➞ Publikacje ➞ 2024

2024

  1. Two-neutrino 0^+ \to 0^+ double beta decay of ^{48}\mathrm{Ca} within the DFT-NCCI framework [preprint]
    Jan Miśkiewicz, Maciej Konieczka, Wojciech Satuła
    arXiv:2506.13747 [nucl-th]
    https://doi.org/10.48550/arXiv.2506.13747
  2. Stability of solutions of the porous medium equation with growth with respect to the diffusion exponent [preprint]
    Tomasz Dębiec, Piotr Gwiazda, Błażej Miasojedow, Zuzanna Szymańska
    arXiv:2403.19070v1 [math.AP]
    https://doi.org/10.48550/arXiv.2403.19070
  3. What do we manipulate when reminding people of (not) having control? In search of construct validity
    Bukowski, M., Potoczek, A., Barzykowski, K. et al.
    Behav Res 56, 3706–3724 (2024);
    https://doi.org/10.3758/s13428-023-02326-8
  4. United as one? Personal and social identity threats differentially predict cooperation and prejudice toward minorities
    Bukowski, M., de Lemus, S., Potoczek, A., Sankaran, S., Petkanopoulou, K., Montañés Muro, M. P., … Tausch, N.
    Self and Identity, 23(1–2), 95–126;
    https://doi.org/10.1080/15298868.2024.2336939
  5. Mathematical modelling of cancer invasion: Phenotypic transitioning provides insight into multifocal foci formation
    Zuzanna Szymańska, Mirosław Lachowicz, Nikolaos Sfakianakis, Mark AJ Chaplain
    Journal of Computational Science, 75, January 2024, 102175
    https://doi.org/10.1016/j.jocs.2023.102175
  6. Exploring explainable AI in the tax domain
    Górski, Ł., Kuźniacki, B., Almada, M. et al.
    Artif Intell Law (2024);
    https://doi.org/10.1007/s10506-024-09395-w
  7. EnsembleFS: an R Toolkit and a Web-Based Tool for a Filter Ensemble Feature Selection of Molecular Omics Data
    Polewko-Klim, A., Grablis, P., Rudnicki, W.
    In: Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2024. ICCS 2024. Lecture Notes in Computer Science, vol 14835. Springer, Cham.;
    https://doi.org/10.1007/978-3-031-63772-8_7
  8. Indicators of biochemical control of diabetes mellitus during limited availability of health service in the context of hypoglycemic therapy
    Kleibert M, Mrozikiewicz-Rakowska B, Korycka K, Płachta I, Bąk PM, Bałut D, Zieliński J, Zgliczyński W.
    Wiad Lek. 2024;77(7):1318-1324;
    https://doi.org/10.36740/wlek202407103
  9. Spatio-temporal mechanisms of consolidation, recall and reconsolidation in reward-related memory trace
    Hamed, A., Kursa, M.B., Mrozek, W. et al.
    Mol Psychiatry (2024);
    https://doi.org/10.1038/s41380-024-02738-8
  10. Modelling of Drug-Induced Liver Injury with Multiple Machine Learning Algorithms
    Lesiński, W., Golińska, A.K., Rudnicki, W.R.
    In: Nguyen, NT., et al. Advances in Computational Collective Intelligence. ICCCI 2024. Communications in Computer and Information Science, vol 2166. Springer, Cham.;
    https://doi.org/10.1007/978-3-031-70259-4_33
  11. Chaos in Opinion-Driven Disease Dynamics
    Götz, T.; Krüger, T.; Niedzielewski, K.; Pestow, R.; Schäfer, M.; Schneider, J.
    Entropy 2024, 26(4), 298;
    https://doi.org/10.3390/e26040298
  12. Loss of pre-stress in impregnated superconducting magnets, experimental results and numerical analysis
    R. Ortwein, J.C. Perez, D. Pszenny
    Cryogenics, Volume 141, 2024; 103893         
    https://doi.org/10.1016/j.cryogenics.2024.103893
  13. Utilizing novel MRI biomarkers for early achilles tendon injury detection and prevention
    Norbert Kapinski, Justyna Witkowska, Michal Starczewski
    British Journal of Sports Medicine 2024;58:A86-A88
    https://bjsm.bmj.com/content/58/Suppl_2/A86.2
  14. Towards Achilles Tendon Injury Prevention in Athletes with Structural MRI Biomarkers: A Machine Learning Approach
    Kapinski, N., Jaskulski, K., Witkowska, J. et al.
    Sports Med – Open 10, 118 (2024);
    https://doi.org/10.1186/s40798-024-00786-6
  15. Sir model for households
    Philipp Dönges, Thomas Götz, Nataliia Kruchinina, Tyll Krüger, Karol Niedzielewski, Viola Priesemann, Moritz Schäfer
    SIAM Journal on Applied Mathematics, 84(4), 1460-1481
    https://doi.org/10.1137/23M1556861
  16. Forecasting SARS-COV-2 epidemic dynamic in Poland with the PDYN agent-based model
    Karol Niedzielewski, Rafał P. Bartczuk, Natalia Bielczyk, Dominik Bogucki, Filip Dreger, Grzegorz Dudziuk, Łukasz Górski, Magdalena Gruziel-Słomka, Jędrzej Haman, Artur Kaczorek, Jan Kisielewski, Bartosz Krupa, Antoni Moszyński, Jędrzej M. Nowosielski, Maciej Radwan, Marcin Semeniuk, Urszula Tymoszuk, Jakub Zieliński, Franciszek Rakowski
    Epidemics, Volume 49, 2023, 100801;
    https://doi.org/10.1016/j.epidem.2024.100801
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