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2,516 results for “Seri”
SYNOPSIS OF SPECIES WITH PAGE AND PLATE REFERENCES. in New genera and species from the Belly River Series (mid-Cretaceous)
SYNOPSIS OF SPECIES WITH PAGE AND PLATE REFERENCES.
Time series of gas, particle, and environmental variables measured at the Mäkelänkatu urban street canyon site in May 2017
<p>Time series data of gas, particle, and environmental variables measured at the Mäkelänkatu urban street canyon site, in Helsinki, Finland, in May 2017.</p>
BIR-MicroED: TEM image series revealing bend contour motion in static microcrystals (biotin, Zn(II)-methionine, Co(II)-porphyrin, AVAAGA) and diffraction patterns acquired from the same crystals at 200 kV
<p>This deposition contains a series zip files each containing TEM image series and electron diffraction images in .mrc file format. Each folder collects data acquired from crystals of a particular compound under the same conditions (electron energy, temperature). Zip files are named according to the format: <em>"CompoundName</em>_bendcontour_imageseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>.zip"</p> <p>Data is further divided into sub-directories according to the particular crystal studied (crystal1, crystal2, crystal3), each containing a TEM image series (name format: "<em>CompoundName</em>_static_imageseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>_crystal#.mrc") and 10 diffraction snapshots (2 frames each, each convering 1 second of electron beam exposure) acquired at equally spaced time intervals throughout the image series. These are named according to the format:</p> <p>"CompoundName_bendcontour_crystal#_diffraction_snap#.mrc"</p>
Smithsonian Contributions Series: Smithsonian Contributions to Zoology
<p></p>https://repository.si.edu/handle/10088/796<p></p><p></p>https://repository.si.edu/handle/10088/5097/browse?type=dateissued
Data package for paper "Transformer models for astrophysical time series and the GRB prompt-afterglow relation"
<p>This is a data package accompanying the paper "Transformer models for astrophysical time series and the GRB<br>prompt-afterglow relation". The code used to acquire the data is in the "data" folder. The code used to analyse the data is in the "analysis" folder.</p> <p>DOI paper: <a href="https://doi.org/10.1093/rasti/rzae026">10.1093/rasti/rzae026</a></p>
New Zealand coastal station sea temperature time series
<p>The following two tables are the daily observations and model output of coastal water temperature analyzed in Souza et al., 2022 (displayed in Figure 13). The first column in both tables are the time in MATLAB datenum format. The subsequent 10 columns are daily temperature values from the following stations with lat/lon information:</p> <p> {'Ahipara' -35.1667 173.1000}<br> {'Leigh' -36.2693 174.7984}<br> {'Moturiki' -37.6330 176.1830}<br> {'Tauranga' -37.6980 176.6160}<br> {'Newplymouth' -39.0500 174.0330}<br> {'Napier' -39.4830 176.9167}<br> {'Evans' -41.3000 174.8000 }<br> {'Lytleton' -43.6330 172.9000 }<br> {'Portobello' -45.8160 170.6500}<br> {'Bluff' -46.6000 168.3000 }</p> <p>Missing data are marked with the value -999. Further observation and station details and quality control procedures are described in the technical data report, Chiswell, S. M. and Grant, B.: New Zealand Coastal Sea Surface Temperature, Tech. rep., National Institute of Water & Atmospheric Research, 2019 </p> <p> </p> <p>We acknowledge the contribution of professional, technical and academic staff from NIWA, University of Otago and University of Auckland who have maintained the coastal SST records and made these available for model validation purposes</p>
"Toy Data Set" referenced in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (https://doi.org/10.1101/2024.08.22.609110)
<p>This data set, referenced as "toy data set" in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (<a href="Lint-to-article">https://doi.org/10.1101/2024.08.22.609110</a>), mimics a high-throughput screening data set. To demonstrate the application of our analysis framework described in the main article this toy data set was generated. It contains in total 1536000 individual transient signals, splitted in 5 batches of each 200 plates in 1536-well plate format. Five distinct signal classes were used to resemble typical shapes encountered in biological experiments. Fequency of occurrences for each class is reported in the main article.</p>
Fig. 1 in Post-extinction brachiopod faunas from the Late Permian Wuchiapingian coal series of South China
Fig. 1. Generalized map showing the locations of the Daijiagou and Chuanmu sections.
Fig. 4 in Post-extinction brachiopod faunas from the Late Permian Wuchiapingian coal series of South China
Fig. 4. Reconstruction of the Edriosteges poyangensis–Spinomarginifera lopingensis Association.
Displacement time series from Foamquake and Gelquake in single- and double asperity configurations: Supplementary material to "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory"
<p><span>This dataset includes displacement data from 4 experiments performed with Foamquake and Gelquake (Mastella et al. 2022, Corbi et al., 2013), two scaled seismotectonic models reproducing the megathrust seismic cycle running at the Laboratory of Experimental Tectonics LET (Univ. Roma Tre). These models enable the generation of hundreds of quasi-periodic cycles of stress accumulation and sudden release through the spontaneous nucleation of frictional instabilities within one or many analog seismic asperities. Models are monitored by the means of a high-resolution top-view monitoring camera acquiring images at 7.5 and 50 frames per second for Gelquake and Foamquake, respectively. This dataset has been created with particle image velocimetry (PIV, using MatPIV (Sveen 2004)) through the cross-correlation between consecutive images. The PIV provides us with velocity field time series. These are integrated to obtain displacement time series. From the whole model surface, in each experiment we selected data from a cross-section striking parallel to the trench and located at the downdip center of the asperities. Cross sections are discretized in 28 and 29 target points in Gelquake and Foamquake, respectively. </span></p> <p><span>Displacement time series have been normalized to zero mean and unit variance to ensure the same level of magnitude for comparison between different experiments. Linear and second order polynomial trends have been removed to make the stick-slip confined in a given range and avoid non-stationary behavior. Time series data are not passed through filters (e.g., smoothing or moving average).</span></p> <p><span>Filename informs about the nature of the analog upper plate (i.e., foam and gel) and geometrical configuration of asperities (i.e., mono and twin). Together with individual files for each experiment, this dataset includes a Matlab script (i.e., all_timeseries.m) that allows visualization of displacement time series from individual target points. </span></p> <p><span>This dataset is supplementary to the paper in SEISMICA "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory” by Corbi et al. (2024), where detailed descriptions of models and experimental results can be found.</span></p>
Pressure time series for waves on shelf
<div> <div>Time: in UTC</div> <div> <div>Position 29.4412 -92.0613</div> </div> <div> <div>Platform CSI 3</div> <div>Station ioos:station:WAVCIS:CSI03</div> <div>Description Marsh Island, LA</div> <div>Units: Pressure (dbar); Sea Pressure (dbar); depth (m)</div> </div> <div>Instrument: RBRvirtuoso pressure sensor</div> <div>Data type: 4Hz ASCII data directly converted from the raw data with no additional user processing.</div> <div>PI: Chunyan Li</div> <div>Funded by NSF (1736713)</div> <div> </div> </div> <p> </p>
Covalent labelling of FabF and FabB by cerulenin and a small series of synthesized compounds
<p><a href="../api/records/13739774/draft/files/FabF,%20FabB%20covalent%20labelling%20of%20selected%20compounds.txt/content" target="_blank" rel="noopener noreferrer">FabF, FabB covalent labelling of selected compounds.txt</a> contains raw data of covalent labelling of the <em>P. Aeruginosa</em> enzymes (FabF wild type (WT), "mut" = FabF C164A, FabB wild type (WT) and "mut" = FabB C161A) by cerulenin and a small set of synthesized compounds. The identity of the compounds in the .txt file can be found in <a href="../api/records/13739774/draft/files/Selected%20compounds.cdx/content" target="_blank" rel="noopener noreferrer">Selected compounds.cdx</a>.</p>
GPS position time series data for the Tatun Volcano Group (TVG) region
<p>GPS Time Series Data Used in "Transient Deformation in the Tatun Volcano Group, Taiwan: A Spatiotemporal GPS Analysis" by Chang et al.:</p> <p>1. Time series data of six GPS stations in TVO (YM03, YM05, YM06, YM07, YMN4, and YMSM, see Figure 1 of the main text) are included in the zip file "tvo.final_igb14.pos.tar.gz".</p> <p>2. The files are in plain text with the stardard PBO data format (https://www.unavco.org/data/gps-gnss/derived-products/docs/knowledgetree-docs-old/gps_timeseries_format.pdf), which is also listed and explained at the top of each file.</p>
Current and Voltage for a Series-Parallel Configurations of Piezoelectric Transducers Dataset
<p>The piezoelectric elements used are arranged in two test configurations for the experiments: a series electrical connection of two units and a parallel electrical connection of two units, while remaining mechanically isolated. It is important to emphasize that although the elements are electrically connected, they are not mechanically coupled. Data collection focuses on two input variables—oscillation frequency and load resistance—with the output being the voltage across the piezoelectric elements and the current through the load. The experiments involve frequency sweeps from 0 to 200 Hz in 1 Hz increments and load resistance sweeps, fixed at 5 k<span><span>Ω</span></span> and ranging from 10 k<span><span>Ω</span></span> to 300 k<span><span>Ω</span></span>.</p> <div> <div> <div> <div> <p><span>The currents and voltages obtained from the measurement of the piezoelectric elements are included, as well as the frequency and resistance values. Finally, a test.m file is included in which the data from one of the sets can be viewed.</span></p> </div> </div> </div> </div>
FAN-GHETS24: A Flying Ad Hoc Network Dataset for Early Time Series Classification of Grey Hole Attacks
<p>Flying ad-hoc networks (FANETs) consist of multiple unmanned aerial vehicles (UAVs) that rely on multi-hop routes for communication. These routes are particularly susceptible to grey hole attacks, necessitating swift and accurate defense to preserve the network's quality of service. This novel dataset, FAN-GHETS24, is designed for early time series classification of various grey hole attack scenarios. The dataset is derived from sequences of packet interactions between UAVs within the network, generated through multiple simulations. These sequences undergo post-processing via two methods: firstly, an anonymization procedure that replaces IP addresses with standard string variables, allowing for offline model training and universal deployment across UAVs; and secondly, the application of feature engineering techniques to format the data for machine learning model integration.</p> <div> <div>The dataset is split across several zip files, combine and extract them by issuing these command:</div> </div> <div> <div>$ zip -FF fan-ghets24.zip --out fan-ghets24-combined.zip</div> <div>$ unzip fan-ghets24-combined.zip</div> </div>
Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing
<p>This Zenodo record contains the dataset and model weights for "Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing".</p> <p> </p> <p>This repository contains the following files:</p> <ul> <li> <p>For the human dataset by Wang et al.:</p> <ul> <li> <p>train_val_test_split.csv containing the mapping of the correct peptide by MaxQuant to either train, validation or test set</p> </li> <li> <p>psms_train_val_test.csv containing the mapping of correct PSMs (scan number, raw file and correct peptide by MaxQuant) to either train, validation or test set</p> </li> <li> <p>updated_spectralis_test_out.csv as before containing Spectralis-EA predictions and scores on test set, as well as initial peptides and scores by Casanovo and Novor and now containing also correct peptides by MaxQuant and Spectralis-scores on the combination of Casanovo and Novor sequences (column named spectralis_score_onlyRescoring)</p> </li> <li> <p>spectralis_test_out_heart_analysis.csv subset of 20220822_spectralis_test_out.csv containing only PSMs for the tissue heart with the computation of precision and recall values</p> </li> <li> <p>spectralis_test_out_pointnovo_deepnovo.csv containing predictions by DeepNovo and PointNovo with original scores and Spectralis-score, as well as correct peptides by MaxQuant</p> </li> </ul> </li> </ul> <p> </p> <ul> <li> <p>For the nine-species dataset by Tran et al.:</p> <ul> <li> <p>spectralis_ninespecies_out.csv containing spectrum identifiers, correct peptides by PEAKSDB, predicted peptides by the different de novo sequencing tools as well as original scores and Spectralis-scores for the different PSMs.</p> </li> </ul> </li> </ul>
A Series of (Bis)bathocuproine Cobalt Complexes
<p>The follwoing collection contains the cartesian coordinates of the calculated structures and the energies obtained by DFT-calculations. Please cite the original source/paper.</p>
Time series transcriptomes resolve metabolic pathways underlying crocin's anti-cancer activity | Dataset: sequencing reads (2,6,12,24 hr crocin treatments)
<p><span>Natural products like saffron show promise in treating hepatocellular carcinoma (HCC), but their mechanisms remain unclear. Here, we used time-series transcriptomics to elucidate crocin's anti-cancer mechanisms in HCC cells. We treated HepG2 cells with 1 and 2 mM crocin for 2, 6, 12, and 24 hours and analyzed transcriptomic profiles at each timepoint. The strongest transcriptional response occurred at 2 hours with 1 mM crocin, with diminishing effects at later timepoints. We observed upregulation of metabolic-, adhesion-, and endocytosis-related genes across all timepoints. Pathway analysis revealed activation of DNA damage checkpoints and senescence while proliferation pathways were suppressed. Notably, 52 genes involved in non-alcoholic fatty liver disease were downregulated at 24 hours (FDR p = 8 × 10⁻⁸), suggesting reversal of carcinogenic pathways. Strikingly, crocin consistently downregulated spliceosomal machinery genes across all timepoints while upregulating senescence and autophagy pathways. This spliceosome targeting represents a clinically relevant mechanism, as aberrant splicing drives oncogenesis in more than 90% of cancers. The transcription factor PAX5 was significantly upregulated while oncogenic ELK1 targets were downregulated. Our findings show that crocin treatment is accompanied by HCC cell senescence induction through coordinated spliceosome disruption and metabolic reprogramming, providing novel therapeutic targets for hepatocellular carcinoma.</span></p> <p><strong><span>Keywords: </span></strong><span>Hepatocellular carcinoma (HCC), crocin, transcriptomics, spliceosome, senescence, natural anti-cancer compounds</span></p>
Hall-Littlewood polynomials, affine Schubert series, and lattice enumeration
<p>Data accompanying the paper <em>J. Maglione, C. Voll, Hall-Littlewood polynomials, affine Schubert series, and lattice enumeration. <a href="https://arxiv.org/abs/2410.08075">https://arxiv.org/abs/2410.08075</a></em></p>
A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu
<p>Lake Taihu has a history of recurrent harmful cyanobacterial blooms under the pressures of climate change and human activities. Despite efforts to limit nutrient loading, there is a need to better understand the water environment of Lake Taihu in order to improve methods for controlling the cyanobacterial blooms. The spatial and temporal characteristics of the water quality, bio-optical parameters, climate, and anthropogenic data of Lake Taihu (THQBCA) could provide comprehensive information regarding cyanobacterial blooms. The THQBCA dataset contains 26 variables organized into four categories: water quality, bio-optics, climate, and anthropogenic data. The dataset spans more than 15 years (8 of which cover approximately 35 years, 4 of which cover 20 years), and the spatial resolutions of the satellite-derived data range from 30 m to 500 m. The THQBCA dataset is expected to advance research on forecasting and early warning of cyanobacterial blooms, and to support science-based management decisions for sustainable ecological development.</p>
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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.