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48 results for “Aquila”
L'Aquila 2009 seismic sequence: integrated dataset of automatic first motion polarities focal mechanisms and RMT with HypoDD high quality relative earthquake locations
<p>This dataset is related to the L'Aquila 2009 seismic sequence that happened in Central Apennines (Italy).</p> <p>It contains:</p> <ul> <li>2782 quality selected focal mechanisms produced with the standard software FPFIT based on automatically determined first motion polarities of automatically detected and analyzed foreshocks and aftershocks recorded from January 2009 to December 2009 (flag <strong>fty</strong> in the header is MP)</li> <li>475 (out of 627) quality selected focal mechanisms produced with the standard software FPFIT also based on automatically determined first motion polarities but for only 3204 M<sub>L</sub> >= 1.9 earthquakes and by using take-off angles calculated within a local 3d tomographic velocity model (<a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2011GL047365">Di Stefano et al., 2011</a>) , published and released in <a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2011JB008352">Chiaraluce et al., 2011</a> (flag <strong>fty</strong> in the header is JG)</li> <li>165 (out of 181) Regional Moment Tensors determined for earthquakes M<sub>L</sub> >= 3.0 based on broadband waveform inversion of ground velocities and published by <a href="https://pubs.geoscienceworld.org/ssa/bssa/article-abstract/101/3/975/349796/Regional-Moment-Tensors-of-the-2009-L-Aquila">Hermann et al., 2011</a> (flag <strong>fty</strong> in the header is HM)</li> <li>The hypocenters of the total 3422 earthquakes reported in the present focal solutions dataset have been taken from the very high quality double difference locations of the about 64000 aftershocks reported in <a href="https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/jgrb.50130">Valoroso et al., 2013</a> and published, as part of the full dataset, <a href="https://doi.org/10.5281/zenodo.4036248">on Zenodo</a>. </li> </ul> <p>The association between the focal solutions and the HypoDD hypocenters has been performed through the direct use of the HypoDD event identifier where possible (the whole MP dataset) and through spatial and temporal earthquakes coordinates matching in all the other case by using the capability of a MySQL database. </p> <p>Two files are uploaded, one in plain text with blank separator, the second in plain text with ";" separator and .csv extension.</p> <p>Here below the header is explained.</p> <p><strong>OT_Date:</strong> date of the origin time in the format YYYY-MM-DD</p> <p><strong>OT_Time:</strong> time of the origin time in the format HH:mm:ss.dcm</p> <p><strong>lat:</strong> hypocenter latitude expressed in degrees </p> <p><strong>lon:</strong> hypocenter longitude east of Greenwich, expressed in degrees</p> <p><strong>dep:</strong> hypocenter depth expressed in km </p> <p><strong>ML:</strong> local magnitude (pure number) from <a href="https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/jgrb.50130">Valoroso et al., 2013</a> (see last column notes also)</p> <p> </p> <p><strong>id_dd:</strong> the hypoDD event identifier, allowing to directly connect to the <a href="https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/jgrb.50130">Valoroso et al., 2013</a> full dataset</p> <p><strong>IMPORTANT NOTE about st1 and st2 (below): </strong>the focal solutions are presented here based on the convention they where produced or published, so there are two different (but compatible) conventions for the fault plains orientation in the 3d space</p> <p><strong>st1:</strong></p> <ul> <li><strong>for fty=</strong>HM or JG this is the strike of plane 1 (CMT convention)</li> <li><strong>for fty=</strong>MP this is the <strong>strike of the dip direction </strong>of plain 1 (FPFIT convention)</li> </ul> <p><strong>dip1: </strong>dip of plane 1</p> <p><strong>rk1: </strong>rake of plane 1</p> <p><strong>st2:</strong></p> <ul> <li><strong>for fty=</strong>HM or JG this is the strike of plane 2 (CMT convention)</li> <li><strong>for fty=</strong>MP this is the <strong>strike of the dip direction </strong>of plain 2 (FPFIT convention)</li> </ul> <p><strong>dip2: </strong>dip of plane 2</p> <p><strong>rk2: </strong>rake of plane 2</p> <p><strong>fty:</strong> flag to distinguish the type of solution, CMT=HM or JG, FPFIT=MP</p> <p><strong>MW:</strong> only for HM, this columns reports also MW from <a href="https://pubs.geoscienceworld.org/ssa/bssa/article-abstract/101/3/975/349796/Regional-Moment-Tensors-of-the-2009-L-Aquila">Hermann et al., 2011</a></p>
Particle size and velocity distributions from a Thies Clima 3D Stereo disdrometer installed at the Casale Calore site in L'Aquila (Italy), monthly netCDF archive
<p>Disdrometric data from a Thies Clima 3D Stereo disdrometer, with 22 size classes and 20 velocity classes, located at the instrumented site of Casale Calore in L'Aquila (Italy, 42.3831 N, 13.3148 E, 683 m a.s.l.), managed by the University of L'Aquila and the Center of Excellence Telesensing of Environment and Model Prediction of Severe Events (CETEMPS). </p> <p>Mid values and widths of the classes and instrument ancillary data are provided. One-minute spectra are aggregated every 5 minutes and saved in monthly netCDF files.</p> <p>Metadata available at <a href="https://antarcticdatacenter.cnr.it/geonetwork/srv/eng/catalog.search#/metadata/27e2bd39-097e-4512-96f0-fb213cd59a00">https://antarcticdatacenter.cnr.it/geonetwork/srv/eng/catalog.search#/metadata/27e2bd39-097e-4512-96f0-fb213cd59a00</a></p> <p>--------------------------------------------------------------------</p> <p>Example of netCDF file structure:</p> <h2><strong>File "LAQ_3DS_202301_5min.nc"</strong></h2> <pre><strong> dimensions</strong>: <em>diameter </em>= 22; <em>velocity </em>= 20; <em>n_image </em>= 20; <em>y_image </em>= 12; <em>x_image </em>= 12; <em>time </em>= UNLIMITED; // (8741 currently) <strong>variables</strong>: long <em>time_UTC</em>(time=8741); :description = "Measurement time. Timestamp indicates the end of the observation interval, e.g. 01-Mar-2020 00:05:00 represents the particle counts registered between 01-Mar-2020 00:00:01 and 01-Mar-2020 00:05:00."; :time_zone = "UTC"; :units = "Seconds since 1970-01-01 00:00:00 (Unix time)."; :_ChunkSizes = 512U; // uint float <em>diameters</em>(diameter=22); :description = "Mid values of the size classes"; :units = "mm"; float <em>velocities</em>(velocity=20); :description = "Mid values of the velocity classes"; :units = "m s^-1"; float <em>diameters_width</em>(diameter=22); :description = "Width of the size classes"; :units = "mm"; float <em>velocities_width</em>(velocity=20); :description = "Width of the velocity classes"; :units = "m s^-1"; int <em>spectrum</em>(diameter=22, velocity=20, time=8741); :description = "Matrix of particle counts in each of the 22 diameter sizes and 20 velocity ranges over 5 minutes."; :units = "counts"; :_ChunkSizes = 22U, 20U, 1U; // uint float <em>PSD</em>(diameter=22, time=8741); :description = "Particle size distribution, 5 minutes interval, normalized by the observed volume."; :units = "m^-3 mm^-1"; :_ChunkSizes = 22U, 1U; // uint double <em>monthlySpectrum</em>(diameter=22, velocity=20); :description = "Matrix of particle counts in each of the 22 diameter sizes and 20 velocity ranges over the entire month."; :units = "counts"; double <em>monthlyPSD</em>(diameter=22); :description = "Particle size distribution for the whole month, normalized by the observed volume."; :units = "m^-3 mm^-1"; int <em>images</em>(x_image=12, y_image=12, n_image=20, time=8741); :description = "Images of samples of the detected precipitating particles. Images are 48x12 pixel maximum, for a max of 4 stacked 12x12 images. Most of the time less than 4 images are provided."; :units = "0-255 pixel values"; :_ChunkSizes = 12U, 12U, 20U, 1U; // uint int <em>image_count</em>(time=8741); :description = "How many images are registred by the instrument in the minute."; :units = "0-4 count"; :_ChunkSizes = 1024U; // uint int <em>precip_type</em>(n_image=20, time=8741); :description = "Precipitation type as classified by the instument based on shape, size, velocity and presence of water, according to the following table with 11 entries (0-10): 0-reserved value, 1-false positive, 2-rain or graupel, 3-drizzle, 4-drizzle with rain, 5-rain, 6-rain with snow, 7-snow, 8-ice prisms, 9-graupel, 10-hail."; :units = "0-10 code"; :_ChunkSizes = 20U, 1U; // uint int <em>particle_diam</em>(n_image=20, time=8741); :description = "Main diameter of the particles shown in the images."; :units = "mm"; :_ChunkSizes = 20U, 1U; // uint //<strong> global attributes</strong>: :<em>title </em>= "Thies Clima 3D Stereo disdrometer data, aggregated to 5min, monthly netCDF archive."; :<em>comment </em>= "Particle counts diveded in 22 size classes and 20 velocity classes. Note that this data has been processed regardless of precipitation type."; :<em>time_label </em>= "Jan 2023"; :<em>institution </em>= "CNR-ISAC, Rome (IT)"; :<em>contact_person </em>= "Luca Baldini, CNR-ISAC, Rome, l.baldini@isac.cnr.it"; :<em>source </em>= "TC 3DS disdrometer at MZS (Antarctica)"; :<em>location </em>= "Mario Zucchelli Station (74°42\'S, 164°07\'E, 15 m a.s.l.)"; :<em>author </em>= "Giacomo Roversi, Ca\' Foscari University, Venice (IT) and CNR-ISAC, Rome (IT), g.roversi@isac.cnr.it"; :<em>creation_date </em>= "23-Oct-2024 11:13:22 UTC"; :<em>coverage </em>= "Monthly coverage (Jan 2023): 100 %"; :<em>time_resolution </em>= "5 minutes"; :<em>history </em>= "Created from raw TC telegram TDD 163, aggregated to 5min temporal resolution with a sum of the 1-minute counts if least 3 out of 5 are not NaN."; </pre> <p> </p> <p> </p>
aquila (Whalen & Carter in Carter, Whalen & Guex, 1998), Orbuk-32; R, Pseudoeucyrtis busuangaensis (Yeh & Cheng, 1998), Orbuk-32; S, Farcus graylockensis Pessagno, Whalen & Yeh, 1986, Orbuk-32; T-U, Farcus sp. A, Orbuk-26; V, Farcus sp. B, Orbuk-27; W-X, Anaticapitula anatiformis (De Wever, 1982); W, Orbuk-32; X, Orbuk-38; Y, Saitoum sp. aff. S. triumphense Whalen & Carter in Carter, Whalen & Guex, 1998, Orbuk-32. Scale bar: A-C, K-L, T-U, W-Y, 100 µm; D-J, M-O, 120 µm; P-S, V, 150 µm. in Late Triassic to Early Jurassic radiolarian, conodont and ammonite assemblages from the Tavuscayiri block, Mersin Mélange, southern Turkey: Time constraints for the T/J boundary and sedimentary evolution of the southern margin of the northern Neotethys
aquila (Whalen & Carter in Carter, Whalen & Guex, 1998), Orbuk-32; R, Pseudoeucyrtis busuangaensis (Yeh & Cheng, 1998), Orbuk-32; S, Farcus graylockensis Pessagno, Whalen & Yeh, 1986, Orbuk-32; T-U, Farcus sp. A, Orbuk-26; V, Farcus sp. B, Orbuk-27; W-X, Anaticapitula anatiformis (De Wever, 1982); W, Orbuk-32; X, Orbuk-38; Y, Saitoum sp. aff. S. triumphense Whalen & Carter in Carter, Whalen & Guex, 1998, Orbuk-32. Scale bar: A-C, K-L, T-U, W-Y, 100 µm; D-J, M-O, 120 µm; P-S, V, 150 µm.
Fig. 2 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population
Fig. 2. Cluster analyses of imperial eagle breeding areas based on prey composition data. Region codes are presented in Fig. 1. Codes with bold characters represent mountainous habitats. The single breeding pair of the Cserehát Mountains was excluded from the analysis, because of low sample size
Fig. 3 in Spatial Variation In Prey Composition And Its Possible Effect On Reproductive Success In An Expanding Eastern Imperial Eagle (Aquila Heliaca) Population
Fig. 3. Frequency of the three main prey species (a-c) and reproductive success (d) of imperial eagles in two East-Hungarian regions. Boxplots presents the minimum-maximum (whiskers), lower and upper quartiles (box) and the median (line) of the data. Dots are outliers. Significance of difference is in-
Figure 3 in A neotype designation for the Ascension Frigatebird Fregata aquila (Aves: Fregatidae)
Figure 3. Neotype of Fregata aquila (Linnaeus, 1758): Ventral, lateral, and dorsal views of specimen BMNH 1899.1.4.13 in the Natural History Museum at Tring, UK. Scale bar: 30 cm.
Figures 1-2 in A neotype designation for the Ascension Frigatebird Fregata aquila (Aves: Fregatidae)
Figures 1-2. (1) Plate LIV, figure 2 of PETIVER (1764 [1702-1706]), named 'The Indian Forked Tail'. (2) Plate LXXX of ALBIN (1731), named the 'The Frigate Bird'. Note the all-black plumage and red gular pouch characteristic of adult male frigatebirds.
Example dataset of stLFR linked reads to run Aquila_stLFR
<p>We provide this small chromosome (chr21) example dataset to run Aquila_stLFR. </p> <p>Aquila_stLFR: <a href="https://github.com/maiziex/Aquila_stLFR">https://github.com/maiziex/Aquila_stLFR</a></p> <p> </p>
The 2009 Mw6.1 L'Aquila normal fault system imaged by 64,051 high-precision foreshock and aftershock locations.
<p>The earthquake catalogue is composed by 64,051 high-precision foreshock and aftershock recorded during the Mw6.1 2009 L'Aquila (Central Italy) normal faulting seismic sequence. The catalog includes events occurred between 1<sup>st</sup> of January and 31<sup>st</sup> December 2009. The completeness magnitude is 0.7. Earthquake locations were obtained by combining an automatic picking procedure for P and S waves, together with cross-correlation and double-difference location methods. </p> <p>Seismic data were recorded at a very dense local network composed of 67 three-component seismic stations (20 permanent stations of the Italian National Network located within 80 km from the epicentral area and 47 temporary stations installed soon after the occurrence of the main shock [Margheriti et al., 2011]). </p> <p>Earthquakes were extracted by the continuous recordings by applying a detection algorithm to all stations, based on the classical STA/LTA coincidence-sum algorithm applied to the trace of the 3C covariance matrix. To these events, we applied an automatic picking algorithm (Manneken Pix) [Di Stefano et al., 2006] able to provide about 1.9 million P-wave and 503,000 S-wave accurate readings, with an estimation of the measurement errors. </p> <p>We applied a time domain cross-correlation method (Schaff and Waldhauser, 2005) to all event pairs with separation distances ≤ 5 km at all stations that recorded the pair. Seismograms were filtered in the 1-15 Hz frequency range using a 4 pole, zero phase band‐pass Butterworth filter. We selected measurements with correlation coefficients greater than 0.85, resulting in a total of ~190 million P and ~85 million S-wave delay times. </p> <p>Earthquakes were located following a two steps procedure. Initial locations for 133,236 events were computed with the Hypoellipse code [Lahr , 1989] using a 1D P-wave gradient velocity model optimized for the area [Chiaraluce et al., 2011]. In the second step, we computed relative locations by applying the large scale double-difference method described in Waldhauser and Schaff, (2008) to the catalog picks and phase delay times measured from waveform cross correlation. The entire dataset was sub-divided in 84 rectangular overlapping boxes, containing a maximum of 3000 earthquakes, orthogonal to the mean strike of the seismic sequence. Resulting relative locations from all boxes were combined into a single catalog, computing the weighted mean of double hypocenters in the overlapping regions (Waldhauser and Schaff, 2008). </p> <p>The final double-difference catalog includes 64,051 events. A subset made of 51,271 earthquakes (i.e., 80% of the whole dataset) indicates highly correlated earthquakes, having at least 10 P-waves and 5 S-waves correlated phases with at least one other event. Highly correlated events (flag=1 in the attached file) mostly occur on the major fault segments, while poorly correlated earthquakes (flag=0 in the attached file) mostly occur in the volume around the major faults.</p> <p>The attached file is a plain text with ";" separator and .csv extension.</p> <p>Here below the header is explained.</p> <p><strong>id_dd: </strong>the hypoDD unique event identifier</p> <p><strong>origin_time: </strong>date of the origin time in the format YYYY-MM-DD[T]hh:mm:ss.msec</p> <p><strong>lat</strong>: hypocenter latitude expressed in degrees </p> <p><strong>lon</strong>: hypocenter longitude east of Greenwich, expressed in degrees</p> <p><strong>dep</strong>: hypocenter depth expressed in km </p> <p><strong>mag</strong>: magnitude (pure number)</p> <p><strong>flag</strong>:<strong> </strong>1 for highly correlated earthquakes; 0 for poorly correlated earthquakes. </p> <p> </p> <p> </p> <p> </p>
Cryptotympana aquila(WALKER, 1850). in Cicadidae (Homoptera) de Nicaragua: Catalogo ilustrado, incluyendo especies exóticas del Museo Entomológico de Leon
Cryptotympana aquila(WALKER, 1850).
Multimodal data helps in identifying spatio-temporal patterns and habitat associations of <em>Aquila chrysaetos</em> (Golden Eagle) in Finland
Open the record for dataset details and reuse information.
Extreme drought increased home range sizes and space use of Aquila chrysaetos (Golden Eagles) in coastal southern California
Open the record for dataset details and reuse information.
Shortgrass Steppe site, station USGS Breeding Bird Survey Route 17305, Nunn, CO, study of animal abundance of Aquila chrysaetos in units of numberPerSightingEffort on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains animal abundance of Aquila chrysaetos measurements in numberPerSightingEffort units and were aggregated to a yearly timescale.
Shortgrass Steppe site, station USGS Bird Breeding Survey area 17901, Rockport, CO, study of animal abundance of Aquila chrysaetos in units of numberPerSightingEffort on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains animal abundance of Aquila chrysaetos measurements in numberPerSightingEffort units and were aggregated to a yearly timescale.
FIGURES 1–5. Elachiptera aquila. 1 in A new brachypterous species of Elachiptera Becker (Diptera: Chloropidae) from freshwater wetlands in eastern Canada
FIGURES 1–5. Elachiptera aquila. 1. Wing; 2. Head (dorsal); 3. Antenna (lateral); 4. Male genitalia (lateral); 5. Male genitalia (posterior). Abbreviations: cer — cercus; epd — epandrium; hyp hypandrium; phap — phallapodeme; phal — phallus; pog — postgonite; sur — surstylus. Scale bar = 0.1mm (Figs. 45)
Aquila africana SPAdes preassembly
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Aquila nipalensis SPAdes preassembly
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Aquila africana decontaminated FSCR
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Aquila nipalensis decontaminated FSCR
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Aquila spilogaster SPAdes preassembly
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