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571 results for “Brightness”
- Tergite 2 smooth to superficially punctate laterally (a), if ambiguous (some E. tombeaodiba) then tergite 1 stouter, less than 1.5x longer than apically wide; general coloration bright yellow (b); tropical Africa ………………………………………………………………………………………10 in A review of the Afrotropical Rhyssinae (Hymenoptera: Ichneumonidae) with the descriptions of five new species
- Tergite 2 smooth to superficially punctate laterally (a), if ambiguous (some E. tombeaodiba) then tergite 1 stouter, less than 1.5x longer than apically wide; general coloration bright yellow (b); tropical Africa ………………………………………………………………………………………10
[NGC3079 / UGC5101] SAUNAS: I. Searching for low surface brightness X-ray emission with Chandra/ACIS
<p>The contained FITS files represent the processed Chandra/ACIS X-ray surface brightness maps of the NGC3079 and UGC5101 galaxies, observed with Chandra/ACIS and analyzed with the SAUNAS pipeline as described in Borlaff et al. 2024 (in revision). All the images have the photometric calibrations (in units of photons cm-2 s-1 pixel-1) and have been astrometrically aligned. </p> <div>Each file contains four FITS extensions as detailed below: </div> <div>----</div> <div>EXTENSION NAME TYPE SIZE DETAILS </div> <div>----</div> <div>0 INFO no-data 0 BLANK EXTENSION. <br>1 SB_FLUX float64 512x512 X-RAY SURFACE BRIGHTNESS MAP. [photons cm-2 s-1 pixel-1] <br>2 STD_SB_FLUX float64 512x512 X-RAY SURFACE BRIGHTNESS NOISE MAP [photons cm-2 s-1 pixel-1]<br>3 SNR float64 512x512 SIGNAL-TO-NOISE RATIO [ - ]</div> <div>-----------</div> <div> </div> <div>Use the SNR extension (extension #3) to determine if your source of interest in the SB_FLUX map (extension #1) is statistically significant over the background limit.</div> <div> </div> <div> </div> <div> </div> <div> </div> <div> </div>
Brightness cues affect gap negotiation behaviour in zebra finches
<p>Flying animals have had to evolve robust and effective guidance strategies for dealing with habitat clutter. Birds and insects use optic flow cues to sense and avoid obstacles, but orchid bees have also been shown to use brightness cues during gap negotiation. Brightness cues might therefore be of general importance in structuring visually guided flight. To test the hypothesis that brightness cues affect gap negotiation behaviours in birds, we presented captive zebra finches <em>Taeniopygia guttata</em> with a symmetric or asymmetric background brightness distribution on the other side of a tunnel. The background brightness conditions influenced both the birds' decision to enter the tunnel aperture, and their flight direction upon exit. Zebra finches were more likely to initiate flight through the tunnel if they could see a bright background through it; they were also more likely to fly to the bright side upon exiting. We found no evidence of the centring response that would be expected if optic flow cues were balanced bilaterally during gap negotiation. Instead, the birds entered the tunnel by targeting a clearance of approximately one wing length from its near edge. Brightness cues therefore affect how zebra finches structure their flight when negotiating gaps in enclosed environments.</p>
The data for new theoretical Fe II templates for bright quasars
<p>The compressed <strong>'.tar.gz' </strong>files contain new theoretical Fe II templates that can be used for fitting UV to near-IR (1000-10000 Angstrom) spectra of quasars. The templates were developed using the latest Fe II atomic database of <a href="http://doi.org/10.1093/mnras/sty3198">Smyth et al. (2019)</a> within the CLOUDY C23.0 photoionization code with the following set of parameters.</p> <ul> <li>H-ionizing photons flux: <strong>17 ≤ log ΦH (cm−2 s−1) ≤ 22</strong>, and</li> <li>Gas density: <strong>9≤ log nH (cm−3) ≤ 14, </strong></li> <li>Step size: <strong>0.25 </strong>on log scale.</li> <li>A fixed Hydrogen column density: <strong>10^24 cm−2 </strong></li> <li>Abundance: <strong>solar </strong></li> <li>SED shapes:</li> </ul> <p>(1) Standard "<strong>agn.sed</strong>", a continuum similar to <a href="https://ui.adsabs.harvard.edu/abs/1987ApJ...323..456M/abstract/">Mathews & Ferland (1987)</a></p> <p>(2) Intermediate SED of (<a href="https://ui.adsabs.harvard.edu/abs/2012MNRAS.425..907J/abstract/">Jin et al., 2012</a>) </p> <ul> <li>The Fe II template is available for the microturbulence values 0, 20, 50 and 100 km/s.</li> </ul> <p><strong>(Note: The Fe II templates are also available in the GitHub link: </strong><strong>https://github.com/Ashwani-88/Fe2_template)</strong></p> <p>Each <strong>tar.gz</strong> file consists of Fe II templates for different SED shapes. <br><br>For each SED shape;</p> <p>The new Fe II templates are available in the directory "Templates_including_only_total_Fe2". </p> <p>Additionally, we provide templates for the outward and inward Fe II emissions in the directory "Templates_including_outward_Fe2"</p> <p>The directory for Fe II templates for a microturbulence velocity is named as</p> <p>turb_v<em><strong>n</strong></em></p> <p>where<em> <strong>n</strong></em> is the microturbulence velocity in km/s. <br><br>The files within each directory are named as follows:</p> <p><br>phi<em><strong>a</strong></em>_nH<em><strong>b</strong></em>_m<em><strong>c</strong></em>.dat</p> <p>where <strong><em> a</em></strong> = log value of the H-ionizing photon flux in cm−2 s−1,<br><em><strong>b</strong></em> = log value of the Hydrogen gas density in cm−3, and<br><em><strong>c</strong></em> = the value of microturbulence in km/s.</p> <h2><strong>Each template file in ``Templates_including_only_total_Fe2'' has two columns </strong> </h2> <p> <br>First column: wavelength in Angstrom with 2 Angstrom binning <br>Second column: Fe II line intensity (in erg cm-2 s-1 A-1)</p> <h2>Templates in ``Templates_including_outward_Fe2'' has four columns.</h2> <p><br>First column: wavelength in Angstrom with 1000 logarithmic bins, each ~ 584 km/s wide, between 1000 and 7000 Angstrom. <br>Second column: Total Fe II line intensity (in erg cm-2 s-1 A-1) <br>Third column: Inward Fe II line intensity (in erg cm-2 s-1 A-1) <br>Fourth column: Outward Fe II line intensity (in erg cm-2 s-1 A-1) </p> <p>The Fe II line intensity includes a covering factor of 30 % and is scaled for our test object RM 102. </p> <p> </p>
DeepBacs – Escherichia coli bright field segmentation dataset
<p>Training and test images of live <em>E. coli</em> cells imaged under bright field for the task of segmentation.</p> <p>Additional information can be found on this <a href="https://github.com/HenriquesLab/DeepBacs/wiki">github wiki</a>.</p> <p>The example shows a bright field image of live <em>E. coli </em>cells and the manually annotated segmentation mask.</p> <p> </p> <p><strong>Data type</strong>: Paired bright field and segmented mask images </p> <p><strong>Microscopy data type</strong>: 2D bright field images recorded at 1 min interval</p> <p><strong>Microscope</strong>: Nikon Eclipse Ti-E equipped with an Apo TIRF 1.49NA 100x oil immersion objective</p> <p><strong>Cell type</strong>: <em>E. coli</em> MG1655 wild type strain (CGSC #6300).</p> <p><strong>File format</strong>: .tif (8-bit)</p> <p><strong>Image size</strong>: 1024 x 1024 px² (79 nm / pixel), 19/15 individual frames (training/test dataset)</p> <p>1024 x 1024 px² (79 nm / pixel), 9 regions of interest with 80 frames @ 1 min time interval (live-cell time series)</p> <p><strong>Image preprocessing</strong>: Raw images were recorded in 16-bit mode (image size 512 x 512 px² @ 158 nm/px). Images were upscaled with a factor of 2 (no interpolation) to enable generation of higher-quality segmentation masks. Two sets of mask images are provided: RoiMaps for instance segmentation using e.g. StarDist or binary images for CARE or U-Net.</p> <p><br> <strong>Author(s)</strong>: Christoph Spahn<sup>1,2</sup>, Mike Heilemann<sup>1,3</sup></p> <p><strong>Contact email</strong>: christoph.spahn@mpi-marburg.mpg.de</p> <p> </p> <p><strong>Affiliation(s)</strong>: </p> <p>1) Institute of Physical and Theoretical Chemistry, Max-von-Laue Str. 7, Goethe-University Frankfurt, 60439 Frankfurt, Germany</p> <p>2) ORCID: 0000-0001-9886-2263 </p> <p>3) ORCID: 0000-0002-9821-3578</p>
Maps of thermal inertia, dielectric constant and brightness temperature of asteroid (16) Psyche derived from ALMA data
<p>These data and results are in support of the findings by Cambioni, S., de Kleer, K. and Shepard, M. in their paper "The Heterogeneous Surface of Asteroid (16) Psyche", Journal of Geophysical Research: Planets, link: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JE007091. </p> <p>If using any of this material, please cite the above article as doi: 10.1029/2021JE007091</p> <p> </p>
DeepBacs – Escherichia coli release from stationary phase - Bright field segmentation dataset and StarDist model
<p>Training and test images of live <em>E. coli</em> cells imaged under bright field for the task of segmentation.</p> <p>Additional information can be found on this<a href="https://github.com/HenriquesLab/DeepBacs/wiki"> github wiki</a>.</p> <p>The example shows a bright field image of live <em>E. coli </em>cells of an overnight culture and the manually annotated segmentation mask.</p> <p> </p> <p><strong>Data type</strong>: Paired bright field and segmented mask images </p> <p><strong>Microscopy data type</strong>: 2D bright field images recorded at 2 min interval</p> <p><strong>Microscope</strong>: Nikon Eclipse Ti-E equipped with an Apo TIRF 1.49NA 100x oil immersion objective</p> <p><strong>Cell type</strong>: <em>E. coli</em> MG1655 wild type strain (CGSC #6300).</p> <p><strong>File format</strong>: .tif (8-bit)</p> <p><strong>Image size</strong>: 512 x 512 px² (106 nm / pixel), 19/15 individual frames (training/test dataset)</p> <p>512 x 512 px² (106 nm / pixel), 7 regions of interest with 20 frames @ 2 min time interval (live-cell time series)</p> <p><strong>Data annotation</strong>: Images were annotated using the Fiji freehand selection tool.</p> <p><strong>Image preprocessing</strong>: Time series were stabilized using the Fiji plugin StackReg and the 480 x 480 px center region was cropped</p> <p><strong>StarDist model</strong></p> <p>The StarDist 2D model was trained from scratch for 200 epochs on 33 paired image patches (image dimensions: (512, 512 px²), patch size: (512 x 512 px²)) with a batch size of 2, 80 rays, grid size 1, 4-fold data augmentation and a mae loss function, using the StarDist 2D ZeroCostDL4Mic notebook (v 1.13) (von Chamier & Laine et al., 2020). Key python packages used include tensorflow (v 0.1.12), Keras (v2.3.1), csbdeep (v 0.6.3), numpy (v 1.21.5), cuda (v 11.1.105). The training was accelerated using a Tesla K80 GPU.</p> <p>Model weights can be used with the ZeroCostDL4Mic StarDist 2D notebook or the Fiji StarDist plugin.</p> <p><br> <strong>Author(s)</strong>: Christoph Spahn<sup>1,2</sup>, Mike Heilemann<sup>1,3</sup></p> <p><strong>Contact email</strong>: christoph.spahn@mpi-marburg.mpg.de</p> <p><strong>Affiliation(s)</strong>: </p> <p>1) Institute of Physical and Theoretical Chemistry, Max-von-Laue Str. 7, Goethe-University Frankfurt, 60439 Frankfurt, Germany</p> <p>2) ORCID: 0000-0001-9886-2263 </p> <p>3) ORCID: 0000-0002-9821-3578 </p>
Dataset of measurements of the soil CO2 flux and soil brightness temperature at Le Biancane (geothermal field of Larderello-Travale, Tuscany, Italy) in the May-June 2021 period.
<p>Dataset of measurements of the soil CO<sub>2</sub> flux and soil brightness temperature at Le Biancane (geothermal field of Larderello-Travale, Tuscany, Italy) in the period May-June 2021. The dataset is structured as follows:</p> <p>Column A is the progressive number of the point (#);</p> <p>Column B is the Longitude of the point, datum WGS 1984;</p> <p>Column C is the Latitude of the point, datum WGS 1984;</p> <p>Column D is the Universal Transverse Mercator (UTM) Longitude coordinate, datum WGS 1984, zone 32N;</p> <p>Column E is the Universal Transverse Mercator (UTM) Latitude coordinate, datum WGS 1984, zone 32N;</p> <p>Column F is the soil brightness temperature, in °C;</p> <p>Column G is the soil CO<sub>2</sub> flux in grams of CO<sub>2</sub> per square meter, per day (g m<sup>-2</sup> day<sup>-1</sup>)</p>
Raster Image Correlation Spectroscopy and Brightness Measurements of AtLEA proteins from Arabidopsis thaliana
<p>Temporal sequences of various fluorescent leaves were captured using a confocal scanning microscope (Olympus FV1000 inverted microscope), equipped with a 1.3 NA oil immersion 60X objective and the photon counting detection mode. Utilizing a 488 nm laser at 0.1% power and GFP filters/cubes, each temporal sequence involved the acquisition of 100 frames of 64x64 pixels, with a dwell time of 10 μs (1.76 ms per line, 130.24 ms per frame) and a pixel size of 66 nm (50X digital zoom). The interval between frames was set at 131.6 ms.</p> <p>Five plants were analyzed, each expressing one of four distinct genetic constructs fused to complementary fragments of Yellow Fluorescent Protein: pYFN-4-/5pYFC-4-5 (representing the complete AtLEA4-5 protein), pYFN-4-51-77/pYFC-4-51-77 (associated with the N-terminal region of AtLEA4-5), pYFN-4-578-158/pYFC-4-578-158 (relating to the C-terminal region of AtLEA4-5), and pYFN-pYFC (serving as the control). The raw data (*.oib files) were collected during three imaging sessions within a one-week period:</p> <p>- 220618 raw oib dataset.zip</p> <p>- 220622 raw oib dataset.zip</p> <p>- 220623 raw oib dataset.zip</p> <p>Images were converted to *.tif format using FIJI/ImageJ for further analysis and were archived in "tif dataset RICS NB LEAs.zip," excluding files with excessive movement of biological specimens. These images were then subjected to "Raster Image Correlation Spectroscopy" and "Number and Brightness" techniques for analysis.</p> <p>Notation:</p> <p>- h1, h2, h3, h4, h5: Replicates (plants) expressing one of four specific genetic constructs fused to complementary fragments of Yellow Fluorescent Protein.</p> <p>- 45: Fused to the full-length AtLEA4-5 protein (pYFN-4-/5pYFC-4-5).</p> <p>- 4h: Fused to the N-terminal region of AtLEA4-5 (pYFN-4-51-77/pYFC-4-51-77).</p> <p>- rc: Fused to the C-terminal region of AtLEA4-5 (pYFN-4-578-158/pYFC-4-578-158).</p> <p>- ct: The control condition (pYFN-pYFC).</p>
РИС. 11. ИЗображениЯ крючков глохидиев при раЗной настройке Яркости и контрастности (Anemina arcaeformis, р. Сита, Хабаровский кр.). А. Оптимальные Яркость и контрастность. В. ИЗбыточнаЯ контрастность. С. ИЗбыточнаЯ Яркость. МасШтаб 20 мкм. Микроскоп Zeiss EVO 40, напыление углеродом. FIG. 11. Imagines of glochidia hooks with different brightness and contrast value (Anemina arcaeformis, Sita River, Khabarovsk Krai). A. Optimal brightness and contrast. B. Excessive contrast. C. Excessive brightness. Scale bars 20 μm. Zeiss EVO 40 microscope, sputter coating with carbon. in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе
РИС. 11. ИЗображениЯ крючков глохидиев при раЗной настройке Яркости и контрастности (Anemina arcaeformis, р. Сита, Хабаровский кр.). А. Оптимальные Яркость и контрастность. В. ИЗбыточнаЯ контрастность. С. ИЗбыточнаЯ Яркость. МасШтаб 20 мкм. Микроскоп Zeiss EVO 40, напыление углеродом. FIG. 11. Imagines of glochidia hooks with different brightness and contrast value (Anemina arcaeformis, Sita River, Khabarovsk Krai). A. Optimal brightness and contrast. B. Excessive contrast. C. Excessive brightness. Scale bars 20 μm. Zeiss EVO 40 microscope, sputter coating with carbon.
Fig. 3 in Spatial distribution of radar bright band intensity
Fig. 3 ― Variation of longitudinally averaged monthly BBI with latitude in (a) February 1999, (b) July 2007, (c) September 2001, and (d) October 2002
Dataset: Bright Minds Biosciences Inc. (DRUG) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Bright Green Corporation (BGXX) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 35. Heterolepidoderma aff. majus Remane, 1927. Adult specimen. Bright field microphotographs. A. Habitus. B. Dorsal view. C in Gastrotricha - not only in sediments: new epiphytic species of Chaetonotida from the Jubilee Greenhouse of the Botanical Garden in Kraków
Fig. 35. Heterolepidoderma aff. majus Remane, 1927. Adult specimen. Bright field microphotographs. A. Habitus. B. Dorsal view. C. Ventral view.
Venus Mesosphere Constituents Brightness Temperatures Dataset
<p>This is a dataset corresponding to a simulation based study that has be performed using Atmospheric Radiative Transfer Simulator (ARTS) radiative transfer model. The ARTS model gives the facility to simulate the brightness temperature (measurements) at specific satellite altitude and for any given viewing geometry. The brightness temperatures are for water vapour, carbon monoxide, sulphur dioxide, hydrogen chloride.</p>
Brightness temperature data and weather station data from general scans of the microwave radiometer HATPRO
<p>This set contains brightness temperature observations and associated weather station data from microwave radiometer HATPRO for three events on Jul 27 and Aug 1, 2023.</p>
Linked collectors and determiners for: Alpheus naranjo, a new brightly coloured snapping shrimp from the Caribbean coast of Panama (Malacostraca, Decapoda, Alpheidae).
Natural history specimen data linked to collectors and determiners held within, "Alpheus naranjo, a new brightly coloured snapping shrimp from the Caribbean coast of Panama (Malacostraca, Decapoda, Alpheidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ce0ab832-46b8-40e9-8aaa-9ca99ab24f32">https://bionomia.net/dataset/ce0ab832-46b8-40e9-8aaa-9ca99ab24f32</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ce0ab832-46b8-40e9-8aaa-9ca99ab24f32">https://gbif.org/dataset/ce0ab832-46b8-40e9-8aaa-9ca99ab24f32</a>. Formatted as a Frictionless Data package.
Data from: Spectroscopic approach to correction and visualisation of bright-field light transmission microscopy biological data
<p>The most realistic information about the transparent sample such as a live cell can be obtained only using bright-field light microscopy. At high-intensity pulsing LED illumination, we captured a primary 12-bit-per-channel (bpc) response from an observed sample using a bright-field wide-field microscope equipped with a high-resolution (4872x3248) image sensor. In order to suppress data distortions originating from the light interactions with undesirable elements in the optical path, poor sensor reproduction (geometrical defects of the camera sensor and some peculiarities of sensor sensitivity), this uncompressed 12-bpc data underwent a kind of correction after simultaneous calibration of all the parts of the experimental arrangement. Moreover, the final intensities of the corrected images are proportional to the photon fluxes detected by a camera sensor. It can be visualized in 8-bpc intensity depth after the Least Information Loss compression [Lect. Notes Bioinform. 9656, 527 (2016)].</p>
Highly consistent brightness temperature fundamental climate data record from SSM/I and SSMIS
<p>The highly consistent brightness temperature (TB) fundamental climate data record (FCDR) comprises intercalibrated TBs from SSM/I on F11 and F13, and SSMIS on board F17. It covers the time period from December 1991 to December 2021. It provides homogenized and intercalibrated TBs in a user-friendly data format (HDF5). SSM/I and SSMIS data are used for various applications, such as analyses of the hydrological cycle. The improved homogenization and inter-calibration procedure ensure the long-term stability of the FCDR for climate related applications. <br> This data files contain daily TBs data on 1°×1° grid-level of satellite F11, F13 and F17 (Level 2A).<br> It is worth noting that the original sensor TB data are provided by Level-1C dataset. The Level-1C data record is complemented with scan status, quality flags, sun glint angles, and earth incidence angles.</p>
Data for: Body size and substrate use affect ventral, but not dorsal, brightness evolution in lizards
<p>Substrate properties can affect the thermal balance of organisms, and the colored integument, alongside other factors, may influence heat transfer via differential absorption and reflection. Dark coloration may lead to higher heat absorption and could be advantageous when substrates are cool (and vice versa for bright coloration), but these effects are rarely investigated. Here, we examined the effect of substrate reflectance, specific heat capacity (<em>c<sub>p</sub></em>), and body size on the dorso-ventral brightness using 276 samples from 12 species of cordylid lizards distributed across 26 sites in South Africa. We predicted, and found, that bright ventral colors occur more frequently in low <em>c<sub>p</sub></em> (i.e. drier, with little energy needed for temperature change) substrates, especially in larger body-sized individuals, possibly to better modulate heat transfer with the surrounding environment. By contrast, dorsal brightness was not associated with body size nor any substrate thermal property, suggesting selection pressures other than thermoregulation. Ancestral estimation and evolutionary rate analyses suggest that ventral brightness rapidly differentiated within the Cordylinae starting 25 Mya, coinciding with an aridification period, further hinting at a thermoregulatory role for ventral colors. Our study indicates that substrate properties can have a direct role in shaping the evolution of ventral brightness in ectotherms.</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.