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5,738 results for “Standards”
Text-fig. 2. CT slices on Block 2. Details of other skeletal parts (a). The familiar shape of an ammonite (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b, c). Heterogeneity of the 'tuffeau' limestone, the more porous areas of the matrix clearly distinguishable from the more compact ones (c). Ferric nodules (c). in Hidden Treasures Uncovered: Successful Detection Of Fossils Below The Surface In Large Limestone Blocks Using A Standard Medical X-Ray Ct Scanner
Text-fig. 2. CT slices on Block 2. Details of other skeletal parts (a). The familiar shape of an ammonite (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b, c). Heterogeneity of the 'tuffeau' limestone, the more porous areas of the matrix clearly distinguishable from the more compact ones (c). Ferric nodules (c).
Text-fig. 1. CT slices on Block 1. Details of the internal bone structure (a, b), teeth (b, c). Invertebrate imprints (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b). in Hidden Treasures Uncovered: Successful Detection Of Fossils Below The Surface In Large Limestone Blocks Using A Standard Medical X-Ray Ct Scanner
Text-fig. 1. CT slices on Block 1. Details of the internal bone structure (a, b), teeth (b, c). Invertebrate imprints (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b).
Text-fig. 3. CT slices on Block 3. Invertebrate moulds (a, c) and remains of their hard skeletons (a, b). Large areas of limestone matrix hold either only a few scattered invertebrates or no fossil at all (b, c). Ring artefacts seen close to the isocentre of the scan (b, c) are a well-known phenomenon caused by the X-ray beams traversing the block at an insufficient radiation dose (as expected in such a large block of dense material), and are not part of any physical structure present therein (Triche et al. 2019). in Hidden Treasures Uncovered: Successful Detection Of Fossils Below The Surface In Large Limestone Blocks Using A Standard Medical X-Ray Ct Scanner
Text-fig. 3. CT slices on Block 3. Invertebrate moulds (a, c) and remains of their hard skeletons (a, b). Large areas of limestone matrix hold either only a few scattered invertebrates or no fossil at all (b, c). Ring artefacts seen close to the isocentre of the scan (b, c) are a well-known phenomenon caused by the X-ray beams traversing the block at an insufficient radiation dose (as expected in such a large block of dense material), and are not part of any physical structure present therein (Triche et al. 2019).
Text-fig. 3. Litho- and biostratigraphic position of fossil floras treated herein, based on lithostratigraphic standard section of upper Oligocene and Miocene in central and eastern Germany (Standke et al. 2010, Escher et al. 2020); only exception from standard section: ** – Thierbach Member restricted to central Germany, replaces Branitz Member in eastern Germany; correlated to global scale of International Chronostratigraphic Chart 2022/02 (Cohen et al. 2013); maximum age ranges of sites/floras indicated by black bars; floristic complexes according to definitions by Mai and Walther 1991 for upper Oligocene, Mai 2000b, 2001b for Miocene; age range of MCO from Steinthorsdottir et al. 2021. in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)
Text-fig. 3. Litho- and biostratigraphic position of fossil floras treated herein, based on lithostratigraphic standard section of upper Oligocene and Miocene in central and eastern Germany (Standke et al. 2010, Escher et al. 2020); only exception from standard section: ** – Thierbach Member restricted to central Germany, replaces Branitz Member in eastern Germany; correlated to global scale of International Chronostratigraphic Chart 2022/02 (Cohen et al. 2013); maximum age ranges of sites/floras indicated by black bars; floristic complexes according to definitions by Mai and Walther 1991 for upper Oligocene, Mai 2000b, 2001b for Miocene; age range of MCO from Steinthorsdottir et al. 2021.
mzML Standard Files from a Diatom
<p>These are mzML files created with Proteowizard. The RAW files are available via MetaboLights Reporistory and are described in the article - DOI: 10.1016/j.phytochem.2022.113267</p> <p>The files are named according to the standard molecule measured with LCMS2. The pure standards used are Betaine, Pipecolatic acid, Methionine Sulfoxide, N,N-dimethylarginine, O-acetyl-L-carnitine, O-propanoyl-L-carnitine, O-butanoyl-L-carnitine, Isovalerylcarnitine, and Cysteinolic acid.</p> <p>The study is done on <em>Skeletonema marinoi </em>which is a diatom. The files with Sc_st are standard+algal QC, and Sc_QC are algal QC.</p>
DrugProt Silver Standard Knowledge Graph
<p><strong>DrugProt Silver Standard Knowledge Graph</strong></p><p> </p><p> </p><p><strong>Please cite if you use any DrugProt resource:</strong></p><p>Antonio Miranda-Escalada, Farrokh Mehryary, Jouni Luoma, Darryl Estrada-Zavala, Luis Gasco, Sampo Pyysalo, Alfonso Valencia, Martin Krallinger, Overview of DrugProt task at BioCreative VII: data and methods for large-scale text mining and knowledge graph generation of heterogenous chemical–protein relations, <i>Database</i>, Volume 2023, 2023, baad080</p><blockquote><p><i>@article{miranda2023overview, title={Overview of DrugProt task at BioCreative VII: data and methods for large-scale text mining and knowledge graph generation of heterogenous chemical--protein relations}, author={Miranda-Escalada, Antonio and Mehryary, Farrokh and Luoma, Jouni and Estrada-Zavala, Darryl and Gasco, Luis and Pyysalo, Sampo and Valencia, Alfonso and Krallinger, Martin}, journal={Database}, volume={2023}, pages={baad080}, year={2023}, publisher={Oxford University Press UK} }</i></p></blockquote><p>Miranda, Antonio, et al. "Overview of DrugProt BioCreative VII track: quality evaluation and large scale text mining of drug-gene/protein relations." <i>Proceedings of the seventh BioCreative challenge evaluation workshop</i>. 2021.</p><blockquote><p><i>@inproceedings{miranda2021overview, title={Overview of DrugProt BioCreative VII track: quality evaluation and large scale text mining of drug-gene/protein relations}, author={Miranda, Antonio and Mehryary, Farrokh and Luoma, Jouni and Pyysalo, Sampo and Valencia, Alfonso and Krallinger, Martin}, booktitle={Proceedings of the seventh BioCreative challenge evaluation workshop}, year={2021} }</i></p></blockquote><p><strong>Description</strong></p><p> </p><p> </p><p><strong>Files:</strong></p><ul><li>drugprot-silver-standard-kg.zip : JSON files with the relations predicted by the DrugProt systems and their precision</li><li>large_scale_network_abstracts.tsv : PubMed abstracts</li><li>large_scale_network_entities.tsv : CHEMICAL/drug and GENE/protein entities predicted by DrugProt NER Taggers</li><li>large_scale_network_pmids.txt : list of PMIDs</li></ul><p> </p><p><strong>Related resources:</strong></p><ul><li><a href="https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-1/">Web</a></li><li><a href="https://doi.org/10.5281/zenodo.4955410">DrugProt corpus</a></li><li><a href="https://github.com/tonifuc3m/drugprot-evaluation-library">Evaluation library</a></li><li><a href="https://codalab.lisn.upsaclay.fr/competitions/8293">Online evaluation (CodaLab)</a></li><li><a href="https://doi.org/10.5281/zenodo.4957137">Relation annotation guidelines</a></li><li><a href="https://doi.org/10.5281/zenodo.4957576">Gene and protein annotation guidelines</a></li><li><a href="https://doi.org/10.5281/zenodo.4957518">Chemicals and drugs annotation guidelines</a></li><li><a href="https://doi.org/10.5281/zenodo.5042178">FAQ</a></li><li><a href="https://doi.org/10.5281/zenodo.5119878">DrugProt Large Scale Additional SubTrack</a></li><li><a href="https://doi.org/10.5281/zenodo.5656991">DrugProt Large Scale document collection protocol</a></li></ul>
Research data supporting "Platinum Nanocatalyst Amplification: Redefining the Gold Standard for Lateral Flow Immunoassays with Ultra-Broad Dynamic Range"
<p>Research data supporting the publication: Loynachan C. N., et al., 2017, ACS Nano, DOI: http://dx.doi.org/10.1021/acsnano.7b06229.</p>
Figure 1 Scatter Plot of Standardized Residual by Standardized Predicted Value-Potential Predictability of ZPD of Children's Cognitive Development
<p>One of the essential assumptions that should be met in regression analysis is the linearity of<br> the data. The result of the analysis of variance (ANOVA) shows that regression model is linear; F<br> (1, 39) = 8.429, P <0.05 for model 1 and F (2, 38) = 8.648, P<0.05 for model 2. Moreover, Scatter<br> plot shows (Figure1) that there is no funnel shaped or crescent shaped cloud. This indicates that two<br> assumptions of linearity and homogeneity of variance have been met.</p>
FRACTESUS_SCK CEN_SA508Cl3 Standard_T0_MCT_input
<div>Fractesus project. Fracture test mini-CT. Master curve input SA508 Cl.3. SCK CEN. </div>
Data from: Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA
<p><span>Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m<sup>3</sup> of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.</span></p> <p><span>The database is organized in five datasets in a csv format (columns separated by commas): (1) metadata providing the location, date, and time for each sample, along with sequencing depth and other essential information (metadata.csv); (2) species-level OTU tables per sample describing the number of sequences assigned to each species (otu.table.csv 3); (3) taxonomic classification of each species-level OTU (taxonomy.csv); (4) closest matching sequences and their taxonomy for ASVs in putatively fungal pseudophyla, which are included in (2) and (3) (fungi_pseudophyla.csv); and (5) closest matching sequences and their taxonomy for ASVs in putatively non-fungal pseudophyla, which are not included in the other datasets (nonfungi_pseudophyla.csv). The first four datasets can be linked to each other using the unique sample codes and the unique identifiers for species-level OTUs. </span><span>The three first datafiles are also provided in allData.RData which can be read into R as load("allData.RData").</span></p>
Data from: Remarkable similarity of oxygen tolerance across marine taxa when standardized for temperature and body size
<p>Species' ranges are shifting in response to increasing temperature and decreasing oxygen in coastal oceans. Forecasting these shifts is limited by information on physiological oxygen thresholds and how they depend on temperature. Here, we adopt an ecophysiological metric, the metabolic index, and estimate its parameters from data collected on marine taxa using phylogenetic trait imputation. The metabolic index is the ratio of temperature-dependent rates of oxygen supply to basal oxygen demands. By applying a hierarchical phylogenetic model to a data set of 74 marine taxa that accounts for both taxonomic distance (from Linnean classification) and biases related to lab methods, we find that the critical oxygen pressure at a reference body size and temperature is remarkably consistent across taxa, ranging 2.9 to 4.9 kPa. In comparison, the estimated effect of temperature on the critical oxygen pressure was more variable among taxa. These findings suggest that species-level differences in oxygen tolerance might be primarily related to differences in body size and preferred temperature. Further, this work provides data-informed distributions of parameters for species that lack experimental data to aid species distribution forecasting.</p>
OrphaCode as a non-standard with mappings to a standard vocabulary in OMOP
<p>The files contain the necessary tables for the introduction of OrphaCode as a non-standard with mappings to a standard vocabulary in OMOP. These include:</p> <ul> <li>concept_manual</li> <li>concept_relationship_manual</li> <li>concept_synonym_manual.</li> </ul> <p>This file has not yet been quality assured, but will be made available for validation.</p>
JAZZVAR: A Dataset of Variations found within Solo Piano Performances of Jazz Standards for Music Overpainting
<p>Release of the MIDI data pairs that constitute the JAZZVAR dataset. See below for the abstract of the publication.</p> <p>The data is also available transposed to C/Am and subsequently, to all keys, with accompanying metadata.</p> <p>Abstract:</p> <p>Jazz pianists often uniquely interpret jazz standards. Passages from these interpretations can be viewed as sections of variation. We manually extracted such variations from solo jazz piano performances. The JAZZVAR dataset is a collection of 502 pairs of Variation and Original MIDI segments. Each Variation in the dataset is accompanied by a corresponding Original segment containing the melody and chords from the original jazz standard. Our approach differs from many existing jazz datasets in the music information retrieval (MIR) community, which often focus on improvisation sections within jazz performances. In this paper, we outline the curation process for obtaining and sorting the repertoire, the pipeline for creating the Original and Variation pairs, and our analysis of the dataset. We also introduce a new generative music task, Music Overpainting, and present a baseline Transformer model trained on the JAZZVAR dataset for this task. Other potential applications of our dataset include expressive performance analysis and performer identification.</p>
Fig. 14. PCA plot for standardized morphometric data for H in A new rupicolous species of gecko of the genus Hemidactylus Oken, 1817 from the Satpura Hills, Central India
Fig. 14. PCA plot for standardized morphometric data for H. chipkali sp. nov. (black), H. cf. murrayi (red) and H. treutleri (blue). Circles = male and squares = female.
MOTU data. FHIR-standardized data collection on the clinical rehabilitation pathway of trans-femoral amputation patients.
<h3>Dataset presented in the article "MOTU on FHIR: A 10-year data collection on the clinical rehabilitation pathway of 1006 trans-femoral amputees".</h3> <p>Data has been anonymised prior the publication. The data are in Comma-separated-values (CSV) format. </p> <p>This work has been conducted within the framework of the MOTU++ project (PR19-PAI-P2).</p> <p><span>This research was co-funded by the Complementary National Plan PNC-I.1 "Research initiatives for innovative technologies and pathways in the health and welfare sector” D.D. 931 of 06/06/2022, DARE - DigitAl lifelong pRevEntion initiative, code PNC0000002, CUP: (B53C22006450001) and by the Italian National Institute for Insurance against Accidents at Work (INAIL) within the MOTU++ project (PR19-PAI-P2). </span></p> <p><span>Authors express their gratitude to all the AlmaHealthDB Team.</span></p>
Dataset: Standard BioTools Inc. (LAB) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Рис. 1. Вероятность обнаружения меченых животных (среΑнее ± ошибка) при пяти- и Αесятиметровых интерваΛах межΑу прикормочными станциями в Αвух экспериментах. По второму эксперименту расчеты сΑеΛаны ΑΛя резуΛьтатов отΛова в течение первых трех и поΛных Αесяти Αней. Значение «p» отражает уровень статистической значимости разΛичий межΑу ΑоΛями животных с меткой при Αвух интерваΛах Fig. 1. Probability of finding marked animals (average±standard error) between feeding stations placed at intervals of five and ten meters in the two experiments. In the second experiment, calculations were made for the results of trapping during the first three days and during the whole period of ten days. The p value reflects the statistical significance of differences between the fractions of animals with a mark for two types of intervals in Verification of the bottle-based method for estimating abundance of small mammals using biomarkers
Рис. 1. Вероятность обнаружения меченых животных (среΑнее ± ошибка) при пяти- и Αесятиметровых интерваΛах межΑу прикормочными станциями в Αвух экспериментах. По второму эксперименту расчеты сΑеΛаны ΑΛя резуΛьтатов отΛова в течение первых трех и поΛных Αесяти Αней. Значение «p» отражает уровень статистической значимости разΛичий межΑу ΑоΛями животных с меткой при Αвух интерваΛах Fig. 1. Probability of finding marked animals (average±standard error) between feeding stations placed at intervals of five and ten meters in the two experiments. In the second experiment, calculations were made for the results of trapping during the first three days and during the whole period of ten days. The p value reflects the statistical significance of differences between the fractions of animals with a mark for two types of intervals
Datasets on approved and ongoing standards for Cloud, Edge and IoT computing in the continuum and analysis and assessment of relevance
<p>Two datasets:</p> <ol> <li><span>the database of standards relevant to the Cloud-Edge-IoT continuum and to the ACES-EDGE Research and Innovation Action funded under the grant agreement No. 101093126 call HORIZON-CL4-2022-DATA-01-02.</span></li> <li><span>the Excel workbook with the analysis of the assessment of the standards in relation to the needs of the ACES-EDGE implementation.</span></li> </ol> <p><span>Both datasets will be used for a more deep assessment of the standardisation requirements of the ongoing technolgical developments.</span></p>
Figure 2. – Otolith images from a in Automatic method to transform routine otolith images for a standardized otolith database using R
Figure 2. – Otolith images from a binocular dissecting microscope under different types of illumination: A. Reflected light and B. Transmitted light.
Figure 1 in Automatic method to transform routine otolith images for a standardized otolith database using R
Figure 1. – Different types of otolith images showing common issues. Scale is different between images depending on the sample, some broken otoliths, various exposures and colors, some particles may be present (hair, bubbles).
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.