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March 3, Daily science and technology trend

  • 2021-03-03
  • 278
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1. Scientists at the Institute of Chemistry of Solutions of the Russian Academy of Sciences have created a new optical thermometer, the mechanism of action of which is to establish the dependence of the fluorescence intensity on temperature. The results obtained can be used to develop new non-contact optical thermal sensors for thermolysis of cancer cells.

https://www.minobrnauki.gov.ru/press-center/news/?ELEMENT_ID=30382

 

2. The competition for the best projects of fundamental scientific research in 2021, canceled by the RFBR due to reorganization processes, will soon be announced by the Russian Science Foundation. The financial support of the projects supported by the results of the competitive selection will be carried out as planned - starting from 2022.

https://minobrnauki.gov.ru/press-center/news/?ELEMENT_ID=30405

 

3. A group of scientists from St. Petersburg State University has created a new technology to protect lithium-ion batteries from fire. They propose to use a "chemical fuse" - a special protective layer made of a conductive polymer to cover the current collector of batteries. In the event of an abnormal situation, it breaks the electrical circuit, saving the device from fire.

https://scientificrussia.ru/news/himiki-razrabotali-tehnologiyu-zashchity-litij-ionnyh-akkumulyatorov-ot-vozgoraniya

 

4. Scientists from the Skoltech Laboratory of Intelligent Space Robotics have proposed a new method for analyzing customer behavior using a robot that performs autonomous inventory using radio frequency tags. The robot monitors buyers, determines the most attractive product locations for them and predicts demand. This gives the seller information about each item in the store that can be used when placing items.

https://www.skoltech.ru/2021/03/skoltehovskij-robot-analiziruet-povedenie-klientov-v-magazine/

 

5. In the new work, scientists from the Institute of Physics of the Earth, Moscow State University. Lomonosov and the Soil Science Institute. Dokuchaev proposed algorithms for assessing soil properties with high accuracy without human intervention. To do this, they used the ResNet-101 + U-net hybrid neural network architecture. With its help, scientists have successfully processed seven X-ray images of the soil. For some samples from the set, the error was only 5%.

https://rscf.ru/news/presidential-program/svoystva-pochv-po-rentgenovskoy-tomografii/

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