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1,609 results for “polarization”
ICON-LEM Ny-Ålesund low-level clouds polar night and polar day 2021/2022
<h3>Low-level clouds during the polar night and polar day simulated in ICON-LEM for Ny-Ålesund </h3> <p>This data set was created using the ICON-LEM model with ca. 600m resolution and a diagnostic tool "microphysical wrapper". It contains the meteogram output of the Ny-Ålesund column (Svalbard) and the microphysical process rates. The data was created for the polar night (Nov 2021- Feb 2022) and polar day (May - Aug 2022). Clouds are classified as low-level if their cloud top height (CTH) is below 2.5 km and the distance between any cloud with CTH above 2.5 km is at least 500 m higher. The data set was first used and described in the <em>publication: </em></p> <p>T. Kiszler, D. Ori, V. Schemann<em>. </em>(preprint) Microphysical processes involving the vapour phase dominate in simulated low-level Arctic clouds. <em>Atmospheric Physics and Chemistry, </em>https://doi.org/10.5194/egusphere-2023-2986<em><br></em></p> <p>This data is related to the repository <a href="https://github.com/TracyMcBean/Kiszler_et_al_2023_microphysics">https://github.com/TracyMcBean/Kiszler_et_al_2023_microphysics</a></p> <p><em>File description:</em></p> <p>*_PN is polar night data</p> <p>*_PD is polar day data</p> <p>LLC_<em>meteo_<yyyymm>_ICONv1</em>_v6.nc : Contains the meteogram variables (thermodynamics, surface variables, hydrometeors)</p> <p>LLC_wrapper_mass_<yyyymm>_ICONv1_v6.nc : Contains hydrometeors masses after diagnostic run of a microphysical wrapper</p> <p>LLC_wrapper_tend_<yyyymm>_ICONv1_v6.nc : Contains the mircophysical process rates showing the mass change per timestep </p> <p>low_cloud_times_v6_*.csv : Contains the date and time when a low-level cloud was detected</p>
DU00-W-212 airfoil polars, sinusoidal inflow
<p>Averaged lift and drag coeffficients of a DU00-W-212 profile in sinusoidally varying inflow (turbulence level approx. 5%) generated with an active grid at Reynolds numbers 500,000 and 900,000.</p> <p>Data is obtained with a three-component load cell and via integration of 48 scanned pressure tabs along the chord.<br> Standard wind tunnel corrections according to Allen & Vincenti are applied.</p> <p>Data sets 182, 183, 186, 188: flow tripped on the surface at 1.5% chord on upper airfoil side, 10% chord on lower airfoil side<br> Data sets 183, 188, 242, 245: measured starting at positive angles of attack (AOA) to negative AOAs<br> Data sets 182, 186, 243, 244: measured starting at negative angles of attack (AOA) to positive AOAs</p> <p>The experiment was performed within in the EU-funded project AVATAR (www.eera-avatar.eu).</p>
DU00-W-212 airfoil polars, laminar inflow
<p>Averaged lift and drag coeffficients of a DU00-W-212 profile in laminar flow (background turbulence level approx. 0.3%) at Reynolds numbers 500,000 and 900,000.</p> <p>Data is obtained with a three-component load cell and via integration of 48 scanned pressure tabs along the chord.<br> Standard wind tunnel corrections according to Allen & Vincenti are applied.</p> <p>Data sets 119, 120, 121, 122: flow tripped on the surface at 1.5% chord on upper airfoil side, 10% chord on lower airfoil side<br> Data sets 104, 107, 119, 122: measured starting at negative angles of attack (AOA) to positive AOAs<br> Data sets 105, 106, 120, 121: measured starting at positive angles of attack (AOA) to negative AOAs</p> <p>The experiment was performed within in the EU-funded project AVATAR (www.eera-avatar.eu).</p>
DU00-W-212 airfoil polars, mimicked DanAero inflow
<p>Averaged lift and drag coeffficients of a DU00-W-212 profile in turbulent inflow generated with an active grid at Reynolds numbers 500,000 and 900,000. The inflow pattern was mimicked from measurements a the blade with a 5-hole pressure probe performed in teh DanAero project.</p> <p>Data is obtained with a three-component load cell and via integration of 48 scanned pressure tabs along the chord.<br> Standard wind tunnel corrections according to Allen & Vincenti are applied.</p> <p>Data sets 203, 204, 210, 211: flow tripped on the surface at 1.5% chord on upper airfoil side, 10% chord on lower airfoil side<br> Data sets 203, 211, 225, 230: measured starting at positive angles of attack (AOA) to negative AOAs<br> Data sets 204, 210, 224, 239: measured starting at negative angles of attack (AOA) to positive AOAs</p> <p>The experiment was performed within in the EU-funded project AVATAR (www.eera-avatar.eu).</p>
Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux -- Supplemental Data Set: Sea Level Sensitivity Kernels
<p><strong>Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux<br> SUPPLEMENTAL DATA SET: SEA LEVEL SENSITIVITY KERNELS</strong></p> <p>To accompany</p> <p> Jerry X. Mitrovica, Carling C. Hay, Robert E. Kopp, Christopher Harig, and<br> Konstantin Laytchev (2018). Quantifying the Sensitivity of Sea Level Change<br> in Coastal Localities to the Geometry of Polar Ice Mass Flux. Journal of<br> Climate. doi: 10.1175/JCLI-D-17-0465.1.</p> <p>We provide sea level kernels for ~740 tide gauge sites in the Permanent Service for Mean Sea Level (PSMSL) database (Holgate et al., 2013). Kernels associated with sensitivities to Greenland and Alaskan glacier melt are given on a spatial grid covering the globe, with 512 latitude rows (i=1,512) and 1024 longitude (j=1,1024) columns.</p> <p>Longitude values are evenly spaced moving eastward from Greenwich (the jth grid point has an east longitude value of (j-1)×360°/1024). Latitude values are Gauss-Legendre points beginning close to the North Pole and ending near the South Pole. Kernels associated with sensitivities to Antarctic melt are given on a spatial grid covering the globe, with 256 (Gauss-Legendre) latitude rows (i=1,256) and 512 longitude (j=1,512) columns. Longitude values are evenly spaced moving eastward from Greenwich.</p> <p>The format of the files is: </p> <p> grid_sitenumber_region.txt</p> <p>where “region” is either “green” (Greenland), “ant” (Antarctic) or “Alaska” (Alaska). The list of sites (and site numbers) is provided in the sites.txt file. The first 8 sites in this list were test sites and can be ignored.</p>
Replication data for: Reconciliation k-median: Clustering with non-polarized representatives
<p># Description<br> These files contain the data employed in the experiments described in Bruno Ordozgoiti and Aristides Gionis. 2019. Reconciliation k-median: Clustering with Non-Polarized Representatives. In Proceedings of the 2019 World Wide Web Conference (WWW’19), May 13–17, 2019, San Francisco, CA, USA.</p> <p>Twitter ID's have been anonymized.</p> <p># Contents<br> domain_mentions.txt: Each line contains a domain name, a user ID and the number of times this user has mentioned this domain name in a tweet.<br> format: domain_name <TAB> user_id <TAB> mention_count</p> <p>domains_ideology_score.txt: Domain names and their ideology score, estimated as described in (Lahoti et al. WSDM 2018). Note: missing scores can be retrieved from supplementary data in https://doi.org/10.1093/poq/nfw006<br> format: domain_name <TAB> ideology_score</p> <p>follow_graph.txt: The Twitter follower graph. Each line contains a user id and the user id of one of its followers.<br> format: user_id <TAB> follower_user_id</p> <p>representatives.txt: US Congress representatives, each with Twitter handle and polarity score computed using Barbera's method (Barbera, 2015).<br> format: rep_name <TAB> website_url <TAB> district <TAB> twitter_handle <TAB> party <TAB> barbera_polarity_score</p> <p>user_polarity.txt: User ID's and polarity score computed using Barbera's method (Barbera, 2015).<br> format: user_id <TAB> barbera_polarity_score</p>
Polarized and nonpolarized Twitter networks from the 2019 Finnish Parliamentary Elections
<p><strong>Polarized and nonpolarized Twitter networks from the 2019 Finnish Parliamentary Elections</strong></p> <p>This dataset includes 183 Twitter retweet networks collected during the 2019 Finnish Parliamentary Elections.</p> <p>The first 150 networks are built around single hashtags, such as #police, #nature, and #immigration. The remaining 33 networks are constructed using a combination of hashtags focused on specific topics like climate change and economic policy.</p> <p>Each filename consists of two parts: the first part indicates whether the network is based on a single hashtag (in lowercase) or a set of hashtags (in uppercase). The second part represents the tweet period.</p> <ul> <li> <p>"p1" corresponds to the pre-election period (March 1 to April 14).</p> </li> <li> <p>"p2" corresponds to the inter-election period (April 15 to May 26).</p> </li> <li> <p>"p3" corresponds to the post-election period (May 27 to July 31).</p> </li> </ul> <p>The nodes in the networks represent anonymized Twitter accounts, and directed ties indicate retweet endorsements on specific topics. Each file contains three columns: retweeter, retweeted, and weight.</p> <p>Please see the references for more details.</p> <p>Network labels, whether they are labeled as controversial, and whether they are based on single or multiple hashtags, can be found in the "networks_info.csv" file.</p> <p>Importantly, the dataset does not contain any identifying information or original raw data from the Twitter platform. Anonymization was achieved by shuffling the order of unique nodes across all networks and assigning each node a new identifier (ID). These new IDs were then applied to the edgelists to obtain the anonymized version.</p> <p>Kindly ensure to reference the original article(s) when utilizing this dataset.</p> <p>Chen, T. H. Y., Salloum, A., Gronow, A., Ylä-Anttila, T., & Kivelä, M. (2021). Polarization of climate politics results from partisan sorting: Evidence from Finnish Twittersphere. <em>Global Environmental Change</em>, <em>71</em>, 102348. <a href="https://doi.org/10.1016/j.gloenvcha.2021.102348">https://doi.org/10.1016/j.gloenvcha.2021.102348</a></p> <p>Salloum, A., Chen, T. H. Y., & Kivelä, M. (2022). Separating polarization from noise: comparison and normalization of structural polarization measures. <em>Proceedings of the ACM on human-computer interaction</em>, <em>6</em>(CSCW1), 1-33. <a href="https://doi.org/10.1145/3512962">https://doi.org/10.1145/3512962</a></p>
Datasets for ``Hemispheric handedness in the Galactic synchrotron polarization foreground''
<pre>This directory contains an index.html file with links to E_lm and B_lm data from WMAP observations in the K and Q bands, denoted by superscripts K and Q, respectively. We also give E_lm and B_lm from numerical simulations of a simple dynamo at two different radii, 8kpc and 3kpc from the galactic center, denoted by superscripts 8kpc and 3kpc, respectively. The corresponding run directories and the idl plotting routines with secondary data for the other figures for the paper "Hemispheric handedness in the Galactic synchrotron polarization foreground" by Axel Brandenburg & Marcus Brueggen with the temporary URL http://norlx51.nordita.org/~brandenb/tmp/brueggen are also given.</pre>
Dynamics of macrophage polarization in Salmonella infection : Raw data
<p>Experimental raw data of the paper "Dynamics of macrophage polarization support <em>Salmonella</em> persistence in a whole living organism", Leiba et al.</p>
Thermally switchable, bifunctional, scalable, mid-infrared metasurfaces with VO2 grids capable of versatile polarization manipulation and asymmetric transmission
<p>The data generated by CST Studio Suite that are used to plot a part of the figures, and sample CST scripts. </p> <p>Research supported by Narodowe Centrum Nauki, project no UMO-2020/39/I/ST3/02413. </p>
Data for the article "Typhon: a polar stream from the outer halo raining through the Solar neighborhood"
<p>This data contains the stellar parameters of Typhon stream stars in the context of the "Typhon: a polar stream from the outer halo raining through the Solar neighborhood" (Tenachi et al. 2022) paper, in two formats:.csv and .fits (which also contains a short description of each column).</p> <p>This data includes:</p> <ul> <li>Stellar coordinates and parameters from Gaia DR3 (Gaia Collaboration 2022) with extinction-corrected magnitudes using the (Schlafly and Finkbeiner 2011) corrections to the (Schlegel et al. 1998) extinction maps, assuming the extinction ratios A<sub>G</sub>/A<sub>V</sub> = 0.86117, A<sub>GBP</sub>/A<sub>V</sub> = 1.06126 and A<sub>GRP</sub> /A<sub>V</sub> = 0.64753, as listed on the web interface to the PARSEC isochrones (Bressan et al. 2012) and assuming a solar position (x,y,z) = (−8.2240, 0, 0.0028) kpc (Bovy 2020, Widmark et al. 2021) and a solar velocity (vx,vy,vz) = (11.10, 7.20, 7.25) km/s with a circular velocity = 243 km/s (Schonrich et al. 2010, Bovy 2020).</li> <li>Added dynamical parameters (actions, energy, apocenters and pericenters values) derived in a (McMillan et al 2017) potential.</li> <li>Metallicity parameters from LAMOST DR8 PASTEL column (Wang et al 2022).</li> <li>Independent measurements from the "Chemical Abundances of the Typhon Stellar Stream" follow-up paper (Ji et al 2022).</li> </ul>
Bootstrapped Lexicon of German Verbal Polarity Shifters
<p>We provide a bootstrapped lexicon of German verbal polarity shifters. Our lexicon covers 2595 verbs of GermaNet. Polarity shifter labels are given for each word lemma. All labels were assigned by an expert annotator who is a native speaker of German.</p> <p><strong>Data</strong></p> <p>The data consists of two lists of GermaNet verbs annotated for whether they cause shifting:</p> <ol> <li><code>verbal_shifters.gold_standard.txt</code>: The initial gold standard (§3) of 2000 randomly sampled verbs.</li> <li><code>verbal_shifters.bootstrapping.txt</code>: The bootstrapped 595 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated.</li> </ol> <p><strong>Format</strong></p> <p>Each line contains a verb and its label, separate by a whitespace.</p> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Marc Schulder, Michael Wiegand, Josef Ruppenhofer (2018). <strong>"Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for German"</strong>. <em>Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018)</em>. Santa Fe, New Mexico, USA, August 20 - August 26, 2018. <a href="https://doi.org/10.5281/zenodo.3365694">DOI: 10.5281/zenodo.3365694</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p>
Lexicon of English Verbal Polarity Shifters
<p>We provide a complete lexicon of English verbal polarity shifters and their shifting scope. Our lexicon covers all verbs of WordNet v3.1 that are single word or particle verbs. Polarity shifter and scope labels are given for each lemma-synset pair (i.e. each word sense of a lemma).</p> <p><strong>Data</strong></p> <p>The data is presented in the following forms:</p> <ol> <li>A complete lexicon of all verbal shifters and their shifting scopes.</li> <li>Two auxiliary lists: <ol> <li>A list of all lemmas with shifter labels</li> <li>A list of all word senses with shifter labels</li> </ol> </li> </ol> <p>All files are in CSV (comma-separated value) format.</p> <p><strong>1. Main Lexicon</strong></p> <p>File name: <code>shifter_lexicon.csv</code></p> <p>The main lexicon lists all verbal shifters and their shifting scopes. Verbal shifters are modelled as lemma-sense pairs with one or more shifting scopes.</p> <p>Each line of the lexicon file contains a single lemma-sense-scope triple, using the format:</p> <pre><code>LEMMA,SYNSET,SCOPE </code></pre> <p>The elements are defined as follows:</p> <ul> <li><strong>LEMMA:</strong> The lemma form of the verb.</li> <li><strong>SYNSET:</strong> The numeric identifier of the synset, commonly referred to as <em>offset</em> or <em>database location</em>. It consists of 8 digits, including leading zeroes (e.g. 00334568).</li> <li><strong>SCOPE:</strong> The scope of the shifting: <ul> <li><code>subj</code>: The verbal shifter affects its subject.</li> <li><code>dobj</code>: The verbal shifter affects its direct object.</li> <li><code>pobj_*</code>: The verbal shifter affects objects within a prepositional phrase. The preposition in question is included in the annotation. For example a <em>from</em>-preposition scope receives the label <code>pobj_from</code> and a a <em>for</em>-preposition receives <code>pobj_for</code>.</li> <li><code>comp</code>: The verbal shifter affects a clausal complement, such as infinitive clauses or gerunds.</li> </ul> </li> </ul> <p>The lexicon lists all lemma-sense pairs that are verbal shifters. Any lemma-sense pair not listed is not a verbal shifter. When a lemma-sense pair has more than one possible scope, a separate entry is made for each scope.</p> <p><strong>2. Auxiliary Lists</strong></p> <p>The auxiliary files represent the same shifter information as the main lexicon, but for lemmas and synsets, respectively, instead of for lemma-sense pairs. Due to their nature, these lists are more coarse-grained than the main lexicon and contain no information on shifter scope. They are provided as a convenience for fast experimentation.</p> <p><strong>2.1. List of Lemmas</strong></p> <p>File name: <code>shifter_lemma_lexicon.csv</code></p> <p>List of all verb lemmas and whether they are shifters in at least one of their word senses.</p> <pre><code>LEMMA,LABEL </code></pre> <ul> <li><strong>LEMMA:</strong> The lemma form of the verb.</li> <li><strong>LABEL:</strong> <code>shifter</code> if the verb is a shifter in at least one of its word senses, otherwise <code>nonshifter</code>.</li> </ul> <p>Many verbal shifter lemmas only cause shifting in some of their word senses. This list is therefore considerably more coarse-grained than the main lexicon.</p> <p><strong>2.2. List of Synsets</strong></p> <p>File name: <code>shifter_synset_lexicon.csv</code></p> <p>List of all synsets and whether their lemmas are shifters in this specific word sense.</p> <pre><code>SYNSET,LABEL </code></pre> <ul> <li><strong>SYNSET:</strong> The numeric identifier of the synset, commonly referred to as <em>offset</em> or <em>database location</em>. It consists of 8 digits, including leading zeroes (e.g. 00334568).</li> <li><strong>LABEL:</strong> <code>shifter</code> if the word sense causes shifting, otherwise <code>nonshifter</code>.</li> </ul> <p>Shifting is shared among lemmas of the same word sense. This list, therefore, provides (almost) the same granularity for the shifter label as the main lexicon. However, in a few exceptions, synsets contained words with subtly different senses that did not all cause shifting. These senses are considered shifters in this list, analogous to the generalisation in the list of lemmas.</p> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Schulder, Marc and Wiegand, Michael and Ruppenhofer, Josef and Köser, Stephanie (2018). <strong>"Introducing a Lexicon of Verbal Polarity Shifters for English"</strong>. Proceedings of the 11th Conference on Language Resources and Evaluation (LREC). Miyazaki, Japan, May 7-12, 2018. <a href="https://doi.org/10.5281/zenodo.3365683">DOI: 10.5281/zenodo.3365683</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p>
Bootstrapped Lexicon of English Verbal Polarity Shifters
<blockquote> <p>An extended version of this dataset that also covers nominal and adjectival polarity shifters can be found at <a href="https://doi.org/10.5281/zenodo.3365601">doi:10.5281/zenodo.3365601</a>.</p> </blockquote> <p> </p> <p>We provide a bootstrapped lexicon of English verbal polarity shifters. Our lexicon covers 3043 verbs of WordNet v3.1 (Miller et al., 1990) that are single word or particle verbs. Polarity shifter labels are given for each word lemma.</p> <p><strong>Data</strong></p> <p>The data consists of:</p> <ol> <li>Two lists of WordNet verbs (Miller et al., 1990), annotated for whether they cause shifting. <ol> <li>The initial gold standard (§2) of 2000 randomly chosen verbs.</li> <li>The bootstrapped 1043 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated.</li> </ol> </li> <li>Data set of verb phrases from the Amazon Product Review Data corpus (Jindal & Liu, 2008), annotated for polarity of phrase and polar noun.</li> </ol> <p> </p> <p><strong>1. Verbal Shifters</strong></p> <p><strong>Files</strong></p> <ul> <li>The initial gold standard: <code>verbal_shifters.gold_standard.txt</code></li> <li>The bootstrapped verbs: <code>verbal_shifters.bootstrapping.txt</code></li> </ul> <p><strong>Format</strong></p> <ul> <li>Each line contains a verb and its label, separate by a whitespace.</li> <li>Multiword expressions are separated by an underscore (WORD_WORD).</li> <li>All labels were assigned by an expert annotator.</li> </ul> <p> </p> <p><strong>2. Sentiment Verb Phrases</strong></p> <p><strong>Files</strong></p> <ul> <li>All annotated verb phrases: <code>sentiment_phrases.txt</code></li> </ul> <p><strong>Content</strong></p> <p>The file starts with 400 phrases containing shifter verbs, followed by 2231 phrases containing non-shifter verbs.</p> <p><strong>Format</strong></p> <p>Every item consists of:</p> <ul> <li>The sentence from which the VP and the polar noun were extracted.</li> <li>The VP, polar noun and the verb heading the VP.</li> <li>Constituency parse for the VP.</li> <li>Gold labels for VP and polar noun by a human annotator.</li> <li>Predicted labels for VP and polar noun by RNTN tagger (Socher et al., 2013) and <code>LEX_gold</code> approach.</li> <li>Items are separated by a line of asterisks (*)</li> </ul> <p><strong>Related Resources</strong></p> <ul> <li><strong>Paper:</strong> <a href="https://aclweb.org/anthology/I17-1063">ACL Anthology</a> or <a href="https://doi.org/10.5281/zenodo.3365609">DOI: 10.5281/zenodo.3365609</a></li> <li><strong>Presentation:</strong> <a href="https://www.aclweb.org/anthology/attachments/I17-1063.Presentation.pdf">ACL Anthology</a></li> <li><strong>Word Embedding:</strong> <a href="https://doi.org/10.5281/zenodo.3370051">DOI: 10.5281/zenodo.3370051</a></li> </ul> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). <strong>"Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features"</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. <a href="https://doi.org/10.5281/zenodo.3365609">DOI: 10.5281/zenodo.3365609</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p> <p> </p>
Polarity Shifter Resources
<p>This repository was created as part of Marc Schulder's doctoral thesis <a href="https://dx.doi.org/10.22028/D291-28454"><em>Sentiment Polarity Shifters: Creating Lexical Resources through Manual Annotation and Bootstrapped Machine Learning</em></a></p> <p>The collection of polarity shifter resources presented herein is also connected to a number of publications:</p> <ul> <li><strong><a href="https://doi.org/10.5281/zenodo.3365609">Schulder et al. (IJCNLP 2017)</a>:</strong> Lexicon of English Verbal Shifters (bootstrapped, lemma-level) and sentiment verb phrase dataset. <a href="https://doi.org/10.5281/zenodo.3364812"><em>doi: 10.5281/zenodo.3364812</em></a></li> <li><strong><a href="https://doi.org/10.5281/zenodo.3365683">Schulder et al. (LREC 2018)</a>:</strong> Lexicon of English Verbal Shifters (manual, sense-level). <em><a href="https://doi.org/10.5281/zenodo.3365288">doi: 10.5281/zenodo.3365288</a></em></li> <li><strong><a href="https://doi.org/10.5281/zenodo.3365694">Schulder et al. (COLING 2018)</a>:</strong> Lexicon of German Verbal Shifters (bootstrapped, lemma-level). <em><a href="https://doi.org/10.5281/zenodo.3365370">doi: 10.5281/zenodo.3365370</a></em></li> <li><strong><a href="https://www.aclweb.org/anthology/2020.lrec-1.616/">Schulder et al. (LREC 2020)</a>:</strong> Lexicon of Polarity Shifting Directions (supervised classification, lemma-level). <em><a href="https://doi.org/10.5281/zenodo.3545947">doi: 10.5281/zenodo.3545947</a></em></li> <li><strong><a href="https://doi.org/10.1017/S135132492000039X">Schulder et al. (JNLE 2020)</a>:</strong> General Lexicon of English Shifters (bootstrapped, lemma-level). <em><a href="https://doi.org/10.5281/zenodo.3365601">doi: 10.5281/zenodo.3365601</a></em></li> </ul> <p><strong>Data</strong></p> <p>The repository contains the following resources:</p> <ol> <li>A general lexicon of English polarity shifters, covering verbs, adjectives and nouns. Provides lemma labels for shifters and for which polarities they can affect.</li> <li>A lexicon of English verbal shifters. Provides word sense labels for shifters and their shifting scopes.</li> <li>A lexicon of German verbal shifters. Provides lemma labels for shifters.</li> <li>A set of verb phrases annotated for shifting polarities.</li> </ol> <p><strong>1. English Shifter Lexicon (Lemma)</strong></p> <p>A lexicon of 9145 English words, annotated for whether they are polarity shifters and which polarities they affect. The lexicon is based on the vocabulary of WordNet v3.1 (Miller et al., 1990). It contains 2631 shifters and 6514 non-shifters.</p> <ul> <li>File: <code>shifters.english.all.lemma.txt</code></li> <li>The lexicon is a comma-separated value (CSV) table.</li> <li>Each line follows the format <code>POS,LEMMA,SHIFTER_LABEL,DIRECTION_LABEL,SOURCE</code>. <ul> <li><code>POS</code>: The part of speech of the word (<code>verb</code>, <code>noun</code>, <code>adj</code>)</li> <li><code>LEMMA</code>: The lemma representation of the word in question. Multiword expressions are separated by an underscore (<code>WORD_WORD</code>).</li> <li><code>SHIFTER_LABEL</code>: Whether the word is a polarity shifter (<code>SHIFTER</code>) or a non-shifter (<code>NONSHIFTER</code>).</li> <li><code>DIRECTION_LABEL</code>: Whether the shifter affects only positive polarities (<code>AFFECTS_POSITIVE</code>), only negative polarities. (<code>AFFECTS_NEGATIVE</code>) or can shift in both directions (<code>AFFECTS_BOTH</code>). Non-shifters are all labeled (<code>NONE</code>).</li> <li><code>SOURCE</code>: Whether the word was part of the gold standard. (<code>GOLD_STANDARD</code>) or was bootstrapped (<code>BOOTSTRAPPED</code>). Note that while bootstrapped shifter labels are verified by a human annotator, their direction label is automatically classified without verification.</li> </ul> </li> </ul> <p><strong>2. English Verbal Shifter Lexicon (Word Sense)</strong></p> <p>A lexicon of word senses of English verbs, annotated for whether they are polarity shifters and their shifting scope. The lexicon covers all verbs of WordNet v3.1 (Miller et al., 1990) that are single word or particle verbs. Polarity shifter and scope labels are given for each lemma-synset pair (i.e. each word sense of a lemma).</p> <p>The data is presented in the following forms:</p> <ol> <li>A complete lexicon of all verbal shifters and their shifting scopes.</li> <li>Two auxiliary lists containing simplified information: <ol> <li>A list of all lemmas with shifter labels</li> <li>A list of all word senses with shifter labels</li> </ol> </li> </ol> <p>All files are in CSV (comma-separated value) format.</p> <p><strong>2.1. Complete Lexicon</strong></p> <p>The main lexicon lists all verbal shifters and their shifting scopes. Verbal shifters are modeled as lemma-sense pairs with one or more shifting scopes.</p> <p>The lexicon lists all lemma-sense pairs that are verbal shifters. Any lemma-sense pair not listed is not a verbal shifter. When a lemma-sense pair has more than one possible scope, a separate entry is made for each scope.</p> <ul> <li>File name: <code>shifters.english.verb.sense.csv</code></li> <li>Each line contains a single lemma-sense-scope triple, using the format <code>LEMMA,SYNSET,SCOPE</code>. <ul> <li><code>LEMMA</code>: The lemma representation of the verb in question. Multiword expressions are separated by an underscore (<code>WORD_WORD</code>).</li> <li><code>SYNSET</code>: The numeric identifier of the synset, commonly referred to as <em>offset</em> or <em>database location</em>. It consists of 8 digits, including leading zeroes (e.g. <code>00334568</code>).</li> <li><code>SCOPE</code>: The scope of the shifting: <ul> <li><code>subj</code>: The verbal shifter affects its subject.</li> <li><code>dobj</code>: The verbal shifter affects its direct object.</li> <li><code>pobj_*</code>: The verbal shifter affects objects within a prepositional phrase. The preposition in question is included in the annotation. For example a <em>from</em>-preposition scope receives the label <code>pobj_from</code> and a a <em>for</em>-preposition receives <code>pobj_for</code>.</li> <li><code>comp</code>: The verbal shifter affects a clausal complement, such as infinitive clauses or gerunds.</li> </ul> </li> </ul> </li> </ul> <p><strong>2.2. List of Lemmas</strong></p> <p>List of all verb lemmas and whether they are shifters in at least one of their word senses. Does not provide shifter scope information.</p> <p>Many verbal shifter lemmas only cause shifting in some of their word senses. This list is therefore considerably more coarse-grained than the main lexicon. It is intended as a convenience measure for quick experimentation.</p> <ul> <li>File name: <code>shifters.english.verb.sense.lemmas_only.csv</code></li> <li>Each line follows the format <code>LEMMA,SHIFTER_LABEL</code>. <ul> <li><code>LEMMA</code>: The lemma representation of the verb in question. Multiword expressions are separated by an underscore (<code>WORD_WORD</code>).</li> <li><code>SHIFTER_LABEL</code>: Whether the verb is a polarity shifter (<code>SHIFTER</code>) or a non-shifter (<code>NONSHIFTER</code>).</li> </ul> </li> </ul> <p><strong>2.3. List of Synsets</strong></p> <p>List of all synsets and whether their lemmas are shifters in this specific word sense. Does not provide shifter scope information.</p> <p>Shifting is shared among lemmas of the same word sense. This list, therefore, provides (almost) the same granularity for the shifter label as the main lexicon. However, in a few exceptions, synsets contained words with subtly different senses that did not all cause shifting. These senses are considered shifters in this list, analogous to the generalization in the list of lemmas.</p> <ul> <li>File name: <code>shifters.english.verb.sense.synsets_only.csv</code></li> <li>Each line follows the format <code>SYNSET,SHIFTER_LABEL</code>. <ul> <li><code>SYNSET</code>: The numeric identifier of the synset, commonly referred to as <em>offset</em> or <em>database location</em>. It consists of 8 digits, including leading zeroes (e.g. <code>00334568</code>).</li> <li><code>SHIFTER_LABEL</code>: Whether the verb is a polarity shifter (<code>SHIFTER</code>) or a non-shifter (<code>NONSHIFTER</code>).</li> </ul> </li> </ul> <p><strong>3. German Verbal Shifter Lexicon (Lemma)</strong></p> <p>A lexicon of 2595 German verbs, annotated for whether they are polarity shifters and which polarities they affect. The lexicon is based on the vocabulary of GermaNet (Hamp and Feldweg, 1997). It contains 677 shifters and 1918 non-shifters.</p> <ul> <li>File: <code>shifters.german.verb.lemma.txt</code></li> <li>The lexicon is a comma-separated value (CSV) table.</li> <li>Each line follows the format <code>LEMMA,SHIFTER_LABEL,SOURCE</code>. <ul> <li><code>LEMMA</code>: The lemma representation of the verb in question. Multiword expressions are separated by an underscore (<code>WORD_WORD</code>).</li> <li><code>SHIFTER_LABEL</code>: Whether the verb is a polarity shifter (<code>SHIFTER</code>) or a non-shifter (<code>NONSHIFTER</code>).</li> <li><code>SOURCE</code>: Whether the word was part of the gold standard. (<code>GOLD_STANDARD</code>) or was bootstrapped (<code>BOOTSTRAPPED</code>). In either case the verbs were verified by a human annotator.</li> </ul> </li> </ul> <p><strong>4. Sentiment Verb Phrases</strong></p> <p>A set of verb phrases, annotated for the polarity of the verb phrase and the polarity of a polar noun that it contains. Can be used to evaluate whether a polarity classifier correctly recognizes polarity shifting. The file starts with 400 phrases containing shifter verbs, followed by 2231 phrases containing non-shifter verbs.</p> <ul> <li>File: <code>sentiment_phrases.txt</code></li> <li>Every item consists of: <ul> <li>The sentence from which the VP and the polar noun were extracted.</li> <li>The VP, polar noun and the verb heading the VP.</li> <li>Constituency parse for the VP.</li> <li>Gold labels for VP and polar noun by a human annotator.</li> <li>Predicted labels for VP and polar noun by RNTN tagger (Socher et al., 2013) and <code>LEX_gold</code> approach.</li> <li>Items are separated by a line of asterisks (*)</li> </ul> </li> </ul>
Dataset for the paper "Designs in finite classical polar spaces"
<div> <div><span>This repository contains the designs from the paper </span><span>"Designs in finite classical polar spaces" by Michael Kiermaier, Kai-Uwe Schmidt, and Alfred Wassermann, </span><span>in Designs, Codes, and Cryptography. </span></div> <div> </div> <div> <div> <div><span>All designs in this repository are simple designs.</span></div> <br> <div><span>The file format is JSON. Each file contains the designs in a fixed finite polar space </span><span>for a pair of parameters t and k. </span></div> <div> </div> <div><span>The file README.md contains more detailed information about the file format.</span></div> </div> </div> </div>
Indicative distribution map for Ecosystem Functional Group T6.3 Polar tundra and deserts
<p>This archive contains indicative distribution maps and profiles for <strong>T6.3 Polar tundra and deserts</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Sentiment polarity lexicon of Bosnian language
<p>First sentiment annotated lexicon of the Bosnian language.</p> <p>The lexicon is divided into two files: positive and negative polarity.</p> <p>The lists are prepared in separate files, each file populated by words of the aforementioned polarity listed each word in a separate row. </p> <p>The positive polarity list BOSNIAN_POSITIVE.txt holds 1219 words.</p> <p>The negative polarity list BOSNIAN_NEGATIVE.txt holds 3935 words.</p>
Contamination pattern and risk assessment of polar compounds in snow melt: an integrative proxy of road runoffs
<p><strong>Abstract</strong></p> <p>To assess the contamination and potential risk of snow melt with polar compounds, road and background snow was sampled during a melting event at 23 sites at the city of Leipzig and screened for more than 500 chemicals using LC-HRMS. Additionally, six 24 h composite samples were taken from the influent and effluent of the Leipzig WWTP during the snow melt event. 207 compounds were at least detected once (concentrations between 0.80 ng/L and 75 µg/L). A toxic unit-based assessment was performed to investigate the risk of adverse environmental effects in the receiving water.</p> <p><strong>Description of the dataset</strong></p> <p>The dataset contains the list of sampling points, the target compounds, the chemical findings, the results of the toxic unit assessment, the underlying ecotoxicity data, and the estimated compound removal rates in WWTP. The data is provided in xlsx and ods formats.</p>
Polarity Dataset v2.0
<p>Preliminary steps were taken to remove rating information from the text files, but only the rating information upon which the rating decision was based is guaranteed to have been removed. Thus, if the original review contains several instances of rating information, potentially given in different forms, those not recognized as valid ratings remain part of the review text. The reviews are split into sentences in the .csv file, which are labeled with the review they come from, as well as the sentiment of the overall review.</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)
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.