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535 results for “dust”
DUST dataset
<p>"DUST is a dataset composed of UDP audio packet traces generated by a real-time Networked Music Performance system. The dataset includes a variety of files collected under different network and device configurations. Each file combines traces of incoming audio packets with local playback status information. The dataset aims to support offline simulations of real-time audio streaming systems, aiding the development of algorithms to address challenges such as packet loss concealment, network jitter resilience, and clock drift compensation."</p> <p>Each experiment has 3 associated files. A pair of gzipped csv files with the actual dataset and a json file providing a description of it. In the json file the duration is expressed in hours, the date in format dd/mm/aaaa. </p>
Data set, Model, and Catalog for: Data-driven stellar intrinsic colors and dust reddenings for spectro-photometric data
<p>Intrinsic colors of stars are essential for the studies on both stellar physics and dust reddening. In this work, we developed an XGBoost model to predict the stellar intrinsic colors with the atmospheric parameters, Teff , log g, and [M/H], which is an improvement of the widely used blue-edge method. The dust reddening toward each line-of-sight can then be calculated by the observed colors minus the derived intrinsic colors.</p> <p>Here we provide the related data sets:</p> <ul> <li>xgb_model.pkl: the trained XGBoost model.</li> <li>use_xgb.py: a simple script showing how to use the XGBoost model to predict intrinsic colors.</li> <li>data_set.fits: this fits file contains the training and test sets, separated into four data arrays: <ul> <li>X_train: X-data (teff,logg,mh) of the training set.</li> <li>X_test: X-data (teff,logg,mh) of the test set.</li> <li>y_train: y-data (BP-RP, BP-Ks, J-Ks) of the training set.</li> <li>y_test: y-data (BP-RP, BP-Ks, J-Ks) of the test set.</li> </ul> </li> <li>IC_catalog.csv: a catalog containing a representative set of intrinsic colors at three bands ('BPRP0', 'BPK0', and 'JK0' in columns) as a function of typical Teff, logg, and [M/H] ('teff', 'logg', and 'mh' in columns).</li> </ul> <p>With the above data and model, users can apply the trained XGBoost to new sources to predict their intrinsic colors and calculate their dust reddenings. One can further control the quality of the prediction by selecting training-like sources with the training set and estimating the <a>generalization error by the test set.</a></p>
Metagenomic analysis suggests low in situ replication rates for dust-associated bacteria over the Red Sea
<p>Gff and fasta files of dust-associated MAGs that were analyzed on GRiD for estimation of in situ replication rates</p>
Advanced bulk dust optical models
<p>This is the advanced bulk optical models for mineral dust particles for lidar applications. The single-scattering properties are obtained from the TAMUdust2020 database. The paritcle shape ensambles and complex refractive index of mineral dust particles are constrained with observations reported in the literature. The organization of this database is described in this ReadMe file.</p>
Comet C/2020F3 (Neowise) with separate dust and ion gas tails and a green glowing coma, by Dietmar Gutermuth, Germany
<p>Second place in the 2021 IAU OAE Astrophotography Contest, category Comets.</p> <p>Comets have a very interesting structure comprising of four main parts: the nucleus, composed of rock, dust and frozen gases, typically spanning a few kilometres, although bigger ones have been observed; a small atmosphere of gas surrounding the nucleus (only present when the comet approaches its closest point to the Sun), called coma; and the two distinctive cometary tails (there is at times third tail). The green colour of the coma is due to carbon and nitrogen present in the coma reacting with the Sun’s ultraviolet radiation. The tail that we are mostly used to observing – dust tail and is composed of micron sized dust particles, the second tail composed of charged particles – ion or gas tail. The tails are released only when the comet approaches the Sun at a distance where the heat and radiation emanating from our star is intense enough to vaporize the frozen gases. The dust tail is curved, while the gas tail is straight and always points away from the Sun as this is carried by the solar wind - flow of charged particles emitted by the Sun. As comets are formed by leftover material, they carry with them important information about the early stages of the Solar System’s formation. This beautiful image shows the comet C/2020 F3 (Neowise), as seen from Germany in July 2020, with three of the four structures clearly visible – coma, gas, and dust tail.</p> <p>Credit:<strong> </strong>Dietmar Gutermuth/IAU OAE</p>
Figure 1 in House dust mites (Acari: Astigmata) from mattresses in Panama
Figure 1 Diversity indices from mattresses sampled in PA and in PO (n=25 in each). A – Species richness; B – Simpson's D index.
Drosophila suzukii population dynamics and control efficiency of mineral dusts with a focus on grape protection
<p>The invasive pest<em> Drosophila suzukii</em> is threatening berry production. It is mainly managed via chemical control, which is associated with consumer and environmental concerns. Here, we tested the efficiency of mineral dusts under field and laboratory conditions. Furthermore, population dynamics were studied in a vineyard and its surroundings. The kaolin products Cutisan and Surround®, as well as the CaCO<sub>3</sub> product Carboliq had neither insecticidal nor repellent effects on <em>Drosophila suzukii</em> adults in laboratory choice tests with grapes at concentrations of up to 2% (w/v). Cutisan and Surround® significantly reduced the number of deposited eggs (-41.9% and -49.3%, respectively) while Carboliq had no effect on the oviposition under laboratory conditions. The Surround® treatment significantly reduced the number of flies trapped on 09/09/2020 at a test vineyard. Depending on the assessment date and treatment, between 59 and 84% of the flies in the bait traps were females. The number of eggs found in fruit treated with Carboliq in the field was higher at each assessment date than in the control but this difference was not statistically significant. Cutisan and Surround® applications in the field showed an equivalent or lower average number of eggs compared to the control but this difference was only significant on 24/09/2020. The highest number of <em>D. suzukii</em> adults was observed around September in the field and a decline of the population occurred in the winter months until July. In epidemic years, temperature - humidity - combinations prior to population peaks were quite stable with low humidity being associated with a high temperature and <em>vice-versa</em>. In non-epidemic years, humidity fluctuated more than in epidemic years and temperatures were lower before population peaks. The effect of global radiation on population maxima seemed to be minor.</p>
The role of mineral dust aerosol particles in aviation soot-cirrus interactions
<p>The files contain the datasets shown in the publication "The role of mineral dust aerosol particles in aviation soot-cirrus interactions" to appear in J. Geophys. Res. Atmos. (revised manuscript submitted) The files are xmgrace plot files containing the research data (ASCII) shown in all figures that appear in the main text (4) and appendix (2).</p> <p> </p>
Mars Dust Activity Database
<table> <tbody> <tr> </tr> <tr> <td> <p>Version 1.1 of the Mars Dust Activity Database (MDAD, v1.1) includes storm boundaries for every instance from the Mars Color Imager (MARCI) era of <a href="http://doi.org/10.7910/DVN/F8R2JX">Version 1.0 of the MDAD</a> (Mars Years 28–32). The dataset is organized into five tar files, one for each Mars year. Two formats are provided in every tar file and provide equivalent data. A netcdf file (*.nc) contains a mask of the dust events on each sol of the Mars Year (soy) in an array called "MDAD," along with a string vector of the name of the sol from the Mars Daily Global Map (MDGM) database in a variable called "dayList," and an array of values in a variable called "timeList" of the time of the sol containing: start soy, end soy, mean soy, median soy, start areocentric longitude (Ls), end Ls, mean Ls, median Ls. The MDAD mask has dimensions time x longitude (3600 points) x latitude (1801 points). The length of the time dimension varies across years: MY 28 (340), MY 29 (551), MY 30 (616), MY 31 (623), MY 32 (358). The dayList and timeList variables have the same time dimension length as the MDAD masks. The mask variable is in uint8 (unsigned byte) format and may be converted directly to unsigned int upon reading. Values of (255) indicate missing pixels of the MDGM. A value of (0) indicates no dust instances. Values ranging 1–133 are the number portion of the member ID to connect the mask back to MDAD v1.0. Values ranging 134–250 are splitting members with the member ID of (mask value - 133)b. </p> <p>Each Mars-year bundle also contains a folder of *.csv files, each of which corresponds to a single dust storm instance on a single sol. The csv files are named with the following convention: SUB_dayXX_MEM_ZZZb.csv, where “SUB” is the MARCI mission subphase and XX is the sol number ranging 01–34. The last seven characters are the member ID for the storm from MDAD v1.0, with ZZZ ranging 001–133 and "MEM" the subphase on which the member starts. For storms that have merged, only the member ID with the smallest ZZZ is included in the file name, and the character "b" is only included in the file name for splitting storms. Each *.csv file consists of a two column matrix. Column 1 is east longitude, and column 2 is latitude. Each longitude, latitude point is a pixel on the boundary of the storm instance. The boundaries have a resolution of 1/10°, so each row of the matrix maps to a unique pixel of a MDGM. The total set of longitude, latitude points is the outline of the dust instance, which traces the outside of the storm masks provided in the *.nc files.</p> <p>An additional comma separated value file with the name SUB.list provides a copy of the "timeList" array included in the *.nc files. For each subphase of MDGMs, there is a single *.list, and each row is a single day with the following information in csv format: subphase_day, start MY, end MY, start sol-of-year (soy), end soy, mean soy, median soy, start areocentric longitude (Ls), end Ls, mean Ls, median Ls. Additionally, a folder entitled "list" contains an additional *.list comma separated value file for each day of the subphase, where each row describes a single swath in that sol's MDGM. It has the following format: Swath name, Earth time collected, MY, Mars month, soy, Ls, center west longitude.</p> <p> </p> <p> </p> </td> </tr> </tbody> </table> <div> </div>
Atmospheric Dust Source Contributions and Synoptic Scale Adjustments in the East Asian Region in April of 2021
<p>The WRF-Chem simulations were conducted to assess the source contributions to the concentrations and ratios across the East Asian region in April 2021. The WRF-Chem baseline was compiled, and sensitivity simulations were conducted regarding the source contributions to the concentrations of PM10 BASE, PM10 Anthro, PM10 Dust, and PM10 Biomass. </p> <p>In our dataset, you can find PM10 concentrations of WRF-Chem baseline simulations and other sensitivity-simulated PM10 concentrations of multi-sources of anthropogenic, wind-blown dust, and biomass-burning emissions. Furthermore, model meteorological variables of air temperature, wind, surface level pressure, and geopotential height can be found here.</p> <p>If you have any difficulty downloading these datasets, please feel free to contact the first author, kimhsung@gmail.com. All references and acknowledgments can be found in our paper.</p> <p> </p>
Derived data supporting the analysis of surface albedo changes from Mars 2020 observations: Probabilistic distribution of the Amplitude Spectral Densities of Supercam microphone recordings and Monte-Carlo dust devil simulations.
<p>These files contain derived data used in the analysis submitted for publication in Journal of Geophysical Research: Planets, entitled "Dust Lifting Through Surface Albedo Changes at Jezero Crater, Mars" by Vicente-Retortillo et al. The article was initially submitted on November 14, 2022, and the revised version on March 1, 2023.</p> <p>Files include the derived data and information needed to generate Figures 4 (Microphone_Data.mat and Plot_ASD_from_Microphone_Data) and 6 (remaining files) of the article.</p>
Infrared Transmission Spectra and Complex Refractive Indices of Surface Soils from Global Dust Entrainment Regions
<p>Spectral data for the paper “Variations in Infrared Complex Refractive Index Spectra of Surface Soils from Global Dust Entrainment Regions” submitted to the journal of <em>Atmosphere</em> Manuscript ID: atmosphere-2291559.</p> <p>Longwave infrared continuum removed transmission spectra, real (<em>n</em>) and imaginary (<em>k</em>) indices of refraction as well as subtractive Kramers-Kronig (SKK) MATLAB code presented in that paper are included in this Zenodo repository.</p> <p>The continuum removed transmission spectral data are stored in an Excel file format in columns and the first column is the wavelengths (µm). </p> <p>Real (<em>n</em>) and imaginary (<em>k</em>) indices of refraction for each sample are stored in a separate file where the first the column is the wavelengths (µm), and the second and third are <em>k</em> and <em>n</em> respectively.</p> <p> </p> <p>LWIR transmission: LWIR transmission was measured in the wavelength range between ~ 2.5 and 25 µm using a benchtop Nicolet 380 Fourier Transform Infrared (FTIR) spectrometer. First, we made soil-KBr pellets using ~ 0.5 mg of soil and ~ 200 mg of KBr blended using a clean mortar and pestle for 2 to 3 minutes to ensure uniform dispersion of mineral particles in the matrix. Pellet production was performed with the means of an evacuable KBr Die Kit and a CrushIR Digital Hydraulic Press from PIKE Technologies (Madison, WI, USA). The mixture was first transferred to the Die Kit which was then pressed under vacuum for about 4 to 5 minutes at a pressure of ~ 10 t cm<sup>-2</sup>, forming a hard disk 13 mm in diameter. Due to the hygroscopic nature of KBr, we pulled a vacuum on the pellet die for approximately 3 to 4 minutes prior to compression, and we immediately placed the pellets in a desiccant box, and then measured transmission within one or two hours of pellet creation.</p> <p>The pellet was attached to a self-adhesive sampling card and placed into the transmission holder. The resulting transmission spectrum for the sample is recorded with the dust-KBr mixture measurement being ratioed to that for an empty chamber, or blank reference. To avoid contamination of transmission spectra with ambient gases, the instrument was initially purged with dry air for at least 5 minutes, prior to each transmission collection. To increase the quality of the spectra and improve the SNR, the numbers of scans averaged were 200 for the blank reference and 100 for the samples.</p> <p>We ratioed transmission spectra to a blank KBr spectrum and then removed the continuum. The continuum removal (CR) transmission spectrum was employed to derive imaginary index of refraction (<em>k</em>) using Beer-Bouguer-Lambert law and <em>k</em> = <em>β<sub>a</sub></em>λ/4π. Real index of refraction (<em>n</em>) spectrum was consequently derived from the <em>k</em> spectrum with a subtractive Kramers-Kronig (SKK) technique. </p> <p>The spectral range of 4–25 μm was chosen to present the transmission spectra as well as real (<em>n</em>) and imaginary (<em>k</em>) indices of refraction since absorption in the region from 2.5 to 3.5 μm is mainly due to water and is not necessarily diagnostic.</p> <p>Here, we define any acronyms that may be present in the names of uploaded Excel files or their contents.</p> <p>*LWIR = Longwave infrared</p> <p>*T = Transmission</p> <p>*CR = Continuum Removed</p>
Data example and code used in the publication "Is transport of microplastics different from that of mineral dust? Results from idealized wind tunnel studies"
<p>Background</p> <p>The code labels microspheres and counts them. Further, the code determines which microspheres are independent of microsphere-microsphere collisions by their relative position to the other microspheres in an image. Images were taken with a full-frame visual camera (Sony Alpha 7RII) with a long-distance-microscopy lens (K2 DistaMax).</p> <p>Description of the dataset</p> <ul> <li>image_data_all.zip contains 228 tif-format images taken in a single experiment <ul> <li>the images show borosilicate microspheres with diameters from 63 to 75 µm</li> <li>during the experiment, the microspheres are detached from the substrate and are transported out of the image</li> </ul> </li> <li>functions_particle_labeling.jl contains all necessary functions for particle labeling</li> <li>analysis_protocol.jl is an example, that first determines a color threshold, and then labels all microspheres in all images stored in "image_data_all/substrate_a/image_data_single_experiment"</li> <li>post_processing_visualisation.R is an r-script, that reads the output of analysis_protocol.jl and demonstrates how logistic functions were fitted to the data</li> </ul> <p> </p> <p>We used julia 1.8.5 and R 4.3.0.</p> <p> </p>
Figure 6 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites
Figure 6 Scanning electron microscope for mites on fabrics: A – Cotton – LM (A1), DM (A2); B – Denim – LM (B1), DM (B2); C – Fleece - LM (C1), DM (C2).
Figure 3 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites
Figure 3 Mean number of LM (Live Mites), DM (Dead Mites) and EM (Euthanized Mites post fabric seeding) recovered according to each treatment applied irrespective of fabric type and duration of vacuuming. ∆ Mean value, and the central line in boxes represents median value of recovered mites.
Figure 5 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites
Figure 5 Scanning Electron Microscope image of the weave structure for fabrics used in this study. A – Cotton; B – Denim; C – Fleece.
Figure 4 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites
Figure 4 Mean number of LM (Live Mites), DM (Dead Mites) and EM (Euthanized Mites post fabric seeding) recovered from each fabric type according to duration of sampling irrespective of fabric type and vacuuming protocol applied. "*", "**" represent values for outliers (observations outside the interquartile range), ∆ Mean value. The central line in boxes represents median value of recovered mites.
Figure 2 in Recovery of Dermatophagoides pteronyssinus (Acariformes: Astigmata: Pyroglyphidae) is influenced by vacuuming protocol, fabric type and the viability of dust mites
Figure 2 Mean number of LM (Live Mites), DM (Dead Mites) and EM (Mites euthanized post fabric seeding) recovered from each fabric type irrespective of the vacuuming protocol used and duration of vacuuming. "*", "**" represent values for outliers (outliers are observations outside the interquartile range), ∆ Mean value, and the central line in boxes represents median of recovered mites.
Vertical profiling of the electrical properties of charged desert dust during the pre-ASKOS campaign: Dataset
<p>The zipped files contain the datasets used to produce Figure 1 of the following conference proceedings paper:</p> <p>Vasiliki Daskalopoulou, George Hloupis, Sotirios A. Mallios, Ilias Makrakis, Evangelos Skoubris, Maria Kezoudi, Zbigniew Ulanowski, & Vassilis Amiridis. (2021, July 6). <em>Vertical profiling of the electrical properties of charged desert dust during the pre-ASKOS campaign</em>. 15th International Conference on Meteorology, Climatology and Atmospheric Physics (COMECAP 2021), Ioannina, Greece. https://doi.org/10.5281/zenodo.5076042</p> <p>The repository contains overall:</p> <ol> <li>the ground-based JCI 131 Fieldmill Electrometer data that were acquired during the campaign (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Fieldmill_Ion_counter_Cyprus_campaign.rar">Fieldmill_Ion_counter_Cyprus_campaign.rar</a>)</li> <li>Data from an Alphalab Air Ion counter co-located with the fieldmill (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Fieldmill_Ion_counter_Cyprus_campaign.rar">Fieldmill_Ion_counter_Cyprus_campaign.rar</a>)</li> <li>Data from the five MiniMill electrometers that were launched (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/MiniMills_Cyprus_campaign.rar">MiniMills_Cyprus_campaign.rar</a>)</li> <li>Data from the two of the charge sensors that were launched (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Charge_sensors_Cyprus_campaign.rar">Charge_sensors_Cyprus_campaign.rar</a>)</li> <li>Data from the eleven ion counters that were launched, tethered together with the MiniMills or the charge sensors (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Ion_counters_Cyprus_campaign.rar">Ion_counters_Cyprus_campaign.rar</a>)</li> <li>A campaign calendar with the launches schedule (<a href="https://zenodo.org/api/files/b9a97eac-3bc2-4468-a43d-efa270ce8d95/Cyprus_campaign_November2019_calendar.pdf">Cyprus_campaign_November2019_calendar.pdf</a>).</li> </ol>
Figure 1 in A faunistic survey of house dust mites of Kolkata, West Bengal, India
Figure 1. Abundance of four major mites DP (Dermatophagoides pteronyssinus), DF (Dermatophagoides farina), BT (Blomia tropicalis), GC (Glycycometus domesticus) along with other mites from Kolkata, West Bengal.
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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)
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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
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.