July 31, Daily science and technology trend

  • 2020-07-31
  • 115

1. The Center for Innovative Development of the Tomsk Region will become the new, 14th in a row, regional operator Skolkovo. The decision was made at an online meeting between the Chairman of the Skolkovo Foundation Arkady Dvorkovich and the Governor of the Tomsk Region Sergei Zhvachkin. Today, 22 start-ups from the Tomsk region are participants in the Skolkovo project.



2. The Russian Academy of Sciences(RAS) and the US National Academy of Sciences have signed a cooperation agreement on research related to coronavirus. The signing took place via video link. On the Russian side, the agreement was signed by the President of the Russian Academy of Sciences, Alexander Sergeev, on the American side, by the head of the US National Academy of Sciences, Marsha McNutt.



3. Recently, the team of the National Research Technological University "MISiS" together with colleagues from Moscow State University. Lomonosov, RKhTU them. Mendeleev, the Russian National Research Medical University and the University of Duisburg-Essen(Germany), studied the formation of hybrid magnetite-gold nanoparticles. Scientists note that the data they obtained allow them to control the size and shape of nanoparticles due to the ability to control the parameters of a chemical reaction. In the future, this will help to scale up the production of theranostic nanoparticles to serial.



4. Postgraduate students and employees of the Department of General Physics and Wave Processes of the Physics Faculty of Moscow State University have developed a new type of polarimetry, which can contribute to the creation of fundamentally new, more effective methods for diagnosing biological tissues. The method developed by scientists can be implemented in the form of computational phantom images - for example, using a spatial light modulator - or quantum phantom polarimetry based on polarization-entangled photons.



5. Scientists at ITMO University in St. Petersburg will develop theoretical tools to improve the efficiency of evolutionary algorithms, which are widely used to solve optimization problems in various fields, such as bioinformatics, logistics, software engineering. For example, they can be used to create a schedule that minimizes equipment downtime in a plant, or to design an antenna that provides maximum signal strength.



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