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9,882 results for “Scale”
Cyclic test data of five URM walls at half-scale
<p>This data presents the results of a test series on five identical unreinforced masonry walls built at half-scale that were constructed using hollow clay brick units and standard cement-based mortar. The test units were subjected to<br> quasi-static cycles of increasing drift demands and the tests differed with regard to the applied axial load and the moment restraint applied at the top of the walls. The walls were tested up to failure. Throughout the loading the deformations of the walls were recorded using a digital photogrammetric measurement system tracking the movement of 312 points per test unit.</p>
Multiple Sclerosis: Cerebral Circulation Time is prolonged and not correlated with expanded disability status scale (EDSS). A study using digital subtracted angiography
<p>Dataset used to study the relationship between cerebral circulation time (CCT) and some clinical evidences, e.g. expand disability status scale (EDSS), disease duration, age at onset,... CCT was measured through the digital subtraction angiography (DSA) technique. </p> <p>Statistical Parametric Mapping software (SPM, Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London; http://www.fil.ion.ucl.ac.uk/spm/) and ad-hoc scripts developed in the MATLAB scientific computing environment (http://www.mathworks.com, MathWorks, MA, USA) were applied to valuate the lesion volume and brain volume in MS patients.</p>
Psychosocial functioning before and after surgical treatment for morbid obesity: Reliability and validity of the Norwegian version of obesity-related problems scale
<p>This is a dataset (SPSS, sav. file) related to the study "Psychosocial functioning before and after surgical treatment for morbid obesity: Reliability and validity of the Norwegian version of obesity-related problems scale". If anyone wants the file in a different format, contact the uploader (see thelink on the right)</p>
DPPC_Berger_NaCl_scaled
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer with 150 mM NaCl. Berger-DPPC-98 force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads) was used with Gromacs 5.0.4. Ions were described by the gromos force field. Ion charges were scaled by a factor 0.7. Conditions: T=323K, 72 lipids, 2880 SPC waters, 8 Na, 8 Cl. 120 ns trajectory, last 60 ns analyzed.</p>
DPPC_Berger_OPLS06_NaCl_scaled
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer with 150 mM NaCl. The OPLS-AA-compatible Berger-DPPC-06 force field (DOI:10.1088/0953--8984/18/28/S07) was used with Gromacs 4.6.7. Ions were described by the Åqvist parameters. The ion charges were scaled by a factor 0.7. Conditions: T=323K, 72 lipids, 2880 SPC waters, 8 Na, 8 Cl. 120 ns trajectory, last 60 ns analyzed.</p>
DPPC_Berger_OPLS06_NaCl_1Mol_scaled
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer with 1 M NaCl. The OPLS-AA-compatible Berger-DPPC-06 force field (DOI:10.1088/0953--8984/18/28/S07) was used with Gromacs 5.0.4. Ions were described by the Åqvist parameters. The ion charges were scaled by a factor 0.7. Conditions: T=323K, 72 lipids, 2778 SPC waters, 51 Na, 51 Cl. 120 ns trajectory, last 60 ns analyzed.</p>
DPPC_Berger_NaCl_1Mol_scaled
<p>MD simulation trajectory and related files for fully hydrated DPPC bilayer with 1 M NaCl. Berger-DPPC-98 force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads) was used with Gromacs 5.0.4. Ions were described by the gromos force field. Ion charges were scaled by a factor 0.7. Conditions: T=323K, 72 lipids, 2778 SPC waters, 51 Na, 51 Cl. 120 ns trajectory, last 60 ns analyzed.</p>
FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure
<p>This upload contains the FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure.</p> <p>If you use the datasets, we would be grateful if you cited the following paper:</p> <p>Zou, C., Zhang, Y., Ouyang, Z. (2016) HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome Biology, 17: 40.</p>
Supporting Data: A large-scale dataset of solar event reports from automated feature recognition modules.
<p>This is the supporting dataset for the paper:</p> <p>A large-scale dataset of solar event reports from automated feature recognition modules. Michael A. Schuh, Rafal A. Angryk, Petrus C. Martens. Journal of Space Weather and Space Climate, 2016.</p>
Efficient Large-Scale Trace Checking Using MapReduce
<p>The problem of checking a logged event trace against a temporal logic specification arises in many practical cases. Unfortunately, known algorithms for an expressive logic like MTL (Metric Temporal Logic) do not scale with respect to two crucial dimensions: the length of the trace and the size of the time interval for which logged events must be buffered to check satisfaction of the specification. The former issue can be addressed by distributed and parallel trace checking algorithms that can take advantage of modern cloud computing and programming frameworks like MapReduce. Still, the latter issue remains open with current state-of-the-art approaches. </p> <p>In this paper we address this memory scalability issue by proposing a new semantics for MTL, called lazy semantics. This semantics can evaluate temporal formulae and boolean combinations of temporal-only formulae at any arbitrary time instant. We prove that lazy semantics is more expressive than standard point-based semantics and that it can be used as a basis for a correct parametric decomposition of any MTL formula into an equivalent one with smaller, bounded time intervals. We use lazy semantics to extend our previous distributed trace checking algorithm for MTL. We evaluate the proposed algorithm in terms of memory scalability and time/memory tradeoffs.</p>
Financial Capability Scale (FCS)
<p>The University of Wisconsin’s Center for Financial Security developed the Financial Capability Scale (FCS) with the support and Annie E. Casey Foundation in 2011 with the goal of developing a standardized client financial capability scale that could be used in the field with clients as well as in evaluation studies. In 2013, the Center conducted field testing to establish the reliability and validity of the scale. The FCS has been shown to be associated with credit use, credit scores, savings and financial attitudes. Although designed for financial coaching, the FCS can be applied to other financial capability services and programs.</p>
IMP small scale test dataset
<p>This file contains the test data set used within the article:</p> <p><strong>IMP: a reproducible pipeline for reference-independent integrated metagenomic and metatranscriptomic analyses</strong></p> <p>Shaman Narayanasamy<sup>†</sup>, Yohan Jarosz<sup>†</sup>, Emilie E.L. Muller, Cédric C. Laczny, Malte Herold, Anne Kaysen, Anna Heintz-Buschart, Nicolás Pinel, Patrick May, and Paul Wilmes<sup>*</sup></p> <p>Preprint: http://biorxiv.org/content/early/2016/02/10/039263</p> <p> </p> <p>This test data set was used for benchmarking the run times of IMP. They are derived by selecting the first 5% of reads from a wastewater sludge microbial community dataset (see manuscript and original publication of data: 10.1038/ncomms6603). Also included are the respective preprocessed FASTQ files such that IMP can be tested without running the preprocessing step. A README file inside the folder briefly describes the different FASTQ files contained in the folder.</p>
Research Data supporting "Linear-Scaling Density Functional Theory using the Projector Augmented Wave Method"
<p>Research Data supporting "Linear-Scaling Density Functional Theory using the Projector Augmented Wave Method" by Nicholas D. M. Hine</p>
Scaling of the electron temperature on the expansion ratio with plasma heating by Neutral Beams only (diamonds) and with both Neutral Beams and ECRH (square)
<p>Scaling of the electron temperature on the expansion ratio with plasma heating by Neutral Beams only (diamonds) and with both Neutral Beams and ECRH (square)</p>
A Multi-Scale Correlative Investigation of Ductile Fracture: supporting data
<p>These files are the raw X-ray CT datasets captured using a Custom Bay instrument as detailed in the article: A Multi-Scale Correlative Investigation of Ductile Fracture (under review as of January 2017). </p>
Figure 7. - Palaemonyuna sp. n. Figure a holotype; figures b–n paratype (CCDB 4866, male, CL 5.5 mm). a anterior part of the carapace b right eye, dorsal view c left scaphocerite, ventral view d left mandible, ventral view e left maxillula, ventral view f left maxilla, ventral view g left second maxilliped, ventral view h left first maxilliped, ventral view i left first maxilliped, dorsal view j right third maxilliped, ventro-lateral view k right second pereiopod, ventro-lateral view l right first pereiopod, ventro-lateral view m right first chela, mesial view n right second chela, mesial view. Scale bar: a, c, k equal to 1 mm; others equal to 0.5 mm.
Figure 7. - Palaemonyuna sp. n. Figure a holotype; figures b–n paratype (CCDB 4866, male, CL 5.5 mm). a anterior part of the carapace b right eye, dorsal view c left scaphocerite, ventral view d left mandible, ventral view e left maxillula, ventral view f left maxilla, ventral view g left second maxilliped, ventral view h left first maxilliped, ventral view i left first maxilliped, dorsal view j right third maxilliped, ventro-lateral view k right second pereiopod, ventro-lateral view l right first pereiopod, ventro-lateral view m right first chela, mesial view n right second chela, mesial view. Scale bar: a, c, k equal to 1 mm; others equal to 0.5 mm.
Figure 8. - Palaemonyuna sp. n. Figures i and m holotype; figures a–e, g, h, j–l paratype (CCDB 4866, male, CL 5.5 mm); figure f paratype (CCDB 4866, female, CL 5.5 mm). a left third pereiopod, lateral view b left fourth pereiopod, lateral view c distal portion of the left fifth pereiopod, lateral view d left fifth pereiopod, lateral view e left first pleopod, posterior view f left first pleopod, posterior view g left second pleopod, posterior view h left appendix masculina and appendix interna, posterior view i right posterior part of the abdomen, lateral view j pre-anal fig, ventral view k telson and uropods, dorsal view l distal part of the telson, dorsal view m left distal portion of the exopod of the uropod, dorsal view. Scale bar: a, b, d–g, i, k equal to 1 mm; c, j, m equal to 0.5 mm; h, l equal to 0.25 mm.
Figure 8. - Palaemonyuna sp. n. Figures i and m holotype; figures a–e, g, h, j–l paratype (CCDB 4866, male, CL 5.5 mm); figure f paratype (CCDB 4866, female, CL 5.5 mm). a left third pereiopod, lateral view b left fourth pereiopod, lateral view c distal portion of the left fifth pereiopod, lateral view d left fifth pereiopod, lateral view e left first pleopod, posterior view f left first pleopod, posterior view g left second pleopod, posterior view h left appendix masculina and appendix interna, posterior view i right posterior part of the abdomen, lateral view j pre-anal fig, ventral view k telson and uropods, dorsal view l distal part of the telson, dorsal view m left distal portion of the exopod of the uropod, dorsal view. Scale bar: a, b, d–g, i, k equal to 1 mm; c, j, m equal to 0.5 mm; h, l equal to 0.25 mm.
Figure 2. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 2. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 24. - Leucotrichiainflaticornis Botosaneanu, 1993 (redrawn from Botosaneanu and Alkins-Koo 1993). Male genitalia: A segment IX, dorsal B segments VIII–IX, ventral C subgenital plate, not to scale, view not specified D phallus, ventral.
Figure 24. - Leucotrichiainflaticornis Botosaneanu, 1993 (redrawn from Botosaneanu and Alkins-Koo 1993). Male genitalia: A segment IX, dorsal B segments VIII–IX, ventral C subgenital plate, not to scale, view not specified D phallus, ventral.
Figure 4. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI and 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 4. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI and 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
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.