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739 results for “prints”
3D Printing of Double Network Granular Elastomers with Locally Varying Mechanical Properties
<p>Dataset for the article entitled "3D Printing of Double Network Granular Elastomers with Locally Varying Mechanical Properties", by Eva Baur, Benjamin Tiberghien and Esther Amstad published in Advanced Materials.</p>
Detecting anomalies in melt-extruded 3D printed parts using in situ data
<p>The data in this repository was gathered from a study to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing, using a set of sensors to non-destructively identfy printed parts that contain defects. The data underwent variance analysis to determine an "acceptable" range of filament diameters and non-destructivley identify spatial regions of printed cylinders in multi-part builds that contain defects.</p> <p>The data consists of two folders and a log meant to track procedural adherence for each cylinder printed, the introduced defects, or lack thereof, and the pressurization of the part. The "Final Build Logs" spreadsheet contains information regarding the two locations of the deformations along the 56 meters of filament needed to have no more than three anomalous cylinders out of the six printed cylinders, the date of the applied deformations to the filament, the initials of the researcher applying the deformations, the date that the build was printed along with the initials of the researcher who printed it, the part number, researcher initials, and date of the pressurization test for each cylinder within the build, and a comment describing any deviations from the procedure that play into the random error of the statistical analysis for each cylinder. </p> <p>The "Pressure Test Data" folder contains a folder for each build. Within these folders are .tdms files containing metadata on the measurement system in the header and tab-delimeted values for the columns. The columns of interest to the study are X_Value, representing time elapsed, and pressure, which we evaluated on the values' exponential decay rate. The files also contain supplemental information such as a column for temperature (celsius), and the flow rate (SLPM Normalized). The "Build Data" folder contains in situ data from the sensor-equipped printer in a .csv file, the STL file for the build, the gcode file from the applied slicer settings, the AMRP file stores printer settings, and a .pdf file for the setup specifications.</p>
Dataset for Effects of sacrificial coating material in laser shock peening of L-PBF printed AlSi10Mg
<p>Includes data received from confocal microscope, CT data, full XRD data, and all figures presented in the article.</p>
Microscopic images of screen-printed conductive layers on polymer fabrics
<p>The data collection includes data from SEM and optical microscope of screen-printed conductive layers on polymer fabrics (PET and cotton). The results of the work related to the attached data and detailed description of the layer production procedure were published in Rac-Rumijowska, O., Pokryszka, P., Rybicki, T., Suchorska-Woźniak, P., Woźniak, M., Kaczkowska, K., & Karbownik, I. (2024). Influence of Flexible and Textile Substrates on Frequency-Selective Surfaces (FSS). Sensors, 24(5), 1704.</p> <p> </p> <p>Description of the included files:</p> <p><strong><span>PET_Ag_PE672_cross_section_1</span></strong><span> – microscopic image of a cross-section of PET fabric covered with DuPoint PE672 silver paste – sample 1</span></p> <p><strong><span>PET_Ag_PE672_cross_section_2</span></strong><span> – microscopic image of a cross-section of PET fabric covered with DuPoint PE672 silver paste – sample 2</span></p> <p><strong><span>PET_Ag_PE674_cross_section_1</span></strong><span> – microscopic image of a cross-section of PET fabric covered with DuPoint PE674 silver paste – sample 1</span></p> <p><strong><span>PET_Ag_PE674_cross_section_2</span></strong><span> – microscopic image of a cross-section of PET fabric covered with DuPoint PE674 silver paste – sample 2</span></p> <p><span> </span><strong><span>SEM_PET_Ag_1W (1-9)</span></strong><span> – microscopic SEM image of a PET fabric covered with 1 layer of DuPoint PE672 silver paste – image 1-9</span></p> <p><strong><span>SEM_PET_Ag_2W (1-6)</span></strong><span> – microscopic SEM image of a PET fabric covered with 2 layers of DuPoint PE672 silver paste – image 1-6</span></p> <p><strong><span>SEM_PET_Ag_2W (1-6)</span></strong><span> – microscopic SEM image of a PET fabric covered with 3 layers of DuPoint PE672 silver paste – image 1-6</span></p> <p><strong><span>SEM_BAWELNA_Ag_2W (1-6)</span></strong><span> – microscopic SEM image of a cotton fabric covered with 2 layers of DuPoint PE672 silver paste – image 1-6</span></p> <p><strong><span>SEM_BAWELNA_Ag_3W (1-6)</span></strong><span> – microscopic SEM image of a cotton fabric covered with 3 layers of DuPoint PE672 silver paste – image 1-6</span></p> <p><strong><span>SEM_BAWELNA_Ag_4W (1-6)</span></strong><span> – microscopic SEM image of a cotton fabric covered with 4 layers of DuPoint PE672 silver paste – image 1-6</span></p> <p><strong><span>BAWELNA </span></strong><span><span> </span>– microscopic image of a cotton fabric</span></p> <p><strong><span>BAWELNA_Ag_4w (1-3) </span></strong><span><span> </span>– microscopic image of <span> </span>cotton fabric covered with 4 layers DuPoint PE674 silver paste – image 1-3</span></p> <p><strong><span>PET </span></strong><span><span> </span>– microscopic image of a PET fabric</span></p> <p><strong><span>PET_Ag_1W (1-2)</span></strong><span> – microscopic image of a PET fabric covered with 1 layer of DuPoint PE672 silver paste – image 1-2</span></p> <p><strong><span>PET_Ag_2W (1-3)</span></strong><span> – microscopic image of a PET fabric covered with 2 layers of DuPoint PE672 silver paste – image 1-3</span></p> <p><strong><span>PET_Ag_2W (1-2)</span></strong><span> – microscopic image of a PET fabric covered with 3 layers of DuPoint PE672 silver paste – image 1-2</span></p>
Print+Mill Dataset
<p>This dataset contains a comprehensive collection of data collected durring additive and subtractive manufacturing operations. it is design to facilitae research and development in manufacturing for the optizimation of production process paramters. The dataset includes images of 3D printed workpieces, as well as detailed CNC Milling machine data in both csv and pkl formats.</p> <p><strong>Dataset Contents:</strong></p> <ol> <li><strong>3D printed workpiece images</strong>: A collection of 3D printed workpiece images made from different materials, captured after the CNC milling operations. These images provide a visual representation of the workpieces quality after the subtractive manufactrring operations .</li> <li><strong>Dataset.csv</strong>: A CSV file containing data related to the milling operations performed on individual materials. This file includes various parameters recorded during the milling process, such as feed rate, spindle speed, Gcode parameters and data about temperature and power.</li> <li><strong>Dataset.pkl</strong>: A PKL file ontaining data related to the milling operations performed on individual materials. This file provides a detailed logs of machine state change durring the cnc machining operations that can be loaded into Python for analysis.</li> </ol> <p><strong>Note : </strong>This dataset is published as part of our recent work-in-progress paper (A Multi-Material and Multi-Scenario Dataset for<br>Additive and Subtractive Manufacturing Operations), which has been accepted at the IEEE ETFA 2024 - IEEE International Conference on Emerging Technologies and Factory Automation. This is the first version of the dataset, and we are working collecting data from other manufacturing operations. Any modifications or updates to this dataset will be included in future versions.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Data and Code For PhD Thesis- Making an Impression: An Assessment of the Role of Print Surfaces Within the Technological, Commercial, Intellectual and Cultural Trajectory of Book Illustration c.1780-c.1860.
<p><strong>Overview</strong></p> <p>These datasets support research found in the PhD Thesis entitled: Making an Impression: An Assessment of the Role of Print Surfaces Within the Technological, Commercial, Intellectual and Cultural Trajectory of Book Illustration c.1780-c.1860, submitted by William Finley. The data was provided by the British Library as part of a wider ambition to digitise millions of book illustrations (further details can be found here: <a href="https://github.com/BL-Labs/imagedirectory">https://github.com/BL-Labs/imagedirectory</a>). The main dataset contains 6063 rows and 108,784 illustrations. All of the data is held in comma-separated values (csv) files. The collection has been subdivided in order to interrogate the dataset further. All of the datasets have been interrogated using Rscript (R 3.4.2 El Capitan Build), the codes of which have been included in the dataset repository. </p> <p><strong>Guidance to Datasets</strong></p> <p>'Counts of Illustration by Size over Time'</p> <ul> <li>Title: Title of Book</li> <li>Author: Author of Book </li> <li>Pub_Place: Location the book was published</li> <li>Book_Id: British Library image identifier </li> <li>YEAR: Year the book was published</li> <li>Image_Count: Number of illustrations belonging to that book</li> <li>N: Number of illustrations according to the size of illustration</li> <li>IMAGE_TYPE: Size of Illustration </li> </ul> <p>'Density Graphs of the Position of Illustrations on the Page'</p> <ul> <li>X1: The X position in pixels of the top left of the image</li> <li>Y1: The Y position in pixels of the top left of the image</li> <li>X2: Width in pixels of the Image</li> <li>Y2: Height in pixels of the Image</li> <li>PERCENT_PAGE: Percentage of the page taken up by illustrations</li> <li>TYPE: Percentage Range of the Page taken up by illustrations </li> <li>VOL: Volume</li> </ul> <p>'Frequency of Illustrations Across First 100 Pages of the Book 1800-1850'</p> <ul> <li>Page: Page number </li> <li>X1: The X position in pixels of the top left of the image</li> <li>Y1: The Y position in pixels of the top left of the image</li> <li>X2: Width in pixels of the image</li> <li>Y2: Height in pixels of the image</li> <li>PERCENTPAGE: Percentage of the page occupied by illustration</li> <li>SIZE: Size category each illustration belongs to</li> </ul> <p>'Illustration Arrangement in Single Books and Editions'</p> <ul> <li>Book_ID: British Library image identifier</li> <li>Page_NO: Page Number Illustration is found on </li> <li>X: The X position in pixels of the top left of the image</li> <li>Y: The Y position in pixels of the top left of the image </li> <li>WIDTH: Width in pixels of the image</li> <li>HEIGHT: Height in pixels of the image</li> <li>IMAGE_SIZE: Percentage of the page occupied by illustration</li> </ul> <p>'Relative Frequency of Printing Methods Over Time'</p> <ul> <li>Publisher: Publisher of the book</li> <li>Title: Title of the book</li> <li>first_author: Author</li> <li>pub_place: Location the book was published</li> <li>book_identifier: British Library image identifier</li> <li>Year: Year the book was published </li> <li>COUNT_IMAGE: Number of illustrations found in a given book</li> <li>YEAR_BOOK_COUNT: Number of book published in a given year</li> <li>YEAR_IMAGE: Number of Illustrations found in books published in a given year</li> <li>AVERAGE_IMAGE: Average number of illustrations found in books published in a given year</li> <li>IMAGE_METHOD: Print method used to produce the illustration</li> <li>IMAGE_SIZE_COUNT: Number of illustrations printed in books in a given year according to its size</li> <li>IMAGE_SIZE: Categories of image sizes</li> </ul> <p><strong>Contact</strong></p> <p>Will Finley can be contacted via the following email. Information listed is accurate at the time of publication</p> <p>Email: wafinley1@sheffield.ac.uk</p> <p> </p> <p> </p>
Dataset of Pages from Early Printed Books with Multiple Font Groups
<p>This dataset is composed of photos of various resolution of 35'623 pages of printed books dating from the 15th to the 18th century. Each page has been attributed by experts from one to five labels corresponding to the font groups used in the text, with two extra-classes for non-textual content and fonts not present in the following list: Antiqua, Bastarda, Fraktur, Gotico Antiqua, Greek, Hebrew, Italic, Rotunda, Schwabacher, and Textura.</p> <p>Note that to make downloading the dataset with slow or unreliable Internet connections easier, the dataset has been separated in several zip files. All zip files must be extracted in the same folder. The CSV files containing the labels should ideally be in the parent folder.</p> <p>The labels are provided in two CSV files, one for training/tuning font group recognition methods, and the second one for evaluation purposes. Where several pages come from the same book, a special care has been taken to have all of them in the same subset.</p> <p>The paper presenting this dataset in detail is "Dataset of Pages from Early Printed Books with Multiple Font Groups", accepted at the 5th International Workshop on Historical Document Imaging and Processing, Sydney, Australia.</p> <p>We would like to thank the British Library (London), Bayerische Staatsbibliothek München, Staatsbibliothek zu Berlin, Universitätsbibliothek Erlangen, Universitätsbibliothek Heidelberg, Staats- und Universitäatsbibliothek Göttingen, Stadt- und Universitätsbibliothek Köln, Württembergische Landesbibliothek Stuttgart and Herzog August Bibliothek Wolfenbüttel for the data they sent us and kindly allowed us to use for this public dataset.</p>
Fig. 2. Print from x in Xyrichtys Koteamea, A New Razorfish (Perciformes: Labridae) From Easter Island
Fig. 2. Print from x-ray of 202-mm paratype of Xyrichtys koteamea showing the hook that caught the specimen.
Fig. 10 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 10. Hydrodynamic restoration of the Baculites compressus 3D printed model following overdamped harmonic motion. Apertural angle (θa) measured in degrees as a function of time after rotating approximately 38° from the equilibrium orientation. An angle of -90° represents a condition where the aperture is directed downwards. The function of decay in θa with time is represented by the grey dashed curve. Note that this model restores more quickly and does not oscillate about the equilibrium orientation.
Fig. 7 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 7. Virtual and physical hydrostatic models of Nautilus pompilius with computed percentage of the phragmocone emptied for neutral buoyancy (Φ) and hydrostatic stability (St). The tip of the up-side-down pyramid = center of buoyancy. The tip of the right-side-up pyramid = total center of mass. A. External view of the virtual model. B. Medial section of the virtual model with each component of unique density (green, soft body; red, cameral gas; blue, cameral liquid; grey, shell). C. Modified virtual model with simplified internal geometry and bismuth counterweight (yellow, PLA plastic; red, air; blue, liquid; purple, bismuth counterweight). D. Neutrally-buoyant, 3D printed model. The differences in Φ and the apertural angle (θa) are a result of the mass discrepancy (Table 5) and irregular geometry of the balloon. The error in St was computed assuming that the total mass discrepancy was distributed in the positive or negative z-directions.
Fig. 9 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 9. Virtual and physical hydrostatic models of Baculites compressus with computed percentage of the phragmocone emptied for neutral buoyancy (Φ) and hydrostatic stability (St). Green, soft body; grey, shell; red, gas; blue, liquid; yellow, PLA plastic; purple, bismuth counterweight; B, center of buoyancy; M, center of mass. A. Virtual model with an even distribution of cameral liquid and gas in the phragmocone (center of mass of cameral liquid and gas = center of volume of the phragmocone; cameral liquid and gas not shown). B. Modified virtual model with simplified internal geometry ("Modified 1" in Table 3). C. Neutrally-buoyant, 3D printed model. D. Modified virtual model with simplified internal geometry and axel hole through pivot point of rotation ("Modified 2" in Table 3). E. Neutrally-buoyant, 3D printed model fixed to an axel and silicone tubing used to supply thrust in the ventral direction. For this model, the mass discrepancy (Table 5) resulted in a slightly lower of 97.3%, but was held constant at 100%. All computed errors in St were computed assuming that the total mass discrepancy was distributed in the positive or negative z-directions.
Fig. 6 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 6. Hydrostatic models of Baculites compressus with computed percentage of the phragmocone emptied for neutral buoyancy (Φ) and hydrostatic stability (St). All models are oriented dorsum-left. The centers of buoyancy are marked by the tip of the higher pyramid. The total centers of mass are marked by the tip of the lower pyramid. Each material of unique density is designated a color (green, soft body; red, cameral gas; blue, cameral liquid; transparent grey, shell). A. Virtual model with 40% body chamber length to total length (BCL/L). B. Virtual model with 33% BCL/L and adorally distributed cameral liquid. C. Virtual model with 33% BCL/L and adapically distributed cameral liquid. D, E. B. compressus model modified with a concave dorsum similar to B. grandis and 33% BCL/L. Adorally (D) and adapically (E) distributed cameral liquid.
Fig. 3. Full 3D in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 3. Full 3D model of Baculites compressus with model components. A. Complete, digitally-reconstructed shell rendered in X-ray view to show internal structure. B. Three-dimensional model the soft body. C. Three-dimensional model of the cameral volumes within the phragmocone.
Fig. 4 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 4. Generation of a 3D printed model of Nautilus pompilius with theoretically equal physical properties to the virtual counterparts. A. Original virtual model from Peterman et al. (2019: fig. 2.5). B. Modified virtual model with simplified internal geometry. The center of buoyancy remains the same because external geometry does not change. The total center of mass, however, is corrected by a bismuth counterweight of known volume, density, and mass. C. 3D printed posterior half of the physical model with bismuth counterweight in the computed position. D. Anterior half of the physical model showing the one-way valve for liquid to exit upon displacement by an air-filled balloon. E. Neutrally buoyant physical model with the required volume to liquid ratio for neutral buoyancy. This computed volume of air is inserted through a one-way entrance valve into the internal balloon. Tracking points are placed parallel to the aperture in order to analyze movement in a hydrodynamic setting.
Fig. 5 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 5. Position of the ventral tracking point (V) and umbilical tracking point (U) as a function of time measured with the physics modeling software (Tracker 4.11.0; Brown 2017). Note that the rotation of the aperture is coupled with translational motion, resulting in complex movement.
Fig. 11 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 11. Thrust required to change the Baculites compressus model orientation (θa). A. Thrust Scenario 1: A continuous thrust supplied to the venter with a similar thrust ratio to Nautilus (Table 1). The average change from a vertical resting orientation (Δ θpeak) is 22.7°. B. Thrust Scenario 2: Periodic pulses from a pump with a simulated mantle cavity of 20% soft body volume of B. compressus (Table 1). The average change from a vertical resting orientation ( Δ θpeak) is 25.6°. C. Thrust Scenario 3: Periodic pulses from a pump with a thrust ratio between Sepia officinalis and Loligo vulgaris (Table 1). The average change from a vertical resting orientation (Δ θpeak) is 72.2°. Average peak thrust (Fpeak) error bars represent one standard deviation calibrated from 30 second intervals of pumping.
Fig. 8 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 8. Hydrodynamic restoration of the Nautilus pompilius 3D printed model following underdamped harmonic oscillation. Apertural angle (θa) measured in degrees as a function of time after rotating approximately 38° from the equilibrium orientation. An angle of zero represents a condition where the aperture is horizontally oriented. Open dots represent the peaks used to calculate decay in amplitude with time (grey dashed curves).
Fig. 2 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 2. Shell and septum thickness measured from three specimens of Baculites compressus (WSU-1400, WSU-1401, and WSU-1405). Exponential curves were fit to these points to define thickness for the full 3D model as a function of whorl height.
Fig. 1 in Mode of life and hydrostatic stability of orthoconic ectocochleate cephalopods: Hydrodynamic analyses of restoring moments from 3D printed, neutrally buoyant models
Fig. 1. Three-dimensional reconstruction of a fragmentary baculite Baculites compressus Say, 1820 (WSU-1400) from the late Campanian Pierre Shale of Meade County, South Dakota. A. Model of a fragmentary specimen generated by photogrammetry with the software (3DF Zephyr). B. Broken septum isolated from the photogrammetry model. C. Suture pattern. D. Complete septum created by reconstructing the higher-order frilling with the suture pattern as a template.
Development Interior Product Using 3D Printing Technology and Waste Management
<p><span>This research aims to increase the variety of interior accessories that can be produced by MSMEs in Malang City and can be used as souvenirs because they carry elements of the locality of Malang City. The 3D printing technology that will be used is the lithophane technique and utilizes 3D printing pen waste on a household scale.</span></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.