WorldWideScience
 
 
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Vladimir P. Demikhov, a pioneer of organ transplantation.  

Science.gov (United States)

Vladimir P. Demikhov was born in a Russian peasant family in 1916. As a biology student at The Moscow University in 1937, he constructed a metal artificial heart and maintained the circulation of a dog for 5.5 hours. From 1946, after his military service, he worked in the Surgical Institute of The Moscow Academy of Sciences performing heterotopic heart transplantations in dogs. In 1947, he performed the first orthotopic lung transplant. Later he performed complex cardiothoracic transplantations as well as renal and hepatic transplantations. He restarted his investigations with the artificial heart and performed coronary bypass operations in dogs. In 1954 he performed a head transplantation, for which he gained worldwide infamy. Stalinist propaganda advertised this fact as the superiority of Soviet science. In fact, it was the upper body of a smaller dog to the neck of a bigger one. The two heads could eat and drink separately. But he could not overcome the problems ...

2011-05-01

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Support vector machines for nuclear reactor state estimation  

Energy Technology Data Exchange (ETDEWEB)

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformed into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear power reactors. In ...

2000-02-14