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1,880 results for “Dimensionality”
F I G U R E 9 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 9 Distribution of first observations of eels closer than 3 m from bar rack at Herting hydropower plant: (a) horizontal distribution and (b) vertical distribution. Distributions are based on 41 observed interactions with the bar rack
F I G U R E 2 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 2 (a) The intake site at the Herting hydropower plant with migration routes available during the study period: a full-depth bypass next to the H1 powerplant and concrete weirs with a nature-like fishway. Location of hydrophones are shown in red. Areas to be analysed are denoted by blue dashed lines. (b) Detailed sketch of the angled rack and bypass at powerhouse H1
F I G U R E 1 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 1 Map of Sweden and the Ätran catchment, showing dams with or without fish passage solutions
F I G U R E 6 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 6 Correlation between relative swimming depths and inflow discharge for upstream- and downstream-swimming eels during the day and night in the river reach. Solid lines represent significant relationships, broken lines insignificant ones. Situation:, downstream day;, downstream night;, upstream day;, upstream night
Fig. 4 in First three-dimensional skull of the Middle Triassic mixosaurid ichthyosaur Phalarodon fraasi from Svalbard, Norway
Fig. 4. The phylogenetic tree of Ichthyosauria and the placement of PMO 235.393. Note that Parvipelvia has collapsed as this part of the tree is not the focus of the paper. Consensus tree of 19 MPTs with a length of 544. Consistancy Index = 0.373, Rentention Index = 0.778. Bremer support values displayed above nodes.
Fig. 1 in First three-dimensional skull of the Middle Triassic mixosaurid ichthyosaur Phalarodon fraasi from Svalbard, Norway
Fig. 1. Mixosaurid ichthyosaur Phalarodon fraasi (Merriam, 1910) PMO 235.393, from the Botneheia Formation, Middle Triassic of the Isfjorden area in Spitsbergen, Svalbard. A. Slab A in concretion, photograph (A1), line drawing (A2) showing the outline and identification of the visible bone elements. B. Hypothetical reconstruction of PMO 235.393.
Fig. 2 in First three-dimensional skull of the Middle Triassic mixosaurid ichthyosaur Phalarodon fraasi from Svalbard, Norway
Fig. 2. The segmented model of right lateral side of the skull of mixosaurid ichthyosaur Phalarodon fraasi (Merriam, 1910) PMO 235.393, from the Botneheia Formation, Middle Triassic of the Isfjorden area in Spitsbergen, Svalbard.
Fig. 3 in First three-dimensional skull of the Middle Triassic mixosaurid ichthyosaur Phalarodon fraasi from Svalbard, Norway
Fig. 3. The computed tomography rendered segmentation of rostral elements of mixosaurid ichthyosaur Phalarodon fraasi (Merriam, 1910) PMO 235.393, from the Botneheia Formation, Middle Triassic of the Isfjorden area in Spitsbergen, Svalbard. Right dentary and maxilla in lingual (A1) and labial (A2) views, right dentary (A3) in dorsal view, right maxilla in dorsal (A4) and lateral (A5) views. Note that the dorsal extent of the maxilla is not complete. Scale bars 10 mm.
Dataset of the publication: Influence of Fe-clustering on the water oxidation performance of two-dimensional layered double hydroxides
<p>Dataset of the publication: Influence of Fe-clustering on the water oxidation performance of two-dimensional layered double hydroxides</p> <p>DOI: 10.1039/d1dt03737d</p> <p>Seijas-Da Silva, A; Oestreicher, V; Coronado, E; Abellán, G</p> <p>Dalton Trans., 2022,51, 4675-4684</p> <p> </p>
Dataset of the publication: Probing the spin dimensionality in single-layer CrSBr van der Waals heterostructures by magneto-transport measurements
<p>Dataset of the publication: Probing the spin dimensionality in single-layer CrSBr van der Waals heterostructures by magneto-transport measurements</p> <p>DOI: 10.1002/adma.202204940</p> <p>C. Boix-Constant, S. Mañas-Valero, A. M. Ruiz, A. Rybakov, K. A. Konieczny, S. Pillet, J. J. Baldoví, E. Coronado</p> <p>Adv. Mater., 34, 2204940 (2022)</p>
Dataset of the publication: Two-dimensional magnetic behaviour in hybrid NiFe-layered double hydroxides by molecular engineering
<p>Dataset of the publication: Two-dimensional magnetic behaviour in hybrid NiFe-layered double hydroxides by molecular engineering</p> <p>DOI: 10.1039/D2DT03804H</p> <p>A. Seijas-Da Silva, J. A. Carrasco, B. J. Vieira, J. C. Bentes Waerenborgh, E. Coronado, G. Abellán</p> <p>Dalton Trans., 2023,52, 1219-1228</p>
Experimental data for: "Multi-slice electron ptychographic tomography for three-dimensional phase-contrast microscopy beyond the depth of field limits"
<p>This is the raw experimental data for the paper: "Multi-slice electron ptychographic tomography for three-dimensional phase-contrast microscopy beyond the depth of field limits"</p> <p>Now also including code to recreate figures, and data from alignment and multi-slice ptychography reconstructions.</p> <p>The data is in zarr format and can be read with the zarr python library. It also contains metadata in a dictionary. </p>
Dataset of the publication: Interplay between optical emission and magnetism in the van der Waals magnetic semiconductor CrSBr in the two-dimensional limit
<p>Dataset of the publication: Interplay between optical emission and magnetism in the van der Waals magnetic semiconductor CrSBr in the two-dimensional limit</p> <p>DOI: 10.1021/acsnano.3c00375</p> <p>F. Marques-Moros, C. Boix-Constant, S. Mañas-Valero, J. Canet-Ferrer, E. Coronado</p> <p>ACS Nano, 17, 14, 13224-13231 (2023)</p>
Data of "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step."
<p>Data related to<br> ===========<br> title = "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step.",<br> journal = "Computer Methods in Applied Mechanics and Engineering",<br> volume ="390",<br> year = "2022",<br> doi = "https://doi.org/<a href="http://dx.doi.org/10.1016/j.cma.2021.114476">10.1016/j.cma.2021.114476</a> ",<br> pages = "114476 ",<br> author = "Wu, Ling and Noels, Ludovic"</p> <p>We would be grateful if you could cite the paper in the case in which you are using the data</p> <p> </p> <p>The files replace version 1 whose zip was corrupted.</p> <p> </p>
Automated metabolic assignment: Semi-supervised learning in metabolic analysis employing two dimensional Nuclear Magnetic Resonance (NMR)
<p>This dataset is related to the paper <strong>“Automated metabolic assignment: Semi-supervised learning in metabolic analysis employing two dimensional Nuclear Magnetic Resonance (NMR)”.</strong></p> <p>https://www.sciencedirect.com/science/article/pii/S2001037021003792?via%3Dihub</p> <p>The dataset comprises horizontal and vertical frequencies of 2D NMR TOCSY of breast cancer-tissue sample. 2D TOCSY was acquired by employing a broadband high resolution 600.13 MHz (B0 = 14.1 T) NMR Bruker spectrometer (AVANCE III 600 with the Bruker magnet ASCEND 600) supported with the room temperature probe (BBO model-Bruker) and Magic Angle Spinning (MAS) probehead. 1D and 2D NMR spectra acquisition and processing were achieved by using the TopSpin software package 3.6.</p> <p>There are two files:</p> <p><strong>BreastCancerMetabolites.csv:</strong></p> <p>First column: numerical labels of the metabolites. Each number represent a metabolite. In total, there are 27 metabolites with multiple multiplets per metabolite.</p> <p>Second and third column: Horizontal and vertical frequencies for each metabolite.</p> <p><strong>Labels.csv:</strong></p> <p>The corresponding metabolites names.</p> <p> </p>
Data from: Twist and chew: three dimensional tongue kinematics during chewing in macaque primates
<p>Three-dimensional (3D) tongue movements are central to performance of feeding functions by mammals and other tetrapods, but 3D tongue kinematics during feeding are poorly understood. Tongue kinematics were recorded during grape chewing by macaque primates using biplanar videoradiography. Complex shape changes in the tongue during chewing are dominated by a combination of flexion in the tongue's sagittal planes and roll about its long axis. As hypothesized for humans, in macaques during tongue retraction the middle (molar region) of the tongue rolls to the chewing (working) side simultaneous with sagittal flexion, while the tongue tip flexes to the other (balancing) side. Twisting and flexion reach their maxima early in the fast close phase of chewing cycles, positioning the food bolus between the approaching teeth prior to the power stroke. Although 3D tongue kinematics undoubtedly vary with food type, the mechanical role of this movement—placing the food bolus on the post-canine teeth for breakdown—is likely to be a powerful constraint on tongue kinematics during this phase of the chewing cycle. The muscular drivers of these movements are likely to include a combination of intrinsic and extrinsic tongue muscles.</p>
Dataset: Tensor-network study of correlation-spreading dynamics in the two-dimensional Bose-Hubbard model
<p>Dataset</p> <p>Tensor-network study of correlation-spreading dynamics in the two-dimensional Bose-Hubbard model</p> <p>Ryui Kaneko, Ippei Danshita</p>
Supplementary material: Picosecond pulse-shaping for strong three-dimensional field-free alignment of generic asymmetric-top molecules
<p><strong>Supplementary material to the manuscript <em>"Picosecond pulse-shaping for strong three-dimensional field-free alignment of generic asymmetric-top molecules"</em> by Terry Mullins, Evangelos T. Karamatskos, Joss Wiese, Jolijn Onvlee, Arnaud Rouzée, Andrey Yachmenev, Sebastian Trippel, and Jochen Küpper, <em>Nat Commun</em> 13, 1431 (2022). <a href="https://doi.org/10.1038/s41467-022-28951-z">https://doi.org/10.1038/s41467-022-28951-z</a>, arXiv: <a href="https://arxiv.org/abs/2009.08157">2009.08157 </a></strong></p> <ul> <li> <em><strong>simulations_part.z*</strong> </em>is split zip archive containing simulations data for indole molecule, such as files with rotational probability density distributions computed at different times <span class="math-tex">\(t=0..1500\)</span> ps during the laser pulse and field-free evolution, and example python scripts for data retrieval.</li> <li><strong><em>rawdata_part.z*</em></strong> is split zip archive containing raw experimental data.</li> <li><strong><em>analysis_scripts.zip</em></strong> is zip archive containing experimental analysis codes.</li> </ul> <p><strong>The <em>simulations_part.zip</em> contains the following files and folders:</strong></p> <ul> <li><em><strong>prob_density_euler_angles</strong></em> contains files <em>rotdens_av_<time>.gz</em> with simulated state-averaged rotational probability density distributions in terms of Euler angles for different times <time>, ranging from the beginning of the alignment laser pulse at <span class="math-tex">\(t=0\)</span> up to <span class="math-tex">\(t=1500\)</span> ps with a time step of 1 ps.<br> Calculations of probability density distributions were done using <a href="https://github.com/CFEL-CMI/richmol">Richmol</a> program.<br> The gzipped ASCII data files <em>rotdens_av_<time>.gz</em> contain in columns the values of the Euler angles <span class="math-tex">\(\phi,\theta,\chi\)</span> followed by the normalized probability density value.</li> <li><em><strong>prob_density_atoms_xyz</strong></em> contains files <em>monte_carlo_av_<time>.h5</em> with state-averaged rotational probability density distributions of all atoms in the indole molecule in terms of their Cartesian coordinates, for different times <time>, ranging from the beginning of the alignment pulse at <span class="math-tex">\(t=0\)</span> up to <span class="math-tex">\(t=1500\)</span> ps with a time step of 1 ps.<br> Structure of <em>monte_carlo_av_<time>.h5</em> HDF5 files:<br> Key Description<br> ----- ----------------<br> 'C10' - Cartesian coordinates of carbon atom no. 10<br> 'C11' - Cartesian coordinates of carbon atom no. 11<br> 'C12' - ...<br> 'C14' - ...<br> 'C3' - ...<br> 'C6' - ...<br> 'C7' - ...<br> 'C9' - ...<br> 'N4' - ...<br> 'H1-C3' - Cartesian coordinates of a vector pointing from carbon atom no. 3 to hydrogen atom no. 1<br> 'H13-C11' - ...<br> 'H15-C12' - ...<br> 'H16-C14' - ...<br> 'H2-N4' - ...<br> 'H5-C7' - ...<br> 'H8-C9' - ...<br> 'ref_vectors' - reference molecular-frame Cartesian coordinates of all atoms<br> 'x' - coordinates of the x-axis of Principal Axes of Inertia Frame<br> 'y' - coordinates of the y-axis of Principal Axes of Inertia Frame<br> 'z' - coordinates of the z-axis of Principal Axes of Inertia Frame<br> 'pol_x' - coordinates of the x-axis of Principal Axes of Polarizability Frame<br> 'pol_y' - coordinates of the y-axis of Principal Axes of Polarizability Frame<br> 'pol_z' - coordinates of the z-axis of Principal Axes of Polarizability Frame</li> <li><em><strong>indole_deflected_states.txt</strong></em> ASCII file contains initial populations of rotational states of indole in the deflected beam.<br> The following data is arranged in columns: <em>m, J</em>, <em>id</em>, <em>energy</em>, <em>normalized population</em>. The <em>J</em> and <em>m</em> are rotational quantum numbers of the total angular momentum and its <em>Z</em>-projection, the <em>id</em> number refers to the state's index in file <em>indole_energies_j0_j20.txt</em> listing rotational states of indole.</li> <li><em><strong>indole_data.py</strong></em> Python module provides basic functions to extract information from HDF5 data files <em>monte_carlo_av_<time>.h5</em>. It can also be used to compute alignment and orientation.</li> <li><em><strong>example_cos.py</strong></em> and <em><strong>example_dens.py</strong></em> Python scripts that demonstrate how to use <em>indole_data.py</em> module for computing and plotting alignment traces and a 2D projection of the probability density distribution, respectively.</li> <li><em><strong>monte_carlo.py</strong></em> Python script that was used to compute through Monte-Carlo sampling probability density distributions for Cartesian positions of atoms in indole (<em>monte_carlo_av_<time>.h5</em> files) using probability density distribution functions in Euler angles (outputs of Richmol program <em>rotdens_av_<time>.gz</em>).</li> </ul> <p><strong>The <em>analysis_scripts.zip</em> contains the following files and folders:</strong></p> <ul> <li><strong><em>H_Plus</em></strong> folder contains codes relevant for the analysis of H<sup>+</sup> ion data. <ul> <li><strong><em>analyse_full_alignment_scans.m</em></strong>: subtracts background and combines delay scan data sets together, takes account of errors.</li> <li><em><strong>calculate_resamped_df.m</strong></em>: called by <em>analyse_full_alignment_scans.m</em> to calculate the frequency sampling.</li> <li><em><strong>unique_mean.m</strong></em>: called by <em>analyse_full_alignment_scans.m</em> when combining data sets. Combines non-unique data points into a single data point.</li> </ul> </li> <li><em><strong>C_Plus2</strong></em> folder contains codes for the analysis of C<sup>2+</sup> ion data. The file descriptions are identical to those in the <em>H_Plus</em> directory.</li> <li><em><strong>intensity/calculate_intensity.m</strong></em>: calculates peak intensity of the laser pulse from measured parameters as well as statistical error.</li> <li><em><strong>intensity/compare_exp_sim.m</strong></em>: fits experimental and theoretical tomography and delay-dependent 2D projection values.</li> <li><em><strong>intensity/nir2hdf5_kHz.py</strong></em>: converts raw data files (from <em>rawdata_part.z*</em> archive<em>)</em> into hdf5 files.</li> </ul>
Two dimensional materials for photonic devices
<p>Video-presentation with the summary of the two dimensional materials for photonic devices project.</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 840064</p>
Raw Data for the article: Changes in the Transcriptome Profiles of Human Amnion-Derived Mesenchymal Stromal/Stem Cells Induced by Three-Dimensional Culture: A Potential Priming Strategy to Improve Their Properties
<p>Mesenchymal stromal/stem cells (MSCs) are believed to function in vivo as a homeostatic tool that shows therapeutic properties for tissue repair/regeneration. Conventionally, these cells are expanded in two-dimensional (2D) cultures, and, in that case, MSCs undergo genotypic/phenotypic changes resulting in a loss of their therapeutic capabilities. Moreover, several clinical trials using MSCs have shown controversial results with moderate/insufficient therapeutic responses. Different priming methods were tested to improve MSC effects, and three-dimensional (3D) culturing techniques were also examined. MSC spheroids display increased therapeutic properties, and, in this context, it is crucial to understand molecular changes underlying spheroid generation. To address these limitations, we performed RNA-seq on human amnion-derived MSCs (hAMSCs) cultured in both 2D and 3D conditions and examined the transcriptome changes associated with hAMSC spheroid formation. We found a large number of 3D culture-sensitive genes and identified selected genes related to 3D hAMSC therapeutic effects. In particular, we observed that these genes can regulate proliferation/differentiation, as well as immunomodulatory and angiogenic processes. We validated RNA-seq results by qRT-PCR and methylome analysis and investigation of secreted factors. Overall, our results showed that hAMSC spheroid culture represents a promising approach to cell-based therapy that could significantly impact hAMSC application in the field of regenerative medicine.</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.