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17,474 results for “Complexes”
Data and Videos for Argos: a toolkit for tracking multiple animals in complex visual environments
<p>Original videos used and data generated for the article "Argos: a toolkit for tracking multiple animals in complex visual environments".</p> <p>The data contains original videos used as input to the Argos Tracking tool, the generated raw tracks in Pandas-HDF5 format, and the corrected tracks after processing with Argos Review tool.</p> <p>It also includes a zip archive with ground truth tracks along with tracks detected from two videos by Argos and several other tracking tools for comparison using the HOTA metric organized in a folder structure suitable for the TrackEval tool.</p>
Twitter hashtags time series used in the paper "Universality, criticality and complexity of information propagation in social media"
<pre>These files contain the time series and the associated hashtags we obtained by sampling Twitter for our paper "Universality, criticality and complexity of information propagation on social media". The analysis is reported in <a href="https://arxiv.org/abs/2109.00116">https://www.nature.com/articles/s41467-022-28964-8</a> Please acknowledge the use of these data by citing the paper above. ################################# ################################# DATA ORGANIZATION We created a single zip file with all the time series and a single zip file with all the hashtags. There is a one-to-one correspondence between lines in the two files. ################################# ################################# FILES CONTENT As stated, here is a one-to-one correspondence between lines in the time series file and lines in the hashtags file, i.e., the hashtag stored in line X is the hashtag of the time series stored in line X. Time series are stored as follows: Ka t1 t2 t3 \n Kb t1 t2 t3 t4 t5 \n . . . Kn t1 t2 \n where: Ka, Kb,..., Kn is an integer specifying the number of events that compose the time series a, b,..., n respectively. In the example above we would have Ka=3, Kb=5, Kn=2. t1 t2 ... is the time series, i.e., a sequence of chronologically ordered interevent times. The last interevent time, in our implementation, represents the distance between the end of the temporal window and the last event time. It thus does not represent an event. As stated in the Supplemental Material of our paper, the temporal window ranges from 2019, October 1st to 2019, November 30th. </pre>
CWID-hi: A Dataset for Complex Word Identification in Hindi Text
<p>This dataset was created by conducting a human intelligence test, wherein native and non-native Hindi speakers annotated words they could not understand in Hindi text. They were then asked to rank the complexity of these words along with their synonyms. A word that received an average rank of <=3 (out of 5) is labeled 1 and the word that received an average rank of >3 is labeled 0. 1 indicates complex and 0 indicates simple.</p>
Datasets for publication titled "Chiral control of spin-crossover dynamics in Fe(II) complexes"
<p>Transient absorption (TA), transient absorption anisotropy (TAA), and time-resolved circular dichroism (TRCD) datasets analyzed and interpreted in the publication titled "Chiral control of spin-crossover dynamics in Fe(II) complexes" published in Nature Chemistry under the DOI 10.1038/s41557-022-00933-0.</p>
Lineage and role in integrative taxonomy of a heterotrophic orchid complex
<p>Lineage-based species definitions applying coalescent approaches to species delimitation have become increasingly popular. Yet, the application of these methods and the recognition of lineage-only definitions have recently been questioned. Species delimitation criteria that explicitly consider both lineages and evidence for ecological ‘role’ shifts provide an opportunity to incorporate ecologically meaningful data from multiple sources in studies of species boundaries. Here, such criteria were applied to a problematic group of mycoheterotrophic orchids, the <em>Corallorhiza striata</em> complex, analyzing genomic, morphological, phenological, reproductive-mode, niche, and fungal host data. A recently developed method for generating genomic polymorphism data–ISSRseq–demonstrates evidence for four distinct lineages, including a previously unidentified lineage in the Coast Ranges and Cascades of California and Oregon, USA. There is divergence in morphology, phenology, reproductive mode, and fungal associates among the four lineages. Integrative analyses, conducted in population assignment and redundancy analysis frameworks, provide evidence of distinct genomic lineages and a similar pattern of divergence in the ‘extended’ data, albeit with weaker signal. However, none of the ‘extended’ datasets fully satisfy the condition of a significant ‘role’ shift, which requires evidence of fixed differences. The four lineages identified in the current study are recognized at the level of variety, short of comprising different species. This study represents the most comprehensive application of ‘lineage+role’ to date and illustrates the advantages of such an approach.</p>
Paramecium Polycomb Repressive Complex 2 physically interacts with the small RNA binding PIWI protein to repress transposable elements
<p>Polycomb Repressive Complex 2 (PRC2) maintains transcriptionally silent genes in a repressed state via deposition of histone H3 K27 trimethyl (me3) marks. PRC2 has also been implicated in silencing transposable elements (TEs), yet how PRC2 is targeted to TEs remains unclear. To address this question, we identified proteins that physically interact with the <em>Paramecium</em> Enhancer-of-zeste Ezl1 enzyme, which catalyzes H3K9me3 and H3K27me3 deposition at TEs. We show that the <em>Paramecium</em> PRC2 core complex comprises four subunits, each required <em>in vivo</em> for catalytic activity. We also identify PRC2 cofactors, including the RNA interference (RNAi) effector Ptiwi09, which are necessary to target H3K9me3 and H3K27me3 to TEs. We find that the physical interaction between PRC2 and the RNAi pathway is mediated by a RING finger protein and that small RNA recruitment of PRC2 to TEs is analogous to the small RNA recruitment of H3K9 methylation SU(VAR)3-9 enzymes.</p>
Data for "Directional asymmetry and direction-giving factors: lessons from flowers with complex symmetry"
<p>These are the raw data associated with the following publication:</p> <p>Budečević, S., S. Manitašević Jovanović, A. Vuleta, B. Tucić, and C. P. Klingenberg. 2022. <strong>Directional asymmetry and direction-giving factors: lessons from flowers with complex symmetry</strong>. Evolution & Development: advance online.<br> <a href="https://doi.org/10.1111/ede.12402">https://doi.org/10.1111/ede.12402</a></p> <p><strong>Abstract: </strong>Directional asymmetry is a systematic difference between the left and right sides for structures with bilateral symmetry, or a systematic differentiation among repeated parts for complex symmetry. This study explores factors that produce directional asymmetry in the flower of <em>Iris pumila</em>, a structure with complex symmetry that makes it possible to investigate multiple such factors simultaneously. The shapes and sizes of three types of floral organs, the falls, standards, and style branches, were quantified using the methods of geometric morphometrics. For each flower, this study recorded the compass orientations of floral organs as well as their anatomical orientations relative to the two spathes subtending each flower. To characterize directional asymmetry at the whole-flower level, differences in the average sizes and shapes according to compass orientation and relative orientation were computed, and the left–right asymmetry was also evaluated for each individual organ. No size or shape differences within flowers were found in relation to anatomical position, which may relate to the terminal position of flowers in <em>Iris pumila</em>, so that there was no evidence of any adaxial–abaxial polarity (which is very prominent in many other taxa). There was clear directional asymmetry of shape in relation to compass orientation, presumably driven by a consistent environmental gradient such as solar irradiance. There was also clear directional asymmetry between left and right halves of every floral organ, most likely related to the arrangement of organs in the bud. These findings indicate that there are different factors acting to produce directional asymmetry at different levels. In conventional analyses, these effects would be impossible to disentangle from each other and would probably be included as part of fluctuating asymmetry.</p> <p><strong>Data included</strong></p> <p>This data set includes landmark data for the falls, standards, and style branches of flowers of <em>Iris pumila</em>, as well as information about the compass orientation of each flower part, the compass orientation of the outer spathe of the respective flower, and the orientation of the flower part relative to the outer spathe, as described in the paper.</p> <p>The plants and flowers considered in this study have been sequentially numbered specifically for this study, and the identifiers for the floral parts use this numbering system. The numbers are consistent between the different flower parts included in the study.</p> <p>Files included:</p> <p><strong>fall_coord.txt</strong>: Landmark coordinates for the falls. The landmark coordinates are presented in the order X, Y, X, Y,… on a single line for each flower part. The first entry on each line is the identifier for the respective flower part.</p> <p><strong>fall_orient.txt</strong>: Information on orientations for the falls. For each fall, this file includes the number of the plant, the number of the flower, the compass orientation of the flower part, the compass orientation of the outer spathe of the respective flower, and the orientation of the flower part relative to the outer spathe. The identifiers (first entry of each line) are the same as in the file fall_coord.txt and can be used for matching the information.</p> <p><strong>standard_coord.txt</strong>: Landmark coordinates for the standards. The landmark coordinates are presented in the order X, Y, X, Y,… on a single line for each flower part. The first entry on each line is the identifier for the respective flower part.</p> <p><strong>standard_orient.txt</strong>: Information on orientations for the standards. For each standard, this file includes the number of the plant, the number of the flower, the compass orientation of the flower part, the compass orientation of the outer spathe of the respective flower, and the orientation of the flower part relative to the outer spathe. The identifiers (first entry of each line) are the same as in the file standard_coord.txt and can be used for matching the information.</p> <p><strong>style_coord.txt</strong>: Landmark coordinates for the style branches. The landmark coordinates are presented in the order X, Y, X, Y,… on a single line for each flower part. The first entry on each line is the identifier for the respective flower part.</p> <p><strong>style_orient.txt</strong>: Information on orientations for the style branches. For each style branch, this file includes the number of the plant, the number of the flower, the compass orientation of the flower part, the compass orientation of the outer spathe of the respective flower, and the orientation of the flower part relative to the outer spathe. The identifiers (first entry of each line) are the same as in the file style_coord.txt and can be used for matching the information.</p> <p> </p> <p>For further information, please see the associated paper. For any use of this data set, cite the dataset itself as well as the associated paper.</p> <p> </p>
Data of publication 'Optical spin-state polarization in a binuclear europium complex towards molecule-based coherent light-spin interfaces'
<p>Data of publication 'Optical spin-state polarization in a binuclear europium complex towards molecule-based coherent light-spin interfaces' by Kuppusamy Senthil Kumar et al. The two versions of Fig. 4d datasets correspond to the preprint version (https://zenodo.org/record/4905692#.Ymj9odpBxaQ) and publication version (https://www.nature.com/articles/s41467-021-22383-x), since a new set of data was taken during the review process. </p>
Single molecule videos related to "MCM complexes are barriers that restrict cohesin-mediated loop extrusion" Part 2/3
<p>Videos of cohesin translocation and collisions between translocating cohesin and MCMs under physiological salt conditions collected with MicroManager 1.4 as tif image sequences. Vidoes of DNA stained with SYTOX Orange after collection of cohesin translocation are included as separate image sequences.</p>
Single molecule videos related to "MCM complexes are barriers that restrict cohesin-mediated loop extrusion" Part 1/3
<p>Videos of collisions between translocating cohesin and MCMs under high salt conditions collected with MicroManager 1.4 as tif image sequences. Vidoes of DNA stained with SYTOX Orange after collection of cohesin translocation are included as separate image sequences.</p>
Single molecule videos related to "MCM complexes are barriers that restrict cohesin-mediated loop extrusion" Part 3/3
<p>Videos of collisions between translocating cohesin and MCM containing the YDF motif under physiological salt conditions collected with MicroManager 1.4 as tif image sequences. Videos of DNA stained with SYTOX Orange after collection of cohesin translocation are included as separate image sequences.</p>
Model output and analysis scripts for "High-latitude precipitation as a driver of multicentennial variability of the AMOC in a climate model of intermediate complexity"
<p>Here, we provide annually averaged model output from a 3000-year control simulation of PlaSim–LSG, a climate model of intermediate complexity. Processed variables and a Jupyter notebook to reproduce all figures of the manuscript (Mehling et al.: "High-latitude precipitation as a driver of multicentennial variability of the AMOC in a climate model of intermediate complexity") can also be found in this repository.</p> <p>In addition, a Python implementation of the three-box model proposed in the manuscript can be found in the notebook <em>boxmodel.ipynb</em>.</p>
The Tracing Convective Momentum Transport in Complex Cloudy Atmospheres Experiment - Level 1
<p>The first field campaign from the Tracing Convective Momentum Transport in Complex Cloudy Atmospheres experiment project (CMTRACE) took place in Cabauw, the Netherlands, between September 13th and October 3rd 2021. During this field campaign, two cloud radars and one wind lidar were operated with a similar scanning strategy for deriving wind speed and direction profiles from near the surface up to cloud tops. Here we provide the daily Level 1 data from each instrument. At this level, several processing steps were applied to the raw data to minimize offsets, reduce the number of spurious data and derive wind speed and direction profiles; however, the data from each instrument is kept on its original spatial and temporal resolution. The raw data is available for the users on request from the corresponding author.</p> <p><strong>Prefix identificaiton:</strong></p> <p>Lidar data: cmtrace_cabauw_wls200-218<br> Scanning radar data: cmtrace_cabauw_rpg_radar_35-94<br> Vertically pointing radar data: cmtrace_cabauw_rpg_radar_94</p> <p> </p>
Channeling: a new class of dissolution in complex porous media
<p>ModelAandBGeometries.7z contains the original 12,000 x 12,000 pixel geometries created for Models A and B in Menke et al. 2022 PNAS. They were subsequently binned by 12 in each direction and padded by 2 on all sides to get the 1,004 x 1,004 pixel geometries input into GeoChemFoam. The original location and radius of each bead is supplied in the .hdf5 file as 'rad', 'x_coor', and y_coor'. </p> <p>ModelA_Pe##_K##.hdf5 and ModelB_Pe##_K##.hdf5 contain all of the simulation results for each flow and reaction scenario. This includes porosity, permeability, time_s, concentration, velocity, pores, grains, throats, and moments for all output timesteps. Pore2 & throat2 denote analyses with the fully dissolved section of the model excluded. </p> <p>The model (GeoChemFoam) used to run these dissolution scenarios can be downloaded with tutorials at https://github.com/GeoChemFoam/. The script used to make the micromodel geometries can be found at https://github.com/hannahmenke/PNAS2022.</p>
Synthetic cryo electron microscopy single particle images containing biomolecular complexes with continuous conformational variability used for validating DeepHEMNMA method and validation results
<p>This archive contains a synthetic dataset used for validating DeepHEMNMA method and the validation results. DeepHEMNMA is a deep learning extension of HEMNMA approach for analyzing continuous conformational variability of biomolecular complexes in cryo electron (cryo-EM) microscopy single particle images. We provide a training set of 20,000 images and an inference set of 50,000 images. The training images were used (1) to estimate the conformational and rigid-body parameters with HEMNMA and (2) to train the neural network using the parameters previously estimated with HEMNMA (the file with the HEMNMA-estimated parameters is provided). The inference images were used to infer the parameters with the trained neural network. Also, we provide (1) the input PDB structure, its normal modes, and the conformational and rigid-body parameters used to synthesize the 20,000 training images (ground-truth parameters) and (2) the conformational and rigid-body parameters inferred from the set of 50,000 inference images.</p> <p>The DeepHEMNMA method and the method for synthesizing images have been fully described in the following article: "Hamitouche I and Jonic S (2022), DeepHEMNMA: ResNet-based hybrid analysis of continuous conformational heterogeneity in cryo-EM single particle images. Front Mol Biosci 9, 965645. <a href="https://doi.org/10.3389/fmolb.2022.965645">https://doi.org/10.3389/fmolb.2022.965645</a> (in press)". Additionally, this article describes a test of DeepHEMNMA using one experimental cryo-EM dataset (available in EMPIAR database under the accession code EMPIAR-10016). </p>
Electronic Supporting Information for Catalytic Ammonia Oxidation to Dinitrogen by a Nickel Complex
<p>The dataset provides electronic supporting information in the format of XYZ molecular files, formatted Gaussian checkpoint files, and cube files for atomic spin density distributions for selected complexes obtained while investigating the catalytic mechanism of ammonia oxidation to dinitrogen using a N-heterocyclic carbene containing nickelocene complex.</p> <p>The level of theory used for all calculations is omega-B97xD with def2TZVP basis set. All calculations were performed using the Gaussian16 suite of programmes.</p> <p><strong>Model Set 1</strong> contains the metal free compounds and were used to calculate the overall thermodynamics of the ammonia oxidation reaction.</p> <p><strong>Model Set 2</strong> corresponds to the most truncated, in vacuo optimized structures.</p> <p><strong>Model Set 3</strong> comprises from non-truncated, realistic structures embedded in polarizable continuum model of benzene.</p> <p> </p>
Assessing the Influence of Zeolite Composition on Oxygen-Bridged Diamino Dicopper(II) Complexes in Cu-CHA DeNOx Catalysts by Machine Learning-Assisted X‑ray Absorption Spectroscopy
<ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements and related elaboration from Figures 1-4 of the corresponding article</li> <li>Files are with filename extensions: <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <p>In situ XANES and EXAFS data were collected at the BM23 beamline of the European Synchrotron Radiation Facility (ESRF, Grenoble, France) in a Microtomo reactor cell; measured Cu-CHA samples are indicated in the following with “Cu/Al”-“Si/Al” labels</p> <ul> <li><strong>fig_01_XANES:</strong> Normalized Cu K-edge XANES for Cu-CHA samples 0.1-5; 0.5-15; 0.6-29, collected at 200 °C after pretreatment in O<sub>2</sub>, reduction in NO+NH<sub>3</sub> and subsequent oxidation in O<sub>2</sub>.</li> <li><strong>fig_02_Conversion:</strong> NOx conversion in the 150−500 °C temperature range for Cu-CHA samples 0.1-5, 0.5-15, 0.6-29; TOF at 200 °C versus fraction of Cu(I) from XANES LCF after oxidation and fraction of Cu(I) from XANES LCF after oxidation versus Cu density for the same catalysts.</li> <li><strong>fig_03_EXAFS_FT_WT:</strong> Magnitude of experimental EXAFS spectra, obtained by Fourier transforming k<sup>2</sup>χ(k) spectra in the 2.4−12.0 Å<sup>−1</sup> range for Cu-CHA samples 0.1-5, 0.5-15, 0.6-29 after reduction in NO+NH<sub>3</sub> and subsequent oxidation in O<sub>2</sub>; corresponding EXAFS WT maps magnified in high-R range (2-4 Å), obtained using a Morlet WT with parameters (σ=1, η=7).</li> <li><strong>fig_04_EXAFS_MLfit:</strong> Magnitude of experimental and best fit EXAFS spectra, obtained by Fourier transforming k<sup>2</sup>χ(k) spectra in the 2.4−12.0 Å<sup>−1</sup> range for Cu-CHA samples 0.1-5, 0.5-15, 0.6-29 after oxidation in O<sub>2</sub>. Scaled components 1 ([Cu<sup>I</sup>(NH<sub>3</sub>)<sup>2</sup>]<sup>+</sup>), 2 and 3 (planar and bent μ-η<sup>2</sup>,η<sup>2</sup>-peroxo diamino dicopper(II)) isolated by ML-assisted EXAFS fitting are also reported, vertically translated.</li> <li><strong>Information on</strong>:</li> <li>specialized abbreviations: <strong>CHA</strong>– chabazite; <strong>XANES</strong>– X-ray absorption near edge structure, <strong>EXAFS</strong> – Extended X-ray absorption fine structure; <strong>LCF</strong> – Linear Combination Fit;<strong> FT</strong>: Fourier Transform; <strong>WT</strong> – Wavelet Transform; <strong>ML</strong> – Machine Learning; <strong>TOF</strong> – Turn Over Frequency;</li> </ul>
A phenomenological law for complex granular materials from Mohr-Coulomb theory
<p>The compressed directory contains the data in .csv format used for the PCA analysis for each dataset (1, 2 and 3). </p>
Reliquary of contacts for: A pragmatic approach to complex citations, closing the provenance gap between IPCC AR6 figures and CMIP6 simulations
<p>Photos and metadadata pannels of a "Reliquary of contacts for: A pragmatic approach to complex citations, closing the provenance gap between IPCC AR6 figures and CMIP6 simulations" produced to support the "A pragmatic approach to complex citations, closing the provenance gap between IPCC AR6 figures and CMIP6 simulations" presentation given at EGU 2024.</p> <p>------</p> <p>With ever growing abilities to process greater volumes of data the abiiity to sustain the citability and tracability of the underluing source data within outputs such as publications is becoming increasingly challenging. With a range of use-cases, work on how to handle complex citations from the perspective of those producing outputs, journals and those handling the knowledge graph and associated services, is exmaning a how to handle these situations in a sustainable and manageable fashion.<br><br>At the European Geophysical Union (EGU) General Assembly in Vienna, 2024, a pragmatic solution using Zenodo to store 'reliquary' objects was presented. The poster presentation demonstrated the use of existing strucutres within a Zenodo object to address the complex citation use-case around figure, the related data and the source datasets related to the IPCC's AR5 figure data. I.e. how to utulise the existing constructs of a Zenodo item and the range of available metadata fields to give an off-the-shelf solution to allow tracability to the specific datasets used (via their Handle identifiers) and citability of the higher level, DOI-ed dataset collections within which the specific Handle-ed datasets were selected from. Additionally, the connectivity between these two levels of PID objects was also captured within the stored files around which the rich metata was captured.<br><br>The concept of a complex citation 'reliquary' as a metadtata rich object, acting as a referencable nexus in the knowledge graph has been put forth as a solution to the complex citation challenge. It borrows the concept from its historical use, denoting a container or shrine, often richly embellished, for sacred relics (e.g. saints bones, artefacts etc). In the same way here we have both the rich metadata 'container' around the specific details (the 'bones in the box', with their preserved connectivity).<br><br>However, the term 'reliquary' is often a hard one to convey, being somewhat of an obscure term (likewise the term 'nexus' may also be one lacking wider recogniton). Thus, to aid the discussions around the presentation by Pascoe et al. (2024) at the EGU 2023 General Assembly, a physical representation of a metadata reliquary object was produced.<br><br>The purpose of this object was two fold:<br><br> - The first was to show how the reliquary container itself is metadata rich, detailing through the use of ORCIDS, RORs and a DOI, references to external items, complemented by further metadata concerning the specifics of the reliquary's own metadata (its title and the credit for the artist that created it). Futher more, the relationship between the reliquary and those referenced parties/objects was also captured. The contents were also used to demonstrate the importance of making the contents useful for onward users (in this case contact details on business cards). <br> - The second, and for the funder of this piece, arguably the most important aspect was a degree of outreach this provided, both to engage the audience of Pascoe et al (2024), and directly to the artist to demonstrate the importance of this work to the international research data management community and overall to aid engagemeng with the funder's work.<br><br>This resource is provided here as a repository of images of the reliquary itself and in context at the EGU 2024 event as a potential resource others may use to aid further discussions around the use of reliquaries with regards to complex citations. The slides provided of the reliquary box labels are also provided with some annotation to further expand on the metadata aspects of their content.</p>
Supplementary dataset to publication: Approaching the complexity of Crimean-Congo hemorrhagic fever virus serology: a study in swine
<p>For the detection of anti-CCHFV antibodies in swine, we established a swine-specific in-house ELISA, indirect immunofluorescence assay and a virus neutralization test. Uploaded data contains sample performance in each test. Samples used in this study include swine serum samples from Germany and Spain.</p>
ScienceDex guides
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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.