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Fig. 6 in The contribution of the Middle Triassic fossil assemblage of Monte San Giorgio to insect evolution.
Fig. 6 | Abundance of fossils per insect lineage found at VM12 site and location of the main Middle Triassic insect deposits. A Time-calibrated phylogenetic tree of insect evolutionary relationships from Montagna et al. (5) where the abundance of insects collected at VM12 per lineage, expressed as the natural logarithm of the number of individuals, is reported; (B). Location of main Middle Triassic fossil insect deposits as in Zheng et al. (11) with the addition of Monte San Giorgio. (1) Tongchuan, China (Ladinian); (2) Karamay, China (Carnian); (3) Madygen, Kyrgyzstan (Ladinian-Carnian); (4) Vosges, France (early Anisian); (5) Solite, USA (late Carnian); (6) Ipswich, Australia (Carnian); (7) Brookvale, Australia (Anisian); (8) Molteno, South Africa (Carnian); (MSG) Monte San Giorgio, Switzerland (Ladinian). Giulia Magoga drew insect silhouettes.
Fig. 5 in The contribution of the Middle Triassic fossil assemblage of Monte San Giorgio to insect evolution.
Fig. 5 | Diptera preserving peculiar features. A MCSN 8696, adult preserving the hexagonal facets of compound eyes and three round-shaped bodies at the end of the abdomen. B MCSN 8696, enlargement of the hexagonal facets of compound eyes. C MCSN 8696, enlargement of the three round-shaped bodies present externally on the abdomen, with visible ornamentations. D MCSN 8697, three round-shaped bodies present externally on the abdomen, with visible ornamentations. Scale bars: A, 500 µm; B, C, 200 µm; D, 100 µm.
Fig. 3 in The contribution of the Middle Triassic fossil assemblage of Monte San Giorgio to insect evolution.
Fig. 3 | Representatives of holometabolous insects. A Magnicapitixyela dilettae (Hymenoptera, Xyelidae), MCSN 8678. B Merithone laetitiae (Neuropterida, †Permithonidae), MCSN 8679 (19). Coleoptera: MCSN 8691, Archostemata (C); MCSN 8692, Archostemata (D); MCSN 8681, Adephaga (E); MCSN 8693, Polyphaga (F). Scale bars: A–D, 1 mm; E, F 200 µm.
Fig. 1 in The contribution of the Middle Triassic fossil assemblage of Monte San Giorgio to insect evolution.
Fig. 1 | Location of the Monte San Giorgio (Italy-Switzerland) UNESCO World Heritage and stratigraphic section of the Middle Triassic sediments. A Simplified map of the Monte San Giorgio showing the Middle Triassic carbonate succession and the location of Val Mara (indicated by a star) where VM 12 site occurs. B Stratigraphic section of the Middle Triassic sediments in Monte San Giorgio, the position of VM 12 strata where the insect fossils were collected is indicated by the black arrow.
Fig. 2 in The contribution of the Middle Triassic fossil assemblage of Monte San Giorgio to insect evolution.
Fig. 2 | Representatives of ametabolous and hemimetabolous insects. G Hemiptera, MCSN 8677. H Incerta sedis, MCSN 8689, possibly Hemiptera of the A Dasyleptus triassicus (†Monura), MCSN 8688. B Dasyleptus triassicus (†Monura), superfamily Protopsyllidioidea. I Psocodea, MCSN 8690. Scale bars: A, C, 1 mm; MCSN 8687. C Odonatan naiad, MCSN 8666. D Blattodean, MCSN 8667. B, E, I, 500 µm; D, 5 mm; F–H, 200 µm. E Enlargement of the external ootheca of MCSN 8667. F Thysanoptera, MCSN 8668.
Fig. 4 in The contribution of the Middle Triassic fossil assemblage of Monte San Giorgio to insect evolution.
Fig. 4 | Representatives of holometabolous insects (Antliophora). A Mecoptera, MCSN 8699. Diptera: MCSN 8694, adult (B); MCSN 8695, adult male (C); MCSN 8698, pupa (D). Scale bars: A-B, 500 µm; C, D, 1 mm.
Linked collectors and determiners for: Contribution to the knowledge on the genus Barsine Walker, 1854 from mainland China and Indochina, with description of a new species (Lepidoptera, Erebidae, Arctiinae, Lithosiini).
Natural history specimen data linked to collectors and determiners held within, "Contribution to the knowledge on the genus Barsine Walker, 1854 from mainland China and Indochina, with description of a new species (Lepidoptera, Erebidae, Arctiinae, Lithosiini)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="http://bionomia.net/dataset/a7bd64b9-5e3b-413f-afba-182b6918ea52">https://bionomia.net/dataset/a7bd64b9-5e3b-413f-afba-182b6918ea52</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a7bd64b9-5e3b-413f-afba-182b6918ea52">https://gbif.org/dataset/a7bd64b9-5e3b-413f-afba-182b6918ea52</a>. Formatted as a Frictionless Data package.
Figure 1. Professor M in Maria Guiomar Nates-Parra: Biographical sketch and summary of contributions to the melittological knowledge of Colombia
Figure 1. Professor M. Guiomar Nates-Parra in 2006 showing a collection of orchid bees in her lab (Photograph courtesy of M.L. Bueno).
Supplementary materials for the manuscript "Revisiting the Contributions of Surface Sensible and Latent Heat Fluxes to Tropical Cyclones"
<p>A subset of outputs of the STD, CTL, SH+LH-_OUT and SH-LH+_OUT experiments in "Revisiting the Contributions of Surface Sensible and Latent Heat Fluxes to Tropical Cyclones".</p>
Fig. 2 in The spermathecal duct of earwig Doru luteipes (Dermaptera: Forficulidae) contributes to spermatozoa survival
Fig. 2. Light micrographs of the spermatheca of Doru luteipes. (A) Section of the spermathecal reservoir containing epithelial cells (ec). (B) Section of the spermathecal reservoir with epithelial cells (ec) positive for P.A.S. (arrow head). (C) Spermathecal reservoir showing epithelial cells (ec) and luminal content (lu) positive for proteins. (D) Section of the spermathecal duct showing epithelial cells (ec) and class III secretory cells (sc) with intracellular canaliculi (ic), which open in pores (p) through the cuticle (ct). (E) Secretory cells (sc) of the duct with P.A.S.-positive regions (arrow heads). (F) Cells of the spermathecal duct positive for proteins. lu: lumen; ea: end apparatus; spt: spermatozoa; m: muscular fiber.
Fig. 1 in The spermathecal duct of earwig Doru luteipes (Dermaptera: Forficulidae) contributes to spermatozoa survival
Fig. 1. Anatomy of the spermatheca in Doru luteipes. (A) Light micrograph showing the spermathecal reservoir (b) and duct (d). (B) Scanning electron micrograph of the spermathecal reservoir (b) and duct (d). (C) Transitional region between the reservoir (b) and the duct (d) showing longitudinal muscles (m). (D) Median portion of the spermathecal duct with longitudinal muscles (m). (E) Distal region of the spermathecal duct with circular muscles (m).
Fig. 1. Example pollinator contribution value for 3 in Importance of insect pollinators for Florida agriculture: a systematic review of the literature
Fig. 1. Example pollinator contribution value for 3 hypothetical crops including banana (no value), tomatoes (moderate value), and watermelons (high value).
Data for "Bulk and fracture process zone contribution to the rate-dependent adhesion amplification in viscoelastic broad-band materials"
<p>This dataset contains all the data generated for the publication</p> <p>[1] A. Maghami, Q. Wang, M. Tricarico et al., Bulk and fracture process zone contribution to the rate-dependent adhesion amplification in viscoelastic broad-band materials. Journal of the Mechanics and Physics of Solids (2024), doi:<br>https://doi.org/10.1016/j.jmps.2024.105844.</p> <p><br>The provided data are those which appear in the figures of Ref. [1]. Data are stored using informative named structures in a ".mat" file. The data are easily accessible through the Commercial Software MATLAB (© 1994-2023 The MathWorks, Inc.) or by using the free software GNU Octave. An exemplary code for loading and plotting the data contained in "data_Sphere_Viscoelastic_BroadBand.mat" is the following:</p> <p>%%%%%%%%%%%%%</p> <div> <div> <div> <div>clc</div> <div>clearvars</div> <div> </div> <div>close all</div> <div> </div> <div> </div> <div>% Create a new figure</div> <div>load('data_Sphere_Viscoelastic_BroadBand.mat');</div> <div> </div> <div> </div> <div>figure</div> <div> </div> <div>% Choose one of the following names:</div> <div>% Fig_3_a, Fig_3_b, Fig_3_c,</div> <div>% Fig_4, Fig_5_a, Fig_5_b, Fig_5_b_inset,</div> <div>% Fig_6, Fig_6_inset, Fig_7, Fig_7_inset,</div> <div>% Fig_8_a, Fig_8_b, Fig_10_a, Fig_10_b</div> <div> </div> <div>name=Fig_3_a;</div> <div>% Note: some plots in the manuscript are in log space.</div> <div> </div> <div>% Plot the data from the structure</div> <div> </div> <div> </div> <div>for i = 1:numel(name.x) hold on</div> <div> </div> <div>x_cell = name.x(i);</div> <div>y_cell = name.y(i);</div> <div>x = cell2mat(x_cell);</div> <div>y = cell2mat(y_cell);</div> <div> </div> <div>plot(x, y);</div> <div>end</div> <div> </div> <div> </div> <div> </div> </div> %%%%%%%%%%%%%</div> </div> <p>The code can be easily adapted for plotting the curves of all the figures contained in Ref. [1]. </p>
Figure 2 in Contribution to knowledge of the oribatid mite genus Idiozetes (Acari, Oribatida, Idiozetidae), with description of a new sexually dimorphic species from Vietnam
Figure 2 Idiozetes schusteri sp. n., adult, male (A, B) and female (C) (gnathosoma and legs not shown): A — dorsal view of notogaster; B — right lateral view of notogaster; C — right lateral view. Scale bars 50 μm.
Figure 1 in Contribution to knowledge of the oribatid mite genus Idiozetes (Acari, Oribatida, Idiozetidae), with description of a new sexually dimorphic species from Vietnam
Figure 1 Idiozetes schusteri sp. n., adult, female (gnathosoma and legs not shown): A — dorsal view; B — ventral view. Scale bar 50 μm.
Figuras 2-6. 2 in Contribution to the knowledge of Copeocoris truncaticornis (Stål) (Heteroptera: Pentatomidae)
Figuras 2-6. 2. Copeocoris truncaticornis (Stål), specimen with cephalic atrophy. 3. Copeocoris truncaticornis (Stål), prosternum and mesosternum. PS = prosternal sulcus, MS = mesosternal sulcus, T = prosternal tubercle. 4. Hillieria acuminata Distant, 1910 (Pentatominae: Aeptini), prosternum and mesosternum. 5. Aeptus singularis Dallas, 1851 (Pentatominae: Aeptini), prosternum and mesosternum. 6. C. truncaticornis, basiabdominal tubercle. Scale: 1 mm.
Supporting data and code for: Myzus persicae resistance to neonicotinoids - unravelling the contribution of different mechanisms to phenotype
<p>This is the first release of the final data and code for the article accepted for publication in <em>Pest Management Science</em> journal. It contains the necessary scripts to produce most of the analyses and figures of the manuscript. All the necessary data can be found in the 'data' folder.</p>
FINANCIAL INSIGHTS INTO HUMAN CAPITAL: ASSESSING EMPLOYEE CONTRIBUTION FROM HR-FINANCE PERSPECTIVE
<p>International Research Journal of <br>Management Sociology & Humanities</p> <p>ISSN 2277 – 9809 (online)<br>ISSN 2348 - 9359 (Print)</p> <p>Volume 15, Issue 9 , page 126-136 </p> <p>Name of the research paper : FINANCIAL INSIGHTS INTO HUMAN CAPITAL: ASSESSING EMPLOYEE CONTRIBUTION FROM HR-FINANCE PERSPECTIVE</p> <p>Authors <br>Suvendu Narayan Roy<br>Director, Knowgen Education Services Private Limited<br>Researcher, Faculty of Finance & Management<br>Orcid id : https://orcid.org/0000-0002-2801-0740<br>Soham Roy<br>Researcher & Partner, E & O Learnet and Learnet Manpower Solutions<br>Orcid id : https://orcid.org/0000-0002-3127-608</p>
Datasets from "Auroral Energy Deposition and Conductance During the 2013 St. Patrick's Day Storm: Meso-Scale Contributions" by Gabrielse et al.
<p><strong>1. README File for netCDF Data to be published alongside “Mesoscale Contributions to Auroral Energy Deposition and Conductance During the 2013 St. Patrick’s Day Storm” by Christine Gabrielse et al. in the Journal of Geophysical Research.</strong></p> <p>The data to be stored on Zenodo (<a href="https://zenodo.org/">https://zenodo.org/</a>) are in a netCDF format.</p> <p>This README applies to the following files:</p> <p> thg_ej_all-sky-imager_20130317050000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317060000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317070000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317080000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317090000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317100000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317110000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317120000_v01.nc</p> <p> thg_ej_all-sky-imager_20130317130000_v01.nc</p> <p> </p> <p>The following are attributes published within the netCDF’s metadata:</p> <p><strong>SUMMARY:</strong></p> <p>FILENAME:</p> <p> thg_ej_all-sky-imager_20130317050000_v01.nc</p> <p> </p> <p>PROJECT:</p> <p> STP>Solar-Terrestrial Physics</p> <p> </p> <p>SOURCE_NAME:</p> <p> THG>THEMIS (Time History of Events and Macroscale Interactions during</p> <p> Substorms) Ground-Based</p> <p> </p> <p>DISCIPLINE:</p> <p> Space Physics>Ionospheric Science</p> <p> Space Physics>Magnetospheric Science</p> <p> </p> <p>DATA_TYPE:</p> <p> EJ>Earth Camera Images, processed</p> <p> </p> <p>DESCRIPTOR:</p> <p> All-Sky-Imager</p> <p> </p> <p>FILE_NAMING_CONVENTION:</p> <p> source_datatype_descriptor_yyyyMMddHHmmss</p> <p> </p> <p>DATA_VERSION:</p> <p> 01</p> <p> </p> <p>PI_NAME:</p> <p> Christine Gabrielse</p> <p> </p> <p>PI_AFFILIATION:</p> <p> The Aerospace Corporation</p> <p> </p> <p>TEXT:</p> <p> Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS</p> <p> white light all-sky-imagers. See Gabrielse et al. (2021, Frontiers) and</p> <p> Gabrielse et al. (2024, JGR) for derivation methodology.</p> <p> </p> <p>INSTRUMENT_TYPE:</p> <p> Ground-Based Imagers</p> <p> </p> <p>MISSION_GROUP:</p> <p> Ground-Based Investigations</p> <p> </p> <p>LOGICAL_SOURCE:</p> <p> thg_ej_all-sky-imager</p> <p> </p> <p>LOGICAL_FILE_ID:</p> <p> thg_ej_all-sky-imager_00000000000000_v01</p> <p> </p> <p>LOGICAL_SOURCE_DESCRIPTION:</p> <p> Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS</p> <p> white light all-sky-imagers.</p> <p> </p> <p>TIME_RESOLUTION:</p> <p> 3s</p> <p> </p> <p>RULES_OF_USE:</p> <p> Invitation to co-authorship for use of this data is required. It is best to</p> <p> reach out to Dr. Gabrielse early in the project for guidance.</p> <p> </p> <p>GENERATED_BY:</p> <p> Christine Gabrielse</p> <p> </p> <p>ACKNOWLEDGEMENT:</p> <p> The work effort for this project was gratefully funded by NASA grants</p> <p> 80NSSC20K0725, 80GSFC22CA011, NAS5-02099, 80NSSC21K1552, AFOSR Grant</p> <p> FA9559-16-1-0364</p> <p> </p> <p><strong>GLOBAL ATTRIBUTES:</strong></p> <p>PROJECT:</p> <p> STP>Solar-Terrestrial Physics</p> <p>SOURCE_NAME:</p> <p> THG>THEMIS (Time History of Events and Macroscale Interactions during</p> <p> Substorms) Ground-Based</p> <p>DISCIPLINE:</p> <p> Space Physics>Ionospheric Science</p> <p> Space Physics>Magnetospheric Science</p> <p>DATA_TYPE:</p> <p> EJ>Earth Camera Images, processed</p> <p>DESCRIPTOR:</p> <p> All-Sky-Imager</p> <p>FILE_NAMING_CONVENTION:</p> <p> source_datatype_descriptor_yyyyMMddHHmmss</p> <p>DATA_VERSION:</p> <p> 01</p> <p>PI_NAME:</p> <p> Christine Gabrielse</p> <p>PI_AFFILIATION:</p> <p> The Aerospace Corporation</p> <p>TEXT:</p> <p> Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS</p> <p> white light all-sky-imagers. See Gabrielse et al. (2021, Frontiers) and</p> <p> Gabrielse et al. (2024, JGR) for derivation methodology.</p> <p>INSTRUMENT_TYPE:</p> <p> Ground-Based Imagers</p> <p>MISSION_GROUP:</p> <p> Ground-Based Investigations</p> <p>LOGICAL_SOURCE:</p> <p> thg_ej_all-sky-imager</p> <p>LOGICAL_FILE_ID:</p> <p> thg_ej_all-sky-imager_00000000000000_v01</p> <p>LOGICAL_SOURCE_DESCRIPTION:</p> <p> Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS</p> <p> white light all-sky-imagers.</p> <p>TIME_RESOLUTION:</p> <p> 3s</p> <p>RULES_OF_USE:</p> <p> Invitation to co-authorship for use of this data is required. It is best to</p> <p> reach out to Dr. Gabrielse early in the project for guidance.</p> <p>GENERATED_BY:</p> <p> Christine Gabrielse</p> <p>ACKNOWLEDGEMENT:</p> <p> The work effort for this project was gratefully funded by NASA grants</p> <p> 80NSSC20K0725, 80GSFC22CA011, NAS5-02099, 80NSSC21K1552, AFOSR Grant</p> <p> FA9559-16-1-0364</p> <p> </p> <p><strong>DIMENSIONS:</strong></p> <p>EPOCH:</p> <p> 1200</p> <p>LATITUDE:</p> <p> 400</p> <p>LONGITUDE:</p> <p> 400</p> <p> </p> <p><strong>VARIABLES:</strong></p> <p><strong>EPOCH:</strong></p> <p>CAT_DESC:</p> <p> Time in seconds since 1970-01-01 00:00:00</p> <p>TIME_SCALE:</p> <p> UTC</p> <p>TIME_BASE:</p> <p> 1970 (POSIX)</p> <p>FIELDNAM:</p> <p> Time in seconds since 1970-01-01 00:00:00</p> <p>FILLVAL:</p> <p> LONG = -2147483648</p> <p>FORMAT:</p> <p> I10</p> <p>UNITS:</p> <p> S</p> <p>VALIDMIN:</p> <p> LONG = 1363496400</p> <p>VALIDMAX:</p> <p> LONG = 1363528800</p> <p>VAR_TYPE:</p> <p> support_data</p> <p><strong>LATITUDE</strong>:</p> <p>_FILLVALUE:</p> <p> FLOAT = NaN</p> <p>CAT_DESC:</p> <p> Geodetic latitude</p> <p>FIELDNAM:</p> <p> Latitude</p> <p>FORMAT:</p> <p> F4.1</p> <p>FILLVAL:</p> <p> DOUBLE = -1.0000000e+31</p> <p>UNITS:</p> <p> deg</p> <p>VALIDMIN:</p> <p> DOUBLE = 45.000000</p> <p>VALIDMAX:</p> <p> DOUBLE = 84.900000</p> <p>VAR_TYPE:</p> <p> support_data</p> <p><strong>LONGITUDE</strong>:</p> <p>_FILLVALUE:</p> <p> FLOAT = NaN</p> <p>CAT_DESC:</p> <p> Geodetic longitude</p> <p>FIELDNAM:</p> <p> Longitude</p> <p>FORMAT:</p> <p> F5.1</p> <p>FILLVAL:</p> <p> DOUBLE = -1.0000000e+31</p> <p>UNITS:</p> <p> Deg</p> <p>VALIDMIN:</p> <p> DOUBLE = 180.00000</p> <p>VALIDMAX:</p> <p> DOUBLE = 339.60000</p> <p>VAR_TYPE:</p> <p> support_data</p> <p><strong>CONDUCTANCE:</strong></p> <p>_FILLVALUE:</p> <p> DOUBLE = NaN</p> <p>CAT_DESC:</p> <p> Hall conductance in a 2D grid organized by geographic latitude and longitude,</p> <p> units of mho</p> <p>DEPEND_0:</p> <p> Epoch</p> <p>DEPEND_1:</p> <p> Latitude</p> <p>DEPEND_2:</p> <p> Longitude</p> <p>DISPLAY_TYPE`:</p> <p> Image</p> <p>FIELDNAM:</p> <p> Hall conductance</p> <p>FILLVAL:</p> <p> DOUBLE = -1.0000000e+31</p> <p>FORMAT:</p> <p> F8.6</p> <p>LABLAXIS:</p> <p> Hall conductance</p> <p>UNITS:</p> <p> Mho</p> <p>VALIDMIN:</p> <p> DOUBLE = 0.00043800000</p> <p>VALIDMAX:</p> <p> DOUBLE = 88.000000</p> <p>VAR_TYPE:</p> <p> Data</p> <p><strong>Energy flux:</strong></p> <p>_FILLVALUE:</p> <p> FLOAT = NaN</p> <p>CAT_DESC:</p> <p> Precipitated energy flux in a 2D grid organized by geographic latitude and</p> <p> longitude, units of ergs/cm^2/s</p> <p>DEPEND_0:</p> <p> Epoch</p> <p>DEPEND_1:</p> <p> Latitude</p> <p>DEPEND_2:</p> <p> Longitude</p> <p>DISPLAY_TYPE`:</p> <p> Image</p> <p>FIELDNAM:</p> <p> Energy Flux (ergs/cm^2/s)</p> <p>FILLVAL:</p> <p> DOUBLE = -1.0000000e+31</p> <p>FORMAT:</p> <p> F9.4</p> <p>LABLAXIS:</p> <p> energy flux</p> <p>UNITS:</p> <p> ergs/cm^2/s</p> <p>VALIDMIN:</p> <p> DOUBLE = 0.010000000</p> <p>VALIDMAX:</p> <p> DOUBLE = 1100.0000</p> <p>VAR_TYPE:</p> <p> Data</p> <p><strong>ENERGY:</strong></p> <p>_FILLVALUE:</p> <p> FLOAT = NaN</p> <p>CAT_DESC:</p> <p> Mean energy of the precipitated population in a 2D grid organized by geographic</p> <p> latitude and longitude, units of keV</p> <p>DEPEND_0:</p> <p> Epoch</p> <p>DEPEND_1:</p> <p> Latitude</p> <p>DEPEND_2:</p> <p> Longitude</p> <p>DISPLAY_TYPE`:</p> <p> Image</p> <p>FIELDNAM:</p> <p> Energy (keV)</p> <p>FILLVAL:</p> <p> DOUBLE = -1.0000000e+31</p> <p>FORMAT:</p> <p> F6.3</p> <p>LABLAXIS:</p> <p> Energy</p> <p>UNITS:</p> <p> keV</p> <p>VALIDMIN:</p> <p> DOUBLE = 0.010000000</p> <p>VALIDMAX:</p> <p> DOUBLE = 22.000000</p> <p>VAR_TYPE:</p> <p> Data</p> <p> </p> <p>Examples of the data are as follows:</p> <p><strong>EPOCH:</strong></p> <p>data.<em>epoch</em>.<em>data</em>[<strong>0</strong>] = 1363496400</p> <p> </p> <p>This data is presented as number of seconds since January 1, 1970 in UT. The example above converts to 2013-03-17/05:00 UT. There are 1200 time values stored in each file.</p> <p> </p> <p><strong>LATITUDE:</strong></p> <p>data.<em>latitude</em>.<em>data</em>[0] = 45.0000</p> <p> </p> <p>This data is the geographic latitude in degrees of the 400x400 grid of data points. There are 400 latitude values stored in each file.</p> <p> </p> <p><strong>LONGITUDE:</strong></p> <p>data.<em>LONGITUDE</em>.<em>data</em>[<strong>0</strong>] = 180.000</p> <p> </p> <p>This data is the geographic longitude in degrees of the 400x400 grid of data points. There are 400 longitude values stored in each file.</p> <p> </p> <p><strong>CONDUCTANCE</strong>:</p> <p>data.<em>conductance</em>.<em>data</em>[<strong>0</strong>] = -1.0000000e+31</p> <p> </p> <p>This data is the Hall conductance in mho measured at 45 deg latitude, 180 deg longitude. The value in this example indicates that no conductance was measured here. A valid value would be something in the range of 0.00043800000 to 88 mho. There are 1200x400x400 conductance values stored in each file.</p> <p> </p> <p><strong>ENERGY FLUX:</strong></p> <p>data.<em>eflux</em>.<em>data</em>[<strong>0</strong>] = -1.00000e+31</p> <p> </p> <p>This data is the energy flux in ergs/cm^2/s measured at 45 deg latitude, 180 deg longitude. The value in this example indicates that no energy flux was measured here. A valid value would be something in the range of 0.01 to 1100.0000 ergs/cm^2/s. There are 1200x400x400 energy flux values stored in each file.</p> <p> </p> <p><strong>ENERGY:</strong></p> <p>data.<em>energy</em>.<em>data</em>[<strong>0</strong>] = -1.00000e+31</p> <p> </p> <p>This data is the energy in keV measured at 45 deg latitude, 180 deg longitude. The value in this example indicates that no energy was measured here. A valid value would be something in the range of 0.01 to 22 keV. There are 1200x400x400 energy values stored in each file.</p> <p> </p> <p><strong>2. README for text file Data to be published alongside “Mesoscale Contributions to Auroral Energy Deposition and Conductance During the 2013 St. Patrick’s Day Storm” by Christine Gabrielse et al. in the Journal of Geophysical Research.</strong></p> <p>This README applies to the following files:</p> <p> march172013_fortyukon_photometer_products.dat</p> <p> march172013_pokerflat_photometer_products.dat</p> <p>Header information in the files describe the contents. </p> <p>These are the photometer derived data taken on March 17, 2023. They include the time [UT], energy flux (Q) [ergs/cm^2/s], average energy (Eavg) [keV], and oxygen scale factor (fo).</p>
Linked collectors and determiners for: Contributions to the knowledge of Elanela: Elanela jordi sp. nov., from Amazonas, Brazil (Hemiptera: Heteroptera: Pentatomidae).
Natural history specimen data linked to collectors and determiners held within, "Contributions to the knowledge of Elanela: Elanela jordi sp. nov., from Amazonas, Brazil (Hemiptera: Heteroptera: Pentatomidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/14c5653c-a351-4e02-aeed-a88be4487b71">https://bionomia.net/dataset/14c5653c-a351-4e02-aeed-a88be4487b71</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/14c5653c-a351-4e02-aeed-a88be4487b71">https://gbif.org/dataset/14c5653c-a351-4e02-aeed-a88be4487b71</a>. Formatted as a Frictionless Data package.
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.