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.
10,016
datasets available to search
ShareScore release 0.9.0
Dataset results
10,016 results for “Observation”
Figure 2 in Description of BOLeODOruS buShehreNSIS n. sp. (Rhabditida: Tylenchidae) from Southern Iran, and Observations on a Commonly Known Species
Figure 2: Light microphotographs of Boleodorus bushehrensis n. sp. (A, B, C, E, F, I, J, K: female; D, G, H: male). (A, B) Anterior region showing cephalic region and stylet, respectively. (C) Pharyngeal metacorpus. (D) Anterior body region showing the oral aperture in a depression. (E, J) Pharyngeal bulb region showing excretory pore. (F, G, I) Tail tip. (H) Bursa. (K) Lateral field at midbody. (All scale bars = 10 Mm).
Figure 6 in Description of BOLeODOruS buShehreNSIS n. sp. (Rhabditida: Tylenchidae) from Southern Iran, and Observations on a Commonly Known Species
Figure 6: Scanning electron microphotographs of Boleodorus thylactus Thorne, 1941 (female). (A–C) Anterior end in ventral and frontal views, respectively (arrows pointing to the amphidial openings). (D,E) Excretory pore in ventral and lateral views (arrow). (F, K) Lateral field at midbody showing four incisures. (G,H) Vulva in lateral and ventral views, respectively. (I) Posterior end in lateral view. (J) Anus in ventral view.
Figure 1 in Description of BOLeODOruS buShehreNSIS n. sp. (Rhabditida: Tylenchidae) from Southern Iran, and Observations on a Commonly Known Species
Figure 1: Line drawings of Boleodorus bushehresnsis n. sp. (A, B, D, E, G: female; C, F: male). (A) Pharynx. (B) Posterior body region. (C) Anterior body region. (D) Vulval region, showing offset spermatheca. (E–G) Tail.
Figure 5 in Description of BOLeODOruS buShehreNSIS n. sp. (Rhabditida: Tylenchidae) from Southern Iran, and Observations on a Commonly Known Species
Figure 5: Bayesian 50% majority rule consensus tree inferred from the LSU rDNA D2–D3 sequences of Boleodorus bushehrensis n. sp. under the GTR + G + I model. Bayesian posterior probability values are given for the corresponding clades. The new species is in bold font. GTR, general time-reversible; G, gamma; I, invariant; LSU, large subunit; rDNA, ribosomal DNA.
Figure 4 in Observations of five litle-known tubenoses from Melanesia in January 2017
Figure 4. Map of the northern Banks Islands, North Vanuatu, marking the locations mentioned in the text, as well as the 'hotspot' for returning Magnificent Petrels (H. Shirihai in lit. 2017) and Vanuatu Petrels (Bretagnolle & Shirihai 2010).
FTIR Microscopy for Direct Observation of Conformational Changes on Immobilized ω-Transaminase: Effect of Water Activity and Organic Solvent on Biocatalyst Performance
<p>Enzyme immobilization is a key strategy to expand the scope of enzyme applications and to enable the recycling of biocatalysts, resulting in greener and more cost-efficient processes. The full exploitation of the technology advantages is strictly connected to the optimal selection of the carriers and the rational development of the immobilization protocol. The present study achieved such objectives by investigating the activity of a ω-transaminase in organic solvent (toluene) upon immobilization on commercially controlled porosity glass carriers (EziG™) with diverse porosity and surface functionalization. In addition to more conventional wet-chemistry approaches and confocal microscopy, infrared microspectroscopy and imaging were exploited to highlight the enzyme distribution in a label-free manner and provide details on the immobilized enzyme's conformation with respect to the native form. Contrary to what could be expected, the highest activity of the enzyme in organic solvent was achieved for the immobilization protocol on the most hydrophilic support that more severely affects the enzyme secondary structure, promoting a beta-sheet rich folding. Experimental data show that values of water activity above 0.90 in the reaction system had a positive effect on the efficiency of the transaminase reaction. The present study represents the first example of rational development of immobilization protocols relying on direct observation of the enzyme conformation upon immobilization, shedding light on the mutual interaction between the diverse process parameters and the carrier properties.</p>
Figure 2 in Endemic and enigmatic: the reproductive biology of Aegla (Crustacea: Anomura: Aeglidae) with observations on sperm structure
Figure 2. Light micrographs of Aegla rostrata Jara, 1977. A, Spermatophoric lobes; B–G, Squash of spermatophoric lobe contents showing spermatozoa (arrowheads) scattered amongst assorted cells (Asterisk in E and G indicate individual spermatozoa with three microtubular arms).
Figure 1 in Endemic and enigmatic: the reproductive biology of Aegla (Crustacea: Anomura: Aeglidae) with observations on sperm structure
Figure 1. Occurrence of ovigerous females of Aegla species obtained from literature sources and USNM specimens. Total USNM specimens examined = 958 (40 ovigerous females). Symbols: 1 Bahamonde and López (1961); 2 Jara (1989); 3 Bueno and Bond-Buckup (2000); 4 Swiech-Ayoub and Masunari (2001a, 2001b); 5 Rodrigues and Hebling (1978); 6 Jara (1977); 7 Lopéz (1965). Shading = range from literature sources indicated. Solid black bar = number from USNM collection for that month.
Figure 3 in Endemic and enigmatic: the reproductive biology of Aegla (Crustacea: Anomura: Aeglidae) with observations on sperm structure
Figure 3. Transmission electron micrograph of spermatozoon of Aegla longirostri Bond-Buckup and Buckup, 1994 in longitudinal section. Abbreviations: av, acrosome vesicle; cy, cytoplasm; m, mitochondrion; ms, membrane system; mt, microtubular bundle; n, nucleus; p, perforatorial column; pm, periacrosomal material.
SERPENTINE catalog of solar energetic particle events observed by Helios
<p>This catalog contains multi-spacecraft solar energetic particle (SEP) events, which were observed by Helios. It has been created within the European Union’s Horizon 2020 project <em>SERPENTINE</em> (Solar energetic particle analysis platform for the inner heliosphere). This catalogue is based on data from the Helios mission provided by the previous European project <a href="https://sepserver.eu/index.php?page=catalogue">SEPServer</a>. In addition, technical reports of the University of Kiel from the time of Helios observation (printed version) were used, but the final judgement was done on the basis of the data from SEPServer.</p> <div> <p>It is not the first time that data from this historical mission are included in a statistical study. In Lario et al., 2006 (<a href="https://doi.org/10.1086/508982">https://doi.org/10.1086/508982</a>) some events observed by two or more spacecraft were analyzed from the point of view of their longitudinal and radial spread. The events where protons with energies above 13 MeV were observed by the Helios spacecraft when they were located at less than ~0.85 AU from the Sun were in the focus of the ESA SOL2UP project (for details see Pacheco, 2019, PhD Thesis, <a href="http://hdl.handle.net/10803/667033">http://hdl.handle.net/10803/667033</a>). The events from our catalogue which overlap with these previous studies are marked by letters L or P, correspondingly. At the same time, the data related to the overlapping events (same as for all other events), either characterizing the solar source, location of the observer (spacecraft) or relating to the properties of the particle fluxes were identified independently for the present catalogue. Nevertheless, we would like to acknowledge the authors of the previous SOL2UP project for providing us with the results of their studies.</p> <p>In the majority of the cases the identification of the location of the solar source was based on the available X-ray data of the related solar flare, published in (<a href="https://www.ngdc.noaa.gov">Solar Geophysical Data</a>). In addition, we used information from a previous study of Helios events (Kallenrode 1997, private communication), marked with the “K” sign. The radial distance of the spacecraft from the Sun, the solar wind speed and the Earth-Sun-spacecraft angle were taken from (<a href="https://cdaweb.gsfc.nasa.gov">CDAweb</a>). If there were no data for the solar wind speed during the time of the event, a standard value of 400 km/s was used (in the list itself and in the calculation of the longitude of the magnetic footpoint of the spacecraft). If there was, e.g., a high speed stream of the solar wind close to the time of the event then the average value of the solar wind stream was used. In both cases we used the “~” sign to denote such uncertainties. The location of the footpoint of the spacecraft of the solar disc was obtained by using a simple ballistic back mapping. The proton onset times are based on the SEPServer data.</p> <p> </p> </div> <p>The csv files provided here are archived versions of the <strong>dynamic catalog available at <a href="https://data.serpentine-h2020.eu/catalogs/sep-helios/">https://data.serpentine-h2020.eu/catalogs/sep-helios/</a></strong></p> <p> </p>
Seasonal and local time variation in the observed peak of the meteor altitude distributions by meteor radars
<p>These uploaded datasets support and appear in the the paper entitled "<strong>Seasonal and local time variation in the observed peak of the meteor altitude distributions by meteor radars</strong>" prepared by: </p> <p>E.C.M. Dawkins<sup>1,2</sup>, D. Janches<sup>1</sup>, G. Stober<sup>3</sup>, J.D. Carrillo-Sánchez<sup>1,2</sup>, R.S. Lieberman<sup>1</sup>, C. Jacobi<sup>4</sup>, T. Moffat-Griffin<sup>5</sup>, N.J Mitchell<sup>5,6</sup>, N. Cobbett<sup>5</sup>, P.P.Batista<sup>7</sup>, V.F. Andrioli<sup>7,8</sup>, R.A. Buriti<sup>9</sup>, D.J. Murphy<sup>10</sup>, J. Kero<sup>11</sup>, N. Gulbrandsen<sup>12</sup>, M. Tsutsumi<sup>13,14</sup>, A. Kozlovsky<sup>15</sup>, M. Lester<sup>16</sup>, J.-H. Kim<sup>17</sup>, C. Lee<sup>17</sup>, A. Liu<sup>18</sup>, B. Fuller<sup>19</sup>, D. O’Connor<sup>19</sup>, S.E. Palo<sup>20</sup>, M.J. Taylor<sup>21</sup>, J.Marino<sup>22</sup>, and N. Rainville<sup>20</sup>.</p> <p> </p> <p>1 ITM Physics Laboratory, NASA Goddard Space Flight Center, Greenbelt MD, U.S.A.</p> <p>2 Department of Physics, Catholic University of America, DC, U.S.A.</p> <p>3 University Bern, Institute of Applied Physics, Microwave Physics, Bern, Switzerland</p> <p>4 Institute for Meteorology, Leipzig University, Germany</p> <p>5 British Antarctic Survey, Cambridge, U.K.</p> <p>6 University of Bath, Bath, U.K.</p> <p>7 National Institute for Space Research (INPE), São José dos Campos, SP, Brazil</p> <p>8 China-Brazil Joint Laboratory for Space Weather, NSSC/INPE, São José dos Campos, SP, Brazil</p> <p>9 Department of Physics, Federal University of Campina Grande, Campina Grande, PB, Brazil</p> <p>10 Australian Antarctic Division, Kingston, TAS, Australia</p> <p>11 Swedish Institute of Space Physics (IRF), Kiruna, Sweden</p> <p>12 Tromsø Geophysical Observatory, UiT - The Arctic University of Norway, Tromsø, Norway</p> <p>13 National Institute of Polar Research, Tachikawa, Japan</p> <p>14 The Graduate University for Advanced Studies (SOKENDAI), Tokyo, Japan</p> <p>15 Sodankylä Geophysical Observatory, University of Oulu, Finland</p> <p>16 Department of Physics and Astronomy, University of Leicester, Leicester, U.K.</p> <p>17 Division of Atmospheric Sciences, Korea Polar Research Institute, Incheon, S. Korea</p> <p>18 Center for Space and Atmospheric Research and Department of Physical Sciences, Embry-Riddle Aeronautical University, Daytona Beach, Florida, U.S.A.</p> <p>19 Genesis Software, Pty Ltd., Adelaide, SA, Australia</p> <p>20 Colorado Center for Astrodynamics Research (CCAR), Ann and H.J. Smead Aerospace Engineering Sciences, College of Engineering and Applied Sciences, University of Colorado Boulder, Boulder, CO, U.S.A.</p> <p>21 Department of Physics, Utah State University, Logan, UT, U.S.A</p> <p>22 University of Colorado at Boulder, Boulder, CO, U.S.A</p> <p> </p> <p> </p> <p>The datasets below are titled according to the figure in which they are used (e.g. "Fig3" for Figure 3, "Fig4" for Figure 4).<br>All uploaded datasets comprised of ASCII files.<br><br>Dataset descriptions:</p> <ul> <li>Figure 3 datasets (<strong>18 files in total</strong>): Each of the 18 different files corresponds to a different meteor radar station (SVA, TRO, KIR, SOD, COL, BLO, CAR, ASI, LEA, CPa, SMa, CON, TdF, KEP, KSS, ROT, DAV, MCM). Within each file, the data comprise of peak meteor altitudes (km) as a function of local time (24) and day-of-year (DOY). </li> <li>Figure 4 datasets (<strong>18 files in total</strong>): As above, but the data now represent the weighted elevation angle in degrees.</li> <li>Figure 5 datasets (<strong>24 files in total</strong>): These data can be used to plot the residual seasonal variation in peak altitude for each of the 18 locations, organized by geographic clusters. There are 24 different Figure 5 datasets, with each including the normalized residual seasonal variation in peak altitude (km) for stations within one of six different geographic clusters (Nordic high-latitude, Northern mid-latitude, Near-equatorial, Southern low/mid-latitude, Southern Andes, Mainland Antarctica) for each local time (00:00 LT, 06:00 LT, 12:00 LT, or 18:00 LT). Each file includes the data for all stations within that given cluster (i.e., "Fig5__Mainland_Antarctica__06LT__Dawkins_et_al_2024.tex" includes data for the Mainland Antarctica cluster (both DAV and MCM) for 06:00 LT), as a function of day-of-year (365) and normalized altitue (km).</li> <li>Figure 6 datasets (<strong>4 files in total</strong>): These data represent the mean absolute deviation (MAD, km) of each of the different geographic clusters as function of DOY (365) for four different local times (00:00 LT, 06:00 LT, 12:00 LT, and<br>18:00 LT).</li> <li>Figure 7 datasets (<strong>14 files in total</strong>): These files present the kinetic gravity wave energy (KGWE) as a function of day-of-year and altitude (km). 12 of the files correspond to one of the following locations: SVA, TRO, KIR, SOD, COL, BLO, CON (ALO only), TdF, KEP, KSS, ROT or DAV. There are two additional files ("Fig7__KGWE__time__Dawkins_et_al_2024.txt" and "Fig7__KGWE__altitude__Dawkins_et_al_2024.txt") which include the time (day-of-year) and altitudes (km) used.</li> <li>Figure 8 datasets (<strong>2 files in total</strong>): These two files ("Fig8__CABMOD_profiles__data__Dawkins_et_al_2024.txt" and "Fig8__CABMOD_profiles__altitude__Dawkins_et_al_2024.txt") include the data necessary to reproduce all panels in Figure 8 which shows the vertical mass profiles from CABMOD for a meteoric particle with a fixed initial mass (178 μg) and velocity (31 kms−1), at a latitude of 60 deg S. The dataset (mass, μg) corresponds to 8 different month and entry angles (in order: March, June, September, December for particle entry angles of 5 deg and 25 deg, respectively) and 201 altitudes (km).</li> <li>Figure 9 datasets (<strong>8 files in total</strong>): These data represent the simulated and observed peak altitudes (km) as a function of day-of-year and LT for each of the four Southern Andes meteor radar station locations (TdF, KEP, KSS, ROT).</li> </ul>
Plasma Parameters From Wind Mission Radio Observations Using Quasi-Thermal Noise Spectroscopy
<p>Database of the high-resolution Velocity Diftribution Function (VDF) moments from Wind Thermal Noise Receiver (TNR) using Quasi-Thermal Noise (QTN) Spectroscopy</p>
Fig. 2 in Observations ofApparent LoricaVariability inSalpingacantha (Ciliophora: Tintinnida) in the Northern Pacific and Arctic Oceans
Fig. 2. Varieties of Salpingacantha from a 2016 sample in the Chuk- chi Sea (2016 St 29). In the sample no typical Salpingella acuminata were found. In the conspectus of Kofoid and Campbell (1929) the form "a" most closely resembles S. ampla, "b" S. unguiculata, "c" S. simplex, "d" S. perca, and "e" S. crenulata. Note that form "c" if rotated 45° could easily be mistaken for Salpingella acuminata.
Fig. 1 in Observations ofApparent LoricaVariability inSalpingacantha (Ciliophora: Tintinnida) in the Northern Pacific and Arctic Oceans
Fig. 1. Varieties of Salpingacantha from a 2015 sample in the Chuk- chi Sea (2015 St 5). In the sample, typical Salpingella acuminata ("a") were dominant with 70 cells found for the 15 Salpingacantha cells encountered. The "b" most closely corresponds with S. crenulata, "c" and "d" with S. perca, "e" with S. unguiculata and "f" with S. ampla. Note that form "e", if rotated 45°, could easily be mistaken for Salpingella acuminata.
Fig. 3 in Observations ofApparent LoricaVariability inSalpingacantha (Ciliophora: Tintinnida) in the Northern Pacific and Arctic Oceans
Fig. 3. The illustrations of Salpingacantha species from Kofoid and Campbell 1929 arranged as the evolutionary series given in Kofoid & Campbell 1939 in which S. perca "presents the earliest phase in evolution of toothed oral margin": a. S. perca, b. S. crenulata, c. S. exilis, d. S. simplex, e. S. unguiculata, f. S. ampla, and g. S. undata. Note that S. perca, S. exilis, and S. unguiculata are depicted with a diaphragm apparatus similar to those of Salpingella (Agatha 2010).
Fig. 2 in New observations of Papulifères, putative ciliate cysts, from the plankton of the Chukchi Sea (Western Arctic Ocean) in August of 2023
Fig. 2. New forms of Papulifères found in samples from the Chukchi Sea region taken in August 2023. Forms A–D are new spindle-shaped Fusopsis forms, and Forms E–H are new spherical or oblong-shaped Sphaeropsis forms. Morphology notes and stations in which each were found along with the nominal concentrations found in the samples are given in Table 2.
Fig. 1 in New observations of Papulifères, putative ciliate cysts, from the plankton of the Chukchi Sea (Western Arctic Ocean) in August of 2023
Fig. 1. Map of the Western Arctic Ocean showing the 36 station locations sampled using a 20 µm mesh plankton net in the Chukchi Sea region during August of 2023. Note that station locations yielding samples in which Papulifère, putative ciliate cysts forms, were found (putative cyst stations) were located throughout the region sampled. Detailed station characteristics are given in Table 1.
Fig. 5 in Jenynsia luxata, a new species from Northwestern Argentina, with additional observations of J. maculata Regan and phylogeny of the genus (Cyprinodontiformes: Anablepidae)
Fig. 5. Topologies from most equally parsimonious trees and relative Bremer support/GC values under (a) equal weights (strict consensus of 12 trees), and (b) implied weighting (strict consensus of two trees), with concavities K = 4 to 20 (with supports measured under K = 8). Unsupported nodes are shown as collapsed. The relationships of genera of the family are consistent with those proposed in previous studies, therefore species of Anableps and Oxyzygonectes are not shown.
Fig. 1 in Jenynsia luxata, a new species from Northwestern Argentina, with additional observations of J. maculata Regan and phylogeny of the genus (Cyprinodontiformes: Anablepidae)
Fig. 1. Jenynsia luxata. Above: holotype CI-FML: 5464, male, 24.4 mm SL, Tucumán, Burruyacu city, a small unnamed stream, río Tajamar basin, Argentina; below: paratype CI-FML 5466, female, 34.8 mm SL, Santiago del Estero, Pellegrini, small flooded pools at Ruta Provincial 4, not connected to but near to río Urueña basin, Argentina.
Fig. 4 in Jenynsia luxata, a new species from Northwestern Argentina, with additional observations of J. maculata Regan and phylogeny of the genus (Cyprinodontiformes: Anablepidae)
Fig. 4. Hydrographic map of South America showing the currently known distribution of Jenynsia luxata. The area delimited by the rectangle is enlarged at right, where the type locality is indicated by an open dot and an additional locality is indicated by a black dot. The small black dot indicates the capital of Tucumán.
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.