The primordial non-Gaussianities for non-singular Horndeski cosmologies

Autor: Ageeva, Y., Kotenko, M., Petrov, P.

We have acquired and analyzed the bispectrum of primordial scalar perturbations and the corresponding non-Gaussianities in the particular model of the contracting Universe with strong gravity in the past within the framework of the Horndeski theory.

Externí odkaz: http://arxiv.org/abs/2410.10742

Hadronic cross section measurements with the DAMPE space mission using 20GeV-10TeV cosmic-ray protons and $^4$He

Autor: Alemanno, F., An, Q., Azzarello, P., Barbato, F. C. T., Bernardini, P., Bi, X. J., Cagnoli, I., Cai, M. S., Casilli, E., Catanzani, E., Chang, J., Chen, D. Y., Chen, J. L., Chen, Z. F., Coppin, P., Cui, M. Y., Cui, T. S., Cui, Y. X., Dai, H. T., De Benedittis, A., De Mitri, I., de Palma, F., Di Giovanni, A., Ding, Q., Dong, T. K., Dong, Z. X., Donvito, G., Droz, D., Duan, J. L., Duan, K. K., Fan, R. R., Fan, Y. Z., Fang, F., Fang, K., Feng, C. Q., Feng, L., Frieden, J. M., Fusco, P., Gao, M., Gargano, F., Gong, K., Gong, Y. Z., Guo, D. Y., Guo, J. H., Han, S. X., Hu, Y. M., Huang, G. S., Huang, X. Y., Huang, Y. Y., Ionica, M., Jiang, L. Y., Jiang, Y. Z., Jiang, W., Kong, J., Kotenko, A., Kyratzis, D., Lei, S. J., Li, W. H., Li, W. L., Li, X., Li, X. Q., Liang, Y. M., Liu, C. M., Liu, H., Liu, J., Liu, S. B., Liu, Y., Loparco, F., Luo, C. N., Ma, M., Ma, P. X., Ma, T., Ma, X. Y., Marsella, G., Mazziotta, M. N., Mo, D., Niu, X. Y., Pan, X., Parenti, A., Peng, W. X., Peng, X. Y., Perrina, C., Putti-Garcia, E., Qiao, R., Rao, J. N., Ruina, A., Sarkar, R., Savina, P., Serpolla, A., Shangguan, Z., Shen, W. H., Shen, Z. Q., Shen, Z. T., Silveri, L., Song, J. X., Stolpovskiy, M., Su, H., Su, M., Sun, H. R., Sun, Z. Y., Surdo, A., Teng, X. J., Tykhonov, A., Wang, J. Z., Wang, L. G., Wang, S., Wang, S. X., Wang, X. L., Wang, Y., Wang, Y. F., Wang, Y. Z., Wang, Z. M., Wei, D. M., Wei, J. J., Wei, Y. F., Wu, D., Wu, J., Wu, S. S., Wu, X., Xia, Z. Q., Xu, H. T., Xu, J., Xu, Z. H., Xu, Z. L., Xu, E. H., Xu, Z. Z., Xue, G. F., Yang, H. B., Yang, P., Yang, Y. Q., Yao, H. J., Yu, Y. H., Yuan, G. W., Yuan, Q., Yue, C., Zang, J. J., Zhang, S. X., Zhang, W. Z., Zhang, Yan, Zhang, Yi, Zhang, Y. J., Zhang, Y. L., Zhang, Y. P., Zhang, Y. Q., Zhang, Z., Zhang, Z. Y., Zhao, C., Zhao, H. Y., Zhao, X. F., Zhou, C. Y., Zhu, Y.

Precise direct cosmic-ray (CR) measurements provide an important probe to study the energetic particle sources in our Galaxy, and the interstellar environment through which these particles propagate. Uncertainties on hadronic models, ion-nucleon cros

Externí odkaz: http://arxiv.org/abs/2408.17224

Implications and Transformative Potential of 5G-Enabled M2M Communication for the IoT Landscape

Autor: Denys Kotenko, Wael Abdulateef Jasim, Mahmoud Shuker, Ahmed Lebanon Hatif Alshami, Mohammed Mubarak Salih, Rashid Merzah Khudhair, Mohammed Abdul Majeed

Publikováno v: Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 36, Iss 1, Pp 35-43 (2024)

Machine-to-machine (M2M) communication and the Internet of Things (IoT) are witnessing significant advancements in rapidly expanding technical paradigms, notably catalysed by the introduction of 5G networks. This article investigates the synergistic

Externí odkaz: https://doaj.org/article/43e52c306d924ba994358335c0e3212d

Wind Turbines Surface Damage Automatic Detection Using YOLOv8 with Specialized Backbone Modification

Autor: Aleksei Samarin, Anastasiia Mamaeva, Aleksei Toropov, Alina Dzestelova, Artem Nazarenko, Egor Kotenko, Elena Mikhailova, Valentin A Malykh, Aleksandr Savelev, Alexandr Motyko

Publikováno v: Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 36, Iss 1, Pp 702-710 (2024)

This work is devoted to incorporating specialized self-attention blocks into deep neural network-based models for detecting and quantifying damage across various components of wind turbines using images captured by unmanned aerial vehicle cameras. In

Externí odkaz: https://doaj.org/article/1e8f4f9a0ac94783ac1b0b4c776c1632

Universal Filter-Based Lightweight Image Enhancement Model with Unpaired Learning Mode

Autor: Aleksei Samarin, Artem Nazarenko, Aleksei Toropov, Egor Kotenko, Alina Dzestelova, Elena Mikhailova, Valentin A Malykh, Alexander Savelev, Alexandr Motyko

Publikováno v: Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 36, Iss 1, Pp 711-720 (2024)

Image enhancement is crucial in digital image processing to improve visual quality across various applications. Recent advancements in deep learning and computer vision have significantly advanced automatic color correction. While heavyweight solutio

Externí odkaz: https://doaj.org/article/71bec7a5142a4723a896b7c9e8a9c821