Importance of international scientific contacts in Tomsk scientific community as the factor of physics research development in the 1970-1980-ies

The article is devoted to historical reconstruction of the international contacts and communications of Tomsk scientific community in the 1970-1980s. Siberian Physical-Technical Institute (SPhTI) was a large center of basic and applied research development in the field of solid state physics, cybernetics, radio electronics and scientific staff training in the USSR. The author analyses the main forms of cooperation between SPhTI and foreign scientific research institutes and higher education institutions, the mechanism of foreign training organization, the forms of the state control on international scientific and educational contacts. The value of SPhTI’s international scientific contacts in developing research on physics is emphasized. SPhTI scientists

Encoding of Passive Anticollision Radio Frequency Identification Surface Acoustic Waves Tags

This paper describes the encoding of anticollision radio-frequency identification tags based on surface acoustic waves. The study is based on the tag model with specific topology, which allows us to receive a response signal with time–frequency information. This research considers the collision case for several passive tags. Therefore, the proposal is to analyze the possibility of using several distinctive signs like frequency and time. We consider the model of passive surface acoustic wave tag, which contains piezoelectric substrate, interdigital transducer, and consecutive orthogonal-frequency-coded structures, which are placed in time slots. Similar topology makes possible the reliability of increasing tag identification in the collision case

TreeDQN: Learning to minimize Branch-and-Bound tree

Combinatorial optimization problems require an exhaustive search to find the optimal solution. A convenient approach to solving combinatorial optimization tasks in the form of Mixed Integer Linear Programs is Branch-and-Bound. Branch-and-Bound solver splits a task into two parts dividing the domain of an integer variable, then it solves them recursively, producing a tree of nested sub-tasks. The efficiency of the solver depends on the branchning heuristic used to select a variable for splitting. In the present work, we propose a reinforcement learning method that can efficiently learn the branching heuristic. We view the variable selection task as a tree Markov Decision Process, prove that the Bellman operator adapted for the tree Markov Decision Process is contracting in mean, and propose a modified learning objective for the reinforcement learning agent. Our agent requires less training data and produces smaller trees compared to previous reinforcement learning methods.Comment: Submitted to NeurIPS 202

Role of βPix in the Kidney

Small GTPases function as molecular switches in cell signaling, alternating between an inactive, GDP-bound state, and active GTP-bound state. βPix is one of guanine nucleotide exchange factors (GEFs) that catalyze the exchange of bound GDP for ambient GTP. The central goal of this review article is to summarize recent findings on βPix and the role it plays in kidney pathology and physiology. Recent studies shed new light on several key questions concerning the signaling mechanisms mediated by βPix. This manuscript provides a review of the various mechanisms whereby βPix has been shown to function within the kidney through a wide range of actions. Both canonical GEF activity and non-canonical signaling pathways mediated by βPix are discussed. Distribution patterns of βPix in the kidney will be also covered. Much has yet to be discerned, but it is clear that βPix plays a significant role in the kidney