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4,107 results for “pointing”
Dataset - Controlled release experiment to investigate uncertainties in UAV-based emission quantification for methane point sources
<p>This dataset was created by Randulph Morales (randulph.morales@empa.ch) and was used for Morales et al. (2021) AMT publication (amt-2021-314). A short description of the files is written in <strong>readme.txt</strong></p> <p>The dataset contains:</p> <ul> <li>QCLAS methane measurement</li> <li>Active AirCore methane measurement</li> <li>Meteorology files</li> </ul>
Dataset of the determination of the topographic spatial resolution of a confocal point sensor with a type ASG material measure
<p>These original measurement data relate to the publication: J. Schaude, A. C. Gröschl, T. Hausotte: Effect of a Misidentified Centre of a Type ASG Material Measure on the Determined Topographic Spatial Resolution of an Optical Point Sensor, Metrology 2(1), p. 19-32, 2022, <a href="https://doi.org/10.3390/metrology2010002">https://doi.org/10.3390/metrology2010002</a>. Please refer to this open access publication for a detailed description of the measurement setup and procedure.</p> <p>All data are in ASCII-format. Each file contains four columns, where column one to three are the <em>x</em>, <em>y</em>, and <em>z</em>-coordinates of the positioning system and column four is the signal of the photodetector.</p> <p><strong>Content of the folders</strong></p> <p>10_Plane: Axial probings on 18 points just outside the grooves.</p> <p>20_Edges: Lateral probings from each point just outside the grooves in the direction of the roughly determined centre of the material measure.</p> <p>30_PlaneArea: Repeated axial probing on a plane area near the material measure.</p> <p>40_RadialMeasurement: Radial measurement of the material measure by lateral (radial) probings conducted on different heights (referring to the distance to the plane fitted to the measuring points of 10_Plane), and radii (referring to the centre of the circle fitted to the edges determined in 20_Edges). Each radial probing has its own data file, with the name of the data file being “radial_probing {radius in m} {height in m} {data and time of probing}.txt”.</p> <p>50_LineMeasurement: Lateral probings conducted on different heights (referring to the distance to the plane fitted to the measuring points of 10_Plane), different lateral offsets (referring to the centre of the circle fitted to the edges determined in 20_Edges) and on two angles (on the groove (0°) and the adjacent top level (10°)). Please refer to sec. 5.2 of the aforementioned publication for a detailed description. Each lateral probing has its own data file, with the name of the file being “lateral probing {angle in °} {offset in m} {height in m} {data and time of probing}.txt”.</p> <p><strong>Acknowledgement</strong></p> <p>This project 20IND07 TracOptic has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme. Funder name: European Metrology Programme for Innovation and Research (EMPIR); Funder ID: 10.13039/10001413</p>
Data set for: Toggle-like current-induced Bloch point dynamics of 3D skyrmion strings in a room-temperature nanowire
<p>This data set contains both the experimental data and the simulation scripts to reproduce the results of [1]: <em>Toggle-like current-induced Bloch point dynamics of 3D skyrmion strings in a room-temperature nanowire</em> by M. T. Birch, D. Cortés-Ortuño, K. Litzius, S. Wintz, F. Schulz, M. Weigand, A. Štefančič, D. Mayoh, G. Balakrishnan, P.D. Hatton, G. Schütz. A preprint of this publication is available at <a href="https://www.researchsquare.com/article/rs-1235546/v1">https://www.researchsquare.com/article/rs-1235546/v1</a>.</p> <p>This data set is also hosted in Github: <a href="https://github.com/davidcortesortuno/paper-2022_toggle-like_current_induced_bp_dynamics_3d_skyrmion_strings">https://github.com/davidcortesortuno/paper-2022_toggle-like_current_induced_bp_dynamics_3d_skyrmion_strings</a></p> <p>If you find this material useful please cite us</p> <pre><code>@Misc{Birch2022, author = {M. T. Birch and D. Cort\'es-Ortu\~no}, title = {{Data set for: Toggle-like current-induced Bloch point dynamics of 3D skyrmion strings in a room-temperature nanowire}}, howpublished = {Zenodo \url{doi:10.5281/zenodo.6393340}. Github: \url{https://github.com/davidcortesortuno/paper-2022_toggle-like_current_induced_bp_dynamics_3d_skyrmion_strings}}, year = {2022}, doi = {10.5281/zenodo.6393340}, url = {https://doi.org/10.5281/zenodo.6393340}, }</code></pre> <p> </p>
Imipenem hydrolysis by the L1 and the NDM-1 metallo-beta-lactamases: QM/MM structures of the stationary points
<p>Stationary points (transition states and minima) for the hydrolysis reactions of the imipenem in the active sites of the L1 and NDM-1 metallo-beta-lactamases. The reactions occure in three elementary steps each. For the NDM-1 there are two compeeting pathways leading to the different products. Enamine and imine forms of the hydrolyzed imipenem may form and those are marked with "N" and "C", respectively, according to the atom being protonated at the last step. Structures are calculated at the QM(PBE0-D3/6-31G**)/MM(AMBER) level.</p>
IODP Expedition 372A Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
IODP Expedition 374 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
Point-of-care monitoring of head and neck cancer treatment response and recurrence development using nanopore-based ctDNA consensus sequencing
<p>Circulating tumor DNA (ctDNA) in blood may become a generic biomarker for non-invasive cancer diagnosis and monitoring. However, detection of ctDNA is challenged by the presence of many circulating DNA molecules from healthy cells. We found that single ctDNA molecules can be sequenced with high accuracy by a three-step process consisting of capturing, copying and concatenation of the original double-stranded ctDNA molecules. This innovative approach - called CyclomicsSeq - is unparalleled by any other method in terms of cost-efficiency and speed, allowing point-of-care cancer diagnostics.</p> <p>Within this CPOC, subsidized by the Oncode institute, we have applied our CyclomicsSeq ctDNA test in patients with advanced head and neck cancer squamous cell carcinoma (HNSCC). Head and neck cancer (HNSCC) accounts for 380,000 cancer-related deaths worldwide. For these patients, determining whether a patient responds to the primary chemoradiation treatment is challenging, and non-responders are sometimes identified when other treatment options are no longer possible. By measuring the ctDNA levels in the blood of these patients prior to and during treatment, we aim to identify non-responders at an earlier stage.</p> <p>This dataset contains base calls of TP53 of 47 nanopore sequencing runs. We included 10 patients and 7 controls. For the patients, we have samples of multiple time points (0 = prior to treatment, 1 = 1 week after treatment initiation, etc).</p>
Correlated k coefficients for H2-He atmospheres; 196 spectral windows and 1060 pressure-temperature points
<p>There are 72 correlated k-coefficients datasets, using the naming convention m-xxx_coyyy.data.196.tar.zip, where xxx is the metallicity in dex relative to solar, and yyy is the C/O ratio relative to solar, as a multiplication factor. For example a metallicity of 0.0 and a C/O ratio of 1.0 indicates solar abundances. There are an additional 5 datasets that do not include the TiO and VO opacities, as indicated by the "_noTiOVO" designation in the file name. We use the Lodders et al. 2010 value for the solar C/O=0.458. The spectral windows are listed in the file 196_windows.txt (intervals defined as starting at lambda1 and ending at lambda2), and the k-coefficients can be read in and checked using the script in the IDL code read_k_coefficients.pro. The k-coefficients are calculated for a grid of 1060 pressure-temperature points listed in the file PT_list_1060.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, where the abundances for each metallicity-C/O combination have been calculated using equilibrium chemistry, as described in Marley et al. 2021. There are 12 Fe/H values: 0.0, 0.5, 0.7, 1.0, 1.5, 1.5, 1.7, 2.0, -0.25, -0.3, -0.5, -0.75, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5.</p> <p> The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, FeH, H2O, H2S, HCN, LiCl, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The references for the line lists and broadening parameters used in these opacity calculations can also be found in Marley et al 2021, and are included here for convenience in the file Table_2_Marley_et.al.2021.png</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>cp_all: contains the mean molecular weight for each layer. The head capacity values do not include the proper H2 heat capacity and should not be used.</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1060-point pressure-temperature grid.</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_cia: relative abundances for the species that could be used for calculating collision-induced absorption (CIA)</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlated k coefficients for H2-He atmospheres; 11 spectral windows and 1060 pressure-temperature points
<p>There are 72 correlated k-coefficients datasets, using the naming convention m-xxx_coyyy.data.11.tar.zip, where xxx is the metallicity in dex relative to solar, and yyy is the C/O ratio relative to solar, as a multiplication factor. For example a metallicity of 0.0 and a C/O ratio of 1.0 indicates solar abundances. There are an additional 10 datasets that do not include the TiO and VO opacities, as indicated by the "_noTiOVO" designation in the file name. We use the Lodders et al. 2010 value for the solar C/O=0.458. The spectral windows are listed in the file 11_windows.txt (intervals defined as starting at lambda1 and ending at lambda2), and the k-coefficients can be read in and checked using the script in the IDL code read_k_coefficients.pro. The k-coefficients are calculated for a grid of 1060 pressure-temperature points listed in the file PT_list_1060.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, where the abundances for each metallicity-C/O combination have been calculated using equilibrium chemistry, as described in Marley et al. 2021. There are 12 Fe/H values: 0.0, 0.5, 0.7, 1.0, 1.5, 1.5, 1.7, 2.0, -0.25, -0.3, -0.5, -0.75, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5.</p> <p> The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, FeH, H2O, H2S, HCN, LiCl, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The references for the line lists and broadening parameters used in these opacity calculations can also be found in Marley et al 2021, and are included here for convenience in the file Table_2_Marley_et.al.2021.png</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>cp_all: contains the mean molecular weight for each layer. The head capacity values do not include the proper H2 heat capacity and should not be used.</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1060-point pressure-temperature grid.</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_cia: relative abundances for the species that could be used for calculating collision-induced absorption (CIA)</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Dataset for a Feasibility Study for Accelerated Reference Point Determination Using Close Range Photogrammetry
<p>The Global Geodetic Observing System (GGOS) aims for an accuracy of 1 mm in position concerning a global geodetic reference frame such as the International Terrestrial Reference Frame (ITRF). To derive a global frame, several space geodetic techniques are combined. The combination procedure requires the geometric relations between the invariant reference points of these techniques, the so-called local tie vectors. Each space geodetic technique defines its reference point individually, so the determination of the position of the reference point varies significantly between techniques. Within the international GeoMetre project, measurement systems and analysis strategies are developed to improve the quality of local tie vectors and, thus, the quality of the resulting global frame.</p> <p>The use of close range photogrammetry to determine the reference point of a telescope used for Satellite Laser Ranging (SLR) at the GGOS core station Wettzell in September 2020 is considered as a milestone in this project. This contribution deals with a novel approach for an accelerated reference point determination using close range photogrammetry. In comparison to the conventional photogrammetric approach, published so far, this new approach leads to a significant reduction in recording time. However, in case of inappropriate measurement configuration the approach also bears the risk of biased results. Most importantly, the new approach has the potential to be automated, which is one of the primary calls of GGOS for reference point determinations.</p>
IODP Expedition 352 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
IODP Expedition 351 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
Fig. 37 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 37. Maximum likelihood phylogeny (identical in topology to Bayesian inference phylogeny) of Kotatea gen. nov., Ushanaia gen. nov., and associated taxa based on combined, partitioned analysis of mtMutS and 28S. New species are identified by individual colours. The type species for Alcyonium Linnaeus, 1758 – A. digitatum Linnaeus, 1758 – appears in bold. ML bootstrap support values are given above each branch and BI posterior probabilities below.
Fig. 36 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 36. Ushanaia solida gen. et sp. nov., holotype (NIWA 102133), SEMs of sclerites. A. Polyp mound. B. Lobe surface, proximal region (close proximity to substrate). C. Lobe surface, distal region. D. Interior.
Fig. 35 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 35. Ushanaia solida gen. et sp. nov., holotype (NIWA 102133), SEMs of sclerites. A. Collaret and points. B. Tentacles. C. Polyp neck. D. Distal points.
Fig. 34 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 34. SEMs of sclerites from polyps (in situ). A. Ushanaia fervens gen. et sp. nov., holotype (NIWA 156311). B. U. solida gen. et sp. nov., holotype (NIWA 102133).
Fig. 32 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 32. Ushanaia fervens gen. et sp. nov., holotype (NIWA 156311), SEMs of sclerites. A. Collaret and points. B. Distal points. C. Tentacles. D. Polyp neck.
Fig. 31 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 31. In situ photographs of Ushanaia fervens gen. et sp. nov. A–B. Encrusting on black coral (uncollected specimen), Fiordland, photos by Richard Kinsey.C. Small colonies (uncollected specimens), Fiordland, photo by Ian Skipworth (ianskipworth.com). Scale bars = ~2 cm.
Fig. 30 in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 30. Ushanaia ferruginea gen. et sp. nov., holotype (NIWA 156313), SEMs of sclerites. A. Surface (of thick, fleshy areas of colony). B. Interior (of thick, fleshy areas of colony).
Fig. 28. Selected preserved specimens. A in Dead man's fingers point to new taxa: two new genera of New Zealand soft corals (Anthozoa, Octocorallia) and a revision of Alcyonium aurantiacum Quoy & Gaimard, 1833
Fig. 28. Selected preserved specimens. A. Ushanaia ferruginea gen. et sp. nov. B. U. fervens gen. et sp. nov. C. U. solida gen. et sp. nov. Note that most specimen lots include additional fragments that are not depicted. * = holotype.
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.