Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Valentin Potapov"'
Autor:
Dmytro Khaskhachikh, Valentin Potapov
Publikováno v:
Journal of V. N. Karazin Kharkiv National University: Series Medicine, Vol 46, Pp 72-79 (2023)
Abstract. The article provides an overview of literary sources that describe research on the microbiome of the endometrium in women of reproductive age. Thus, in many works, data is given indicating that the uterine cavity is not sterile. Various mic
Externí odkaz:
https://doaj.org/article/426d329ddff04dacae050a961cdeed66
Autor:
Dmytro Khaskhachykh, Valentin Potapov
Publikováno v:
Ukrainian Scientific Medical Youth Journal, Vol 134, Iss 4, Pp 22-28 (2022)
the article presents a review of the literature, which examines the impact of changes in the vaginal microbiome and chronic endometritis on the development of hyperplastic processes of the endometrium in women. Many studies have proven the undoubted
Externí odkaz:
https://doaj.org/article/413aa610a52041919a8e319977ebb6ba
Publikováno v:
Ukrainian Scientific Medical Youth Journal. 134:22-28
the article presents a review of the literature, which examines the impact of changes in the vaginal microbiome and chronic endometritis on the development of hyperplastic processes of the endometrium in women. Many studies have proven the undoubted
Publikováno v:
E3S Web of Conferences, Vol 177, p 03001 (2020)
A mathematical model of particles movement of separated material in a friction separator is proposed. It includes equations of their movement at each stage of separation (along a rough inclined plane, on a curvilinear part of a springboard, impact of
Autor:
Valentin Potapov
Publikováno v:
Proceedings of the National Aviation University. 69:64-68
Мета: Представлено метод діагностування технічного стану турбореактивного двоконтурного двигуна з використанням гібридного нейросет
Autor:
Valentin Potapov
Publikováno v:
Vìsnik Nacìonalʹnogo Avìacìjnogo Unìversitetu, Vol 69, Iss 4, Pp 64-68 (2016)
Purpose: This work presents a method of diagnosing the technical condition of turbofan engines using hybrid neural network algorithm based on software developed for the analysis of data obtained in the aircraft life. Methods: allows the engine diagno