Shukirgaliyev B 1
1. Impact of swift heavy ion-induced point defects on nanoscale thermal transport in ZnO
2. Evaluating machine learning models for supernova gravitational wave signal classification
3. Evaluating multi-GPU computing capabilities of Numba and CuPy
4. Evaluation of pseudo-random number generation on GPU cards
5. Exploring Numba and CuPy for GPU-Accelerated Monte Carlo Radiation Transport
6. Centrally concentrated star formation in young clusters
7. Cluster membership analysis with supervised learning and N-body simulations
8. Evolution of star clusters with initial bulk rotation via N -body simulations
9. Thermal properties of Klein–Gordon oscillator in the context of Amelino-Camelia and Magueijo–Smolin doubly special relativity (DSR) frameworks
10. Dynamical evolution of the open clusters with different star formation efficiencies and orbital parameters
11. Nonrelativistic limits of the Klein-Gordon and Dirac equations in the Amelino-Camelia DSR
12. Exploring supernova gravitational waves with machine learning
13. Probing nuclear physics with supernova gravitational waves and machine learning
14. Bound mass of Dehnen models with a centrally peaked star formation efficiency
15. NGC 6240 supermassive black hole binary dynamical evolution based on Chandra data
16. Dynamical model of Praesepe and its tidal tails
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