March 30, Daily science and technology trend

  • 2021-03-30
  • 230

1. An agreement on cooperation with the aim of creating a Center for Nuclear Medicine was signed today by the head of the Ministry of Education and Science of the Russian Federation Valery Falkov, President of the Kurchatov Institute Research Center Mikhail Kovalchuk and Director of the N. acad. B.V. Petrovsky Konstantin Kotenko. The main task of the Center being created is to develop innovative nuclear medicine technologies in Russia, conduct clinical research and introduce new methods and equipment for radiation therapy into clinical practice, train highly qualified scientific, medical and engineering personnel in the field of nuclear medicine, expand international cooperation in this area.



2. Acceptance of applications for the VII All-Russian Prize ‘For Faithfulness to Science‘ will begin on 15 April. The Award is being held for the seventh time and it has a special meaning in the Year of Science and Technology. The prize is awarded to those media representatives, those young scientists who contribute to the popularization of science.



3. On March 30–31, the Skolkovo Foundation and VTB Group will hold an international online conference Data Fusion, during which Data Science experts will discuss a new approach to working with big data and artificial intelligence technologies. The first day of the event will be devoted to the economic aspects of the topic, the second - to scientific ones.



4. For the production of plastics, drugs and other materials, nanocatalysts with expensive and non-environmentally friendly palladium are used. The RUDN University chemist figured out how to reduce the consumption of palladium and make production more environmentally friendly - for this he created catalysts based on a substance obtained from plant residues. They cut palladium consumption in half. Moreover, they can be reused many times without loss of efficiency.



5. Skoltech researchers have developed the first prototype of a medical imaging system based on the use of neural networks to analyze near-infrared vein images and project the venous pattern onto the patient's body.



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