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3,684 results for “extract”
Dataset for "Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis"
<p>JCIM paper link: <a href="https://pubs.acs.org/doi/10.1021/acs.jcim.2c00359">https://pubs.acs.org/doi/10.1021/acs.jcim.2c00359</a><br><br>Github repo: <a href="https://github.com/nsndimt/CatalysisIE">https://github.com/nsndimt/CatalysisIE</a><br><br><br>Dataset Content:</p> <ul> <li>Pretrained BERT: <code>scibert_domain_adaption.tar.gz</code> extract it to <em>pretrained</em> directory</li> <li>Cross-Validation Checkpoint: <code>cross_validation_checkpoint.tar.gz</code> extract it to <em>checkpoint</em> directory</li> <li>Annotated Data: <code>data.jsonl</code> and <code>split.jsonl</code> put it under <em>data</em> directory</li> </ul>
Conserved structural elements specialize ATAD1 as a membrane protein extraction machine
<p>The mitochondrial AAA protein ATAD1 (in humans; Msp1 in yeast) removes mislocalized membrane proteins, as well as stuck import substrates from the mitochondrial outer membrane, facilitating their re-insertion into their cognate organelles and maintaining mitochondria's protein import capacity. In doing so, it helps to maintain proteostasis in mitochondria. How ATAD1 tackles the energetic challenge to extract hydrophobic membrane proteins from the lipid bilayer and what structural features adapt ATAD1 for its particular function has remained a mystery. Previously, we determined the structure of Msp1 in complex with a peptide substrate (Wang et al., 2020). The structure showed that Msp1's mechanism follows the general principle established for AAA proteins while adopting several structural features that specialize it for its function. Among these features in Msp1 was the utilization of multiple aromatic amino acids to firmly grip the substrate in the central pore. However, it was not clear whether the aromatic nature of these amino acids were required, or if they could be functionally replaced by aliphatic amino acids. In this work, we determined the cryo-EM structures of the human ATAD1 in complex with a peptide substrate at near atomic resolution. The structures show that phylogenetically conserved structural elements adapt ATAD1 for its function while generally adopting a conserved mechanism shared by many AAA proteins. We developed a microscopy-based assay reporting on protein mislocalization, with which we directly assessed ATAD1's activity in live cells and showed that both aromatic amino acids in pore-loop 1 are required for ATAD1's function and cannot be substituted by aliphatic amino acids. A short α-helix at the C-terminus strongly facilitates ATAD1's oligomerization, a structural feature that distinguishes ATAD1 from its closely related proteins.</p>
Data Set used in "Full backward and forward dependencies through regional hypothetical extraction method"
<p>This set of data was obtained from EUREGIO database, developed by the Tinbergen Institute, which is a set of global IO tables with regional and sectoral disaggregation. The EUREGIO database collects the productive structure and commercial relations of the WIOD in the period 2000-2010. The table is broken down into 249 administrative regions at the NUTS2 level, from 24 EU countries, 16 non-EU countries, and a block that brings together countries from the rest of the world, making a total of 266 regions. The statistical information is organised in 11 IO tables, one for each year.</p> <p>The data base that we provid in this repository is used in our study with the aim to determine the key regions of the Spanish economy. In order to address this objective, IO tables of smaller dimensions are built, through an aggregation and disaggregation procedure. First, the 14 industries are grouped, then the 4 sectors of final demand and, lastly, the 4 components of value added. Below, the 266 EUREGIO regions are grouped into 21 regions. Of these, 19 regions correspond to Spain <a href="#_ftn1">[1]</a>, one region includes the rest of the NUTS2 in the EU and another region covers the rest of the world.</p> <p><a href="#_ftnref1">[1]</a> The 17 Spanish regions and the two autonomous cities of Ceuta and Melilla.</p>
BiodivNERE: Gold Standard Corpora for Named Entity Recognition and Relation Extraction in Biodiversity Domain
<p>BiodivNER+RE are two gold-standard manually annotated corpora that are meant to be for Named Entity Recognition (NER) and Relation Extraction (RE) tasks based on abstracts and metadata files from the biodiversity domain</p> <p>Such corpora are designed for machine learning techniques, for example, NER as TokenClassification technique, and RE as SequenceClassification technique.</p>
Highly time-resolved chemical speciation and source apportionment of organic aerosol components in Delhi, India, using extractive electrospray ionization mass spectrometry
<p>In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution,<br> especially during winters. Comprehensive knowledge of the composition and sources of the organic aerosol<br> (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating<br> effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary<br> OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA<br> sources. We address the latter through the first field deployment of an extractive electrospray ionization timeof-<br> flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer<br> (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF)<br> was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded<br> three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning<br> OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LOOOA).<br> On average, 40%of the total OA mass was apportioned to the secondary factors. The SOA contribution to<br> total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %,<br> 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA<br> sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary<br> biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin:<br> aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in<br> the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the<br> total AMS SOA (i.e. MO-OOA C LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major<br> SOA component during the daytime, with a 55.2% contribution to total SOA mass (42.4% contribution to total<br> OA). Its contribution to total SOA, however, decreased to 25.4% (7.9% of total OA) during the nighttime. This<br> factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA<br> accounted for 18.4% of total SOA mass (14.2% of total OA) during the daytime and 36.1% of total SOA mass<br> (11.2% of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2%<br> and 11.0% of total SOA mass (11.7% and 8.5% of total OA mass), respectively, during the daytime and 15.4%<br> and 22.9% of total SOA mass (4.8% and 7.1% of total OA mass), respectively, during the nighttime. A simple<br> dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime<br> concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged<br> biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production,<br> likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was<br> related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study<br> show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass<br> burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction.<br> Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the<br> daytime suggests an increased OA toxicity and health-related consequences for the general public.</p> <p>This repository has excel file corresponding to each figures presented in main text published version.</p>
Reference Datasets for: SHAFTS (v2022.3): a deep-learning-based Python package for Simultaneous extraction of building Height And FootprinT from Sentinel Imagery
<p>These are reference building height and footprint datasets which consist of 46 cities worldwide and support the development of SHAFTS (https://github.com/LllC-mmd/3DBuildingInfoMap).</p> <p>The snapshot of original reference datasets from 46 cities and related GitHub repository has been created as a zipped file named <strong><em>SHAFTS_220527_snapshot.zip</em></strong>.</p> <p>On 2022.5.27, we added 8 additional cities from ArcGIS Hub when compared with the previous version (https://doi.org/10.5281/zenodo.6370003).</p>
Annotated compounds in extracts from alpine aromatic and medicinal plants grown in an aeroponics system
<p>The compounds were annotated by comparing the experimental HRMS/MS spectra of the samples with an <em>in silico</em> MS/MS spectral database of natural products.</p>
Event Registry titles only dataset with multiple extracted features (both sparse and dense)
<p>This is the same content as:</p> <p>Guillaume Bernard. (2022). Event Registry dataset with multiple extracted features (both sparse and dense) (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6630367</p> <p>But with titles of articles only.</p>
CoAID dataset with multiple extracted features (both sparse and dense)
<p>This is a publication of the CoAID dataset originaly dedicated to fake news detection. We changed here the purpose of this dataset in order to use it in the context of event tracking in press documents.</p> <p>Cui, Limeng, et Dongwon Lee. 2020. « CoAID: COVID-19 Healthcare Misinformation Dataset ». <em>ArXiv:2006.00885 [Cs]</em>, novembre. <a href="http://arxiv.org/abs/2006.00885">http://arxiv.org/abs/2006.00885</a>.</p> <p>In this dataset, we provide multiple features extracted from the text itself. <strong>Please note the text is missing from the dataset published in the CSV format for copyright reasons. You can download the original datasets and manually add the missing texts from the original publications.</strong></p> <p>Features are extracted using:</p> <p>- A corpus of reference articles in multiple languages languages for TF-IDF weighting. (<em>features_news</em>) [1]</p> <p>- A corpus of tweets reporting news for TF-IDF weighting. (<em>features_tweets)</em> [1]</p> <p>- A S-BERT model [2] that uses <em>distiluse-base-multilingual-cased-v1 </em>(called <em>features_use</em>) [3]</p> <p>- A S-BERT model [2] that uses <em>paraphrase-multilingual-mpnet-base-v2 </em>(called <em>features_mpnet</em>) [4]</p> <p><strong>References:</strong></p> <p>[1]: Guillaume Bernard. (2022). Resources to compute TF-IDF weightings on press articles and tweets (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6610406</p> <p>[2]: Reimers, Nils, et Iryna Gurevych. 2019. « Sentence-BERT: Sentence Embeddings Using Siamese BERT-Networks ». In <em>Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)</em>, 3982‑92. Hong Kong, China: Association for Computational Linguistics. <a href="https://doi.org/10.18653/v1/D19-1410">https://doi.org/10.18653/v1/D19-1410</a>.</p> <p>[3]: https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v1</p> <p>[4]: https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2</p>
AD ASTRA project - WP4 Characterization of Interconnects extracted from operated SUN stacks
<p>Report on the complete investigation performed on interconnects extracted from SOFC stacks operated from 5'000 to 20'000 hours</p>
Formal Methods for NFA Equivalence: QBFs, Witness Extraction, and Encoding Verification
<p>Supplemental material to the paper.</p>
LC-MS raw dataset of Dendrobium extracts
<p class="MsoNormal"><span>Orbitrap mass spectrometry is one kind of high-</span><span>resolution mass analyzer containing </span><span>multistage </span><span>fragment monitoring, a selective fragmentation mode, and a personalized data acquisition method</span><span><span>, </span></span><span><span>which </span></span><span><span>i</span></span><span><span>s </span></span><span>widely applied in </span><span>p</span><span>harmacokinetic analysis, </span><span><span>t</span></span><span><span>he </span></span><span>food </span><span>industry</span><span>, environmental monitoring</span><span><span>,</span></span><span> and proteomi</span><span>cs. </span><span><span>Alkaloids are an important active ingredient in Dendrobium officinale, but there are few studies on their isolation and identification. Here, </span></span><span>a </span><span><span>c</span></span><span><span>om</span></span><span><span>bin</span></span><span><span>atio</span></span><span><span>n </span></span><span><span>meth</span></span><span><span>od </span></span><span>for </span><span><span>s</span></span><span><span>ep</span></span><span><span>a</span></span><span><span>ra</span></span><span><span>tin</span></span><span><span>g</span></span><span> and </span><span><span>de</span></span><span><span>tect</span></span><span><span>ing </span></span><span>alkaloids and </span><span><span>the</span></span><span><span>ir </span></span><span>precursors</span><span> </span><span>was </span><span>established. </span><span>T</span><span>he accurate mass </span><span>of the </span><span>components</span><span> separated by HPLC were determined using an </span><span>high resolution</span><span><span> </span></span><span>mass analyzer. </span><span>T</span><span>he multistage fragmentation </span><span><span>p</span></span><span><span>at</span></span><span><span>hway</span></span><span> of </span><span>alkaloids</span><span> w</span><span><span>as</span></span><span> </span><span>speculated</span><span><span> </span></span><span>based on a database-dependent retrieval method.</span></p> <p class="MsoNormal"><span><span>By using a SPE-HP</span></span><span><span>LC</span></span><span><span>-</span></span><span><span>M</span></span><span><span>S</span></span><span><span>/MS </span></span><span><span>method, the potential compounds were tentatively identified by aligning the accurate molecular weight with the METLIN and Dictionary of Natural Products databases. The chemical structures and main characteristic fragments of the potential compounds were further confirmed by retrieving the multistage mass spectra from the MassBank and METLIN databases.The Mass Frontier software was used to speculate the fragmentation pathway of the identified compounds. Seven alkaloids were separated and identified from </span></span><em><span><span>D. officinale</span></span></em><span><span>, which were mainly classified into five types (tropane alkaloids, tetrahydroisoquinoline alkaloids, quinolizidine alkaloids, piperidine alkaloids and spermidine alkaloids). Besides the alkaloids, forty-nine chemical substances, including guanidines, nucleotides, dipeptides, sphingolipids and nitrogen-containing glucosides, were concurrently identified. </span></span></p>
Information Extraction in Handwritten Historical Logbooks
<p>Contains the datasets with tables used in the following paper: Information Extraction in Handwritten Historical Logbooks.</p> <p>The pages starting with "vol003" correspond to the Jeannette corpus, while the ones starting with "Albatross" correspond to the Albatross corpus.</p>
Some original, intermediate, and result data in the papar entited "Highway marking extraction and degradation analysis by using MLS point clouds"
<p>Some original, intermediate, and result data in the papar entited "Highway marking extraction and degradation analysis by using MLS point clouds"</p>
Lakkasuo carbon isotope and AWEN extraction data for Yasso-C13 model development
<p>This package contains carbon isotope and AWEN extraction data from litterbag experiments (5 year) at Lakkasuo, a raised bog complex near Hyytiälä weather station in Finland. Additionally present are driving data and parameter values needed to run soil carbon model Yasso. The given data is used to implement and calibrate carbon-13 related soil organic matter decomposition in the Yasso model. The dataset also contains calibration results, scripts to run the results anew and to produce plots and images. The updated dataset uses new Yasso20 parameter values.</p>
Regeneration data of bryophyte fragments extracted from feces of Chloephaga picta and Attagis malouinus in Navarino Island, sub-Antarctic Chile
<p class="Normal1"><span><span><span><span><span><span><span><span><span><span><span>Birds are known to act as potential vectors for the exogenous dispersal of bryophyte diaspores. Given the totipotency of vegetative tissue of many bryophytes, birds could also contribute to endozoochorous bryophyte dispersal. Research has shown that fecal samples of the upland goose (<i>Chloephaga picta</i>) and white-bellied seedsnipe (<i>Attagis malouinus</i>) contain bryophyte fragments. Although few fragments from bird feces have been known to regenerate, the evidence for the viability of diaspores following passage through the bird intestinal tract remains ambiguous. We evaluated the role of endozoochory in these same herbivorous and sympatric bird species in sub-Antarctic Chile. We hypothesized that fragments of bryophyte gametophytes retrieved from their feces are viable and capable of regenerating new plant tissue. Eleven feces samples containing undetermined moss fragments from <i>C. picta</i> and <i>A. malouinus</i>, six moss fragment samples from wild collected mosses (<i>Conostomum </i><i>tetragonum</i>,<i> Syntrichia </i><i>robusta</i>,<i> </i>and <i>Polytrichum </i><i>strictum</i>), and one spore sample from <i>C. tetragonum </i>were grown ex situ in peat soil and in vitro<i> </i>using a Gamborg (agar) medium. After 91 days, 20% of fragments from <i>A. malouinus </i>feces, 50% of fragments from <i>C. picta </i>feces, and 57% of propagules from wild mosses produced new growth. The fact that moss diaspores remained viable and can regenerate under experimental conditions following the passage through the intestinal tracts of these robust fliers and altitudinal and latitudinal migrants, suggests that sub-Antarctic birds may play a </span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span>critical, role in bryophyte dispersal. This relationship may have important implications in the way bryophytes disperse and colonize facing climate change.</span></span></span></span></span></span></span></span></span></span></span></p>
Experimental meterials for "How Developers Extract Functions: An Experiment"
<p>Experimental materials for the manuscript "How Developers Extract Functions: An Experiment", published in the 34th Workshop of the Psychology of Programming Interest Group, pp. 142-156, Aug 2023.</p><p>Includes the original code given to experimental subjects, the results of refactoring this code by the subjects, and scripts for analyzing these results.</p>
Transient Absorption Spectroscopy for "The Other Dimension - Tuning Hole Extraction via Nanorod Width"
<p>This is the transient absorption spectroscopy dataset for the publication "The Other Dimension - Tuning Hole Extraction via Nanorod Width". It contains the originally obtained data, chirp corrected 2D datasets, and the Gauss fittings of spectra obtained at delay times of 20 ps.</p>
Collection of Extracted Data as part of the Publication "(Why) Do Taint Analyzers Fail in Practice? A Critical Literature Review"
<p>This document provides an extensive list of the data extraction process for the systematic literature review. This anonymous version is review-friendly for double-blinded peer reviews.</p>
Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation
<p>This repository contains the following 3 datasets for legal document summarization :</p> <p>- IN-Abs : Indian Supreme Court case documents & their `abstractive' summaries, obtained from http://www.liiofindia.org/in/cases/cen/INSC/<br> - IN-Ext : Indian Supreme Court case documents & their `extractive' summaries, written by two law experts (A1, A2).<br> - UK-Abs : United Kingdom (U.K.) Supreme Court case documents & their `abstractive' summaries, obtained from https://www.supremecourt.uk/decided-cases/</p> <p>Please refer to the paper and the README file for more details.</p>
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.