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

[1] 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. Nature Communications, 15(1), 3285 [ DOI | http ]
[2] Aguayo, J., Bertoglio, C., & Osses, A. (2024). Distributed parameter identification for the Navier–Stokes equations for obstacle detection. Inverse Problems, 40(1), 015012 [ DOI | http ]
[3] Arrowsmith-Kron, G., Athanasakis-Kaklamanakis, M., Au, M., et al. (2024). Opportunities for fundamental physics research with radioactive molecules. Reports on Progress in Physics, 87(8), 084301. Publisher: IOP Publishing [ DOI | http ]
[4] 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. British Journal of Mathematical and Statistical Psychology, page bmsp.12339 [ DOI | http ]
[5] Cotteret, M., Greatorex, H., Ziegler, M., & Chicca, E. (2024). Vector Symbolic Finite State Machines in Attractor Neural Networks. Neural Computation, 36(4), 549--595 [ DOI | http ]
[6] Driver, M. D. & Onck, P. R. (2024). Selective phase separation of transcription factors is driven by orthogonal molecular grammar [ DOI | http ]
[7] 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. Transactions of the Association for Computational Linguistics, 12, 392--410 [ DOI | http ]
[8] Erić, V., Li, X., Dsouza, L., et al. (2024). Observation of Dark States in Two-Dimensional Electronic Spectra of Chlorosomes. The Journal of Physical Chemistry B, 128(15), 3575--3584 [ DOI | http ]
[9] Es Sayed, J., Mukherjee, A., El Aani, S., et al. (2024). Structure–Property Relationships of Granular Hybrid Hydrogels Formed through Polyelectrolyte Complexation. Macromolecules, 57(7), 3190--3201 [ DOI | http ]
[10] Ferreira, P., Neves, R. P. P., Miranda, F. P., et al. (2024). DszA Catalyzes C–S Bond Cleavage through N 5 –Hydroperoxyl Formation. Journal of Chemical Information and Modeling, 64(10), 4218--4230 [ DOI | http ]
[11] Gürel, U., Keten, S., & Giuntoli, A. (2024). Bidispersity Improves the Toughness and Impact Resistance of Star-Polymer Thin Films. ACS Macro Letters, 13(3), 302--307 [ DOI | http ]
[12] Jafari, H., Barts, E., Przybysz, P., et al. (2024). Robust Zeeman-type band splitting in sliding ferroelectrics. Physical Review Materials, 8(2), 024005 [ DOI | http ]
[13] Kasaei, H. & Kasaei, M. (2024). Harnessing the Synergy between Pushing, Grasping, and Throwing to Enhance Object Manipulation in Cluttered Scenarios. ArXiv:2402.16045 [cs] [ http ]
[14] Kasaei, H., Kasaei, M., Tziafas, G., Luo, S., & Sasso, R. (2024). Simultaneous Multi-View Object Recognition and Grasping in Open-Ended Domains. Journal of Intelligent & Robotic Systems, 110(2), 62 [ DOI | http ]
[15] Kleibergen, F. & Kong, L. (2024). Identification robust inference for the risk premium in term structure models. Journal of Econometrics, page 105728 [ DOI | http ]
[16] Koopmans, L., Dhali, M. A., & Schomaker, L. (2024). Performance Analysis of Handwritten Text Augmentation on Style-Based Dating of Historical Documents. SN Computer Science, 5(4), 397 [ DOI | http ]
[17] König, K., Berengut, J. C., Borschevsky, A., et al. (2024). Nuclear Charge Radii of Silicon Isotopes. Physical Review Letters, 132(16), 162502 [ DOI | http ]
[18] 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. Transportation Science, page trsc.2023.0111 [ DOI | http ]
[19] Markovitch, O., Wu, J., & Otto, S. (2024). Binding of Precursors to Replicator Assemblies Can Improve Replication Fidelity and Mediate Error Correction. Angewandte Chemie International Edition, 63(14), e202317997 [ DOI | http ]
[20] Marx, A. C., Jafari, H., Tekelenburg, E. K., et al. (2024). Nonlinear magnetotransport in MoTe 2. Physical Review B, 109(12), 125408 [ DOI | http ]
[21] 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] [ http ]
[22] 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 2 O 2 disproportionation. ChemCatChem, page e202301594 [ DOI | http ]
[23] Ndung’u, S., Grobler, T., Wijnholds, S. J., Karastoyanova, D., & Azzopardi, G. (2024). Classification of radio galaxies with trainable COSFIRE filters. Monthly Notices of the Royal Astronomical Society, 530(1), 783--794 [ DOI | http ]
[24] Nelemans, S. (2024). Asset Pricing with Economic Inequality: a Macrofinancial Approach. Ph.D. thesis, University of Groningen [ DOI | http ]
[25] Nguyen, H. L., Do, T. N., Zhong, K., et al. (2024). Inter-subunit energy transfer processes in a minimal plant photosystem II supercomplex. Science Advances, 10(8), eadh0911 [ DOI | http ]
[26] Oldenburg, V., Cardenas-Cartagena, J., & Valdenegro-Toro, M. (2024). Forecasting Smog Clouds With Deep Learning: A Proof-Of-Concept [ http ]
[27] 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. Physical Chemistry Chemical Physics, 26(7), 6235--6241 [ DOI | http ]
[28] 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, Complex Networks & Their Applications XII, 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 [ DOI | http ]
[29] 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. The Journal of Chemical Physics, 160(2), 024110 [ DOI | http ]
[30] Tittes, C., Nijland, J., Schoentag, A. M. C., et al. (2024). Development of a genetic system for Haloferax gibbonsii LR2-5, model host for haloarchaeal viruses. Applied and Environmental Microbiology, 90(4), e00129--24 [ DOI | http ]
[31] Truong, H., Tello, A., Lazovik, A., & Degeler, V. (2024). Graph Neural Networks for Pressure Estimation in Water Distribution Systems. Water Resources Research, 60(7), e2023WR036741 [ DOI | http ]
[32] Wouda, N. A., Lan, L., & Kool, W. (2024). PyVRP: A High-Performance VRP Solver Package. INFORMS Journal on Computing, page ijoc.2023.0055 [ DOI | http ]
[33] 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. Genomics, 116(4), 110880 [ DOI | http ]
[34] 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. Acta Materialia, 270, 119788 [ DOI | http ]
[35] Zhang, X., Nijland, J. G., & Driessen, A. J. M. (2024). Maltose accumulation-induced cell death in Saccharomyces cerevisiae. FEMS Yeast Research, 24, foae012 [ DOI | http ]
[36] Zhang, Z. & Krushynska, A. O. (2024). Shape Morphing of Tubular Structures with Tailorable Mechanical Properties. Advanced Engineering Materials, 26(2), 2300383 [ DOI | http ]

2023

[1] 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. Journal of Biomolecular Structure and Dynamics, pages 1--12 [ DOI | http ]
[2] 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. Computational and Structural Biotechnology Journal, 21, 128--133 [ DOI | http ]
[3] 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. Astronomy & Astrophysics, 670, A55 [ DOI | http ]
[4] Bechlenberg, A., Wei, Y., Jayawardhana, B., & Vakis, A. I. (2023). Analysing the influence of power take-off adaptability on the power extraction of dense wave energy converter arrays. Renewable Energy, 211, 1--12 [ DOI | http ]
[5] Bellas, C., Hackl, T., Plakolb, M.-S., et al. (2023). Large-scale invasion of unicellular eukaryotic genomes by integrating DNA viruses. Proceedings of the National Academy of Sciences, 120(16), e2300465120 [ DOI | http ]
[6] Biçer, A., Koelewijn, T., & Başkent, D. (2023). Short Implicit Voice Training Affects Listening Effort During a Voice Cue Sensitivity Task With Vocoder-Degraded Speech. Ear & Hearing, 44(4), 900--916 [ DOI | http ]
[7] Boer, D. & Setyadi, C. (2023). Probing gluon GTMDs through exclusive coherent diffractive processes. The European Physical Journal C, 83(10), 890 [ DOI | http ]
[8] Boot, T. (2023). Joint inference based on Stein-type averaging estimators in the linear regression model. Journal of Econometrics, 235(2), 1542--1563 [ DOI | http ]
[9] Boot, T., Niccodemi, G., & Wansbeek, T. (2023). Unbiased estimation of the OLS covariance matrix when the errors are clustered. Empirical EconomicsDOI | http ]
[10] Castro-Alvarez, S., Bringmann, L. F., Meijer, R. R., & Tendeiro, J. N. (2023). A Time-Varying Dynamic Partial Credit Model to Analyze Polytomous and Multivariate Time Series Data. Multivariate Behavioral Research, pages 1--20 [ DOI | http ]
[11] Chang, Y.-C. & Jian, J.-C. (2023). Biomaterial-based nonvolatile photonic memory. Carbon, 202, 167--172 [ DOI | http ]
[12] Chiariello, M. G., Grünewald, F., Zarmiento-Garcia, R., & Marrink, S. J. (2023). pH-Dependent Conformational Switch Impacts Stability of the PsbS Dimer. The Journal of Physical Chemistry Letters, 14(4), 905--911 [ DOI | http ]
[13] Chu, H., De La O Arévalo, L. R., Tang, W., et al. (2023). Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach. In V. Andrearczyk, V. Oreiller, M. Hatt, & A. Depeursinge, editors, Head and Neck Tumor Segmentation and Outcome Prediction, volume 13626, pages 114--120. Springer Nature Switzerland, Cham. ISBN 978-3-031-27419-0 978-3-031-27420-6. Series Title: Lecture Notes in Computer Science [ DOI | http ]
[14] De Biase, A., Sijtsema, N. M., Van Dijk, L. V., Langendijk, J. A., & Van Ooijen, P. M. A. (2023). Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images. Physics in Medicine & Biology, 68(5), 055013 [ DOI | http ]
[15] De Klein, N., Tsai, E. A., Vochteloo, M., et al. (2023). Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases. Nature Genetics, 55(3), 377--388 [ DOI | http ]
[16] Dekker, M., Van Der Giessen, E., & Onck, P. R. (2023). Phase separation of intrinsically disordered FG-Nups is driven by highly dynamic FG motifs. Proceedings of the National Academy of Sciences, 120(25), e2221804120 [ DOI | http ]
[17] Do, P., Coler, M., Dijkstra, J., & Klabbers, E. (2023). Strategies in Transfer Learning for Low-Resource Speech Synthesis: Phone Mapping, Features Input, and Source Language Selection. In 12th ISCA Speech Synthesis Workshop (SSW2023), pages 21--26. ISCA [ DOI | .html ]
[18] Do, P., Coler, M., Dijkstra, J., & Klabbers, E. (2023). The Effects of Input Type and Pronunciation Dictionary Usage in Transfer Learning for Low-Resource Text-to-Speech. In INTERSPEECH 2023, pages 5461--5465. ISCA [ DOI | .html ]
[19] Do, P., Coler, M., Dijkstra, J., & Klabbers, E. (2023). Resource-Efficient Fine-Tuning Strategies for Automatic MOS Prediction in Text-to-Speech for Low-Resource Languages. In INTERSPEECH 2023, pages 5466--5470. ISCA [ DOI | .html ]
[20] Erić, V., Li, X., Dsouza, L., et al. (2023). Manifestation of Hydrogen Bonding and Exciton Delocalization on the Absorption and Two-Dimensional Electronic Spectra of Chlorosomes. The Journal of Physical Chemistry B, 127(5), 1097--1109 [ DOI | http ]
[21] Etienne, R. S., Haegeman, B., Dugo-Cota, \C3., et al. (2023). The Phylogenetic Limits to Diversity-Dependent Diversification. Systematic Biology, 72(2), 433--445 [ DOI | http ]
[22] Faber, T., Filipovic, L., & Koster, L. J. A. (2023). The Role of Thermalization in the Cooling Dynamics of Hot Carrier Solar Cells. Solar RRL, page 2300140 [ DOI | http ]
[23] Fazi, S., Choudhary, S. K., & Dong, J.-X. (2023). The multi-trip container drayage problem with synchronization for efficient empty containers re-usage. European Journal of Operational Research, 310(1), 343--359 [ DOI | http ]
[24] Feliciani, T., Tolsma, J., & Flache, A. (2023). Ethnic segregation and spatial patterns of attitudes: studying the link using register data and social simulation. Journal of Computational Social ScienceDOI | http ]
[25] Florez, E., Zapata-Escobar, A. D., Ferraro, F., et al. (2023). Coordination of Mercury(II) in Water Promoted over Hydrolysis in Solvated Clusters [Hg(H 2 O) 1–6 ] (aq) 2+ : Insights from Relativistic Effects and Free Energy Analysis. The Journal of Physical Chemistry A, 127(39), 8032--8049 [ DOI | http ]
[26] Flöss, T., Biagetti, M., & Meerburg, P. D. (2023). Primordial non-Gaussianity and non-Gaussian covariance. Physical Review D, 107(2), 023528 [ DOI | http ]
[27] Frans, N., Braeken, J., Veldkamp, B. P., & Paap, M. C. S. (2023). Empirical Priors in Polytomous Computerized Adaptive Tests: Risks and Rewards in Clinical Settings. Applied Psychological Measurement, 47(1), 48--63 [ DOI | http ]
[28] Ghara, S., Barts, E., Vasin, K., et al. (2023). Magnetization reversal through an antiferromagnetic state. Nature Communications, 14(1), 5174 [ DOI | http ]
[29] Grasso, S., Dabene, V., Hendriks, M. M. W. B., et al. (2023). Signal Peptide Efficiency: From High-Throughput Data to Prediction and Explanation. ACS Synthetic Biology, 12(2), 390--404 [ DOI | http ]
[30] Gurung, K., Vink, S. N., Salles, J. F., & Wertheim, B. (2023). More persistent bacterial than fungal associations in the microbiota of a pest insect. Journal of Pest Science, 96(2), 785--796 [ DOI | http ]
[31] Gürel, U. & Giuntoli, A. (2023). Shear Thinning from Bond Orientation in Model Unentangled Bottlebrush Polymer Melts. Macromolecules, 56(15), 5708--5717 [ DOI | http ]
[32] Haja, A., Horcas-Nieto, J. M., Bakker, B. M., & Schomaker, L. (2023). Towards automatization of organoid analysis: A deep learning approach to localize and quantify organoid images. Computer Methods and Programs in Biomedicine Update, 3, 100101 [ DOI | http ]
[33] Haja, A., Van Der Woude, B., & Schomaker, L. (2023). Organoids Segmentation using Self-Supervised Learning: How Complex Should the Pretext Task Be? In Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering, pages 17--27. ACM, Kyoto Japan. ISBN 9798400708343 [ DOI | http ]
[34] Haja, A., Zhelev, I., & Schomaker, L. (2023). Segmentation Of Organoid Cultures Images Using Diffusion Networks with Triplet Loss. In Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering, pages 1--10. ACM, Kyoto Japan. ISBN 9798400708343 [ DOI | http ]
[35] van Hengel, C. D. N., van Adrichem, K. E., & Jansen, T. L. C. (2023). Simulation of two-dimensional infrared Raman spectroscopy with application to proteins. The Journal of Chemical Physics, 158(6), 064106 [ DOI | http ]
[36] Huo, Y., Espinoza Cangahuala, M. K., Zamudio-Bayer, V., et al. (2023). An X-ray spectroscopy study of structural stability of superhydrogenated pyrene derivatives. Monthly Notices of the Royal Astronomical Society, 523(1), 865--875 [ DOI | http ]
[37] Kasaei, H. & Kasaei, M. (2023). MVGrasp: Real-time multi-view 3D object grasping in highly cluttered environments. Robotics and Autonomous Systems, 160, 104313 [ DOI | http ]
[38] Kind, L., Driver, M., Raasakka, A., et al. (2023). Structural properties of the HNF-1A transactivation domain. Frontiers in Molecular Biosciences, 10, 1249939 [ DOI | http ]
[39] Landau, A., Eduardus, Behar, D., et al. (2023). Chiral molecule candidates for trapped ion spectroscopy by ab initio calculations: From state preparation to parity violation. The Journal of Chemical Physics, 159(11), 114307 [ DOI | http ]
[40] Leach, I. F., Sorbelli, D., Belpassi, L., et al. (2023). How reduced are nucleophilic gold complexes? Dalton Transactions, 52(1), 11--15 [ DOI | http ]
[41] Leach, I. F., Speelman, T., Somsen, C., Klein, J. E. M. N., & Havenith, R. W. A. (2023). Revisiting sp 2 Dilithio Methandiides: From Geometric Curiosity to Simple Bonding Description. Chemistry – A European Journal, 29(56), e202301911 [ DOI | http ]
[42] Lefebvre, M. J. M., Daron, J., Legrand, E., et al. (2023). Population Genomic Evidence of Adaptive Response during the Invasion History of Plasmodium falciparum in the Americas. Molecular Biology and Evolution, 40(5), msad082 [ DOI | http ]
[43] Lepage, M. L., Alachouzos, G., Hermens, J. G. H., et al. (2023). Electron-Poor Butenolides: The Missing Link between Acrylates and Maleic Anhydride in Radical Polymerization. Journal of the American Chemical Society, 145(31), 17211--17219 [ DOI | http ]
[44] Leurs, G., Verkuil, Y. I., Hijner, N., et al. (2023). Addressing data-deficiency of threatened sharks and rays in a highly dynamic coastal ecosystem using environmental DNA. Ecological Indicators, 154, 110795 [ DOI | http ]
[45] Leyva-Vallina, M., Strisciuglio, N., & Petkov, N. (2023). Data-efficient large scale place recognition with graded similarity supervision. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 23487--23496
[46] Liu, T., Roy, A., Hidding, J., et al. (2023). Crystallographically dependent bilinear magnetoelectric resistance in a thin WTe 2 layer. Physical Review B, 108(16), 165407 [ DOI | http ]
[47] Luo, S. & Schomaker, L. (2023). Reinforcement learning in robotic motion planning by combined experience-based planning and self-imitation learning. Robotics and Autonomous Systems, 170, 104545 [ DOI | http ]
[48] Marinho, J. P. N., Neme, N. P., Matos, M. J. D. S., et al. (2023). Nanostructured system based on hydroxyapatite and curcumin: A promising candidate for osteosarcoma therapy. Ceramics International, 49(12), 19932--19949 [ DOI | http ]
[49] Marinus, N., Eisink, N. N. H. M., Reintjens, N. R. M., et al. (2023). A Predictive Model for the Pd‐Catalyzed Site‐Selective Oxidation of Diols. Chemistry – A European Journal, page e202300318 [ DOI | http ]
[50] Merekalov, A. S., Derikov, Y. I., Ezhov, A. A., et al. (2023). Orientation control of the hexagonal and lamellar phases in thin block copolymer films using in-plane AC electric field. Polymer, 264, 125544 [ DOI | http ]
[51] Mposhi, A., Cortés-Mancera, F., Heegsma, J., et al. (2023). Mitochondrial DNA methylation in metabolic associated fatty liver disease. Frontiers in Nutrition, 10, 964337 [ DOI | http ]
[52] Mulder, T. E., Baars, S., Wubs, F. W., et al. (2023). Symbiotic Ocean Modeling Using Physics‐Controlled Echo State Networks. Journal of Advances in Modeling Earth Systems, 15(12), e2023MS003631 [ DOI | http ]
[53] Nagam, B. C., Koopmans, L. V. E., Valentijn, E. A., et al. (2023). DenseLens – Using DenseNet ensembles and information criteria for finding and rank-ordering strong gravitational lenses. Monthly Notices of the Royal Astronomical Society, 523(3), 4188--4201 [ DOI | http ]
[54] Ndung’u, S., Grobler, T., Wijnholds, S. J., Karastoyanova, D., & Azzopardi, G. (2023). Deep supervised hashing for fast retrieval of radio image cubes. In 2023 XXXVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), pages 1--4. IEEE, Sapporo, Japan. ISBN 978-94-6396-809-6 [ DOI | http ]
[55] Nichols, M., Athanasakis-Kaklamanakis, M., Borschevsky, A., et al. (2023). Investigating radioactive negative ion production via double electron capture. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 541, 264--267 [ DOI | http ]
[56] Norrgard, E. B., Chamorro, Y., Cooksey, C. C., et al. (2023). Radiative decay rate and branching fractions of MgF. Physical Review A, 108(3), 032809 [ DOI | http ]
[57] Palacino-González, E. & Jansen, T. L. C. (2023). Modeling the Effect of Disorder in the Two-Dimensional Electronic Spectroscopy of Poly-3-hexyltiophene in an Organic Photovoltaic Blend: A Combined Quantum/Classical Approach. The Journal of Physical Chemistry C, 127(14), 6793--6801 [ DOI | http ]
[58] Parisotto, T., Mukherjee, S., & Kasaei, H. (2023). MORE: simultaneous multi-view 3D object recognition and pose estimation. Intelligent Service RoboticsDOI | http ]
[59] Pase, G., Brinkhuis, E., De Vries, T., et al. (2023). A parametric geometry model of the aortic valve for subject-specific blood flow simulations using a resistive approach. Biomechanics and Modeling in Mechanobiology, 22(3), 987--1002 [ DOI | http ]
[60] Pramanik, R., Verstappen, R. W. C. P., & Onck, P. R. (2023). Magnetic-field-induced propulsion of jellyfish-inspired soft robotic swimmers. Physical Review E, 107(1), 014607 [ DOI | http ]
[61] Ramanantoanina, H., Borschevsky, A., Block, M., Viehland, L., & Laatiaoui, M. (2023). State-specific ion mobilities of Lr + ( Z = 103 ) in helium. Physical Review A, 108(1), 012802 [ DOI | http ]
[62] Sasso, R., Sabatelli, M., & Wiering, M. A. (2023). Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning. Transactions on Machine Learning Researchhttp ]
[63] Saxena, A., Cole, A., Gazagnes, S., et al. (2023). Constraining the X-ray heating and reionization using 21-cm power spectra with Marginal Neural Ratio Estimation. Monthly Notices of the Royal Astronomical Society, 525(4), 6097--6111 [ DOI | http ]
[64] Saxena, A., Meerburg, P. D., de Lera Acedo, E., Handley, W., & Koopmans, L. V. E. (2023). Sky-averaged 21-cm signal extraction using multiple antennas with an SVD framework: the REACH case. Monthly Notices of the Royal Astronomical Society, 522(1), 1022--1032 [ DOI | http ]
[65] Schenkel, M. A., Billeter, J.-C., Beukeboom, L. W., & Pen, I. (2023). Divergent evolution of genetic sex determination mechanisms along environmental gradients. Evolution Letters, 7(3), 132--147 [ DOI | http ]
[66] Shomalzadeh, K., Scherpen, J. M., & Camlibel, M. K. (2023). A real-time balancing market optimization with personalized prices: From bilevel to convex. Operations Research Perspectives, 10, 100276 [ DOI | http ]
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2014

[1] Bauer, J., Hou, L., Kistemaker, J. C., & Feringa, B. L. (2014). Tuning the rotation rate of light-driven molecular motors. Journal of Organic Chemistry, 79(10), 4446--4455 [ DOI | http ]
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[4] Bos, E. G., Van De Weygaert, R., Kitaura, F., & Cautun, M. (2014). Bayesian cosmic web reconstruction: BARCODE for clusters. Proceedings of the International Astronomical Union, 11(S308), 271--288 [ DOI | http ]
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[13] Deckers, T. & Hanck, C. (2014). Multiple testing for output convergence. Macroeconomic Dynamics, 18(1), 199--214 [ DOI | http ]
[14] Deckers, T. & Hanck, C. (2014). Variable Selection in Cross-Section Regressions: Comparisons and Extensions. Oxford Bulletin of Economics and Statistics, 76(6), 841--873 [ DOI | http ]
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[17] Dini-Andreote, F., De Cássia Pereira E Silva, M., Triadó-Margarit, X., et al. (2014). Dynamics of bacterial community succession in a salt marsh chronosequence: Evidences for temporal niche partitioning. ISME Journal, 8(10), 1989--2001 [ DOI | http ]
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[19] Ghavami, A., Veenhoff, L. M., Van Der Giessen, E., & Onck, P. R. (2014). Probing the disordered domain of the nuclear pore complex through coarse-grained molecular dynamics simulations. Biophysical Journal, 107(6), 1393--1402 [ DOI | http ]
[20] de Gier, H. D., Rietberg, B. J., Broer, R., & Havenith, R. W. (2014). Influence of push-pull group substitution patterns on excited state properties of donor-acceptor co-monomers and their trimers. Computational and Theoretical Chemistry, 1040-1041, 202--211 [ DOI | http ]
[21] Haver, V. G., Verweij, N., Kjekshus, J., et al. (2014). The impact of coronary artery disease risk loci on ischemic heart failure severity and prognosis: Association analysis in the COntrolled ROsuvastatin multiNAtional trial in heart failure (CORONA). BMC Medical Genetics, 15(1), 140 [ DOI | http ]
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[23] Li, J., Nowak, P., Fanlo-Virgós, H., & Otto, S. (2014). Catenanes from catenanes: Quantitative assessment of cooperativity in dynamic combinatorial catenation. Chemical Science, 5(12), 4968--4974 [ DOI | http ]
[24] Lillington, M., Havenith, R. W., Fowler, P. W., Baker, J., & Jenneskens, L. W. (2014). The homotropenylium cation: A system with a pinched π ring current. Physical Chemistry Chemical Physics, 16(23), 11566--11572 [ DOI | http ]
[25] Namdeo, S., Khaderi, S. N., & Onck, P. R. (2014). Numerical modelling of chirality-Induced bi-Directional swimming of artificial flagella. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 470(2162), 20130547 [ DOI | http ]
[26] Nijland, J. G., Shin, H. Y., De Jong, R. M., et al. (2014). Engineering of an endogenous hexose transporter into a specific D-xylose transporter facilitates glucose-xylose co-consumption in Saccharomyces cerevisiae. Biotechnology for Biofuels, 7(1), 168 [ DOI | http ]
[27] Riese, H., Muñoz, L. M., Hartman, C. A., et al. (2014). Identifying genetic variants for heart rate variability in the acetylcholine pathway. PLoS ONE, 9(11), e112476 [ DOI | http ]
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[29] Rudavskyi, A., Sousa, C., De Graaf, C., Havenith, R. W., & Broer, R. (2014). Computational approach to the study of thermal spin crossover phenomena. Journal of Chemical Physics, 140(18), 184318 [ DOI | http ]
[30] Saane, S. S., Mangipudi, K. R., Loos, K. U., De Hosson, J. T. M., & Onck, P. R. (2014). Multiscale modeling of charge-induced deformation of nanoporous gold structures. Journal of the Mechanics and Physics of Solids, 66(1), 1--15 [ DOI | http ]
[31] Sergentu, D. C., Maurice, R., Havenith, R. W., Broer, R., & Roca-Sanjuán, D. (2014). Computational determination of the dominant triplet population mechanism in photoexcited benzophenone. Physical Chemistry Chemical Physics, 16(46), 25393--25403 [ DOI | http ]
[32] Simino, J., Shi, G., Bis, J. C., et al. (2014). Gene-age interactions in blood pressure regulation: A large-scale investigation with the CHARGE, global BPgen, and ICBP consortia. American Journal of Human Genetics, 95(1), 24--38 [ DOI | http ]
[33] Spierdijk, L. & Koning, R. H. (2014). Estimating Outstanding Claim Liabilities: The Role of Unobserved Risk Factors. Journal of Risk and Insurance, 81(4), 803--830 [ DOI | http ]
[34] Spierdijk, L. & Umar, Z. (2014). Are commodity futures a good hedge against inflation? The Journal of Investment Strategies, 3(2), 35--57 [ DOI | http ]
[35] Spierdijk, L. & Umar, Z. (2014). Stocks for the long run? Evidence from emerging markets. Journal of International Money and Finance, 47, 217--238 [ DOI | http ]
[36] Steglich, C. & Knecht, A. (2014). Über Beurteilungsfehler aufgrund verzerrt wahrgenommener Schülerfreundschaften. Zeitschrift fur Erziehungswissenschaft, 17(5), 153--170 [ DOI | http ]
[37] Taatgen, N. A. (2014). Between architecture and model: Strategies for cognitive control. Biologically Inspired Cognitive Architectures, 8, 132--139 [ DOI | http ]
[38] Van Duijnen, P. T., De Gier, H. D., Broer, R., & Havenith, R. W. (2014). The behaviour of charge distributions in dielectric media. Chemical Physics Letters, 615, 83--88 [ DOI | http ]
[39] Verkuil, Y. I., Juillet, C., Lank, D. B., Widemo, F., & Piersma, T. (2014). Genetic variation in nuclear and mitochondrial markers supports a large sex difference in lifetime reproductive skew in a lekking species. Ecology and Evolution, 4(18), 3626--3632 [ DOI | http ]
[40] Verweij, N., Leach, I. M., Van Den Boogaard, M., et al. (2014). Genetic Determinants of P Wave Duration and PR Segment. Circulation: Cardiovascular Genetics, 7(4), 475--481 [ DOI | http ]
[41] Voortman, T. P., De Gier, H. D., Havenith, R. W., & Chiechi, R. C. (2014). Stabilizing cations in the backbones of conjugated polymers. Journal of Materials Chemistry C, 2(17), 3407--3415 [ DOI | http ]
[42] Wezenberg, S. J., Vlatković, M., Kistemaker, J. C., & Feringa, B. L. (2014). Multi-state regulation of the dihydrogen phosphate binding affinity to a light- and heat-responsive bis-urea receptor. Journal of the American Chemical Society, 136(48), 16784--16787 [ DOI | http ]

2013

[1] Codd, V., Nelson, C. P., Albrecht, E., et al. (2013). Identification of seven loci affecting mean telomere length and their association with disease. Nature Genetics, 45(4), 422--427 [ DOI | http ]
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[3] Demetrescu, M. & Hanck, C. (2013). Nonlinear IV panel unit root testing under structural breaks in the error variance. Statistical Papers, 54(4), 1043--1066 [ DOI | http ]
[4] Markov, V., Kriksin, Y., Erukhimovich, I., & Ten Brinke, G. (2013). Perpendicular lamellar-in-lamellar and other planar morphologies in A-b-(B-b-A)2-b-C and (B-b-A)2-b-C ternary multiblock copolymer melts. Journal of Chemical Physics, 139(8), 084906 [ DOI | http ]
[5] Pijper, T. C., Kudernac, T., Browne, W. R., & Feringa, B. L. (2013). Effect of immobilization on gold on the temperature dependence of photochromic switching of dithienylethenes. Journal of Physical Chemistry C, 117(34), 17623--17632 [ DOI | http ]
[6] Surinta, O., Schomaker, L., & Wiering, M. (2013). A comparison of feature and pixel-based methods for recognizing handwritten bangla digits. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, pages 165--169. IEEE. ISBN 978-0-7695-4999-6. ISSN: 15205363 [ DOI | http ]
[7] Taatgen, N. a. (2013). Diminishing Return in Transfer: A PRIM Model of the Frensch (1991) Arithmetic Experiment. In Proceedings of the International Conference on Cognitive Modeling, pages 29--34. Issue: 1991
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[9] Verweij, N., Mahmud, H., Leach, I. M., et al. (2013). Genome-wide association study on plasma levels of midregional- proadrenomedullin and C-terminal-pro-endothelin-1. Hypertension, 61(3), 602--608 [ DOI | http ]

2012

[1] Asselbergs, F. W., Guo, Y., Van Iperen, E. P., et al. (2012). Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci. American Journal of Human Genetics, 91(5), 823--838 [ DOI | http ]
[2] ĆurČić Blake, B., Swart, M., Ter Horst, G. J., et al. (2012). Variation of the gene coding for DARPP-32 (PPP1R1B) and brain connectivity during associative emotional learning. NeuroImage, 59(2), 1540--1550 [ DOI | http ]
[3] de Boer, R. A., Verweij, N., van Veldhuisen, D. J., et al. (2012). A Genome-Wide Association Study of Circulating Galectin-3. PLoS ONE, 7(10), e47385 [ DOI | http ]
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