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June 4, 2026
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The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
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Search for Bs0 → ℓ∓τ± with the Semi-leptonic Tagging Method at Belle

Journal of High Energy Physics. 2023. Article 178.
Nayak L., Aihara H., Aushev T., Bodrov D., Pakhlov P., Pakhlova G., Uglov T.

We present a search for the lepton-flavor-violating decays B0s→ℓ∓τ±, where ℓ=e,μ, using the full data sample of 121 fb−1 collected at the Υ(5S) resonance with the Belle detector at the KEKB asymmetric-energy e+e− collider. We use B0sB¯¯¯¯0s events in which one B0s meson is reconstructed in a semileptonic decay mode and the other in the signal mode. We find no evidence for B0s→ℓ∓τ± decays and set upper limits on their branching fractions at 90% confidence level as B(B0s→e∓τ±)<14×10−4 and B(B0s→μ∓τ±)<7.3×10−4. Our result represents the first upper limit on the B0s→e∓τ± decay rate.

Research target: Physics
Language: English
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Keywords: Belle detectorbranching fractionsKEKBLFV
Publication based on the results of:
Development of new methods for searching for physics beyond the Standard Model in experiments at the Super Charm-Tau Factory and Belle at the KEKB B-Factory (2023)
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