bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spark plasma sintering of transparent YAG:Ce ceramics with LiF flux
Authors: Paygin V D , Ilela A E , Deulina D E , Lyamina G V , Stepanov S A , Alishin T R , Dvilis E S , Khasanov O L , Valiev D T , Kalashnikov M P 
Published: August 2021

Abstract
Transparent yttrium aluminum garnet (YAG) ceramics doped with cerium ions (Ce3+) were successfully synthesized using the spark plasma sintering (SPS) process at a temperature of 1600 °C, isothermal exposure 10 minutes, pressure 100 MPa and a heating rate 10 °C/min from a mechanical mixture of powders of yttrium, aluminum, and cerium oxides. Transmittance in the visible range for 1 mm thick samples is above 40 %; in the near infrared is above the 60 %. Vickers hardness was 15±1.05 GPa. The optimal SPS conditions have been discussed and suggested in order to obtain a good combination of density and transmittance.
Study of thermophysical characteristics of composite sorption-active materials for life support systems of manned spacecraft and civil aviation
Authors: Ferapontova L L , Zakharov I V , Ferapontov Y A , Kurzina I A , Grunski V N 
Published: August 2021

Abstract
The method of differential thermal analysis (DTA) was used to study the heat resistance of composite sorption-active materials (CSAM) based on a matrix of fluoroplast and NaX crystallites. Decrease in the temperature of thermal destruction of the polymer matrix by about 90°C was found with an increase in the NaX content in KCAM from 2 to 25% by weight. Using the original method, the thermal conductivity was also studied. The analysis of the totality of the obtained results suggests that the studied parameters depend on the ratio of adsorbent-filler/polymer matrix: with an increase in the binder content in the CSAM from 5 to 25 wt. % thermal conductivity decreases from 0.227 to 0.184 W/mk. This pattern is due to the growth of CSAM mesopores filled with air. The hypothesis is confirmed by the analysis of the secondary porous structure of KSAM
Elemental composition of single-phase kidney stones. Part II
Authors: Aleksandrova A , Tsygankova A , Lundovskaya O , Korolkov I , Filatov E , Sabantseva E , Gubanov A 
Published: August 2021

Abstract
The article is devoted to the element composition study of 5 kidney stones types. Calculi consisting of calcium oxalate, uric acid, hydroxyapatite, brushite and struvite were analysed by optical emission spectrometry with inductively coupled plasma (ICP-OES). The elements Ba, Ca, Cu, Fe, K, Li, Mg, Mn, Na, P, Sr and Zn were determined in each stone types. Also, correlation analysis for stones consisting of uric acid (n=100) was performed and Spearman’s rank correlation coefficient was calculated. Average and high positive correlations were found between K/Mg, Mg/Na, Mg/P, Mg/Sr, Na/P (r=0.41 ÷ 0.50) and Ca/Sr (r=0.71) respectively.
Assessing the efficiency of using carbon nanocomposite materials for corrosion protection of gas pipelines
Authors: Belov D , Gruchenkova A , Chepur P 
Published: August 2021

Abstract
The use of innovative technologies in the transportation and production of hydrocarbons is one of priority tasks. In the context of competition for energy, this issue is brought to the fore in the development of areas for the modernization of the industry. In addition, it is a matter of strengthening the country’s competitive advantage in the world market of fuel and energy carriers. The study is dedicated to finding ways to improve the composition of anticorrosive coatings used in the gas industry. The paper studies the physical and mechanical characteristics of the main anticorrosive coatings. Carbon nanotubes were found to be the most profitable and economically viable. The composite material with new nanotubes was studied by comparing the physical and mechanical properties of various anticorrosive coatings in the framework of the experiment. The results of the experiment confirmed the feasibility of using nanotechnological materials and coatings. So, the use of carbon nanocomposites in the composition of anticorrosive coatings will increase the efficiency of transportation of gas, oil, and other raw materials.
Research of light diffraction on multilayer inhomogeneous holographic PPM diffraction structures formed under PIA conditions
Authors: Dolgirev V O , Sharangovich S N 
Published: August 2021

Abstract
This work presents a research of the diffraction of light on the multilayer inhomogeneous holographic diffraction structures (MIHDS) in a photopolymer material (PPM) under photoinduced light absorption (PIA) conditions. Considering PIA, the authors showed possible distortions of the selective response of the diffracted beam due to the heterogeneity of the profiles of lattices over the depth of the layer.
Rapid direct electric heating of fresh concrete
Authors: Batyuk M I , Gnyrya A I , Ushakov V Ya , Korobkov S V 
Published: August 2021

Abstract
Direct electric curing as a volume-heating method can provide fairly uniform temperature field at high heating rates. However, most of the current research focuses on reproduction of general form of temperature curve used in conventional techniques, i.e. at low heating rates. This paper evaluates the effect of rapid direct electric heating of fresh concrete on temperature variation, compressive strength and energy consumption. Samples subjected to rapid electric heating to 50, 60 and 70°C in 10 minutes were insulated, kept for 13 hours, demolded and tested for compressive strength. According to measurements in three points saved every 30 seconds, the temperature field remains uniformly over the cycle. The ratio of energy consumption and the resulting strength allows to select the most optimal mode for a particular case. It has been determined that an increase in temperature of 10 °C leads to an increase in strength by 4% (for the considered composition). Results derived from this study confirm the effectiveness of applying rapid electric heating of fresh concrete for precast concrete production.
Forecast of the near ground air temperature based on the multilayer perceptron model
Authors: Del I V , Starchenko A V 
Published: August 2021

Abstract
In this study, a multilayer perceptron model is implemented for predicting meteorological values. Based on the known distribution of meteorological values for several previous days, the task was set to predict the values of the near ground air temperature. The overall mean square error for the entire forecast was 3.11 C. Comparison of various optimization methods showed the advantage of the method of Adaptive Moment Estimation. Comparison of the multilayer perceptron model forecasting results with the Weather Research and Forecasting numerical model forecast showed the promise of using neural networks to predict meteorological parameters at weather observation points.
Application of a Weather Research and Forecasting model to study the urban heat island in Tomsk
Authors: Svarovsky A I , Starchenko A V 
Published: August 2021

Abstract
The results of application of a Weather Research and Forecasting model (version 4.2) to study the heat island phenomenon in the city of Tomsk are considered. The results of numerical calculations were compared with measurements obtained using the instruments of Joint Use Center (JUC) Atmosphere and Tomsk Bogashevo Airport. On some days, the temperature difference between the city and the suburbs was shown to reach 1-3 °C.
Transition metals in the process of complexation with organic ligands containing heteroatoms in the structure
Authors: Marakina E I , Andrienko O S , Sachkov V I , Medvedev R , Amelichkin I , Shcherbakov P S 
Published: August 2021

Abstract
The synthesis and research of copper subgroup metal complexes with organic ligands, which have several heteroatoms in their structure, is highly perceptive. Since the resulting complex compounds differ in physical and chemical properties from the original organic compounds they will have a set of new characteristics of practical significance. In this study, 2-mercaptonicotinic acid and 2-mercapto-4(3H)-quinazolinone were used. During the research, complex compounds of metals of the copper subgroup were obtained from aqueous and water-alcohol solutions. The resulting compounds represent colored powder-like materials. The coordination of the organic reagent to metal ions was established by instrumental methods of analysis. The effect of the introduced reagent (alkali, ammonia) on the coordination of the organic reagent was investigated.
Friction Stir Processing of Aluminum Alloy 5556 With Different Pin Configuration of Tool
Authors: Sudarikov A V , Chumaevskii A V , Dobrovolsky A R , Zykova A P , Gusarova A V , Gurianov D A , Ivanov A N 
Published: August 2021

Abstract
The paper investigates the features of the friction stir processing of aluminum-magnesium alloy using tools with a screw pin and with a square section pin. The conducted studies show that during the friction stir process with a tool with a square cross-section pins it is possible to form instabilities during treatment, leading to non-uniform longitudinal movement of the tool and formation of defects. One mechanism for this phenomenon could be contamination of the surface of the aluminum-magnesium alloy treating tool after working on aluminum-silicon alloys, resulting in unstable adhesion contact. This effect is less noticeable for treating by tool with a cylindrical pin. Mechanical properties of the treated material in 1-4 passes remain quite close and the average ultimate tensile strength of the stir zone is 325-335 MPa. The plasticity of the material decreases on average from 33% to 25-30%, but remains at an acceptable level. The average ultimate tensile strength and ductility values are slightly higher when processing with a square-shaped pin tool than when processing with a spiral-shaped pin tool.
Friction Stir Processing Regularities of Cast Aluminum Alloy AlSi12
Authors: Indoitu D V , Gusarova A V , Zykova A P , Kalashnikova T A , Chumaevskii A V , Gurianov D A , Beloborodov V A 
Published: August 2021

Abstract
The paper studies the structure and morphology of the treating zone surface of cast aluminum alloy AlSi12 after 1-4 passes with a friction stir tool. The studies show that after all four passes, the surface of the tool exit zone has traces of material tearing out along the edge of the pin, but the overall appearance of the machining surface improves. The structure after four passes with the tool is dominated by smaller and more rounded particles, while after one pass there is a large number of elongated particles. Friction stir processing leads to improvement of material plasticity by up to 2.5 times and ultimate tensile strength value by 9-10%.
Clustering-based rule generation methods for fuzzy classifier using Autonomous Data Partitioning algorithm
Authors: Svetlakov M O , Hodashinsky I A 
Published: August 2021

Abstract
In this paper, clustering-based rule generation methods for fuzzy classifier using non-parametric Autonomous Data Partitioning algorithm have been proposed. ADP-algorithm is used to determine the number of clusters for use in various k-means-like clustering algorithms. Proposed method contributes to solving the problem of determining optimal number of clusters/rules. The efficiency of fuzzy classifiers with rules constructed by the specified algorithms has been tested on data sets from the KEEL repository. Experimental results show that proposed method outperforms baseline algorithm (the extremums rulebase generation algorithm) both in terms of classification accuracy and geometric mean metrics.
Sub-THz absorbers based on BaTiO3/Epoxy composites
Authors: Moskalenko V D , Shematilo T N , Dorozhkin K V , Badin A V 
Published: August 2021

Abstract
The paper presents the results of studying electromagnetic response from polymer composite materials in the frequency range from 0.1 THz to 1.6 THz obtained using a BWO-based spectrometer and a time-domain spectrometer. The composites used were epoxy resin with the addition of barium titanate (BaTiO3) with a mass concentration of 40% to 80%. Based on these data, the values of the complex permittivity of composite samples are calculated and analyzed, and the electromagnetic response from the samples is modeled. An assessment of the applicability of this material in the elements of the THz range technology is carried out.
Temperature distribution in the phantom of limb in the microwave chamber with linear source of radiation
Authors: Nechaev A N , Dunaevskii G E 
Published: August 2021

Abstract
The paper presents results of temperature distribution in the phantom of limb under the microwave radiation. The authors have developed automated apparatus based on linear positioner and temperature detector. The apparatus is aimed at measuring the distribution of thermal field in phantom of a human hand. It was shown that impulse microwave radiation with a power of 40W during 6 minutes leads to uniform heating along longitudinal axis of phantom. The apparatus “SMVi-200” was used as a microwave source being normally applied for hypothermia treatment.
Determination of mercury (II) by precipitation potentiometric titration
Authors: Zakharkiva A M , Shumar S V 
Published: August 2021

Abstract
The article presents the results of potentiometric titration of the solution containing Hg (II) with the solution of sodium diethylditheocarbamate (NaDEDC). The efficiency of electrochemical analysis is defined by the presence of the most appropriate indicator system. The possibility of using carbon composite electrode (CCE) as a sensor for mercury ions determination has been explored. The conditions for potentiometric determination of Hg (II) (titrant, indicating electrode, pH, response time, range of concentrations, and background electrolyte) were studied. Titration curves were processed by the linearization method.
Formation of beam-produced plasma by a forevacuum plasma-cathode source of a pulsed large-radius electron beam
Authors: Kazakov A V , Medovnik A V , Oks E M , Panchenko N A 
Published: August 2021

Abstract
The research of formation of beam-produced plasma by a pulsed low-energy (up to 7 keV) large-radius electron beam, generated by a forevacuum plasma-cathode electron source based on a cathodic arc, is presented. Density of the beam-produced plasma depends nonmonotonically on accelerating voltage. A certain threshold voltage, which depends on the gas pressure and a distance from the extractor of the electron beam source, provides maximal plasma density. At a voltage higher than the threshold voltage, a further increase in the accelerating voltage leads to a decrease in the density of the beam-produced plasma, and the plasma density increases as the distance from the extractor of the electron source increases. These dependencies of plasma density are caused by change in the electron-impact ionization cross sections of gas. Plasma density increases with increasing electron beam current and increasing gas pressure. For the used forevacuum plasma-cathode source of the large-radius electron beam and experimental conditions, varying parameters of the electron beam provides formation of beam-produced plasma with cross-section radius up to 4–5 cm and plasma density up to 1017 – 1018 m-3 at distance from the extractor up to 19 cm.
Influence of vacancy on helium interaction with α-Zirconium
Authors: Svyatkin L A , Terenteva D V , Laptev R S 
Published: August 2021

Abstract
The first-principle calculations of the interaction between helium and zirconium have been carried out. The main feature of studying such systems is the localization of a He atom in a region near the vacancy in Zr. It has shown that the location of a helium atom in a vacancy vicinity leads to lower formation energy. The calculated density of electron states curves revealed shifts of He 1s state by ~ 0.5 eV towards higher binding energies while located the vacancy vicinity against He-in-vacancy position. Moreover, He 2s states are observed in a region of Zr 4d states from –1.2 to –0.1 eV suggest the hybridization between these states. The crystal orbital Hamilton populations curves have been analyzed to reveal the features of the Zr-He chemical interaction due to the hybridization of He 2s and Zr 4d states.
Onboard device for UAS remote identification
Authors: Bragin D S , Urazayev D R , Konev A A , Cherepanova I V 
Published: August 2021

Abstract
The unsupervised use of UAS creates threats to the security of general aviation and ground objects, including objects of critical information infrastructure. Equipping UAS with a remote identification device can be the solution to this problem. It should increase the sense of responsibility among UAS pilots and allow the public, aviators and law enforcement to identify and track UAS and their operators during flight. The goal of the article is the technical requirements specifications of a device for UAS remote identification. The existing technologies of UAS remote identification have been reviewed during this research, and the criteria of their choice have been defined. The result of the work takes into account the territorial features of Russia and the concept of the RUTM system. The authors propose the network model for UAS remote identification using the ADS-B direct broadcast technology to form the aircraft pilots’ situational awareness of the air situation near the vessel. ADS-B 1090 ES, cellular and satellite communications have been chosen as data transmission channels for the onboard UAS remote identification device. Based on this, the technical requirements have been developed for the onboard device for UAS remote identification.
Power Energy Supply and Demand Scheduling Method Based on Blockchain Technology
Authors: Li Wei , Wang Lixia , Wang Dawei 
Published: August 2021

Abstract
In order to solve the problem of a large difference between the dispatching operation power and the actual required operation power existing in the traditional power energy dispatching, which affects the dispatching efficiency and causes serious energy waste, the design of power energy supply and demand scheduling method based on blockchain technology is carried out. Based on the power energy supply and demand scheduling hierarchy, based on the supply and demand scheduling model of the blockchain technology architecture, the distributed consensus mechanism for the supply and demand scheduling of power energy is established, and a new power supply and demand scheduling method is proposed. Through the experiment, it is proved that compared with the traditional dispatching method, the dispatching power obtained by the new dispatching method can be close to the actual dispatching power on the basis of meeting the normal operation needs of each equipment, realizing the energy saving of electric power, and providing technical support for the construction of green power grid.
English billboard text recognition using deep learning
Authors: Yu Enbo , Zhang Zitong 
Published: August 2021

Abstract
English billboards are common in our daily work and life, and how to effectively recognize them is a problem worthy of study. This paper mainly uses Progressive Scale Expansion Network (PSENet) and Convolutional Recurrent Neural Network (CRNN) to conduct text recognition experiments on English billboards. The English billboards are divided into four categories: text distortion, larger background, special text font, and normal format. PSENet is used for text detection, and CRNN is used for text recognition. The identification results of PSENet and CRNN revealed differences among the four groups of English billboards: normal format text recognition is the best, and large background text recognition is the worst, and the recognition effect of text distortion and special text font is less accurate. Finally, the work of this paper is analyzed and summarized, and the future work is prospected.
Feature-Enhanced Data Classification Using B-center Function
Authors: Li Enyu , Lyu Leyu , Mao Wenfei 
Published: August 2021

Abstract
Linear-kernel Support Vector Machine (SVM) classification algorithm needs to constantly calculate the similarity between the data to be tested and the sample during classification. If samples in the dataset are linearly indivisible, the accuracy of the algorithm will get worse. The feature weight calculation based on category information in Multi-layer Perceptron (MLP) algorithm is not accurate enough to express the relationship between features and categories, i.e. it cannot distinguish categories precisely when the features with the same category frequency. In order to improve the performance of MLP and linear-kernel SVM algorithms in classification, an improved function: the Base function, which is based on clustering, is proposed in this paper. Before running the classification algorithm, a series of possible centers is predicted, after which the Base function is used for data clustering to increase the dimension of data, and then samples with more features are passed to classification models. In the high-position Gaussian data space, the Base function can obviously improve the spatial distribution of samples. Experimental comparison in the thesis also proved that the Base function can improve the performance of MLP or SVM in classification effectively. The proposed feature-enhanced MLP is superior to the baseline with 32.6% accuracy promotion on the Gaussian dataset.
An End-to-End Deep Learning Approach for Diagnosis of Parkinson’s Disease Based on Hand Drawing
Authors: Wang Yifan , Zhang Yifan 
Published: August 2021

Abstract
At present, Parkinson’s disease is mainly subject to the doctor’s subjective assessment of the patient’s symptoms through the unified Parkinson’s disease score scale, which easily leads to a high rate of misdiagnosis. Some wearable devices have been developed to assist in providing accurate diagnostic results. However, this process requires the cooperation of patients and doctors, which is very inconvenient for Parkinson’s patients who have limited mobility. According to reports, Parkinson’s patients will show some writing disabilities in the early stages. Therefore, to provide a non-invasive and convenient diagnosis program, this research is devoted to developing a Parkinson’s disease diagnosis program based on hand-drawn data. This search provides diagnostic solutions for Convolutional Neural Network (CNN) and Residual Neural Network (ResNet). Unlike the traditional hand drawing preprocessing scheme that only retains the trajectory, the color information of the image for the hand drawing was reserved, which allows the subsequent model to learn the stroke pressure, speed, stroke time, and other based on the color information. Compared with CNN, the ResNet can better solve the semantic gap problem, achieve faster convergence speed, and get higher diagnostic accuracy (accuracy = 88.9%). In general, the two diagnostic schemes proposed in this study only require the patient to provide a hand drawing to confirm whether the patient has Parkinson’s disease, which is of great significance for the convenient diagnosis of Parkinson’s disease.
Unsupervised feature learning for data classification
Authors: An Shixuan , Lu Ruicheng , Zhang Tianyi 
Published: August 2021

Abstract
Data classification is a critical task for data analysis. However, recent methods aim to model this task as a classification or regression task, which needs ground truth for discriminative representation learning. This paper aims to learn a more efficient and effective feature for data analysis in an unsupervised learning manner. Our method consists of two main components: a customized autoencoder network (C-AENet) and a customized squeeze-and-excitation network (C-SENet). The C-AENet aims to reconstruct the feature using the fewer dimension, and C-SENet is to improve the representation by providing channel attention. Experiment on the Avila dataset shows that both modules are effective in data classification with fewer feature dimension.