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132 results for “Continental margin”
FIGURE 4 in Capitellidae (Annelida) from the Brazilian Continental Margin (SW Atlantic): new occurrences of three genera and description of new species
FIGURE 4. Peresiella megapapilata sp. nov. (A) Anterior region, lateral view; (B) Thoracic region, lateral view; (C) Anterior region, dorsal view; (D) Methyl Green staining pattern; (E) Modified spatulate chaetae; (F) (G) Notopodial hooded hook, frontal view; (H) Neuropodial hooded hook, top view. A: abdomen. Ch: chaetiger. NeL: neuropodial lobe. NoL: notopodial lobe. Pa: palpode. Pb: proboscis. Pe: peristomium. Pr: prostomium. SpCh: spatulate chaetae. T: thorax. Scale bars: A, 0.2 mm; 1 mm; B, D, 0.5 mm; C, 0,1 mm; E, 10 µm; F, G, 2 µm; H, 5 µm.
FIGURE 3 in Capitellidae (Annelida) from the Brazilian Continental Margin (SW Atlantic): new occurrences of three genera and description of new species
FIGURE 3. Mastobranchus braziliensis sp. nov. (A) Anterior region, lateral view; (B) Thoracic region, lateral view; (C) Abdominal region, dorsal view; (D) Abdominal region, ventral view; (E) Posterior end; (F) Methyl Green staining pattern; (G) Notopodial hooded hooks, lateral view; (H) Notopodial hooded hooks, frontal view; (I) Neuropodial hooded hooks, lateral view; (J) Neuropodial hooded hooks, frontal view. A: abdomen. Br: branchiae. Ch: chaetiger. MLL: mid-lateral lobe. NeL: neuropodial lobe. NoL: notopodial lobe. Pa: palpode. Pe: peristomium. Pr: prostomium. T: thorax. Black arrows: genital pores. Scale bars: A, E, 0.2 mm; B, C, D, F, 0.5 mm; G, H, I, J, 5 µm.
FIGURE 2 in Capitellidae (Annelida) from the Brazilian Continental Margin (SW Atlantic): new occurrences of three genera and description of new species
FIGURE 2. Mastobranchus loii (A) Anterior region, lateral view; (B) Thoracic region, dorsal view; (C) Thorax-Abdomen division, dorsal view; (D) Thorax-Abdomen division, lateral view; (E) Abdominal region, dorsal view; (F) Posterior end. A: abdomen. Br: branchiae. Ch: chaetiger. MLL: mid-lateral lobe. NeL: neuropodial lobe. NoL: notopodial lobe. Pe: peristomium. Pr: prostomium. T: thorax. Scale bars: A, B, C, D, E, F, 0.5 mm.
FIGURE 1 in Capitellidae (Annelida) from the Brazilian Continental Margin (SW Atlantic): new occurrences of three genera and description of new species
FIGURE 1. Morphology of the studied genera. (A) Modified spatulate chaetae of Peresiella megapapilata sp. nov., lateral view; (B) Peresiella megapapilata sp. nov., lateral view; (C) Mastobranchus braziliensis sp. nov., lateral view; (D) Polymastigos profundus sp. nov., dorsal view on thorax and lateral view on abdomen. A: abdomen. Ch: chaetiger. NeL: neuropodial lobe. Pe: peristomium. Pr: prostomium. T: thorax. Scale bars: A, 10 µm; B, C, D, 1.0 mm.
FIGURE 5 in Capitellidae (Annelida) from the Brazilian Continental Margin (SW Atlantic): new occurrences of three genera and description of new species
FIGURE 5. Polymastigos profundus sp. nov. (A) Thoracic region, lateral view; (B) Anterior end, lateral view; (C) Abdominal region; lateral view; (D) Abdominal region; dorsal view; (E) Abdominal region; ventral view; (F) Methyl Green staining pattern, lateral view; (G) Methyl Green staining pattern, ventral view; (H) Notopodial hooded hook, frontal view; (I) Neuropodial hooded hook, frontal view. A: abdomen. Ch: chaetiger. GP: genital pores. LG: lateral groove. NeL: neuropodial lobe. NoL: notopodial lobe. Pa: palpode. Pb: proboscis. Pe: peristomium. Pr: prostomium. T: thorax. White arrows: genital pores. Scale bars: A, F, 1 mm; B, E, 0.2 mm; C, D, G, 0.5 mm; H, I, 5 µm.
Radiogenic heat production dataset of borehole CSDP-2 in the South Yellow Sea, East Asian continental margin
<p>Appendix A includes radiogenic heat production Data of CSDP-2 borehole of 302 samples in the South Yellow Sea, Appendix B includes radiogenic heat production Data of 84 samples in the Yangtze Block in Nanjing and Chaohu</p>
Chemical characterization of deep-sea corals from the continental slope of Santos Basin (southeastern Brazilian upper margin)
<p>Supplementary Material of the article "Chemical characterization of deep-sea corals from the continental slope of Santos Basin (southeastern Brazilian upper margin)":</p> <p>- Supplementary Material Table S1: Correlation between elementary ratios (mmol mol<sup>-1</sup>), carbon and oxygen stable isotopics composition (δ<sup>13</sup>C and δ<sup>18</sup>O, ‰) in corals and environmental parameters: temperature (T ºC), salinity (Sal) and depth (Dep; m). Pearson's correlation coefficient (r) \ p value. Significant correlations in bold.</p>
Seismic velocity models (Vp, Vs and Vp/Vs) of the Beaufort Sea continental margin
<p>This folder contains the local tomography software (LOTOS, Koulakov et al. 2009), three-dimensional seismic velocity models (Vp, Vs and Vp/Vs) and the earthquake relocations presented in "Seismic evidence for a weakened thick crust at the Beaufort Sea continental margin" submitted to <em>Geophysical Research Letters</em>. Please consult the detailed description of these files provided by I. Koulakov (http://www.ivan-art.com/science/LOTOS/).</p> <p>Koulakov, I. (2009). LOTOS code for local earthquake tomographic inversion: Benchmarks for testing tomographic algorithms. Bulletin of the Seismological Society of America, 99 (1), 194–214. doi: https://doi.org/10.1785/0120080013</p>
Underlying data for Figures 1 - 6 in "Glacial troughs as centres of organic carbon accumulation on the Norwegian continental margin"
<p>This repository contains source data underlying Figures 1 - 6 in the publication titled "Glacial troughs as centres of organic carbon accumulation on the Norwegian continental margin".</p>
Input data for predicted sedimentary environments on the Norwegian continental margin
<p>Input and output data relating to R workflow for predicting sedimentary environments on the Norwegian continental margin (https://github.com/diesing-ngu/SedEnv). The following files are included:</p><p><strong>SedEnv_4km_MaxCombArea_point_20230622.shp</strong> - Point shapefile of the response data (substrate type). Note that these data points were derived from mapped products and are not sample points as such. </p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced TIFF-file of predicted mud content. Used as an additional predctor.</p>
Predicted mud content on the Norwegian continental margin
<p>Output data relating to R workflow for predicting mud content on the Norwegian continental margin (https://github.com/diesing-ngu/GSMgrids). The following files are included:</p><p><strong>alrM_2023-10-31.tif </strong>- Georeferenced Tiff-file of the predicted additive log-ratio model</p><p><strong>alrM_aoa2023-10-31.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced Tiff-file of the mud content</p>
Predicted organic carbon content on the Norwegian continental margin
<p>Output data relating to R workflow for predicting organic carbon content on the Norwegian continental margin (https://github.com/diesing-ngu/TOC). The following files are included:</p> <p><strong>OC0-10cm_median_2024-02-16.tif</strong> - Georeferenced Tiff-file of the predicted organic carbon content in the upper 10 cm of the sediment column</p> <p><strong>OC0-10cm_PI90_2024-02-16.tif</strong> - Georeferenced Tiff-file of the 90% prediction interval. Can be used as a measure of uncertainty.</p> <p><strong>OC0-10cm_AOA_2024-02-16.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p> <p><strong>OC0-10cm_AOA_2024-02-16.shp</strong> - Same as above but as polygon shapefile</p>
Input data for predicted sediment accumulation rates on the Norwegian continental margin
<p>Input data relating to R workflow for predicting sediment accumulation rates on the Norwegian continental margin (https://github.com/diesing-ngu/SedRates). The following files are included:</p><p><strong>norway_sar_2023-08-28.csv</strong> - Data on sediment accumulation rates from the <a href="https://doi.org/10.5194/essd-15-4105-2023">MOSAIC v2.0</a> database</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced TIFF-file of predicted mud content. Used as an additional predctor.</p><p><strong>SedEnv3_probabilities_2023-07-01.tif </strong>- Georeferenced Tiff-file of the prediction probabilities of the predicted sedimentary environments. Used as additional predctors.</p><p><strong>SedEnv3_max_probabilities_2023-07-01.tif </strong>- Georeferenced Tiff-file of the maximum probabilities, i.e., the probability of the class that was mapped.</p><p><strong>SedEnv3_AOA_2023-07-01.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p>
Input data for predicted dry bulk densities on the Norwegian continental margin
<p>Input data relating to R workflow for predicting dry bulk densities on the Norwegian continental margin (https://github.com/diesing-ngu/DBD). The following files are included:</p><p><strong>DBD_2023-07-21.csv </strong>- Data on dry bulk densities in surface sediments</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>GrainSizeReg_folk8_probabilities_2023-06-28.tif</strong> - Georeferenced TIFF-file of the prediction probabilities of the predicted substrate classes. Used as additional predctors.</p>
Input data for predicted substrate types on the Norwegian continental margin
<p>Input data relating to R workflow for predicting substrate types on the Norwegian continental margin (https://github.com/diesing-ngu/GrainSizeReg). The following files are included:</p><p><strong>AoI_Harris_mod </strong>- Polygon shapefile delimiting the area of interest</p><p><strong>GrainSize_4km_MaxCombArea_folk8_point_20230628</strong> - Point shapefile of the response data (substrate type). Note that these data points were derived from mapped products and are not sample points as such. </p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p>
Predicted sediment accumulation rates on the Norwegian continental margin
<p>Output data relating to R workflow for predicting sediment accumulation rates on the Norwegian continental margin (https://github.com/diesing-ngu/SedRates). The following files are included:</p> <p><strong>SAR_median_2024-02-15.tif</strong> - Georeferenced Tiff-file of the oredicted sediment accumulation rates</p> <p><strong>SAR_PI90_2024-02-15.tif</strong> - Georeferenced Tiff-file of the 90% prediction interval. Can be used as a measure of uncertainty.</p> <p><strong>SAR_AOA_2024-02-15.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p> <p><strong>SAR_AOA_2024-02-15.shp</strong> - Same as above but as polygon shapefile</p>
Predicted sedimentary environments on the Norwegian continental margin
<p>Output data relating to R workflow for predicting substrate types on the Norwegian continental margin (https://github.com/diesing-ngu/SedEnv). The following files are included:</p><p><strong>SedEnv3_classes_2023-07-01.tif </strong>- Georeferenced Tiff-file of the predicted sedimentary environments</p><p><strong>SedEnv3_probabilities_2023-07-01.tif </strong>- Georeferenced Tiff-file of the prediction probabilities of the predicted sedimentary environments</p><p><strong>SedEnv3_max_probabilities_2023-07-01.tif </strong>- Georeferenced Tiff-file of the maximum probabilities, i.e., the probability of the class that was mapped. Can be used as an indicator of map confidence.</p><p><strong>SedEnv3_AOA_2023-07-01.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p><p><strong>SedEnv3_AOA_2023-07-01.shp</strong> - Same as above but as polygon shapefile</p>
Predicted dry bulk densities on the Norwegian continental margin
<p>Output data relating to R workflow for predicting dry bulk densities on the Norwegian continental margin (https://github.com/diesing-ngu/DBD). The following files are included:</p> <p><strong>DBD0-10cm_median_2024-02-16.tif</strong> - Georeferenced Tiff-file of the Predicted dry bulk densities in the upper 10 cm of the sediment column</p> <p><strong>DBD0-10cm_PI90_2024-02-16.tif</strong> - Georeferenced Tiff-file of the 90% prediction interval. Can be used as a measure of uncertainty.</p> <p><strong>DBD0-10cm_AOA_2024-02-16.tif </strong>- Georeferenced Tiff-file of the area of applicability of the model <a href="https://doi.org/10.1111/2041-210X.13650">(Meyer & Pebesma, 2021)</a></p> <p><strong>DBD0-10cm_AOA_2024-02-16.shp</strong> - Same as above but as polygon shapefile</p>
Input data for predicted organic carbon content on the Norwegian continental margin
<p>Input data relating to R workflow for predicting organic carbon content on the Norwegian continental margin (https://github.com/diesing-ngu/TOC). The following files are included:</p><p><strong>mosaic_2023-04-21.csv</strong> - Data on organic carbon content in surface sediments from the <a href="https://doi.org/10.5194/essd-15-4105-2023">MOSAIC v2.0</a> database</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced TIFF-file of predicted mud content. Used as an additional predctor.</p>
Input data for predicted mud content on the Norwegian continental margin
<p>Input data relating to R workflow for predicting mud content on the Norwegian continental margin (https://github.com/diesing-ngu/GSMgrids). The following files are included:</p><p><strong>gsm_data.csv</strong> - Data on gravel, sand and mud of surface sediments</p><p><strong>MGObsPkt_150_160_170.shp </strong>- Point shapefile of categorical samples</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>GrainSizeReg_folk8_probabilities_2023-06-28.tif</strong> - Georeferenced TIFF-file of the prediction probabilities of the predicted substrate classes. Used as additional predctors.</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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
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