Scientific output
This page gives an overview of scientific papers that have been produced based on work performed on the Hábrók, Peregrine and Millipede compute clusters of the University of Groningen, or computing work that has been supported by staff of the HPC team of the Center of Information Technology of the university.
If you want to acknowledge the use of the Hábrók cluster and the support of the CIT in your papers you can use the following acknowledgement:
We thank the Center for Information Technology of the University of Groningen for their support and for providing access to the Hábrók high performance computing cluster.
This list has been first constructed in February 2016, many older papers are therefore not reported. It also relies on input from the individual researchers and will therefore also not be complete. If you want to have your paper(s) added to this list, please send the references (preferably DOI) to hpc@rug.nl.
2024
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<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“adupa_tertiary_2024”>1</a>] </td> <td class=“bibtexitem”> Adupa, V., Ustyantseva, E., Kampinga, H. H., & Onck, P. R. (2024). Tertiary structure and conformational dynamics of the
anti-amyloidogenic chaperone DNAJB6b at atomistic resolution.
<em>Nature Communications</em>, <em>15</em>(1), 3285 [ <a href=“http://dx.doi.org/10.1038/s41467-024-46587-z”>DOI</a> | <a href=“https://www.nature.com/articles/s41467-024-46587-z”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“aguayo_distributed_2024”>2</a>] </td> <td class=“bibtexitem”> Aguayo, J., Bertoglio, C., & Osses, A. (2024). Distributed parameter identification for the Navier–Stokes
equations for obstacle detection.
<em>Inverse Problems</em>, <em>40</em>(1), 015012 [ <a href=“http://dx.doi.org/10.1088/1361-6420/ad1133”>DOI</a> | <a href=“https://iopscience.iop.org/article/10.1088/1361-6420/ad1133”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“arrowsmith-kron_opportunities_2024”>3</a>] </td> <td class=“bibtexitem”> Arrowsmith-Kron, G., Athanasakis-Kaklamanakis, M., Au, M., et al. (2024). Opportunities for fundamental physics research with radioactive
molecules.
<em>Reports on Progress in Physics</em>, <em>87</em>(8), 084301. Publisher: IOP Publishing [ <a href=“http://dx.doi.org/10.1088/1361-6633/ad1e39”>DOI</a> | <a href=“https://dx.doi.org/10.1088/1361-6633/ad1e39”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“castroalvarez_assessment_2024”>4</a>] </td> <td class=“bibtexitem”> Castro‐Alvarez, S., Sinharay, S., Bringmann, L. F., Meijer, R. R., &
Tendeiro, J. N. (2024).
Assessment of fit of the time‐varying dynamic partial credit model
using the posterior predictive model checking method.
<em>British Journal of Mathematical and Statistical Psychology</em>,
page bmsp.12339
[ <a href=“http://dx.doi.org/10.1111/bmsp.12339”>DOI</a> | <a href=“https://bpspsychub.onlinelibrary.wiley.com/doi/10.1111/bmsp.12339”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“cotteret_vector_2024”>5</a>] </td> <td class=“bibtexitem”> Cotteret, M., Greatorex, H., Ziegler, M., & Chicca, E. (2024). Vector Symbolic Finite State Machines in Attractor Neural
Networks.
<em>Neural Computation</em>, <em>36</em>(4), 549–595 [ <a href=“http://dx.doi.org/10.1162/neco_a_01638”>DOI</a> | <a href=“https://direct.mit.edu/neco/article/36/4/549/119784/Vector-Symbolic-Finite-State-Machines-in-Attractor”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“driver_selective_2024”>6</a>] </td> <td class=“bibtexitem”> Driver, M. D. & Onck, P. R. (2024). Selective phase separation of transcription factors is driven by
orthogonal molecular grammar
[ <a href=“http://dx.doi.org/10.1101/2024.04.12.589262”>DOI</a> | <a href=“http://biorxiv.org/lookup/doi/10.1101/2024.04.12.589262”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“edman_are_2024”>7</a>] </td> <td class=“bibtexitem”> Edman, L., Sarti, G., Toral, A., Noord, G. V., & Bisazza, A. (2024). Are Character-level Translations Worth the Wait? Comparing
ByT5 and mT5 for Machine Translation.
<em>Transactions of the Association for Computational Linguistics</em>,
<em>12</em>, 392--410
[ <a href=“http://dx.doi.org/10.1162/tacl_a_00651”>DOI</a> | <a href=“https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00651/120650/Are-Character-level-Translations-Worth-the-Wait”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“eric_observation_2024”>8</a>] </td> <td class=“bibtexitem”> Erić, V., Li, X., Dsouza, L., et al. (2024). Observation of Dark States in Two-Dimensional Electronic
Spectra of Chlorosomes.
<em>The Journal of Physical Chemistry B</em>, <em>128</em>(15),
3575--3584
[ <a href=“http://dx.doi.org/10.1021/acs.jpcb.4c00067”>DOI</a> | <a href=“https://pubs.acs.org/doi/10.1021/acs.jpcb.4c00067”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“es_sayed_structureproperty_2024”>9</a>] </td> <td class=“bibtexitem”> Es Sayed, J., Mukherjee, A., El Aani, S., et al. (2024). Structure–Property Relationships of Granular Hybrid
Hydrogels Formed through Polyelectrolyte Complexation.
<em>Macromolecules</em>, <em>57</em>(7), 3190–3201 [ <a href=“http://dx.doi.org/10.1021/acs.macromol.3c02335”>DOI</a> | <a href=“https://pubs.acs.org/doi/10.1021/acs.macromol.3c02335”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“ferreira_dsza_2024”>10</a>] </td> <td class=“bibtexitem”> Ferreira, P., Neves, R. P. P., Miranda, F. P., et al. (2024). DszA Catalyzes C–S Bond Cleavage through N
<sup>5</sup> –Hydroperoxyl Formation.
<em>Journal of Chemical Information and Modeling</em>, <em>64</em>(10),
4218--4230
[ <a href=“http://dx.doi.org/10.1021/acs.jcim.4c00301”>DOI</a> | <a href=“https://pubs.acs.org/doi/10.1021/acs.jcim.4c00301”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“gurel_bidispersity_2024”>11</a>] </td> <td class=“bibtexitem”> Gürel, U., Keten, S., & Giuntoli, A. (2024). Bidispersity Improves the Toughness and Impact Resistance of
Star-Polymer Thin Films.
<em>ACS Macro Letters</em>, <em>13</em>(3), 302–307 [ <a href=“http://dx.doi.org/10.1021/acsmacrolett.3c00671”>DOI</a> | <a href=“https://pubs.acs.org/doi/10.1021/acsmacrolett.3c00671”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“jafari_robust_2024”>12</a>] </td> <td class=“bibtexitem”> Jafari, H., Barts, E., Przybysz, P., et al. (2024). Robust Zeeman-type band splitting in sliding ferroelectrics. <em>Physical Review Materials</em>, <em>8</em>(2), 024005 [ <a href=“http://dx.doi.org/10.1103/PhysRevMaterials.8.024005”>DOI</a> | <a href=“https://link.aps.org/doi/10.1103/PhysRevMaterials.8.024005”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“kasaei_harnessing_2024”>13</a>] </td> <td class=“bibtexitem”> Kasaei, H. & Kasaei, M. (2024). Harnessing the Synergy between Pushing, Grasping, and
Throwing to Enhance Object Manipulation in Cluttered Scenarios.
ArXiv:2402.16045 [cs] [ <a href=“http://arxiv.org/abs/2402.16045”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“kasaei_simultaneous_2024”>14</a>] </td> <td class=“bibtexitem”> Kasaei, H., Kasaei, M., Tziafas, G., Luo, S., & Sasso, R. (2024). Simultaneous Multi-View Object Recognition and Grasping in
Open-Ended Domains.
<em>Journal of Intelligent & Robotic Systems</em>, <em>110</em>(2), 62 [ <a href=“http://dx.doi.org/10.1007/s10846-024-02092-5”>DOI</a> | <a href=“https://link.springer.com/10.1007/s10846-024-02092-5”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“kleibergen_identification_2024”>15</a>] </td> <td class=“bibtexitem”> Kleibergen, F. & Kong, L. (2024). Identification robust inference for the risk premium in term
structure models.
<em>Journal of Econometrics</em>, page 105728 [ <a href=“http://dx.doi.org/10.1016/j.jeconom.2024.105728”>DOI</a> | <a href=“https://linkinghub.elsevier.com/retrieve/pii/S0304407624000745”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“koopmans_performance_2024”>16</a>] </td> <td class=“bibtexitem”> Koopmans, L., Dhali, M. A., & Schomaker, L. (2024). Performance Analysis of Handwritten Text Augmentation on
Style-Based Dating of Historical Documents.
<em>SN Computer Science</em>, <em>5</em>(4), 397 [ <a href=“http://dx.doi.org/10.1007/s42979-024-02688-6”>DOI</a> | <a href=“https://link.springer.com/10.1007/s42979-024-02688-6”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“konig_nuclear_2024”>17</a>] </td> <td class=“bibtexitem”> König, K., Berengut, J. C., Borschevsky, A., et al. (2024). Nuclear Charge Radii of Silicon Isotopes. <em>Physical Review Letters</em>, <em>132</em>(16), 162502 [ <a href=“http://dx.doi.org/10.1103/PhysRevLett.132.162502”>DOI</a> | <a href=“https://link.aps.org/doi/10.1103/PhysRevLett.132.162502”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“lan_iterative_2024”>18</a>] </td> <td class=“bibtexitem”> Lan, L., Van Doorn, J. M. H., Wouda, N. A., Rijal, A., & Bhulai, S. (2024). An Iterative Sample Scenario Approach for the Dynamic
Dispatch Waves Problem.
<em>Transportation Science</em>, page trsc.2023.0111 [ <a href=“http://dx.doi.org/10.1287/trsc.2023.0111”>DOI</a> | <a href=“https://pubsonline.informs.org/doi/10.1287/trsc.2023.0111”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“markovitch_binding_2024”>19</a>] </td> <td class=“bibtexitem”> Markovitch, O., Wu, J., & Otto, S. (2024). Binding of Precursors to Replicator Assemblies Can Improve
Replication Fidelity and Mediate Error Correction.
<em>Angewandte Chemie International Edition</em>, <em>63</em>(14),
e202317997
[ <a href=“http://dx.doi.org/10.1002/anie.202317997”>DOI</a> | <a href=“https://onlinelibrary.wiley.com/doi/10.1002/anie.202317997”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“marx_nonlinear_2024”>20</a>] </td> <td class=“bibtexitem”> Marx, A. C., Jafari, H., Tekelenburg, E. K., et al. (2024). Nonlinear magnetotransport in MoTe 2. <em>Physical Review B</em>, <em>109</em>(12), 125408 [ <a href=“http://dx.doi.org/10.1103/PhysRevB.109.125408”>DOI</a> | <a href=“https://link.aps.org/doi/10.1103/PhysRevB.109.125408”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“mastella_texture_2024”>21</a>] </td> <td class=“bibtexitem”> Mastella, M., Tiemens, T., & Chicca, E. (2024). Texture Recognition Using a Biologically Plausible Spiking
Phase-Locked Loop Model for Spike Train Frequency Decomposition.
ArXiv:2403.09723 [q-bio] [ <a href=“http://arxiv.org/abs/2403.09723”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“maurits_de_roo_reaction_2024”>22</a>] </td> <td class=“bibtexitem”> Maurits De Roo, C., Sardjan, A. S., Postmus, R., et al. (2024). Reaction of (N4Py)Fe with H 2 O 2
and the relevance of its Fe(IV)=O species during and after H <sub>2</sub> O <sub>2</sub> disproportionation.
<em>ChemCatChem</em>, page e202301594 [ <a href=“http://dx.doi.org/10.1002/cctc.202301594”>DOI</a> | <a href=“https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cctc.202301594”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“ndungu_classification_2024”>23</a>] </td> <td class=“bibtexitem”> Ndung’u, S., Grobler, T., Wijnholds, S. J., Karastoyanova, D., & Azzopardi,
G. (2024).
Classification of radio galaxies with trainable COSFIRE filters. <em>Monthly Notices of the Royal Astronomical Society</em>,
<em>530</em>(1), 783--794
[ <a href=“http://dx.doi.org/10.1093/mnras/stae821”>DOI</a> | <a href=“https://academic.oup.com/mnras/article/530/1/783/7634374”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“nguyen_inter-subunit_2024”>24</a>] </td> <td class=“bibtexitem”> Nguyen, H. L., Do, T. N., Zhong, K., et al. (2024). Inter-subunit energy transfer processes in a minimal plant
photosystem II supercomplex.
<em>Science Advances</em>, <em>10</em>(8), eadh0911 [ <a href=“http://dx.doi.org/10.1126/sciadv.adh0911”>DOI</a> | <a href=“https://www.science.org/doi/10.1126/sciadv.adh0911”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“oldenburg_forecasting_2024”>25</a>] </td> <td class=“bibtexitem”> Oldenburg, V., Cardenas-Cartagena, J., & Valdenegro-Toro, M. (2024). Forecasting Smog Clouds With Deep Learning: A
Proof-Of-Concept
[ <a href=“https://openreview.net/forum?id=UQa2PEVHMF”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“p_neme_cyclopentene_2024”>26</a>] </td> <td class=“bibtexitem”> P. Neme, N., Jansen, T. L. C., & Havenith, R. W. A. (2024). Cyclopentene ring effects in cyanine dyes: a handle to fine-tune
photophysical properties.
<em>Physical Chemistry Chemical Physics</em>, <em>26</em>(7), 6235–6241 [ <a href=“http://dx.doi.org/10.1039/D3CP05219B”>DOI</a> | <a href=“https://xlink.rsc.org/?DOI=D3CP05219B”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“cherifi_decentralized_2024”>27</a>] </td> <td class=“bibtexitem”> Sabo, E., Riveni, M., & Karastoyanova, D. (2024). Decentralized Networks Growth Analysis: Instance Dynamics
on Mastodon.
In H. Cherifi, L. M. Rocha, C. Cherifi, & M. Donduran, editors,
<em>Complex Networks & Their Applications XII</em>, volume 1144, pages 366--377. Springer Nature Switzerland, Cham.
ISBN 978-3-031-53502-4 978-3-031-53503-1. Series Title: Studies in Computational Intelligence [ <a href=“http://dx.doi.org/10.1007/978-3-031-53503-1_30”>DOI</a> | <a href=“https://link.springer.com/10.1007/978-3-031-53503-1_30”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“soh_controlling_2024”>28</a>] </td> <td class=“bibtexitem”> Soh, J. H., Jansen, T. L. C., & Palacino-González, E. (2024). Controlling the nonadiabatic dynamics of the charge-transfer process
with chirped pulses: Insights from a double-pump time-resolved fluorescence spectroscopy scheme.
<em>The Journal of Chemical Physics</em>, <em>160</em>(2), 024110 [ <a href=“http://dx.doi.org/10.1063/5.0177073”>DOI</a> | <a href=“https://pubs.aip.org/jcp/article/160/2/024110/2932845/Controlling-the-nonadiabatic-dynamics-of-the”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“tittes_development_2024”>29</a>] </td> <td class=“bibtexitem”> Tittes, C., Nijland, J., Schoentag, A. M. C., et al. (2024). Development of a genetic system for <i>Haloferax gibbonsii</i>
LR2-5, model host for haloarchaeal viruses.
<em>Applied and Environmental Microbiology</em>, <em>90</em>(4),
e00129--24
[ <a href=“http://dx.doi.org/10.1128/aem.00129-24”>DOI</a> | <a href=“https://journals.asm.org/doi/10.1128/aem.00129-24”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“truong_graph_2024”>30</a>] </td> <td class=“bibtexitem”> Truong, H., Tello, A., Lazovik, A., & Degeler, V. (2024). Graph Neural Networks for Pressure Estimation in Water
Distribution Systems.
<em>Water Resources Research</em>, <em>60</em>(7), e2023WR036741 [ <a href=“http://dx.doi.org/10.1029/2023WR036741”>DOI</a> | <a href=“https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR036741”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“wouda_pyvrp_2024”>31</a>] </td> <td class=“bibtexitem”> Wouda, N. A., Lan, L., & Kool, W. (2024). PyVRP: A High-Performance VRP Solver Package. <em>INFORMS Journal on Computing</em>, page ijoc.2023.0055 [ <a href=“http://dx.doi.org/10.1287/ijoc.2023.0055”>DOI</a> | <a href=“https://pubsonline.informs.org/doi/10.1287/ijoc.2023.0055”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“yi_systematic_2024”>32</a>] </td> <td class=“bibtexitem”> Yi, Y., Liang, L., De Jong, A., & Kuipers, O. P. (2024). A systematic comparison of natural product potential, with an
emphasis on RiPPs, by mining of bacteria of three large ecosystems.
<em>Genomics</em>, <em>116</em>(4), 110880 [ <a href=“http://dx.doi.org/10.1016/j.ygeno.2024.110880”>DOI</a> | <a href=“https://linkinghub.elsevier.com/retrieve/pii/S0888754324001010”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“zhang_efficiency_2024”>33</a>] </td> <td class=“bibtexitem”> Zhang, L., Csányi, G., Van Der Giessen, E., & Maresca, F. (2024). Efficiency, accuracy, and transferability of machine learning
potentials: Application to dislocations and cracks in iron.
<em>Acta Materialia</em>, <em>270</em>, 119788 [ <a href=“http://dx.doi.org/10.1016/j.actamat.2024.119788”>DOI</a> | <a href=“https://linkinghub.elsevier.com/retrieve/pii/S135964542400140X”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“zhang_maltose_2024”>34</a>] </td> <td class=“bibtexitem”> Zhang, X., Nijland, J. G., & Driessen, A. J. M. (2024). Maltose accumulation-induced cell death in <i>Saccharomyces
cerevisiae</i>.
<em>FEMS Yeast Research</em>, <em>24</em>, foae012 [ <a href=“http://dx.doi.org/10.1093/femsyr/foae012”>DOI</a> | <a href=“https://academic.oup.com/femsyr/article/doi/10.1093/femsyr/foae012/7639402”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“zhang_shape_2024”>35</a>] </td> <td class=“bibtexitem”> Zhang, Z. & Krushynska, A. O. (2024). Shape Morphing of Tubular Structures with Tailorable
Mechanical Properties.
<em>Advanced Engineering Materials</em>, <em>26</em>(2), 2300383 [ <a href=“http://dx.doi.org/10.1002/adem.202300383”>DOI</a> | <a href=“https://onlinelibrary.wiley.com/doi/10.1002/adem.202300383”>http</a> ]
</td> </tr> </table></html>
2023
<html>
<table>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“alshehri_repurposing_2023”>1</a>] </td> <td class=“bibtexitem”> Alshehri, M. M., Danazumi, A. U., Alshammari, M. K., et al. (2023). Repurposing the inhibitors of MMP-9 and SGLT-2 against ubiquitin
specific protease 30 in Parkinson’s disease: computational modelling studies.
<em>Journal of Biomolecular Structure and Dynamics</em>, pages 1–12 [ <a href=“http://dx.doi.org/10.1080/07391102.2023.2208223”>DOI</a> | <a href=“https://www.tandfonline.com/doi/full/10.1080/07391102.2023.2208223”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“anteghini_organelx_2023”>2</a>] </td> <td class=“bibtexitem”> Anteghini, M., Haja, A., Martins Dos Santos, V. A., Schomaker, L., & Saccenti,
E. (2023).
OrganelX web server for sub-peroxisomal and sub-mitochondrial
protein localization and peroxisomal target signal detection.
<em>Computational and Structural Biotechnology Journal</em>, <em>21</em>,
128--133
[ <a href=“http://dx.doi.org/10.1016/j.csbj.2022.11.058”>DOI</a> | <a href=“https://linkinghub.elsevier.com/retrieve/pii/S2001037022005529”>http</a> ]
</td> </tr>
<tr valign=“top”> <td align=“right” class=“bibtexnumber”> [<a name=“barkai_comparative_2023”>3</a>] </td> <td class=“bibtexitem”> Barkai, J. A., Verheijen, M. A. W., Talavera, E., & Wilkinson, M. H. F.
(2023).
A comparative study of source-finding techniques in H I emission
line cubes using SoFiA, MTObjects, and supervised deep learning.
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<table>
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