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13,117 results for “Maps”
FIGURES 49–50. Maps. 49 in Taxonomic revision of Schausiana Viette with two new species from Guatemala and notes on biogeography and correlated tectonics (Lepidoptera: Hepialidae)
FIGURES 49–50. Maps. 49, Distribution of endemic Schausiana spp. and Pallas sp. in Central America with respect to the Motagua-Polochic fracture zone, S. chalciope sp. nov.—dark blue, S. maishei sp. nov.—pale blue, Pallas reynaudi—yellow circles. 50, Approximate location of the Guerrero terrane, the Greater Antilles and other island arcs (colored areas) within the Pacific basin ~140 Ma. Hypothetical ancestral range of Schausiana as blue dashed line. Map modified from Clennett et al. (2020) with the inferred addition of the Greater Antilles arcs, including portions that have since accreted to Colombia.
FIGURES 47–48. Distribution maps. 47. D. elongata n in Revision of the Nearctic species of Ditomyia Winnertz and a new species from the Neotropical Region (Diptera: Ditomyiidae)
FIGURES 47–48. Distribution maps. 47. D. elongata n. sp. (yellow star) and D. sohnsi n. sp. (red circle). 48. D. potomaca (green circle) and D. euzona (red square); although no D. euzona specimens were examined from the District of Columbia, because D.C. is the type locality of D. euzona and is the most southern record known for the species, it has been plotted on the map.
FIGURES 5–7. Distribution maps for Metallactus generosus species-group. M. generosus Suffrian, 1866 in Revision of the Metallactus generosus species-group with a preliminary evaluation of the effectiveness of the endophallus morphology in distinguishing critical sibling species (Coleoptera: Chrysomelidae: Cryptocephalinae)
FIGURES 5–7. Distribution maps for Metallactus generosus species-group. M. generosus Suffrian, 1866 (5); M. argentinensis Jacoby, 1907 (6); M. nigroplagiatus new species (7). Grey square: hypothetical location for specimen labelled from 'Brazil'.
Coherent map
<p><strong>Figure 1-5.</strong> <strong>(A)</strong> A twelve-lead electrocardiogram of a PVC and sinus rhythm, and intracardiac electrograms at the successful ablation site. A presystolic potential during the PVC and late potential during SR are recorded by the ablation catheter. The late potential during SR was eliminated after the successful ablation. Coherent vector activation maps annotating the onset of the presystolic potentials during the PVC <strong>(B)</strong> and the offset of the late potentials during SR<strong> (C)</strong>. The ablation catheter at the successful ablation site is shown in the figure. The case number is corresponded to the figure number, except the 2 PVCs (Figures 4 and 5) from the case 4.</p> <p>SR, sinus rhythm; PVC, premature ventricular contraction; LCC, left coronary cusp; RCC, right coronary cusp; ABL, ablation.</p>
Mapping Manuscript Migrations Knowledge Graph
<p>The Mapping Manuscript Migrations (MMM) project transformed three separate datasets into a unified knowledge graph. The source databases include</p> <p>- <a href="https://sdbm.library.upenn.edu">Schoenberg Database of Manuscripts</a> from the Schoenberg Institute for Manuscript Studies,<br> - <a href="http://bibale.irht.cnrs.fr">Bibale database</a> from the Institute for Research and History of Texts, and<br> - <a href="https://medieval.bodleian.ox.ac.uk">Medieval Manuscripts in Oxford Libraries</a>.</p> <p>The Knowledge Graph has been created using the <a href="https://github.com/mapping-manuscript-migrations/mmm-data-conversion">MMM data transformation pipeline</a>. This dataset is available on a public SPARQL endpoint (<em>http://ldf.fi/mmm/sparql</em>) and it can be directly deployed onto a SPARQL endpoint using <a href="https://github.com/mapping-manuscript-migrations/mmm-fuseki">this docker recipe</a>.</p> <p>To test and demonstrate its usefulness, the MMM Knowledge Graph is in use in the <a href="https://mappingmanuscriptmigrations.org/">MMM Semantic Portal</a>.</p> <p><strong>Version History</strong></p> <ul> <li>1.0.0, January 2020.</li> <li>1.1.0, February 2020, Updated Bibale and SDBM source datasets, data processing improvements.</li> <li>2.0.0, May 2020, Updated SDBM source dataset, data processing fixes affecting some generated URIs.</li> <li>2.1.0, September 2020, Updated Bibale and SDBM source datasets, minor data processing bug fixes.</li> <li>2.2.0, January 2021, Updated Oxford source dataset, minor data processing improvements.</li> </ul> <p> </p> <p> </p>
Computational epitope map of SARS-CoV-2 spike protein
<p>Dataset accompanying the publication "Map of SARS-CoV-2 spike epitopes not shielded byglycans" published in XYZ.</p> <p> </p> <p>The dataset contains:</p> <p>1. raw epitope screening scores (README file attached in the archive)</p> <p>2. structure and GROMACS topology and input files for two systems:</p> <p> - 4x SARS-CoV-2 spike protein, glycosylated<br> - 4x SARS-CoV-2 spike protein, non-glycosylated</p> <p> </p>
FIGURE 2 in Description and bioecology of two new species of the genus Cryncus (Orthoptera Gryllidae, Gryllinae) from Cameroon with a key and distribution map of all African species
FIGURE 2. Morphology of Cryncus camerounensis sp. nov.: (A) male head and pronotum, (B) male lateral view of head and pronotum, (C) male forewing, (D) female head and pronotum, (E) female lateral view of head and pronotum, (F) female fore wing, (G) male forewing drawing, (H) male genitalia drawing in dorsal view, (I) male genitalia drawing in ventral view. Scale bars: A: 7 mm; B, C, E: 5 mm;D, 8 mm;F, 11 mm;G, 5 mm; H, I, 500 µm.
FIGURE 3 in Description and bioecology of two new species of the genus Cryncus (Orthoptera Gryllidae, Gryllinae) from Cameroon with a key and distribution map of all African species
FIGURE 3. Morphology of Cryncus desutterae sp. nov.: (A) male head and pronotum, (B) male lateral view of head and pronotum, (C) male fore wing, (D) female head and pronotum, (E) female lateral view of head and pronotum, (F) female forewing, (G) male forewing drawing, (H) male genitalia drawing in dorsal view, (I) male genitalia drawing in ventral view. Scale bars: A, 9 mm; B, 8 mm; C, 5 mm; D, F: 7 mm; E, 6 mm; H, I, 500 µm.
Mapping the Redshift Evolution of Hα Equivalent Width Distributions & RST Grism Surveys
<p>The Hα Equivalent Width (EW) is an observational proxy for the specific star formation rate (sSFR) and can give us valuable insight in regards to bursty star formation histories. Studies find Hα EW anti-correlates with stellar mass and increases in redshift similar to the `main sequence’ and sSFR redshift evolution. However, selection effects may bias the underlying results, such that measurements of the intrinsic correlations are needed. In this talk, I will be presenting a new methodology of constraining EW distributions by simulating emission line galaxies assuming an intrinsic EW distribution and applying selection criteria to match observations drawn from Hα narrowband surveys between z ~ 0.4 and 2. This nicely overlaps with the expected redshift coverage of RST planned surveys. We find EW intrinsically correlates with Hα luminosity and stellar mass, while ignoring selection effect corrections causes a steeper correlation. We also observe an increasing redshift evolution between EW and stellar mass. The correlation between EW and stellar mass is found to reproduce the EW distribution, LF, and SMF at all redshifts probed, which suggests it is shaped by physical processes associated with star formation. I will finish by discussing the implication of our results for RST survey planning by taking into account the effective EW threshold in slitless grism surveys set by the limiting resolving power using the redshift evolution of the EW — stellar mass correlation.</p>
Use of Linux in Education: A Systematic Mapping Study – dataset
<p>The dataset used in the article Use of Linux in Education: A Systematic Mapping Study.</p>
High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles)
<p>On the Caribbean island of St. Eustatius, Coralita (<i>Antigonon leptopus</i>)<i> </i>is an aggressive invasive vine posing major biodiversity conservation concerns. The generation of distribution maps can address these conservation concerns by helping to elucidate the drivers of invasion. We test the use of support vector machines to map the distribution of Coralita on St. Eustatius at high spatial resolution and use this map to identify potential landscape and geomorphological factors associated with Coralita presence. This latter step was performed by comparing the actual distribution of Coralita patches to a random distribution of patches. To train the support vector machine algorithm, we used three vegetation indices and seven texture metrics derived from a 2014 WorldView-2 image. The resulting map shows that Coralita covered 3.18% of the island in 2014, corresponding to an area of 64 ha. The mapped distribution was highly accurate, with 93.2% overall accuracy (Coralita class producer's accuracy: 76.4%, user's accuracy: 86.2%). Using this classification map, we found that Coralita is not randomly distributed across the landscape, occurring significantly closer to roads and drainage channels, in areas with higher accumulated moisture, and on flatter slopes. Coralita was found more often than expected in grasslands, disturbed forest and urban areas, but was relatively rare in natural forest. These results highlight the ability of high spatial resolution data from sensors such as WorldView-2 to produce accurate invasive species, providing valuable information for predicting current and future spread risks and for early detection and removal plans.</p>
MAPS 10–12 in Taxonomic review of Tipula (Vestiplex Bezzi) crane flies (Diptera: Tipulidae) in Mongolia
MAPS 10–12. Distribution maps of T. (Vestiplex) crane flies in Mongolia. 10. T. (Vestiplex) nubeculosa; 11. T. (Vestiplex) pallitergata; 12. T. (Vestiplex) scripta.
MAPS 13–14 in Taxonomic review of Tipula (Vestiplex Bezzi) crane flies (Diptera: Tipulidae) in Mongolia
MAPS 13–14. Distribution maps of T. (Vestiplex) crane flies in Mongolia. 13. T. (Vestiplex) longitudinalis; 14. T. (Vestiplex) virgatula.
MAPS 1–3 in Taxonomic review of Tipula (Vestiplex Bezzi) crane flies (Diptera: Tipulidae) in Mongolia
MAPS 1–3. Distribution maps of T. (Vestiplex) crane flies in Mongolia. 1. T. (Vestiplex) mediovittata; 2. T. (Vestiplex) balioptera; 3. T. (Vestiplex) coronifera.
MAPS 4–6 in Taxonomic review of Tipula (Vestiplex Bezzi) crane flies (Diptera: Tipulidae) in Mongolia
MAPS 4–6. Distribution maps of T. (Vestiplex) crane flies in Mongolia. 4. T. (Vestiplex) kiritshenkoi; 5. T. (Vestiplex) laccata; 6. T. (Vestiplex) leucoprocta.
MAPS 7–9 in Taxonomic review of Tipula (Vestiplex Bezzi) crane flies (Diptera: Tipulidae) in Mongolia
MAPS 7–9. Distribution maps of T. (Vestiplex) crane flies in Mongolia. 7. T. (Vestiplex) sintenisi; 8. T. (Vestiplex) subcentralis; 9. T. (Vestiplex) tchukchi.
Global oil palm map
<p>This report has been written by the IUCN Oil Palm Task Force in response to IUCN Resolution WCC-2016-Res-061-EN requesting "a situation analysis of the implications for biodiversity conservation from the expansion of oil palm, and to review and define best practices in the industry". The Situation Analysis primarily focuses on oil palm in the context of biodiversity conservation based on literature published before 31 January 2018, and aims to provide a more constructive pathway to addressing sustainability challenges in the palm oil industry. A draft version of this report was reviewed by 43 external reviewers from non-governmental organizations, academic institutions and people working in the palm oil industry, who provided some 600 comments that were then incorporated into a revised version.</p> <p>This report does not assess the social and economic implications of palm oil production and expansion but will refer to these when they are likely to have an impact on biodiversity conservation. Through identification of key knowledge gaps, the Situation Analysis will also provide direction to the Oil Palm Task Force in terms of seeking to address these knowledge gaps in the remainder of the 2017-2020 Quadrennium.</p>
Data from: Guiding carbon farming using interdisciplinary mixed methods mapping
In recognition of the need to address complex environmental problems, some ecological studies have adopted social research methods to better understand the complexity of social‐ecological systems management. The overwhelming majority of these studies stop short of fully embracing qualitative methodologies. The lack of integrative social and natural science data for a topic such as soil carbon farming is problematic as theoretical carbon sequestration opportunities identified through soil mapping and process‐based models can fail to deliver the sequestration levels promised when introduced on‐the‐ground. Such mapping needs to account for the human factors involved in delivering increased soil carbon on‐farm. Here, we develop a mixed methods mapping approach to explore the potential for increasing soil carbon stocks on upland farms in the UK. Our approach considers ecological and social complexity through application of soil science, ecology, participant observation, interviews and a focus group. Our maps revealed landscapes that are full of carbon farming opportunity, but contain previously hidden barriers to the delivery of increased soil carbon. For example, they revealed that carbon farming can be considered by farmers to work in opposition to perceived 'good farming' practices and be correlated with increased incidents of livestock disease. We also discovered that the use of maps in research can be problematic as they can close down discussion and exclude local representation of an area. Trialling an interdisciplinary mixed methods approach produced new, deeper and more richly‐textured understandings about how soil carbon management is produced socially as well as ecologically on upland livestock farms. Our findings have potential to improve the success of future carbon farming initiatives by incorporating farmer knowledge and social drivers of implementation.
Data from: Exploiting Poisson additivity to predict fire frequency from maps of fire weather and land cover in boreal forests of Québec, Canada
Predictive models of fire frequency conditional on weather and land cover are essential to assess how future cover-type distributions and weather conditions may influence fire regimes. We modelled the effects of bottom-up variables (e.g. land cover) and top-down variables (e.g. fire weather) simultaneously with data aggregated or interpolated to spatial and temporal units of 100 km2 and 1yr in the boreal forest of Québec, Canada. For models of human-caused fires, we used road density as a surrogate for human access and behaviour. We exploited the additive property of Poisson distributions to estimate cover-type specific fire count rates, which would normally not be possible with data of this spatial resolution. We used piecewise linear functions to model nonlinear relations between fire weather and fire frequency for each cover-type simultaneously. The estimated conditional rates may be considered as expected mean counts per unit area and time. It follows that these rates can be rescaled to arbitrary spatial and temporal extents. Our results showed fire frequency increased nonlinearly as aridity increased and more quickly in disturbed areas than other types. Road density exerted the strongest influence on the frequency of human-caused fires, which were positively correlated with road density. The estimates may be used to parameterize the fire ignition component of spatial simulation models, which often have a resolution different from that at which the data were collected. This is an essential step in incorporating biotic and abiotic feedbacks, land-cover dynamics, and climate projections into ecological forecasting. The insight into the power of Poisson additivity to reveal high-resolution ecological processes from low-resolution data could have applications in other areas of ecology.
FIGURE 1. Map showing the localities from where specimens have been studied. 1 in Multivariate analysis of geographic variation in Darevskia clarkorum (Darevsky & Vedmederja, 1977), correlation with geographic and climatic parameters, and true status of Darevskia dryada (Darevsky & Tuniyev, 1997)
FIGURE 1. Map showing the localities from where specimens have been studied. 1. Sümela, Maçka, Trabzon, northeastern Anatolia, Turkey, 2. Çataldere, Kaptanpaşa, Rize, northeastern Anatolia, Turkey, 3. 11 km southwest of Hemşin, Rize, northeastern Anatolia, Turkey, 4. Ayder Plateau, Çamlıhemşin, Rize, northeastern Anatolia, Turkey, 5. Hatila Plateau, Artvin, northeastern Anatolia, Turkey, 6. 16 km northeast of Ortacalar, Arhavi, Artvin, northeastern Anatolia, Turkey, 7. Subaşı Village, Hopa, Artvin, northeastern Anatolia, Turkey, 8. Cankurtaran, Hopa, Artvin, northeastern Anatolia, Turkey, 9. Karagöl, Borçka, Artvin, northeastern Anatolia, Turkey, 10. Charnaly, Georgia
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.