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35 results for “sampling event”
Antarctic Circumnavigation Expedition event log: recording data and sample collection in the Southern Ocean during the austral summer of 2016/17.
<p><strong>Dataset abstract</strong></p> <p>The Antarctic Circumnavigation Expedition (ACE) spent 90 days circumnavigating Antarctica on the R/V Akademik Tryoshnikov during the austral summer of 2016/17. This dataset provides a record of the instrument deployments as well as dataset and sample collection events that took place during the expedition.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_events.csv, data file, comma-separated values</li> <li>sampling_method_descriptions.csv, metadata, comma-separated values</li> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This event log is made available under a Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p> <p> </p>
Table S27: Target and identified unknown organic micropollutants detected in surface water samples taken during heavy rain events
<p>In the following table, peak intensities of detected organic micropollutants in water samples are displayed.</p> <p>This data table is part of the appendix of Chapter 4 of the PhD thesis “Novel approaches to identify drivers of chemical stress in small rivers” by Liza-Marie Beckers prepared at RWTH Aachen University and at the Helmholtz Centre for Environmental Research-UFZ. In Chapter 4, precipitation-related pollutant patterns and indicator compounds during heavy rain events were identified in the Holtemme River by nontarget screening and cluster analysis. The table contains peak heights of organic micropollutants detected in water samples taken during heavy rain events in the Holtemme River (Saxony – Anhalt, Germany). The table is structured into the following columns: Compound name, use class of compound (e.g., pharmaceutical or pesticide), distinction between target or identified unknown compounds, mass-to-charge ratio (m/z), retention time (RT), assignment to a pattern identified by cluster analysis (i.e., “Base” or “Quick”), the probability of belonging to the assigned pattern as number between 0 and 1 as well as the peak height of the compound in each sample. The samples are indicated by "B" for "bottle" and a number from 1-16. The use class “NA” indicates that now major use class for this compound could be identified.</p> <p>The sampling was triggered by combined sewer overflow at a wastewater treatment plant upstream of the sampling point. Samples were taken by an automated sampler in 30-min composite samples for 8 hours resulting in 16 samples per rain event. In total, 6 heavy rain events from May to September 2016 were sampled during this study. The table is divided into 6 subtables (i.e., Table S27 A-F). Each subtable displays compounds and their peak heights detected in samples from one heavy rain event. The different rain events are abbreviated by the sampling date:</p> <p>Table S27A displays results from the rain event samples May 29<sup>th</sup> 2016 : E2905</p> <p>Table S27B displays results from the rain event samples June 01<sup>st</sup> 2016 : E0106</p> <p>Table S27C displays results from the rain event samples June 24<sup>th</sup> 2016 : E1306</p> <p>Table S27D displays results from the rain event samples June 13<sup>th</sup> 2016 : E2406</p> <p>Table S27E displays results from the rain event samples July 13<sup>th</sup> 2016 : E1307</p> <p>Table S27F displays results from the rain event samples September 17<sup>th</sup> 2016 : E1709</p> <p>Chemical analysis of the water samples was performed by liquid chromatography (UltiMate 3000 LC system (Thermo Scientific)) coupled to high resolution mass spectrometry (Q Exactive Plus, Thermo Scientific) with a heated electrospray ionization (HESI) source. Nontarget screening was performed as it allows for a comprehensive characterization of the chemical exposure during heavy rain events. However, only annotated target compounds and unknown compounds identified by structure elucidation are presented in the table. Details on data evaluation methods are described in Chapter 4 of the PhD thesis.</p> <p>Beckers, L.M. (2019): Novel approaches to identify drivers of chemical stress in small rivers. RWTH Aachen University, Aachen.</p>
CCE LTER process cruise, in the California Current region, event log records including date, time, position and activity for use in post-cruise data integration based on co-sampling indexes. From 2006 to 2019 CCE LTER used a locally developed event logging system. During P2107, CCE LTER started to utilize the R2R Event Logger on UNOL ships, 2006 - 2024 (ongoing).
The event logger program developed and maintained by the California Cooperative Oceanic Fisheries Investigations, SIO, program is used aboard CCE LTER process cruises to create indexes with temporal, spatial and activity information for post-cruise data integration. The event log is configured aboard the ship for the recording of sampling events by both ship crew personnel on the bridge, and research personnel in the lab. The event log is processed post-cruise to correct for various errors.
Marine Mammal Survey, Sightings and Sampling Event Log at Palmer Station, Antarctica, 2020-2024
Seasonal sea ice-influenced marine ecosystems at both poles are characterized by high productivity concentrated in space and time by local, regional, and remote physical forcing. These polar ecosystems are among the most rapidly changing on Earth. The PALmer (PAL) LTER seeks to build on three decades of long-term research along the western side of the Antarctic Peninsula (WAP) to gain new mechanistic and predictive understanding of ecosystem changes in response to disturbances spanning long-term, subdecadal, and higher-frequency “pulses” driven by a range of processes, including long-term climate warming, natural climate variability, and storms. These disturbances alter food-web composition and ecological interactions across time and space scales that are not well understood. We seek to determine the differential effects of disturbance and resilience on krill predators with different life histories, foraging behaviors, and demographic patterns. Specifically, changes in foraging behavior can affect adult fitness, body condition, and reproductive rates, as well as offspring survival. Preliminary analyses suggest mean chick fledgling mass decreases later in the austral summer as storm disturbances increase. If storms are not a factor influencing chick mass, parental effects or ecosystem phenology may play a larger role. For whales, changes in foraging effort and increases in body condition should correlate with increased pregnancy rates. We will test for linkages between whale foraging efficiency related to storms with female pregnancy rates the following year. Our prediction is that in seasons with more storms and poorer foraging conditions, fewer whales will become pregnant. However, as whales are long-lived, we predict this will not have a major effect on the long-term positive population trend. We will contribute fundamental understanding of how population dynamics and physiological processes are responding within a polar marine ecosystem undergoing profound change
Peak Flow Event Durations in the Mississippi River Basin and Implications for Temporal Sampling of Rivers
<p><strong>Corresponding peer-reviewed publication</strong></p> <p>This repository corresponds to all the input and output files that were used in the study reported in:</p> <ul> <li>Cerbelaud, A., David, C. H., Biancamaria, S., Wade, J., Tom, M., Prata de Moraes Frasson, R., & Blumstein, D. (2024). Peak flow event durations in the Mississippi River basin and implications for temporal sampling of rivers. Geophysical Research Letters, 51, e2024GL109220. <a href="https://doi.org/10.1029/2024GL109220" target="_blank" rel="noopener">https://doi.org/10.1029/2024GL109220</a>.</li> </ul> <p>When making use of any of the output files of this dataset, please cite both the aforementioned article and the dataset herein. </p> <p><strong>Main goals of the publication</strong></p> <p>The corresponding work aims to quantify peak flow event durations at an hourly time scale and their impact on high-frequency river sampling requirements using sampling ratios. The analysis is performed over the Mississippi basin using hourly USGS gages over 2010-2022.</p> <p>The findings derived from these output files have direct implications for future satellite missions concerned with capturing high-frequency dynamics in rivers, including flood events.</p>
Sampling-event dataset of short-term monitoring in Poblacion and Kadurong Reefs in Liloan, Cebu, Philippines
<p>This is a sampling-event dataset of the short-term monitoring of Poblacion and Kadurong Reefs, two of the marine protected areas Municipality of Liloan, Cebu, Philippines. Water quality and ecological assessments were carried out to monitor the status and trends of biological and physical parameters associated with coral reefs using the standard protocols for surveying tropical marine resources. Specifically, the following measurements were conducted: (1) physico-chemical parameters, (2) phytoplankton and zooplankton occurrence and abundance, (3) fish occurrence and density, and (4) percent cover of benthic components of coral reef. The data can serve as the basis for the formulation and implementation of relevant measures for conservation and protection management of the Poblacion and Kadurong Reefs in Liloan, Cebu, Philippines. </p> <p>In this version, occurrence.csv was revised as described below:</p> <ul> <li>TaxonID for <em>Abudefduf vaigiensis</em> (Quoy & Gaimard, 1825) and <em>Hemiaulus</em> P.A.C. Heiberg, 1863 were corrected.</li> <li>Author names with corrupted characters/symbols were corrected. </li> </ul> <p> </p>
Stream sampling for total suspended solids (TSS), volatile suspended solids (VSS), and chemistry during storm events at the Coweeta LTER intensive and hillslope sites in Macon County, NC.
Stream storm samples were collected at 21 streams and rivers in Macon County, NC. Nine intensive sites were monitored in 2010-2011, nine hillslope sites were monitored in 2012-2013, and three river sites were monitored from 2010-2013. An ISCO water sampler was used to collect stream water samples during storm events. Water samples were analyzed at the Coweeta Analytical Lab.
MadGraph proton pair to top pair sample dataset (100 events)
<p>This is a small dataset for the purpose of code testing and examples with the HEP + ML packages produced to aid the research at the University of Southampton.</p>
Environmental data at the sampling event level collected with Inline instruments, almanach, models and satellites during the Tara Pacific Expedition 2016-2018
<p>The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples. The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide at the sampling event level, the environmental data originating from all instruments acquiring continuously during the full course of the campaign. This dataset is augmented with the addition of variables originating from almanach (local sun/moon set/rise, local zenith), from operational models obtained from Copernicus Marine Services, but also <strong>f</strong>rom satellite imagery (MODIS-AQUA satellite - Level 3 mapped product, 8 day average, 4km resolution) at <a href="https://oceandata.sci.gsfc.nasa.gov">https://oceandata.sci.gsfc.nasa.gov</a>. The zone corresponding to the station position and date was recovered either by taking a two pixel buffer around the given location (total zone being a 5 by 5 pixels square of 20 km side) and in order to propose an alternative measure in the inevitable case where clouds were present an alternative 12 pixels buffer was taken (total zone being a 25 by 25 pixels square of 100 km side). All data were provided as mean, standard deviation (sd) together with 0.05, 0.25, 0.5, 0.75 and 0.95 quartiles</p>
Text-fig. 2. Studied section in Jirásek's Quarry with essential data on lithology and samples studied on rhynchonelliform brachiopods and trilobites (black dots – productive, white dots – barren). in Rhynchonelliform Brachiopods And Trilobites Of The 'Upper Dark Interval' In The Koněprusy Area Devonian, Eifelian, Kačák Event; The Czech Republic
Text-fig. 2. Studied section in Jirásek's Quarry with essential data on lithology and samples studied on rhynchonelliform brachiopods and trilobites (black dots – productive, white dots – barren).
Sampling Rare Event Energy Landscapes via Birth-Death Augmented Dynamics
<p>Archive with data supporting the paper "Sampling Rare Event Energy Landscapes via Birth-Death Augmented Dynamics" and the related PhD thesis by B. Pampel</p>
Data from: Improved transcriptome sampling pinpoints 26 ancient and more recent polyploidy events in Caryophyllales, including two allopolyploidy events
• Studies of the macroevolutionary legacy of polyploidy are limited by an incomplete sampling of these events across the tree of life. To better locate and understand these events, we need comprehensive taxonomic sampling as well as homology inference methods that accurately reconstruct the frequency and location of gene duplications. • We assembled a dataset of transcriptomes and genomes from 169 species in Caryophyllales, of which 43 were newly generated for this study, representing one of the densest sampled genomic-scale datasets available. We carried out phylogenomic analyses using a modified phylome strategy to reconstruct the species tree. We mapped phylogenetic distribution of polyploidy events by both tree-based and distance-based methods, and explicitly tested scenarios for allopolyploidy. • We identified twenty-six ancient and more recent polyploidy events distributed throughout Caryophyllales. Two of these events were inferred to be allopolyploidy. • Through dense phylogenomic sampling, we show the propensity of polyploidy throughout the evolutionary history of Caryophyllales. We also provide a framework for utilizing transcriptome data to detect allopolyploidy, which is important as it may have different macro-evolutionary implications compared to autopolyploidy.
Neutral-current DIS event samples at leading order with $E_e = 27.5\,{\rm GeV}$, $E_p = 920\,{\rm GeV}$, and $\mu_{\rm F}^2 = \mu_{\rm R}^2 = \frac{1}{2}(Q^2+H_{\rm T}^2)$
<p>Neutral-current DIS multi-jet event samples at parton level in the HDF5 event format.</p> <p>Beam energies: $E_e = 27.5\,{\rm GeV}$, $E_p = 920\,{\rm GeV}$</p> <p>Renormalisation and factorisation scale: $\mu_{\rm F}^2 = \mu_{\rm R}^2 = \frac{1}{2}(Q^2 + H_{\rm T}^2)$ with seven-point scale variation</p> <p>PDF: NNPDF40_lo_pch_as_01180</p> <p>Generation cuts: $Q^2 > 2\,{\rm GeV}^2$, $k_{\rm T} > 2\,{\rm GeV}$ in the $k_{\rm T}$-algorithm with $D=1.0$</p> <p>Generated with <a href="https://gitlab.com/hpcgen/me" target="_blank" rel="noopener">Sherpa</a> using the run cards below.</p>
Neutral-current DIS event samples at leading order with $E_e = 27.5\,{\rm GeV}$, $E_p = 820\,{\rm GeV}$, and $\mu_{\rm F}^2 = \mu_{\rm R}^2 = \frac{1}{2}(Q^2+H_{\rm T}^2)$
<p>Neutral-current DIS multi-jet event samples at parton level in the HDF5 event format.</p> <p>Beam energies: $E_e = 27.5\,{\rm GeV}$, $E_p = 820\,{\rm GeV}$</p> <p>Renormalisation and factorisation scale: $\mu_{\rm F}^2 = \mu_{\rm R}^2 = \frac{1}{2}(Q^2 + H_{\rm T}^2)$ with seven-point scale variation</p> <p>PDF: NNPDF40_lo_pch_as_01180</p> <p>Generation cuts: $Q^2 > 2\,{\rm GeV}^2$, $k_{\rm T} > 2\,{\rm GeV}$ in the $k_{\rm T}$-algorithm with $D=1.0$</p> <p>Generated with <a href="https://gitlab.com/hpcgen/me" target="_blank" rel="noopener">Sherpa</a> using the run cards below.</p>
Neutral-current DIS event samples at leading order with $E_e = 27.5\,{\rm GeV}$, $E_p = 920\,{\rm GeV}$, and $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$
<p>Neutral-current DIS multi-jet event samples at parton level in the HDF5 event format.</p> <p>Beam energies: $E_e = 27.5\,{\rm GeV}$, $E_p = 920\,{\rm GeV}$</p> <p>Renormalisation and factorisation scale: $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$ with seven-point scale variation</p> <p>PDF: NNPDF40_lo_pch_as_01180</p> <p>Generation cuts: $Q^2 > 2\,{\rm GeV}^2$, $k_{\rm T} > 2\,{\rm GeV}$ in the $k_{\rm T}$-algorithm with $D=1.0$</p> <p>Generated with <a href="https://gitlab.com/hpcgen/me" target="_blank" rel="noopener">Sherpa</a> using the run cards below.</p>
Neutral-current DIS event samples at leading order with $E_e = 27.5\,{\rm GeV}$, $E_p = 820\,{\rm GeV}$, and $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$
<p>Neutral-current DIS multi-jet event samples at parton level in the HDF5 event format.</p> <p>Beam energies: $E_e = 27.5\,{\rm GeV}$, $E_p = 820\,{\rm GeV}$</p> <p>Renormalisation and factorisation scale: $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$ with seven-point scale variation</p> <p>PDF: NNPDF40_lo_pch_as_01180</p> <p>Generation cuts: $Q^2 > 2\,{\rm GeV}^2$, $k_{\rm T} > 2\,{\rm GeV}$ in the $k_{\rm T}$-algorithm with $D=1.0$</p> <p>Generated with <a href="https://gitlab.com/hpcgen/me" target="_blank" rel="noopener">Sherpa</a> using the run cards below.</p>
Physical features for small sample of data (1000 events per class)
<p>These repository contains physical features extracted from four classes - <br>1) Earthquake, 2) Explosions, 3) Noise, 4) Surface events. <br><br>Each waveform is of 40s (P-10, P+30). <br>tapered 10%<br>bandpass filtered (0.5 - 15 Hz)<br>normalized by max. </p>
Higgs + jets event samples at next-to-leading order QCD at 14 TeV
<p>Higgs plus multi-jet event samples at parton level in HDF5 event format</p> <p><span class="math-tex">\(\sqrt{s}=14\,{\rm TeV}\)</span></p> <p><span class="math-tex">\(m_H=125\,{\rm GeV}\)</span></p> <p><span class="math-tex">\(\mu_R=\mu_F=\frac{1}{2}\Big(m_{\perp,H}+\sum_{jets}p_{\perp,j}\Big)\)</span></p> <p>Generated with <a href="https://gitlab.com/hpcgen/me">Sherpa</a> using the attached setup files</p> <p>Files can be filtered and merged using the <a href="https://gitlab.com/shoeche/lheh5-reader">tools provided on GitLab</a></p>
Higgs + jets event samples at leading-order QCD at 14 TeV
<p>Higgs plus multi-jet event samples at parton level in HDF5 event format</p> <p><span class="math-tex">\(\sqrt{s}=14\,{\rm TeV}\)</span></p> <p><span class="math-tex">\(m_H=125\,{\rm GeV}\)</span></p> <p><span class="math-tex">\(\mu_R=\mu_F=\frac{1}{2}\Big(m_{\perp,H}+\sum_{jets}p_{\perp,j}\Big)\)</span></p> <p>Generated with <a href="https://gitlab.com/hpcgen/me">Sherpa</a> using the attached setup files</p> <p>Files can be filtered and merged using the <a href="https://gitlab.com/shoeche/lheh5-reader">tools provided on GitLab</a></p>
VBF Higgs + jets event samples at leading order QCD at 14 TeV
<p>VBF Higgs plus multi-jet event samples at parton level in HDF5 event format</p> <p><span class="math-tex">\(\sqrt{s}=14\,{\rm TeV}\)</span></p> <p><span class="math-tex">\(m_H=125\,{\rm GeV}\)</span></p> <p><span class="math-tex">\(\mu_R=\mu_F=\frac{1}{2}\Big(m_{\perp,H}+\sum_{jets}p_{\perp,j}\Big)\)</span></p> <p>Generated with <a href="https://gitlab.com/hpcgen/me">Sherpa</a> using the attached setup files</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.