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3,172 results for “Publications”
Adirondack Public Good Events Database: Natural Resource, Environmental, Economic and Recreation Policy and Common Pool Resources for a Social-Ecological System in Adirondack Park, New York, USA, 1760-2020.
I assembled this dataset from various published sources to evaluate how the social-ecological system (SES) in Adirondack Park, New York changed through time and the interplay of public goods (Common Pool Resources, CPRs), public land rules and private land rights, and related concepts over 260 years (1760-2020). The database was the basis for a doctoral dissertation titled "Blue Lining: Assessing the Resilience of Adirondack Park, New York Using Polycentricity and Panarchy Frameworks." The goal of the dissertation was to assess patterns and changes in institutional rules, actors and arrangements before and after establishment of the public Adirondack Forest Preserve in 1885 and Adirondack Park in 1892 as those actors and rules were modified and as both internal and external events influenced the SES as it moved through different phases of the adaptive cycle through space and time (see panarchy). Using the database, I identified which organizations and events contributed to natural resource and CPR policy. The dissertation can be downloaded here: https://experts.esf.edu/esploro/outputs/99917370604826.
Throw trap and electrofishing data collected during 1996–2022 from the Everglades, Florida, United States for the publication "Contrasting invasion histories and effects of three non-native fishes observed with long-term monitoring data"
This dataset was used to analyze the effects of three non-native fishes in the Florida Everglades for a publication in the journal Biological Invasions. The dataset incorporates plot-level mean densities (# of individuals per square meter) of common aquatic animals collected during 1996–2022 from 17 sites across three regions of the Everglades: Taylor Slough, Shark River Slough, and Water Conservation Area 3A. Prey species included are nine common small fishes and three common decapod species (two crayfish species and grass shrimp). The dataset includes throw trap data on three predator taxa: African Jewelfish (Hemichromis letourneuxi), Mayan Cichlids (Mayaheros uruphthalmus), and sunfishes (Lepomis spp.). Annual indices of mean wet season electrofishing catch-per-unit-effort of Asian Swamp Eels (Monopterus albus/javanesis), Mayan Cichlids, sunfishes, and the three other large 'top predator' fishes (Amia calva, Lepisosteus platyrhincus, Micropterus salmoides) are included for plots where electrofishing was performed from 1997-2021. Hydrologic measures used in analyses and R code used to conduct analyses are also included.
SBC LTER: Land: Hydrology: Daily precipitation from Santa Barbara County Flood Control (Public Works Department)
These daily total precipitation data represent legacy data obtained by SBC LTER from the the Santa Barbara County Flood Control District for several coastal watersheds draining into the Santa Barbara Channel (California, USA). Starting in 2001, SBC also began archive high-frequency data from County stations with active data loggers which are available in other SBC data packages. These data were collected in accordance with current industry standards. The data are contained in 3 tables, for stations with active data loggers and tipping gauges, active stations with other types of gauges, and inactive stations. Only data collected with tipping gauges and data loggers can be interpolated to to the resolution required by SBC's research objectives, and so only this data table will be updated (annually, at the end of the water year).
Online supplementary data linked to the publication "Aubenas-les-Alpes (S-E France). Part III – Last and final part of the mammalian assemblage with some comments on the palaeoenvironment and palaeobiogeography" doi:10.1016/j.annpal.2019.03.001
<p>Online supplementary appendix including the list of Oligocene localities and associated faunal lists compared to Aubenas-les-Alpes, and the size estimation of the non-predatory species for the construction of Fig.10.</p>
Pre- and post-publication citations to published arXiv preprints
<p>This dataset contains citations to published preprints, both before they are published and after they are published. Details of the data are provided in the <code>README.md</code>.</p>
Raw EEG-EOG data used in the publication "Auditory Electrooculogram-based Communication System for ALS Patients in Transition from Locked-in to Complete Locked-in State"
<p>The dataset includes raw EEG and EOG recordings during BCI experiments for three patients: p11, p13, p15, and p16. The structure of the dataset is the following: patient/visit/day.</p> <p>The experiment is described in detail in the publication "Auditory Electrooculogram-based Communication System for ALS Patients in Transition from Locked-in to Complete Locked-in State". The correspondence between raw file and BCI session is reported in the attached pdf file "Supplementary Table S5 Session to Raw File Recordings Correspondence".</p> <p>The datasets include EEG and EOG channels. The data are raw (i.e. non filtered and non processed). Data have been acquired with a sampling rate of 500Hz using active electrodes and the amplifier V-Amp DC (Brain Products, Germany). EOG channels are labeled EOGU, EOGD, EOGR, EOGL namely for EOG up, down, right, left; the location in the 10-20 system are respectively SO1, IO1, LO1, LO2.</p> <p>The data are marked with triggers: for each session two markers indicate start and end of the session; for each trial markers indicate start of baseline, start of presentation of question, start of response time, start of feedback. Each trial was marked in a different way if it was a yes trial belonging to a training or feedback session, a no trial belonging to a training or feedback session, or a trial belonging to a speller session. The markers that have been used are the following:<br> <strong>start</strong> 9<br> <em> yes no speller</em><br> <strong>baseline</strong> 10 11 12<br> <strong>presentation</strong> 5 6 7<br> <strong>response</strong> 4 8 13<br> <strong>feedback</strong> 1 2 3</p> <p><strong>end</strong><strong> </strong> 15</p>
Brainport, Highway pilot, control center ADAS instructions publication
<p><strong>Scenario description</strong>:</p> <p>Hazards have been detected and populate the map. Control Center publishes ADAS instructions for some hazards.</p> <p><strong>Session description</strong>:</p> <p>Control Center published ADAS Instructions for 4 identified hazards of the track.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_AdasCommand</strong>: Data from the automated driver assistance system</p> <p>Dataset Description This dataset contains the ADAS command in the vehicle</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_Anomaly</strong>: Data sent from detecting vehicle to the service, and from service to vehicles</p> <p>Dataset Description This dataset contains information about all the detected anomalies on the road</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_AnomalyImage</strong>: Data sent from detecting vehicle to service</p> <p>Dataset Description This dataset contains images of the detected anomalies</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>Dataset Description This dataset contains e.g. throttlestatus,clutchstatus,brakestatus,brakeforce,wipersstatus,steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>Dataset Description This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>Dataset Description This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_Hazard</strong>: Data sent from service to vehicle</p> <p>Dataset Description This dataset contains specific information for a vehicle about anomalies and hazards</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Dataset Description Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>Dataset Description This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>Dataset Description This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_HighwayPilot_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>Dataset Description This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Insights into European research funders policies and practices - public dataset
<p>This is the dataset arising from a survey of European research funders on Open Access (OA) and Research Data (RD) policies, commissioned by SPARC Europe, in consultation with representatives from the following organisations: <a href="https://www.allea.org/">ALLEA</a>, the <a href="https://www.efc.be/">European Foundation Centre</a> and <a href="http://scienceeurope.org/">Science Europe</a> and a wider advisory group.</p> <p>Launched in the spring of 2019, the survey, which targeted about 400 funders, garnered just over 60 responses from 29 countries. The cohort includes important national funding agencies (almost 50%), pan-European funders, national and regional academies, foundations and philanthropic organisations and research charities. </p>
Datasets and images of publication: Additive manufacturing for self-healing soft robots
<p>This entry contains the images and data used for the publication: Additive manufacturing for self-healing soft robots (DOI: 10.1089/soro.2019.0081). The datasets are named after the image they refer to and are available under the CC-BYSA 4.0 International license.</p>
Dataset related to the publication "Electromagnetic Amplification of Microwave Phonons in Nonlinear Resonant Microcavities", DOI: 10.1109/TMTT.2018.2855176
<p>This folder contains the raw data from which the graphs in paper "Electromagnetic Amplification of Microwave Phonons in Nonlinear Resonant Microcavities", DOI: 10.1109/TMTT.2018.2855176, have been obtained.</p>
Dataset related to the publication "Transformation Optics: Large Multiphysics Simulation of Nonlinear Optomechanical Coupling in Microstructured Resonant Cavities", DOI: 10.1109/MMM.2018.2821086
<p>This folder contains the raw data from which the graphs in paper "Transformation Optics: Large Multiphysics Simulation of Nonlinear Optomechanical Coupling in Microstructured Resonant Cavities", DOI: 10.1109/MMM.2018.2821086, have been obtained.</p>
Figure 7 in Fifty years of devotion to spiders: a concise biography of Christo Deltshev, with a complete list of his publications and described taxa
Figure 7. Christo Deltshev at his first International Arachnological Congress in Brno, Czechoslovakia, August, 1971 (congress photo).
Figure 5 in Fifty years of devotion to spiders: a concise biography of Christo Deltshev, with a complete list of his publications and described taxa
Figure 5. Christo, Peter van Helsdingen and Konrad Thaler in Szombathely, Hungary, July, 2002 (photo Stoyan Lazarov).
Datasets from Approximate equality of character strings and its application to record linkage in metadata of scientific publications thesis
<p>The datasets were produced in my thesis project. The thesis (in Czech language) explores the application of approximate string matching in scientific publication record linkage process. An introduction to record matching along with five commonly used metrics for string distance (Levenshtein, Jaro, Jaro-Winkler, Cosine distances and Jaccard coefficient) are provided. These metrics are applied on publication metadata from V3S current research information system of the Czech Technical University in Prague. Based on the findings, optimal thresholds in the F1, F2 and F3-measures are determined for each metric.</p> <p>Thesis citation:<br> DOBIÁŠOVSKÝ, Jan. <em>Approximate equality of character strings and its application to record linkage in metadata of scientific publications</em> [online]. Praha, 2020 [cit. 2020-05-04]. Masters thesis. Charles University. Faculty of Arts. Institute of Information Studies and Librarianship.</p> <p> </p>
Standard Distributions of Blood Tests for Public Use
<p>This dataset is the distribution parameters obtained by approximating the distribution of blood test values taken from inpatients in a Japanese hospital by a lognormal distribution or an exponential distribution. </p> <p>The parameters P1, P2 and P3 of the lognormal distribution are used in the following equation.<br> P1*exp(-(ln(x/P2)/P3)^2)</p> <p>The parameters P1 and P2 of the exponential distribution are used in the following.<br> P1*exp(-P2*x)</p> <p>This file is CSV with UTF-8 charset, and the columns are as follows.</p> <p>---<br> Test name<br> Test name in Japanese<br> Unit of the value<br> Distribution type (LogNormal or Exp)<br> P1<br> P2<br> P3<br> P1 Error(1sigma)<br> P2 Error(1sigma)<br> P3 Error(1sigma)<br> Number of data points used to make this distribution<br> Bin width used to make the distribution<br> ---</p> <p>Any researchers can use this dataset without privacy issues.<br> CC BY-NC 4.0<br> </p>
Dataset for publication: Validation of large-volume batch solar reactors for the treatment of rainwater in field trials in sub-Saharan Africa, Reyneke et al. (2020). DOI: 10.1016/j.scitotenv.2020.137223
<p>Datasets, Supplementary Information and Water Safety Plan (Assessment Form and Risk Matrix) for the publication: "Validation of large-volume batch solar reactors for the treatment of rainwater in field trials in sub-Saharan Africa" which was published in Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2020.137223).</p>
Factors affecting altmetrics attention to scholarly publication in peer-reviewed journals published in Iran and Turkey
<p>The goal of this study was to trace the altmetric measures of peer-reviewed journals in two non-English speaking countries na,ely Iran and Turkey, in order to understand their correlation with some website structure and design determinants, as well as the subject and the full-text language of the journals.</p> <p> </p>
Data, materials, methods and codes for publication Reis et al., "Understanding the stickiness of commodity supply chains is key to improving their sustainability", 2020, One Earth.
<p>Explanation of the data and code used for the article: "Understanding the stickiness of commodity supply chains is key to improving their sustainability", 2020, One Earth.</p> <p> The file: "StickinessAnalysisCompleteGeneric_CleanUpdate18-5-2020.R" is the R code/ script containing all the data preparation and the stickiness analysis.</p> <p>The file: "BRAZIL_SOY_V2.3_WITH_DOMESTIC_TRADERS.csv" contains the raw data of Brazil's soy exports and domestic consumption from trase.earth. This dataset can also be obtained from trase.earth in the latest version.</p> <p>The file: "NodesCiS.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: A. logistics hubs supplying traders, and D. traders supplying countries. They are put together in the same table because they are all "sending" relationships.</p> <p>The file: "NodesCiR.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: C. traders sourcing from logistics hubs, and E. countries sourcing from traders. They are put together in the same table because they are all "receiving" relationships.</p> <p>The file "NodesCiSMunCountry.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: B. logistics hubs supplying countries (directly not passing through traders). This is separate in another table because it is a direct sending relationship from LHs to countries.</p> <p>The file "NodesCiRMunCountry.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: F. countries sourcing from logistics hubs (directly not passing through traders). This is separate in another table because it is a direct receiving relationship from LHs to countries.</p> <p>The file: "NodesWPiS.csv" is a table with the WPi (stickiness on flows) measured for the types of supply chain relationships: A. logistics hubs supplying traders, and D. traders supplying countries. They are put together in the same table because they are all "sending" relationships.</p> <p>The file: "NodesWPiR.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: C. traders sourcing from logistics hubs, and E. countries sourcing from traders. They are put together in the same table because they are all "receiving" relationships.</p> <p>The file "NodesWPiSMunCountry.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: B. logistics hubs supplying countries (directly not passing through traders). This is separate in another table because it is a direct sending relationship from LHs to countries.</p> <p>The file "NodesWPiRMunCountry.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: F. countries sourcing from logistics hubs (directly not passing through traders). This is separate in another table because it is a direct receiving relationship from LHs to countries.</p>
Approach of concepts of public opinion, communication and information
<p>The general accepted definition of public opinion is that it can describe the attitudes held by a significant number of people on matters of government and politics, thus public opinion plays an important role in the political sphere.</p> <p>https://www.youtube.com/watch?v=nk7zXuuuuNQ&feature=youtu.be </p>
Emotion and Diversity in Online Publics - Supporting Materials
<p>Supporting materials for the article "Counterpublic, Deliberative Sphere, Incubator, Battleground: Emotion and Diversity in Online Publics".</p> <p>"</p>
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.