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528 results for “equivalence”
Supplementary data to "Radiative forcing and equivalent effective chlorine due to hydrochlorofluorocarbons peaked in 2021"
<p><span>README for Supplementary data to “</span><span>Radiative forcing and equivalent effective chlorine due to hydrochlorofluorocarbons peaked in 2021”</span></p> <p> </p> <p><span>This repository contains 4 folders:</span></p> <p><span>1) agage: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the AGAGE network.</span></p> <p><span>2) noaa: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the NOAA network.</span></p> <p><span>3) vollmer: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the measurements published in Vollmer et al. (2021).</span></p> <p><span>4) Projections: contains a csv file with the merged mole fractions (i.e., mean) from the various networks and the projected quantities.</span></p> <p> </p> <p><span>The 12-box model and the method used to quantify global mean mole fractions are available via GitHub (https://github.com/mrghg/py12box (last accessed 5 March 2024) and https://github.com/mrghg/py12box_invert (last accessed 5 March 2024)) and Zenodo (https://doi.org/10.5281/zenodo.6857447 and https://doi.org/10.5281/zenodo.6857794).</span></p> <p> </p> <p><span>AGAGE data are also available at http://agage.mit.edu/data/agage-data (last accessed 5 March 2024) and https://data.ess-dive.lbl.gov/ (current dataset <a href="https://doi.org/10.15485/1998580"><span>https://doi.org/10.15485/1998580</span></a>) and newer data can be made available upon request. The most recent NOAA atmospheric observations are available at https://gml.noaa.gov/aftp/data/hats/hcfcs/ (last accessed 5 March 2023). </span></p> <p> </p> <p><span>References:</span></p> <p><span>Vollmer, M. K. et al. Unexpected nascent atmospheric emissions of three ozone-depleting hydrochlorofluorocarbons. Proc Natl Acad Sci USA 118, e2010914118 (2021).</span></p>
CEAD Population Survey Quito: Data and Variable Code Equivalencies
<p>We conducted a cross-sectional study with 656 adults from health district 17D06, South Quito, Ecuador, using multi-stage cluster sampling. The study followed an adapted WHO STEPwise approach, considering Ecuador's 2018 STEPwise survey.</p> <p>For more information, contact Clara Blanes Mira: c.blanes@umh.es</p> <p> </p>
Seamount volume equivalent layer thickness for the Pacific plate
<p>Volume equivalent layer thickness (VELT) grids are computed from seamount topography in the Pacific plate. We use SRTM15+V2.0 global bathymetric grid for seafloor topography. We first apply a white-Tophat filter to the bathymetry data to isolate short-spatial-wavelength seamount topography above the long-wavelength seafloor. Subsequently, we apply Gaussian Process regression to determine seamount structure above the seafloor in order to extrapolate structure beneath the sediment (GlobSed V3) to the basaltic basement (i.e., the top of the oceanic crust). Finally, we map the spatial distribution of seamount volume on the Pacific plate by calculating a volcanic equivalent layer thickness (VELT) using a moving window of 300 km × 300 km.</p> <p>The VELT grids have a grid spacing of 37 km x 37 km and are provided in GeoTIFF format in a cylindrical equal area projection with the following PROJ string:<br> +proj=cea +lon_0=180 +lat_ts=30 +x_0=0 +y_0=0 +ellps=WGS84 +units=m +no_defs</p> <ul> <li>VELT_above_seafloor.tif is the grid for VELT above the top of the sediments.</li> <li>VELT_above_basement.tif is the grid for VELT above the top of the basaltic basement.</li> </ul>
Long-term reconstruction of satellite-based precipitation, soil moisture, and snow water equivalent in China
<p>A daily 0.1<sup>°</sup> dataset of precipitation (<em>P</em>), soil moisture (SM), and snow water equivalent (SWE) in 1981-2017 across China.</p>
Dataset of Functionally Equivalent Java Methods
<p>This is a dataset of functionally equivalent Java methods.</p> <p>This dataset is published as a supplemental data as the following submission.</p> <p> </p> <p>Yoshiki Higo, Shinsuke Matsumoto, Shinji Kusumoto, and Kazuya Yasuda, "Constructing Dataset of Functionally Equivalent Java Methods Using Automated Test Generation Techniques", submitted to MSR 2022.</p> <p> </p> <p>This dataset includes 276 groups of functionally equivalent Java methods, which have been manually verified by the authors.</p> <p>The 276 groups include 728 Java methods in total.</p>
Text-fig. 4. Graphical visualization of Phytogeographic Reference Regions Assessment (PRRA) of nearest living relative genera of fossil-taxa from late Early Miocene Wiesa assemblage in eastern Germany. Analysis yields only NLRs which have modern distribution area (partly) in E and SE Asia. For relationships of fossil-taxa to nearest living relatives or ecological equivalents, see Tab. 6; taxa used for analysis marked with asterisks. Three geographic resolutions conducted: a – grid with 1.5° latitude/longitude resolution, b – grid with 2°, c – grid with 3°; similarity column indicates cooccurrences of genera of nearest living relatives in single grid box. Maximum value in our analysis: grid box marked with arrow in map a, located in western Yunnan Province, P. R. China and southern Kachin Province, NE Myanmar (east of Myitkyina city), area with 97.371 7–98.874 2° longitude and 24.586 7–25.837 5° latitude, yields 23 co-occurring species of 13 genera (Tab. 7). in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)
Text-fig. 4. Graphical visualization of Phytogeographic Reference Regions Assessment (PRRA) of nearest living relative genera of fossil-taxa from late Early Miocene Wiesa assemblage in eastern Germany. Analysis yields only NLRs which have modern distribution area (partly) in E and SE Asia. For relationships of fossil-taxa to nearest living relatives or ecological equivalents, see Tab. 6; taxa used for analysis marked with asterisks. Three geographic resolutions conducted: a – grid with 1.5° latitude/longitude resolution, b – grid with 2°, c – grid with 3°; similarity column indicates cooccurrences of genera of nearest living relatives in single grid box. Maximum value in our analysis: grid box marked with arrow in map a, located in western Yunnan Province, P. R. China and southern Kachin Province, NE Myanmar (east of Myitkyina city), area with 97.371 7–98.874 2° longitude and 24.586 7–25.837 5° latitude, yields 23 co-occurring species of 13 genera (Tab. 7).
Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014
<p>We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfalls occur in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 ×10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse-rate coefficients and hygrobarometric adjustments to simulate snow series at 100 m elevations bands for each 10 × 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism and risk management .</p> <p> </p>
Figure 1: Asymmetric representation for the ¯rst four generations, in its elec- trical equivalent-THE RESPIRATORY IMPEDANCE IN AN ASYMMETRIC MODEL OF THE LUNG STRUCTURE
<p>For example, the average of the radius ratio<br> changes from 2¡0:1713 = 0:8881 to 0:8923 when only the ¯rst 16 generations are<br> taken into account, respectively to 0:8783 for the alveoli (generations 17-24)<br> [5]. This implies that the homothety factor changes, depending on the spatial<br> location within the tree. On the other hand, if we analyze the radius ratio from<br> generations 1 to 24 in steps of 4, we obtain an average of 0:8535, whereas if we<br> use steps of 2, we obtain an average homothety factor of 0:8623. These changes<br> might not seem signi¯cant, but one should recall that they are originated by<br> the symmetric geometry of the respiratory tree. However, when asymmetry<br> is considered, one deals with several homothety factors, i.e. as schematically<br> drawn in figure 1.</p>
Figure 1: Asymmetric representation for the ¯rst four generations, in its elec- trical equivalent-THE RESPIRATORY IMPEDANCE IN AN ASYMMETRIC MODEL OF THE LUNG STRUCTURE
<p>These changes<br> might not seem signi¯cant, but one should recall that they are originated by<br> the symmetric geometry of the respiratory tree. However, when asymmetry<br> is considered, one deals with several homothety factors, i.e. as schematically<br> drawn in ¯gure 1.</p>
Probability distributed equivalent circuit model - Data
<h2>General information</h2> <p>Measurement data, parameter and analytical functions for the simulation of the results described in the publication "A physically motivated hysteresis model for lithium-ion batteries using a probability distributed equivalent circuit" published in Nature Communications Engineering in 2024 by Jahn et al. </p> <p>Matlab Code for the simulation can be found under:</p> <p><a href="https://www.doi.org/10.5281/zenodo.10852695">www.doi.org/10.5281/zenodo.10852695</a></p> <h2>File description</h2> <h3>_incrOCV.csv</h3> <p>Measurement: Full cycle with current interupts at specific states of charge. </p> <p>Data: nx2 vector [Q U] with <strong>Q</strong> being the currently stored amount of charge in the cell and <strong>U</strong> being the voltage measured </p> <h3>_pOCV.csv</h3> <p>Measurement: C/20 constant current full cycle starting at fully discharge state.</p> <p>Data: nx3 vector [t Q U] with <strong>t</strong> being the recorded time, <strong>Q</strong> the amount of charge stored in the cell, and <strong>U</strong> the measured terminal voltage.</p> <h3>HysPowerTest_ ... _SOC50.csv / HysPowerTest_ ... _SOC100.csv</h3> <p>Measurement: <br>SOC50 - starting at 0 % SOC with C/2 constant current charge to 50 % SOC followed by a 4C constant current discharge to the lower cut-off voltage. <br>SOC100 - starting at 100 % SOC with C/2 constant current discharge to 50 % SOC followed by a 4C constant current discharge to the lower cut-off voltage. </p> <p>Data: nx4 vector [t Q I U] with <strong>t</strong> being the recorded time, <strong>Q</strong> the amount of charge stored in the cell, <strong>I</strong> the current flowing, and <strong>U</strong> the measured terminal voltage.</p> <h3>Hysteresis_SOC50Loops_ ... </h3> <p>Measurement: Partial cycles with widening SOC window in 5 % steps in higher and lower SOC direction. The first hysteresis loop is measured from 45 % SOC to 55 % SOC while the final loop is measured from 0 % SOC to 100 % SOC.</p> <p>Data: 9x5 Matlab struct with each row being a partial cycle. Each column corresponds to [t SOC U I Q] of this partial cycle. <strong>t</strong> being the recorded time, <strong>SOC</strong> the amount of stored charge referenced to the previously determined cell capacity, <strong>Q</strong> the amount of charge stored in the cell, <strong>I</strong> the current flowing, and <strong>U</strong> the measured terminal voltage.</p> <p><strong>Parameter sets</strong></p> <p>Parameter sets for the Matlab code for the simulation of the probability distributed equivalent circuit model, available under Zenodo repository given in the Related Works section.</p> <p>param_ocpn_graphite.mat - OCP function parameter for the graphite anode half-cell<br>20230221_graphite_opt_parameter_man - optimized model parameter for the graphite half-cell<br>param_ocpn_lfp.mat - OCP function parameter for the LFP cathode half-cell<br>20230221_lfp_opt_parameter_man.mat - optimized model parameter for the LFP half-cell<br>A123_parameter_posPulse/A123_parameter_negPulse - parameter of the R-RC ECM extracted using positive or negative pulses respectively</p>
Fig. 7. Connection between UABM and ulnerve nerve. A in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 7. Connection between UABM and ulnerve nerve. A. In the proximal forearm, a thin branch from the ulnar nerve meets a branch from the UABM to make a neural arch that gives off motor branches to the flexor digitorum profundus (FDP) of the ring and little fingers. B. A thin proximal branch (hollow arrow) from the ulnar nerve unites with the radial bundle (motor fasciculi) of the UABM and the other thicker distal one (solid arrow) unites with its ulnar bundle (sensory fasciculi).
Fig. 3. Brachial plexus. A in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 3. Brachial plexus. A. The brachial plexus is composed of the upper trunk·C4, C5 and C6 roots, the middle trunk·C7 root and the lower trunk·C8 root. B. The subclavian artery was found to split the middle trunk into two bundles: upper and lower. The upper bundle consists of the anterior and posterior divisions, and the lower bundle is the medial division (Eisler) going to the medial cord.
Fig. 4 in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 4. Components of UABM. A. The UABM is composed of ᶃfasciculi from the medial division of the middle trunk·C7 root and ᶄfasciculi from the lower trunk·C8 root, and some from ᶅthe lateral cord. B. Intraneural dissection of the medial cord revealed that one half of fasciculi going to UABM come from the medial division of the middle trunk·C7 root (Eisler) and the other half from the lower trunk·C8 root.
Fig. 6 in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 6. Motor branches to FCU of the ulnar nerve. Three motor branches to the flexor carpi ulnaris (FCU); two to the proximal and middle portion of the muscle, and another to its distal portion. A thin branch is also seen to meet with a branch from UABM to make a neural arch.
Fig. 2 in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 2. Innervation of all ulnar intrinsic muscles by the radial bundle of UABM. The radial bundle (motor branch) first gives off branches to the hypothenar muscles and to the lumbrical muscles of the little and ring fingers (marked with asterisks), and then to interossei (4th DI, 3rd PI and 3rd DI, 2nd PI). It goes further radially to give branches to both heads of ADP.
Fig. 5 in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 5. The route of fasciculi composing the UABM. Several fasciculi of C8 root going to the UABM pass anterior or posterior to the ulnar nerve, two thick fasciculi anterior, and two thick and one thin fasciculi posterior. Three fasciculi from the lateral cord join the UABM.
Fig. 1 in The Nerve Bundle via the Median Nerve Innervating the Ulnar Intrinsic Muscles of the Hand in a Gorilla Equivalent to the Deep Branch of the Ulnar Nerve in the Human
Fig. 1. Ulnar antebrachial branch of the median nerve (UABM). It branched off the median nerve at the anterior aspect of the elbow and ran ulno-distally in the forearm toward the wrist. The ulnar artery is seen to come out from under the ulnar head of the pronator teres and to run distally along but about one cm apart from UABM.
Bio-ML: Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching
<p> </p> <blockquote> <p><strong>This version is used in the Bio-ML track of the OAEI 2024; the only change compared to the OAEI 2023 is the deletion of certain training subsumption mappings.</strong></p> </blockquote> <p> </p> <h3><strong>Overview</strong></h3> <p>The purpose of these datasets is to support <em>equivalence</em> and <em>subsumption</em> ontology matching.</p> <p>There are five ontology pairs extracted from MONDO and UMLS:</p> <table> <tbody> <tr> <td>Source</td> <td>Task</td> <td>Category</td> <td>#SrcCls</td> <td>#TgtCls</td> <td>#Ref (equiv)</td> <td>#Ref (subs)</td> </tr> <tr> <td>Mondo</td> <td>OMIM-ORDO</td> <td>Disease</td> <td>9,648</td> <td>9,275</td> <td>3,721</td> <td>103</td> </tr> <tr> <td>Mondo</td> <td>NCIT-DOID</td> <td>Disease</td> <td>15,762</td> <td>8,465</td> <td>4,686</td> <td>3,338 (-1)</td> </tr> <tr> <td>UMLS</td> <td>SNOMED-FMA</td> <td>Body</td> <td>34,418</td> <td>88,955</td> <td>7,256</td> <td>5,453 (-53)</td> </tr> <tr> <td>UMLS</td> <td>SNOMED-NCIT</td> <td>Pharm</td> <td>29,500</td> <td>22,136</td> <td>5,803</td> <td>4,224 (-1)</td> </tr> <tr> <td>UMLS</td> <td>SNOMED-NCIT</td> <td>Neoplas</td> <td>22,971</td> <td>20,247</td> <td>3,804</td> <td>213</td> </tr> </tbody> </table> <p>The "-" numbers reflect the changes due to lthe deletion of certain training subsumption mappings.</p> <p>The main track is available at "bio-ml", where each pair is associated with a task folder, containing the source and target ontologies, reference equivalence mappings (in "refs_equiv"), reference subsumption mappings ("refs_subs"). </p> <p>The special sub-track is available at "bio-llm", where each pair is associated with a task folder, containing the source and target ontologies, and the test candidate mappings. </p> <p> </p> <h3><strong>Citation</strong></h3> <p><strong>Bio-ML (Main Track)</strong></p> <pre>```<br>@inproceedings{he2022machine, title={Machine learning-friendly biomedical datasets for equivalence and subsumption ontology matching}, author={He, Yuan and Chen, Jiaoyan and Dong, Hang and Jim{\'e}nez-Ruiz, Ernesto and Hadian, Ali and Horrocks, Ian}, booktitle={International Semantic Web Conference}, pages={575--591}, year={2022}, organization={Springer} }<br>```</pre> <p><strong>Bio-LLM (Sub-track)</strong></p> <pre>```<br>@article{he2023exploring, title={Exploring large language models for ontology alignment}, author={He, Yuan and Chen, Jiaoyan and Dong, Hang and Horrocks, Ian}, journal={arXiv preprint arXiv:2309.07172}, year={2023} }<br>```</pre> <p> </p> <h3><strong>Important Links</strong></h3> <ul> <li>See detailed documentation at: <a href="https://krr-oxford.github.io/DeepOnto/bio-ml">https://krr-oxford.github.io/DeepOnto/bio-ml</a>.</li> <li>See the OAEI Bio-ML track at: <a href="https://www.cs.ox.ac.uk/isg/projects/ConCur/oaei/">https://www.cs.ox.ac.uk/isg/projects/ConCur/oaei/</a></li> <li>See our resource paper for the original Bio-ML at <a href="https://arxiv.org/abs/2205.03447">arxiv</a> or <a href="https://link.springer.com/chapter/10.1007/978-3-031-19433-7_33">springer</a> (accepted at <em>ISWC-2022</em> and nominated as the <em>best resource paper candidate</em>). See our poster paper for the Bio-LLM sub-track at <a href="https://arxiv.org/abs/2309.07172">arxiv </a>(accepted at <em>ISWC-2023 Posters & Demos</em>).</li> </ul> <p> </p> <h3><strong>Changelog</strong></h3> <p>The only change in this version compared to the OAEI 2023 is the deletion of certain training subsumption mappings that can be directly exploited through deductive reasoning.</p>
Feature count data for Love et al. 2019 analysis for "Using equivalence class counts for fast and accurate testing of differential transcript usage" paper
<p>Feature count data for Love et al. 2019 analysis used in the "Using equivalence class counts for fast and accurate testing of differential transcript usage" paper. For reproducing the analyses and figures using the <a href="https://github.com/Oshlack/ec-dtu-paper/">ec-dtu-paper</a> code.</p> <p>Contains:</p> <ul> <li>Equivalence class count matrix for all 24 samples (using counts from Salmon)</li> <li>Salmon quantification results for all 24 samples</li> <li>Exon counts for all 24 samples using DEXSeq-count</li> </ul>
Oracles for the Equivalence of Java Bytecode
<p>Incidents like <em>log4shell</em> and <em>SolarWinds</em> have led to an increased focus on software supply chain security. A particular concern is the detection and prevention of compromised builds. A common approach is to independently re-build projects, and compare the results. This leads to the availability of different binaries built from the same sources, and raises the question of how to compare the respective binaries (to confirm the integrity of builds, to detect compromised builds, etc). It is however not clear how to do this: naive bitwise comparison is often too strict, and establishing the behavioural equivalence of two binaries is undecidable. <br> <br>A pragmatic step towards a solution is to provision a benchmark that can be used to test and train equivalence relations. We present such a benchmark for Java bytecode, consisting of \input{generated/total-oracle-record-count}pairs of binaries (compiled Java classes) labelled as to whether these classes are equivalent or not. We refer to these pairs as equivalence and non-equivalence oracles, respectively. <br> <br>We derive equivalence oracles from building 56 projects and project versions using 32 dockerised build environments (with different compilers, compiler versions and configurations). Non-equivalence oracles are derived from three different sources: (1) proven breaking API changes, (2) semantic code changes synthesised by means of bytecode mutations, and (3) code changes extracted from vulnerability patches.</p> <p> </p> <p>A detailed description of the dataset can be found in: </p> <p><em>Jens Dietrich, Tim White, Mohammad Mahdi Abdollahpou, Elliott Wen and Behnaz Hassanshahi: BenEq -- A Benchmark of Compiled Java Programs to Assess Alternative Builds. Proceedings of the ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses (SCORED '24). </em></p>
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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)
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DANDI Archive for NWB datasets
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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.