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2,516 results for “Seri”
Simulated time series and indicators for the Omo-Turkana Basin case study
<p>The archive includes:</p> <ul> <li>daily time series over 2021-2099 time horizon of different physical variables, simulated by the Water Energy Food Integrated Model on the Omo Turkana River Basin for the 6 interesting pathways identified in the Negotiation Simulation Lab meeting;</li> <li>a set of evaluation indicators, aggregated at different spatial and temporal scales, for the 6 interesting pathways.</li> </ul> <p>More details on physical variables and indicators included are available in the DAFNE Deliverable D7.3.</p> <p>Files are provided in the <em>csv </em>format, one per each physical variable or indicator: the first 13 rows contain metadata, while data starts at row 14 and use as many columns as the pathways considered. Metadata are the following:</p> <ul> <li><em>name</em>, time series or indicaror label</li> <li><em>author, </em>reference person or team for the specific time series</li> <li><em>created,</em> timestamp of the file creation</li> <li><em>description, </em>description of file content</li> <li><em>unit, </em>unit of measurement</li> <li><em>origin, </em>description of the simulation</li> <li><em>time_sampling,</em> whether the variable is sampled at a given point in time (instantaneous) or represents a time interval (interval)</li> <li><em>frequency, </em>time step of the time series</li> <li><em>scenario, </em>label of scenario</li> <li><em>marker_id, </em>label of the related model component</li> <li><em>id_type, </em>type of time series</li> <li><em>timestart,timeend,P1,P2,P3,P4,P5,P6 : </em>header row of the data, with time information (in the matlab datenum format) at the beginning and pathways on each column</li> </ul>
Substituents isolated from analog series
<p>From ~24,000 analog series extracted from ChEMBL, more than 19,000 substituent fragments (SF) were identified. A subset of ~400 substituent fragments occurred most frequently in different compound classes (frequent SF, FSF). The entire SF/FSF collection is made available here as a part of a forthcoming publication in the Journal of Medicinal Chemistry. </p>
Sliding velocity, water discharge and basal shear stress time series at Argentière Glacier
<p>The data set contains all data presented in:</p> <p>Gimbert, F., Gilbert, A., Gagliardini, O., Vincent, C., & Moreau, L. (2021). Do Existing Theories Explain Seasonal to Multi-Decadal Changes in Glacier Basal Sliding Speed? <em>Geophysical Research Letters</em>, <em>48</em>(15), e2021GL092858. <a href="https://doi.org/10.1029/2021GL092858">https://doi.org/10.1029/2021GL092858</a></p> <p>and also in:</p> <p>Gilbert, A., Gimbert, F., Thøgersen, K., Schuler, T. V., & Kääb, A. (2022). A Consistent Framework for Coupling Basal Friction with Subglacial Hydrology on Hard-bedded Glaciers. <em>Geophysical Research Letters</em>, <em>49</em>, e2021GL097507. <a href="https://doi.org/10.1029/2021GL097507">https://doi.org/10.1029/2021GL097507</a></p> <p>Files Description:</p> <p>==================================<br> SlidingVelocities1989_2019.csv :<br> ==================================</p> <p>Contains daily values of recorded sliding velocities at the wheel.</p> <p>Column 1 = Date<br> Column 2 = Daily Values (cm/day)</p> <p>================================<br> BasalShearStress1980_2019.csv :<br> ================================</p> <p>Contains daily values of inferred basal shear stress at the wheel.</p> <p>Column 1 = Date<br> Column 2 = Daily Values (MPa)</p> <p>================================<br> WaterDischarge1985_2019.csv :<br> ================================</p> <p>Contains daily values of recorded water discharge at the glacier outlet</p> <p>Column 1 = Date<br> Column 2 = Daily Values (m3/s)</p>
Data from: Disturbance detection in Landsat time series is influenced by tree mortality agent and severity, not by prior disturbance
<p><span>Landsat time series (LTS) and associated change detection algorithms are useful for monitoring the effects of global change on Earth's ecosystems. Because LTS algorithms can be easily applied across broad areas, they are commonly used to map changes in forest structure due to wildfire, insect attack, and other important drivers of tree mortality. But factors such as initial forest density, tree mortality agent, and disturbance severity (i.e., percent tree mortality) influence patterns of surface reflectance and may influence the accuracy of LTS algorithms. And while LTS algorithms are widely used in areas with a history of multiple disturbance events during the Landsat record, the effectiveness of LTS algorithms in these conditions is not well understood. We compared products from the LTS algorithm LandTrendr (<span>Landsat-based Detection of Trends in Disturbance and Recovery) with</span> a unique field dataset from a landscape heavily influenced by both wildfire and spruce beetles (<i>Dendroctonus rufipennis</i>) since c. 2000. We also compared LandTrendr to other common methods of mapping fire- and spruce beetle-affected areas. We found that LandTrendr more accurately detected wildfire than spruce beetle-induced tree mortality, and both mortality agents were more easily detected when they occurred at high severity. Surprisingly, prior spruce beetle outbreaks did not influence the detectability of subsequent wildfire. Compared to alternative disturbance mapping approaches, LandTrendr predicted a c. 40% lower area affected by wildfire or spruce beetle outbreaks. <span>Our findings indicate that disturbance type- and severity-specific differences in omission error may have broad implications for disturbance mapping efforts that utilize Landsat data. Gradual, low-severity disturbances (e.g., background tree mortality and non-stand replacing disturbance) are pervasive in forest ecosystems, yet they can be difficult to detect using automated LTS algorithms. Whenever possible, methods to account for these biases should be incorporated in LTS-based mapping efforts, including the use of multispectral ensembles and ancillary spatial data to refine predictions. However, our findings also indicate that LTS algorithms appear to be robust in areas with multiple disturbance events, which is important because these areas will increase as new acquisitions extend the length of the Landsat record. </span></span></p>
Supplementary Material and Code of Evidence for immunity to SARS-CoV-2 from epidemiological data series
<p>This Supplementary Material file, Code and Data correspond to the manuscript:</p> <p>Evidence for immunity to SARS-CoV-2 from epidemiological data series<br> Pablo Yubero, Alvar A. Lavin, Juan F Poyatos<br> medRxiv 2020.07.22.20160028; doi: https://doi.org/10.1101/2020.07.22.20160028</p>
Establishing diversity in synthetic time series for prediction performance evaluation
<p>This dataset enables practitioners to evaluate their time series prediction algorithms on various types of time series</p>
The growth of COVID-19 scientific literature: A forecast analysis of different daily time series in specific settings
<p>Submitted to The ISSI 2021 Conference. The conference is organised by KU Leuven in close collaboration with the university of Antwerp under the auspices of ISSI – the International Society for Informetrics and Scientometrics (<a href="http://www.issi-society.org/">http://www.issi-society.org/</a>). </p> <p>We present a forecasting analysis on the growth of scientific literature related to COVID-19 expected for 2021. Considering the paramount scientific and financial efforts made by the research community to find solutions to end the COVID-19 pandemic, an unprecedented volume of scientific outputs is being produced. This questions the capacity of scientists, politicians and citizens to maintain infrastructure, digest content and take scientifically informed decisions. A crucial aspect is to make predictions to prepare for such a large corpus of scientific literature. Here we base our predictions on the ARIMA model and use two different data sources: the Dimensions and World Health Organization COVID-19 databases. These two sources have the particularity of including in the metadata information on the date in which papers were indexed. We present global predictions, plus predictions in three specific settings: by type of access (Open Access), by NLM source (PubMed and PMC), and by domain-specific repository (SSRN and MedRxiv). We conclude by discussing our findings.</p>
High-frequency measurements of aeolian saltation flux: time series data
<p>High-frequency (25-50 Hz) coupled observations of wind speed and aeolian saltation flux (i.e, the wind-blown movement of sand) were measured at three field sites: Jericoacoara, Brazil; Rancho Guadalupe, California; and Oceano, California. The dataset provided here contains the full record of raw and processed time series of saltation flux and wind speed measured at multiple heights above the sediment surface.</p>
Scripts and data for "The adequacy of time-series reduction for renewable energy systems"
<p>This upload provides the scripts and data used for the computations in the aforementioned working paper. To run these files, you will need to adjust the directory in the files 'testTimeSeries.jl' and 'calli.bat' to your local directory.</p> <p>The subfolder 'reduceTimeSeries' contains all data and the script 'reduceTimeSeries.jl' to reduce the full time-series. Reduction using the 'Gerbaulet' method unfortunately requires a GAMS installation. The results of the reduction are already provided in the folder 'output'.</p> <p>The subfolder 'testTimeSeries' contains all data and the script 'testTimeSeries.jl' to test the reduced time-series with a capacity expansion model. The 'comment' and ‘source’ columns in the AnyMOD.jl input files provide further documentation on the used input parameters. The labels 'lowDem' and 'newDem' relate to what was referred to conventional demand and demand with sector integration in the paper, respectively.</p>
InSAR time series analysis results of ALOS-2/PALSAR-2 data for the post-eruptive displacement of the 2015 phreatic eruption of Hakone volcano, Japan
<p>This repository contains the InSAR products used in Doke et al., GRL (submitted).</p> <p> </p> <p><strong>Dataset 1</strong>: Surface velocity data estimated by InSAR time series analysis with NetCDF grid format.</p> <ol> <li>surface_velocity_p126.nc</li> <li>surface_velocity_p18.nc</li> </ol> <p> </p> <p><strong>Dataset 2</strong>: Time-series of LOS displacements in selected locations with text format.</p> <ol> <li>time_series_p126.txt</li> <li>time_series_p18.txt</li> </ol> <p> </p> <p><strong>Dataset 3</strong>: Inputs and results of model inversion with shapefile.</p> <p>Subsampled observation data, modeled (simulated) displacements, and other parameters are shown in attribute tables in shapefiles. Shapefiles that show the location of the estimated models are also included in ZIP files.</p> <ol> <li>point_source_deflation.zip</li> <li>sill_deflation.zip</li> </ol>
Data From: Analysing social media forums to discover potential causes of phasic shifts in cryptocurrency price series
<p>The recent extreme volatility in cryptocurrency prices occurred in the setting of popular social media forums devoted to the discussion of cryptocurrencies. We develop a framework that discovers potential causes of phasic shifts in the price movement captured by social media discussions. This draws on principles developed in healthcare epidemiology where, similarly, only observational data are available. Such causes may have a major, one-off effect or recurring effects on the trend in the price series. We find a one-off effect of regulatory bans on bitcoin, the repeated effects of rival innovations on ether and the influence of technical traders, captured through discussion of market price, on both cryptocurrencies. The results for Bitcoin differ from Ethereum, which is consistent with the observed differences in the timing of the highest price and the price phases. This framework could be applied to a wide range of cryptocurrency price series where there exists a relevant social media text source. Identified causes with a recurring effect may have value in predictive modelling, whilst one-off causes may provide insight into unpredictable black swan events that can have a major impact on a system.</p>
Daigi series pottery (大木式土器)
This is an Daigi series pottery excavated from the Koda V site in Yokote City, Akita Prefecture. Early Daigi series potteries are characterized by those clean, cylindrical form and thick, whorled or wavy clay strings attached to the rim. -- in Japanese -- これは、 秋田県横手市の小田(こだ)V遺跡から出土した、大木(だいぎ)式土器です。前期大木式土器は、すっきりした円筒形のフォルムと、口縁部に貼り付けられた渦巻きや波状の太い粘土紐が特徴です。 Source: Objaverse 1.0 / Sketchfab
Alms - Ramadhan Series
give something of value to others, in the month of Ramadan there is also such a thing as zakat fitrah which is the fourth pillar of Islam Source: Objaverse 1.0 / Sketchfab
Detailed data sets of MMP-cliffs, SAR transfer series, RECAP-MMPs and compound activities
<p>An up-to-date version of three MMP-based data sets derived from compounds included in the latest release of ChEMBL is presented. These data sets include activity cliffs, structure-activity relationship (SAR) transfer series, and second generation MMPs based upon retrosynthetic rules. The structural data and information are provided in eight different files comprising the data sets of MMP-cliffs, SAR transfer series, and RECAP-MMPs. Compound activities are incorporated in files of RECAP-MMPs. For transfer series, substituted fragments are also provided. All MMP-cliffs, SAR transfer series with approximate or regular potency progression, and RECAP-MMPs are provided in canonical SMILES representation on a per-target basis separately for the Ki and IC50 subsets. The corresponding files are clearly designated.</p>
Subsidence of Beijing (China) mapped by Copernicus Sentinel-1 time series interferometry
<p><strong>RESULTS DESCRIPTION</strong></p> <p>Recent reports from scientific and mainstream media have indicated that the city of Beijing, together with its surroundings, is subsiding at fast and alarming rate as result of the overexploitation of groundwater. The depletion of groundwater causes underlying soil to compact, creating a phenomenon called subsidence. The Beijing region has been experiencing this phenomenon since 1935, but in last years the rate of sinking has significantly increased.</p> <p>A team of researchers, within ESA sponsored, SEOM InSARap project performed an interferometric analysis of Copernicus Sentinel-1 data which confirms the reported findings also with current data. While the results speak for themselves, we can just once more reiterate on the usefulness of the Copernicus Programme, in this case for deformation monitoring applications.</p> <p><strong>ANALYSIS SUMMARY</strong></p> <ul> <li>Data overview: <ul> <li>Sentinel-1 IW</li> <li>Track 47 descending</li> <li>Observation window December 2014 - June 2016</li> <li>Data download via Scientific Data Hub</li> </ul> </li> <li>Processing overview: <ul> <li>Time series analysis performed with Small Baseline Subset (SBAS) methodology</li> <li>Interferometric combinations of up to 96 days used</li> </ul> </li> </ul> <p><em>More information and context available at insarap.org</em></p> <p><em>Terms and Conditions:</em> All Sentinel-1 results that are available for download are Derived Works of Copernicus data (2014-2016), subject to the "<em>TERMS AND CONDITIONS FOR THE USE AND DISTRIBUTION OF SENTINEL DATA AND SERVICE INFORMATION</em>".</p> <p><em>Acknowledgments: </em> ESA SEOM InSARap project - Sentinel-1 InSAR Performance Study with TOPS Data, contract number 4000110680/14/I-BG-InSARap</p>
A series of pathological macromolecular crystallography datasets with twinning and other lattice disorders
<p>These 11 datasets were collected at the Diamond Light Source and belong to the same protein, NAL (N-acetyl neuraminic acid lyase), which crystallised in 4 different crystal forms from the same crystallisation conditions producing crystals with the same morphology. The file names, where applicable (10/11 cases), contain the corresponding PDB deposition code.</p>
Results from monitoring changes in NDVI time series over southwest Ethiopia based on 11 years of Landsat 7 imagery and BFAST
<p>(see README.md)</p>
Entire confocal z-stack series as .tif image sequences
<p>The manuscript entitled "Parvalbumin-expressing ependymal cells in rostral lateral ventricle wall adhesions contribute to aging-related ventricle stenosis in mice" shows confocal z-stack maximum intensity projections and thin z-plane reconstructions in the figure plates. The entire confocal z-stack image series are provided here as .tif image sequences, respectively the confocal z-stacks of the negative controls as well. The file names refer to the figure numbers and position in the figure plates. For more information about the immunostaining and image acquisition, see the Materials & Methods and Figure legends in the manuscript.</p>
Load and renewable generation time series for selected regions in Africa and Eurasia
<p>The data set consist of three groups of yearly time series for 2003-2012 used in grid modelling. All time series are presented in .csv format. The data covers wind and PV power generation and load of 12 regions. The regions have 2 letter identifier and include the following:</p> <p>EU - EU countries</p> <p>NA - Algeria, Egypt, Libya, Morocco, Tunisia</p> <p>WA - Cameroon, Ghana, Nigeria</p> <p>EA - Ethiopia, Kenya, Tanzania, Uganda</p> <p>SA - South Africa</p> <p>RU - European part of Russia, Belarus, Ukraine</p> <p>MS - Arabic countries, Israel, Turkey</p> <p>IP - Bangladesh, India, Pakistan, Sri Lanka</p> <p>SB - Asian part of Russia, Kazakhstan, Turkmenistan, Uzbekistan</p> <p>IC - Indonesia, Malaysia, Philippines, Thailand, Vietnam</p> <p>CN - China</p> <p>FE - South Korea, Japan</p> <p> </p> <p>Wind power time series are derived from MERRA wind speed data for Enercon E-126 wind turbine.</p> <p>PV power time series are derived from MERRA solar surface irradiance data.</p> <p>Load time series are generated with the periodical function.</p> <p> </p> <p>Data for EU was derived within the project RESTORE 2050 as described in</p> <p>Kies, A., Chattopadhyay, K., von Bremen, L., Lorenz, E., & Heinemann, D. (2016). Simulation of renewable feed-in for power system studies.</p> <p>Data for all other nodes was derived as described in</p> <p>Krutova, M. et al., The smoothing effect for renewable resources in an Afro-Eurasian power grid, Adv. Sci. Res., 2017</p> <p>Load for EU is obtained from ENTSO-E and is not included in this data set.</p>
BioTIME 2.0: expanding and improving a database of biodiversity time series
<p>Here we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies in the database, and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database.</p> <p>We include here:</p> <ul> <li>SQL file of the database - biotime_v2_sql_15April25.sql</li> <li>RDS file of the query combining raw data with species names - biotime_v2_query_15April25.rds</li> <li>csv file for metadata information - biotime_v2_metadata_15April25.csv</li> <li>csv file of citations - references_biotime_v2_15April25.csv</li> <li>text file of BIB text citations - BIB_biotime_v2_15April25.csv.txt</li> </ul> <p>for issue of version 2.0 of the BioTIME database</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.