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5,738 results for “Standards”
Identifying continuing education resources on new data standards and technologies through an automatic crawling system
<p><span>This presentation discusses part of a project that aims to create a continuing education repository for information professionals. The presentation covers: the current challenges that information professionals face; issues in accessing continuing education resources; the design of the project and in particular its automatic crawler; and the results.</span></p>
Data and code for "Large volume injection and assessment of reference standards for n-alkane δD and δ13C analysis via gas chromatography isotope ratio mass spectrometry"
<p>This file includes data and code related ot the publication, "<span>Large volume injection and assessment of reference standards for <em>n</em>-alkane δD and δ<sup>13</sup>C analysis via gas chromatography isotope ratio mass spectrometry" in Rapid Communications in Mass Spectrometry (in review). Included are datasets of <em>n</em>-alkane δD and δ<sup>13</sup>C measurements with a recently developed large-volume injeciton method. Measuremtns of reference standards and lake sediment samples from Eifel maar lakes of Germany are included. Additionally, code to implement the correction schemes and reporduce the figures and analysis described in the paper are included. </span></p>
FIGURE 2. Pueraria grandiflora. A. Calyx. B. Bracteoles. C. Bracts. D. Standard. E. Wing. F. Keel. G. Stamens. H. Pistil. I. Inflorescence. J. Tuberous roots. K. Flower. L. Pod. M. Flowering branch. N. Seed. O in Pueraria grandiflora (Fabaceae), a new species from Southwest China
FIGURE 2. Pueraria grandiflora. A. Calyx. B. Bracteoles. C. Bracts. D. Standard. E. Wing. F. Keel. G. Stamens. H. Pistil. I. Inflorescence. J. Tuberous roots. K. Flower. L. Pod. M. Flowering branch. N. Seed. O. Leaf with entire leaflets. Illustrations by Bo Pan.
FIGURE 6. Indigofera karuppiana. A. Habit, B. Standard petal, C.,D. Wing petals, E. Keel,F. Calyx, G in A revision of trifoliolate Indigofera (Tribe Indigofereae: Fabaceae) in India
FIGURE 6. Indigofera karuppiana. A. Habit, B. Standard petal, C.,D. Wing petals, E. Keel,F. Calyx, G. Pod. (Based on: Chauhan 1465 DUH). Drawn by V. Chauhan.
FIGURE 8. Indigofera prostrata. A. Habit, B. Trifoliolate leaf, C. Calyx, D. Standard petal, E.,F. Wing petals, G. Keel, H. Pod, I in A revision of trifoliolate Indigofera (Tribe Indigofereae: Fabaceae) in India
FIGURE 8. Indigofera prostrata. A. Habit, B. Trifoliolate leaf, C. Calyx, D. Standard petal, E.,F. Wing petals, G. Keel, H. Pod, I. Seeds. (Based on: Chauhan & Pandey 1452 DUH). Drawn by V. Chauhan.
FIGURE 10. Indigofera trita. A. Habit, B. Standard petal, C.,D. Wing petals, E. Keel, F. Calyx, G in A revision of trifoliolate Indigofera (Tribe Indigofereae: Fabaceae) in India
FIGURE 10. Indigofera trita. A. Habit, B. Standard petal, C.,D. Wing petals, E. Keel, F. Calyx, G. Pod. (Based on: A, B, C, D, E, F, Chauhan 1455 DUH; G, Chauhan 1471 DUH). Drawn by V. Chauhan.
FIGURE 77. Daviesia articulata. A. Flowering branchlet. B. Inflorescence. C. Pod with persistent standard. A, B from Crisp 6058 in A monograph of Daviesia (Mirbelieae, Faboideae, Fabaceae)
FIGURE 77. Daviesia articulata. A. Flowering branchlet. B. Inflorescence. C. Pod with persistent standard. A, B from Crisp 6058; C from Crisp 5201. Drawn by B-J. Osborne. Adapted from Crisp (1995) with permission from CSIRO Publishing.
FIGURE 34. Daviesia spiralis. A. Flowering branchlet. B. Inflorescence. C. Standard, adaxial view. D in A monograph of Daviesia (Mirbelieae, Faboideae, Fabaceae)
FIGURE 34. Daviesia spiralis. A. Flowering branchlet. B. Inflorescence. C. Standard, adaxial view. D. Same, showing calli in transection (indicated by arrows in C), adaxial face upward. E. Wing. F. Keel. G. Pod. H, I. Seed in lateral and hilar view respectively. A from Kenneally 2303; B–I from Crisp 5491 (holotype). Drawn by B-J. Osborne and M.D. Crisp.
FIGURE 1. A. argaeus A. General view. B. Stipule. C.Leaflet. D. Bract. E. Calyx. F. Standard. G. Wings. H. Keel. I in Morphological, anatomical, palynological, karyological and ecological remarks of Astragalus argaeus (Fabaceae) endemic to Turkey
FIGURE 1. A. argaeus A. General view. B. Stipule. C.Leaflet. D. Bract. E. Calyx. F. Standard. G. Wings. H. Keel. I. Pistil ve Stamen. J. Fruit.
FIG. 3. Body depth–standard length relationships among L. fuelleborni, L in Six New Species of Labeotropheus (Cichliformes: Cichlidae) from the Malaŵian Shore of Lake Malaŵi, Africa
FIG. 3. Body depth–standard length relationships among L. fuelleborni, L. trewavasae, and the three new species of Labeotropheus from the southwestern portion of Lake Malaŵi. The ANOVA accompanying these data is in Table 4.
FIG. 6. Body depth–standard length relationships among L. fuelleborni, L. trewavasae, L. chlorosiglos, L in Six New Species of Labeotropheus (Cichliformes: Cichlidae) from the Malaŵian Shore of Lake Malaŵi, Africa
FIG. 6. Body depth–standard length relationships among L. fuelleborni, L. trewavasae, L. chlorosiglos, L. simoneae, and the three new species of Labeotropheus from the northwestern portion of Lake Malaŵi. (A) All seven species; (B) same plot as A, but L. fuelleborni and L. trewavasae are omitted for clarity. The ANOVA accompanying these data is in Table 7.
Dataset: Gold standard dataset for explainability need detection in app reviews.
<p>We crawled 90,000 app reviews from both Google Play Store and Apple App Store, including reviews from both free and paid apps. These reviews were filtered for explainability needs, and after this process, 4,495 reviews remained. Among them, 2,185 reviews indicated an explanation need, while 2,310 did not. This resulting gold standard dataset was used to train and evaluate several machine learning models and rule-based approaches for detecting explanation needs in app reviews.</p> <p>The dataset includes both balanced and unbalanced evaluation sets, as well as the original crawled data from October 2023. In addition to machine learning approaches, rule-based methods optimized for F1 score, precision, and recall are also included.</p> <p>We provide several pre-trained machine learning models (including BERT, SetFit, AdaBoost, K-Nearest Neighbor, Logistic Regression, Naive Bayes, Random Forest, and SVM) along with training scripts and evaluation notebooks. These models can be applied directly or retrained using the included datasets.</p> <p>For further details on the structure and usage of the dataset, please refer to the README.md file within the provided ZIP archive.</p>
HR Measures From Four Consumer-Grade Optical Heart Rate Sensors with Gold Standard ECG Reference
<p>Accompanying paper that explains data collection, research methods, cleaning etc. is under review as:</p> <p>"Validity of Four Consumer-Grade Optical Heart Rate Sensors for Assessing Volume and Intensity Distribution of Physical Activity"</p> <p>Currently with: Scandinavian Journal of Medicine & Science in Sports TBD, 2024-12-31</p> <p>Four files contain HR data at 1 Hz for each of the devices (Garmin Venu2S and Polar Vantage M2, and the upper arm-worn Polar Verity Sense and Scosche Rhythm24) [device column] paired with medical-grade ECG [ecg column], Type: EP830, Amedtec ECGpro, Aue, Germany</p>
Demo ER Lab ALEX DNA Standards
Open the record for dataset details and reuse information.
Means and standard errors of fits for the l=2 spherical harmonic expansion coefficients of the radio brightness distribution on the sky using Parker Solar Probe/FIELDS/RFS data
Open the record for dataset details and reuse information.
Data from: Deep COI sequencing of standardized benthic samples unveils overlooked diversity of Jordanian coral reefs in the Northern Red Sea
High-Throughput Sequencing (HTS) of DNA barcodes (metabarcoding), particularly when combined with standardized sampling protocols, is one of the most promising approaches for censusing overlooked cryptic invertebrate communities. We present biodiversity estimates based on sequencing of the cytochrome c oxidase subunit 1 (COI) gene for coral reefs of the Gulf of Aqaba, a semi-enclosed system in the Northern Red Sea. Samples were obtained from standardized sampling devices [Autonomous Reef Monitoring Structures (ARMS)] deployed for 18 months. DNA barcoding of non-sessile specimens >2mm revealed 83 OTUs in six phyla, of which only 25% matched a reference sequence in public databases. Metabarcoding of the 2mm-500μm and sessile bulk fractions revealed 1197 OTUs in 15 animal phyla, of which only 4.9% matched reference barcodes. These results highlight the scarcity of COI data for cryptobenthic organisms of the Red Sea. Compared with data obtained using similar methods, our results suggest that Gulf of Aqaba reefs are less diverse than two Pacific coral reefs but much more diverse than an Atlantic oyster reef at a similar latitude. The standardized approaches used here show promise for establishing baseline data on biodiversity, monitoring the impacts of environmental change, and quantifying patterns of diversity at regional and global scales.
FIGURE 1. Rhynchosia bolusii. A, Standard petal. B, Keel petal. C, Wing petal. D in Rhynchosia bolusii (Phaseoleae, Fabaceae), a new species from the Western Cape Province of South Africa
FIGURE 1. Rhynchosia bolusii. A, Standard petal. B, Keel petal. C, Wing petal. D, Flower in lateral view. E, Pistil. F, Androecium. G, Pod in lateral view. H, Leaf in abaxial view. I, Outer surface of the calyx (upper lobes to the left). J, Bract. Scale bars represent 1 mm. Voucher specimens. A–F, H–J, Stokoe 66079 (NBG). G, Bolus 11841 (BOL).
FIGURE 1. a–n. a. Habit. b. Upper leaf surface. c. Lower leaf surface. d. Inflorescence. e. Sepals. f. Standard. g in Rhynchosia sousae (Leguminosae, Papilionoideae), a new species from eastern Mexico
FIGURE 1. a–n. a. Habit. b. Upper leaf surface. c. Lower leaf surface. d. Inflorescence. e. Sepals. f. Standard. g. Detail of the glanddotted. h. Wings. i. Claw. j. Androecium. l. Gynophore. m. Fruit. n. Seed, hilar view and side view.
FIGURE 3. A in A standardized and statistically defensible framework for quantitative morphological analyses in taxonomic studies
FIGURE 3. A visual description of a boxplot to illustrate how outliers are detected. Using this method, values above the maximum range or below the minimum range are considered outliers. The maximum range is defined as the upper quartile (Q3) plus 1.5 times the interquartile range (IQR), while the minimum range is defined as the lower quartile (Q1) minus 1.5 times the IQR.
FIGURE 2. The 5 in A standardized and statistically defensible framework for quantitative morphological analyses in taxonomic studies
FIGURE 2. The 5-step workflow for statistical hypothesis testing of morphological characters. Note that mensural and meristic data should be analyzed separately and that Step 4 should only be performed on mensural data. * = parametric tests; ** = nonparametric tests. The non-parametric tests shown here only serve as examples—the appropriate test should be selected based on which assumptions are violated. A companion R script that implements this workflow is provided in the Supplementary Material.
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.