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355 results for “data extraction”
MySQL dump for finding optimal parameters for data augmentation techniques in publication "Leveraging Data Augmentation for Process Information Extraction"
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Relationship between mineral extraction, oil extraction, and agribusiness with employability, municipal gross domestic product, and voting data in Brazil
<p>This dataset looks at the number of Brazilian municipalities where mining is a key economic activity and those where mining is a key job provider. We also listed municipalities that have mining as both a main economic activity and the main employer in a given town. We have also generated maps to visualize the impact of mining in Brazil as a key economic activity and/or job provider. Similarly, we have listed the same information for all the municipalities that received oil royalties in 2019, and the top 100 municipalities whose wealth was mainly generated by agribusiness in 2022. By detailing the economic and employment situation in Brazilian extractive municipalities (mining, oil, and crops), we demonstrate that company towns in Brazil (locations that are highly dependent on one key economic activity for employment generation) are few. Extractive industries may no longer be labour intensive, although economic dependency may follow indirectly, such as because of tax generation. We also offer data on national elections to demonstrate that there is not a clear correlation between economic activity and voting patterns, which may be explained by low employability. The main objective of this dataset is to generate a discussion on the need to redefine company towns in Brazil.</p>
Data Extraction and Quality Assessment about Cybersecurity in the Context of Agile Software Development
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Raw mass spectrometry data for "Quinone extraction drives atmospheric carbon monoxide oxidation in bacteria"
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Assessment of animal diseases caused by bacteria resistant to antimicrobials: Sheep and goats- Appendix B: Excel file with all data extracted
<p>Information on all the full-text studies that were assessed, including the reason for exclusion for those that were excluded at the full-text screening and the data extracted from the included studies, can be consulted here. </p> <p>The extensive literature review was carried out by the University of Copenhagen under the contract OC/EFSA/ALPHA/2020/02 – LOT 1 (https://ted.europa.eu/udl?uri=TED:NOTICE:457654-2020:TEXT:EN:HTML)</p>
Data from: Chemical extraction of phosphorus from dairy manure and utilization of recovered manure solids
<p>This is digital research data corresponding to a published manuscript, <em>Chemical extraction of phosphorus from dairy manure and utilization of recovered manure solids. </em>Agronomy 2020, 10, 1725; doi:10.3390/agronomy10111725</p> <p>Repeated land application of dairy manure can increase soil phosphorus above crop requirements because of manure's low nitrogen (N) to phosphorus (P) ratio (N:P < 4:1). This soil P build-up can lead to off-site P transport and impairment of surface water quality. We evaluated a treatment process to extract P from manures, called Quick Wash, integrated with a double-stage solids separation system to recover coarse and fine manure solids. The Quick Wash process uses a combination of acid, base, and organic polymers to extract and recover P from manures, improving the N:P ratio of recovered manure solids (RMS).</p>
The EMG source data, data processing code and feature extraction source code
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TTV Data Extraction
<p>This data set contains TTV (threats to validity) analysis extracted from 91 studies.</p>
Raw data for extract yields and trigonelline amounts in fenugreek
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Data from: Immunotherapy-related adverse events (irAEs): extraction from FDA drug labels and comparative analysis
Objectives: Immune checkpoint inhibitors (ICIs) have dramatically improved outcomes in cancer patients. However, ICIs are associated with significant immune-related adverse events (irAEs) and the underlying biological mechanisms are not well-understood. To ensure safe cancer treatment, research efforts are needed to comprehensively detect and understand irAEs. Materials and Methods: We manually extracted and standardized irAEs from FDA drug labels for six FDA-approved ICIs. We compared irAE profile similarities among ICIs and 1,507 FDA-approved non-ICI drugs. We investigated how irAEs have differential effects on human organs by classifying irAEs based on their targeted organ systems. Finally, we identified broad-spectrum (non-target specific) and narrow-spectrum (target-specific) irAEs. Results: A total of 893 irAEs were extracted. 31.4% irAEs were shared among ICIs as compared to the 8.0% between ICIs and non-ICI drugs. irAEs were resulted from both on- and off-target effects: irAE profiles were more similar for ICIs with same target than different targets, demonstrating the on-target effects; irAE profile similarity for ICIs with the same target is less than 50%, demonstrating unknown off-target effects. ICIs significantly target many organ systems, including endocrine system (3.4-fold enrichment), metabolism (3.7-fold enrichment), immune system (3.6-fold enrichment) and autoimmune system (4.8-fold enrichment). We identified 21 broad-spectrum irAEs shared among all ICIs, 20 irAEs specific for PD-L1/PD-1 inhibition, and 28 irAEs specific for CTLA-4 inhibition. Discussion and Conclusion: Our study presents the first effort toward building a standardized database of irAEs. The extracted irAEs can serve as a goldstandard for automatic irAE extractions from other data resources and set a foundation to understand biological mechanisms of irAEs.
Data from: New sporopollenin-based β-cyclodextrin functionalized magnetic hybrid adsorbent for magnetic solid-phase extraction of nonsteroidal anti-inflammatory drugs from water samples.
A magnetic solid-phase extraction (MSPE) procedure on the newly synthesized magnetic β-cyclodextrin functionalized with toluene diisocyanate (TDI) as a linker and was further modified with bio-polymeric spores of sporopollenin (MSp-TDI-βCD) was developed for the extraction of nonsteroidal anti-inflammatory drugs (NSAIDs) namely indoprofen (INP), ketoprofen (KTP), ibuprofen (IBP) and fenoprofen (FNP) from water samples prior to their HPLC-DAD determination. The newly synthesised MSp-TDI-βCD was comprehensibly characterized using FT-IR, XRD, SEM-EDX, BET and VSM analyses. The separation of selected NSAIDs on MSp-TDI-βCD from aqueous solution was simply achieved by applying an external magnetic field via a permanent magnet. The MSPE parameters affecting extraction performance i.e., sorbent dosage, sample volume, extraction and desorption time, type of organic eluent and volume and solution pH were investigated and optimized. The proposed method showed linear range between 0.5 - 500 ng/mL, low limit of detection at S/N = 3 (0.16 - 0.37 ng/mL) and limit of quantification at S/N = 10 (0.53 - 1.22 ng/mL). The interday (n = 15) and intraday (n = 5) precision for the proposed methods given by relative standard deviation (RSD%) in the range of 2.5 - 4.0 and 2.1 - 5.5 respectively. The extraction recoveries of NSAIDs from environmental samples (tap, drinking and river water) ranged from 92.5 - 123.6%, with satisfactory precision (RSD% less than 12.4%).
Data-Driven Extract Method Recommendations: A Study at ING: Appendix
<p>The appendix of our FSE 2021 industry track paper.</p>
Data extracted from Scopus database in BibTex format.
<p>Data extracted from Scopus database in BibTex format for publication in Healthcare.</p>
Data extraction and synthesis table
<p>Table showing the data extraction and synthesis for a recent paper submission. </p>
Assessment of animal diseases caused by bacteria resistant to antimicrobials: Swine - Appendix B: Excel file with all data extracted
<p>Information on all the full-text studies that were assessed, including the reason for exclusion for those that were excluded at the full-text screening and the data extracted from the included studies, can be consulted here. </p> <p>The extensive literature review was carried out by the University of Copenhagen under the contract OC/EFSA/ALPHA/2020/02 – LOT 1 (https://ted.europa.eu/udl?uri=TED:NOTICE:457654-2020:TEXT:EN:HTML)</p>
Assessment of animal diseases caused by bacteria resistant to antimicrobials: Poultry- Appendix B: Excel file with all data extracted
<p>Information on all the full-text studies that were assessed, including the reason for exclusion for those that were excluded at the full-text screening and the data extracted from the included studies, can be consulted here. </p> <p>The extensive literature review was carried out by the University of Copenhagen under the contract OC/EFSA/ALPHA/2020/02 – LOT 1 (https://ted.europa.eu/udl?uri=TED:NOTICE:457654-2020:TEXT:EN:HTML)</p>
Procyanidins from cranberry press residues - extraction opti-mization, purification and characterization HRMS data
<p>Data of HRMS</p>
"What do We Know about Requirements Management in Software Ecosystems?" - Data extraction form
<p>Data extraction form. </p>
Satellite precipitation data (extracted)
<p>Daily satellite precipitation datasets extracted for hydrological modeling</p>
Supplementary data to the paper: Automatic Extraction of Anthropometric Features for the Individualization of the Pinna-Related Transfer Function in the Median Plane
<p>Supplementary research data to the paper (rejected):</p> <blockquote> <p>Davide Fantini, Federico Avanzini, Stavros Ntalampiras and Giorgio Presti (2023) "Automatic Extraction of Anthropometric Features for the Individualization of the Pinna-Related Transfer Function in the Median Plane"</p> </blockquote> <p>The repository includes the research data generated and analyzed in the abovementioned paper describing a method for PRTF individualization. In particular, the following data are included:</p> <ul> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/README.md">README.md</a>: instructions for the data</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/pinna_range_img.mat">pinna_range_img.mat</a>: pinna range images extracted from the 3D head meshes of the <a href="https://depositonce.tu-berlin.de/items/dc2a3076-a291-417e-97f0-7697e332c960">HUTUBS dataset</a></li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/landmarks.mat">landmarks.mat</a>: landmarks coordinates both manually annotated and automatically placed with ASM</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/anthropometry.mat">anthropometry.mat</a>: anthropometric parameters automatically extracted from both manually annotated and ASM-fitted landmarks</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/img_features.mat">img_features.mat</a>: image features pinna cavities extracted from both manually annotated and ASM-fitted landmarks</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/grnn_models.mat">grnn_models.mat</a>: Generalized Regression Neural Network (GRNN) models trained from both HUTUBS anthropometry and the proposed pinna features</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/predicted_dtf.mat">predicted_dtf.mat</a>: Directional Transfer Function (DTF) sets predicted from both HUTUBS anthropometry and the proposed pinna features</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/anthropometry_documentation.pdf">anthropometry_documentation.pdf</a>: documentation of the pinna anthropometric parameters</li> <li><a href="../api/files/bf20ab4d-c913-4cd0-9357-3b4039f1affb/auditory_model_complete_elevation_range.pdf">auditory_model_complete_elevation_range.pdf</a>: auditory model evaluation in the complete elevation range</li> </ul> <p>The data are provided in the Matlab file format MAT. Nevertheless, the MAT files can be read with other programming languages, such as Python (<a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html">scipy.io.loadmat</a>).</p> <p>A GitHub repository to automatically extract the pinna landmarks and features as described in the paper is available <a href="https://github.com/DavideFantini/pinna-landmarks-fitting-and-anthropometry-extraction" target="_blank" rel="noopener">here</a>.</p>
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.