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FIGURE 5 in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 5. Processed views of a fossil sample acquired by the optical FPP system OTY. Each view is re-oriented 60º degrees with respect to the prior. Where: "a" indicates a zone that has no information at 60º in this stage of the process and will be corrected with the information of the next view, as is shown in "b".
FIGURE 3 in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 3. Magnitude maps of the sample obtained every 60º for 8 and 128 pixels/period. The images show the resolution and detail levels given the number of fringes projected over the sample. The measurements' accuracy of surface and depth depends on the number of projected fringes, which include as many as the system can display (8 pixels/period for each fringe in this case). When the acquisition of details is difficult, a wider fringe is required (based on our sample size, we used 128 pixels).
FIGURE 1 in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 1. Optical set up specifications for fringe projection profilometry (FPP) used in this study for the recovery of a 3-D image of a hemimandible sample.
FIGURE 7 in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 7. Examples of analyses that can be performed with the obtained data from the fossils: 1) denoting the relief (emboss filter), 2) detecting edges and transitions (sobel filter), 3) study of the roughness and waviness of a sample (topography filter).
FIGURE 2 in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 2. Flowchart of the 'OTY' procedure employed in this study, where: α = angle (60º in this case), * = MBE algorithm (Gutiérrez-García et al., 2013), and ** = Goldstein algorithm. OTY: name given to the white light system together with the phase shifting algorithm filter, based on the fact that it was developed for use on Ototylomys samples (see main text).
FIGURE 6. Full 3-D in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 6. Full 3-D image of the reconstructed fossil after merging all the six views. 1) Cloud of points, 2) Final mesh.
FIGURE 4 in A novel application of the white light/fringe projection duo: recovering high precision three-dimensional images from fossils for the digital preservation of morphology
FIGURE 4. Process applied to recover the topography of the fossil sample. Where: 1) image captured by the CCD of the fringe projection on the sample, 2) wrapped phase obtained of the 8 frames after applying the MBE filter, 3) unwrapped phase map, 4) phase carrier compensation, and 5) surface of one of the views of the fossil recovered.
Supplementary material to the publication entitled "Digital transformation at what cost? A case study from Germany estimating the adoption potential of precision farming technologies under different scenarios" in Smart Agricultural Technology, https://doi.org/10.1016/j.atech.2024.100585
<p>The file '<em>PAT_Descriptions_Assumptions_Supplementary Material.pdf</em>' contains descriptions of the selected Precision Agricultural Technologies (PATs) and detailed explanations of the assumptions made in the calculation model.</p> <p> </p> <p>The file '<em>Calculation Model_NUTS3_BW.xlsx</em>' includes the calculation model created for the publication.</p>
Precisely controlled colloids: A playground for path-wise non-equilibrium physics
<p>Particle Trajectories from Non Equilibrium Steady State (Driven) and Equilibrium state.</p> <p>Number of trajectories can be found in the Book1.xlx </p> <p>File format description on the individual *.dat files is explained in the instructions.pdf</p> <p> </p>
Fig. 1 in LiDAR sensors in smartphones can enrich herbarium specimens with 3D models of habitat at high precision and little cost
Fig. 1. Example of a 3D point-cloud model of specimen habitat obtained with the LiDAR scanner of an iPad Pro. A, Plan view of the model with potential use cases, including annotation and extraction of general habitat characteristics; B, Side view with measurements that can be extracted from the model at centimetre precision (DBH, diameter at breast height); C, Average times needed for physical herbarium specimen collection (orange) and LiDAR scanning (purple) in the field over 20 replicates; time for scanning depends on the area scanned and the habitat.
Metabolic pathway prediction using non-negative matrix factorization with improved precision
<p>We include samples of various data types used in the work "Metabolic pathway prediction using non-negative matrix factorization with improved precision"</p> <p>More information about the software package and instructions are provided in <a href="https://github.com/hallamlab/triUMPF">hallamlab/triUMPF</a></p>
Data for paper "Constructing precisely quasi-isodynamic magnetic fields"
<p>This archive contains data and source code used for the paper "Constructing precisely quasi-isodynamic magnetic fields".</p>
Controlling long ion strings for quantum simulation and precision measurements
<p>Experimental data for the publication "Controlling long ion strings for quantum simulation and precision measurements" published in Physical Review A, 105, 052426 (2022)</p>
Data and materials for "The Consequences of Data Dispersion in Genomics: A Comparative Analysis of Data Sources for Precision Medicine" manuscript"
<p>Data and sripts for the "The Consequences of Data Dispersion in Genomics: A Comparative Analysis of Data Sources for Precision Medicine" manuscript" manuscript, sent to BMC Bioinformatics</p>
Precision Ephemerides for Gravitational-wave Sources+
<p>Zenodo repository containing datasets and ephemeris predictions from the Precision Ephemerides for Gravitational-wave Searches project. New ephemerides will be published here, and updated incrementally as new data is acquired.</p> <p><strong>Version history</strong></p> <ul> <li><strong>1.0.0-release</strong>: first data release based on the PEGS IV MNRAS publication</li> <li><strong>1.0.1: t_asc </strong>column now correctly corresponds to the neutron star time of ascending node.</li> <li><strong>1.0.2: </strong>now provide files tabulating our measured velocities, and velocity errors for each dataset.</li> </ul>
Onco-mNGS Facilitates Rapid and Precise Identification of The Etiology of Fever of Unknown Origin: A Single-centre Prospective Study in North China
<p>Supplemental Files and Data.</p> <p>Raw data for the copy numbers of chromosome were shown in fd.txt format. The picture of genomic of each sample was shown in png format.</p>
Precision agricultural data and ecosystem services: can we put the pieces together?
<ol> <li>Ecosystem services can maintain or increase crop yield in agricultural systems, but data to support management decisions is expensive and time-consuming to collect. Furthermore, relationships derived from small-scale plot data may not apply to ecosystem services operating at larger spatial scales (fields, landscapes).</li> <li>Precision yield data can be used to improve the accuracy and geographic range of ecosystem service studies, but have been underused in previous studies: out of 370 literature records, we found that less than 2% of all records were used to study biotic or landscape effects on yield. We argue that this is likely due to low data accessibility and a lack of familiarity with spatial data analysis.</li> <li>We provide examples of analysis using simulated and real precision yield data and outline two case studies of ecosystem services using precision yield data. Ecologists and agronomists should consider using precision yield data more broadly, as it can be used to test hypotheses about ecosystem services across multiple spatial scales, and could be used to inform the design of multifunctional farming landscapes.</li> </ol>
Data for ZIP Model, Tanzania Precision Mapping 2021
<p>Socio-demographic data to be imported into the ZIP model</p>
Perinatal Precision Medicine
ClinicalTrials.gov study NCT03211039. IPD Sharing: YES. Countries: 1. Publications: 11.
Precision agricultural data and ecosystem services: can we put the pieces together?
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.