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4,669 results for “Environment;”
Data from: Genetic divergence and isolation by thermal environment in geothermal populations of an aquatic invertebrate
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Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1
<p>This is the JULES input and output data and plotting scripts used in the paper titled "Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1.</p> <p>The tar file contains the following:</p> <p>outputs/cardwfdei_gl4_uncompressed.mon.nc<br> outputs/cardwfdei_gl4_surf_ft_dom_soil.mon.nc<br> outputs/cardwfdei_gl4_gb_dom_soil_decompr_loam.mon.nc<br> outputs/cardwfdei_gl4_surf-soil_consolidated.mon.nc<br> outputs/cardwfdei_gl4_gb_dom_soil_compr_loam.mon.nc<br> plotting_scripts/utils.py<br> plotting_scripts/gb_flux_summary.py<br> plotting_scripts/tile_fsmc_summary.py<br> plotting_scripts/gb_smcl_closure_summary.py<br> plotting_scripts/colors_names.py<br> inputs/drive-file-WFDEI-79-10.txt<br> inputs/WFDEI_data/README.txt<br> inputs/extract_cardwfdei_point.py</p> <p>uncompressed is the output for experiment HResTex.<br> surf_ft_dom_soil is the output for experiment SurfDom.<br> gb_dom_soil_decompr_loam is the output for experiment SurfGB.<br> surf-soil_consolidated is the output for experiment HResTexAgg.<br> gb_dom_soil_compr_loam is the output for experiment DC.</p> <p>Descriptions about the individual plotting scripts are given within each file.</p> <p>The WFDEI data is freely available from a separate source and inputs/WFDEI_data/README.txt describes how to obtain this dataset.</p> <p>inputs/extract_cardwfdei_point.py extracts the WFDEI data for the single latitude/longitude point used in this paper.</p> <p>inputs/drive-file-WFDEI-79-10.txt is the input file required by JULES to read in the WFDEI driving data files.</p>
Automated Classification of Estuarine Sub-depositional Environment Using Sediment Texture
<p>The repository corresponding to the paper "Automated classification of estuarine sub-depositional environment using sediment texture" by Houghton et al., 2023. <a href="https://doi.org/10.1029/2022JF006891">https://doi.org/10.1029/2022JF006891</a></p>
RailVID: A Dataset for Rail Environment Semantic
<p>At present, rail transit is becoming the main means of urban and intercity fast passenger and freight transportation. Its safe operation is of great significance to protect the life of people, security of property and maintain social stability. Though the degree of intelligent traffic has been improved , there are still many safety risks in the current system by using manual hazard monitoring in the railway. Limited by the particularity and complexity of railway scenes, there are few studies on the perception and understanding of rail transit environment. In this paper, we propose a new rail transit dataset – RailVID. We use the AT615X Infrared thermography from InfiRay to collect data and record different railway scenarios, including carport, depot, and straight. We then propose an improved BiSeNet realtime semantic segmentation network for evaluation. Based on this dataset, we carry out environment perception, environment understanding, and safety decisions on the track area in front of the train, and we propose a solution for fully automatic train operation of rail transit.The dataset we provide compensates for the infrared data that is not in the existing dataset, and our data covers special weather and various conditions. Experiments show that our method achieves a higher Mean Pixel Accuracy in the collected dataset, and the processing speed also meets the real-time requirement.</p>
Data for: Transplant experiments demonstrate that larger brains are favored in high competition environments in Trinidadian killifish
<p><span>The extent to which the evolution of a larger brain is adaptive remains controversial. Trinidadian killifish (<em>Anablepsoides hartii</em>) are found in sites that differ in predation intensity; fish that experience decreased predation and increased intraspecific competition exhibit larger brains. We evaluated the connection between brain size and fitness (survival and growth) when killifish are found in their native habitats and when fish are transplanted from sites with predators to high-competition sites that lack predators. Selection for a larger brain was absent within locally adapted populations. Conversely, there was a strong positive relationship between brain size and growth in transplanted but not resident fish in high-competition environments. We also observed significantly larger brain sizes in the transplanted fish that were recaptured at the end of the experiment versus those that were not. Our results provide experimental support that larger brains increase fitness and are favored in high-competition environments.<br><br></span></p>
Figure 4 from: Costa BG, Pellegrini TG, Bernardi LFO, Ferreira RL (2017) Notes on predator-prey relationships among Tanypodinae larvae (Diptera, Chironomidae) and mites (Acariformes) in Brazilian subterranean aquatic environments. Subterranean Biology 22: 67-74. https://doi.org/10.3897/subtbiol.22.13925
Figure 4 - A General view of gut contents from a specimen of Tanypodinae (Chironomidae), where the arrow shows an specimen of Tyrophagus sp. (Acariformes: Sarcoptiformes: Acaridae) among alimentary items B Detail view of the partially digested Tyrophagus sp. C Detail of specimen already partially digested which possibly belongs to the family Frontipodopsidae (Acariformes: Trombidiformes).
Figure 3 from: Costa BG, Pellegrini TG, Bernardi LFO, Ferreira RL (2017) Notes on predator-prey relationships among Tanypodinae larvae (Diptera, Chironomidae) and mites (Acariformes) in Brazilian subterranean aquatic environments. Subterranean Biology 22: 67-74. https://doi.org/10.3897/subtbiol.22.13925
Figure 3 - A–C Teratopiidae (Acariformes: Sarcoptiformes) found in gut contents of four specimens of Tanypodinae (Chironomidae).
Figure 2 from: Costa BG, Pellegrini TG, Bernardi LFO, Ferreira RL (2017) Notes on predator-prey relationships among Tanypodinae larvae (Diptera, Chironomidae) and mites (Acariformes) in Brazilian subterranean aquatic environments. Subterranean Biology 22: 67-74. https://doi.org/10.3897/subtbiol.22.13925
Figure 2 - Mites found in gut contents of four specimens of Tanypodinae (Chironomidae). A Two examples of Limnesiidae larvae (Acariformes: Trombidiformes), probably belonging to the genus Limnesia B–D partially digested mites, probably Hydrachnidia.
Figure 1a from: Ioanas H, Saab B, Rudin M (2017) Gentoo Linux for Neuroscience - a replicable, flexible, scalable, rolling-release environment that provides direct access to development software. Research Ideas and Outcomes 3: e12095. https://doi.org/10.3897/rio.3.e12095
Figure 1a - Minimal (excluding all optional features) dependency graph of the contributed neuroscience package set.
Figure 1b from: Ioanas H, Saab B, Rudin M (2017) Gentoo Linux for Neuroscience - a replicable, flexible, scalable, rolling-release environment that provides direct access to development software. Research Ideas and Outcomes 3: e12095. https://doi.org/10.3897/rio.3.e12095
Figure 1b - Maximal (including all optional features) dependency graph of the contributed neuroscience package set.
Figure 6 from: Visagie CM, Yilmaz N, Renaud JB, Sumarah MW, Hubka V, Frisvad JC, Chen AJ, Meijer M, Seifert KA (2017) A survey of xerophilic Aspergillus from indoor environment, including descriptions of two new section Aspergillus species producing eurotium-like sexual states. MycoKeys 19: 1-30. https://doi.org/10.3897/mycokeys.19.11161
Figure 6 - Aspergillus megasporus (DAOMC 250799). a Colonies on MEA, MEA20S, MY10-12 (top row, from left to right), DG18, CY20S, MY50G (bottom row, from left to right) b Texture on DG18 c Asci d Ascospores e Cleistothecium f, g Conidiophores h Conidia. Scale bars: e = 50 µm, c, d, f–h = 10 µm.
Figure 5 from: Visagie CM, Yilmaz N, Renaud JB, Sumarah MW, Hubka V, Frisvad JC, Chen AJ, Meijer M, Seifert KA (2017) A survey of xerophilic Aspergillus from indoor environment, including descriptions of two new section Aspergillus species producing eurotium-like sexual states. MycoKeys 19: 1-30. https://doi.org/10.3897/mycokeys.19.11161
Figure 5 - Aspergillus mallochii (DAOMC 146054). a Colonies on MEA, MEA20S, MY10-12 (top row, from left to right), DG18, CY20S, MY50G (bottom row, from left to right) b Texture on DG18 c Asci d Ascospores e Cleistothecium f, g Conidiophores h Conidia. Scale bars: e = 50 µm, c, d, f–h = 10 µm.
Figure 2 from: Visagie CM, Yilmaz N, Renaud JB, Sumarah MW, Hubka V, Frisvad JC, Chen AJ, Meijer M, Seifert KA (2017) A survey of xerophilic Aspergillus from indoor environment, including descriptions of two new section Aspergillus species producing eurotium-like sexual states. MycoKeys 19: 1-30. https://doi.org/10.3897/mycokeys.19.11161
Figure 2 - One of the most parsimonious trees of Aspergillus sect. Aspergillus based on a combined dataset of ITS, BenA, CaM and RPB2. The tree was rooted to A. xerophilus, A. leucocarpus and A. osmophilus. Support in nodes higher than 80% bootstrap values and 0.95 posterior probabilities are shown above thickened branches. New species are shown in bold and colour, while ex-type strains are followed by T.
Figure 3 from: Visagie CM, Yilmaz N, Renaud JB, Sumarah MW, Hubka V, Frisvad JC, Chen AJ, Meijer M, Seifert KA (2017) A survey of xerophilic Aspergillus from indoor environment, including descriptions of two new section Aspergillus species producing eurotium-like sexual states. MycoKeys 19: 1-30. https://doi.org/10.3897/mycokeys.19.11161
Figure 3 - Base peak chromatograms observed in positive ionization mode. a Aspergillus mallochii (DAOMC 146054 = KAS 7618) b Aspergillus megasporus (DAOMC 250799 = KAS 6176). Both species show some production of echinulin class of alkaloids to varying amounts. Quinolactacin A1, A2 and B were not detected in A. mallochii.
Figure 1 from: Visagie CM, Yilmaz N, Renaud JB, Sumarah MW, Hubka V, Frisvad JC, Chen AJ, Meijer M, Seifert KA (2017) A survey of xerophilic Aspergillus from indoor environment, including descriptions of two new section Aspergillus species producing eurotium-like sexual states. MycoKeys 19: 1-30. https://doi.org/10.3897/mycokeys.19.11161
Figure 1 - One of the most parsimonious trees of Aspergillus sect. Aspergillus based on ITS, CaM, BenA and RPB2. Trees were rooted to A. xerophilus, A. leucocarpus and A. osmophilus. Support in nodes higher than 80% bootstrap values and 0.95 posterior probabilities are shown above thickened branches. New species are shown in bold and colour, while ex-type strains are followed by T.
Figure 3 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Figure 3 - Analysis of the MIxS-BE "building occupancy type" (type of building where the underlying sample was taken).
Figure 2 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Figure 2 - Krona chart of the taxonomic affiliation of the BMS sequences down to order level. The Krona chart lists all annotated BMS sequences except those classified as Fungi sp. (36.4%) and those of non-fungal origin (0.9%). An interactive version of the Krona chart is provided as Suppl. material 3. The figure includes pre-existing data plus the data added during the workshop, such that these charts indicate the scientific state of ITS-based Sanger-derived sequencing of the built mycobiome as of spring 2016. Sequences that were not annotated with a single built environment-related term in the INSDC were not included in this effort, and are not represented in these charts.
Figure 1 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Figure 1 - Analysis of the BMS sequences for country of collection. Country centroids marked with bubbles of different size on the global map indicate the number of BMS sequences originating from these countries (54 distinct countries, sequence count ranging from 1 to 2,914). For an additional 2.9% of the sequences, country information could not be restored during the workshop. The figure includes pre-existing data plus the data added during the workshop, such that these charts indicate the scientific state of ITS-based Sanger-derived sequencing of the built mycobiome as of spring 2016. Sequences that were not annotated with a single built environment-related term in the INSDC were not included in this effort, and are not represented in these charts.
Supplementary material 4 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The interactive Krona chart associated with Figure 2 :
Supplementary material 2 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The MIxS-BE annotations implemented for the built environment sequences during the workshop :
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.