bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic studies of human–chimpanzee divergence using stem cell fusions
Authors: Song Janet H. T. , Grant Rachel L. , Behrens Veronica C. , Kučka Marek , Roberts Kingman Garrett A. , Soltys Volker , Chan Yingguang Frank , Kingsley David M. 
Published: December 2021

Significance
Comparative studies of humans and chimpanzees have revealed many anatomical, physiological, behavioral, and molecular differences. However, it has been challenging to map these differences to particular chromosome regions. Here, we develop a genetic approach in fused stem cell lines that makes it possible to map human–chimpanzee molecular and cellular differences to specific regions of the genome. We illustrate this approach by mapping chromosome regions responsible for species-specific gene expression differences in fused tetraploid cells. This approach is general, and could be used in the future to map the genomic changes that control many other human–chimpanzee differences in various cell types or organoids in vitro.
An analysis of stochastic variance reduced gradient for linear inverse problems
*
Authors: Jin Bangti , Zhou Zehui , Zou Jun 
Published: December 2021

Abstract
Stochastic variance reduced gradient (SVRG) is a popular variance reduction technique for accelerating stochastic gradient descent (SGD). We provide a first analysis of the method for solving a class of linear inverse problems in the lens of the classical regularization theory. We prove that for a suitable constant step size schedule, the method can achieve an optimal convergence rate in terms of the noise level (under suitable regularity condition) and the variance of the SVRG iterate error is smaller than that by SGD. These theoretical findings are corroborated by a set of numerical experiments.
Two-dimensional ultrathin MoS2 modified hydrogenated TiO2 nanoparticles for superior photocatalytic degradation under simulated sunlight
Authors: Wang Dandan , Yu Bo , Li Hongji , Liu Qianyu , Sun Dongshu , Wang Jia , Che Guangbo , Liu Chunbo 
Published: December 2021

Abstract
Photocatalysis is an effective technology for degradation of organic contaminants. Herein, we firstly synthesized hydrogenated TiO2 (HT) nanoparticles by calcining P25, and on the basis of HT, two-dimensional ultrathin MoS2/HT binary composites with different component ratios (MHT-20%, MHT-30% and MHT-35%) were controlled prepared. UV–vis diffuse reflectance spectra (DRS) showed that the HT nanoparticles exhibited stronger absorption towards visible light in the range of 550–800 nm compared to P25, and the introduction of two-dimensional ultrathin MoS2 nanosheets further enhanced the visible light absorption ability of MHT composites. Under simulated sunlight irradiation, the removal test of methylene blue (MB) in the present of various photocatalysts indicated that the catalytic performance of HT sample was better than that of P25, and MHT binary composites displayed more excellent photocatalytic performance. A maximum removal efficiency of MB reached 95% within 4 h over MHT-30% photocatalyst. Moreover, the kinetic constant of MHT-30% catalyst is 5.6, 3.6 and 2.5 times as much as that of P25, MoS2 and HT, respectively. In addition, the repeated degradation study and composition analysis of MHT-30% before and after photocatalytic reaction showed that MHT-30% photocatalyst exhibited good stability, and the removal rate of MB still reached 88% in four cycles. The improved and stable photocatalytic performance of MHT-30% can be attributed to band matching and tight interface bonding between MoS2 and HT, which accelerated the electron transfer and broaden the visible-light response range.
Shock-induced plasticity and phase transformation in single crystal magnesium: an interatomic potential and non-equilibrium molecular dynamics simulations
Authors: Jian Zhiyong , Chen Yangchun , Xiao Shifang , Wang Liang , Li Xiaofan , Wang Kun , Deng Huiqiu , Hu Wangyu 
Published: December 2021

Abstract
An effective and reliable Finnis–Sinclair (FS) type potential is developed for large-scale molecular dynamics (MD) simulations of plasticity and phase transition of magnesium (Mg) single crystals under high-pressure shock loading. The shock-wave profiles exhibit a split elastic–inelastic wave in the [0001]HCP shock orientation and a three-wave structure in the [10-10]HCP and [-12-10]HCP directions, namely, an elastic precursor, a followed plastic front, and a phase-transition front. The shock Hugoniot of the particle velocity (U
p) vs the shock velocity (U
s) of Mg single crystals in three shock directions under low shock strength reveals apparent anisotropy, which vanishes with increasing shock strength. For the [0001]HCP shock direction, the amorphization caused by strong atomic strain plays an important role in the phase transition and allows for the phase transition from an isotropic stressed state to the product phase. The reorientation in the shock directions [10-10]HCP and [-12-10]HCP, as the primary plasticity deformation, leads to the compressed hexagonal close-packed (HCP) phase and reduces the phase-transition threshold pressure. The phase-transition pathway in the shock direction [0001]HCP includes a preferential contraction strain along the [0001]HCP direction, a tension along [-12-10]HCP direction, an effective contraction and shear along the [10-10]HCP direction. For the [10-10]HCP and [-12-10]HCP shock directions, the phase-transition pathway consists of two steps: a reorientation and the subsequent transition from the reorientation hexagonal close-packed phase (RHCP) to the body-centered cubic (BCC). The orientation relationships between HCP and BCC are (0001)HCP ⟨-12-10⟩HCP // {110}BCC ⟨001⟩BCC. Due to different slipping directions during the phase transition, three variants of the product phase are observed in the shocked samples, accompanied by three kinds of typical coherent twin-grain boundaries between the variants. The results indicate that the highly concentrated shear stress leads to the crystal lattice instability in the elastic precursor, and the plasticity or the phase transition relaxed the shear stress.
Analysis and improvement of the Bancroft algorithm for GNSS satellite orbit determination
Authors: Chen Yongchang , Sheng Chuanzhen , Yi Qingwu , Li Ran , Ma Guangqing , Zhang Jingkui 
Published: December 2021

Abstract
Satellite orbit information is crucial for ensuring that global navigation satellite systems (GNSSs) provide appropriate positioning, navigation and timing services. Typically, users can obtain access to orbit information of a specific accuracy level from navigation messages or precise ephemeris products. Without this information, a system will not be able to provide normal service. In response to this problem, initial orbit information of a certain level of precision must be obtained to support subsequent applications, such as broadcasting or precise ephemeris calculations, thereby ensuring the successful subsequent operation of the navigation system. One of two ways to calculate the initial orbit of a GNSS satellite is to utilize ground tracking stations to observe satellite vector information in the geocentric inertial system; the second way is to utilize GNSS range observations and known orbit information from other satellites. For the second approach, some researchers use the Bancroft algorithm combined with receiver clock offset to determine the initial orbit of GNSS satellites. Because this method requires an additional known receiver clock offset, we study the dependence of the Bancroft algorithm on clock offset in GNSS orbit determination. By assessing the impact of errors of different magnitude on the accuracy of the orbit results, we obtain experimental conclusions. After comprehensively analyzing various errors, we determine the accuracy level that the Bancroft algorithm can achieve for orbit determination without considering receiver clock correction. Dual-frequency and single-frequency pseudorange data from International GNSS Service stations are used in orbit determination experiments. When a small receiver clock offset is considered and no correction is made, the deviations in the calculated satellite positions in three dimensions are approximately 979.3 and 1118.1 m (dual and single frequency); with a satellite clock offset, these values are approximately 928.8 and 1062.7 m (dual and single frequency).
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interface
Authors: Mattioli F , Porcaro C , Baldassarre G 
Published: December 2021

Abstract

Objective. Brain-computer interface (BCI) aims to establish communication paths between the brain processes and external devices. Different methods have been used to extract human intentions from electroencephalography (EEG) recordings. Those based on motor imagery (MI) seem to have a great potential for future applications. These approaches rely on the extraction of EEG distinctive patterns during imagined movements. Techniques able to extract patterns from raw signals represent an important target for BCI as they do not need labor-intensive data pre-processing. Approach. We propose a new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a ‘baseline’ class) using a data augmentation algorithm and a limited number of EEG channels. In addition, we present a transfer learning method used to extract critical features from the EEG group dataset and then to customize the model to the single individual by training its late layers with only 12-min individual-related data. Main results. The model tested with the ‘EEG Motor Movement/Imagery Dataset’ outperforms the current state-of-the-art models by achieving a

99.38
%

accuracy at the group level. In addition, the transfer learning approach we present achieves an average accuracy of

99.46
%

. Significance. The proposed methods could foster the development of future BCI applications relying on few-channel portable recording devices and individual-based training.
Method for dynamic measurement of thermal diffusivity during laser soldering of biological tissues
Authors: Ryabkin D I , Molodykh V V , Gerasimenko A Yu. 
Published: December 2021

Abstract
In this paper, we propose a method for dynamic measurement of the thermal diffusivity coefficient during laser soldering of biological tissues. The method is based on modelling the function of temperature dependence on time during cooling of biological tissue after exposure to laser radiation. The simulation is carried out by solving the heat equation for a homogeneous biological tissue and the absence of external heat sources. The desired value of the thermal diffusivity coefficient was determined by optimizing the residual functional of the temperature functions from time obtained experimentally and by solving the thermal diffusivity equation. Experiments were carried out to measure the thermal diffusivity coefficient by the proposed method for myocardial and skin tissues at maximum heating temperatures of 40, 50, 60 °C. The measured values of the thermal diffusivity coefficient for the myocardium are in the range from 2.3 to 2.7 m2/s*10-6, and for the skin from 1.5 to 1.7 m2/s*10-6.
Application of machine learning methods for automated classification and routing in ITIL
Authors: Nikulin VV , Shibaikin S D , Vishnyakov A N 
Published: December 2021

Abstract
The article analyzes the application of machine learning methods for automated classification and routing in ITIL library. ITSM technology and ITIL are considered. The definitions of the incident and IT services are given. Then, the vectorization and extraction of keywords in the information written in natural language is carried out and lemmatization and TF-IDF measure will be used. A comparative analysis of the application of machine learning methods is given as well as a comparison of the results of automatic classification of text information using gradient boosting and a convolutional neural network. Various parameters of these methods are considered and the most effective method of machine learning is determined. The results of using machine learning methods for automated classification of incidents allows high-precision routing of requests for restoring the operability of IT services, reducing response time and errors associated with the human factor.
Measuring the depth of surface cracks using alternating current potential drop technique, with suppression of the influence of the electromagnetic properties of the metal
Authors: Shkatov P N 
Published: December 2021

Abstract
Traditional measuring techniques often lead to errors due to the need to register signals in both defective and defect-free areas. In this paper, we introduce an alternating current potential drop technique with detuning from the influence of variations in the electromagnetic properties of the metal achieved by registering a signal only at the defective site. We show that, with an appropriate choice of measurement parameters, the use of the proposed technique leads to an increase in sensitivity to the crack depth as well as to an increase in the measurement range.
Building a decision support system based on fuzzy logic to reduce the total harmful emissions from a fossil fuel boiler or power plant
Authors: Filinkov L I , Likhter A M , Rybakov A V , Varlamov K S 
Published: December 2021

Abstract
This article discusses the software implementation using the theory of fuzzy sets. To build the model, we use data on wind direction, wind strength, the distance of residential buildings and the population of the expected area of pollution distribution. To do this, the most critical parameters must be ranked such as size of population. wind speed and wind direction. We will consider them as input data. We use Scilab as the processing environment.
Control system of intelligent buildings based on convolutional neural networks
Authors: Lezhnina Yu. A. , Maltseva N. S. 
Published: December 2021

Abstract
In recent years, with the development of ”Internet of things” appeared another concept – smart home environment, which is defined as the physical infrastructure to operate of ambient intelligence. For the effective operation of such facilities requires to develop of new methods and approaches for adaptive control. In this paper, we analyzed the parameters characterizing the state of the control object, identify the necessary set of measured parameters obtained from the sensors, and an informative set of input parameters. We design method of training of neural network.
Dynamics of media with stationary parameters and telegraph equations
Authors: Kushner A G , Kushner E N 
Published: December 2021

Abstract
The paper proposes an approach for constructing exact solutions of differential equations of mathematical physics, in particular, the telegraph equation. The method is based on the theory of finite-dimensional dynamics of systems of evolutionary differential equations. This theory is a natural extension of the theory of dynamical systems to partial differential equations. It allows one to construct exact solutions of partial differential equations even in the case when equations do not have symmetry algebras sufficient for integration.
Diffraction propagation of vortex diffractals
Authors: Korolenko P , Kubanov R , Pavlov N , Zotov A 
Published: December 2021

Abstract
A brief retrospective analysis of studies of fractal light radiation is carried out. To assess the prospects of this scientific direction, new original results of studying the diffraction propagation of vortex wave beams with a fractal structure (vortex diffractals) are also presented. For this purpose, computational algorithms and related software have been developed. In calculating the amplitude-phase and scaling characteristics of diffractals two-dimensional Weierstrass functions and multistructures of Gaussian beams were used. The results indicate a high information capacity of vortex diffractals and explain their resistance to the influence of turbulence in the propagation medium.
Active positioning system based on hall-effect sensors
Authors: Karlova G F , Avdochenko B I , Belozyorova E A 
Published: December 2021

Abstract
The paper investigates the behavior of Hall-effect sensors (HES) operating in microwave frequency range. In order to evaluate the capabilities of small radars based on HES’s, the calculation of HES output voltage dependence on microwave intensity is carried out. It is shown that at power flow density I(t) = 10 μW/cm2 (a permissible value for a long-term human body exposure) the single GaAs sensor output Hall voltage U
H ~ 0.03 μV.
It is also demonstrated that integration of signals with due regard for their delays (as in the case of range-difference radar systems) gives an opportunity to obtain electromagnetic image of any point within the antenna coverage area with centimeter-level accuracy. The paper describes the experimental assembly and estimates the distances to the detected contrasting objects.
Investigation of the effect of the summation of monopolar pulses of individual generators for a bipolar UWB pulse formation
Authors: Balzovsky E V , Lysykh P M 
Published: December 2021

Abstract
A technique for the formation of ultra-wideband bipolar pulses using two synchronized generators of monopolar pulses of different polarities and a broadband ring summing unit is considered. In contrast to the traditional circuit on short-circuited segments of line, the proposed approach allows varying the duration of bipolar pulses by changing the time delay between the generators
Enhancing performance in a LOS MIMO communication using a passive repeater
Authors: Eissa Mahmoud , Sukhanov D 
Published: December 2021

Abstract
This paper presents a technique for obtaining a well-conditioned channel matrix in a line of sight multiple input multiple output (MIMO) environment. The technique is based on the implementation of a back-to-back antenna system as a passive repeater to enhance performance in MIMO systems. The flexible configuration with no need for a phase controller allows to spread the proposed repeater in MIMO communications to ensure spatial multiplexing and enhance capacity. A condition number and matrix rank are proposed as metrics to demonstrate the validity of the proposed method.
Two-dimensional THz reflectometry of a periodic structure obtained by additive technology
Authors: Badin A V , Berdyugin A I , Moskalenko V D , Simonova K V , Gursky R P 
Published: December 2021

Abstract
This paper considers the development and application of a system of reflectometry for the analysis of the homogeneity of structures manufactured by additive technologies. A system of reflectometry based on a backward wave oscillator, a two-dimensional object positioning system and an optoacoustic detector (Goley cell) is described. The results of reflectometry of the hexagonal periodic structure of cells based on acrylonitrile butadiene styrene at a wavelength of 343 microns are presented.
Modeling of electrotransport properties of Li-intercalated graphene film
Authors: Sergeyev D , Duisenova A , Embergenov Zh 
Published: December 2021

Abstract
In this work, within the framework of density functional theory combined with the method of nonequilibrium Green’s functions the density of states, transmission spectrum, current-voltage characteristics, and differential conductivity of Li-intercalated graphene (LiC6) have been determined. It is shown that in the energy range of -1.3÷-1.05 eV the quasiparticle transport through the nanostructure is disable. The features of IV- and dI/dV-characteristics of LiC6 in the form of decreasing of resistance in the range of -0.4÷0.4 V were revealed, and in the interval of 0.4÷1.4 V formation of negative differential resistance area, related to scattering of quasiparticles. It is established, that LiC6 nanodevice has 12÷13 ballistic channels and has the maximum amount of conductance 12÷13G0
, where Go
is the conductance quantum.
Issues of technical implementation of ground-based microwave radiometric system calibration
Authors: Rostokin I N , Fedoseeva E V , Rostokina E A , Shchukin G G 
Published: December 2021

Abstract
The theoretical bases of a method of carrying out calibration of microwave radiometric system on a noise signal of the external noise generator are analysed, the parameters setting value of gain of antenna temperature at introduction in structure of system of such external source of a calibration signal are determined. The questions of technical realization of an external source of a calibration signal for microwave radiometric system are considered, the structural scheme is presented, the place of its arrangement in structure of the antenna is determined. The necessity of using a horn antenna to create directional radiation towards the mirror antenna emitter is shown. The data on the design of such a calibration signal source for the case of its use in a three-band microwave radiometric system with the reception of a noise signal at the common antenna aperture and a sequential separation of the input signals of the three bands in the feeder path of the common mirror irradiator are presented. The influence of the design and, accordingly, the directional properties of the horn antenna of a microwave radiometric system calibration signal source on the coefficient characterizing the radiation divergence created by the noise generator horn, as well as the frequency properties of this coefficient are analysed. The results of measurements of radio-thermal radiation by a three-band microwave radiometric system when two calibration periods with reception of a radio-noise signal from an external calibration signal source located at the base of the antenna mirror are presented.
Active IR location as the roadway profilometry method
Authors: Khmelev V L , Fominykh A F 
Published: December 2021

Abstract
This article observe a using of active infrared beam location as roadway surface quality control. Changes in the spatial structure of the emitted IR radiation by surfaces within the capture scene allow creating a depth map of this scene. An optical camera makes it possible to use classical computer vision methods for stitching a depth map. For testing the possibility of using this approach, we made statistical studies on a multiple sample of distance measurements. Here we explain two experimental schemes with a programmable mechanical scanning system. The first one, we had determined the distance, which the image is capture accurately. The second, we measure the planar resolution, a minimum size of the defect that recognize by the infrared beam location system.