bluuebunny/crossref_metadata_2025_split huggingface dataset:
ANALYSIS OF METHODS FOR AUTOMATED RESEARCH OF DC VOLTAGE CONVERTERS OF MODULAR STRUCTURE
Authors: Kharchenko R. Yu. , Kochetkov A. V. , Mikhaylenko V. S. 
Published: October 2022

Context. DC voltage converters (DCV) are part of modern power supply systems (PSS) and power supply ensuring the operation of electronic and radio devices, telecommunication systems and communication and to a large extent determine their power consumption, reliability, time of readiness for operation, weight, size and cost indicators. Even though there are a large number of different software packages used in engineering practice for the study and design of radio engineering devices, such computer-aided design (CAD) systems and virtual computer simulation of electronic circuits have some limitations that do not allow to quickly carry out the entire complex of studies of DCV required for the analysis of electrical processes in various operating modes.
Objective. In this section, the goal is to select the most suitable methods and algorithms that allow the development of software necessary for solving the problems of research and analysis of electrical processes for select energy parameters of the DCV of a modular structure in a separate power channel (PWC).
Method. The paper proposes a method that consists in using mathematical models describing electrical processes in DC voltage converters and creating, on the basis of the developed calculation algorithms, specialized software for the automated study of electrical processes in the DCV of a modular structure using a computer.
Results. The paper discusses the main methods of automated research of radio engineering devices, which can be used to analyze the electrical processes of pulsed DC voltage converters of a modular structure. Algorithms of calculation are given and, as an example, some results of automated research obtained using this method.
Conclusions. The analysis of the known methods of automated research of DC voltage converters of modular structure is carried out. Their advantages and disadvantages are given. It is shown that the most suitable method is based on the use of mathematical models describing electrical processes in DC voltage converters of this type. On the basis of the mathematical models presented in the second section of the work, algorithms and specialized software have been developed that allow them to be widely used in the automated research and design of modular-structured DC voltage converters.
MATHEMATICAL MODEL FOR DECISION MAKING SYSTEM BASED ON THREE-SEGMENTED LINEAR REGRESSION
Authors: Kuzmin V. M. , Khrashchevskyi R. V. , Kulik M. S. , Ivanets O. B. , Zaliskyi M. Yu. , Petrova Yu. V. 
Published: October 2022

Context. The problem of approximation of empirical data in the decision-making system in safety management.. The object of the study was to verify the adequate coefficients of the mathematical model for data approximation using information technology.
Objective. The goal of the work is the creation adequate math-ematical model using information technology on the bases analyze different approaches for approximating empirical data an that can be used to predict the current state of the operator in the flight safety system..
Method. A comparative analysis of the description of the transformation of information indicators with a non-standard structure. The following models of transformation of information indicators with similar visual representation are selected for comparison: parabolas of the second and third order, single regression and regression with jumps. It is proposed to use new approaches for approximation, based on the use of the criterion proposed by Kuzmin and the Heaviside function. The adequacy of the approximation was checked using these criteria, which allowed to choose an adequate mathematical model to describe the transformation of information indicators. The stages of obtaining a mathematical model were as follows: determining the minimum sum of squares of deviations for all information indicators simultaneously; use of the Heaviside function; optimization of the abscissa axis in certain areas; use of the linearity test. The obtained mathematical model adequately describes the process of transformation of information indicators, which will allow the process of forecasting changes in medical and biological indicators of operators in the performance of professional duties in aviation, as one of the methods of determining the human factor in a proactive approach in flight safety.
Results. The results of the study can be used during the construction of mathematical models to describe empirical data of this kind.
Conclusions. Experimental studies have suggested recommending the use of three-segment linear regression with jumps as an adequate mathematical model that can be used to formalize the description of empirical data with non-standard structure and can be used in practice to build models for predicting operator dysfunction as one of the causes of adverse events in aviation.
Prospects for further research may be the creation of a multiparameter mathematical model that will predict the violation of the functional state of the operator by informative parameters, as well as experimental study of proposed mathematical approaches for a wide range of practical problems of different nature and dimension.
OUTLIER DETECTION TECHNIQUE FOR HETEROGENEOUS DATA USING TRIMMED-MEAN ROBUST ESTIMATORS
Authors: Shved A. V. , Davydenko Ye. O. 
Published: October 2022

Context. Fortunately, the most commonly used in parametric statistics assumptions such as such as normality, linearity, independence, are not always fulfilled in real practice. The main reason for this is the appearance of observations in data samples that differ from the bulk of the data, as a result of which the sample becomes heterogeneous. The application in such conditions of generally accepted estimation procedures, for example, the sample mean, entails the bias increasing and the effectiveness decreasing of the estimates obtained. This, in turn, raises the problem of finding possible solutions to the problem of processing data sets that include outliers, especially in small samples. The object of the study is the process of detecting and excluding anomalous objects from the heterogeneous data sets.
Objective. The goal of the work is to develop a procedure for anomaly detection in heterogeneous data sets, and the rationale for using a number of trimmed-mean robust estimators as a statistical measure of the location parameter of distorted parametric distribution models.
Method. The problems of analysis (processing) of heterogeneous data containing outliers, sharply distinguished, suspicious observations are considered. The possibilities of using robust estimation methods for processing heterogeneous data have been analyzed. A procedure for identification and extraction of outliers caused by measurement errors, hidden equipment defects, experimental conditions, etc. has been proposed. The proposed approach is based on the procedure of symmetric and asymmetric truncation of the ranked set obtained from the initial sample of measurement data, based on the methods of robust statistics. For a reasonable choice of the value of the truncation coefficient, it is proposed to use adaptive robust procedures. Observations that fell into the zone of smallest and lowest ordinal statistics are considered outliers.
Results. The proposed approach allows, in contrast to the traditional criteria for identifying outlying observations, such as the Smirnov (Grubbs) criterion, the Dixon criterion, etc., to split the analyzed set of data into a homogeneous component and identify the set of outlying observations, assuming that their share in the total set of analyzed data is unknown.
Conclusions. The article proposes the use of robust statistics methods for the formation of supposed zones containing homogeneous and outlying observations in the ranked set, built on the basis of the initial sample of the analyzed data. It is proposed to use a complex of adaptive robust procedures to establish the expected truncation levels that form the zones of outlying observations in the region of the lowest and smallest order statistics of the ranked dataset. The final level of truncation of the ranked dataset is refined on the basis of existing criteria that allow checking the boundary observations (minimum and maximum) for outliers.
CREDIBILISTIC FUZZY CLUSTERING BASED ON ANALYSIS OF DATA DISTRIBUTION DENSITY AND THEIR PEAKS
Authors: Bodyanskiy Ye. V. , Pliss I. P. , Shafronenko A. Yu. , Kalynychenko O. V. 
Published: October 2022

Context. The task of clustering – classification without a teacher of data arrays occupies a rather important place in Data Mining. To solve this problem, many approaches have been proposed at the moment, differing from each other in a priori assumptions in the studied and analyzed arrays, in the mathematical apparatus that is the basis of certain methods. The solution of clustering problems is complicated by the large dimension of the vectors of the analyzed observations, their distortion of various types.
Objective. The purpose of the work is to introduce a fuzzy clustering procedure that combines the advantages of methods based on the analysis of data distribution densities and their peaks, which are characterized by high speed and can work effectively in conditions of classes that overlapping.
Method. The method of fuzzy clustering of data arrays, based on the ideas of analyzing the distribution densities of these data, their peaks, and a confidence fuzzy approach has been introduced. The advantage of the proposed approach is to reduce the time for solving optimization problems related to finding attractors of density functions, since the number of calls to the optimization block is determined not by the volume of the analyzed array, but by the number of density peaks of the same array.
Results. The method is quite simple in numerical implementation and is not critical to the choice of the optimization procedure. The experimental results confirm the effectiveness of the proposed approach in clustering problems under the condition of cluster intersection and allow us to recommend the proposed method for practical use in solving problems of automatic clustering of large data volumes.
Conclusions. The method is quite simple in numerical implementation and is not critical to the choice of the optimization procedure. The advantage of the proposed approach is to reduce the time for solving optimization problems related to finding attractors of density functions, since the number of calls to the optimization block is determined not by the volume of the analyzed array, but by the number of density peaks of the same array. The method is quite simple in numerical implementation and is not critical to the choice of the optimization procedure. The experimental results confirm the effectiveness of the proposed approach in clustering problems under conditions of overlapping clusters.
Projeto de desenvolvimento moral para a prevenção das situações de incivilidade entre adolescentes em sala de aula online
Authors: Leal Flávia Daniela Bosi , Sousa Raphael Campagnaro Baptista de 
Published: October 2022

O presente texto aborda a importância de se desenvolver projetos de intervenção em ambiente escolar para a formação moral e ética do estudante adolescente, sobretudo quando em ambiente remoto. Destacamos que é papel do professor estimular seu aluno adolescente a repensar as atitudes tomadas entre os pares e também com professores, tendo em vista as sutilidades que o ensino on-line proporciona. Temos como hipótese que é possível promover a conscientização do estudante a respeito de suas atitudes e estabelecer um ambiente propício ao desenvolvimento moral e intelectual através da interação mediada pelo professor, em sala de aula virtual e destacamos os projetos de desenvolvimento moral como meio para isso.O arcabouço teórico adotado compreende: estudos sobre escola, democracia e construção de personalidades morais de ARAÚJO (2000); Formação Ética de LA TAILLE (2009); Temas Transversais de MORENO (1997); O Juízo Moral da Criança de PIAGET (1994); Pensamento e Linguagem de VIGOTSKY (1998) e a abordagem sobre o vigiar e o punir de FOUCAULT (2014), dentre outras. Salientamos que esta pesquisa é financiada pela Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
Cidoncha Redondo, Francisco, El concubinato y el contubernio en la sociedad romana (siglos I a.C.-III d. C.), Editorial Universidad de Sevilla, Sevilla, 2021, 358 pp
Authors: Valmaña Alicia 
Published: October 2022

Recensión al libro Cidoncha Redondo, Francisco, El concubinato y el contubernio en la sociedad romana (siglos I a.C.-III d. C.), Editorial Universidad de Sevilla, Sevilla, 2021, 358 pp
Comparison of Serum Levels of Adiponectin and Cortisol between Overweight/Obese and Normal Weight Men
Authors: Nezhadali Masoumeh 
Published: October 2022

Introduction: Obesity, results in a number of serious complications, such as type 2 diabetes, non-alcoholic fatty liver disease and metabolic syndrome. The levels of blood of adiponectin and cortisol have been associated with obesity. This study aimed to investigate the relationship of adiponectin and cortisol levels with obesity and biochemical parameters.
Methods: This case-control study was conducted only on men, 80 participants with body mass index (BMI)≥25 considered as case group, and 100 participants with BMI<25 as control group in the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences. Plasma levels of adiponectin and cortisol were measured through ELISA kit and other variables were determined by standard methods. Data were analyzed using SPSS software version 16. P-values <0.05 were considered as significant.
Results: Our findings showed no significant difference in cortisol level between individuals with BMI≥25 and individuals with BMI<25. Obese men had significantly higher levels of triglycerides, systolic and diastolic blood pressure and lipid profiles whereas, adiponectin and high-density lipoprotein-cholesterol (HDL-C) levels were lower compared to the control group (p-value<0.05). In this study, an inverse correlation was observed between adiponectin and fasting blood glucose (FBS), and also BMI. It was found a positive correlation between cortisol and cholesterol and also FBS.
Conclusion: The results show that there is no relationship between cortisol and obesity, but a negative correlation between adiponectin levels and obesity.
OXIDACIÓN BIOCATALÍTICA DE CONTAMINANTES AROMÁTICOS POR LA PEROXIDASA PROVENIENTE DE LA SOYA
Authors: Hernández Hernández María Ixel , Romero Guido Cynthia , Torres Ramírez Eduardo 
Published: October 2022

El presente artículo describe el desempeño biocatalítico de la enzima peroxidasa de la soya para oxidar contaminantes acuosos del tipo aromáticos como plaguicidas organofosforados, hidrocarburos policíclicos aromáticos (HPAs), y flavonoides provenientes de residuos agroindustriales. Los ensayos se realizaron en muestras modelo y también en muestras simuladas de efluentes contaminados. El análisis se realizó por cromatografía de líquidos de alta resolución (HPLC) y por espectrofotometría UV-vis. Las conversiones alcanzadas fueron para los plaguicidas terbufos (14%) y dimetoato (30% de conversión); para los HPAs como azuleno (32%), 9-metil antraceno (22%); antraceno y pireno (29% cada uno), y carbazol (18%); y los flavonoides como ácido ferúlico (99%), quercetina (98%), rutina (50%) y naringina (10%). Se estudió el efecto del cambio de pH y de temperatura en la actividad de la enzima, siendo activa desde un pH de 3 hasta 6, y desde los 25 ˚C hasta los 80 ˚C. Lo anterior permite concluir que la peroxidasa de soya es un buen candidato para estudios más completos para su posible aplicación en la descontaminación de efluentes que contienen contaminantes aromáticos.
Cross-Well Reflection Imaging at the Verkhnekamskoe Potash Deposit
Authors: Chugaev A.V. , Sanfirov I.A. , Tarantin M.V. 
Published: October 2022

Abstract
—We propose the technique of extended processing of cross-well seismic data for reflection imaging. Based on the analysis of the wave field and synthetic modeling, a graph for processing cross-well data is developed to separate the reflections in the presence of a boundary of a sharp change in the velocity of elastic waves. The migration of the reflected waves from the time scale to the depth is performed by solving a forward problem for each source–receiver pair. As a result, the position of the reflection points is calculated, after which all the traces are stacked based on the binning grid. The input information for performing migration and solving a forward problem is the velocity characteristic of the massif, which is calculated using traveltime tomography on direct body waves obtained from the same data set of cross-well survey and vertical seismic profiling. The resulting depth seismic section has a much higher resolution than that of vertical seismic profiling and ground-based shallow seismic studies. This opens up the opportunity of identifying different small natural or technogenic objects in the interwell space.
Study on the effect of oil supply on the friction state of the micro-texture surface of sliding guide
Authors: Yu jiefan , Li bin , Xia jing , Su yu , Liu fanghua , Chu zepeng 
Published: October 2022

Abstract
To investigate the law and mechanism of the effect of oil supply (initial oil film thickness) on the friction state of the micro-texture surface of the sliding guide. The friction and wear experiment of pin-slider surface contact is carried out to study the influence law of initial oil film thickness on friction coefficient, contact surface temperature, and lubrication state at different velocities. This experiment reveals the wear mechanism of the micro-texture surface under different initial oil film thickness, and establishes the lubrication state control model of the micro-texture surface. The results show that the velocity and initial oil film thickness have a more significant effect on the friction properties of the micro-texture surface. When the velocity is less than 0.06 m/s, the contact surface has been in the semi-dry friction state with the initial oil film thickness increases, the COF decreases by up to 13.32%, and the micro-textured surface produces abrasive wear, adhesive wear, and fatigue wear. When the velocity is more significant than 0.06 m/s, as the initial oil film thickness increases, the contact surface transits from the semi-dry friction state to the boundary lubrication state, and the COF decreases by up to 44.96%. When the velocity increases to 0.18 m/s and the initial oil film thickness is more significant than 19.8 µm, the micro-texture has a hydrodynamic pressure effect and the contact surface in the mixed lubrication state. The wear surface of the micro-texture has only slight abrasive wear, and the COF decreases by 64.07% at the highest. The study lays the theoretical foundation for the control of the lubrication state of the sliding guide surface to improve the sliding guide motion accuracy and service life.
The relationship between honesty-credit, specialty identity, career Identity and performance intention among rural-Oriented tuition-waived medical students of China in the context of COVID-19: a cross-sectional study
Authors: Zhang Xuewen , Sun Bing , Tian Zhuang , Yu Bin , Wei Chao , Zhang Ying , Zheng Canlei , Chen Xuejun , Liu Qing 
Published: October 2022

Abstract
Background: Whether the rural-oriented tuition-waived medical students fulfil the contract to work in rural medical institutions after graduation is directly related to the improvement of rural health quality. This study not only quantitatively measured the direct impact of honesty-credit, specialty identity, career identity on RTMSs' performance intention, but also quantifies the intermediary role of specialty identity and career identity between honesty-credit and performance intention. The research results provide recommendations for the RTME program to achieve its goal of training rural primary health care personnel.
Methods: From March to May 2022, a total of 1162 RTMSs were selected as the research objects, honesty-credit, specialty identity, career identity and performance intention were quantitated by self-completed questionnaire. Person correlation analysis and Structural Equation Modelling (SEM) were used for statistical analysis and mediating effect evaluation.
Results: 455 (42.3%) of RTMSs had high performance intention, and honesty-credit had a significant direct positive effect on performance intention (β=0.198, p<0.001), specialty identity (β=0.653, p<0.001) and career identity (β=0.180, p<0.001). Specialty identity has a direct positive effect on career identity (β=0.777, p<0.001), and the latter also has a direct positive effect on performance intention (β=0.321, p<0.001). In the intermediary path between honesty-credit and performance intention, career identity 95%CI:( 0.007)– (0.051) had significant mediating effects. Career Identity 95%CI:( 0.030)– (0.149) also had significant mediating effects between specialty identity and performance intention, and specialty identity had significant mediating effects between honesty-credit and career Identity, 95%CI:( 0.465)– (0.760). These results strongly confirm that honesty-credit, specialty identity, career identity are early and powerful predicators of RTMSs' performance intention.
Conclusion: Medical universities need to strengthen the sense of honesty-credit and performance of RTMSs, and make clear their important contribution and significance of their role to the country, society, and realize the national expectation and individual win-win development.
The Global Climate-Change-Attributed Costs of Extreme Weather
Authors: Newman Rebecca , Noy Ilan 
Published: October 2022

Abstract
Extreme weather events have significant adverse costs for individuals, firms, communities, regional, and national economies. Extreme Event Attribution (EEA), a methodology that examines the degree to which anthropogenic greenhouse gas emissions had changed the occurrence of specific extreme weather events, allows us to quantify the climate-change-induced component of these costs. We use EEA to aggregate the global economic damage from extreme weather events that is attributable to anthropogenic climate change. For that, we collect data from all available attribution studies which estimate the Fraction of Attributable Risk (FAR) for extreme events, and combine these FAR estimates with data on the socio-economic costs of these events. With extrapolation for missing data, we then arrive at our benchmark estimates. We find that US$ 143 billion per year, of the costs of extreme events during the last twenty years, is attributable to anthropogenic climatic change. This EEA-based method for calculating the costs of climate change from extreme weather differs fundamentally from other approaches to climate cost estimation. Those other approaches use macroeconomic modelling embedded within climate models in various types of Integrated Assessment Models (IAM). As we show, our research is not directly comparable, but it does provide a new form of evidence that suggests that most IAMs are substantially under-estimating the current economic costs of climate change. Given some of the data deficiencies we identify in terms of temporal and spatial coverage, the purpose here is not to produce a definitive quantification, but rather to sketch a path towards a more comprehensive and reliable estimation. As better EEA studies and more thorough and exhaustive economic costs estimates for extreme events become available over time, and the method is refined, the precision of this approach's estimates will increase in tandem.