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1,118 results for “Time series”
Supplementary material 1 from: Cerri J, Carnevali L, Monaco A, Genovesi P, Bertolino S (2022) Blacklists do not necessarily make people curious about invasive alien species. A case study with Bayesian structural time series and Wikipedia searches about invasive mammals in Italy. NeoBiota 71: 113-128. https://doi.org/10.3897/neobiota.71.69422
Supplementary information
ETNP_ODZ_time_series
<p>Time series of data corresponding to Evans et al. (2022) "Natural variability and expansion of the nitrogen deficit within the Eastern Tropical North Pacific Oxygen Deficient Zone", containing secondary quality controlled data of 8 cruises in the ETNP ODZ, seven of which on the 110 W line, as well as supplemental sediment core data and CalCOFI oxygen data for comparison. Intermediate data products generated by the code used for this paper are also included, and the code to generate these intermediate products as well as the final outputs has been uploaded onto a separate Zenodo repository, "ETNP_ODZ_time_series_code" at https://doi.org/10.5281/zenodo.6519316. More detailed information is available in the README, but should you have any questions, please reach out to Allan Devol or Natalya Evans.</p> <p> </p>
A Large-Scale Annotated Multivariate Time Series Aviation Maintenance Dataset from the NGAFID
<p>Aviation flight records and maintenance labels. </p>
3D+time nuclei tracking dataset of diSPIM lightsheet fluorescence microscopy time series of C. elegans embryos
<p>The dataset consists of 3 diSPIM microscopy time series of <em>C. elegans</em> embryos, fully tracked.</p> <ul> <li>3 raw time-series and the corresponding tracks/lineage trees</li> <li>temporal resolution: 1min</li> <li>temporal extent: 350-400 frames, tracked for at least 330 frames</li> <li>spatial resolution (zyx): 0.1625 x 0.1625 x 0.1625μm</li> <li>spatial extent (zyx): 250 x 250 x 400px (average)</li> <li>Microscope: dual-view ASI diSPIM (fused and deconvolved using the MIPAV GenerateFusion plugin)</li> </ul> <p>The original raw data and annotations were part of the following publication (please also cite this if you use the dataset):</p> <p><em> </em>Moyle, M.W., Barnes, K.M., Kuchroo, M. <em>et al.</em> Structural and developmental principles of neuropil assembly in <em>C. elegans</em>. <em>Nature</em> 591<strong>, </strong>99–104 (2021). <a href="https://doi.org/10.1038/s41586-020-03169-5">https://doi.org/10.1038/s41586-020-03169-5</a></p> <p>Additionally the data was extended and slightly curated further by Peter Hirsch (MDC) and used for the development of a new tracking method in the following publication:</p> <p><em> Hirsch, P., Malin-Mayor, C., Santella, A., Preibisch, S., Kainmueller, D., Funke, J. Tracking by weakly-supervised learning and graph optimization for whole-embryo C. elegans lineages. MICCAI 2022</em></p> <p>For questions please contact Peter Hirsch (<a href="mailto:peter.hirsch@mdc-berlin.de">peterhirsch@posteo.de</a>).</p>
Data from: A time series model for estimating temporal variation in phenotypic selection on laying dates in a Dutch great tit population
[No abstract entered]
Detecting periodicities in time-series (for exoplanet detection)
<p>Recording of the presentation given at the Summer School</p>
Daily hydro power time series (1979-2016) for 43 Chinese reservoir hydro stations
<p>This is the hydro time series used in the article </p> <p><em>The role of hydro power, storage and transmission in the decarbonization of the Chinese power system</em></p> <p><a href="https://doi.org/10.1016/j.apenergy.2019.02.009">https://doi.org/10.1016/j.apenergy.2019.02.009</a></p> <p>Their calculations are detailed in this article:</p> <p><a href="https://doi.org/10.1016/j.mex.2019.05.024">https://doi.org/10.1016/j.mex.2019.05.024</a></p> <p> </p> <p>--------------------------------------------</p> <p><a href="https://zenodo.org/api/files/c3dc671c-7d64-4a5f-b535-650c7e7445b7/dams_large.csv?versionId=a2ceab14-c1e5-49be-805d-7ebce1f7b749">dams_large.csv </a> lists the names, coordinates, provinces, historical yearly inflows, historical water consumption rate and historical yearly electricity generation of the reservoir stations.</p> <p><a href="https://zenodo.org/api/files/c3dc671c-7d64-4a5f-b535-650c7e7445b7/reservoir_effective_capacity.pickle?versionId=9b4a5ca7-ae15-44ab-aa38-6554ed0d5a97">reservoir_effective_capacity.pickle </a> contains the effective capacity for the reservoirs.</p> <p><a href="https://zenodo.org/api/files/c3dc671c-7d64-4a5f-b535-650c7e7445b7/daily_hydro_inflow_per_dam_1979_2016_m3.pickle?versionId=069e756e-3fe7-4fd5-ae82-1f51618d4f77">daily_hydro_inflow_per_dam_1979_2016_m3.pickle </a> and <a href="https://zenodo.org/api/files/c3dc671c-7d64-4a5f-b535-650c7e7445b7/daily_hydro_inflow_per_dam_1979_2016_GWh.pickle?versionId=d0bc17ce-e48b-4a5c-934f-e602f8b9f797">daily_hydro_inflow_per_dam_1979_2016_GWh.pickle </a> contains the daily hydro inflow time series in terms of water (m3) and potential energy (GWh), respectively.</p> <pre><code class="language-python">import pandas data_pickle = pandas.read_pickle('*.pickle') data_csv = pandas.read_csv('dams_large.csv')</code></pre> <p> </p>
An effective low-cost remote sensing approach to reconstruct the long-term and dense time series of area and storage variations for super-large lakes
<p>Supplementary File</p>
Association Between Short-term Exposure to Air Pollutants and Emergency Attendance for Upper Gastrointestinal Bleeding in Hong Kong: A Time-series Study
<p>Related data and DLNM code for generating figures and results.</p>
Time series root system
Open the record for dataset details and reuse information.
Data for Science Time Series: Deep Learning in Hydrology
<p>Processed CAMELS and Caravan data.</p>
Figure 3 from: Miller J, Beentjes K, van Helsdingen P, IJland S (2013) Which specimens from a museum collection will yield DNA barcodes? A time series study of spiders in alcohol. ZooKeys 365: 245-261. https://doi.org/10.3897/zookeys.365.5787
Figure 3 - DNA concentration (log10 transformed) for specimens in the time series study that yielded or failed to yield a successful DNA barcode sequence arranged by A body size B year collected. Successes (filled circles) and failures (while circles) partitioned into destructive (red) and nondestructive (blue) DNA extraction methods.
Figure 2 from: Miller J, Beentjes K, van Helsdingen P, IJland S (2013) Which specimens from a museum collection will yield DNA barcodes? A time series study of spiders in alcohol. ZooKeys 365: 245-261. https://doi.org/10.3897/zookeys.365.5787
Figure 2 - Sequencing success for the time series study of 31 spider species frequently collected in the Netherlands. Data for each species arranged horizontally along a time axis (year of collection). Small circles represent standard destructive extraction; outer circle represents nondestructive extraction. Red small circle and blue outer circle indicate successful sequencing, unfilled circles represent failed attempts; half-filled circle indicates mixed success among multiple specimens for that species and year. Solid horizontal lines extend from the present to the oldest successful DNA barcode based on destructive extraction for each species; where nondestructive extraction yielded successful DNA barcode from older specimens, this is indicated by a dashed line. Data are arranged according to a neighbour joining tree (A) or by species body size (B). Spider families and major lineages (Orbiculariae and 'RTA' clade) are indicated in A. AGE Agelenidae AMA Amaurobiidae ARA Araneidae CLU Clubionidae COR Corinnidae LIN Linyphiidae LYC Lycosidae PHI Philodromidae PIS Pisauridae SAL Salticidae THD Theridiidae THO Thomisidae ZOR Zoridae.
Figure 1 from: Miller J, Beentjes K, van Helsdingen P, IJland S (2013) Which specimens from a museum collection will yield DNA barcodes? A time series study of spiders in alcohol. ZooKeys 365: 245-261. https://doi.org/10.3897/zookeys.365.5787
Figure 1 - A Sequencing success profile for specimens included in this study. Data are species attempted, all specimens in the study including the time series, and fresh specimens collected in 2010 or later. Success expressed as a percentage appears on the blue (success) portion of each bar B Sequencing success rates for fresh (collected 2010 or later) and older specimens grouped by decade. Data given for all extractions regardless of method, and also partitioned into destructive and nondestructive extraction methods. Total number of specimens attempted and the subset of specimens attempted using nondestructive extraction given in parentheses. Note that the relatively high success rate for nondestructive extractions of specimens from the 1960s is based on two successes out of four attempts.
Figure 5 from: Miller J, Beentjes K, van Helsdingen P, IJland S (2013) Which specimens from a museum collection will yield DNA barcodes? A time series study of spiders in alcohol. ZooKeys 365: 245-261. https://doi.org/10.3897/zookeys.365.5787
Figure 5 - DNA barcode sequencing success for fresh specimens (collected 2010 or later). A Specimen body size not significantly different for successful vs. failed DNA barcode sequencing attempts (one-way ANOVA, F (1, 216) = 1.45, p = 0.230). Boxes are 25–75% quartiles bisected by the median, whisker lines drawn to the largest/smallest data point less than 1.5 times the box height, outliers less than 3 times the box height shown as circles, more than 3 shown as stars. B Most of the fresh specimens included in this study belonged to one of two clades: Orbiculariae (ORB) or the 'RTA' clade (RTA); only a handful of specimens represented older phylogenetic branches, such as haplogyne (HAP) spiders; no mygalomorph spiders were included; success expressed as a percentage appears on or above each bar. Success rate for Orbiculariae vs. 'RTA' clade specimens not significantly different (χ2 = 2.18, d.f. = 2, N = 220, p = 0.337).
Figure 4 from: Miller J, Beentjes K, van Helsdingen P, IJland S (2013) Which specimens from a museum collection will yield DNA barcodes? A time series study of spiders in alcohol. ZooKeys 365: 245-261. https://doi.org/10.3897/zookeys.365.5787
Figure 4 - A DNA concentration (log10 transformed) for specimens in the time series study that yielded or failed to yield a successful DNA barcode sequence ranked by DNA concentration; symbols as in Figure 3 B Box plot showing difference in DNA concentration for specimens extracted using both destructive and nondestructive methods; species arranged by size (Araneus quadratus, Tegenaria atrica, and Dolomedes plantarius excluded). Sample size in parentheses, boxes are 25–75% quartiles bisected by the median, whisker lines indicate minimum/maximum values (where n > 4).
Streamwater dissolved organic carbon, discharge, temperature and precipitation electrical conductivity time series and associated site information for eight European headwater streams.
<p>This dataset (in Microsoft Excel format) provides the underlying data described in the Science Advances paper, "Long-term rise in riverine dissolved organic carbon concentration is predicted by electrolyte solubility theory", by D.T. Monteith, P.A. Henrys, J.Hruška, H.A. de Wit, P. Krám, F. Moldan, M. Posch, A. Räike, J.L. Stoddard, E.M. Shilland, M.G. Pereira & C.D. Evans, It includes the following spreadsheets: 1) A "<strong>readme</strong>" page providing the information above; 2) <strong>Site data</strong>. including site physical attributes and information on data sources; 3) <strong>Temporal smoothing</strong>. Detailing the temporal smoothers applied to the electrical conductivity and air temperature data for modelling purposes; and 4) <strong>Input data</strong>. Multi-decadal time series of dissolved organic carbon (DOC) concentrations for a range of intensively monitored headwater streams, together with data for the following variables used to model DOC, i.e. associated stream discharge measurements, and temporally averaged precipitation electrical conductivity and air temperature data. </p>
Data attached to Radio Science paper "Model to Scale Rain Attenuation Time Series with Link Elevation Angle for LEO Satellite Based Systems"
<p>Data attached to Radio Science paper "Model to Scale Rain Attenuation Time Series with Link Elevation Angle for LEO Satellite Based Systems"</p>
Time series of mesozooplankton data at LTER-MC in the Gulf of Naples (1984-2015)
<p>The present dataset contains the abundance data (ind. m<sup>-3</sup>) of total mesozooplankton, main groups and copepod species from the Long Term Ecological Research station MareChiara in the Gulf of Naples (st. LTER-MC, 40°48.5’ N, 14°15’ E) over the years 1984-2015. Zooplankton samples were collected by vertical tows in the upper 50 m using an Indian Ocean net (200-µm mesh, 113-cm mouth diameter) and fixed with buffered formaldehyde (2–4% final concentration). In the laboratory, the samples were concentrated and resuspended in filtered seawater to a volume of 200 ml to remove the formaldehyde. Aliquots ranging from 1/4 to 1/32, according to the sample density, were initially taken using the Huntsman beaker subsampling technique and successively with a large-bore graduated pipette after careful mixing. Aliquots were transferred to a mini-Bogorov chamber (10 ml) and examined under a stereomicroscope and all zooplankton taxa were identified and counted. The entire sample was checked for the presence of rare species. The copepod abundances reported here correspond to the whole population (adult females and males, and copepodites).</p>
Time series of electrical conductivity, temperature, relative stream stage and total pressure recorded in surface water and streambed sediments of River Erpe and River Ammer, Germany, and the Sturt River, South Australia
<p>Time series of electrical conductivity (mS cm<sup>-1</sup>), temperature (degC), relative stream stage (cm) and total pressure (hPa) recorded in the surface water and in streambed sediments (depth in cm) of River Erpe and River Ammer, Germany, and the Sturt River, South Australia.</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.