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1,291 results for “gap”
CoNEXT21: Mind the Gap: Multi-hop IPv6 over BLE in the IoT - Experiment Result Data
<p>This dataset contains the all raw experiment data that was used in our paper "Mind the Gap: Multi-hop IPv6 over BLE in the IoT" published at CoNEXT21.</p>
Validation of temperature-controlled rheo-MRI measurements in a sub-mm gap Couette cell
<p>Validation of temperature-controlled rheo-MRI measurements in a sub-mm gap Couette cell</p>
Monthly averaged 1-km gap-free AOD, PM2.5, and PM10 grids in China, v1 (2000–2020)
<p>A Long-term Gap-free High-resolution Air Pollutants concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and earth system science analysis. In the current release of LGHAP aerosol dataset (LGHAP.v1), we provide 21-year-long (2000–2020) gap free AOD, PM2.5 and PM10 concentration data with monthly 1-km resolution covering the land area of China. The dataset was generated from the daily gap free AOD (https://doi.org/10.5281/zenodo.5652257) that was derived through an integration of a set of data tensors of AOD and other related datasets such as air pollutants concentration and atmospheric visibility acquired from diversified sensors or platforms via a machine learned regression model. The dataset was provided in the NetCDF format, while data in each individual year were archived in a zip file. Python, Matlab, R, and IDL codes were also provided to help users read and visualize the LGHAP data.</p>
Distribution. Continuous distribution in W & C African rainforest blocks also including Dahomey Gap and Bioko I; reaches as easternand southernmost boundaries SW Kenya, extreme W Tanzania, NW Zambia, and N Angola. in Manidae
Distribution. Continuous distribution in W & C African rainforest blocks also including Dahomey Gap and Bioko I; reaches as easternand southernmost boundaries SW Kenya, extreme W Tanzania, NW Zambia, and N Angola.
Distribution. Discontinuously distributed, from Senegal to Ghana in W Africa, and in the C African rainforest block from Cameroon to Uganda, W Kenya, and W Tanzania, and south to extreme NW Angola, also present in Bioko I. Sightings from Dahomey Gap and S Nigeria remain unconfirmed. in Manidae
Distribution. Discontinuously distributed, from Senegal to Ghana in W Africa, and in the C African rainforest block from Cameroon to Uganda, W Kenya, and W Tanzania, and south to extreme NW Angola, also present in Bioko I. Sightings from Dahomey Gap and S Nigeria remain unconfirmed.
Data from: A burning issue: Savanna fire management can generate enough carbon revenue to help restore Africa's rangelands and fill protected area funding gaps
<p>Many savanna-dependent species in Africa including large herbivores and apex predators are at increasing risk of extinction. Achieving effective management of protected areas (PAs) in Africa where lions live will cost an estimated USD >$1-2 B/year in new funding. We explored the potential for fire management-based carbon-financing programs to fill this funding gap and benefit degrading savanna ecosystems. We demonstrated how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods ranging from USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M–$1.7 B/year (at USD $13/ton). We highlighted variable but significant PCR for savanna PAs from USD $1.5–$44.4 M/year per PA. We suggest investing in fire management programs to jump-start the United Nations Decade of Ecological Restoration to help restore degraded African savannas and conserve imperiled keystone herbivores and apex predators. </p>
Supplementary material 1 from: Trégarot E, Failler P (2021) Adequacy of ecosystem services assessment tools and approaches to current policy needs and gaps in the European Union Overseas entities. One Ecosystem 6: e74170. https://doi.org/10.3897/oneeco.6.e74170
Selection of MAES tools and approaches to facilitate the uptake of Ecosystem Services in EU Overseas entities
Gap Directo y Gap Indirecto
<p>En este vídeo se describen los términos Gap Directo y Gap indirecto y se muestran cuales son sus diferencias.</p>
DIFERENCIAS ENTRE UN MATERIAL CON GAP DIRECTO Y UN MATERIAL CON GAP INDIRECTO
<p>DIFERENCIAS ENTRE UN MATERIAL CON GAP DIRECTO Y UN MATERIAL CON GAP INDIRECTO</p>
Cómo afecta el gap de una célula de Silicio
<p>En esta presentación se pretende mostrar cómo afecta la dismunución del gap al comportamiento de la célula de silicio.</p>
Diferencia entre el gap indirecto y el gap directo
<p>En este video se explican las diferencias habidas entre una célula con material de gap indirecto y otra con material de gap directo</p>
A new bohaiornithid-like bird from the Lower Cretaceous of China fills a gap in enantiornithine disparity
<p>A new enantiornithine – <em>Musivavis amabilis</em> n. gen. n. sp. – is reported from the Lower Cretaceous Jehol Biota in western Liaoning, China. The new taxon is similar to the bohaiornithids in the robust subconical teeth, bluntly expanded omal ends of the furcula, caudolaterally oriented lateral trabeculae with triangular distal ends of the sternum, and a robust second pedal digit, yet it differs from members of Bohaiornithidae in several features recalling other enantiornithine lineages, such as the acuminate rostral ramus of maxilla, the shape of the coracoid lateral margin, the presence of craniolateral processes on the sternum, the proportions of the manual phalanges, and the unspecialized third pedal ungual phalanx. A comprehensive phylogenetic analysis of Mesozoic birds shows that homoplasy significantly impacts the reconstruction of enantiornithine relationships. When all phylogenetic characters are considered of equal weight, <em>Musivavis</em> is reconstructed in a lineage related to a radiation of large-bodied enantiornithines including Bohaiornithidae and Pengornithidae. Alternative scenarios based on progressive downweighting of the homoplastic characters support more basal placements of the pengornithids among Enantiornithes, but do not alter the affinity of <em>Musivavis</em> as a member of the "bohaiornithid-grade" group.</p>
Data from: Sea turtle epibiosis: Global patterns and knowledge gaps
<p>This database serves to summarize over 100 years of sea turtle epibiont research. We conducted a two-tiered literature search to compile all records of sea turtle-epibiont interactions along with their associated metadata. A structured search was conducted in Web of Science, Google Scholar, and Sea Turtle Online Bibliography (Archie Carr Center for Sea Turtle Research, University of Florida), then an unstructured literature search was conducted by reviewing the reference lists of all relevant publications and reports from the structured search. We included any peer-reviewed scientific article, thesis/dissertation, conference presentation, and official report that contained information on sea turtle epibiosis. From each applicable reference, we extracted data on all reported sea turtle-epibiont interactions according to the data categories and descriptions listed below (Table 1 in Robinson and Pfaller 2022; doi link when available). We constrained our database to only include records of sea turtle-epibiont interactions from (1) turtles surveyed in the wild, (2) animal epibionts (i.e., Kingdom Animalia), and (3) macro-epibionts (>1 mm). For the seven global sea turtle species, we identified 304 studies conducted between 1886 and 2020 that included a combined total of 1717 sea turtle-epibiont interactions involving 374 unique epibiont taxa from 11 Phyla. </p>
Supplementary Figure 1: The road to FAIR genomes: a gap analysis of NGS data generation and sharing in the Netherlands
<p><em>Supplementary Figure 1: a flow chart conceptualizing the gap analysis. A generic NGS process diagram was created, based on a commonly used care workflow (Step 1). Next, a questionnaire about the inventory of (meta)data standards and retrieval of gaps was drafted (Step 2), which together with the process diagram was used as a basis for the subsequent interviews (Step 3). In parallel with the first three steps, a short literature review was performed (Step 4). The interviews were processed and current gaps were identified, anonymized and classified (Step 5). Finally, the results are shared with the community through presentations, publications and suggestions for next steps for addressing the identified gaps.</em></p>
Mind the Gap: Reach and Mechanical Diversity of Searcher Shoots in Climbing Plants
<p>This dataframe corresponds to the article Hattermann et al. "Mind the Gap: Reach and Mechanical Diversity of Searcher Shoots in Climbing Plants"</p> <table> <tbody> <tr> <td>Variable Abbreviation</td> <td>Description of the variable</td> <td>Type of variable</td> <td>Units</td> </tr> <tr> <td>ID</td> <td>Sample identification label at the shoot level</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>Taxa</td> <td>Species name</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>family</td> <td>Family name</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>ds</td> <td>Biomes where shoots have been sampled - "temperate" corresponds to Montpellier, south of France and tropical corresponds to Sinnamary, French Guiana </td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>Leaf_expanded</td> <td>Indicates whether a shoot has been considered with at least one expanded leaf (1) or with no leaves (0)</td> <td>Discrete variable</td> <td> </td> </tr> <tr> <td>Group</td> <td>Functional group based on the climbing habit at the species level</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>reach</td> <td>Distance in a straight line from the base to the apex of the searcher shoot (here called the “reach”)</td> <td>Continuous variable</td> <td>cm</td> </tr> <tr> <td>length</td> <td>Length of the searcher shoot</td> <td>Continuous variable</td> <td>cm</td> </tr> <tr> <td>A1_diam_basal</td> <td>Basal diameter of the searcher shoot (measured at the base of the searcher shoot)</td> <td>Continuous variable</td> <td>mm</td> </tr> <tr> <td>N_leaves</td> <td>Number of leaves</td> <td>Discrete variable</td> <td> </td> </tr> <tr> <td>seco_mom_I</td> <td>Second moment of area (I) of the measured basal segment (in 4-point bending) of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>young_mod_E</td> <td>Structural Young's modulus (E) of the measured basal segment (in 4-point bending) of the searcher shoot from I and EI</td> <td>Continuous variable</td> <td>MN.m-2</td> </tr> <tr> <td>flex_rig_EI</td> <td>Flexural bending rigidity (EI) of the measured basal segment (in 4-point bending) of the searcher shoot</td> <td>Continuous variable</td> <td>N.mm^2</td> </tr> <tr> <td>total_freshmass</td> <td>Freshmass of the searcher shoot (including stems, laminas and petioles)</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>lam_freshmass</td> <td>Lamina freshmass borne by the searcher shoot</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>total_drymass</td> <td>Total drymass of the searcher shoot (including stems, laminas and petioles)</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>lam_drymass</td> <td>Lamina drymass borne by the searcher shoot</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>lam_area</td> <td>Lamina fresh area of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Pith</td> <td>Medullary parenchyma cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Pith_fibers</td> <td>Medullary fibre cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Xylem</td> <td>Xylem vessel and fibres cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Xylem_ray</td> <td>Xylem parenchymatous ray cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Phloem</td> <td>Phloem cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Cortex</td> <td>Cortical parenchyma cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Sclereids</td> <td>Cortical sclereids cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Cort_fibers</td> <td>Cortical fibre cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Collenchyma</td> <td>Collenchyma cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Periderm</td> <td>Periderm cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>I_Pith</td> <td>Medullary parenchyma second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Pith_fibers</td> <td>Medullary fibre second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Xylem</td> <td>Xylem vessel and fibres second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Xylem_ray</td> <td>Xylem parenchymatous ray second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Phloem</td> <td>Phloem second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Cortex</td> <td>Cortical parenchyma second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Cort_fibers</td> <td>Cortical sclereid second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Sclerites</td> <td>Cortical fibre second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Collenchyma</td> <td>Collenchyma second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Periderm</td> <td>Periderm second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> </tbody> </table>
Distribution. Known only from three localities in SE Ghana and SW Kenya, with a gap of ¢.4000 km between them. in Vespertilionidae
Distribution. Known only from three localities in SE Ghana and SW Kenya, with a gap of ¢.4000 km between them.
Subspecies and Distribution. H. uw. underwoodi Thomas, 1903 — disjunct from 8S Mexico (Veracruz) to E Guatemala, S Belize, and N & W Honduras, and from SE Nicaragua to W Panama. H. u. minor C. J. Phillips & J. K. Jones, 1971 — Pacific slope in Mexico, from Nayarit and Jalisco to S Oaxaca. A.p. discontinuous distribution with gap in Nicaragua might just reflect lack of data because Underwood's Long-tongued bat always occursat rather low densities and is therefore not very often captured. in Phyllostomidae
Subspecies and Distribution. H. uw. underwoodi Thomas, 1903 — disjunct from 8S Mexico (Veracruz) to E Guatemala, S Belize, and N & W Honduras, and from SE Nicaragua to W Panama. H. u. minor C. J. Phillips & J. K. Jones, 1971 — Pacific slope in Mexico, from Nayarit and Jalisco to S Oaxaca. A.p. discontinuous distribution with gap in Nicaragua might just reflect lack of data because Underwood's Long-tongued bat always occursat rather low densities and is therefore not very often captured.
Distribution. It ranges through temperate zone forests and paramos from the Cordillera Central in C Colombia through the Cordillera Oriental of Ecuador to the eastern Andean cloud forests in Peru, southward to Junin department. The exact range is unknown and there are obvious distributional gaps. One major natural gap is the dry forest south of the Huancabamba depression, which separates the northern population from the main Peruvian population. in Cervidae
Distribution. It ranges through temperate zone forests and paramos from the Cordillera Central in C Colombia through the Cordillera Oriental of Ecuador to the eastern Andean cloud forests in Peru, southward to Junin department. The exact range is unknown and there are obvious distributional gaps. One major natural gap is the dry forest south of the Huancabamba depression, which separates the northern population from the main Peruvian population.
the dataset for "Investigating multiple observations around a seismic gap during the Lushan earthquake in Sichuan, China"
<p>The relocation of the earthquake before and after Lushan earthquakes.</p>
Eficiencia límite en células de gap simple
<p>Cómo alcanzar la eficiencia límite con células de gap simple según el Modelo de Balance Detallado.</p>
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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.