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1,393 results for “traces”
Combinational quantification of distinct neural projections from retrograde tracing
<p>This record contains the experimental cases with the following ids, used for data analysis of the paper. <br><br>SW190423-07<br>Sw190423-08<br>SW190423-09<br>SW190425-07<br>SW190425-08<br>SW190425-09<br>SW190425-10<br>SW190426-01<br>SW190426-02<br>SW190426-03<br>SW190816-01<br>SW190816-03</p>
222Rn tracing groundwater–lake water exchange in the transitional lake
<p>There are three tables including continuous monitoring data, profile radon activity data and sediments experiment data. The continuous monitoring table includes the time of continuous monitoring, radon in the profile, lake water temperature, and wind speed. Lake water volume, sediment mass, overlying water radon activity, wet density, porosity, pore water radon activity, and radon released per unit volume of sediment are listed in the sediment experimental data table.</p>
Data from: Comparison of priority rules, machine allocation, and stage allocation strategies for hybrid flow shop instances using combinatorial logic and a standard trace format
<p>datsets.zip contains benchmark data by Ruiz et al. (2008), Naderi et al.(2010), and Wittwock (1988). The according publications are listed in the related works section. The instances are publicly available under unclear license.</p><p>results.zip contains computational results for the aforementioned benchmarks using the algorithms described in "Comparison of priority rules, machine allocation, and stage allocation strategies for hybrid flow shop instances using combinatorial logic and a standard trace format". The data is licensed under Creative Commons Attribution 4.0 International license.</p>
TRACE Dataset: Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation
<p>Features dataset, as described in Simonovsky, Eyal, et al. "Predicting molecular mechanisms of hereditary diseases by using their tissue‐selective manifestation." <i>Molecular Systems Biology</i> (2023): e11407.</p><p>Article: https://doi.org/10.15252/msb.202211407</p><p>Code: https://github.com/eyalsim/trace</p>
The code and software to identify putative trace makers of horizontal trace fossils: Palaeontology
<p>These are the code ("CurveGithub.m") and the free software ("Curvesoftware.exe") that help you identify putative trace makers of horizontal trace fossils with frequency spectrum and autocorrelation function. You can also use it to study the frequency and size of self-repeating patterns in a horizontal trace. You can use the metrics to quantify ichnotaxonomy as well. An example of the coordinates of a horizontal trace is "A curve-Github.txt", which is output from Getdata Graph Digitizer, with the first describing sentence in the output file removed, leaving cooridnates only. Zero-value is not allowed in the coordinates. The paper is published in Palaeontology, with doi: 10.1111/pala.12686, <a title="Quantitative Ichnology" href="https://onlinelibrary.wiley.com/doi/abs/10.1111/pala.12686">https://onlinelibrary.wiley.com/doi/abs/10.1111/pala.12686</a> </p> <p>IMPORTANT NOTICE !!!!!</p> <p>MATLAB code Line 41:</p> <p>"plot(ss,YY(M:M+99)/max(YY(M:M+99)),'r-'); " means plotting the autocorrelation over sampling steps;</p> <p>If you would like to plot the autocorrelation over normalized length (as in both the manuscript and the free software), it should be</p> <p>"plot(ss/Fs,YY(M:M+99)/max(YY(M:M+99)),'r-'); "</p>
Multiplex DNA fluorescence in situ hybridization to analyze maternal vs. paternal C. elegans chromosomes - Gutnik et al - Tracing Datasets
<p>Tracing datasets (MATLAB Structure Format) from <i>C.elegans</i> N2 and HI embryos, as well as N2:HI and HI:N2 hybrid embryos presented in Gutnik et al.2024 (<strong>Multiplex DNA fluorescence in situ hybridization to analyze maternal vs. paternal </strong><i><strong>C. elegans</strong></i><strong> chromosomes)</strong></p><p> </p><p> </p><p> </p>
Dataset and codes: Abundance of trace fossil Phycosiphon incertum in core sections measured using a convolutional neural network
Open the record for dataset details and reuse information.
Virtual Reality Traces for Traffic Classification
<p>We use two Python scripts located in the 'Python Scripts' folder: one for `Feature Extraction' and another for the `Classification Model'. Initially, we extract features from raw packet traces, which have been stored in the 'Packet Traces' folder. The `Feature Extraction' script generates CSV output files, which become the input for the `Classification Model' script. The resulting input for the training and testing phase is stored in the folders of `Input For Training' and `Input For Test', respectively. Specifically, we have four designated folders: `Packet Traces', `Input For Training', `Input For Test', and `Python Scripts'.</p>
FIO (Zipfian) trace file for testing MiDAS code
<p>This trace is an FIO (Zipfian) trace file, designed for testing MiDAS code. It consists of 54 million write operations on a 4GiB block device.</p> <p>The format of the trace file is as follows: <br><strong><em><Time Stamp (s)> <Request Type> <LBA (unit: 4KB)> <Request Size> <Stream Number></em></strong></p> <ul> <li><strong>Time Stamp (in seconds):</strong> This is the time when the request is made to a block device.</li> <li><strong>Request Type:</strong> This is categorized into four types: 0 for READ, 1 for WRITE, 2 for NOT USED, and 3 for TRIM.</li> <li><strong>LBA (Logical Block Address, unit: 4KB):</strong> This represents the logical block address on the block device, with each unit of LBA being 4KB.</li> <li><strong>Request Size:</strong> This indicates the size of the request being processed.</li> <li><strong>Stream Number:</strong> This is used for multi-stream SSDs, but is not utilized in MiDAS.</li> </ul>
Detecting Usage of Deprecated Web APIs via Tracing: Replication Package
<p>Replication package for "Detecting Usage of Deprecated Web APIs via Tracing", published at 21st IEEE International Conference on Software Architecture (ICSA 2024)</p> <p> </p> <p>Changes from v2 to v3:</p> <ul> <li>readme.md: The requirements are now stated and explanations are given in more detail. Some typos in commands are fixed.</li> </ul> <p> </p> <p>Changes from v1 to v2:</p> <ul> <li>DATA: In addition to the intermedia data (output.json), the overall result files (results.json) are now provided as well for all example projects.</li> <li>IMPLEMENTATION: An incomplete version of the DeprecationDetector was present in v1. The new version includes extended matching functionality for specifications and improved export formatting.</li> <li>PROJECT: The server.jar in the client-server example project has been improved.</li> </ul>
Trace and rare-earth element composition of 2480 Ma detrital zircons in Proterozoic metapsammites from northwestern Arizona
<p>Detrital zircon grains in the ~1740-1750 Ma Vishnu Schist and similar rock units in northwestern Arizona consist of up to 30% grains dated by U-Pb isotopic analysis at 2470-2490 Ma. These zircon grains are distributed over ~40,000 km<sup>2 </sup>and define an age peak at 2480.0 ± 27.3 Ma (2SE). These grains have yielded unusually consistent <sup>207</sup>Pb/<sup>206</sup>Pb dates, with generally smaller analytical uncertainty and greater concordance to ideal U-Pb evolution than grains of other ages. A weighted mean age of 2480 ± 0.9 Ma (2SE) for this zircon population reflects consistent analytical results and high analytical precision but not the accuracy of the age. The source of these zircons has not been identified. To better characterize the unidentified source, we analyzed 45 of these grains for trace and rare-earth elements by laser-ablation mass spectrometry and scanned 16 grains with an electron microprobe to identify mineral inclusions. Mass spectrometer determinations of Sc/Yb and Nb/Sc support derivation from an oceanic-island igneous source. Electron microprobe scans revealed quartz in 5 of 16 grains, indicating a felsic source. The low variability in <sup>207</sup>Pb/<sup>206</sup>Pb dates and a generally linear relationship between U and Th support zircon derivation from a single igneous unit or closely related set of units without xenocrystic zircons. A literature search for other zircon populations with similar age and U/Th ratios identified ~2480 Ma zircons in a Mesoproterozoic(?) metapsammite and conglomerate in southwestern Montana. This sandstone was deposited near the margin of the Wyoming craton and contains almost entirely 2400-3600 Ma zircons, unlike zircon grains in Vishnu Schist which include a large population of 1730-1900 Ma zircons. From this relationship, we infer that the 2480 Ma zircons in both areas were derived from a source in the Wyoming craton. We conclude that the 2480 Ma Vishnu zircons were derived from a felsic batholith that formed above and from hotspot magma related to the ~2450-2480 Ma Matachewan Large Igneous Province, that this batholith formed by mixing between a mantle-derived hotspot magma and assimilated Archean continental crust, and that the source rock was emplaced during initial rifting between the Wyoming craton and the Superior province.</p>
Supplemental Dataset S2 for Tracing Fossil-Based Plastics, Chemicals and Fertilizers Production in China
<p>Supplemental Data S2 of the article "<em><strong>Tracing Fossil-Based Plastics, Chemicals, and Fertilizers Production in China</strong></em>" presents detailed calculation data. It provides calculation data across six key areas: the division of energy and feedstock used in fossil hydrocarbons, linking primary chemicals to downstream production, tracing the carbon source, evaluating CO2 mitigation potential, and comparing emission intensities. Uncertainty ranges are indicated alongside the process-based coefficients.</p>
Data from: Prebiotic membrane structures mimic the morphology of purported early traces of life on Earth
<p>Original microscopy files used in figures for publication.</p>
Exploring the preservation of a parasitic trace in decapod crustaceans using finite elements analysis
<p>The fossil record of parasitism is poorly understood, due largely to the scarcity of strong fossil evidence of parasites. Understanding the dynamics of preservation for fossil parasitic evidence is critical to contextualizing the fossil record of parasitism. Here, we present the first use of X-ray computed tomography (CT) scanning and finite elements analysis (FEA) to analyze the impact of a parasite-induced fossil trace on host preservation. Seven fossil and modern decapod crustacean specimens with branchial swellings attributed to an epicaridean isopod parasite were CT scanned and examined with FEA to assess differences in the magnitude and distribution of stress between normal and swollen branchial chambers. The results of the FEA show highly localized stress peaks in reaction to point forces, with higher peak stress on the swollen branchial chamber for all specimens, suggesting a possible shape-related decrease in the preservation potential of these parasitic swellings. Broader application of these methods as well as advances in the application of 3D data analysis in paleontology are critical to understanding the fossil record of parasitism and other poorly represented fossil groups.</p>
Dataset for "Ray Tracing of Whistler Mode Waves in Jupiter's Magnetosphere"
<p>Dataset for "Ray Tracing of Whistler Mode Waves in Jupiter's Magnetosphere". Containing all the ray tracing results that are used in this paper. </p>
Figure 1 in Air sac attachments or tendon scars: the distinction between soft tissue traces in archosaur bone
Figure 1. Lamellar bone fibres in an anhanguerid pterosaur ulna (DGEO-CTG-UFPE 7516; A-F) and in a spinosaurine theropod tibia (LPP-PV-0042; G-L). Note that these fibres are only visible at high magnifications (100×; arrowheads). Silhouettes in A and G indicate sampled elements (not to scale; art by Felipe A. Elias). All polarized light. Crossed nicols in A-E and G-L. Parallel nicols in F. Compensator in A-D, G-I and L. The relative angle to the cortical surface is approximately 80° in A, B; 340° in C; 290° in D-F; 120° in G-L. Scale bar in A, H = 250 µm; in B, I = 50 µm; G = 500 µm; in C-F, J-L = 10 µm.
Figure 4 in Air sac attachments or tendon scars: the distinction between soft tissue traces in archosaur bone
Figure 4. Side-by-side comparison between lamellar bone fibres A, pneumosteum B and Sharpey's fibres C, all indicated by arrowheads. A, an anhanguerid pterosaur ulna (DGEO-CTG-UFPE 7516). B, a megaraptoran theropod caudal vertebra (MPMA 08-003-94). C, a dorsal vertebra of Arrudatitan (MPMA 12-0001-97-1024). Magnifier indicates microscope magnification. All polarized light and crossed nicols. Compensator in B. The relative angle to the bone surface is approximately 290° in A; 320° in B; 150° in C. Scale bar in A = 10 µm; in B = 50 µm; in C = 300 µm.
Figure 3 in Air sac attachments or tendon scars: the distinction between soft tissue traces in archosaur bone
Figure 3. Pneumosteum in saurischian dinosaurs. A-C, a megaraptoran theropod caudal vertebra (MPMA 08-003-94). D-F, a cervical vertebra of the lithostrotian titanosaur Uberabatitan (CPPLIP-1024). G-I, a dorsal vertebra of the saltasaurid titanosaur Ibirania (LPP-PV-0200). Pneumosteum is distinguished from regular lamellar bone due to the presence of an array of tiny asbestiform densely packed fibres (usually shorter than 60 µm; arrowheads). These feature low optical relief and undulose extinction. Silhouettes in A, D and G indicate sampled elements (not to scale; art by Felipe A. Elias). All polarized light. Crossed nicols in A-E and G-I. Parallel nicols in F. Compensator in A-D, G-I, and L. The relative angle to the bone surface is approximately 320° in A-B; 220° in C-D; 105° in E-F; 290° in G; 80° in H-I. Scale bar in A, D = 250 μm; in C, E = 100 μm; in B, F, H, I = 50 μm; in G = 200 μm.
Figure 2 in Air sac attachments or tendon scars: the distinction between soft tissue traces in archosaur bone
Figure 2. Sharpey's fibres in a dorsal vertebra of Arrudatitan (MPMA 12-0001-97-1024; A-F) and in a spinosaurine theropod tibia (LPP-PV-0042; G-I). Note that these fibres are visible at low magnifications (5×; arrowheads). G, H show a cross pattern of Sharpey's fibres. Silhouettes in A and G indicate sampled elements (not to scale; art by Felipe A. Elias). All polarized light. Crossed nicols in A-F. Parallel nicols in. Compensator in G, H. The relative angle to the bone surface is approximately 150° in A-C; 90° in D; 70° in E; 120° in F; 90° in G-I. Scale bar in A = 300 µm; in D, I = 250 µm; in B, C, E, F = 100 µm; in G, H = 500 µm.
Satellite Traces simulated by virtual ionosonde experiment
<p>This dataset contains the ionospheric electron density distributions consisting of shallow and deep upwellings and a plasma bubble simulated from the High-resolution plasma bubble model, which were used as different cases of background ionosphere for the virtual ionosonde experiment. The resultant virtual ionograms consisting of main and satellite traces are also included in this dataset. </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.