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2,288 results for “periodicals”
Fig. 4 in Biomass of the chironomid larvae (Chironomidae, Diptera) in Vaya Lake (Bulgaria) during the period 2003-2007
Fig. 4. Distribution of chironomid biomass by station.
Fig. 1 in Circadian activity patterns of the Red fox (Vulpes vulpes) and the Stone marten (Martes foina) in agricultural landscape of Northwestern Bulgaria during autumn-winter period
Fig. 1. Location of the protected area "Zlatiyata" in Northwestern Bulgaria.
Fig. 1 in Biomass of the chironomid larvae (Chironomidae, Diptera) in Vaya Lake (Bulgaria) during the period 2003-2007
Fig. 1. Map of the Vaya Lake (= Bourgas Lake) with the location of the stations.
Fig. 2 in Biomass of the chironomid larvae (Chironomidae, Diptera) in Vaya Lake (Bulgaria) during the period 2003-2007
Fig. 2. Seasonal dynamics of chironomid biomass.
Fig. 5 in Biomass of the chironomid larvae (Chironomidae, Diptera) in Vaya Lake (Bulgaria) during the period 2003-2007
Fig. 5. Dendrogram of similarity by biomass of chironomids (Bray – Curtis index).
Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model
<p>This archive provides the GRISLI ice sheet model and iLOVECLIM model outputs as part of the manuscript "Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model".<br><br></p> <p>Contact: louise.abot@locean.ipsl.fr</p>
Data set for "Chiral Magnonic Crystals: Unconventional Spin-Wave Phenomena Induced by a Periodic Dzyaloshinskii-Moriya Interaction"
<p>Scripts for the micromagnetic simulations of the publication "Chiral Magnonic Crystals: Unconventional Spin-Wave Phenomena Induced by a Periodic Dzyaloshinskii-Moriya Interaction", using the OOMMF software. These codes reproduce the result of magnonic waveguides with periodic Dzyaloshinskii-Moriya interactions. A Dockerfile and a Makefile are included for the reproducibility of the results.</p> <p>The repository containing these results, together with a explanatory README document can be found in:</p> <p>https://github.com/davidcortesortuno/paper-2018-chiral_magnonic_crystals</p> <p> </p> <p>The files included in this Zenodo release refer to the v1.0 version of the data set. For an updated version of the scripts refer to the Github repository.</p>
Bichromatic wave groups with DIFFerent REPetition periods over a 1:100 sloping bed (DIFFREP-ICL).
<p><strong>DATASET DESCRIPTION</strong></p> <p>DIFFREP-ICL is the dataset that gathers the measurements described in <em>Padilla and Alsina, 2018</em>: <em>Long Wave Generation Induced by Differences in the Wave-Group Structure</em>.</p> <p>For wave cases from MR-01 to MR-10, the provided variables are:</p> <p><strong>i.</strong> Spatial domain measured from the wave paddle (<em>X</em>)</p> <p><strong>ii.</strong> Spatial domain measured from the shoreline at still water conditions (<em>x</em>)</p> <p><strong>iii.</strong> Water depth (<em>d</em>)</p> <p><strong>iv.</strong> Temporal domain (<em>time</em>)</p> <p><strong>v.</strong> Surface elevation series (<em>eta</em>) </p> <p><strong>vi.</strong> Run-up series measured according to the x-coordinate (<em>runup</em>) </p>
Vector shapefiles of the rural-urban interface in Portugal estimated for different periods (1990, 2000, 2006, 2012)
<p>Vector shapefiles of the rural-urban interface (RUI) in Portugal estimated for different periods (1990, 2000, 2006, 2012). RUI was mapped considering the first and the second level hierarchy of CORINE Land Cover (CLC). A specific geospatial approach was designed to extract the area of intersection between a buffer around the artificial surfaces and the area resulting from the sum of the forest and semi natural areas plus the heterogeneous agricultural areas. We adopted a buffer width of 1 km, corresponding to two times the spatial resolution of CLC inventories. </p> <p>The field “code_yy” refers to CLC class level 3. More about the Corine Land Cover (CLC) programme and datasets can be found at <a href="http://www.eea.eu">http://www.eea.eu</a></p> <p>More about the the RUI maps elaboration can be found at: <a href="https://doi.org/10.5194/nhess-18-1-2018">https://doi.org/10.5194/nhess-18-1-2018</a>. Please, cite data and the related paper if you use them. (cite as: Tonini., M., Parente., J., Pereira., M., Global assessment of rural-urban interface in Portugal related to land cover changes; Nat. Hazards Earth Syst. Sci., 18, 1–18, 2018)</p>
Investigating sensitivity of East Asian monsoon to orbital forcing during the Late Pliocene warm period
<p>CESM model outputs in a set of orbital sensitivity runs for the Late Pliocene.</p> <p>Only for the East Asia region</p> <p> </p>
Wide-field Infrared Survey Explorer (WISE) Catalog of Periodic Variable Stars
<p> Wide-field Infrared Survey Explorer (WISE) Catalog of Periodic Variable Stars<br> Xiaodian Chen, Shu Wang, Licai Deng, Richard de Grijs and Ming Yang</p> <p> We have compiled the first all-sky mid-infrared variable-star catalog based on Wide-field<br> Infrared Survey Explorer (WISE) five-year survey data. Requiring more than 100 detections<br> for a given object, 50,282 carefully and robustly selected periodic variables are discovered,<br> of which 34,769 (69%) are new. Most are located in the Galactic plane and near the equatorial<br> poles. A method to classify variables based on their mid-infrared light curves is established<br> using known variable types in the General Catalog of Variable Stars. Careful classification of<br> the new variables results in a tally of 21,427 new EW-type eclipsing binaries, 5654 EA-type <br> eclipsing binaries, 1312 Cepheids, and 1231 RR Lyraes. By comparison with known variables <br> available in the literature, we estimate that the misclassi- fication rate is 5% and 10% for<br> short- and long-period variables, respectively. A detailed comparison of the types, periods, <br> and amplitudes with variables in the Catalina catalog shows that the independently obtained <br> classifications parameters are in excellent agreement. This enlarged sample of variable <br> stars will not only be helpful to study Galactic structure and extinction properties, <br> they can also be used to constrain stellar evolution theory and as potential candidates for<br> the James Webb Space Telescope.<br> <br> These supplementary materials contain ALLWISE and NEOWISE-R single-exposure photometry tables of variables list<br> in Table 2 and 6 of the paper, and light curve figures for the 50,282 periodic variables in Table 2. <br> SourceID is identifier join these attachments to Table 2 and 6.</p> <p>Example: For variable star WISEJ094812.4+093448 in Table 2, the SourceID=170 is adopted to search <br> corresponding single-exposure information in both 'allwise12.txt' and 'neowise12.txt'. </p> <p>File Description:</p> <p>allwise12.txt Single exposure photometry data of variables from ALLWISE.</p> <p> Bytes Format Units Label Explanations<br> ----------------------------------------------------------------------------------------- <br> 1- 8 I5 --- SourceID Internal source identifier <br> 10- 20 F11.7 deg RAdeg Right Ascension in decimal degrees (J2000) <br> 22- 32 F11.7 deg DEdeg Declination in decimal degrees (J2000) <br> 34- 47 F14.8 day MJD Modified Julian date of the mid-point of the observation <br> 49- 54 F6.3 mag W1mag Single exposure WISE W1 (3.35 micron) band magnitude<br> 56- 63 F6.3 mag eW1mag W1 band uncertainty<br> 65- 77 F6.3 mag W2mag Single exposure WISE W2 (4.6 micron) band magnitude <br> 79- 86 F6.3 mag eW1mag W2 band uncertainty<br> -----------------------------------------------------------------------------------------<br> <br> <br> neowise12.txt Single exposure photometry data of variables from NEOWISE-R.</p> <p> Bytes Format Units Label Explanations<br> -----------------------------------------------------------------------------------------<br> 1- 8 I5 --- SourceID Internal source identifier <br> 10- 21 F11.7 deg RAdeg Right Ascension in decimal degrees (J2000) <br> 23- 34 F11.7 deg DEdeg Declination in decimal degrees (J2000) <br> 36- 44 F6.3 mag W1mag Single exposure WISE W1 (3.35 micron) band magnitude<br> 46- 54 F6.3 mag eW1mag W1 band uncertainty<br> 56- 64 F6.3 mag W2mag Single exposure WISE W2 (4.6 micron) band magnitude <br> 66- 74 F6.3 mag eW1mag W2 band uncertainty<br> 76- 90 F14.8 day MJD Modified Julian date of the mid-point of the observation<br> -----------------------------------------------------------------------------------------</p> <p> <br> figure0.zip -- figure23.zip Full figures of 50282 WISE variables. They are divided into 24 <br> packages by the order of Right Ascension.</p>
The shape of convective core overshooting from gravity-mode period spacings
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018arXiv180202051P/abstract">The shape of convective core overshooting from gravity-mode period spacings</a></p>
The OmegaWhite Survey for Short-period Variable Stars. V. Discovery of an Ultracompact Hot Subdwarf Binary with a Compact Companion in a 44-minute Orbit
<p>MESA inlists and run_star_extras associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017ApJ...851...28K">Kupfer et al. (2017)</a>. MESA version 9793.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-4357/aa9522">10.3847/1538-4357/aa9522</a></p>
The coincidence degree between the geochemical behavior of elements and the periodic variation of elements based on geochemical data of C2 coal seam in the Fengfeng mining area of the Handan Coalfield in Hebei, China
<p>In this data-set, based on the geochemical data of C2 coal seam in the Fengfeng mining area of the Handan Coalfield in Hebei (China), where provided ideal coal samples changing continuously from low-rank metamorphic coal to high-rank metamorphic coal, the coincidence degree (or similarity degree) between the geochemical behavior of 57 elements and the periodic variation of elements during the thermal metamorphism process is calculated.</p>
Empirical Predictions for the Period Distribution of Planets to be Discovered by the Transiting Exoplanet Survey Satellite
<p>This repository contains the supplement materials for our paper :</p> <p>Jonathan H. Jiang, Xuan Ji, Nicolas Cowan, Renyu Hu, Zonghong Zhu, Empirical Predictions for the Period Distribution of Planets to be Discovered by the Transiting Exoplanet Survey Satellite, Submitted to AJ.</p> <p>Supplemental materials include:</p> <p>1.Data behind the Figures</p> <p>2.Simulation Results to estimate the error range</p> <p> </p>
visualizing the developement of painting production in periods of 50 years from 1300 to 2000 (source: https://kor.uni-frankfurt.de)
<p>Data<br> * entities representing a painting were selected<br> ** since there is no classification of works of art in the database, a set of values describing the technical and material features of the works of art were used to filter works of art being most probably paintings. The filter values can be found in ../../unique_material_values_new.xlsx on tabs "Öl auf Leinwand" and "Tafelmalerei"<br> * the selected entities were classified in periods of 50 years starting in 1300 and ending in 2000. Additionally there were two classes for paintings before 1300 and after 2000, and a class for non dated painting entities<br> * for each of the classes, the proprtion of its cardinal number in respect to the global number of selected entities was calculated<br> * class labels and the calculated proportion were written in data.csv (column 1: class labels, column 2: proprtion)</p> <p>Processing<br> * script that creates a bar chart from data in data.tsv<br> ** the script uses d3.js</p> <p> </p>
Dataset of predicted dynamic specific yield under periodic water table oscillations
<p>This dataset accompanies the submitted paper in the Water Resources Research: An approximate model for predicting the specific yield under periodic water table oscillations.</p> <p>The dataset includes 299 numerical experiments on predicting dynamic specific yield with different soil properties and different amplitudes of groundwater level oscillations. With this dataset, we proposed an approximate model for predicting the specific yield under diurnal and seasonal water level fluctuations.</p>
SFigure1. OTUs at genus level significantly different (p<0.05) between rumen samples of cows fed control and cold-pressed sunflower cake in the first period of the experiment (n=5).
<p>OTUs at genus level significantly different (p<0.05) between rumen samples of cows fed control and cold-pressed sunflower cake in the first period of the experiment (n=5). </p>
The distribution data of sandhill crane in Asia during non-breeding period from our fieldwork
<p>This data is the wintering distribution data of sandhill cranes collected by our research team in the fieldwork. The data has been used to publish an article in Peerj.</p>
Observation of very short period atmospheric gravity waves in the lower Ionosphere using Very Low Frequency waves
<p>This is the VLF frequency data recorded at PARI station owned by Prof Morris Cohen, at Georgia Institute of Technology, Atlanta, USA.</p> <p>Data is for six transmitter signals, DHO, NAA, NAU, NLK, NPM, NML with both amplitude and Phase</p>
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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.