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FIG. 18 in New genera and species from the Belly River Series (mid-Cretaceous)
FIG. 18. Monoclonius canadensis part of the skull from the right lateral aspect: one-eighth natural size. fp, postirontal h, horn core o, orbit: sqnztmoszil p, right lateral extension from parietal j, jugal l, lower jaw.
Vertical profiles and integrated time series of bird density and flight speed vector (19.09.2016-10.10.2016)
<p><strong>Description</strong></p> <p>This dataset contains the vertical profiles and integrated time series of bird density and flight speed (NS and EW) used in Nussbaumer (2019) [open access: <a href="https://www.mdpi.com/2072-4292/11/19/2233">https://www.mdpi.com/2072-4292/11/19/2233</a>]. Data are stored in a JavaScript Object Notation (JSON) file for each radar, with the following structure:</p> <pre><code>{ "name" : "bejab", //code name of the radar (http://eumetnet.eu/wp-content/themes/aeron-child/observations-programme/current-activities/opera/database/OPERA_Database/index.html) "lat" : 51.1917, //Latitude "lon" : 3.0642, //Longitude "height" : 50, //Height of the radar antenna [m] a.s.l. "maxrange" : 25, //Maximum range [km] used for profile "alt" : [100, 300,...], "time" : ["19-Sep-2016 00:00:00", "19-Sep-2016 00:05:00",...], "dens" : [[...],...], //Vertical profile of bird density [1/km3] "u" : [[...],...], //Vertical profile of bird flight speed in East(+)/West(-) [m/s] "v" : [[...],...], //Vertical profile of bird flight speed in North(+)/South(-) [m/s] "denss" : [...], //Integrated profile of bird density [1/km2] "us" : [...], //Integrated profile of bird flight speed in East(+)/West(-) [m/s] "vs" : [...], //Integrated profile of bird flight speed in North(+)/South(-) [m/s] }</code></pre> <p> </p> <p><strong>Procedure</strong></p> <p>The raw data are downloaded on the <a href="http://enram.github.io/data-repository/">ENRAM repository</a>,( see Dokter (2011) and (2019) for more details) and processed according to the procedure described below.</p> <ol> <li>Of the 84 radars contributing data during the study period, 11 radars are discarded because of their poor quality due to S-band radar type, poor processing or large gaps (temporal or altitude cut). The same radars were removed in Nilsson et al. (2019).In addition, the 4 radars from Bulgaria and Portugal were excluded because of their geographic isolation.</li> <li>The full vertical profile was discarded when rain was present at any altitude bin. A dedicated MATLAB GUI was used to visualise the data and manually set bird densities to “not-a-number” in such cases. </li> <li>Zones of high bird densities can sometimes be incorrectly eliminated in the raw data. To address this, Nilsson et al. (2019) excluded problematic time or height ranges from the data. Here, in order to keep as much data as possible, the data was manually edited to replace erroneous data either with “not-a-number”, or by cubic interpolation using the dedicated MATLAB GUI.</li> <li>Due to ground scattering,the lower altitude layers are sometimes contaminated by errors or excluded in the raw data. We vertically interpolated bird density by copying the first layer without error into to the lower ones. This approach is relatively conservative as bird migration intensity usually decreases with height in the absence of obstacles, and more so in autumn (Bruderer, 2018)</li> <li>The vertical profiles are vertically integrated from the radar altitude and up to 5000 m asl.</li> <li>The data recorded during daytime are excluded. Daytime is defined at each radar by the civil dawn and dusk (6° below horizon).</li> <li>Finally, the data of 10 radars with high temporal resolution (5-10minutes) was down-sampled to 15 minutes to preserve a balanced representation of each radar.</li> </ol> <p>The resulting cleaned vertical-integrated time series of nocturnal bird density can be viewed in vp_corrected.zip.</p> <p>More details and illustrations are available in Nussbaumer (2019) [open access: <a href="https://www.mdpi.com/2072-4292/11/19/2233">https://www.mdpi.com/2072-4292/11/19/2233</a>], </p> <p><strong>Acknowledgement</strong></p> <p>We acknowledge the <a href="http://eumetnet.eu/activities/observations-programme/current-activities/opera/">European Operational Program for Exchange of Weather Radar Information (EUMETNET/OPERA)</a> for providing access to European radar data, faciliated through a research-only license agreement between EUMETNET/OPERA members and <a href="http://enram.eu/">ENRAM</a>.</p> <p> </p> <p><strong>References</strong></p> <p>Bruderer, B.; Liechti, F. Variation in density and height distribution of nocturnal migration in the south of israel. <em>Israel Journal of Zoology</em> <strong>1995</strong>, <em>41</em>, 477–487. <a href="http://doi.org/10.1080/00212210.1995.10688815">doi:10.1080/00212210.1995.10688815</a>.</p> <p>Dokter A. M. , F. Liechti, H. Stark, L. Delobbe, P. Tabary, and I. Holleman, “Bird migration flight altitudes studied by a network of operational weather radars,” <em>J. R. Soc. Interface</em>, vol. 8, no. 54, pp. 30–43, Jan. <strong>2011</strong>. <a href="http://doi.org/10.1098/rsif.2010.0116">doi:10.1098/rsif.2010.0116</a></p> <p>Dokter A. M. , P. Desmet, J. H. Spaaks, S. van Hoey, L. Veen, L. Verlinden, C. Nilsson, G. Haase, H. Leijnse, A. Farnsworth, W. Bouten, and J. Shamoun‐Baranes, “bioRad: biological analysis and visualization of weather radar data,” <em>Ecography </em>(Cop.)., vol. 42, no. 5, pp. 852–860, May <strong>2019</strong>. <a href="http://doi.org/10.1111/ecog.04028">doi: 10.1111/ecog.04028</a></p> <p>Nilsson, C.; Dokter, A.M.; Verlinden, L.; Shamoun-Baranes, J.; Schmid, B.; Desmet, P.; Bauer, S.; Chapman, J.; Alves, J.A.; Stepanian, P.M.; Sapir, N.;Wainwright, C.; Boos, M.; Górska, A.; Menz, M.H.M.; Rodrigues, P.; Leijnse, H.; Zehtindjiev, P.; Brabant, R.; Haase, G.; Weisshaupt, N.; Ciach, M.; Liechti, F. Revealing patterns of nocturnal migration using the European weather radar network. <em>Ecography </em><strong>2019</strong>, <em>42</em>, 876–886. <a href="http://doi.org/10.1111/ecog.04003">doi:10.1111/ecog.04003</a>.</p> <p>Nussbaumer R., L. Benoit, G. Mariethoz, F. Liechti, S. Bauer, and B. Schmid, “A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network,” <em>Remote Sens</em>., vol. 11, no. 19, p. 2233, Sep. <strong>2019</strong>. <a href="https://www.mdpi.com/2072-4292/11/19/2233">doi: 10.3390/rs11192233</a></p> <p> </p> <p> </p>
Fig.21.—A in New genera and species from the Belly River Series (mid-Cretaceous)
Fig.21.—A, front view of right femur of Trachodon selwyni, from Red Deer river B, front _ view of right femnr of Iguanodon 1mantelli, from the Wealden of England One-sixteenth naturalsize. h,head t,greattrochanter m, thirdtrochanter; c,innercondyle.
Bias-corrected simluated wind power generation time series for Brazil
<p>Simulated and bias corrected wind power generation time series data sets for Brazil, its North-East and South, seven states and seven wind parks.</p> <p>The data sources, generation and validation of the datasets are described in the article "Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil", preprint available on arXiv: arxiv.org/abs/1904.13083, final version DOI: <a href="https://doi.org/10.1016/j.energy.2019.116212">10.1016/j.energy.2019.116212</a></p> <p>Code for generating the datasets is available at github.com/KatharinaGruber/BrazilWindpower_biascorr</p> <p> </p> <p>The files "comp_*" contain comparisons of simulated and observed wind power generation time series with daily resolution for all regions.</p> <p>"comp_noc.RData" is for comparison of interpolation methods and contains time series generated with Nearest Neighbour interpolation (NN), Bilinear Interpolation (BLI) and Inverse Distance Weighting (IDW).</p> <p>"comp_wmsa.RData" is for comparison of wind speed mean approximation methods and contains time series generated with Nearest Neighbour interpolation (NN - no correction applied), mean approximation with measured data (IN) and mean approximation with the Global Wind Atlas (GWA).</p> <p>"comp_wsc.RData" is for comparison of spatiotemporal wind speed correction methods and contains time series generated with mean approximation with the Global Wind Atlas (wmsa) and combined mean approximation with the Global Wind Atlas and hourly and monthly mean approximation with measured data (wschm).</p> <p> </p> <p>The files "statpowlist_*" contain hourly simulated wind power generation time series for three interpolation methods (NN, BLI, IDW), two mean approximation methods (wsmaIN - measured data (INMET), wsmaWA - Global Wind Atlas) as well as for spatiotemporal (hourly and monthly) wind speed bias correction (wschm) for each wind park available in The Wind Power dataset.</p>
Paired time series of daily discharge and storm surge
<p>This dataset presents daily time series of discharge and maximum storm surge at river mouths globally from 1980 - 2014. </p> <p>Daily river discharge is the product of routing the mean daily runoff of the JULES model from the eartH2Observe WRR2 reanalysis data at 0.5° resolution (Best et al., 2011; Clark et al., 2011; Schellekens et al., 2017) with CaMa-Flood at a 0.25° resolution (Yamazaki et al., 2011). The maximum daily storm surge is obtained from the Global Tide and Surge Model (GTSM) (Muis et al., 2016; Verlaan et al., 2015). Each discharge location at the river mouth of coastal catchments larger than 1,000 km<sup>2</sup> is paired with the nearest (≤ 75 km) GTSM output location (Eilander et al., 2019). </p> <p> </p>
Figs. 1–9. Stenosigma humerale holotype female. 1 in On the type series of Stenosigma humerale Giordani Soika with the description of a new species (Hymenoptera, Vespidae, Eumeninae)
Figs. 1–9. Stenosigma humerale holotype female. 1, habitus; 2, lower head in lateral view; 3, lateral surface of pronotum in lateral view; 4, mesepisternum; 5, mesoscutum and scutellum in dorsal view; 6, metanotum in dorsal view; 7, T1 in dorsal view; 8, T1 in lateral view; 9, S1 in ventral view. Scale bars for Fig. 1 = 2 mm, Figs. 2–4 = 0.5 mm, and Figs. 5–9 = 1 mm.
Figs. 10–12 in On the type series of Stenosigma humerale Giordani Soika with the description of a new species (Hymenoptera, Vespidae, Eumeninae)
Figs. 10–12. Labels attached to the putative female paratype of S. humerale, presently attributed to a new species.
Figs. 13–21. Stenosigma quechua holotype female. 13 in On the type series of Stenosigma humerale Giordani Soika with the description of a new species (Hymenoptera, Vespidae, Eumeninae)
Figs. 13–21. Stenosigma quechua holotype female. 13, habitus; 14, lower head in lateral view; 15, lateral surface of pronotum in lateral view; 16, mesepisternum; 17, mesoscutum and scutellum in dorsal view; 18, metanotum in dorsal view; 19, T1 in dorsal view; 20, T1 in lateral view; 21, S1 in ventral view. Scale bars for Fig. 13 = 2 mm, Figs. 14–17 = 0.5 mm, and Figs. 18–21 = 1 mm.
Text-fig. 5. Mytoconula vonkai sp. n. The holotype NM L 31983, internal mould. A – apical, B – right apical and right antero-lateral views, both with visible series of muscle scars in two raised zones, ×......;. Note the two long divergent scar zones in A. Dobrotivá F., Mýto near Holoubkov. in Patelliconus Horný, 1961 And Mytoconula Gen. N. (Mollusca, Tergomya) From The Ordovician Of Perunica
Text-fig. 5. Mytoconula vonkai sp. n. The holotype NM L 31983, internal mould. A – apical, B – right apical and right antero-lateral views, both with visible series of muscle scars in two raised zones, ×......;. Note the two long divergent scar zones in A. Dobrotivá F., Mýto near Holoubkov.
Figs 18–20 in Redescription of larva, pupa and adult of Anopheles (Anopheles) annulipalpis (Diptera: Culicidae) and the removal of the specie of the Cycloleppteron Series
Figs 18–20, Anopheles (Anopheles) annulipalpis Lynch Arribálzaga, 1878, pupa: 18, CT (cephalothorax); 19, MT (metathorax) and abdominal segments I-VIII (left side dorsal, right side ventral); 20, pupa trumpet; Pa. (paddle). Scales in mm except, when indicated.
Figs 10–17 in Redescription of larva, pupa and adult of Anopheles (Anopheles) annulipalpis (Diptera: Culicidae) and the removal of the specie of the Cycloleppteron Series
Figs 10–17, Anopheles (Anopheles) annulipalpis LYnch ArribÁlzaga, 1878, larva: 10, pro- (P), meso- (M) and metathorax (T), and abdominal segments I-VI (left side dorsal, right side ventral); 11, head, left dorsal side, right ventral side; 12, abdominal segments VII–X lateral view; 13, pecten plate; 14, dorsomentum; 15, detail of antenna; 16, seta 3-C alternative; 17, seta 1-III. Scales in mm.
Figs 1–9 in Redescription of larva, pupa and adult of Anopheles (Anopheles) annulipalpis (Diptera: Culicidae) and the removal of the specie of the Cycloleppteron Series
Figs 1–9, Anopheles (Anopheles) annulipalpis LYnch ArribÁlzaga, 1878. 1, Female genitalia; 2–9, male genitalia: 2, dorsal lobe of Claspette, 3; setae of dorsal lobe of Claspette; 4, aedeagus; 5, lateral view of aedeagus; 6, gonocoxite and gonostylus dorsal aspect (prerotation sense); 7, ventral lobe of Claspette; 8, detail of ventral lobe of Claspette; 9, IX-Tergum. Scales in mm, except when indicated.
Fig. 11. Ontogenetic size progression from D4 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 11. Ontogenetic size progression from D4 to D16 of Changaspis elongata Lee in Chien, 1961. A. Least square linear regression of ln CELd on the d stage (rA = 0.96622, n = 13). B. Least square linear regression of ln TRLd on the d stage (rB = 0.98373, n = 13). Bars are mean standard errors caused by structural deformation and measurement. Abbreviation: CELd, cephalic length on the d stage; TRLd, trunk length on the d stage.
Fig. 13 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 13. Frequency distribution of the index of conformity to Dyar's rule from the D4 to D16 of Changaspis elongata Lee in Chien, 1961. A. Cephalic length (n = 13). B. Trunk length (n = 13).
Fig. 12 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 12. Boxplot showing the relationship about the index of conformity to Dyar's rule for the cephalic and trunk length of Changaspis elongata Lee in Chien, 1961. The middle line in the box, which is the median of the dataset, represents the average of the sample data. The width of the box partly reflects the volatility of the dataset. Above and below the box, there is a line, respectively represent the maximum and minimum value.
Fig. 9 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 9. Relative axial length of different body parts from the D4 to H stage of Changaspis elongata Lee in Chien, 1961. A. Relative trunk length of each thoracic segment and pygidium. B. Relative body length of cephalon, each thoracic segment and pygidium. Thorax and pygidium together constitute the trunk. Cephalon, thorax, and pygidium make up the body. Abbreviation: CEL, cephalic length; LTH, length of thorax; PYL, pygidial length; TS1, thoracic segment 1.
Fig. 10 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 10. Growth gradient in the trunk of Changaspis elongata Lee in Chien, 1961. A. Allometric coefficients of individual thoracic segments with respect to trunk length. B. Average per-moult growth rates of individual thoracic segments. Both exhibit significant increasing value from anterior to posterior (Spearman's rank correlation test, n = 16, pA = 0.988, pB = 0.988). Bars are standard errors caused by structural deformation and measurement (not calculable for TS16), n = 14 for TS1–4 and decreases from n = 13 to 2 for TS5–16, respectively. Abbreviation: TS1, section 1 thoracic segment.
Fig. 8 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 8. Trunk development schedule of Changaspis elongata Lee in Chien, 1961. Green, dark grey, white, and black represent cephalon, thoracic segments, pygidial segments, and terminal axial piece, respectively. Dotted lines represent estimated, because of axial ring of pygidium faint.
Fig. 7 in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 7. Reconstructions in dorsal view of ontogenetic series of Changaspis elongata Lee in Chien, 1961. A–M. D4–16. N. H. Scale bars 1 mm.
Fig. 1. A in Morphology and developmental traits of the trilobite Changaspis elongata from the Cambrian Series 2 of Guizhou, South China
Fig. 1. A. Map showing the position of collecting localities in the Guizhou Province. B. Map of the fossil locality Lazizhai, 6.4 km from Jianhe, Guizhou Province, South China. C. Stratigraphical column of the Balang Formation (Cambrian Stage 4), showing the horizon where the material was collected arrows), and the stratigraphic occurrences of oryctocephalid trilobites.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.