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2,288 results for “Periodical”
Dataset of land uses for the period 1961-2014 (Peyne watershed)
<p>The study area corresponds to the Peyne watershed, which covers approximately 76 km2 and is located in Languedoc-Roussillon in southern France (43° 35′N, 3° 19′E). The smaller enclosed watershed is called the Bourdic subwatershed and covers 7 km2. The area of the Peyne watershed is mostly covered by perennial crops (mainly vineyards), and five towns are present in the zone. In 2012, the IGN released a large, open-access database of aerial black-and-white photographs from 1937 until the present. We selected a sample of images from the IGN database covering the Peyne watershed from 1962 to 2003 with a time interval between 4 and 5 years. We completed the series by taking orthophotos from 2005 to 2012 processed by the IGN from colour photographs. The aerial photographs were orthorectified using structure-from-motion approach and corrected from vignetting effects to get orthophotos defined at pixel resolution of less than 1 m. The satellite images were also sampled at the same resolution. The raster database was then transformed into polygons with a minimal area of approximately 200 m2 using manual digitizing and classification procedures to separate field entities and their associated land use categories using QGIS software. Land uses of each homogeneous polygon were classified according to the Corine Land Cover nomenclature expanded to the fourth level of detail for vineyards to distinguish goblet vines from trellised vines, with a special case noted for undefined vines when the difference in land management was difficult to detect. The distinction between goblet and trellised vineyards was based on the presence of a clear row orientation in the pictures.</p>
study of second harmonic generation in periodically poled fiber in double pass configuration
<p>This dataset includes the experimental measurements and the numerical simulations of the power of second harmonic generated inside a periodically poled fiber traversed in single and double pass by a fundamental signal whose wavelength is included in a certain range of values. This measurements are the preliminary study for situation where the PPSF can be exploited in multiple pass configuration, such as in a cavity. </p>
Data set and scripts - Influence of Festive Periods on Road Safety: Multidimensional Analysis (Road Accidents in Colombia 2017-2021)
<p>This dataset comprises historical information about road accidents in Colombia from 2017 to 2021, titled 'Road Accidents 2017-2021', containing 18,600 records of accident events on roads managed by the National Roads Institute (INVÍAS, 2021). The dataset includes 41 descriptors and was last updated on July 15, 2022. It has been published under the Open Data initiative (Law 1712 of 2014 on Transparency and Access to National Public Information).</p> <p>In addition to accident information, the dataset integrates a database with holiday dates and road identifiers, ensuring data coherence and quality for data analysis purposes. Statistical analysis is conducted through exploratory data analysis focusing on the years 2017 to 2021, utilizing Python (version 3.10) within the Jupyter Notebooks execution environment and specialized libraries (Pandas, NumPy, Matplotlib, and Seaborn), due to their ease of application for this dataset. After data normalization, the dataset comprises 18,554 records, with 46 excluded due to inconsistent data formats.</p>
Growth of Heracleum sosnowskyi Manden. plant in indoor conditions after end of vegetation period
<p>Growth of<em> Heracleum sosnowskyi</em> Manden. plant in indoor conditions after end of vegetation period. The period of observation of plant growth from October 2017 to February 2018. The series of images.</p>
Raw data for "Sparse periodicity-based auditory features explain human performance in a spatial multi-talker auditory scene analysis task"
<p>Raw data for the simulation study " Sparse periodicity-based auditory features explain human performance in a spatial multi-talker auditory scene analysis task" [1].</p> <p>[1] Josupeit, A., Schoenmaker, E., van de Par, S., & Hohmann, V. (2018). Sparse periodicity‐based auditory features explain human performance in a spatial multitalker auditory scene analysis task. <em>European Journal of Neuroscience</em>, https://doi.org/10.1111/ejn.13981.</p>
FADN data on the support under the CAP delimited for LAU2 (NUTS2) regions in the EU Member States for the 2007-2013 programming period
<p> </p> <p>Ready to use FADN dataset on the support under the CAP in 2007-2013 delimited for LAU2 (NUTS2) regions in the EU Member States.</p> <p>Investigation of the interaction between Cohesion and Rural Policies requires analysing comparable data. However, the CAP data are usually collected at the national level. The FADN database is the only data source for analysing the impact of agricultural policy instruments on the economic situation of farms. However, the regional breakdown of FADN data in some countries does not correspond to the NUTS2 breakdown for which cohesion policy is defined.</p> <p>The provided FADN data delimitation uses a methodology that takes into account the range of impact and features specific to a given region. Because the research shows a very strong relationship between the amount of support under the CAP and the number and size of farms on a given area, this criterion was used to delimit FADN data for particular LAU2 (NUTS2) regions, while maintaining the allocation to individual measures.</p> <p>FADN data aggregated (averaged) to the level of FADN regions and economic size classes were used. Each FADN region has been assigned a corresponding NUTS2 region (or regions) according to the classification in 2010 in which the full census of the farm structure survey was carried out. The delimitation of FADN data to NUTS2 regions was based on weights constructed on the basis of Eurostat data on utilised agricultural area and number of holdings in 2010. In each economic size class, each FADN region consisted of the sum of the NUTS2 regions weighted by the utilised agricultural area. The result of each FADN variable was the sum of its values in each economic size class, weighted by the total number of holdings in each class.</p> <p>This database has served as a basis for two articles, one validating the assumptions of the NUTS2 (LAU) delimitation of the FADN regions and the other using the database to compare synergies and trade-offs between cohesion policy and the common agricultural policy.</p>
Inundation maps of Donana for 23 dates within the period 2015/12/19 to 2017/08/20 and their accompanying INSPIRE metadata XML files
<p>Satellite-derived inundation maps offer an efficient solution for monitoring the spatial and temporal variability of the hydrological cycle of wetlands. This task is important for taking mitigation actions against factors (e.g. climate change and human pressures) threatening wetlands' functions and services.</p> <p>Inundation maps within the period 2015/12/19 to 2017/08/20 were generated for Donana based on the methodology presented in "Kordelas, G.A.; Manakos, I.; Aragonés, D.; Díaz-Delgado, R.; Bustamante, J. Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data. <em>Remote Sens.</em> <strong>2018</strong>, <em>10</em>, 910.".</p> <p>Each inundation map is named as " 'Date'_inundation_map_Donana_S2.tif ", and contains the following classes: Inundated Class, Non-inundated Class. In this map, Inundated and Non-inundated Classes are denoted with 0 and 1, respectively. 'Date' is in the form YYYY_MM_DD.</p>
Inundation maps of Danube Delta for 10 dates within the period 2016/10/05 to 2017/08/01 and their accompanying INSPIRE metadata XML files
<p>Satellite-derived inundation maps offer an efficient solution for monitoring the spatial and temporal variability of the hydrological cycle of wetlands. This task is important for taking mitigation actions against factors (e.g. climate change and human pressures) threatening wetlands' functions and services.</p> <p>Inundation maps within the period 2016/10/05 to 2017/08/01 were generated for Danube Delta based on the methodology presented in "Kordelas, G.A.; Manakos, I.; Aragonés, D.; Díaz-Delgado, R.; Bustamante, J. Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data. <em>Remote Sens.</em> <strong>2018</strong>, <em>10</em>, 910.".</p> <p>Each inundation map is named as " 'Date'_inundation_map_Danube_Delta_S2.tif ", and contains the following classes: Inundated Class, Non-inundated Class. In this map, Inundated and Non-inundated Classes are denoted with 0 and 1, respectively. The regions, which are manually denoted as affected by clouds, are denoted with 2. 'Date' is in the form YYYY_MM_DD.</p>
Inundation maps of Camargue for 47 dates within the period 2016/02/09 to 2018/06/19 and their accompanying INSPIRE metadata XML files
<p>Satellite-derived inundation maps offer an efficient solution for monitoring the spatial and temporal variability of the hydrological cycle of wetlands. This task is important for taking mitigation actions against factors (e.g. climate change and human pressures) threatening wetlands' functions and services.</p> <p>Inundation maps within the period 2016/02/09 to 2018/06/19 were generated for Camargue based on the methodology presented in "Kordelas, G.A.; Manakos, I.; Aragonés, D.; Díaz-Delgado, R.; Bustamante, J. Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data. <em>Remote Sens.</em> <strong>2018</strong>, <em>10</em>, 910.".</p> <p>Each inundation map is named as " 'Date'_inundation_map_Camargue_S2.tif ", and contains the following classes: Inundated Class, Non-inundated Class. In this map, Inundated and Non-inundated Classes are denoted with 0 and 1, respectively. 'Date' is in the form YYYY_MM_DD.</p>
Bergtold, 1917: Incubation Periods of Birds
Bergtold, William Harry. A Study of the Incubation Periods of Birds; What Determines Their Lengths,. Denver, Col.: Kendrick-Bellamy, 1917.<p></p>Bergtold, William Harry. A Study of the Incubation Periods of Birds; What Determines Their Lengths,. Denver, Col.: Kendrick-Bellamy, 1917.
5405 MHz SigMF baseband recording of RCM-2 (Radarsat Constellation) using PlutoPlus SDR and four log periodic array (LPA) antennas
<p>This dataset contains a recording of the <a href="https://www.asc-csa.gc.ca/eng/satellites/radarsat/technical-features/radarsat-comparison.asp">RCM-2</a> (<a href="https://en.wikipedia.org/wiki/RADARSAT_Constellation">Radarsat Constellation</a>) satellite as it passed over Berkeley, California. The recording was made on 2024-08-13 and is about 15 seconds long, containing acquisition of signal pulses and loss of signal at the tail end of the recording. The dataset is stored in SigMF format. The data files are compressed with xz to reduce their size. The IQ sample rate is 20.0 Msps and the center frequency is 5405 MHz.</p> <p>The linear antenna array used to record contained four HT5 antennas, labeled as: "HT5 antenna UWB log-periodic antenna 1300MHz-10GHz". These four antennas were spaced 21 cm apart. The input from these four antennas was combined with a SP-TX-4B splitter/combiner using equal lengths of LMR400 coax, then amplified using an LNA labeled as "RF AMP 04A: TQP3M9037 0.1-6GHz". The LNA was powered via a +5 volt bias-tee. A "Pluto+" or Pluto Plus SDR was used to sample, with SatDump software. </p> <p> </p>
Cortisol in fish scales remains stable during extended periods of storage.
<p>Dataset to accompany the manuscript: <a href="https://doi.org/10.1093/conphys/coae065">https://doi.org/10.1093/conphys/coae065</a></p> <p>The dataset contains two data files describing cortisol concentrations in the scales of adult salmon and a "Read Me" file that explains the data structure and source. </p>
Data supporting "Burn Period: A use-inspired metric to track wildfire risk across the southwest U.S."
<p>Comma delimited data file of derived daily meteorological metrics from hourly, gap filled and quality controlled Remote Automated Weather Station (RAWS) data for Arizona and New Mexico (southwest U.S.) provided by the Climate, Ecosystems, and Fire Applications (CEFA) program at the Desert Research Institute (Brown, 2022, unpublished data). Data file contains daily average dewpoint temperature, air temperature, maximum Hot-Dry-Windy Index, maximum Fosberg Fire Weather Index, maximum vapor pressure deficit, and total number of hours/day with relative humidity below 20% for 124 RAWS from 2000-2022.</p>
Cryogenically Cooled Periodically Poled Lithium Niobate Wafer Stacks for Multi-Cycle Terahertz Pulses
<p>Dataset used for the figures in the paper: "Cryogenically Cooled Periodically Poled Lithium Niobate Wafer Stacks for Multi-Cycle Terahertz Pulses" by Dalton et al. Accepted for publication in Applied Physics Letters on the 6th September 2024.</p>
CD5 index of works published in the period 1945-2018
<p>The xz-compressed data file (2.7 GiB uncompressed) contains 44,008,797 records comprising two fields separated by a "|" character:</p> <ol> <li>Publication DOI</li> <li>Five-year consolidation / disruption (CD₅) index (when available)</li> </ol> <p>The data set was derived from the <a href="https://www.crossref.org/blog/2024-public-data-file-now-available-featuring-new-experimental-formats/">Crossref 2024 public data file</a> using <a href="https://github.com/dspinellis/alexandria3k">Alexandria3k</a> and <a href="https://github.com/dspinellis/fast-cdindex">fast-cdindex</a>. More information about the process can be found in the following papers.</p> <ul> <li>Diomidis Spinellis. Open reproducible scientometric research with Alexandria3k. <em>PLoS ONE</em>, 18(11):e0294946, November 2023. <a href="https://dx.doi.org/10.1371/journal.pone.0294946">doi:10.1371/journal.pone.0294946</a></li> <li>Diomidis Spinellis. Efficient graph processing. <em>IEEE Software</em>, 42(1):22–25, January 2025. <a href="https://dx.doi.org/10.1109/ms.2024.3477013">doi:10.1109/ms.2024.3477013</a></li> </ul> <p>In common with the latest revision of the previously released 1945–2016 data set, this one incorporates into the calculation works lacking a reference list, but not calculating a CD₅ index for them. It also excludes works published after 2018, as they lack five years of citations to them.</p>
Van Dijk et al. (2021), A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050, data and scripts
<p>This repository contains all data and R scripts to reproduce the figures in Van Dijk et al. (2021), A meta-analysis of global food demand and population at risk of hunger projections for the period 2010-2050, Nature Food. More specifically, it includes two databases: (1) A database with standardized information to describe the characteristics of 57 studies that were identified by the systematic literature review and (2) The Global Food Security Projections Database v1.0.1 with harmonized projections for three global food security indicators: food consumption in kcal per capita and total kcal, and population at risk of hunger. The database also includes projections for total global population that are required to derive the global food security indicators.</p> <p>The two scripts (nf_figures.r and nf_meta_regression.r) can be used to reproduce the figures and tables in the main paper and the supplementary information. Please start with the first script, which sources the second script. </p> <p>This is the first version of the Global Food Projections Database. We expect to update the data, including additional studies and variables in the future. For issues and suggestions, please contact michiel.vandijk@wur.nl.</p> <p> </p>
The 4.2 ka event and the end of the Maltese 'Temple Period'
<p>These data are intended to facilitate replication efforts for a study described in a paper titled "The 4.2 ka event and the end of the Maltese ‘Temple Period’". The files herein reflect the data at the submission stage---i.e., the initial version of the associated paper has been or shortly will be submitted to a peer-reviewed journal. Most of the files are R bigmatrix files and R::bigmemory (https://cran.r-project.org/web/packages/bigmemory) will be required to make use of them. The R scripts needed to reproduce these files and analyze them further following the methods in the associated paper can be found at https://github.com/wccarleton/malta42.</p>
Meteorological data from the experimental period of the submersion test of photovoltaic cables
<p>Meteorological data recorded by the onsite weather station (coordinates: 38°31'50.0"N 8°00'40.3"W) regarding the study of submersion of photovoltaic cables (with two different insulation materials) in freshwater and artificial seawater. The metereological data is logged with 1minute time resolution for the period from 16/10/2020 to 25/01/2021.</p> <p>The meteorological station is composed by:</p> <p>Kipp and Zonen Solys2 Sun tracker</p> <p>Kipp and Zonen CMP6 Pyranometer (horizontal global solar radiation, data units W/m2)</p> <p>RH and Air temperature sensor (air relative humidity, data units % and ambient air temperature, data units ºC)</p> <p>Rain Gauge (precipitation, data units mm)</p>
Reconstitution of August SPEI3 drought index based on the δ18O in tree-ring cellulose for the Eastern Carpathian, for the period 1331-2012CE
<p>Here we report the reconstruction of the summer (June to August) Standardized Precipitation-Evapotranspiration Index (SPEI3), for the period 1331-2012CE, for eastern Europe, based on annually-resolved stable oxygen isotope ratios (δ<sup>18</sup>O) from Pinus cembra L. tree-ring cellulose from the Călimani Mountains, Romania. Variations of the δ18O values capture the August SPEI3 changes both at high and low frequencies (from interannual to multidecadal scales).<br> <br> The palaeoclimate potential of stable isotopes in Pinus cembra L. (Swiss stone pine) tree-ring cellulose from the Călimani Mountains has been demonstrated by Nagavciuc et al. 2019 (DOI: 10.1002/joc.6349), showing that δ18O variability allows high-resolution paleoclimatic reconstructions over the eastern part of Europe, where few such reconstructions are available.</p>
Database of Planar and Three-Dimensional Periodic Orbits and Families Near the Moon
<p>The lunarPOdatabase.zip is the digital database accompanying the paper:<br> <br> C. Franz and R. P. Russell, “Database of planar and three-dimensional periodic orbits and families near the Moon,” The Journal of the Astronautical Sciences, DOI 10.1007/s40295-022-00361-9 (accepted Nov. 2022).</p> <p>Please see the paper for details, and cite the paper as appropriate. The database is accessible and permanently archived with the following DOI <a href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.6411980&data=05%7C01%7C%7C1770e232817c4c99fc1b08dad0a0e3ad%7C31d7e2a5bdd8414e9e97bea998ebdfe1%7C0%7C0%7C638051686701542157%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Spb%2FFj5YL8QKaBoojr09MCCIdloAkzLiGKHoUo3uVGE%3D&reserved=0">https://doi.org/10.5281/zenodo.6411980</a>. See accompanying license.txt and gpl-3.0.txt for license information, applying to all files included in the .zip distribution.</p> <p>The database contains over 13 million planar and three-dimensional solutions in the Earth-Moon circular restricted three body problem, grouped into 34,000 family and sub-family clusters. The database exists as human readable text files with periodic orbits organized by clusters and other dynamical characteristics. The database contains the clustered data, a README file describing the output format, an interactive GUI, and a simple MATLAB script as a basic interface with the database. The data are split into five files, one for each of the planar prograde, planar retrograde, axial prograde, axial retrograde, and x-z cases. The results (i.e. initial conditions and relevant dynamical parameters of each converged periodic orbit) are contained in a human-readable text file where each row is a new solution. The data are sorted by cluster and ordered inside the cluster to form a smooth curve. Summary files are included for both the grid search and the clustering for each run. The input parameters to the grid search software are also included with each case for reproducibility. File sizes range from approximately 1.1GB to 2.6GB, with a total uncompressed file size of 5.4GB and a total compressed file size of 1.2GB.</p> <p>It is emphasized that the GUI and other MATLAB interface files are only a preliminary capability to ease interaction with the database. They may not be stable under future releases of MATLAB. On the initial use of the GUI, we recommend to restrict the data to a single value of N (say N=1 or N=16), otherwise the number of solutions may overwhelm the system memory. If a user has difficulties using the GUI, the user is encouraged to use the MATLAB code interfaces or interface with the text files directly. The text files containing the database are the primary product provided here, with the GUI and test scripts provided as a courtesy to help ease the database's use.</p> <p>Please send questions to <a href="mailto:cfranz21@gmail.com">cfranz21@gmail.com</a> and/or <a href="mailto:ryan.russell@utexas.edu">ryan.russell@utexas.edu</a>.</p>
ScienceDex guides
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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.