargo, 97 is the PH-Akt-Halo PIP<sub>3</sub> reporter, and mcPak is the Pak-PBD-mCherry Rac reporter)</li> <li>A generic phrase 'Assays', 'VariousFrontStimulations', 'simpleStimScreen' that has no experimental meaning</li> <li>An indicator of the pre-programmed assay "type" - either 'none, 'front', 'side', 'back', 'global', 'lateral45', 'lateral90', '0Rad', '0.2 Rad', '0.39Rad', '0.79Rad' or '1.57Rad'</li> <li>The intensity of blue LED light used in the experiment ('50000'). This did not turn out to be very important for the paper in this particular dataset, but cells do not display an all-or-none response to optogenetic PI3K acitvation.</li> <li>And finally a replicate number for that assay that day (i.e. '000', '001', ...)</li> </ul> </li> <li>Within each file folder, there is a collection of images (Note that each image has a lot of extra information in the associated metadata) <ul> <li>Channel 0 is the PHAkt PIP<sub>3</sub> reporter fluorescence data</li> <li>Channel 1 is the Pak-PBD Rac reporter fluorescence data</li> <li>Channel 2 is a reflected blue light dataset. A small degree of blue light reflected off the bottoms of coverslips and could be collected on the camera</li> <li>Channel 3 is a binary segmentation channel generated on-the-fly during acquisition by our automated microscopy software</li> <li>Channel 4 is another binary segmentation channel, but this one is a prediction of the real image of the optogenetic stimulus based on a calibrated affine transformation of the projected image onto the microscopy field of view. </li> <li>if present, Channels 5 and 6 are control images taken at the end of the experiment to verify the presence of optogenetic constructs 35 (405 channel) and 52 (488 channel)</li> </ul> </li> <li>There is a small amount of data here that was not directly used in the paper. For example, the 'frontToGlobal' experiments did not produce interesting results, but actually led us to develop the method shown in Figure 5 in our paper where we did something closer to a 'sideToGlobal' assay (See Fig 5 in the paper). </li> </ul> </li> <li>"fig03Data" contains data used to generate Fig 3 and Fig S7B in the paper. This data is structured identically to the data in simpleStimData described above</li> <li>"fig04Data" contains data used to generate Fig 4 and Fig S9D in the paper. Some of this is from older software, so the metadata (i.e. LED intensities) are stored in a separate file called intensities.txt. This text file contains time stamps and LED intensity data that can be matched with the temporal metadata from the microscopy images. </li> <li>"fig05Data" contains data used to generate Fig 5 and Fig S11. These are structured identically to the simpleStimData structure described above. (Though these files are stored in more organized subdirectories compared to simpleStimData). </li> <li>"figS01Data" contains the microscopy data used to generate Fig S1</li> <li>"figS08Data" contains data used to generate Fig S8 in the paper. This is from older microscopy automation software, so the metadata (i.e. LED intensities) are stored in a separate file called metadata.txt. This text file contains time stamps and LED intensity changes that can be matched with the temporal metadata from the microscopy images. </li> <li>"figS10Data" contains data used to generate Fig S10 in the paper. This is a combination of data structures similar to that described above in "fig04Data" for the step inputs and "simpleStimData" for the turning assays.</li> </ul> <p> </p> <p> </p>
Data collected from questionnaires to collect feedback on the services' performance / accelerator programme and outcomes
<p>Results of the immediate satisfaction surveys deployed to: <br> (i) all participants of the syncronous induction training [Tab: 2.InductionTrainingSync]; <br> (ii) all participants of the asyncrhous induction training - [Tab: 3.InductionTrainingAsync]; <br> (iii) makerpsace admins, consultants,mentors that participated in the delivery of the entire PMCA programme [Tab: 4.PCMA - Admins] and <br> (iv) to maker teams that succesfully finished the Mentoring stage of the PCMA programme [Tab: 5.PCMA - Makers] with a view to capture their impressions of programme and recommendations for further improvements. </p> <p>The present spreadsheet is also accompanied by four (4) documents (.pdf) that present the surveys deployed for collecting the above responses. In particular: <br> 1.InductionTrainingAsyncSatisfactionSurvey_Questions.pdf<br> 2.InductionTrainingSyncSatisfactionSurvey_Questions.pdf<br> 3.PCMASatisfactionSurveyMakerpace_Questions.pdf<br> 4.PCMASatisfactionSurveyMakers_Questions.pdf</p>
Additional data supporting "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benefits."
<p>Additional data for study "Chemistry-albedo feedbacks offset up to a third of forestation’s CO2 removal benefits". UKESM data is prefixed with "UKESM_" and CESM data starts with "CAM-Chem_". Please see READMEs for additional details on the UKESM and CESM data.</p> <p> </p> <p> </p>
Contrasting carbon dioxide removal potential and nutrient feedbacks of simulated ocean alkalinity enhancement and macroalgae afforestation
<p>PISCES model outputs supporting the associated publication.</p> <p>Files are for the following simulations: historical control (CTL), OAE without nutrient addition (OAE), OAE with nutrient addition (OAE_Fe_Si), macroalgae afforestation without nutrient feedbacks (MACRO) and macroalgae afforestation with nutrient feedbacks (MACRO_N_P). The following outputs are provided at monthly resolution: air-sea carbon flux (Cflx), export flux at 100m (EPC100) and depth integrated net primary production of phytoplankton (INTPP). In addition masks of the regions of OAE (mask_OAE) and macroalgae afforestation (mask_MACRO) are provided. All files have been regridded from the original eORCA025 grid to a regular 360x180 degree grid.</p>
Data from: Root-exuded benzoxazinoids can alleviate negative plant-soil feedbacks
<p><span>Plants can suppress the growth of other plants by modifying soil properties. These negative plant-soil feedbacks are often species-specific, suggesting that some plants possess resistance strategies. However, the underlying mechanisms remain largely unknown. </span><span>Here, we investigated if and how benzoxazinoids, a class of dominant secondary metabolites that are exuded into the soil by maize and other cereals, influence plant-soil feedbacks. </span><span>We find that three out of five tested crop species suppress maize (<em>Zea mays</em>) performance via negative plant-soil feedbacks relative to the mean across species. This effect is partially alleviated by the capacity of maize plants to produce benzoxazinoids. Soil complementation with purified benzoxazinoids is sufficient to restore the protective effect for benzoxazinoid-deficient mutants. Sterilization and re-inoculation experiments suggest that benzoxazinoid-mediated protection acts via changes in soil biota. Substantial variation of the protective effect between experiments and soil types illustrates that its magnitude is context-dependent. In summary, our study demonstrates that plant secondary metabolites can confer resistance to negative plant-soil feedbacks. These findings expand the functional repertoire of plant secondary metabolites and reveal a mechanism by which plants can resist negative soil feedbacks. The uncovered phenomenon may represent a promising avenue to stabilize plant performance in crop rotations in the future.</span></p>
Alpha-frequency feedback to early visual cortex orchestrates coherent naturalistic vision (Rawdata)
<p>During naturalistic vision, the brain generates coherent percepts by integrating sensory inputs scattered across the visual field. Here, we asked whether this integration process is mediated by rhythmic cortical feedback. In EEG and fMRI experiments, we experimentally manipulated integrative processing by changing the spatiotemporal coherence of naturalistic videos presented across visual hemifields. Our EEG data revealed that information about incoherent videos is coded in feedforward-related gamma activity while information about coherent videos is coded in feedback-related alpha activity, indicating that integration is indeed mediated by rhythmic activity. Our fMRI data identified scene-selective cortex and hMT as likely sources of this feedback. Analytically combining our EEG and fMRI data further revealed that feedback-related representations in the alpha band shape the earliest stages of visual processing in cortex. Together, our findings indicate that the construction of coherent visual experiences relies on cortical feedback rhythms that fully traverse the visual hierarchy.</p>
A Positive Atmospheric Feedback on the North Atlantic Warming Hole Data Availability
<p>There are three files with the data required to recreate: Figure 1, Figures 2&3, and Figure 4. Contact the corresponding author (sydney.kramer@colorado.edu) for additional information. The MATLAB files contain variables including: Sea Surface Temperature (SST), Zonal Wind (u), Meridional Wind (v), Sea Level Pressure (slp), Geopotential Height (z), Virtual Temperature (VirtualTemp), Latitude (lat), Longitude (lon), Vertical Levels (lev), and coastlines (xcoast/ycoast). These variables are provided for five different experiments, CESM control, CESM NAWH, CESM NAWH-S, ECHAM control, and ECHAM NAWH. </p>
Rehabilitation of the Upper Extremity With Enhanced Proprioceptive Feedback Following Incomplete Spinal Cord Injury
ClinicalTrials.gov study NCT00833105. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Cardiovascular Rehabilitation Early After Stroke Using Feedback-controlled Robotics-assisted Treadmill Exercise
ClinicalTrials.gov study NCT01679600. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Combined Bio- and Neuro- Feedback vs. Varenicline Use for Smoking Cessation
ClinicalTrials.gov study NCT02991781. IPD Sharing: YES. Countries: 3. Publications: 2.
Automated Real-time Feedback on CPR Study
ClinicalTrials.gov study NCT00539539. IPD Sharing: Not stated. Countries: 2. Publications: 1.
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.