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2,984 results for “Raw data”
Raw data for article "In Situ Synchrotron X-Ray Diffraction Characterization of Corrosion Products of a Ti-Based Metallic Glass for Implant Applications" Gostin et al 2018
<p>This repository contains raw data for the article "In Situ Synchrotron X-Ray Diffraction Characterization of Corrosion Products of a Ti-Based Metallic Glass for Implant Applications" by Gostin et al. 2018 in Advanced Healthcare Materials, 7, 1800338 (https://doi.org/10.1002/adhm.201800338).</p> <p>Most data comes from one beamtime at the Diamond synchrotron in the UK in May 2016. It consists of X-ray diffraction images taken in situ in artificial corrosion pits on a Ti-based metallic glass.</p> <p>Please see the README file for more details.</p>
Transient Electromagnetic data from the Los Humeros geothermal field in Mexico: raw data
<p>The dataset is composed of raw data from TerraTEM (from Monex GeoScope, single loop) from the Los Humeros geothermal field, Mexico and their locations in a .csv file.</p> <p>The data were gathered under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727550, and by the Mexican Energy Sustainability Fund CONACYT-SENER, Project 2015-04-268074.</p>
Raw and processed GO term data to support running GCEA analyses using ensemble-based nulls, as described in the manuscript, 'Overcoming bias in gene category enrichment analyses of brain-wide transcriptomic data'.
<p>Data to support a toolbox for performing gene category enrichment analyses, including against ensembles of null phenotypes.</p> <p>Descriptions of how these data files can be used for this purpose are in the documentation for the toolbox, at https://github.com/benfulcher/GCEA_FalsePositives</p>
Raw and analyzed data for manuscript: "An open-source surface barrier discharge plasma pretreatment for reduced cracking of outdoor wood coatings"
<p><strong>Highlights:</strong></p> <ul> <li>Surface barrier discharges are an affordable and available plasma technology for industrial, laboratory and home-workshop applications.</li> <li>Plasma pretreatments had no impact on the appearance of different protective wood coating for outdoor usage.</li> <li>The weathering performance of outdoor wood coatings improved by plasma, showing less cracks and less biotic factors.</li> </ul>
Fixed-Wing Micro UAV Open Data With Digicam And Raw INS/GNSS - IGN Flight 8
<p>The data set originate from a series of flights conducted with fixed-wing micro UAV carrying high-quality small camera and navigation sensors. This data was previously used in several peer-reviewed publications and will also be used in ISPRS workshop on dynamic networks given during the 2021 ISPRS Congress. This is part of a larger series of data that will be released gradually after incorporating user's feedback (e.g., on formats, description,etc.). The data set contains the sensor measurements from GPS, IMU and Camera.</p>
BAM reference data: EDS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a)
<p>The EDS spectra are given in the EMSA/MAS format as defined by ISO 22029:2012 Microbeam analysis — EMSA/MAS standard file format for spectral-data exchange. The exact locations of the sample areas measured with EDS are indicated in the SEM images.</p> <p>For further information please look at:</p> <p>- Radnik, J. Kersting, R., Hagenhoff, B., Bennet, F., Ciornii, D.; Nymark, P., Grafström R. and Hodoroaba, V.- D. <em>Nanomaterials </em><strong>2021</strong>, <em>11</em>, 639. https://doi.org/10.3390/nano11030639, and</p> <p>- Radnik, Jörg. (2021). BAM reference data: XPS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a) [Data set]. Nanomaterials. Zenodo. http://doi.org/10.5281/zenodo.4986068</p> <p>Measurement conditions:</p> <p>The EDS analysis in the present study has been performed with a QUANTAX 400 EDS system (BRUKER, Berlin, Germany), which is equipped with an SDD (Silicon Drift-Detector) of the 10 mm2 nominal area. An excitation of 10 keV was applied for the analysis of the titania samples prepared as a thick dry powder layer on an aluminum stub, so that the substrate cannot be coexcited. The analysis reas were selected as large as 5 x 5 µm<sup>2</sup> on sample agglomerates of about 1eng0 µm size.</p>
NoSyms: A neural network approach to detecting data structures in raw memory
<p>This data was used for a experiments with graph convolutional neural networks for memory forensics as part of a bachelor thesis (included as pdf).<br> <br> Abstract:<br> <br> This work presents a neural network based approach for data structure detection in raw memory that does not require an entirely matching description of the target data structure. Instead, it’s merely necessary to provide multiple descriptions of data structures similar to the target as training data in the form of debugging symbols. The core contribution of this work is a formal description and implementation of encoding data structure definitions as well as raw memory contents such that they can be processed by graph convolutional neural networks. A description and implementation of a neural network meant to detect data structures in the memory contents of a Linux Kernel demonstrates the practical applicability of the described approach.<br> <br> The Code is available on GitHub <a href="https://github.com/NiklasBeierl/nosyms">https://github.com/NiklasBeierl/nosyms</a>.<br> <br> nokaslr_dump is the qemu memory snapshot used to test the model.<br> nokaslr.raw is the "raw" form of the snapshot as produced by Volatility 3's layerwriter plugin.<br> symbols-training-data contains the Volatility symbol JSON files from which training data was derived.<br> nokaslr_pointers.csv lists the kernel space pointers in the snapshot and<br> nokaslr_tasks.csv lists task structs in the snapshot. Both were extracted via a Volatility plugins that are included in the GitHub Repo.<br> vmlinux-5.4.0-58-generic.json is the symbol file for the kernel the snapshot was taken from.<br> other-symbols.zip contains symbol files I generated vor various other kernels but did not end up using, use at your own discretion.</p>
Raw X-Ray CT data of CFC-Cu ITER monoblock mock-up
<p>Raw X-Ray CT data for CFC-Cu ITER monoblock mock-up. The monoblock was manufactured at Politecnico di Torino, Italy (Dr Valentina Casalegno) and X-ray tomography scanning was performed at the Manchester X-ray Imaging Facility, University of Manchester, UK (Dr Llion Evans).</p> <p>This data was used for the publication Evans, Ll.M. et al. "Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data", Fusion Engineering and Design 2015. DOI: 10.1016/j.fusengdes.2015.04.048</p>
Raw data acquired necessary to produce the plots introduced in the scientific paper: "Upper-limb kinematic reconstruction during stroke robot-aided therapy" (Medical & Biological Engineering & Computing)
<p>These files contain the raw data acquired necessary to produce the plots introduced the Figure 6 of the scientific paper: “Upper-limb kinematic reconstruction during stroke robot-aided therapy” (Medical & Biological Engineering & Computing).</p> <p>Fig. 6 shows the data recorded from two patients performing five forward/backward movements at InMotion2 robot before and after rehabilitation treatment. Mean values of the five execution have been reported in Fig. 6.</p>
Raw data employed to perform the algorithm used in the scientific paper: "Kinematic reconstruction of the upper limb joints in planar robot-aided therapies
<p>These files contain the raw data (acquired from different users) necessary to perform the algorithm introduced in the scientific paper:</p> <p>PAPER: Kinematic reconstruction of the upper limb joints in planar robot-aided therapies</p> <p>Authors: Arturo Bertomeu-Motos, Ricardo Morales, Jorge A. Díez, Luis D. Lledó, Francisco J. Badesa, Nicolas Garcia-Aracil</p> <p>Conference: ICORR 2015, IEEE 14th International Conference on Rehabilitation Robotics, August 2015</p> <p><br> All the orientations are expressed regarding the origin of the robot.</p> <p>a) Robot Joints: Planar robot joints acquired during the experiment, in radians (j1-j3 columns). This robot is referenced in the paper.<br> b) Quaternion IMU shoulder: Unit quatenion acquired through a 9DoFs Inertial Measurement Unit (IMU) developed by Shimmer (qw1-qz columns).<br> c) Upper arm acceleration: Acceleration acquired from a 3-axial accelerometer developed by Shimmer (X-Z columns). It is normalized regarding the gravity (9.81m/s^2).<br> d) Quaternion Tracker onto Shoulder: unit quaternion of the tracker placed onto the shoulder acquired from the tracking camera V120:trio developed by Optitrack (qw1-qz columns).<br> e) Quaternion Tracker onto Upper Arm: unit quaternion of the tracker placed onto the upper arm acquired from the tracking camera V120:trio developed by Optitrack (qw1-qz columns).</p>
Raw data employed to perform the algorithm used in the scientific paper: "Kinematic reconstruction of the human arm joints in robot-aided therapies with Hermes robot"
<p>This file contains the raw data necessary to perform the algorithm introduced in the scientific paper:</p> <p>PAPER: Kinematic reconstruction of the human arm joints in robot-aided therapies with Hermes robot</p> <p>Authors: Arturo Bertomeu-Motos, Ricardo Morales, Luis D. Lledó, Jorge A. Díez, Jose M. Catalan, Nicolas Garcia-Aracil.</p> <p>Conference: EMBC 2015, IEEE 37th International Conference in Medicine and Biology Society, August 2015.</p> <p>Raw data acquired necessary to perform thee algorithm introduced in this paper.</p> <p>a) Robot Joints: Robot joints generated to develop the simulation, in radians (j1-j7 colums). This robot is referenced in the paper.<br> b) Direct Upper Limb Joints: Upper limb joints generated to develop the simulation, in radians (q1-q7 columns). This data is used to simulate the accelerometer value.</p>
Raw data corresponding to the scientific paper: "A modular telerehabilitation architecture for upper limb robotic therapy" (Advances in Mechanical Engineering 2017, Vol. 9(1) 1-13)
<p>Acquired raw data necessary to implement the adaptive control strategy grounded on multimodal information.<br> In addition, raw data for the computation of the communication parameters needed for the assessment of the implemented telerehabilitation architecture are provided.</p> <p>a) End-effector positions and velocities (x, y, vx, vy) in three conditions: healthy (Fig 9) and constraint simulated stroke behaviour (Fig 10) without robotic assistance and simulated stroke behavior with robotic assistance (Fig 11)</p> <p>b) Performance indicators and control parameters for all the recruited subjects in both conditions healthy behaviour and simulated stroke behaviour (Fig 12a and Fig 12b)</p> <p>c) Computational values for evaluating telerehabilitation performance (Table 1)</p> <p> </p> <p> </p>
Raw male and female fitness data
<p>Raw male and female fitness data for 223 hemiclonal genotypes sampled from the LH<sub>M</sub> laboratory adapted population. See Gilks et al (2017; https://f1000research.com/articles/5-2644/v3) for full details on how these lines were established. Assays were designed to measure total adult lifetime fitness for both males and females from each line, under conditions that match as close as possible those experienced by adults in the base population (Chippindale <em>et al.</em>, 2001; Rice, 2005; Rice <em>et al.</em>, 2006).</p> <p><em>Male fitness assay</em><br> 5 hemiclonal males per line were combined in adult competition vials with 10 competitor <em>bw</em><sup>-</sup> males and 15 virgin <em>bw</em><sup>-</sup> females. After 2 days, each <em>bw</em><sup>- </sup>female was isolated into individual oviposition test-tubes (containing the cornmeal-molasses-agar media but with no additional dried yeast) and left to oviposit for 18 hours. On Day 12, progeny were scored for eye-colour, in two observation rounds to allow ensure that as many eclosing offspring were included. Hemiclonal males were assigned paternity to progeny with wild-type red eyes (progeny of competitors are homozygous for the <em>bw</em><sup>-</sup> allele and therefore have brown eyes), giving an average fitness score (number of offspring sired) for the 5 hemiclonal males that were assayed per line. This assay was independently replicated 5 times, representing data from a total of 25 hemiclonal males per line. Male fitness was calculated as the proportion of offspring sired per assayed male, which accounts for instances where less than 5 hemiclonal males were included (6 out of 1105 assays).</p> <p><em>Female fitness assays</em><br> Assays of female fitness followed a similar protocol to the male assays, again to match as close as possible the timing and conditions experienced by individuals in the base population. In this case, 5 virgin hemiclonal females were combined in adult competition vials with 10 competitor <em>bw</em><sup>- </sup>females and 15 <em>bw</em><sup>- </sup>males for 2 days. After 2 days, the 5 hemiclonal females were isolated into individual test-tubes and left to oviposit for 18hrs. The tubes were immediately chilled (4°C) to halt embryo development and the number of eggs per female was counted to provide a measure of fecundity. Data was excluded for tubes in which the female was either dead or not present. Since unmated females are known to produce eggs at a low rate, we also excluded data from females where egg counts were 0 or 1 as these are likely to represent output from unmated females (see Supplementary figure 1). By averaging fecundity across all 5 females this provided an average female fitness score for that line. This assay was independently replicated 5 times, representing a total of 25 hemiclonal females per line.</p> <p><strong>Dataset Column headings:</strong></p> <p><strong><em>Male</em></strong><br> sex - all male (value = 1)<br> rep - replicate (values from 1 to 5)<br> line - hemiclonal line (223 different lines, values from 1 to 230 with 7 lines missing)<br> red_1 - number of wild-type red-eyed offspring in first round of counting<br> red_2 - number of wild-type red-eyed offspring in second round of counting<br> brown_1 - number of brown-eyed offspring in first round of counting<br> brown_2 - number of brown-eyed offspring in second round of counting<br> total_red - number of offspring counted with wild-type red eyes (genotype bw<sup>+</sup>/bw<sup>-</sup>)<br> total_brown - number of offspring counted with brown eyes (genotype bw<sup>-</sup>/bw<sup>-</sup>)<br> male_density - number of hemiclonal males per vial (value usually 5, but may be less due to missing males)</p> <p>note: NA - missing value</p> <p><em><strong>Female</strong></em><br> sex - all female (value = 2)<br> rep - replicate (values from 1 to 5)<br> line - hemiclonal line (223 different lines, values from 1 to 230 with 7 lines missing)<br> f1 - fecundity of female 1<br> f2 - fecundity of female 2<br> f3 - fecundity of female 3<br> f4 - fecundity of female 4<br> f5 - fecundity of female 5</p> <p>note: NA - missing value</p> <p><strong>References</strong></p> <p>Chippindale, A.K., Gibson, J.R. & Rice, W.R. 2001. Negative genetic correlation for adult fitness between sexes reveals ontogenetic conflict in Drosophila. <em>Proc. Natl. Acad. Sci.</em> <strong>98</strong>: 1671–1675.</p> <p>Gilks WP, Pennell TM, Flis I et al. Whole genome resequencing of a laboratory-adapted <em>Drosophila melanogaster</em> population sample [version 3; referees: 2 approved]. F1000Research 2016, 5:2644 (doi: 10.12688/f1000research.9912.3)</p> <p>Rice, W.R. 2005. Inter-locus antagonistic coevolution as an engine of speciation: Assessment with hemiclonal analysis. <em>Proc. Natl. Acad. Sci.</em> <strong>102</strong>: 6527–6534.</p> <p>Rice, W.R., Stewart, A.D., Morrow, E.H., Linder, J.E., Orteiza, N. & Byrne, P.G. 2006. Assessing sexual conflict in the Drosophila melanogaster laboratory model system. <em>Philos. Trans. R. Soc. B Biol. Sci.</em> <strong>361</strong>: 287–299.</p>
Raw data of "Seasonal fluctuations of ichthyoplankton assemblage in the northeastern South China Sea influenced by the Kuroshio intrusion"
<p>The uploaded data here is the raw data of the manuscript "Seasonal fluctuations of ichthyoplankton assemblage in the northeastern South China Sea influenced by the Kuroshio intrusion" submitted to the Journal of Geophysical Research-Oceans. The CTD file (.cnv) is the data recorded by a Sea-Bird conductivity, temperature and depth (CTD) in the sampling stations. This data is used to analyze the water masses during the study period. It can be analyzed with free software of the Ocean Data View 4 (http://odv.awi.de/) or the MATLAB R2017 (http://www.mathworks.com/products/matlab/). The sequence data (.fasta) is used to evaluate the species composition. The data can be analyzed with free software of the BOLD Identification tool (http://www.boldsystems.org/), the basic local-alignment search tool (BLAST) (https://www.ncbi.nlm.nih.gov/), the Clustal X 2.1 (http://www.clustal.org/) and the MEGA 7 (http://www.megasoftware.net/). In additon, the .nc files are the data of surface temperature during the sampling periods. The data can be analyzed with the MATLAB R2017 (http://www.mathworks.com/products/matlab/).</p>
O(3P)+CO2 scattering cross sections at superthermal collision energies for planetary aeronomy: Raw data release
<p>Raw data and codes used in M. Gacesa, R. J. Lillis, and K. J. Zahnle, "O(3P)+CO2 scattering cross sections at superthermal collision energies for planetary aeronomy", MNRAS 491, 5650-5659 (2020).</p> <ul> <li>v1.1 includes <strong>differential cross section</strong> data for inelastic scattering: O(3P)+CO2(v=0,j=ji) -> O(3P)+CO2(v=0,jf) and energy transfer to the internal degrees of freedom calculated as in Gacesa & Kharchenko, Geophys. Res. Lett. 39, L10203 (2012).</li> </ul> <p>These files are distributed under GNU General Public License v3.0 and include NO liability or warranty of any kind. No support is provided by the authors. We cannot promise to answer any questions related to this dataset nor to prepare different products for you.</p> <p>Please cite this work as: Marko Gacesa, Lillis, Robert J., & Zahnle, Kevin J. (2019). O(3P)+CO_2 scattering cross sections at superthermal collision energies for planetary aeronomy: Raw data pre-release (Version v0.9-beta) [Data set]. Zenodo. <a href="http://doi.org/10.5281/zenodo.3256699">http://doi.org/10.5281/zenodo.3256699</a></p>
Raw experimental data for `Tailoring the Rotational Memory Effect in Multimode Fibers`
<p>Raw data for the article [**Tailoring the Rotational Memory Effect in Multimode Fibers**](https://arxiv.org/abs/2310.19337)</p><p>Measurement of transmission matrices and rotational memory effect for 4 segments of 50 micron core graded index multimode fibers with a numerical aperture of 0.2.</p>
The coupling mechanism of ligands with SERT distinguishes substrates from inhibitors (raw data)
<p>Raw data of the manuscript: Ligand coupling mechanism of the human serotonin transporter differentiates substrates from inhibitors</p> <p><strong>Abstract:</strong></p> <p>The presynaptic serotonin transporter (SERT) reuptakes the serotonin (5HT) released into the synaptic cleft, thus ensuring temporal and spatial regulation of serotonergic signalling. Clinically approved drugs used for the treatment of neurological disorders, including depression and anxiety modulate SERT by trapping the transporter in the outward-open conformation. Illicit drugs of abuse as amphetamines act as substrates but reverse the transport direction, thereby releasing intracellular accumulated 5HT. Both mechanisms increase extracellular 5HT levels. Stoichiometry of the transport cycle has been described by kinetic schemes, the structures of the main conformations within the transport cycle revealed static coordinates. By combining <em>in-silico</em> approaches with <em>in-vitro</em> experiments and making use of a homologous series of 5HT analogues, we decoded the essential coupling mechanism between the substrate and the transporter which triggers uptake. The free energy calculations showed that only scaffold-bound substrates can correctly close the extracellular gate by pulling on the bundle domain through long-range electrostatic interactions. The associated spatial and physico-chemical requirements define substrate and inhibitor properties, opening new possibilities for rational drug design approaches.</p>
Extracted raw data from: Global dominance of lianas over trees is driven by forest disturbance, climate, and topography
<p>In a meta-analysis, we use an unprecedented dataset, representing 556 unique locations worldwide, distributed across 44 countries and six continents to show for the first time that lianas (woody vines) thrive relatively better than trees when forests are disturbed, temperature increase, precipitation decrease, and particularly in tropical lowlands. We demonstrate that liana dominance can persist for decades post-disturbance and hinder the recovery of disturbed forests, especially when climate favours lianas. With implications for the global carbon sink, our findings suggest that degraded tropical forests with environmental conditions favouring lianas should be the highest priority to consider for restoration management.</p>
Raw data of healthy children and adults in a visual learning task, a conditional learning task and a transitive inference task.
<p>Raw data of 71<strong> </strong>healthy children (31 girls; average age: 6.42 years; range: 2.95-11.64 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.</p><p>Raw data of 22 healthy adults (11 femaleswomen; average age: 26.05 years; range: 20.32-29.76 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.</p>
Raw data for D1.1: Inventory of skills and competencies
<p>Raw data for the manuscript entitled: <strong>European Agrifood and Forestry Education for a Sustainable Future - Gap Analysis from an Informatics Approach</strong></p> <p><strong>Abstract</strong></p> <p><strong>Purpose: </strong>To evaluate how well European agrifood and forestry Masters program websites use vocabulary associated with the NextFood Project ‘categories of skills’.</p> <p><strong>Methodology: </strong>Web-scraping Python scripts were used to collect texts from European Masters programs websites, which were then analysed using statistical tools including Partial Least Squares Regression and contextual relation analysis. A total of fourteen countries, twenty-seven universities, 1303 European Masters programs, 3305 web-pages and almost two million words were studied using this approach.</p> <p><strong>Findings: </strong>While agrifood and forestry Masters programs used vocabulary from the NextFood Project ‘categories of skills’ in most cases equal to or more often than non-agrifood and forestry Masters programs, we found evidence for the relative underuse of words associated with networking skills, with least use among agriculture-related Masters programs. </p> <p><strong>Practical Implications: </strong>The informatic approach provides evidence that European agrifood and forestry Masters programs are for the most part following the educational paths for meeting future challenges as outlined by the NextFood Project, with the possible exception of networking skills.</p> <p><strong>Theoretical Implications: </strong>This text-based, informatic approach complements the more targeted approaches taken by the NextFood Project in studying the skilling-pathways, which involved focus-group interviews, surveys of stakeholders, interviews of individuals with expert-knowledge and literature reviews.</p> <p><strong>Originality: </strong>A text-based, web-scraping informatic approach has thus far been limited in the study of agrifood and forestry higher education, especially relative to recent advances made in the social sciences.</p>
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.