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388 results for “Data element”
Understanding the impact of host networking elements on traffic bursts: Raw measurement data
<p>This record contains the raw trace files gathered by the Valinor network traffic burst measurement framework in Redis dump (rdb) format. Please refer to the artifact repository for instructions on how to parse and use the datasets:</p> <p><a href="https://github.com/hopnets/valinor-rawdata">hopnets/valinor-rawdata: Raw Redis datasets containing the measurement results of Valinor NSDI '23 paper (github.com)</a></p>
Raw target enrichment of conserved element sequence data for 24 black coral species
<p><span>Deep-sea lineages are generally thought to arise from shallow-water ancestors, but this hypothesis is based on a relatively small number of taxonomic groups. Anthozoans, which include corals and sea anemones, are significant contributors to the faunal diversity of the deep sea, but the timing and mechanisms of their invasion into this biome remain elusive. Here, we reconstruct a fully resolved, time-calibrated phylogeny of 83 species in the order Antipatharia (black coral) to investigate their bathymetric evolutionary history. Our reconstruction indicates that extant black coral lineages first diversified in continental slope depths (~250–3,000 m) during the early Silurian (~437 Ma) and subsequently radiated into, and diversified within, both continental shelf (<250 m) and abyssal (>3,000 m) habitats. Ancestral state reconstruction analysis suggests that the appearance of morphological features that enhanced the ability of black corals to acquire nutrients coincided with their invasion of novel depths. Our findings have important conservation implications for anthozoan lineages, as the loss of "source" slope lineages could threaten millions of years of evolutionary history and confound future invasion events, thereby warranting protection. </span></p>
Automatic Featurization Aided Data-Driven Method for Estimating the Presence of Intermetallic Phase in Multi-Principal Element Alloys
<p><strong>Description:</strong></p> <p>There are two folders in the dataset:</p> <p><strong>(A. ) AutomaticFeaturizerMPEA.zip</strong> : </p> <p>AutomaticFeaturizerMPEA.pynb is an interactive computational environment developed in python programming language to compute the properties of Multi Principal-component Element Alloy (MPEA) system .</p> <p>The code present in the .ipynb file is capable of firstly extracting composition feature from the name of MPEA and then compute thermodynamic/physical and chemical properties using these composition features. The properties that can be automatically calculated and featurized by the code are: <br> 1. Valence Electron Concentration<br> 2. Average Melting Temperature<br> 3. Enthalpy of Mixing<br> 4. Entropy of Mixing<br> 5. Electronegativity<br> 6. Atomic size difference<br> 7. Omega parameter <br> 8. 41 elemental composition</p> <p>The primary source used for the calculation of these alloy properties are taken from two python libraries: "pymatgen" and "matminer". </p> <p>The AutomaticFeaturizerMPEA.pynb is not only capable of calculating an alloy's properties but also featurizes them along with the composition and export it as a .csv file for further machine learning training process. The AutomaticFeaturizerMPEA.pynb file consists of two parts:</p> <p>1. "Part 1": A sample set of 25 MPEAs is used to demonstarte how to calculate & featurize the porperties and composition of alloy, save the calculated values in a .csv file.<br> 2. "Part 2": The alloy property of a single MPEA "Ti0.8CoCrFeNiCu" is calculated using the same code, if one needs to calculate them for a single MPEA at a time (as in our GUI application IMCATHEA https://github.com/subediupadesh/IMCATHEA) </p> <p>The repository also consists two "CSV" files:</p> <p>1. "MPEA_data.csv" file is the sample set of 25 collected MEPA observations with their source and phase information in one hot encoding method for which we want to calculate their properties and featurize them.<br> 2. "Featurized_MPEA.csv" file is the processed ready to train file which consists of MPEA, their properties and composition featurized in special order. It is the final file generated by the AutomaticFeaturizerMPEA.pynb python file.</p> <p> </p> <p><strong>(B.) IMCATHEA.zip:</strong> </p> <p>IMCATHEA is a python based Graphical User Interface application capable of detecting the IM phase in a High Entropy Alloy or Multi Principal Element Alloy system using a Neural Network Algorithm.</p> <p>## For Linux User:<br> Python with following libraries are needed to run the GUI application: pymatgen (v2022.0.16), matminer (v0.7.4), tensorflow (v2.2.0), pandas (v1.3.4), numpy (v1.21.2), tkinter (v8.6), sklearn (v1.0.1).</p> <p>"IMCATHEA_GUI.py" also needs 4 extra supporitng files (icon, standardizations, and model) to operate, which will be made available from the author upon reasonable request. </p> <p><br> ## For Windows User:<br> Executable (.exe) file: </p> <p>User can run "IMCATHEA_GUI.exe" wihout any softwares to be installed.</p> <p><br> ## Procedure for using "IMCATHEA" GUI Application:</p> <p>Step 0. Open / Run "IMCATHEA_GUI.py" (for Linux users) & "IMCATHEA_GUI.exe" (for Windows users) file to open the GUI application</p> <p>Step 1. User need to select the No. of Elements/Components in the HEA where IM phase is to be detected, from the dropdown menu at the top left corner.<br> After selection of element size/number (from 2 to 10),<br> <br> Step 2. User can select each element of HEA, one at a time from the drop down menu generated just below "No. of Component" tab</p> <p>Step 3. After selection of each element a blank space is provided just at the right side of selected element tab where user need to enter the corresponding composition/elemental fraction of the element.</p> <p>Step 4. Repeat Step 2-3 until the last element of the HEA and it's composition/elemental fraction is entered.</p> <p>Step 5. Press "Detect IMC" tab to get the prediction if IM is present in the provided HEA or not along with the physical properties of the entered HEA displayed in the right side of the GUI application.</p> <p>Step 6. If user wants to detect the presence or absence of IM phase for another HEA, user can click on "Restart" tab at the right top side of GUI application to restart the application instantly.</p> <p><br> If the user makes errors while selecting any options from dropdown menu as suggested in Step 1,2,3,4 user can click on "Restart" tab at the right top side of GUI application to restart the application instantly and start the process for prediction again from Step 1.</p> <p>## Video (YouTube) Tutorial for using IMCATHEA:<br> The stepwise process to predict the phase for an example case of "CrNbTiZr" MPEA is shown in the YouTube video tutorial at: https://youtu.be/G3aHE1Wsmgk</p>
Buzz pollination: Investigations of pollen expulsion using the discrete element method data
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Data from: LHFPL5 is a key element to the gating spring of cochlear hair cells: comparison of mechanotransduction channel activation in presence or absence of LHFPL5
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Data for the article: Coupling of leaf elemental traits with root fungal community composition reveals a plant resource acquisition strategy in a desert ecosystem
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Data from: A phylogenomic perspective on the biogeography of skinks in the Plestiodon brevirostris group inferred from target enrichment of ultraconserved elements
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Data from: Convergent evolution of noncoding elements associated with short tarsus length in birds
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Data from: Conodont size, trophic level and the evolution of platform elements.
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Data from: Diversification in Amazonian <em>Hypocnemis</em> antbirds (Aves: Thamnophilidae) inferred from Ultraconserved Elements (UCEs)
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Data from: Soil fauna trophic multifunctionality mediates the release of elements from decomposing typhoon generated leaf litter
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Data from: Diversity and evolution of the transposable element repertoire in arthropods with particular reference to insects
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Data from: Ultraconserved elements improve resolution of marmot phylogeny and offer insights into biogeographic history
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Data from: Ultraconserved element phylogenomics and biogeography of the agriculturally important mason bee subgenus Osmia (Osmia)
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Data for: Phylogenomic and population genomic analyses of ultraconserved elements reveal deep coalescence and introgression shaped diversification patterns in Lamprologine cichlids of the Congo River
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Data from: The fire ant social supergene is characterized by extensive gene and transposable element copy number variation
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Ultraconserved element data for phylogenomic analysis and four-gene Sanger dataset for phylogenetic analysis of Tenkana, a new genus of plexippine jumping spider (Salticidae, Plexippini, Plexippina)
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Data from: high repeat content in the genomes of sparrows: the importance of genome assembly completeness for transposable element discovery
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Data from: Variations in root functional traits facilitate the adaptation of pioneer plants to rare earth element mine tailings
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Raw target enrichment of conserved element sequence data for 24 black coral species
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Allen Brain Atlas
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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.