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Text-fig. 10. Langtonia bisulcata REID et CHANDLER. a, b, e–g: Holotype, V. 22984, from micro-CT data. a: Dorsiventral view surface rendering. b: Dorsiventral view translucent volume rendering showing outline of locule cast. c: Equatorial transverse fracture showing paired dorsal infolds and locules with shape of a ε in cross section, reflected light, V. 22993. d: Digital transverse section from micro-CT data, of fruit with two well developed ε-shaped locules, V. 22985. e–g: Successive digital transverse sections with one well developed ε-shaped locule and infolds of the abortive locule visible in (g) (arrows). h–j: Physical transverse thin sections of specimen from middle Eocene Clarno Formation, Oregon, USA with well-preserved mesocarp including longitudinal canals in (j) (arrows), USNM 424875; Scale bars 0.5 cm in (a, b), 2.5 mm in (c–g), 5 mm in (h), 2 mm in (i), 1 mm in (j); (a, b) share same scale bar; (c, d) share same scale bar; (e, f, g) share same scale bar. in Mastixioid Fruits (Cornales) From The Early Eocene London Clay Flora: Morphology, Anatomy And Nomenclatural Revision
Text-fig. 10. Langtonia bisulcata REID et CHANDLER. a, b, e–g: Holotype, V. 22984, from micro-CT data. a: Dorsiventral view surface rendering. b: Dorsiventral view translucent volume rendering showing outline of locule cast. c: Equatorial transverse fracture showing paired dorsal infolds and locules with shape of a ε in cross section, reflected light, V. 22993. d: Digital transverse section from micro-CT data, of fruit with two well developed ε-shaped locules, V. 22985. e–g: Successive digital transverse sections with one well developed ε-shaped locule and infolds of the abortive locule visible in (g) (arrows). h–j: Physical transverse thin sections of specimen from middle Eocene Clarno Formation, Oregon, USA with well-preserved mesocarp including longitudinal canals in (j) (arrows), USNM 424875; Scale bars 0.5 cm in (a, b), 2.5 mm in (c–g), 5 mm in (h), 2 mm in (i), 1 mm in (j); (a, b) share same scale bar; (c, d) share same scale bar; (e, f, g) share same scale bar.
Text-fig. 1. Modern vegetation proxies as delivered by the Drudge 1 and 2 tools for Parschlug. Left column results from KovarEder et al. (2021) based on the floristic spectrum published by Kovar-Eder et al. (2004). The other three columns result from three variants using the enlarged floristic spectrum herein. Differences between variants 1–3 from this study are caused by differences in assignment of some taxa and morphotypes (see Appendix 1). European vegetation formations: Formation C – Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation; Formation D – Mesophytic and hygromesophytic coniferous and mixed broad-leaved-coniferous forests; Formation F – Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation G – Thermophilous mixed deciduous broadleaved forests; Formation J – Mediterranean sclerophyllous forests and scrub; Formation K – Xerophytic coniferous forests, coniferous woodland and scrub. East Asian vegetation types: MCF China, Japan – Montane Coniferous Forests China, Honshu, Yakushima; BLDF N and NE Provinces, China – Broad-leaved Deciduous Forests of the Northern and Northeastern Provinces (China); BLDF Upper Yangtze, Honshu – Broad-leaved Deciduous Forest, Upper Yangtze Provinces, Mt. Emei, and Honshu; MMF China – Mixed Mesophytic Forest, Lower Yangtze Provinces; BLEF China, Japan – Broad-leaved Evergreen Forests, China, Japan; Meili Snow Mt. high altitude SCL and BLF, China – Meili Snow Mt., Sclerophyllous and broad-leaved forest zone (2,580-3,650 m alt.). (Designations of European vegetation formations follow Bohn et al. (2004) and Asian ones follow Kovar-Eder et al. (2021). in Floristic, Vegetation And Climate Assessment Of The Early/Middle Miocene Parschlug Flora Indicates A Distinctly Seasonal Climate
Text-fig. 1. Modern vegetation proxies as delivered by the Drudge 1 and 2 tools for Parschlug. Left column results from KovarEder et al. (2021) based on the floristic spectrum published by Kovar-Eder et al. (2004). The other three columns result from three variants using the enlarged floristic spectrum herein. Differences between variants 1–3 from this study are caused by differences in assignment of some taxa and morphotypes (see Appendix 1). European vegetation formations: Formation C – Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation; Formation D – Mesophytic and hygromesophytic coniferous and mixed broad-leaved-coniferous forests; Formation F – Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation G – Thermophilous mixed deciduous broadleaved forests; Formation J – Mediterranean sclerophyllous forests and scrub; Formation K – Xerophytic coniferous forests, coniferous woodland and scrub. East Asian vegetation types: MCF China, Japan – Montane Coniferous Forests China, Honshu, Yakushima; BLDF N and NE Provinces, China – Broad-leaved Deciduous Forests of the Northern and Northeastern Provinces (China); BLDF Upper Yangtze, Honshu – Broad-leaved Deciduous Forest, Upper Yangtze Provinces, Mt. Emei, and Honshu; MMF China – Mixed Mesophytic Forest, Lower Yangtze Provinces; BLEF China, Japan – Broad-leaved Evergreen Forests, China, Japan; Meili Snow Mt. high altitude SCL and BLF, China – Meili Snow Mt., Sclerophyllous and broad-leaved forest zone (2,580-3,650 m alt.). (Designations of European vegetation formations follow Bohn et al. (2004) and Asian ones follow Kovar-Eder et al. (2021).
Text-fig. 16. Reconstruction of herbaceous angiosperms from Bolshoy Kuvshin locality, Frentsevka Formation, early-middle Albian. a: undescribed species, spec. IBSS 320-137; b: Achaenocarpites capitellatus KRASSILOV et VOLYNETS. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 16. Reconstruction of herbaceous angiosperms from Bolshoy Kuvshin locality, Frentsevka Formation, early-middle Albian. a: undescribed species, spec. IBSS 320-137; b: Achaenocarpites capitellatus KRASSILOV et VOLYNETS.
Text-fig. 15. Reconstruction of herbaceous angiosperms from Bolshoy Kuvshin locality, Frentsevka Formation, early-middle Albian. a: Asiatifolium elegans G.SUN, SHUANG X.GUO et SHAO L.ZHENG; b: Jixia pinnatipartita SHUANG X.GUO et G.SUN. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 15. Reconstruction of herbaceous angiosperms from Bolshoy Kuvshin locality, Frentsevka Formation, early-middle Albian. a: Asiatifolium elegans G.SUN, SHUANG X.GUO et SHAO L.ZHENG; b: Jixia pinnatipartita SHUANG X.GUO et G.SUN.
Text-fig. 14. Bolshoy Kuvshin, Frentsevka Formation, early-middle Albian. a, e: Asiatifolium elegans G.SUN, SHUANG X.GUO et SHAO L.ZHENG, a – spec. IBSS 320-8, e – spec. IBSS 320-75; b, c: Jixia pinnatipartita SHUANG X.GUO et G.SUN, b – spec. IBSS 320-359, c – spec. IBSS 320-367; d: Achaenocarpites capitellatus KRASSILOV et VOLYNETS, spec. IBSS 320-120; f: Ternaricarpites floribundus KRASSILOV et VOLYNETS, spec. IBSS 320-10; g: undescribed species, spec. IBSS 320-137. Scale bar 1 cm in a, e–g and 5 mm in b–d. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 14. Bolshoy Kuvshin, Frentsevka Formation, early-middle Albian. a, e: Asiatifolium elegans G.SUN, SHUANG X.GUO et SHAO L.ZHENG, a – spec. IBSS 320-8, e – spec. IBSS 320-75; b, c: Jixia pinnatipartita SHUANG X.GUO et G.SUN, b – spec. IBSS 320-359, c – spec. IBSS 320-367; d: Achaenocarpites capitellatus KRASSILOV et VOLYNETS, spec. IBSS 320-120; f: Ternaricarpites floribundus KRASSILOV et VOLYNETS, spec. IBSS 320-10; g: undescribed species, spec. IBSS 320-137. Scale bar 1 cm in a, e–g and 5 mm in b–d.
Text-fig. 11. a: Sapindopsis sp., 3rd Kamenka, Frentsevka Formation, early-middle Albian, spec. IBSS 40-1; b, c: Trochodendroides sp., Konstantinovka, Galenki Formation, early-middle Albian, spec. IBBS 11/145, b – upper part of leaf, c – crenate margin; d: Dicotylophyllum sp. 2, Konstantinovka, Galenki Formation, early-middle Albian, spec. IBBS 11/133; e: Sapindopsis cf. angusta (HEER) SEWARD et V.M.CONWAY, Andreev Inlet, Frentsevka Formation, early-middle Albian, spec. IBSS 28/104; f: Sapindopsis variabilis FONTAINE, Bikin River, Alchan Formation, early-middle Albian, spec. IBSS 4561/124-1; g: Laurophyllum sp., Konstantinovka, Galenki Formation, early-middle Albian, spec. IBBS 11/131. Scale bar 1 cm in a, b, d, f, g and 5 mm in c, e. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 11. a: Sapindopsis sp., 3rd Kamenka, Frentsevka Formation, early-middle Albian, spec. IBSS 40-1; b, c: Trochodendroides sp., Konstantinovka, Galenki Formation, early-middle Albian, spec. IBBS 11/145, b – upper part of leaf, c – crenate margin; d: Dicotylophyllum sp. 2, Konstantinovka, Galenki Formation, early-middle Albian, spec. IBBS 11/133; e: Sapindopsis cf. angusta (HEER) SEWARD et V.M.CONWAY, Andreev Inlet, Frentsevka Formation, early-middle Albian, spec. IBSS 28/104; f: Sapindopsis variabilis FONTAINE, Bikin River, Alchan Formation, early-middle Albian, spec. IBSS 4561/124-1; g: Laurophyllum sp., Konstantinovka, Galenki Formation, early-middle Albian, spec. IBBS 11/131. Scale bar 1 cm in a, b, d, f, g and 5 mm in c, e.
Text-fig. 5. a: coal seam "Rabochy" with three tuff layers in upper part of Lipovtsy Formation in Porechye open pit coal mine; b: same section, enlarged view, upper tuff layer, sample 160/4 site; c: tuff layer in upper part of Frentsevka Formation below conglomerate at Palets Cape; d: same section, enlarged view, sample 1 site. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 5. a: coal seam "Rabochy" with three tuff layers in upper part of Lipovtsy Formation in Porechye open pit coal mine; b: same section, enlarged view, upper tuff layer, sample 160/4 site; c: tuff layer in upper part of Frentsevka Formation below conglomerate at Palets Cape; d: same section, enlarged view, sample 1 site.
Text-fig. 12. a: Artocarpidium sp., Andreev Inlet, Frentsevka Formation, early-middle Albian, spec. IBSS 28-105; b–d: Onoana nicanica KRASSILOV, Fedorovsky Rudnik, Lipovtsy Formation, Aptian, spec. IBSS 63-83; e: Araliaephyllum ussuriense (KRASSILOV) GOLOVN., Andreev Inlet, Frentsevka Formation, early-middle Albian, e1 – spec. IBSS 28-102/1, lectotype, e2 – spec. IBSS 28-102/2. Scale bar 1 cm in a, d, e and 5 mm in b, c. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 12. a: Artocarpidium sp., Andreev Inlet, Frentsevka Formation, early-middle Albian, spec. IBSS 28-105; b–d: Onoana nicanica KRASSILOV, Fedorovsky Rudnik, Lipovtsy Formation, Aptian, spec. IBSS 63-83; e: Araliaephyllum ussuriense (KRASSILOV) GOLOVN., Andreev Inlet, Frentsevka Formation, early-middle Albian, e1 – spec. IBSS 28-102/1, lectotype, e2 – spec. IBSS 28-102/2. Scale bar 1 cm in a, d, e and 5 mm in b, c.
Text-fig. 9. a–d: Nyssidium orientale SAMYLINA, Partizansk, Starosuchan Formation, Barremian, a – spec. BIN 506/3749, general view of four fruits, b1 – spec. BIN 506/3749-1, holotype, b2 – spec. BIN 506/3749-2, c – spec. BIN 506/3749-6, d – spec. BIN 506/3749-5; e–f: Cercidiphyllum sujfunense KRASSILOV, Konstantinovka, Galenki Formation, early-middle Albian, e – spec. IBSS 11-135, fruit, f – spec. IBSS 11-134, leaf, holotype. Scale bar 5 mm in a, e, f and 2 mm in b–d. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 9. a–d: Nyssidium orientale SAMYLINA, Partizansk, Starosuchan Formation, Barremian, a – spec. BIN 506/3749, general view of four fruits, b1 – spec. BIN 506/3749-1, holotype, b2 – spec. BIN 506/3749-2, c – spec. BIN 506/3749-6, d – spec. BIN 506/3749-5; e–f: Cercidiphyllum sujfunense KRASSILOV, Konstantinovka, Galenki Formation, early-middle Albian, e – spec. IBSS 11-135, fruit, f – spec. IBSS 11-134, leaf, holotype. Scale bar 5 mm in a, e, f and 2 mm in b–d.
Text-fig. 10. a–d: Araliaephyllum luciferum (KRYSHT.) GOLOVN., Partizansk, Severosuchan Formation, Aptian, a – spec. TSNIGRM 3013/1, lectotype, b – spec TSNIGRM 3013/2, c – spec. TSNIGRM 3013/4, d – spec. TSNIGRM 3013/3; e, j: Pandanites ahnertii (KRYSHT.) GOLOVN., Konstantinovka, Lipovtsy Formation, Aptian, TSNIGRM 3013/5, e – fragment of leaf margin, j – general view, j1 – lectotype, j2 – leaf, figured in (e); f: Araliaephyllum ussuriense (KRASSILOV) GOLOVN., Andreev Inlet, Frentsevka Formation, early-middle Albian, spec. IBBS 28/103; g: Araliaephyllum vittenburgii GOLOVN. et VOLYNETS, Podgorodenka coalfield, Galenki Formation, early-middle Albian, spec. IBBS 41/1, g1 – spec. IBBS 41/1a, holotype, g2 – spec. IBBS 41/1b; h: Dicotylophyllum sp. 1, Podgorodenka coalfield, Lipovtsy Formation, Aptian, spec. IBBS 28L-4; i: Sapindopsis sp., 3rd Kamenka, Frentsevka Formation, early-middle Albian, spec. IBSS 325/8. Scale bar 5 mm in a–h and 1 cm in i, j. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 10. a–d: Araliaephyllum luciferum (KRYSHT.) GOLOVN., Partizansk, Severosuchan Formation, Aptian, a – spec. TSNIGRM 3013/1, lectotype, b – spec TSNIGRM 3013/2, c – spec. TSNIGRM 3013/4, d – spec. TSNIGRM 3013/3; e, j: Pandanites ahnertii (KRYSHT.) GOLOVN., Konstantinovka, Lipovtsy Formation, Aptian, TSNIGRM 3013/5, e – fragment of leaf margin, j – general view, j1 – lectotype, j2 – leaf, figured in (e); f: Araliaephyllum ussuriense (KRASSILOV) GOLOVN., Andreev Inlet, Frentsevka Formation, early-middle Albian, spec. IBBS 28/103; g: Araliaephyllum vittenburgii GOLOVN. et VOLYNETS, Podgorodenka coalfield, Galenki Formation, early-middle Albian, spec. IBBS 41/1, g1 – spec. IBBS 41/1a, holotype, g2 – spec. IBBS 41/1b; h: Dicotylophyllum sp. 1, Podgorodenka coalfield, Lipovtsy Formation, Aptian, spec. IBBS 28L-4; i: Sapindopsis sp., 3rd Kamenka, Frentsevka Formation, early-middle Albian, spec. IBSS 325/8. Scale bar 5 mm in a–h and 1 cm in i, j.
Data for: Weak, but not strong, ties support coalition formation among wild female chimpanzees
<div> <div> <div> <div> <p>In social species, individuals may be able to overcome competitive constraints on cooperation by leveraging relationships with familiar, tolerant partners. While strong social ties have been linked to cooperation in several social mammals, it is unclear the extent to which weak social ties can support cooperation, particularly among non-kin. We tested the hypothesis that weakly affiliative social relationships support cooperative coalition formation using 10 years of behavioural data on wild female chimpanzees. Female chimpanzees typically disperse and reside with non-kin as adults. Their social relationships are differentiated but often relatively weak, with few dyads sharing strong bonds. Females occasionally form aggressive coalitions together. Three measures of relationship quality - party association, five-meter proximity, and whether a dyad groomed - positively predicted coalitions, indicating that relationship quality influenced coalition partnerships. However, dyads that groomed frequently did not form more coalitions than dyads that groomed occasionally, and kin did not cooperate more than expected given their relationship quality. Thus, strong bonds and kinship did not bolster cooperation. We conclude that cooperative coalitions among female chimpanzees depend on social tolerance but do not require strong bonds. Our findings highlight social tolerance as a distinct pathway through which females can cultivate cooperative relationships.</p> </div> </div> </div> </div>
NFFA-Europe|Pilot proporsal "NANO meets ASTRO: simulating the formation of silicon oxide nanoparticles in the atmosphere of dying stars" (PID: 140).
<p>XPS, IRRAS, QMS and OES data of the nanoparticles synthesized within the NFFA-Europe|Pilot proporsal "NANO meets ASTRO: simulating the formation of silicon oxide nanoparticles in the atmosphere of dying stars" (PID: 140).</p>
ENTSO-E Pan-European Climatic Database (PECD 2021.3) in Parquet format
<p><strong>ENTSO-E Pan-European Climatic Database (PECD 2021.3) in Parquet format</strong></p> <p><strong>TL;DR</strong>: this is a tidy and friendly version of a subset of the PECD 2021.3 data by ENTSO-E: hourly capacity factors for wind onshore, offshore, solar PV, hourly electricity demand, weekly inflow for reservoir and pumping and daily generation for run-of-river. All the data is provided for >30 climatic years (1982-2019 for wind and solar, 1982-2016 for demand, 1982-2017 for hydropower) and at national and sub-national (>140 zones) level.</p> <p><strong>UPDATE (19/10/2022): </strong>updated the demand files due after fixing a bug in the processing code (the file for 2030 was the same for 2025) and solving an issue caused by a malformed header in the ENTSO-E excel files. </p> <p> </p> <p> </p> <p>ENTSO-E has released with the latest European Resource Adequacy Assessment (<a href="https://www.entsoe.eu/outlooks/eraa/">ERAA 2021</a>) all the inputs used in the study.<br> Those inputs include:<br> - Demand dataset: <a href="https://eepublicdownloads.azureedge.net/clean-documents/sdc-documents/ERAA/Demand%20Dataset.7z">https://eepublicdownloads.azureedge.net/clean-documents/sdc-documents/ERAA/Demand%20Dataset.7z</a><br> - Climate data: <a href="https://eepublicdownloads.entsoe.eu/clean-documents/sdc-documents/ERAA/Climate%20Data.7z">https://eepublicdownloads.entsoe.eu/clean-documents/sdc-documents/ERAA/Climate%20Data.7z</a></p> <p>The data files and the methodology are available on the <a href="https://www.entsoe.eu/outlooks/eraa/2021/eraa-downloads/">official webpage</a>. </p> <p>As done for the previous releases (see <a href="https://zenodo.org/record/3702418#.YbmhR23MKMo">https://zenodo.org/record/3702418#.YbmhR23MKMo</a> and <a href="https://zenodo.org/record/3985078#.Ybmhem3MKMo">https://zenodo.org/record/3985078#.Ybmhem3MKMo</a>), the original data - stored in large Excel spreadsheets - have been tidied and formatted in open and friendly formats (CSV for the small tables and Parquet for the large files)</p> <p>Furthermore, we have carried out a simple country-aggregation for the original data - that uses instead >140 zones.</p> <p><strong>DISCLAIMER</strong>: <em>the content of this dataset has been created with the greatest possible care. However, we invite to use the original data for critical applications and studies. </em></p> <p><strong>Description</strong></p> <p>This dataset includes the following files:</p> <p>- <em>capacities-national-estimates.csv</em>: installed capacity in MW per zone, technology and the two scenarios (2025 and 2030). The files include also the total capacity for each technology per country (sum of all the zones within a country)<br> - <em>PECD-2021.3-wide-LFSolarPV-2025</em> and <em>PECD-2021.3-wide-LFSolarPV-2030</em>: tables in Parquet format storing in each row the capacity factor for solar PV for a hour of the year and all the climatic years (1982-2019) for a specific zone. The two files contain the capacity factors for the scenarios "National Estimates 2025" and "National Estimates 2030"<br> - <em>PECD-2021.3-wide-Onshore-2025</em> and<em> PECD-2021.3-wide-Onshore-2030</em>: same as above but for wind onshore<br> - <em>PECD-2021.3-wide-Offshore-2025</em> and <em>PECD-2021.3-wide-Offshore-2030</em>: same as above but for wind offshore<br> - <em>PECD-wide-demand_national_estimates-2025</em> and<em> PECD-wide-demand_national_estimates-2030</em>: hourly electricity demand for all the climatic years for a specific zone. The two files contain the load for the scenarios "National Estimates 2025" and "National Estimates 2030" <br> - <em>PECD-2021.3-country-LFSolarPV-2025</em> and <em>PECD-2021.3-country-LFSolarPV-2030</em>: tables in Parquet format storing in each row the capacity factor for country/climatic year and hour of the year. The two files contain the capacity factors for the scenarios "National Estimates 2025" and "National Estimates 2030"<br> -<em> PECD-2021.3-country-Onshore-2025</em> and<em> PECD-2021.3-country-Onshore-2030</em>: same as above but for wind onshore<br> -<em> PECD-2021.3-country-Offshore-2025</em> and <em>PECD-2021.3-country-Offshore-2030</em>: same as above but for wind offshore<br> - <em>PECD-country-demand_national_estimates-2025</em> and <em>PECD-country-demand_national_estimates-2030</em>: same as above but for electricity demand<br> - <em>PECD_EERA2021_reservoir_pumping.zip</em>: archive with four files per each scenario: 1. table.csv with generation and storage capacities per zone/technology, 2. zone weekly inflow (GWh), 3. table.csv with generation and storage per country/technology and 4. country weekly inflow (GWh)<br> - <em>PECD_EERA2021_ROR.zip</em>: as for the previous file but the inflow is daily<br> - <em>plots.zip</em>: archive with 182 png figures with the weekly climatology for all the variables (daily for the electricity demand)</p> <p><strong>Note</strong></p> <p>I would like to thank Laurens Stoop for sharing the onshore wind data for the scenario 2030, that was corrupted in the original archive.</p>
Greigite formation modulated by turbidites and bioturbation in deep-sea sediments offshore Sumatra
<p>This repository contains the rock magnetic and paleomagnetic data, TOC and TN data, and XRD spectra data associated with the research paper titled "Greigite formation modulated by turbidites and bioturbation in deep-sea sediments offshore Sumatra" by Yang et al. published in Journal of Geophysical Research: Solid Earth, Volume127, Issue11, e2022JB024734, https://doi.org/10.1029/2022JB024734</p>
Text-fig. 4—Femur of Albertosaurus cf. A. lancensis (LACM 23845) in anterior aspect. Diagonal lines indicate broken surfaces. Bar represents 10 cm. in An albertosaur from the Hell Creek formation of Montana
Text-fig. 4—Femur of Albertosaurus cf. A. lancensis (LACM 23845) in anterior aspect. Diagonal lines indicate broken surfaces. Bar represents 10 cm.
Data from: Widespread moulin formation during supraglacial lake drainages in Greenland
<p>This dataset is the data associated with the manuscript "Widespread moulin formation during supraglacial lake drainages in Greenland". It includes field observations, spatial data derived from remote sensing, and model output for a study area in west Greenland. Specifically the data included are:</p> <ul> <li>GPS-derived ice surface velocity at 11 GPS stations in the study area</li> <li>Moulin locations mapped from high resolution satellite imagery</li> <li>Crevasse field locations mapped from high resolution satellite imagery</li> <li>Model output from the Albany/FELIX Model</li> </ul> <p>Details of the data and methods are described in the accompanying README file and the associated manuscript.</p>
1-3. Trionyx foveatus 4.Emys obscurus 5-7. Compsemys victus. 9-19 Crocodilus humilis. 20-23. Lepidotus occidentalis. 24-30 in Extinct vertebrata from the Judith River and Great Lignite formations of Nebraska.
1-3. Trionyx foveatus 4.Emys obscurus 5-7. Compsemys victus. 9-19 Crocodilus humilis. 20-23. Lepidotus occidentalis. 24-30 Mylognathus priscus
1-20. Trachodon mirabilis 21-48. Deinodon horridus 49-52. Palaeoscincus costatus 53-55 in Extinct vertebrata from the Judith River and Great Lignite formations of Nebraska.
1-20. Trachodon mirabilis 21-48. Deinodon horridus 49-52. Palaeoscincus costatus 53-55. Troodon formosus
Datasets used for developing sulfuric acid-water neutral and ion-induced particle formation parameterizations
<p>Supporting data for "New parameterizations for neutral and ion-induced sulfuric acid-water particle formation in nucleation and kinetic regimes" by Määttänen et al. (2017). A README file describing the datasets is included.</p> <p>Five datasets used for developing sulfuric acid-water neutral and ion-induced particle formation parameterizations, published in Määttänen et al. 2017, JGR Atmospheres (submitted) and at https://doi.org/10.5281/zenodo.1044366.</p> <p>Two datasets that have been used to produce Fig 8. of the manuscript: these datasets contain global model output of nucleation rates and total aerosol number concentrations.</p>
Data format figures-DATA MINING LEARNING MODELS AND ALGORITHMS ON A SCADA SYSTEM DATA REPOSITORY
<p>The original data set included noisy, missing and inconsistent data. Data<br> preprocessing improved the quality of the data and facilitated e±cient data<br> mining tasks.<br> Before the experiment, we prepared data suitable to next operation as<br> following steps:<br> ² Delete or replace missing values;<br> ² Delete redundant properties (columns);<br> ² Data Transformation;<br> ² Data Discretization;<br> ² Export data to a required .ar® or .csv format ¯le [11].<br> The original and modi¯ed formats of data set are shown in Figure 1 and<br> Figure 2.<br> Data visualization is also a very useful technique because it helps to deter-<br> mine the di±culty of the learning problem. We visualized with Weka single<br> attributes (1-d) and pairs of attributes (2-d). The ¯gure 3 shows the variation<br> of the temperature in time.</p>
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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.