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3,688 results for “Computer”
Figures for "New method for computing post-seismic deformations in a realistic gravitational viscoelastic Earth model"
<p>Here are all the figures used in the paper "New method for computing post-seismic deformations in a realistic gravitational viscoelastic Earth model". </p>
Plant leaf computing. Videos.
<p>Action potentials are multi-functional signals in plants. While most plant cells are conductive, and electrically coupled with each other, the action potentials are channelled faster along the plants' vascular network. Conductivity of the networks is geometrically constrained, thus allow for selective propagation and interaction between the impulses. Using FitzhHugh-Nagumo model we show that it is possible to realise a functionally complete set of Boolean functions by selecting locations of stimulating and recording electrodes. The results pave theoretical grounds for further experimental studies of plant-based computing. </p>
Iterative Arylation of Amino Acids and Aliphatic Amines via δ‐C(sp3)−H Activation: Experimental and Computational Exploration
<p>This dataset contains the geometries of all optimized structures (in <em>.xyz</em> format with their associated energy in Hartrees) accompanying the paper "Iterative Arylation of Amino Acids and Aliphatic Amines via δ‐C(sp3)−H Activation: Experimental and Computational Exploration" published in Angew. Chem. Int. Ed.. doi:<a href="https://doi.org/10.1002/anie.201900479">10.1002/anie.201900479</a> on 28 Feb 2019.</p>
Chemistry and Mass Density of Aluminum Hydroxide Gel in Eco- Cements by Ptychographic X‑ray Computed Tomography
<p>Raw data for: Chemistry and Mass Density of Aluminum Hydroxide Gel in Eco- Cements by Ptychographic X‑ray Computed Tomography </p> <p>doi: http://dx.doi.org/10.1021/acs.jpcc.6b10048</p> <p> </p> <p>Eco-cements are a desirable alternative to ordinary Portland cements because of their lower CO<sub>2</sub> footprints. Ye'elimite-based eco-cements are attracting a lot of interest but most of them exhibit relatively poor mechanical properties. Understanding the reasons for the low performances requires the characterization of features such as mass density of the hydrated mineralogical phases, including the amorphous gel, on the sub-micrometer scale which is very challenging. Here we use ptychographic X-ray computed tomography to provide 3D mass density and attenuation coefficient distributions of eco-cement pastes with an isotropic resolution close to 100 nm allowing to distinguish between mineralogical phases with very similar contrast. In combination with laboratory techniques such as the Rietveld method, <sup>27</sup>Al MAS-NMR and electron microscopies, we report compositions and densities of key components. The ettringite and gel volume distributions have been mapped out in the segmented tomograms. Moreover, we discriminate between an aluminum hydroxide gel and calcium aluminum monosulfate, which have close electron density values. Specifically, the composition and mass density of two aluminum hydroxide gels have been determined: (CaO)<sub>0.04</sub>Al(OH)<sub>3</sub>·2.3H2O with 1.48(3) g∙cm<sup>-3</sup> and (CaO)<sub>0.12</sub>Al(OH)<sub>3</sub> with 2.05(3) g∙cm<sup>-3</sup>, which was a long standing challenge.</p>
Computation-Ready, Experimental Metal–Organic Frameworks
<p>Experimentally refined crystal structures for metal–organic frameworks (MOFs) often include solvent molecules and partially occupied or disordered atoms. This creates a major impediment to applying high-throughput computational screening to MOFs. To address this problem, we have constructed a database of MOF structures that are derived from experimental data but are immediately suitable for molecular simulations. </p> <p>The development of the CoRE MOF 2014 database is described in “Computation-ready, experimental metal-organic frameworks: A tool to enable high-throughput screening of nanoporous crystals” Chung, Y.G. et al., Chem. Mater. 2014, 26, 6185-6192 (DOI: <a href="https://doi.org/10.1021/cm502594j">10.1021/cm502594j</a>). The CoRE MOF 2014 database was developed through a collaboration of research groups participating in the Nanoporous Materials Genome Center that is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-12ER16362.</p>
dataset for root canal configuration of mandibular first and second premolars using in vivo cone-beam computed tomography imaging
<p>dataset for root canal configuration of mandibular first and second premolars using in vivo cone-beam computed tomography imaging</p>
Computational Data for Identification of an allosteric binding site on the Glycine Transporter, GlyT2
<p>Input structures and gromacs trajectories for Identification of an allosteric binding site on the Glycine Transporter, GlyT2, for bioactive lipid analgensics</p>
Microscale Investigation of the Mechanical and Seepage Characteristics of Hydrate-bearing Sands by Computed Tomography
<p>This supporting information includes four movies S1-S4, providing animations of hydrate decomposition process and shear deformations in the main article.</p> <p> </p> <p>Movie S1 is uploaded with file name Movie S1. gif. Detailed information includes vertical-sectional view of a specimen during the decomposition process.</p> <p>Movie S2 is uploaded with file name Movie S2. gif. Detailed information includes longitudinal cross-sectional X-ray CT images of #T-1 specimen during shear deformation.</p> <p>Movie S3 is uploaded with file name Movie S3. gif. Detailed information includes longitudinal cross-sectional X-ray CT images of #T-2 specimen during shear deformation.</p> <p>Movie S4 is uploaded with file name Movie S5. gif. Detailed information includes longitudinal cross-sectional X-ray CT images of #T-3specimen during shear deformation.</p>
Three principles of data science: predictability, computability, and stability (PCS)
<p>This repository contains the data, codes, and PCS documentation described in: <em>Three principles of data science: predictability, computability, and stability (PCS)</em>.</p>
Computational History of Philosophy of Science (Comp HOPOS) Dataset
<p>The Computational History of Philosophy of Science (Comp HOPOS) aims to be a comprehensive set of article and (when available) book chapter metadata for philosophy of science. The dataset covers the full run of over 40 journals and 3 major book series in the field. An automated author disambiguation script is used to construct canonical names for each author, and a combination of gender attribution methods is used to attribute the gender of each author. The full code used to generate the dataset is available at <a href="https://github.com/dhicks/comp-HOPOS">https://github.com/dhicks/comp-HOPOS</a>. See the file data_dictionary.txt for data dictionary and additional information.</p>
Three-dimensional Stable Matching with Cyclic Preferences: Computational proofs log files
<p>Output from SAT solvers in the computational proofs of the paper: "Three-dimensional Stable Matching with Cyclic Preferences" by Kanstantsin Pashkovich and Laurent Poirrier.</p>
An Alkyne Linchpin Strategy for Drug:Pharmacophore Conjugation: Experimental and Computational Realization of a meta-selective Inverse Sonogashira Coupling
<p>This folder contains the output log files of the study of Pd-catalysed alkynylation</p> <p>entitled "A Linchpin Approach to Access Drug-Pharmacophore Conjugate by Inverse Sonogashira at meta-Position: Experimental and Computational Exploration"</p> <p>The folder structure is organised as below:</p> <p>/0_sm/: starting materials for the reactions</p> <p>/1_alkynylation_of_1b/: alkynylation reaction using substrate 1b, including regioconvergence studies</p> <p>/2_alkynylation_of_1b_aa_ligand/: alkynylation (C-H activation and 1,2-migratory insertion) reaction using MPAA ligand instead of acetate</p> <p>/3_alkynylation_of_1b_copper/: alkynylation involving Cu(OAc)2 additive</p> <p>/4_arene_site_selectivity_ortho_para/: site selectivity studies for C-H activation</p> <p>/5_alternative_oxidative_addition_TSs/: oxidative addition TSs that all have higher activation barriers that 1,2-migratory insertion TSs</p> <p>/6_ethynyltrimethylsilane_1c/: alkynylation reaction using substrate 1c, including regioconvergence studies</p> <p>/7_bromoethynylbenzene_1d/: alkynylation reaction using substrate 1d, including regioconvergence studies</p> <p>/8_other_substrates/: alkynylation reaction using </p> <p> - substrates 1e-1h (TIPS-, TBDMS-, TES-alkynyl bromide and siloxy-substituted alkynyl bromide), </p> <p> - arene substrates 4, 5, 12 having different substituents</p> <p> - substrates for products 17-19 with different DG tether lengths</p> <p>including regioconvergence studies</p>
Supporting data of the publication: Conquering chemical spaces in the billion range: is docking a computational alternative to DNA-encoded libraries?
<p>Raw data of the publication: "Conquering chemical spaces in the billion range: is high-throughput docking a computational alternative to DNA-encoded libraries?" by Levente M. Mihalovits, Tibor V. Szalai, Dávid Bajusz and György Miklós Keserű. Figures of the manuscript and the supporting information were created using these data.</p>
FIG. 10 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 10. Distributions of valid species of Xyliphius based on museum specimens and literature accounts (Alonso de Arámburu and Arámburu, 1962; Orcés, 1962; Taphorn and Marrero, 1993; Maldonado-Ocampo et al., 2005; Figueiredo and Britto, 2010; Ohara and Zuanon, 2013). Black triangles ¼ X. kryptos; white triangles ¼ X. magdalenae; white circles ¼ X. melanopterus; black circles ¼ X. lepturus; star ¼ X. sofiae; black squares ¼ X. barbatus; white diamonds ¼ X. anachoretes; circles half black, half white mark localities where X. melanopterus and X. lepturus were collected together.
FIG. 7 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 7. HRXCT model of suspensorium plus lower jaw (A) and hyoid arch (B–C) of Xyliphius sofiae, ANSP 182322, 44.1 mm SL. ach: anterior ceratohyal; ang: anguloarticular; br: branchiostegal rays; den: dentary; en: endopterygoid; hyo: hyomandibula; ih: interhyal; iop: interopercle; mc: mandibular canal tubules; met: metapterygoid; op: opercle; pch: posterior ceratohyal; pop: preopercle; qu: quadrate; ret: retroarticular; sup: suprapreopercle; uh: urohyal; vh: ventral hypohyal. Scale bar ¼ 2 mm.
FIG. 4 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 4. HRXCT model of skull and anterior body of Xyliphius sofiae, ANSP 182322, holotype, 44.1 mm SL. (A) Dorsal view. (B) Lateral view of left side. ang: anguloarticular; at: antorbital tubule; br: branchiostegal rays; cl: cleithrum; co: scapulocoracoid; cv: complex vertebrae; den: dentary; en: endopterygoid; epo: epioccipital; ex: extrascapular; fr: frontal; hyo: hyomandibula; ih: interhyal; io1: infraorbital 1; iop: interopercle; iot: infraorbital tubules; lal: lateral line tubules; let: lateral ethmoid; mc: mandibular canal tubules; mes: mesethmoid; met: metapterygoid; mnp: middle nuchal plate; mx: maxilla; na: nasal; op: opercle; pal: autopalatine; pch: posterior ceratohyal; pfr: pectoral-fin rays; pmx: premaxilla; po: preopercle; ps: pectoral-fin spine; pto: pterotic; pv5: parapophysis of vertebra five; qu: quadrate; rad: pectoral-fin radial; rb6: rib six; ret: retroarticular; sc: posttemporal-supracleithrum; soc: supraoccipital; spo: sphenotic; sup: suprapreopercle; v6: vertebrae six. Scale bar ¼ 2 mm.
FIG. 3 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 3. Ventral view of head. (A) Xyliphius sofiae, ANSP 182322, holotype, 44.1 mm SL. (B) X. melanopterus, FMNH 99495, 120.4 mm SL. (C) X. lepturus, ANSP 128941, 94.5 mm SL. (D) X. barbatus, MLP 6798, 92.0 mm SL. Photos by M. Sabaj.
FIG. 8 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 8. HRXCT model of branchial arches (A–B, left side, dorsal view, anterior up), and 5th ceratobranchial of cleared and stained specimens (left side, dorsal view, anterior up). (A) Xyliphius sofiae, ANSP 182322, holotype, 44.1 mm SL (scale bar ¼ 2 mm). (B) Unobscured dorsal view of 5th ceratobranchial in ANSP 182322 (scale bar ¼ 1 mm). (C) Xyliphius lepturus, FMNH 99488, 72.1 mm SL (scale bar ¼ 1 mm). (D) Xyliphius melanopterus, FMNH 99493, 81.9 mm SL (scale bar ¼ 1 mm). bb: basibranchial; cb: ceratobranchial; cb5: ceratobranchial five; eb: epibranchial; hb: hypobranchial; pb: pharyngobranchial; tp: tooth patch.
FIG. 2 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 2. Lateral view of select species of Xyliphius. (A) X. barbatus, MLP 6798, holotype, 92.0 mm SL. (B) X. lepturus, ANSP 128941, 94.5 mm SL. (C) X. magdalenae, CZUT-IC 1288, 75 mm SL. (D) X. melanopterus, FMNH 99495, 120.4 mm SL. (E) X. kryptos, MCNG 27310, 112.0 mm SL. Photos by M. Sabaj (A), T. Carvalho (B, E), J. Garcia-Melo (C), and A. Thomaz (D).
FIG. 6 in Description of a New Blind and Rare Species of Xyliphius (Siluriformes: Aspredinidae) from the Amazon Basin Using High-Resolution Computed Tomography
FIG. 6. HRXCT model of select bones in Xyliphius sofiae, ANSP 182322, holotype, 44.1 mm SL. Bones associated with the anterior cephalic canals of the lateral line system (anterior is left) in dorsal (A) and lateral (B) views. Entire lateral ethmoid (anterior is left) in ventral (C) and frontal (D) view. (E) Partial lateral ethmoid in dorsal view cut to about half of its depth (anterior is left). (F) Partial lateral ethmoid in frontal view cut to about vertical through origin of lateral process. at: antorbital tubule; i1–i6: infraorbital branches one to six; io1: infraorbital one; iot: infraorbital tubules; lp: lateral process of lateral ethmoid; na: nasal; obc: olfactory bulb chamber; s1–s3: supraorbital branches one to three. Scale bar ¼ 2 mm.
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.