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917 results for “Theorie”
Fig. 4 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 4. Evolving timing of the Siljan Ring (53 km diameter; see Fig. 2), depending on different timescales and improved radiometric dates.
Fig. 3 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 3. Extraterrestrial elemental proxy Ir, and supplementary Ni, against other geochemical markers in the F–F boundary beds at Kowala, Holy Cross Mountains (after Racki et al. 2002: fig. 8; used with permission from Elsevier); Ir values from an unpublished report (dated 2004) by Yuichi Hatsukawa and Mohammad Mahmudy Gharaie; Ni contents from Racka (1999: table 2); for other data see references in Racki et al. (2011).
Fig. 2 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 2. Crater temporal distribution, with possible record at the F–F boundary (A), plotted against Devonian biodiversity losses in terms of substages (B), data from Bambach 2006: fig. 1 (used with permission from the Annual Review of Earth and Planetary Sciences, Volume 34 © 2006 by Annual Reviews, http://www.annualreviews.org.), re−arranged according to the timescale of Kaufman (2006; see the updated tiiming in Becker et al. 2012; Fig. 4); the reconstructed middle Frasnian Alamo crater is also shown to reveal low biodiversity loss in that time (arrowed), as well as the controversial Woodleigh impact structure (see Fig. 5) and the biostratigraphically dated Flynn Creek submarine crater (Schieber and Over 2005). Vertical lines correspond to possible temporal ranges. Abbreviations: Carb., Carboniferous; Givet., Givetian; Lochk., Lochkovian; Prag., Pragian; Silur, Silurian.
Fig. 1 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 1. Scheme of the three successive levels in the testing process, encompassing application of the Alvarez impact theory of mass extinction, and possible errors resulting from the "great expectations syndrome" (sensu Tsujita 2001).
Fig. 6 in The Alvarez impact theory of mass extinction; limits to its applicability and the "great expectations syndrome"
Fig. 6. The Late Triassic cratering record plotted against extinction events (based on Lucas and Tanner 2008: fig. 8; crater dates modified after Schmieder and Buchner 2008 and Martin Schmieder personal communication, 2011) and two alternative time scales. Note that the 100 km−sized and precisely dated Manicouagan crater (214.56±0.05 Ma; see ottawa−rasc.ca/wiki/index.php?title=Odale−Articles− Manicouagan) is within the age range of the end−Carnian extinction only in the ICS 2009 geochronologic scheme (see also Lucas et al. 2012). Carbon isotope events compiled from Tanner (2010) and Ruhl and Kürschner (2011: fig.1). Vertical lines correspond to possible temporal ranges. J., Jurassic.
Fig. 1 in A Flashback on the Dawn of the Meteorite Impact/Extinction Theory
Fig. 1. Plot of the relationship between size, mass, energy and frequency of smaller and major impacts in the history of planet Earth. These frequencies are, after 35 years, still valid! (redrawn from Dachille 1977: fig. 2).
Data for "On the atomic structure of the β′′ precipitate by density functional theory"
<p>The dataset contains the DFT results which is the basis for the results and discussions in the related article, "On the atomic structure of the β′′ precipitate by density functional theory". The details of the DFT calculations are written in the article.</p> <p>The names of the OUTCAR files in enthalpy_study_OUTCARS.tar.gz are more or less self-explanatory, at least within the context of the journal article. The KPOINT tests have the following format for the KPOINTS "XYZ" where X is always a single digit, Y is first to get a double-digit, while Z gets a double-digit second. The max distance in reciprocal space is thus not a constant as the OUTCAR files would suggest.</p> <p> </p> <p>The LET_DATA is the linear-elastic theory displacement-field as explained in the article for different aspect ratios of the precipitate eye structure.</p>
Surrogate waveform model data for black hole binary systems computed in point-particle black hole perturbation theory
<p>This repository contains all publicly available surrogate data for gravitational waveforms produced within the point-particle black hole perturbation theory framework and calibrated to numerical relativity simulations performed with the Spectral Einstein Code (SpEC). </p> <p>Several surrogate models are currently available in this catalog:</p> <ol> <li><strong>BHPTNRSur2dq1e3</strong>, for aligned spin black hole binary systems with mass-ratios varying from 3 to 1000 and spins from −0.8≤χ1≤0.8 on the larger black hole. This surrogate model is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT) with calibration to numerical relativity (NR) data. The waveforms include all spin-weighted spherical harmonic modes up to ℓ=4 except the (4,1) and m=0 modes. Model details can be found in <a href="https://arxiv.org/abs/2407.18319">Rink et al. 2024</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="https://bhptoolkit.org/BHPTNRSurrogate/">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/BHPTNRSurrogate/blob/main/tutorials/BHPTNRSur2dq1e3.ipynb">tutorial</a>) or the GWSurrogate Python package, which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a> or <a href="https://anaconda.org/conda-forge/gwsurrogate">conda-forge</a>.</li> <li><strong>BHPTNRSur1dq1e4</strong>, an updated version of the <strong>EMRISur1dq1e4 </strong>model described below. The updated version includes better calibration to NR, a smoother transition to plunge model, and more harmonic modes. Model details can be found in <a href="https://arxiv.org/abs/2204.01972">Islam et al. 2022</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="https://bhptoolkit.org/BHPTNRSurrogate/">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/BHPTNRSurrogate/tree/main/tutorials/BHPTNRSur1dq1e4">tutorial</a>) or the GWSurrogate Python package, which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a> or <a href="https://anaconda.org/conda-forge/gwsurrogate">conda-forge</a>.</li> <li><strong>EMRISur1dq1e4</strong>, for non-spinning black hole binary systems with mass-ratios varying from 3 to 10000. This surrogate model is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT), with the total mass rescaling parameter tuned to NR simulations. Available modes are [(2,2), (2,1), (3,3), (3,2), (3,1), (4,4), (4,3), (4,2), (5,5), (5,4), (5,3)]. The m<0 modes are deduced from the m>0 modes. Model details can be found in <a href="https://arxiv.org/abs/1910.10473">Rifat et al. 2019</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="http://github.com/BlackHolePerturbationToolkit/EMRISurrogate">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/EMRISurrogate/blob/master/EMRISur1dq1e4.ipynb">tutorial</a>) or the GWSurrogate Python package (Jupyter notebook <a href="https://github.com/sxs-collaboration/gwsurrogate/blob/master/tutorial/notebooks/nonspinning_nr_emri.ipynb">tutorial</a>), which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a>.</li> </ol>
Structure and Excitation Spectra of Third-Row Transition Metal Hexafluorides Based on Multi-Reference Exact Two-Component Theory: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Structure and Excitation Spectra of Third-Row Transition Metal Hexafluorides Based on Multi-Reference Exact Two-Component Theory", by Ayaki Sunaga.</p>
Assessing Student Sustainable Learning Engagement in Mobile Learning through Social Cognitive Theory and Social Learning Theory
<p><span>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em>Project ID: HORIZON MSCA-SE 101086381)</em>.</span><span> the data was collected as part of ODDEA WP2.</span></p>
Authors and Theories - Comparative table (Update October 2024)
<p>This Excel file features a comparative chronological table/report including data on authors, theories, discoveries, inventions, major events, studies, and the preliminary results of my research work carried out through the outgoing phase of my MSCA Fellowship at Johns Hopkins University and Ca' Foscari University Venice (Horizon 2020 – MGA MSCA-IF – Grant agreement No. 101019781 – SOUNDEPTH).</p>
Gaussian16 data for "Dynamic electronic structure fluctuations in the de novo peptide ACC-dimer revealed by first-principles theory and machine learning"
<p>This is the Gaussian 16 input and corresponding output, which was used as input into the machine learning presented in the paper titled "Dynamic electronic structure fluctuations in the de novo peptide ACC-dimer revealed by first-principles theory and machine learning". This upload is required before submission of the paper.<br><br>The 1001 and 100 snapshots from different extractions are preserved in separated directories. Each snapshot directory <code>*_snapshot</code> has the initial GROMACS snapshot <code>test_*.pdb</code> , the geometry after truncating the solvation shell in various formats, the Gaussian16 input, qsub input and the output directory <code>*.1</code> with a JobID number assigned by qsub. The output directory has the standard output from Gaussian in a <code>.log</code> file and <code>grep</code>ed output from the <code>.fchk</code> file in <code>*.out</code> .</p>
Amorphous Niobium Oxide Structures Calculated from First Principles using Density Functional Theory and Molecular Dynamics
<p>The dataset contains fifteen different amorphous niobium oxide structures. Nine of the structures have the same stoichiometry as Nb2O5. The other six are defect structures containing 1 or 2 oxygen vacancies, or 1 or 2 interstitial oxygens, or 1 Nb vacancy. Each of the structure files is in the VASP POSCAR file format. Each structure was created using ab-initio molecular dynamics at 5000~K to liquidate the structure, then snapshots of the structure were taken every 2 ps, and geometry optimizations were performed on each individual snapshot. The naming convention is relatively simple: 'conf_x_POSCAR' is a stoichiometric POSCAR, and 'conf_x_oadd1_POSCAR' is a defect structure originating from structure 'x' with a single oxygen interstitial. The defect labels correspond to 1 oxygen interstitial (oadd1), 2 oxygen interstitials (oadd2), 1 oxygen vacancy (ovac1), 2 separated oxygen vacancies (ovac2), 2 nearest neighbor oxygen vacancies (ovac2nn), and 1 Nb vacancy (nbvac).</p>
Age-specific effects of deletions: Implications for ageing theories
<p><span>Evolution of ageing requires mutations with late-life deleterious effects. Classic theories assume these mutations either have neutral (Mutation Accumulation) or beneficial (Antagonistic Pleiotropy) effects early in life, but it is also possible that they start out as mildly harmful and gradually become more deleterious with age. Despite a wealth of studies on the genetics of ageing, we still have a poor understanding of how common mutations with age-specific effects are and what ageing theory they support. To advance our knowledge on this topic we measure a set of genomic deletions for their heterozygous effects on juvenile performance, fecundity at three ages, and adult survival. Most deletions have age-specific effects, and these are commonly harmful late in life. Many of the deletions assayed here would thus contribute to ageing if present in a population. Taking only age-specific fecundity into account, some deletions support Antagonistic Pleiotropy, but the majority of them better fit a scenario where their negative effects on fecundity become progressively worse with age. Most deletions have a negative effect on juvenile performance, a fact which strengthens the conclusion that deletions primarily contribute to ageing through negative effects that amplify with age.</span></p>
Dataset for the publication "Theory and Experimental Validation of Two Techniques for Compensating VT Nonlinearities"
<p>This is dataset for paper published:</p> <p>G. D’Avanzo <em>et al</em>., "Theory and Experimental Validation of Two Techniques for Compensating VT Nonlinearities," in <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 71, pp. 1-12, 2022, Art no. 9001312, doi: 10.1109/TIM.2022.3147883.</p>
Database used in : Analysis of intermunicipal journeys for cardiac surgery in Brazilian Unified Health System (SUS): an approach based on network theory
<p>Data and scripts referring to the results generated in the article entitled: <strong>Analysis of intermunicipal journeys for cardiac surgery in Brazilian Unified Health System (SUS): an approach based on network theory.</strong></p> <p> </p> <p>To obtain the results of the work the following sequence of database treatment was performed:</p> <p> </p> <p>DATASUS --> BASE_PER_YEAR --> EDGES_BASE --> EDGES_VC_BASE</p> <p>The bases were downloaded from the DATASUS site (link: https://datasus.saude.gov.br/transferencia-de-arquivos/#) in .dbc format separated by month and year; using Tabwin we joined the bases generating a base for each year in csv format. The reformatted bases are gathered together in the file PER_YEAR_BASE.ZIP; from the bases for each year we manually built the files in csv format with the list of the edges with the following fields: "Source", "Target", "Type", "Id", "Label" and "Weight". The "Source" column was filled with data from MUNIC_RES and the "Target" column with data from MUNIC_MOV. The "ID" and "Weight" fields were filled in automatically using Gephi, where the "Weight" column represents the sum of the edge, defined by the pair of Source and Target columns, were repeated throughout the year. This generated the bases containing the list of edges that are grouped in the file EDGES_BASE.ZIP. Each base was filtered to contain only edges related to the city "Vitória da Conquista" and grouped in the file EDGES_VC_BASE.zip</p> <p>INDE BASE --> NODES_BASE</p> <p>To build the list of nodes containing the list of municipalities with their respective geographical locations (in UTM), we used the database of the INDE (available on the link: https://visualizador.inde.gov.br/). The file in shape format was treated in the ArqGis program and the database with the network nodes was created (file NODES_BASE.csv).</p> <p>EDGES_VC_BASE and NODES_BASE --> NETWORK</p> <p>Using the program Gephi we joined the bases referring to the edges (EDGES_VC_BASE) and those referring to the nodes of the network (NODES_BASE) and built the networks for each year studied for the city of "Vitória da Conquista". All networks are in gephi format and compressed in the NETWORKS.zip file.</p> <p>EDGES_VC_BASE and NODES_BASE --> INDICES</p> <p>Using the R script "distance.R" and using as input the files of edges (EDGES_VC_BASE) and nodes (NODES_BASE) we generate files in csv format with the columns: dist_med_in , dist_med_out, Flow_in and flow_out. The indexes dist_med_in and dist_med_out represent the average distance traveled in meters to enter and leave the municipality, respectively; the indexes flow_in and flow_out estimate the quantity of people that entered and left the municipality. All index files are grouped in the compressed file INDICES.zip.</p> <p>The last two digits at the end of all file names represent the year of analysis. </p>
Replication package for Shishkin ® Ortoleva "Ambiguous Information and Dilation: An Experiment" (Journal of Economic Theory)
<p>Replication package for Shishkin ® Ortoleva "Ambiguous Information and Dilation: An Experiment" (Journal of Economic Theory).</p> <p>It contains raw experimental data and code producing tables and figures from the paper.</p>
Dataset: Core excitations and ionizations of uranyl in Cs2UO2Cl4 from relativistic embedded damped response time-dependent density functional theory and equation of motion coupled cluster calculations
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Core excitations and ionizations of uranyl in Cs2UO2Cl4 from relativistic embedded damped response time-dependent density functional theory and equation of motion coupled cluster calculations", by Wilken Aldair Misael and Andre Severo Pereira Gomes. It also contains the figures used in the manuscript.</p>
When the practice does not meet the theory: results from an Italian survey on the clini-cal and pathway management of inpatients with decompressive craniectomy or cranioplasty admitted to rehabilitation
<p>Cranioplasty (CP) is supposed to improve the functional outcome of severe acquired brain injury (sABI) patients with decompressive craniectomy (DC). However, ongoing controversies exist regarding its indications, optimum materials, timing, complications, and relationships with hydrocephalus (HC). For these reasons, an International Consensus Conference (ICC) on CP in traumatic brain injury (TBI) was held in June 2018 to issue some recommendations.</p> <p>AIM: To investigate cross-sectionally before the ICC the prevalence of DC/CP in sABI inpatients admitted to neurorehabilitation units in Italy; to assess the perception of Italian clinicians working in the sABI neurorehabilitation settings on the management of inpatients with DC/CP during their rehabilitation stay.</p> <p>DESIGN: Cross-sectional.</p> <p>SETTING AND POPULATION: Physiatrists or neurologists working in 38 Italian rehabilitation centers involved in the care of sABI, giving a pooled sample of 599 inpatients.</p> <p>METHODS: Survey questionnaire consisting of 21 closed-ended questions with multiple-choice answers. Sixteen questions regarded the respondents' opinions and experiences regarding the clinical and management aspects of patients. Survey data were collected via e-mail between April and May 2018.</p>
Global dataset for "Global leaf-trait mapping based on optimality theory "
<p>This repository contains Global data used for “<em>Global leaf-trait mapping based on optimality theory</em><strong>” </strong>published in GEB.</p> <ol> <li>Global_Maps_SLA represents climatology of published Global SLA used for comparison (details products see table 1 and figure 4).</li> <li>Global_Maps_Na represents climatology of published Global Narea used for comparison (details see table 1 and figure 4).</li> <li>Global_Maps_Nmass represents climatology of published Global Nmass used for comparison (details see table 1 and figure 4).</li> <li>TS_SLA is simulated time-series of <em>SLA</em> based on optimality theories from 1992 to 2015</li> <li>TS_Na is simulated time-series of <em>Narea </em>based on optimality theories from 1992 to 2015</li> <li>TS_Nmass is simulated time-series of <em>Nmass </em>based on optimality theories<em> </em> from 1992 to 2015</li> <li>TS_LMA_decidudous is simulated time-series of deciduous <em>LMA</em> based on optimality theories from 1982 to 2016</li> <li>TS_LMA_evergreen is simulated time-series of evergreen <em>LMA</em> based on optimality theories from 1982 to 2016</li> <li>TS_Vcmax25 is simulated time-series of Vcmax25 based on optimality theories from 1982 to 2016</li> </ol>
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.