Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,351
datasets available to search
ShareScore release 0.9.0
Dataset results
1,351 results for “Intermediates”
FIGURES 6‒10 in Taxonomy of 'Euconnus complex'. Part XXIV. Intermediate forms between Psomophus, Eupentarius and Euconnus s. str. in the East Palaearctic fauna unify problematic subgenera (Coleoptera, Staphylinidae, Scydmaeninae)
FIGURES 6‒10. Euconnus multiinsularis sp. n., male (Takarajima). Dorsal habitus (6); aedeagus in ventral (7, 9) and lateral (8, 10) views.
FIGURES 37‒45 in Taxonomy of 'Euconnus complex'. Part XXIV. Intermediate forms between Psomophus, Eupentarius and Euconnus s. str. in the East Palaearctic fauna unify problematic subgenera (Coleoptera, Staphylinidae, Scydmaeninae)
FIGURES 37‒45. Euconnus yaimanus sp. n., male, specimens from Iriomote-jima (37‒41) and Yonaguni-jima (42‒45). Dorsal habitus (37); aedeagus in ventral (30, 32, 42, 44) and lateral (39, 41, 43, 45) views.
FIGURES 54‒58 in Taxonomy of 'Euconnus complex'. Part XXIV. Intermediate forms between Psomophus, Eupentarius and Euconnus s. str. in the East Palaearctic fauna unify problematic subgenera (Coleoptera, Staphylinidae, Scydmaeninae)
FIGURES 54‒58. Euconnus pseudotrimerus sp. n., male. Dorsal habitus (54); aedeagus in ventral (55, 57) and lateral (56, 58) views.
Intermediate files for dRep / inStrain tutorial
<p>Intermediate files for dRep / inStrain tutorial</p>
Aviation Fuel Production Pathways from Lignocellulosic Biomass via Alcohol Intermediates – A Technical Analysis - Supplementary Material
<p>Data for the associated publication </p>
Raw data for the article "Photocatalytic Decarboxylative Functionalization of Cyclopropenes via Cyclopropenium Cation Intermediates"
<p>Raw NMR, IR and MS data for the article "Photocatalytic Decarboxylative Functionalization of Cyclopropenes via Cyclopropenium Cation Intermediates" published in Angewandte Chemie, DOI: </p> <p><a href="https://doi.org/10.1002/anie.202404265">https://doi.org/10.1002/anie.202404265</a></p> <p>The number of the folders either correspond to compounds numbers in the article or the name of the folder is self-describing. All details concerning conditions and equipment for measurements can be found in the supporting information of the article. For convenience, the word file version of the supporting information can be found on the top of the raw data folder.</p> <h2> </h2>
Dataset and code for 'Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region'
<p>Feature fitting code and spectra of olivine samples used in paper "<em>Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region: Applications in Planetary Sciences</em>"</p>
Experimental data supporting the paper "Rep structures can be tuned by ionicity via metastable intermediates in the absence of DNA"
<p>experimental data sets for our paper on the conformational dynamics of Rep helicase "Rep structures can be tuned by ionicity via metastable intermediates in the absence of DNA"</p>
Catalyst Control over S(IV)-stereogenicity via Carbene-derived Sulfinyl Azolium Intermediates
<p><span>This folder /DFT_optimized_structures/ contains the DFT-optimized geometries (in .xyz format together with the gas-phase energy, E) accompanying the paper</span></p> <p><span>"Catalyst Control over S(IV)-stereogenicity via Carbene-derived Sulfinyl Azolium Intermediates"</span></p> <p><span>where conformers occur, they are always named from the lowest Gibbs energy to the highest in ascending order from c1 (sometimes omitted), c2, c3, ...</span></p>
Intermediate data objects from running the machine learning code for Shen et al, Nature, 2018
<p>These are the RData objects of the processed cfMeDIP data that were used to run the machine learning analyses in "Sensitive tumour detection and classification using plasma cell-free DNA methylomes", Nature, 2018. This archive also includes the models we generated, and training and validation data matrices that people can use to fit new models and evaluate performance. These objects are to be used with the scripts and markdown at doi: 10.5281/zenodo.1242697 . The ReadMe contains descriptions. </p>
Intermediate-onset colorectal cancer: a clinical and familial boundary between both early and late-onset colorectal cancer
<p>Comparative studies of colorectal cancer (CRC) according to the age of onset<br> have found differences between early-onset CRC (EOCRC) and late-onset CRC<br> (LOCRC). Using this as a starting point, we wished to determine whether intermediateonset<br> CRC (IOCRC) might also be considered as an independent group within CRC.<br> We performed a retrospective comparative study of the clinicopathological and familial<br> features, as well as of the symptoms and their duration, of a total of 272 subjects<br> diagnosed with CRC classified into three groups according to the age-of-onset (98<br> EOCRC, 83 IOCRC and 91 LOCRC). The results show that from a clinicopathological<br> point of view, IOCRC shared certain features with EOCRC (gender, prognosis), and<br> with LOCRC (multiple primary CRCs), whereas it also had characteristics that were<br> specific for IOCRC (mean number of associated polyps). A gradual progression was<br> observed from EOCRC to LOCRC from a greater family aggregation to sporadic cases,<br> in parallel with a change of Lynch Syndrome cases to the sporadic microsatellite<br> instability pathway, with the IOCRC being a boundary group that is more related to<br> EOCRC. With respect to symptoms, duration and correlation with stages, IOCRC<br> appeared more similar to EOCRC. Clinically, IOCRC behaves as a transitional group<br> between EOCRC and LOCRC, with features in common with both groups, but also<br> with IOCRC-specific features. Excluding cases with familial cancer history, the<br> awareness for EOCRC diagnosis should be extended to IOCRC.</p>
Intermediate bosonic metallic state in the superconductor-insulator transition
<p>Whether a metallic ground state exists in a two-dimensional system beyond Anderson localization remains an unresolved question. Here, we study how quantum phase coherence evolves across superconductor-metal-insulator transitions via magneto-conductance quantum oscillations in nanopatterned high-temperature superconducting films. We tune the degree of phase coherence by varying the etching time of our films. Between the superconducting and insulating regimes, we detect a robust intervening anomalous metallic state characterized by saturating resistance and oscillation amplitude at low temperatures. Our measurements suggest that the anomalous metallic state is bosonic and that the saturation of phase coherence plays a prominent role in its formation.</p>
Properties of intermediate- to high-mass stars in the young cluster M17 Characterizing the (pre-)Zero Age Main Sequence
<p>Data and extra figures of the paper "Properties of intermediate- to high-mass stars in the young cluster M17 -- Characterizing the (pre-)Zero Age Main Sequence" by Frank Backs. Published in Astronomy and Astrophysics.</p> <p>The observed data and the fitted models are included. The fitting algorithm Kiwi-GA is available on Github: https://github.com/sarahbrands/Kiwi-GA</p> <p>Additional figures are available. These figures give an overview of the best fit models for each line like Fig. 1 in the paper. </p>
Intermediate Data Products for "A NASA GISTEMPv4 Observational Uncertainty Ensemble"
<p>Contains the Intermediate data for "A NASA GISTEMPv4 Observational Uncertainty Ensemble" as accepted at JGR:Atmospheres (August 2024).</p> <p>Raw and Results Data can be found here: <a href="https://doi.org/10.5281/zenodo.13343335">https://doi.org/10.5281/zenodo.13343335</a></p>
FIGURE 87. Daviesia debilior subsp. debilior. A. Flowering branchlet. B. Juvenile phyllode. C. Intermediate phyllode. D. Inflorescence. E in A monograph of Daviesia (Mirbelieae, Faboideae, Fabaceae)
FIGURE 87. Daviesia debilior subsp. debilior. A. Flowering branchlet. B. Juvenile phyllode. C. Intermediate phyllode. D. Inflorescence. E. Calyx opened out, upper lobes at left. F. Standard. G. Wing. H. Keel. I. Pod. Daviesia debilior subsp. sinuans. J. Fruiting branchlet. K Seed, lateral view. L. Same, hilar view. A from Chapman (21B)77 (type); B–H from Chapman s.n. (CBG 8004030); I from Chapman (66)77; J from Ising s.n. (AD 97622028); K, L from Demarz 1854. Drawn by A.L. Prowse.
FIGURE 6. Daviesia acicularis. A. Fruiting branchlet. B. Developmentally intermediate phyllode. C. Flower. D. Pod. A from Crisp 6790 in A monograph of Daviesia (Mirbelieae, Faboideae, Fabaceae)
FIGURE 6. Daviesia acicularis. A. Fruiting branchlet. B. Developmentally intermediate phyllode. C. Flower. D. Pod. A from Crisp 6790; B from Anon. (NSW 35616); C from Burgess s.n. (CBG 7468); D from Carolin 3880 (SYD). Drawn by B-J. Osborne.
FIGURE 7. Nepenthes fusca Danser. A—climbing stem with emerging inflorescence. B—lower pitcher. C—intermediate pitcher. D in Revisions in Nepenthes following explorations of the Kemul Massif and the surrounding region in north-central Kalimantan, Borneo
FIGURE 7. Nepenthes fusca Danser. A—climbing stem with emerging inflorescence. B—lower pitcher. C—intermediate pitcher. D— base of lower/intermediate pitcher lid, showing detail of highly glandular keel. E—upper pitchers, top right ventral view, bottom left lateral view. F—base of upper pitcher lid showing distribution of indumentum. G—lower pitcher lid, top adaxial surface, bottom abaxial surface. H—peristome in cross-section. I—dehiscing seed capsules. J—male flowers. Scale bars: A, B, C, E, G = 1 cm, D, F, H, I, J = 5 mm. Based on Endert 3955 (isotype K) and supplemented with photographs and measurements made of in situ material. Illustrated by M. Barer.
FIGURE 3. Pteridocalyx appunii. Calycophyll variation within the same inflorescence branch. A. Basal flower. B–D. Intermediate flowers, from base towards distal portion. E. Distal flower. A–E in Notes on calycophyllous Rubiaceae. Part V. A succinct overview of genera with calycophylls, and a revision of Pteridocalyx (Sipaneeae) with observations on distyly and calycophyll variation
FIGURE 3. Pteridocalyx appunii. Calycophyll variation within the same inflorescence branch. A. Basal flower. B–D. Intermediate flowers, from base towards distal portion. E. Distal flower. A–E: drawn from P.G. Delprete & P. Benjamin 12813 (CAY). Illustration by Piero Delprete.
13 New Instances for the Mixed Capacitated Arc Routing Problem with Intermediate Facilities under Time Constraints (MCARPTIF) (Road Cleaning Problem)
<p><strong>Dataset Overview</strong></p> <p>This dataset includes 13 instances specifically designed for evaluating the performance of vehicle routing algorithms in road cleaning problems. Existing benchmark instances in the literature predominantly focus on waste collection applications, which are not directly suitable for testing the unique characteristics of the road cleaning problem addressed in this study. To fill this gap, we have utilized a real-world dataset from the city of Zibo and a synthetic dataset modeled after the well-known lpr dataset.</p> <p><strong>1. Zibo Road Cleaning Dataset (zb)</strong></p> <p>The Zibo dataset (zb) represents a portion of the actual road network in Zibo, consisting of three depots, 319 nodes, and 962 arcs. We partitioned this road network into three sub-networks—zb1, zb2, and zb3—based on the distance between the arcs and depots, as well as the operational capabilities of the fleet. This transformation allowed us to treat the problem as a single-depot problem for each sub-network. The zb dataset serves as a realistic benchmark for the road cleaning problem.</p> <p><strong>2. lpr-rc Dataset</strong></p> <p>To further test the heuristics, we generated the lpr-rc dataset using a generation method inspired by the lpr dataset (Belenguer et al., 2006). The lpr-rc dataset consists of ten instances (labeled lpr-rc-1 to lpr-rc-10) of varying sizes, with nodes ranging from 27 to 268 and arcs ranging from 88 to 952. Each instance features a depot fixed in the top-left corner of the road network. Infrastructure facilities (IFs), including sewage disposal stations and water replenishment stations, are uniformly distributed across the network. The number of IFs is scaled based on the network size, adding complexity to the routing tasks.</p> <p><strong>Dataset Format</strong></p> <p>The dataset is provided in Excel format, with each instance containing two sheets:</p> <ol> <li> <p><strong>Road Network</strong>: This sheet includes the unique road segment codes, the codes for the endpoints of each road segment, and the latitude and longitude coordinates for these points. Both road segment codes and endpoint codes are unique identifiers.</p> </li> <li> <p><strong>Intermediate Facilities (IFs)</strong>: This sheet provides the unique codes for each facility and their respective latitude and longitude coordinates. The facilities represent points where vehicles can perform water replenishment or sewage disposal.</p> </li> </ol> <p><strong>Vehicle Fleet Information</strong></p> <p>While the dataset does not impose specific vehicle parameters, it is designed to support the use of heterogeneous fleets. The following information describes a typical fleet of medium-sized mechanized cleaning vehicles, which we used in our study:</p> <ul> <li>The fleet is homogeneous, and we define the following parameters: <ul> <li>Q_w: Freshwater tank capacity = 8000 L</li> <li>Q_s: Sewage tank capacity = 2000 L</li> <li>R_w: Freshwater consumption rate = 83.33 L/min</li> <li>R_s: Sewage collection rate = 22.22 L/min</li> <li>\lambda_w: Duration for water replenishment at IFs = 0.25 h</li> <li>\lambda_s: Duration for sewage disposal at IFs = 0.16 h</li> <li>V_w: Service speed = 10 km/h</li> <li>V_d: Dead-heading speed (traveling without service) = 30 km/h</li> </ul> </li> </ul> <p>This fleet configuration enables a realistic simulation of road cleaning operations and can be adjusted based on real-world vehicle specifications as needed.</p> <p><strong>Availability</strong></p> <p>The 13 instances, including the zb and lpr-rc datasets, are now publicly available on Zenodo. These instances are designed to facilitate further research in road cleaning and related vehicle routing problems.</p> <p><strong>Reference</strong></p> <p>Belenguer, J.M., Benavent, E., Lacomme, P., Prins, C., 2006. Lower and upper bounds for the mixed capacitated arc routing problem. Computers & Operations Research 33, 3363–3383. doi:10.1016/j.cor.2005.02.009.</p>
Alphafold2_ab_initio iterative predictions for folding intermediate identification
<p>Iterative structure predictions for protein PDB ids starts from 6.</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.