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638 results for “thinning”
Figure 2 in The employment of a conformal polydopamine thin layer reduces the cytotoxicity of silver nanoparticles
Figure 2. Cell viability test of NP systems at different concentrations.
Data and Code for "Mesoscale modeling of deformations and defects in thin crystalline sheets"
<p>Research data and code supporting the paper ""Mesoscale modeling of deformations and defects in thin crystalline sheets"".</p> <p> </p> <p><strong>Code (apfc-python-surf.zip)</strong></p> <p>The implementation of the APFC model is performed in python by exploiting the pseudo-spectral Fourier method. Library pyfftw is adopted. However, standard fft libraries can be used as well by changing the corresponding module/functions. The code supports equations of the APFC model both coupling with the evolution of the surface considered in this work and on a simple flat domain. Updates can be found in the GitLab repository linked below.</p> <p> </p> <p><strong>GitLab repository for the code</strong></p> <p><a href="https://gitlab.com/3ms-group/apfc_python/">https://gitlab.com/3ms-group/apfc_python/</a></p> <p> </p> <p><strong>Data</strong></p> <p>The data.zip files contain the simulation results and auxiliary scripts used to produce the results illustrated in the paper's figures. The folder numbering refers to the one used for the figures in the final version.</p> <p> </p> <p>For further information please contact the authors.</p>
Hydrodynamic thinning of a coating film induced by a small solid defect: evidence of a time-minimum thickness
<p>groove_min.csv contains the data of the section on the minimum of the groove thickness.</p> <p>Newton.csv contains the data of the section on the Newton film.</p> <p>fig1.bil and fig8.bil are the files of the datacubes of the space-time diagrams of Fig.1 and 8 respectively, and the .bil.hdr file is the header corresponding to the .bil file.</p> <p>w header.csv is the header for the w files, which are all the remaining files; it contains the name of the files and the initial thickness e0 and fiber radius rf to make the correspondence with the remaining files.</p> <p>fig2.csv contains the thickness profiles (in nm): each row is the thickness profile at one time, and the last two rows are the time vector (in s) and the space vector (in m).</p> <p>fig3a.csv contains the data of the thickness and the position of the groove, and the time used in Fig.3.</p> <p> </p>
A Novel Integrated Reference-Counter Electrode for Electrochemical Measurements of HOMO and LUMO Levels in Small-Molecule Thin-Film Semiconductors for OLEDs
<p>This dataset <span>includes all raw data, processed data, and analysis scripts necessary to replicate the findings reported in the published paper.</span></p>
Accurate Determination of the Uniaxial Complex Refractive Index and the Optical Band Gap of Polymer Thin Films to Correlate their Absorption Strength and Onset of Absorption
<p>The uploaded datasets contain complex refractive indices of polymer thin films and a glass substrate and are published in connection with the following article:</p> <p>Kamptner, Scharber, Schiek.<br>Accurate Determination of the Uniaxial Complex Refractive Index and the Optical Band Gap of Polymer Thin Films to Correlate their Absorption Strength and Onset of Absorption.<br>ChemPhysChem 2024.</p> <p><a href="https://doi.org/10.1002/cphc.202400233">https://doi.org/10.1002/cphc.202400233</a></p> <p> </p> <p><strong>F8BT</strong> (or PFBT): Poly(9,9-dioctylfluorene-alt-benzothiadiazole).</p> <p><strong>MDMO-PPV</strong> (or OC1C10-PPV): Poly-[2-(3,7-dimethyloctyloxy)-5-methyloxy]-para-phenylene-vinylene.</p> <p><strong>PBDB-T-2F</strong> (or PBDB-T-F, PBDB-TF, PM6): Poly[(2,6-(4,8-bis(5-(2-ethylhexyl-3-fluoro)thiophen-2-yl)-benzo[1,2-b:4,5-b’]dithiophene))-alt-(5,5-(1’,3’-di-2-thienyl-5’,7’-bis(2-ethylhexyl)benzo[1’,2’-c:4’,5’-c’]dithiophene-4,8-dione)].</p> <p><strong>PDCBT</strong>: Poly[2,2''''-bis[[(2-butyloctyl)oxy]carbonyl][2,2':5',2'':5'',2'''-quaterthiophene] -5,5'''-diyl].</p> <p><strong>PTB7</strong>: Poly[[4,8-bis[(2-ethylhexyl)oxy]benzo[1,2-b:4,5-b']dithiophene-2,6-diyl][3-fluoro-2-[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophenediyl]].</p> <p><strong>ZZ50</strong> (or c-PCPDTBT): Poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4-b']dithiophene)-alt-4,7(2,1,3-benzothiadiazole)].</p> <p><strong>float glass</strong> objective slide (Marienfeld) "tin" and "air" side.</p>
In-vivo video microscopy of the rupturing process of thin blood vessels in transparent fish during contact with a blunt indenter
<p>To clarify the mechanism of bruise injuries caused by blunt impact, in vivo microscopy was performed. A flat ended indenter made of transparent acrylic was loaded onto the lateral side of the tail region of anesthetized fish. The process of the rupture of thin blood vessels was recorded in two specimens.</p> <p>This data set includes two types of files; (1) mp4 files of the in vivo microscopy; (2) pdf files to explain the mp4 files.</p> <p><span>The mp4 files are the original data of “Fujikawa, T., Yamada, Y. In vivo video microscopy of the rupturing process of thin blood vessels to clarify the mechanism of bruising caused by blunt impact: an animal study. BioMed Eng OnLine 23, 94 (2024). https://doi.org/10.1186/s12938-024-01284-2.”</span></p>
Data for "Ultrafast Excitonic Transitions in Enantiopure and Racemic Squaraine Thin Films"
<p>Here we present the raw data and data processing files for the paper entitled "Ultrafast Excitonic Transitions in Enantiopure and Racemic Squaraine Thin Films", which is published in Aggregate.</p>
Preparation techniques of thin cyanoacrylate adhesive films for interface analysis
<p>For understanding the interactions between adhesives and different surfaces, the in-situ characterization of the interface is essential. Especially for highly reactive cyanoacrylates, better known as instant adhesives, the adhesion mechanism is poorly understood because, among other things, the characterization of the interface is difficult. The objective of this work is to evaluate the methods of thermal evaporating and spin coating to produce nm-thin, homogeneous films of cyanoacrylate. The aim is to enable spectroscopic analysis of the interface in the future.</p>
Pretraining convolutional neural networks for mudstones petrographic thin section image classification
<p>This dataset was used in the paper "Pretraining convolutional neural networks for mudstones petrographic thin section image classification"</p>
In Situ Epitaxy of Pure Phase Ultra-Thin InAs-Al Nanowires for Quantum Devices
<p>This repository contains the raw data and processing codes of the paper "<em>In Situ</em> Epitaxy of Pure Phase Ultra-Thin InAs-Al Nanowires for Quantum Devices".</p>
Images of Thin Cuboids Transported on a Chute - Recording 5
<p>This data set comprises images of thin cuboids on a chute. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the Tablesort system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>, Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/inside-schuettgut.html">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings on optical sorters. Please use the search function with the keyword "Tobias Hornberger" (in quotes) to find them.</p> <p>The camera was recorded on a Bonito CL-400C. The calibration image for the extrinsic parameters can be found in calibration_extrinsics.png for the extrinsics and calibration_color.png for the color calibration. Please see the debayer script on <a href="https://github.com/geomai/debayer_bonito">GitHub</a><strong>.</strong> The frame rate is 192.9 Hz.</p> <p>Algorithms for two key challenges can be developed and evaluated on the data sets:</p> <ol> <li>Multitarget tracking for predicting the particle’s motion. This can be used to enhance the separation of optical sorters. For further details on this, see the publications <ul> <li><em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials,</strong><br> Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015.</li> <li><em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>Predictive Tracking with Improved Motion Models for Optical Belt Sorting</strong>,<br> at – Automatisierungstechnik, April 2020.</li> </ul> </li> <li>Classification of particles. The classification may use a multitarget tracker to accumulate visual features over time. One can also use the information on the trajectory to classify the particles. For information on this, refer to <ul> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information,</strong><br> Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017.</li> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Motion-Based Material Characterization in Sensor-Based Sorting,</strong> <br> tm – Technisches Messen, De Gruyter, October 2017.</li> </ul> </li> </ol> <p><strong>Acknowledgment</strong></p> <p>The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.</p>
Images of Thin Cuboids Transported on a Chute - Recording 4
<p>This data set comprises images of thin cuboids on a chute. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the Tablesort system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>, Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/inside-schuettgut.html">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings on optical sorters. Please use the search function with the keyword "Tobias Hornberger" (in quotes) to find them.</p> <p>The camera was recorded on a Bonito CL-400C. The calibration image for the extrinsic parameters can be found in calibration_extrinsics.png for the extrinsics and calibration_color.png for the color calibration. Please see the debayer script on <a href="https://github.com/geomai/debayer_bonito">GitHub</a><strong>.</strong> The frame rate is 192.9 Hz.</p> <p>Algorithms for two key challenges can be developed and evaluated on the data sets:</p> <ol> <li>Multitarget tracking for predicting the particle’s motion. This can be used to enhance the separation of optical sorters. For further details on this, see the publications <ul> <li><em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials,</strong><br> Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015.</li> <li><em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>Predictive Tracking with Improved Motion Models for Optical Belt Sorting</strong>,<br> at – Automatisierungstechnik, April 2020.</li> </ul> </li> <li>Classification of particles. The classification may use a multitarget tracker to accumulate visual features over time. One can also use the information on the trajectory to classify the particles. For information on this, refer to <ul> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information,</strong><br> Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017.</li> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Motion-Based Material Characterization in Sensor-Based Sorting,</strong> <br> tm – Technisches Messen, De Gruyter, October 2017.</li> </ul> </li> </ol> <p><strong>Acknowledgment</strong></p> <p>The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.</p>
Images of Thin Cuboids Transported on a Chute - Recording 2
<p>This data set comprises images of thin cuboids on a chute. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the Tablesort system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>, Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/inside-schuettgut.html">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings on optical sorters. Please use the search function with the keyword "Tobias Hornberger" (in quotes) to find them.</p> <p>The camera was recorded on a Bonito CL-400C. The calibration image for the extrinsic parameters can be found in calibration_extrinsics.png for the extrinsics and calibration_color.png for the color calibration. Please see the debayer script on <a href="https://github.com/geomai/debayer_bonito">GitHub</a><strong>.</strong> The frame rate is 192.9 Hz.</p> <p>Algorithms for two key challenges can be developed and evaluated on the data sets:</p> <ol> <li>Multitarget tracking for predicting the particle’s motion. This can be used to enhance the separation of optical sorters. For further details on this, see the publications <ul> <li><em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials,</strong><br> Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015.</li> <li><em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>Predictive Tracking with Improved Motion Models for Optical Belt Sorting</strong>,<br> at – Automatisierungstechnik, April 2020.</li> </ul> </li> <li>Classification of particles. The classification may use a multitarget tracker to accumulate visual features over time. One can also use the information on the trajectory to classify the particles. For information on this, refer to <ul> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information,</strong><br> Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017.</li> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Motion-Based Material Characterization in Sensor-Based Sorting,</strong> <br> tm – Technisches Messen, De Gruyter, October 2017.</li> </ul> </li> </ol> <p><strong>Acknowledgment</strong></p> <p>The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.</p>
Images of Thin Cuboids Transported on a Chute - Recording 3
<p>This data set comprises images of thin cuboids on a chute. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the Tablesort system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>, Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/inside-schuettgut.html">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings on optical sorters. Please use the search function with the keyword "Tobias Hornberger" (in quotes) to find them.</p> <p>The camera was recorded on a Bonito CL-400C. The calibration image for the extrinsic parameters can be found in calibration_extrinsics.png for the extrinsics and calibration_color.png for the color calibration. Please see the debayer script on <a href="https://github.com/geomai/debayer_bonito">GitHub</a><strong>.</strong> The frame rate is 192.9 Hz.</p> <p>Algorithms for two key challenges can be developed and evaluated on the data sets:</p> <ol> <li>Multitarget tracking for predicting the particle’s motion. This can be used to enhance the separation of optical sorters. For further details on this, see the publications <ul> <li><em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials,</strong><br> Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015.</li> <li><em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>Predictive Tracking with Improved Motion Models for Optical Belt Sorting</strong>,<br> at – Automatisierungstechnik, April 2020.</li> </ul> </li> <li>Classification of particles. The classification may use a multitarget tracker to accumulate visual features over time. One can also use the information on the trajectory to classify the particles. For information on this, refer to <ul> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information,</strong><br> Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017.</li> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Motion-Based Material Characterization in Sensor-Based Sorting,</strong> <br> tm – Technisches Messen, De Gruyter, October 2017.</li> </ul> </li> </ol> <p><strong>Acknowledgment</strong></p> <p>The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.</p>
Images of Thin Cuboids Transported on a Chute - Recording 1
<p>This data set comprises images of thin cuboids on a chute. The images were recorded on the small-scale optical belt sorter Tablesort. A thorough description of the Tablesort system can be found in</p> <ul> <li><em>Georg Maier, Florian Pfaff, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Jürgen Beyerer,</em> <strong>Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking</strong>, Transactions on Industrial Electronics, February 2020.</li> <li>See also the <a href="https://www.iosb.fraunhofer.de/en/projects-and-products/inside-schuettgut.html">project website</a>.</li> </ul> <p>This dataset is part of a batch of recordings on optical sorters. Please use the search function with the keyword "Tobias Hornberger" (in quotes) to find them.</p> <p>The camera was recorded on a Bonito CL-400C. The calibration image for the extrinsic parameters can be found in calibration_extrinsics.png for the extrinsics and calibration_color.png for the color calibration. Please see the debayer script on <a href="https://github.com/geomai/debayer_bonito">GitHub</a><strong>.</strong> The frame rate is 192.9 Hz.</p> <p>Algorithms for two key challenges can be developed and evaluated on the data sets:</p> <ol> <li>Multitarget tracking for predicting the particle’s motion. This can be used to enhance the separation of optical sorters. For further details on this, see the publications <ul> <li><em>Florian Pfaff, Marcus Baum, Benjamin Noack, Uwe D. Hanebeck, Robin Gruna, Thomas Längle, Jürgen Beyerer,</em><br> <strong>TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials,</strong><br> Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, September 2015.</li> <li><em>Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Thomas Längle, Jürgen Beyerer,</em><br> <strong>Predictive Tracking with Improved Motion Models for Optical Belt Sorting</strong>,<br> at – Automatisierungstechnik, April 2020.</li> </ul> </li> <li>Classification of particles. The classification may use a multitarget tracker to accumulate visual features over time. One can also use the information on the trajectory to classify the particles. For information on this, refer to <ul> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information,</strong><br> Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, March 2017.</li> <li><em>Georg Maier, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden, Thomas Längle, Uwe D. Hanebeck, Siegmar Wirtz, Viktor Scherer, Jürgen Beyerer,</em><br> <strong>Motion-Based Material Characterization in Sensor-Based Sorting,</strong> <br> tm – Technisches Messen, De Gruyter, October 2017.</li> </ul> </li> </ol> <p><strong>Acknowledgment</strong></p> <p>The IGF project 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) was supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.</p>
Multidimensional Parameter Study of Double Detonation Type Ia Supernovae Originating from Thin Helium Shell White Dwarfs
<p>This dataset provides the end-state ejecta data for each of the simulations from Boos et al. 2021, along with condensed versions for use in radiative transfer calculations.</p>
In-plane, In-situ domain switching in BaTiO3 thin films. BE-PFM data and CV curve.
<p>In-Plane band-exitation piezoresponse force microsopy data and CV curve in BaTiO3<br> The BE-PFM data have been fit to a second harmonic oscillator.<br> The data is stored as as python dictionaries that have been pickled. They contain the fitting paramaters for each pixel in each image.<br> The first image run4_0002_fit.lsqfit with zero bias.<br> The bias for all images are stored in CV.CV, also a python dictionary that has been pickled, and contains the voltage [V] and capacitance [F] for all 129 images.<br> See the jupyter notebook for how to read the data</p>
Data from: Temporary thinning shock in previously shaded red spruce
<p class="MsoNormal">Silvicultural thinning can lead to rapid microclimatic changes for residual trees. Despite the benefits of decreased competition, thinning may induce "thinning shock" – temporary negative physiological responses as trees acclimate to new conditions. We examined the impact of thinning on the microclimate and physiology of residual, previously shaded red spruce (<em>Picea rubens</em> Sarg.) trees relative to non-thinned controls. Both daily maximum temperature and vapor pressure deficit increased post-thinning, with larger increases observed on hotter and drier days. In response to these environmental changes, we found clear evidence of physiological declines. At 1.7 weeks post thinning, we found a 0.59-MPa reduction in average midday water potential relative to control trees, which lasted for an additional 1.4 weeks. Thus, the trees in the thinning treatment were at or beyond published estimates of needle turgor loss. Thinning decreased photosynthetic efficiency of current-year needles by 3.8% after two weeks, and it declined by 1.3% per week for the remainder of the growing season. These results suggest that thinning shock occurs in red spruce, a shade-adapted, climate-sensitive species. Thinning shock may contribute to the lagged growth responses commonly observed post-thinning, and these effects may be more extreme in novel future climates.</p>
3D-Printed Encapsulation of Thin-Film Transducers for Reliable Force Measurement in Biomedical Applications
<p>Data csv</p>
Data of Forced-response characterization of PBF-LB/AlSi10Mg particle dampers with thin and flat cavities
<p>Powder Bed Fusion (PBF) enables the production of complex geometries which offer the opportunity to manufacture lightweight, stiffness-optimised or integrally designed components. Although these properties are usually advantageous for the performance in many applications, they pose disadvantages under vibration as they lead to low damped components. These are prone to high vibration amplitudes which result in higher sound radiation and a reduced lifetime. Particle damping can counteract these disadvantages. By including cavities during the design process, unmelted powder remains inside the component after its production. This powder dissipates energy under vibration by inelastic impacts and friction in particle-–particle or particle-–wall-interactions, increasing the damping characteristics of the component. In this work, additively manufactured AlSi10Mg specimens with cavities are investigated with respect to their damping characteristics by experimental modal analysis. The focus of the investigation is on thin and flat cavities that can be easily integrated into components without adapting the external geometry. The damping characteristics in dependence on excitation amplitude and mode are quantified. The extent to which settling effects of the powder during shaking influence the damping is analysed. The vibration of the specimens is forced by an electrodynamic shaker and their response is measured contactlessly via Scanning Laser Doppler Vibrometry (SLDV). A damping effect of up to 564% depending on the mode, excitation amplitude and specimen can be achieved. In addition, a significant settling effect of the powder which hampers the damping effect is identified by CT scans and modal analysis.<br> The data of the CT scans as well as the data of the modal analysis is uploaded here. </p>
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