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6,059 results for “Journale”
Supplementary material 2 from: Lahey Z, Simmons AM, Andreason SA (2022) Encarsia hera Lahey & Andreason (Hymenoptera, Aphelinidae): a charismatic new parasitoid of Aleurocybotus Quaintance & Baker (Hemiptera, Aleyrodidae) from Florida. Journal of Hymenoptera Research 94: 89-104. https://doi.org/10.3897/jhr.94.94677
Maximum likelihood cladogram of a trimmed version of the 28S-D2-3 dataset analyzed in Fig. 9 (495 sites, GTR+F+G4)
Supplementary material 1 from: Lahey Z, Simmons AM, Andreason SA (2022) Encarsia hera Lahey & Andreason (Hymenoptera, Aphelinidae): a charismatic new parasitoid of Aleurocybotus Quaintance & Baker (Hemiptera, Aleyrodidae) from Florida. Journal of Hymenoptera Research 94: 89-104. https://doi.org/10.3897/jhr.94.94677
Maximum likelihood cladogram of the 28S-D2-3 region in 71 Encarsia and two outgroup species (1,070 sites, SYM+R3)
Processing steps to generate a Digital Surface Model based on SPOT-7 tri-stereo images published in the study "An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcan Copahue (Argentina & Chile)" in the Journal of South American Earth Sciences https://doi.org/10.1016/j.jsames.2022.104138
<p>The Digital Surface Model (DSM) was created from SPOT-7 tri-stereo images for the Copahue volcano between the border of Argentina and Chile. Two versions of the DSM are provided: an unfiltered product and a final, filtered product. The final product has a spatial resolution of 5-m and was used for lahar inundation modeling for the Copahue volcano (Viotto, Toyos, and Bookhagen 2022, <a href="https://doi.org/10.1016/j.jsames.2022.104138">https://doi.org/10.1016/j.jsames.2022.104138</a> : An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at Volcán Copahue (Argentina & Chile). <em>Journal of South American Earth Sciences</em> ). The dataset provided should be cited together with the article. </p> <p><strong>DSM processing </strong></p> <p>The source images were given by a SPOT-7 snow- and cloud-free triplet (Nadir, Backward and Forward) of 1.5 m spatial resolution from 19 April 2018 (SPOT Image, Airbus Defence and Space GmbH, distributed by CONAE; Dataset ID: <em>SEN_SPOT7_20180419_142955500_000</em>, delivered by CONAE as <em>DS_SPOT7_20180419</em>).</p> <p>The data were processed with the suite of digital photogrammetry tools AMES Stereo Pipeline ASP (Beyer et al., 2018). The procedure for the generation of the DSM is summarized by following steps: </p> <ol> <li> <p>The orbital parameters (RCP models) were adjusted using the bundle adjustment tool with no ground control points, since they were unavailable.</p> </li> <li> <p>The scenes were map-projected onto the NASADEM (spatial resolution of 30 m) elevation dataset, assisted by the results of the orbital adjustment in Step 1.</p> </li> <li>The stereo correlation of the map-projected scenes including the results of the adjusted orbital parameters, was performed three times, using as first scene (i.e., primary image) the nadir (N), backward (B), and forward (F) images . In each run, the order of images to perform the stereo correlation was: N-F-B, F-N-B, and B-N-F. Thus, three point clouds were generated. Specific ASP correlator settings (other than defaults parameters; for details see the provided stereo-default file) were set in the following way: <em>Correlation Kernel</em>: 15 x 15 pixels; <em>Sub-pixel Refinement Kernel</em>: 21 x 21 pixels; <em>Subpixel Refinement Mode</em>: 2 (Weighted Affine Adaptive Window Correlator EM)</li> <li> <p>The three point clouds were merged into one point cloud with a regular grid of 5 m (unfiltered product, known as <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em>).</p> </li> </ol> <p>The quality of the final point cloud was assessed by comparing the unfiltered DSM with a spatial resolution of 12-m against the WorldDEM<sup>TM</sup> elevation dataset (Collins et al., 2015). The WorldDEM was provided by Airbus Defence and Space GmbH under license for the scope of the Viotto et al., 2022 study. The comparison of the pixel-to-pixel heights above the ellipsoid (WGS84) between the two datasets resulted in a mean difference of 0.67 m and a standard deviation of +/- 4.82 m. </p> <p>Comprehensive details on the methodologies evaluated to create the dataset with ASP, can be found in the corresponding master's thesis “Topografía digital y modelado de lahares en el Volcán Copahue, Argentina-Chile” from S. Viotto (link: https://rdu.unc.edu.ar/handle/11086/15384). Recommended literature about processing DEMs from SPOT imagery is given by Mueting et al., 2021 (<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330</a>). </p> <p><strong>Creation of the Final, Filtered DSM product</strong></p> <p>The corrections and improvements applied to the unfiltered product to create the final, filtered DSM (named DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif) are summarized by following steps. </p> <p> </p> <ol> <li> <p><em>Water Bodies Delineation</em></p> </li> </ol> <p>The delineation of the water bodies was based on a mask created from the free access water bodies datasets provided by the Instituto Geográfico Nacional of Argentina (<a href="https://www.ign.gob.ar/NuestrasActividades/InformacionGeoespacial/CapasSIG">https://www.ign.gob.ar/ NuestrasActividades/InformacionGeoespacia l/CapasSIG</a>) and by the Ministerio de Bienes Nacionales in Chile ( <a href="https://www.ide.cl/index.php/aguas-continentales/item/1508-catastro-de-lagos">https://www.ide.cl/index.php /aguas-continentales/item/1508-catastro-de-lagos</a>). A total of 45 lakes within the area of interest were considered. Lakes with areas below or equal to 25 m2 were smoothed with a median filter in the last step. Lakes with areas above this threshold were filled in with a constant value and their borders were smoothed with a median filter to provide smooth shorelines.</p> <p><em>2 . Void Filling</em></p> <p>Voids (other than water bodies) were filled with the tool “Close Gaps” from Saga GIS software. </p> <p><em>3. Smoothing</em></p> <p>Finally, the elevation dataset was smoothed with a median filter using a 3 x 3 pixel window, excluding water bodies filled in the step 1. </p> <p><strong>Final Remarks and Suggestion</strong></p> <p>The quality assessment of the final version by visual inspection of the hillshades suggested an improvement of the signal to noise ratio. However, the void filling process may be improved.</p> <p><br> </p> <p><strong>Dataset Description</strong></p> <table align="center"> <caption> </caption> <tbody> <tr> <td>Digital Surface Models</td> <td> <p>No Data Value = -9999</p> <p>Format = float 32 bit</p> <p>File Format = GeoTiff</p> <p>Vertical Datum: WGS84</p> <p>Projection information: EPSG 32719 (UTM19S)</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>) </p> <p>Versions: </p> <ul> <li> <p>Unfiltered product: without corrections <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em></p> </li> <li> <p>Final, filtered product: smoothed and void filled <em>DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</em></p> </li> </ul> </td> </tr> <tr> <td>Water Bodies Mask</td> <td> <p>No Lake Value = 0</p> <p>Lakes Values = 1 to 45</p> <p>File Format= GeoTiff</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>)</p> <p>Projection information : EPSG 32719 (UTM19S)</p> <p><em>WB_mask_5m_UTM19S.tif</em></p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>Repository structure</strong></p> <p>|__ 01_Scripts</p> <p> |+ run21_CopahueDSM_AMES_sviotto.sh</p> <p> |+ stereo.default</p> <p>|__ 02_DSMs</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_raw.tif</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</p> <p> |+ WB_mask_5m_UTM19S.tif</p> <p><strong>References</strong></p> <p>Beyer, R. A., Alexandrov, O., & McMichael, S. (2018). The Ames Stereo Pipeline: NASA's open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537– 548. <a href="https://doi.org/10.1029/2018EA000409">https://doi.org/10.1029/2018EA000409</a></p> <p>Collins, J., Riegler, G., Schrader, H., Tinz, M., 2015. Applying terrain and hydrological editing to TanDEM-X data to create a consumer-ready worlddem product. Int. Arch. Photogram. Rem. Sens. Spatial Inf. Sci. 40 (7), 1149. https://doi.org/10.5194/isprsarchives-XL-7-W3-1149-2015.</p> <p>Mueting, A., Bookhagen, B., & Strecker, M. R. (2021). Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina. <em>Journal of Geophysical Research: Earth Surface</em>, 126, e2021JF006330. <a href="https://doi.org/10.1029/2021JF006330">https://doi.org/10.1029/2021JF006330</a></p> <p>Viotto, S., Toyos, G., & Bookhagen, B. (2022). An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at volcán copahue (Argentina & Chile). Journal of South American Earth Sciences, 104138. https://doi.org/10.1016/j.jsames.2022.104138</p> <p> </p> <p> </p>
Scholastica survey 2022: The state of journal production and access
<p>Responses from the 2022 survey "The State of Journal Production and Access" conducted by Scholastica. </p> <p>"The State of Journal Production and Access" is a global survey that spans all scholarly publishing disciplines and welcomes feedback from publishing programs of all sizes. The survey representation has been wide-reaching with responses from members of scholarly publishing organizations in 28 countries in various roles, ranging from senior leaders to journal editors to technical staff. The goal of this survey is to help society and university journal publishers and stakeholders gauge the current state of production and access among independent publishing organizations and what they are prioritizing in the future.</p>
Data for: Five decades of biogeography: A view from the Journal of Biogeography
<p>Since the first issue of <em>Journal of Biogeography</em> (JBI) was published in 1974, the discipline and its eponymous journal have grown in scope and consequence. On this 50th anniversary of the journal, we reflect on changes in biogeography and publishing, describe trends of the past five decades, and present lists of the 50 most-cited articles from JBI's back catalogue. We describe current initiatives intended to chart a course for continued success in the coming 50 years, during what may well be a period of global biogeographic crises.</p>
Data set for the journal article: The Spatial Distribution of Cobalt Phthalocyanine and Copper Nanocubes Controls the Selectivity towards C2 Products in Tandem Electrocatalytic CO2 Reduction
<p>Data set for the journal article:</p> <p>The coupling of CO-generating molecular catalysts with copper electrodes in tandem schemes is a promising strategy to boost the formation of multi-carbon products in the electrocatalytic reduction of CO<sub>2</sub>. While the spatial distribution of the two components is important, this aspect remains underexplored, especially for molecular-based tandem systems. Herein, we address this knowledge gap by studying tandem catalysts comprising Co-phthalocyanine (CoPc) and Cu nanocubes (Cu<sub>cub</sub>). In particular, we identify the importance of the relative spatial distributions of the two components on the performance of the tandem catalyst by preparing CoPc-Cu<sub>cub</sub>/C, wherein the CoPc and Cu<sub>cub</sub> share an interface, and CoPc-C/Cu<sub>cub</sub>, wherein the CoPc is loaded first on carbon black (C) before mixing with the Cu<sub>cub</sub>. The electrocatalytic measurements of these two catalysts show that the faradaic efficiency towards C<sub>2 </sub>products almost doubles for the CoPc-Cu<sub>cub</sub>/C, whereas it decreases by half for the CoPc-C/Cu<sub>cub</sub>, compared to the Cu<sub>cub</sub>/C. Our results highlight the importance of a direct contact between the CO-generating molecular catalyst and the Cu to promote C-C coupling, which hints at a surface transport mechanism of the CO intermediate between the two components of the tandem catalyst instead of a transfer via CO diffusion in the electrolyte followed by re-adsorption.</p>
Supplementary material 7 from: Herrera-Mesías F, Ep Jarboui IK, Weigand AM (2022) A metabarcoding framework for wild bee assessment in Luxembourg. Journal of Hymenoptera Research 94: 215-246. https://doi.org/10.3897/jhr.94.84617
Species delimitation congruence, comparing Linnaean species assignment of the original sequences retrieved from BOLD v/s results of MOTU clustering
Supplementary material 1 from: Herrera-Mesías F, Ep Jarboui IK, Weigand AM (2022) A metabarcoding framework for wild bee assessment in Luxembourg. Journal of Hymenoptera Research 94: 215-246. https://doi.org/10.3897/jhr.94.84617
In silico penalty scores, barcode coverage and congruency analysis of the wild bee species of Luxembourg
Supplementary material 3 from: Herrera-Mesías F, Ep Jarboui IK, Weigand AM (2022) A metabarcoding framework for wild bee assessment in Luxembourg. Journal of Hymenoptera Research 94: 215-246. https://doi.org/10.3897/jhr.94.84617
Summary and metadata of the wild bee samples from Luxembourg and Germany used in the mock communities
Supplementary material 1 from: Lahey Z, Chen H, Dowton M, Austin AD, Johnson NF (2023) The genome of the egg parasitoid Trissolcus basalis (Wollaston) (Hymenoptera, Scelionidae), a model organism and biocontrol agent of stink bugs. Journal of Hymenoptera Research 95: 31-44. https://doi.org/10.3897/jhr.95.97654
Genome of the egg parasitoid Trissolcus basalis (Wollaston) (Hymenoptera, Scelionidae), a model organism and biocontrol agent of stink bugs
Supplementary material for Journal of Fungi (Jof-2078054)
<p>Supplementary material for Journal of Fungi (Jof-2078054). Supplementary Figures S1-S6; and Tables S1, S2 and S3.</p>
Data products associated with: Tamburo, Withers, Dalba, Moore, and Koskinen (2023) Cassini radio occultation observations of Saturn's ionosphere: Electron density profiles from 2005 to 2013, Journal of Geophysical Research, doi:10.1029/2023JA031310
<p>These data products are associated with Tamburo, Withers, Dalba, Moore, and Koskinen (2023) Cassini radio occultation observations of Saturn’s ionosphere: Electron density profiles from 2005 to 2013, Journal of Geophysical Research, doi:10.1029/2023JA031310. At the time of writing, this manuscript is under review. In the future, these data products will be submitted for archiving at the NASA Planetary Data System (PDS).</p> <p> </p>
Data for the Journal article "Reduced whereas still noteworthy atmospheric pollution of trace elements in China"
<p>This dataset provides the trace elements emission inventory with 27km resolution for China in 2017, the model simulated concentrations of trace elements for China in 2017 and the associated health risks of trace elements for China in 2017.</p>
Replication package of: 'When information conflicts with obligations: the role of motivated cognition' ECONOMIC JOURNAL
<p>Final_Ramadan_Survey.dta is the dataset from the survey experiment described in the paper.</p> <p>Final_Ramadan_Admin.dta is the dataset that includes exam takers’ score in the College Entrance Exam.</p>
DAta set. Fallen Journals
<p>Producción de las universidades españolas en el periodo 2018-2022, en las revistas expulsadas de Web of Science en 2023. Se incluye le listado de autores que tienen 6 o más trabajos.</p>
Data from: Collective protection against the type VI secretion system in bacteria (The ISME Journal 2023)
<p>Raw experimental data as presented in Granato, Smith & Foster The ISME Journal 2023.</p> <p>Data used to prepare each figure can be found under separate tabs.<br> Tabs are labelled with their corresponding figure number in the manuscript.</p>
Supplementary material 6 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 6 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 5 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 5 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 3 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 3 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 2 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
Supplementary material 2 from: Tanaka S (2023) Biology of Patanga japonica (Orthoptera, Acrididae): Nymphal growth, host plants, reproductive activity, hatching behavior, and adult morphology. Journal of Orthoptera Research 32(1): 93-108. https://doi.org/10.3897/jor.32.95753
ScienceDex guides
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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.