bluuebunny/crossref_metadata_2025_split huggingface dataset:
On some problems of mathematical modeling of diffusion of non-equilibrium minority charge carriers generated by kilovolt electrons in semiconductors
Authors: Stepovich M A , Seregina E V , Kalmanovich V V , Filippov M N 
Published: January 2021

Abstract
Some problems of mathematical modeling of the diffusion of non-equilibrium minority charge carriers generated by kilovolt electrons in semiconductor targets are considered. The calculations were carried out by the matrix method, which makes it possible to solve the equations of heat and mass transfer in multilayer planar structures with an arbitrary number of layers. Estimates of the distributions of minority charge carriers in two-layer semiconductor structures of the "film-substrate" type are obtained.
Some Features of Sentiment Analysis for Russian Language Posts and Comments from Social Networks
Authors: Sidorov N , Slastnikov S 
Published: January 2021

Abstract
Sentiment analysis of different language texts is one of the very popular machine learning tasks. The complexity of its solution depends both on the characteristics of a particular language, and on the length of the evaluated texts. In our work, we consider the task of creating a sentiment analysis software tool for Russian posts and comments from the most popular social networks without any domain restriction. The features of constructing both the algorithmic and the software parts of the problem are described, some quality and performance metrics of the suggested neural network system are presented.
A study of a complex model of opinion dynamics in social networks
Authors: Gubanov D A 
Published: January 2021

Abstract
Many micro-level models of information processes in social networks consider either a change in the information-psychological state of agents (opinions, beliefs, attitudes) or a change in their observable behavior (actions). The goal in this paper is to develop and analyze a complex agent-based model of opinion dynamics that describes the dynamics of agents’ beliefs and the process of performing actions by agents. The issues of reaching consensus and polarizing opinions of agents are investigated.
Limit evolution in some Markovian models of opinion dynamics with large number of participants
Authors: Vorobyeva Margarita , Manita Anatoly 
Published: January 2021

Abstract
We consider a discrete time Markov process describing dynamics in a society of K agents with special opinion exchange rules. In the limit as K goes to infinity, we prove that the process converges to some limiting dynamical system and afterwards we discuss some properties of that system.
Particle size and phase equilibria in classical logarithmic fluid
Authors: Lasich M , Zloshchastiev K G 
Published: January 2021

Abstract
An interparticle interaction potential has been recently proposed in studies of condensate-like systems described by logarithmically nonlinear equations, such as the superfluid helium-4 and Korteweg-type melts. It has the shape of a Gaussian multiplied by a linear function and can switch between the attraction and repulsion regimes as the distance varies. We consider a classical fluid model with a discretized version of this potential in Monte Carlo molecular simulations in the Gibbs ensemble. We demonstrate a two-phase system consisting of a dense “liquid” phase in coexistence with a significantly less dense “vapour” phase. For computations, the particle size term in the potential was varied to determine its effect on both the phase envelope and the critical point of the system. It is found that the logarithm of the dimensionless critical temperature decreases in a sigmoid fashion with increasing particle size, while the critical density may be directly proportional to the particle size.
DMRG study of FQHE systems in the open cylinder geometry
Authors: Misguich G. , Jolicoeur Th. 
Published: January 2021

Abstract
The study of the fractional quantum Hall liquid state of two-dimensional electrons requires a non-perturbative treatment of interactions. It is possible to perform exact diagonalizations of the Hamiltonian provided one considers only a small number of electrons in an appropriate geometry. Many insights have been obtained in the past from considering electrons moving on a sphere or on a torus. In the Landau gauge it is also natural to impose periodic boundary conditions in only one direction, the cylinder geometry. The interacting problem now looks formally like a one-dimensional problem that can be attacked by the standard DMRG algorithm. We have studied the efficiency of this algorithm to study the ground state properties of the electron liquid at lowest Landau level filling factor v = 1/3 when the interactions are truncated to the two most important repulsive hard-core components. Use of finite-size DMRG allows us to conclude that the ground state is a compressible two-electron bubble phase in agreement with previous Hartree-Fock calculations. We discuss the treatment of Coulomb interactions in the cylinder geometry. To regularize the long-distance behavior of the Coulomb potential, we compare two methods : using a Yukawa potential or forbidding arbitrary long distances by defining the interelectron distance as the chord distance through the cylinder. This allows us to observe the Wigner crystal state for small filling factor.
Initial Acquisition and Synchronization Based on Nonparametric Reception Techniques for IoT
Authors: Osipov Dmitry 
Published: January 2021

Abstract
Internet of Things (IoT) is one of the most important emerging techniques for the future generation communication systems. Recently a new approach to IoT physical layer design based on FH OFDMA and nonparametric reception techniques has been proposed. This approach offers a number of benefits including: high interference proofness and thus high user capacity, elimination of the channel estimation and equalization techniques and thus reduced overhead, low complexity of both transmission and reception techniques. However initial acquisition and synchronization methods design for such systems remains a challenging problem. In existing IoT solutions this problem is solved by employing signals with special properties. This paper advocates a different approach: initial acquisition and synchronization methods development based solely on the same signalling and reception techniques that are used for information transmission and the use of low-rate codes with low complexity decoding.
The development of statistical methods for the diagnosis of neurological diseases based on multiparameter analysis of brain activity
Authors: Yunusov V A , Demin S A 
Published: January 2021

Abstract
The application of data science for the analysis of biomedical data presented as time series allows using new methods of analysis of living systems. Therefore, using these methods it could be possible to discover new diagnostic criteria for neurological diseases. In this paper, in the framework of Memory Functions Formalism, one of the approaches of statistical physics, we analyze recordings of signals of the human brain cortex in the sleep state of 19 patients with nocturnal frontal lobe epilepsy and 8 healthy subjects. We observe alterations of dynamic parameter behavior at the pathology and in healthy subjects. Furthermore, we reveal significant alterations in brain rhythms manifestations at statistical memory functions power spectra of patients with epilepsy and healthy subject. As a result, we show that the application of the statistical analysis of electroencephalogram recordings, after appropriate verification, can be helpful in the search of diagnostic criteria of nocturnal frontal lobe epilepsy.
HPC Resources of the Higher School of Economics
Authors: Kostenetskiy P. S. , Chulkevich R. A. , Kozyrev V. I. 
Published: January 2021

Abstract
The National Research University Higher School of Economics launched its HPC cluster and created a new division named the Supercomputer Simulation Unit. Now the university HPC cluster occupies seventh place in rating the most powerful computers of the CIS TOP50. The HPC cluster uses to solve machine learning problems, population genomics, hydrodynamics, atomistic and continuous modeling in physics, generative probabilistic models, financial row forecasting algorithms, and other actual problems. Paper describes the HSE HPC resources and experience of their use for scientific and educational tasks.
Online detection of failures generated by storage simulator
Authors: Arzymatov Kenenbek , Hushchyn Mikhail , Sapronov Andrey , Belavin Vladislav , Gremyachikh Leonid , Karpov Maksim , Ustyuzhanin Andrey 
Published: January 2021

Abstract
Modern large-scale data-farms consist of hundreds of thousands of storage devices that span distributed infrastructure. Devices used in modern data centers (such as controllers, links, SSD- and HDD-disks) can fail due to hardware as well as software problems. Such failures or anomalies can be detected by monitoring the activity of components using machine learning techniques. In order to use these techniques, researchers need plenty of historical data of devices in normal and failure mode for training algorithms. In this work, we challenge two problems: 1) lack of storage data in the methods above by creating a simulator and 2) applying existing online algorithms that can faster detect a failure occurred in one of the components.
We created a Go-based (golang) package for simulating the behavior of modern storage infrastructure. The software is based on the discrete-event modeling paradigm and captures the structure and dynamics of high-level storage system building blocks. The package's exible structure allows us to create a model of a real-world storage system with a configurable number of components. The primary area of interest is exploring the storage machine's behavior under stress testing or exploitation in the medium-or long-term for observing failures of its components.
To discover failures in the time series distribution generated by the simulator, we modified a change point detection algorithm that works in online mode. The goal of the change-point detection is to discover differences in time series distribution. This work describes an approach for failure detection in time series data based on direct density ratio estimation via binary classifiers.
Local high-order conservative space-time adaptive mesh refinement with the Runge-Kutta time integration for solving the systems of conservation laws
Authors: Korneev B A , Levchenko V D , Ivanov A V , Zakirov A V 
Published: January 2021

Abstract
Numerical simulation is widely used as a main way of researching the processes described by the systems of partial differential equations in the divergence form, like fluid dynamics, traffic flow, wave propagation. To obtain desired accuracy and resolution, the high-order numerical methods are used. In this paper we consider the Runge-Kutta (RK) time discretization, when the space discretization can be high-order finite volume method, discontinuous Galerkin method or others. Presence of discrete analogue of conservation is considered to be very important for such methods as it corresponds to the essential feature of simulated process, becoming especially vital at the discontinuous solutions. The adaptive mesh refinement (AMR) techniques are used to get the numerical solution with more resolution where needed. For the explicit numerical scheme obeying the Courant-Friedrichs-Lewy (CFL) condition, the bigger time integration step can be chosen for the coarser cells. The problem is how to reformulate the numerical scheme near the boundary between cells of different size, keeping the conservation and high-order accuracy. In this paper a new algorithm is suggested. The changes in the numerical method are made only in the vicinity of the boundary. The local character of the developed algorithm allows us to efficiently implement it at modern computer systems. Results of validation tests of developed solver are shown.
Performance analysis of CUDA, OpenACC and OpenMP programming models on TESLA V100 GPU
Authors: Khalilov Mikhail , Timoveev Alexey 
Published: January 2021

Abstract
Graphics processors are widely utilized in modern supercomputers as accelerators. Ability to perform efficient parallelization and low-level allow scientists to greatly boost performance of their codes. Modern Nvidia GPUs feature low-level approaches, such as CUDA, along with high-level approaches: OpenACC and OpenMP. While the low-level approach aims to explore all possible abilities of SIMT GPU architecture by writing low-level C/C++ code, it takes significant effort from programmer. OpenACC and OpenMP programming models are opposite to CUDA. Using these models the programmer only have to identify the blocks of code to be parallelized using pragmas. We compare the performance of CUDA, OpenMP and OpenACC on state-of-the-art Nvidia Tesla V100 GPU in various typical scenarios that arise in scientific programming, such as matrix multiplication, regular memory access patterns and evaluate performance of physical simulation codes implemented using these programming models. Moreover, we study the performance matrix multiplication implemented in vendor-optimized BLAS libraries for Nvidia Tesla V100 GPU and modern Intel Xeon processor.
Optimization of request processing times for a heterogeneous data aggregation platform
Authors: Tokareva Victoria 
Published: January 2021

Abstract
A heterogeneous data aggregation system, e.g. developed within the frame of the GRADLC project, allows for a flexible expansion by connecting new data storages, as well as providing researchers a fast and aggregated access to heterogeneous data from independent (astroparticle physics) projects, while reducing the load on the original data storages. However, this flexibility requires balancing user requests in the queue with respect to various request processing times for the distributed storages, taking into account the different data processing policies on each particular storage. In order to attack this problem, a mathematical model of the data aggregation system was developed, and approaches to optimization of the request ordering in the processing queue are proposed and investigated by performing a numerical experiment. Based on this results, a job shop scheduling algorithm was revealed which gives benefit in mean request processing times compared to the well-known first in, first out (FIFO) model.
Monte Carlo simulations of the switching processes in the superconducting quantron-based neuron
Authors: Gorchavkina A A , Bastrakova M V , Klenov N V , Satanin A M 
Published: January 2021

Abstract
We study the response function of a superconducting single-contact interferometer (quantron or rf-SQUID), which is the building block for adiabatic neuron with a nonlinear transfer characteristic. It is shown that the intrinsic shunt capacitance of the junction leads to distortions in the response function. At the same time the contact resistance leads to the suppression of these vibrations. The response function of the rf-SQUID at finite temperature is calculated by Monte Carlo method.
Cloud storage capable to select events upon user request for medium-sized astrophysical experiments
Authors: Kryukov Alexander , Bychkov Igor , Korosteleva Elena , Mikhalov Andrey , Nguyen Min-Duc 
Published: January 2021

Abstract
We present a cloud storage for collaborations of small and medium-sized experiments in the field of particle astrophysics. This storage provides a unified interface for accessing data from different experiments. In this article, we will focus on the capabilities of the storage for processing user requests for data, as well as on some technical details of the implementation of data selection. We have deployed a working prototype of the storage. Currently the prototype integrates data from such astrophysical experiments as TAIGA and KASCADE. As a result, users of the respective collaborations have the opportunity to collect scientific data from different experiments seamlessly within one request to conduct joint data analysis.
Semiclassical Approximation for the Curie – Weiss Model
Authors: Bulekov Aleksandr 
Published: January 2021

Abstract
The paper is devoted to the construction of spectral series and the estimation of the approximation accuracy for the operator of the Curie – Weiss model. In the course of work, the operator is reduced to a tridiagonal form in the subspace of the original space, then to a second-order difference equation. The admissibility of reducing an operator to a subspace is presented. It is shown that the difference equation can be considered in the discrete semiclassical approximation. In the obtained classical system, the dependence of the turning points on the model parameters is investigated. The asymptotics of the spectrum of the Curie-Weiss operator is calculated and the accuracy of the approximation is estimated.
Development of the new ensemble weather prediction system at the Hydrometcentre of Russia
Authors: Mizyak Vasily , Rogutov Vladimir , Alipova Ksenia 
Published: January 2021

Abstract
The new ensemble weather prediction system developed at Hydrometcenter of Russia is presented. It is based on the global atmospheric model with the resolution of 0.9×0.72 degrees in longitude and latitude, respectively, 96 vertical levels, and the Local Ensemble Transform Kalman Filter (LETKF) algorithm implemented by the authors. The key feature of this system is the centering of the initial data ensemble onto the operational analysis of the Hydrometcenter of Russia, which allows to take into account some satellite observations not assimilated in LETKF. Some improvements in assimilating radiosounding data has increased the accuracy of short range weather forecasts. The first results of ensemble medium-range forecasts are presented. Now this ensemble prediction system is ready for a quasi-operational use.
Analysis of Leakage and Corrosion of Air Preheater in Coal-Fired Power Plant
Authors: Jiang Long 
Published: January 2021

Abstract
A unit of a coal-fired power plant (300MW) in North China was selected to study. The flue gas parameters (NH3, O2 and flue gas temperature) at the outlet of denitration system, oxygen content at the inlet and outlet of air preheater, and composition of combustion coal were tested. Then, the air leakage and corrosion of air preheater were evaluated from the operation of denitration system, air preheater leakage detection, and acid dew point calculation of flue gas. The influence of ammonium hydrogen sulfate from denitration system on the downstream air preheater is limited due to the low ammonia escaping. The air leakage rates of the air preheater at the side A and B were 8.45% and 3.01%, which are higher than the normal value (< 3%). Due to the air leakage of air preheater on side B, the cold end temperature of air preheater is significantly lower than the acid dew point of flue gas, resulting in the condensation of sulfuric acid mist in flue gas on the air preheater and the sulfuric acid corrosion on the air preheater.
Comparison and Summary of Relevant Standards for Comprehensive Utilization of Fly Ash at Home and Abroad
Authors: Jin Shengxiang , Zhao Zhihong , Jiang Shifeng , Sun Jian , Pan Haibin , Jiang Long 
Published: January 2021

Abstract
Based on the comprehensive utilization situation of fly ash in some countries, the contents and characteristics of the existing fly ash comprehensive utilization standard systems of these countries were discussed and compared, so as to provide guidance and suggestions for improving the standard system and the comprehensive utilization of fly ash in China. The average comprehensive utilization rate of fly ash in China is 70%, which is mainly used in building materials, but is relatively low in road, backfill and other scopes. Compared with developed countries, the scope and limit value of indexes involved in the standards of fly ash in China are loose, and the fields involved are mostly traditional building materials and infrastructure construction. The comprehensive utilization of fly ash of China can be improved from the following points: the indexes investigated in standards should reflect and conform to the particularity of China; the comprehensive utilization standard of fly ash should be more suitable for the local region; the power plants should actively explore and improve their own comprehensive utilization.
Study on the Safety Guarantee of Ship Mooring from Frequent Cable Accidents
Authors: Gao Feng , Hu Ke , Shen Wen-jun , Li Yan 
Published: January 2021

Abstract
According to the review of the frequent mooring broken cable accidents around the world, this paper analyzes the current situation of port ship mooring operation, and analyzes the innovative research, development and application of mooring technology at home and abroad. In this paper, on the basis of the motion compensation principle of active anti-rolling, and relying on the parallel platform, an intelligent mooring system which can act as both cable and fender function is developed. The system can autonomously adapt to the ship’s six-degree-of-freedom movement, monitor the ship’s load data, and realize the active control of the ship through follow-up and damping, so as to achieve the purpose of autonomously controlling the ship-shore mooring process intellectualization.
Experiential Study of Measurement Comparison between Ocean Buoys and Wave Gauges in Large Wave Flume
Authors: Hu Chuanqi , Wang Yina , Li Yuesong , Chen HanBao 
Published: January 2021

Abstract
The actual wave flow condition is difficult to control, so the real measurement accuracy of ocean wave buoy has not been verified. Based on the above background, this experiment conducted comparison test on two kinds of ocean wave buoys in the large-scale wave flume laboratory. Based on regular waves and under different conditions of period, velocity and wave height, the wave height measured by the 2m capacitive wave height meter was compared with the measured wave surface data by the buoy. The experimental results show that the relative error of wave height of SBF6-1 and SBF3-2 buoys is 1.2%∼15% and 2.5%∼14.2%. According to the results of spectrum comparison, the spectrum peak frequency of buoy and wave height instrument is relatively consistent under the same working conditions, but the difference of wave energy density at the spectrum peak frequency is obvious and the error range is 14%∼30%.
Unconventional Oil Ores around the World: A Review
Authors: Ma Guoqiang , Jia Jianna , Qi Zhaoyu , Peng Shitao 
Published: January 2021

AbstractWith the increasing demand of the conventional oil and gas, unconventional oils are playing an increasingly important role in global energy supplying. Unconventional oil ore (such as oil sands, asphalt rocks) has been widely used in the industry. The bitumen recovered from the unconventional oil ore can be used for the production of synthetic crude oil. Canada has the world’s largest oil sands deposits in Alberta. Since the discovery of the Athabasca oil sands, many technologies have been applied to recovery the bitumen in industry, and the daily production of unconventional oil has reached 10.9 × 106barrels in 2018. However, the Chinese oil sands has not been applied to the industry due to the complex characteristics. Much more attention will be paid to the fundamental research and process development of the unconventional oil ores.