Equivalent  electrical  circuits  of  multilayer  film  structures  with  memristor  switching  of  resistance at   interlayer boundaries and at the boundaries of crystal grains in each layer are proposed. Numerical modeling of   the  current-voltage characteristics of such structures has shown that their loop-shaped form, typical of memristors, is transformed into a linear ohmic dependence of the total current on the magnitude of the applied external voltage as both the number of layers and the number of grains in each layer increase. A certain combination of the  number of layers and grains in a layer has been established, at which the maximum total current flowing through the structure and the ratio of resistances in the “off” and “on” states reach the highest values.

The research has been carried out on the formation of anti-reflection coatings based on porous aluminum obtained by electrochemical anodic etching and a layer of barium titanate xerogel deposited on its surface. The  thickness of the porous aluminum ranged from 15 to 100 microns. Analysis of the reflection spectra of the resulting structures showed effective anti-reflection properties of the formed coatings with a specular reflection coefficient of 0.25–2.50 % in the range of 200–1100 nm. The use of formed coatings with a low reflectance coefficient is possible in aircraft manufacturing, electronics and energy.

The influence of recrystallization of a mechanically damaged layer on the working side of a silicon wafer using rapid heat treatment (1000 °C, 20 s) on the electrical parameters of complementary metal-oxide-semiconductor microcircuits has been established. The analyzed characteristics of  n- and  p-channel transistors were selected: drain current from the gate voltage when diode-connected; output characteristics at various gate voltages; drain current from the drain voltage without applying potential to the gate; percentage of yield of suitable products. These parameters were compared with microcircuits manufactured using standard technology. Analysis of  the results showed that rapid thermal treatment of the original silicon wafers can significantly improve the above characteristics  of  n-channel  metal-oxide-semiconductor  ( n-MOS)  and  p-channel  metal-oxide-semiconductor (p-MOS) transistors by reducing the fixed charge in gate dielectric obtained by pyrogenic oxidation of silicon. This makes it possible to improve the quality of manufactured complementary metal-oxide-semiconductor  microcircuits and  increase the percentage of yield of suitable products from 74.38 to 77.53 %.

Syntheses and investigations of bulk samples of compositions based on B_axSr_(1–x)TiO₃, Pb(Zr,  Ti)O₃, Bi_1,7Pb₀,₃Sr₂Ca_(n–1)CunO_(n+4+1),  n  =  (5, 9, 12), which are used to obtain hybrid structures, have been carried out. The technology for producing high temperature superconductor–ferroelectric hybrid structures has been developed and the optimal temperature-time modes for their production have been determined. The conditions for the formation of the high temperature superconductor–ferroelectric structure have been studied. The microstructure, crystal structure and electrical properties of the high temperature superconductor–ferroelectric hybrid structure were studied. The ferroelectric–superconductor transition boundary was studied and it was found that its size is 4 μm. The ferroelectric–superconductor–electrode structures have been formed. It has been shown that the deposition of  silver contacts on the surface of a superconducting coating is possible in one technological cycle. It has been established that to obtain composite materials with high electrical parameters it is necessary to use superconducting materials Bi_1,7Pb_0,3Sr₂Ca_(n–1)Cu_nO_y с n ≥ 12.

The results of testing the spectral-acoustic cavitometer with measurement modes that differ in the frequency ranges of integration of cavitation noise are presented. For each of the H1–H4 modes, the lower integration frequency  f_min is 1, 70, 180 and 300 kHz, respectively. The upper frequency is the same for all modes and  is   f_max  =  10  MHz. Piezoelectric waveguide sensors were used as a cavitation noise receivers. The distributions of cavitation activity in non-uniform ultrasonic fields were recorded: in the volume of the ultrasonic bath  (f₀ = 35 kHz) and in the field of the submersible emitter (f₀ = 21 kHz). The frequency range of integration was varied by changing the lower bound. It has been established that a change in the integration range within a fairly wide range does not have a noticeable qualitative effect on the result of measurements of cavitation activity, only a multiple change in the readings occurs. This conclusion was confirmed using sensors that differ in their spectral characteristics.

Gyrotron-type amplifiers are being developed for various applications requiring high power in the millimeter wavelength range. Calculations of the optimal designs of gyrotron traveling wave tubes (gyro-TWTs), presented in the article, were carried out using the Gyro-K computer program using a coordinate transformation technique, which made it possible to significantly reduce the calculation time of gyroresonance devices by reducing the three-dimensional problem of excitation of an irregular waveguide to a one-dimensional one. Two options for creating a gyro-TWT using the TE₀₂ wave mode are considered: the first one is operating at the first harmonic of   the gyrofrequency, the second is a frequency multiplier. The achievable characteristics of devices in the terahertz frequency range are presented, such as gain bands, efficiency, gain factors and distributions of high-frequency fields in longitudinal and transverse sections. The gyro-TWT frequency multiplier has a gain bandwidth of  7.2 %, an efficiency of 17 %, and a gain of 30 dB.

The creation of DRFM (Digital Radio Frequency Memory) technology is a revolutionary step in the development of simulating interference techniques. The technology made it possible to transform the received signal with high quality, make the necessary changes to it and emit it in the form of simulating interference. Currently, a high level of imitation of radar signals reflected from real objects has been achieved. The basis for counteracting such interference is a detailed analysis of the differences between the real reflected signal and simulating interference. In this regard, a mathematical model of a signal reflected from a spatially distributed object is considered before and after frequency conversion to video frequency. Based on the analysis of typical variants of interference generation, mathematical models of simulating interference are considered, providing various degrees of similarity to the reflected signal. The results of the model analysis are the basis for constructing algorithms for protecting radar stations from simulating interference.

Adaptive methods have been developed for generating a radar image of a probed surface area. A block diagram of a subsurface sounding radar is described. The results of modeling and experimental studies are presented. Their use makes it possible to develop a subsurface sensing radar capable of effectively identifying hidden objects in concrete walls, as well as detecting cracks, voids and defects in the walls of buildings and structures, snow debris and avalanches, underground communications and organic bodies in the ground.

A simulation procedure for analyzing the electrical and optical characteristics of an AlGaN/GaN intersubbandquantum well middle-wavelength infrared photodetector is presented. The photoconductive gain spectrumwas simulated by coupling the drift-diffusion and capture-escape models in the active region of the devicestructure and by ignoring the contribution of radiative emission. It was shown that the photodetector at zero biasis sensitive over a spectral range from 4 to 6 μm, with the peak absorption occurring at 4.64 μm. The dependenceof the available photocurrent on both the wavelength and the angle of incidence of an unpolarized monochromaticbeam of light was also evaluated. An assessment of the dark current characteristics was estimated at varioustemperatures.

An analysis of methods for processing data from gait deceleration sensors for detecting Parkinson’s disease and a description of the development of a Parkinson’s recognition system based on neural networks with long short term memory (LSTM) are performed. The data used was a publicly available dataset of gait deceleration scores of patients with Parkinson’s disease, obtained using three wearable sensors to collect data from different parts of the body. The research was carried out using machine learning using an LSTM neural network. First, the DAPHNet datasets were segmented using a fixed sliding window algorithm. The wavelet algorithm was then used to extract features from the data set: wavelet entropy and energy, wavelet waveform length, variance and standard deviation of wavelet coefficient. Next, a data enhancement algorithm was used to balance the number of samples in the data sets. To train the model, an LSTM neural network was built with a six-layer network structure: input layer, LSTM layer, reLU layer, fully connected layer, Softmax layer and output layer. After training the model for 1000 iterations, the LSTM neural network algorithm achieved 96.3 % accuracy, 96.05 % precision, 96.5 % sensitivity, and 96.24 % average F1 score for recognizing Parkinson’s disease based on test datasets. Similar studies conducted by other scientific organizations achieved a maximum accuracy of 91.9 % for the same data sets.

Biomedical image segmentation plays an important role in quantitative analysis, clinical diagnosis, and  medical manipulation. Objects in medical images have different scales, types, complex backgrounds, and similar tissue appearances, making information extraction challenging. To solve this problem, a module is proposed that takes into account the features of images, which will improve the biomedical image segmentation network FE-Net. An integral part of the FE-Net algorithm is the connection skipping mechanism, which ensures the connection and fusion of feature maps from different layers in the encoder and decoder. Features at the encoder level are combined with high-level semantic knowledge at the decoder level. The algorithm establishes connections between feature maps, which is used in medicine for image processing. The proposed method is tested on three public datasets: Kvasir-SEG, CVC-ClinicDB and 2018 Data Science Bowl. Based on the results of the study, it  was found that FE-Net demonstrates better performance compared to other methods in terms of Intersection over Union and F1-score. The network under consideration copes more effectively with segmentation details and object boundaries, while maintaining high accuracy. The study was conducted jointly with the Department of Magnetic Resonance Imaging of the N. N. Alexandrov National Oncology Center. Access to the source code of the algorithm and additional technical details is available at https://github.com/tyjcbzd/FE-Net.

The problem of recognizing emotions in a speech signal using mel-frequency cepstral coefficients using a classifier based on the support vector machine has been studied. The RAVDESS data set was used in the experiments. A model is proposed that uses a 306-component suprasegmental feature vector as input to a support vector machine classifier. Model quality was assessed using unweighted average recall (UAR). The use of linear, polynomial and radial basis functions as a kernel in a classifier based on the support vector machine is considered. The  use of different signal analysis frame sizes (from 23 to 341 ms) at the stage of extracting mel-frequency cepstral coefficients was investigated. The research results revealed significant accuracy of the resulting model (UAR = 48 %). The proposed approach shows potential for applications such as voice assistants, virtual agents, and mental health diagnostics.

There obtained an estimate of the minimum value of the photon energy attenuation constant in vacuum α: α = 8 · 10^–19 m^–1 based on quantum concepts of the structure of vacuum and data on the red shift of the emitter spectra of distant galaxies. Presumably, the cosmic microwave radiation is partly the thermal vacuum radiation heated by the photon fluxes from the infinite universe. Despite the universe infinity, the sky is dark precisely due to the photon’s energy absorption from distant and ultra-distant galaxies in vacuum, and not only the photon absorption during various interactions with the gas or dust components of intergalactic clusters. Thus, the emission spectrum of these ultra-distant objects is transformed into the microwave range, which complements the intensity of thermal radiation in this range. The inconsistency of alternative explanations for the red shift is shown: the Doppler effect in the cosmological model of the expanding universe and the Big Bang, and the gravitational shift.

In the present paper there are considered metric Riemannian spaces  V_n^4a,  in the metrics of which four algebraic structures work at once: real numbers  D_m1 and  complex numbers  C_m2, quaternions  H_m3 and octions  O_m4. We are interested in these spaces in terms of their isometric and homothetic mobility. It turns out that there are lacunas (gaps) in the orders  r of complete groups of isometries  G_r and homotheties P_r. The metrics of the most mobile spaces  V_n^4a of the first six lacunarities in the sense of I. P. Egorov are found.