bluuebunny/crossref_metadata_2025_split huggingface dataset:
An analysis of how business owners use Valencian and Spanish in
the linguistic landscape
Authors: Martínez Ibarra Francisco 
Published: February 2021

Abstract
The study of the Linguistic Landscape provides
opportunities to ethnolinguistically depict a community. It also
allows for deciphering communication patterns among users and
understand societal perceptions of language use. This paper examines
the contact between Spanish and a western variety of Catalan (i.e.
Valencian) on the linguistic landscape produced by private business
owners in Elche, Spain. An analysis of data collected through
observation, personal interviews and written questionnaires suggests
the reader and potential customer appears to be the main driving
force behind language choice in the linguistic landscape of
Elche.
Cooling during short‐term heat acclimation enhances aerobic capacity but not sweat capacity
Authors: Naito Takashi , Haramura Miki , Muraishi Koji , Yamazaki Misa , Takahashi Hideyuki 
Published: February 2021

ABSTRACTTo characterize the adaptive responses to short‐term heat acclimation (HA) training with repeated‐sprint exercises and to determine the effects of ice slurry ingestion during HA on aerobic capacity and adaptations. Seven physically active males completed two 5 consecutive day interventions in a randomized cross‐over design. Participants performed approximately 80‐min intermittent repeated‐sprints using a cycling ergometer including break‐time and half time in 36.5°C and 50%RH. Participants ingested either 1.25 g·kg body mass−1 of ice slurry (ICE: −1°C) or room temperature beverage (NOC: 36.5°C) throughout each break and 7.5 g·kg body mass−1 of the same drink during half time. Maximum oxygen uptake ( O2max) test in hot conditions was completed before and after HA training. Ice slurry ingestion during short‐term HA training induced significantly higher both O2max and watt at O2max following HA training. Total work done was significantly higher in HA with ICE than for the NOC trial on both day 1 and day 5. Sweating Na+ concentration in NOC trial at day 5 were significantly lower than those in the NOC trial day 1, but was not observed in ICE trial. Cooling during HA training may be an effective strategy for enhancement of aerobic capacity via the adaptations gained from a higher quantity of exercise caused by cooling, but does not improve heat loss capacity.Highlights
There is the potential dilemma whether cooling during short‐term training in the heat might negatively impacts the process of helping athletes adapt to hot environments.
Cooling during short‐term heat training may be an effective strategy to enhancement of aerobic capacity via the adaptations gained from a higher quantity of exercise caused by cooling, but does not improve heat loss capacity.
The study suggests the importance to selecting cooling during the heat acclimation phase of consecutive field training according to the individual's training plan.
Time-dependent diffusive interactions between dark matter and dark energy in the context of k-essence cosmology
Authors: Bandyopadhyay Abhijit , Chatterjee Anirban 
Published: February 2021

Abstract
We investigated the scenario of time-dependent diffusive interaction between dark matter and dark energy and showed that such a model can be accommodated within the observations of luminosity distance-redshift data in Supernova Ia (SN Ia) observations. We obtain constraints on different relevant parameters of this model from the observational data. We consider a homogeneous scalar field ϕ(t) driven by a k-essence Lagrangian of the form L = V(ϕ)F(X) with constant potential V(ϕ) = V, to describe the dynamics of dark energy in this model. Using the temporal behaviour of the FRW scale factor, the equation of state and total energy density of the dark fluid, extracted from the analysis of SN Ia (JLA) data, we have obtained the time-dependence of the k-essence scalar field and also reconstructed the form of the function F(X) in the k-essence Lagrangian.
Search for age pattern across spiral arms of the Milky Way
Authors: He Zhi-Hong , Xu Ye , Hou Li-Gang 
Published: February 2021

Abstract
The age pattern across spiral arms is one of the key observational features utilised to study the dynamic nature of the Galaxy’s spiral structure. With the most updated samples of high-mass star formation region (HMSFR) masers, O stars and open clusters, we investigated their distributions and kinematic properties in the vicinity of the Sun. We found that the Sagittarius-Carina Arm traced by HMSFRs, O stars (≲ 10 Myr) and young open clusters (<30 Myr) seem to deviate gradually towards the Galactic Anticenter (GAC) direction. The Local Arm traced by HMSFRs, O stars, young clusters and also medium-young clusters (30–100 Myr) are inclined to gradually deviate toward the Galactic Center (GC) direction. The properties for the Local Arm are supported by a simplified simulation of cluster motions in the Galaxy. Indications of systematic motions in the circular and radial velocities are noticed for the old open clusters (>200 Myr). These results are consistent with the idea that star formation can be triggered by spiral shocks of density waves, and indicate that the corotation radius of the Galaxy is located between the Sagittarius-Carina Arm and the Local Arm, close to the Solar circle.
Towards engineering in memristors for emerging memory and neuromorphic computing: A review
Authors: Sokolov Andrey S. , Abbas Haider , Abbas Yawar , Choi Changhwan 
Published: February 2021

Abstract
Resistive random-access memory (RRAM), also known as memristors, having a very simple device structure with two terminals, fulfill almost all of the fundamental requirements of volatile memory, nonvolatile memory, and neuromorphic characteristics. Its memory and neuromorphic behaviors are currently being explored in relation to a range of materials, such as biological materials, perovskites, 2D materials, and transition metal oxides. In this review, we discuss the different electrical behaviors exhibited by RRAM devices based on these materials by briefly explaining their corresponding switching mechanisms. We then discuss emergent memory technologies using memristors, together with its potential neuromorphic applications, by elucidating the different material engineering techniques used during device fabrication to improve the memory and neuromorphic performance of devices, in areas such as I
ON/I
OFF ratio, endurance, spike time-dependent plasticity (STDP), and paired-pulse facilitation (PPF), among others. The emulation of essential biological synaptic functions realized in various switching materials, including inorganic metal oxides and new organic materials, as well as diverse device structures such as single-layer and multilayer hetero-structured devices, and crossbar arrays, is analyzed in detail. Finally, we discuss current challenges and future prospects for the development of inorganic and new materials-based memristors.
A revew of in situ transmission electron microscopy study on the switching mechanism and packaging reliability in non-volatile memory
Authors: Yang Xin , Luo Chen , Tian Xiyue , Liang Fang , Xia Yin , Chen Xinqian , Wang Chaolun , Liang Steve Xin , Wu Xing , Chu Junhao 
Published: February 2021

Abstract
Non-volatile memory (NVM) devices with non-volatility and low power consumption properties are important in the data storage field. The switching mechanism and packaging reliability issues in NVMs are of great research interest. The switching process in NVM devices accompanied by the evolution of microstructure and composition is fast and subtle. Transmission electron microscopy (TEM) with high spatial resolution and versatile external fields is widely used in analyzing the evolution of morphology, structures and chemical compositions at atomic scale. The various external stimuli, such as thermal, electrical, mechanical, optical and magnetic fields, provide a platform to probe and engineer NVM devices inside TEM in real-time. Such advanced technologies make it possible for an in situ and interactive manipulation of NVM devices without sacrificing the resolution. This technology facilitates the exploration of the intrinsic structure-switching mechanism of NVMs and the reliability issues in the memory package. In this review, the evolution of the functional layers in NVM devices characterized by the advanced in situ TEM technology is introduced, with intermetallic compounds forming and degradation process investigated. The principles and challenges of TEM technology on NVM device study are also discussed.
Neutron irradiation-induced effects on the reliability performance of electrochemical metallization memory devices
Authors: Tao Ye , Li Xuhong , Wang Zhongqiang , Li Gang , Xu Haiyang , Zhao Xiaoning , Lin Ya , Liu Yichun 
Published: February 2021

Abstract
In this work, electrochemical metallization memory (ECM) devices with an Ag/AgInSbTe (AIST)/amorphous carbon (a-C)/Pt structure were irradiated with 14 MeV neutrons. The switching reliability performance before and after neutron irradiation was compared and analyzed in detail. The results show that the irradiated memory cells functioned properly, and the initial resistance, the resistance at the low-resistance state (LRS), the RESET voltage and the data retention performance showed little degradation even when the total neutron fluence was as high as 2.5 × 1011 n/cm2. Other switching characteristics such as the forming voltage, the resistance at the high-resistance state (HRS), and the SET voltage were also studied, all of which merely showed a slight parameter drift. Irradiation-induced Ag ions doping of the a-C layer is proposed to explain the damaging effects of neutron irradiation. The excellent hard characteristics of these Ag/AIST/a-C/Pt-based ECM devices suggest potential beneficial applications in the aerospace and nuclear industries.
Methodological foundations of scaling in modern Measurement Theory. Classification of measurement scales and their application under uncertainty based on Bayesian Intelligent Technologies
Authors: Prokopchina S V 
Published: February 2021

Abstract
Measurement theory is currently being actively developed due to its relevance in modern information technologies that implement the principles and algorithms of DATA SCIENCE, BIG DATA, Internet of Things, Business Intelligence, and DATA MINING. One of the most important applications of measurement theory methods and tools is implemented in artificial intelligence technologies. This is due to the need to use a variety of measurement data in these technologies. The conditions for obtaining such measurement information are associated with uncertainty, which necessitates the use of special methods and tools for obtaining measurement data. This, in turn, determines the need to develop and apply new types of scales focused on uncertainty conditions. The article offers a classification of measurement scales for the implementation of classical and intelligent measurement algorithms. The principles of implementing scales with dynamic constraints for measurement intellectualization based on Bayesian intelligent technologies are considered. Examples of using smart measurement scales are given.
Metrological parameters of information and measurement systems for the study of a kinematic portrait of a person
Authors: Romantsova N V , Suloeva E S , Tsareva A V 
Published: February 2021

Abstract
When developing measurement procedures and means, it is necessary to carry out an analytical description of errors and their characteristics. The report discusses the methods of metrological analysis when creating a portable information and measurement system for evaluating walking techniques. The paper describes the metrological analysis of estimates of total error components of the measurement results of informative parameters for the task.
Hybrid intelligent system of rules extraction for decision making
Authors: Averkin A N , Yarushev S A 
Published: February 2021

Abstract
This article attempts to give an overview of several algorithms for extracting rules from an artificial neural network. The goal of this article is to find critical links three important parts of artificial intelligence – production models, fuzzy logic and deep learning. Such an approach will stimulate researchers in the field of soft computing to develop applied systems in the field of explanational artificial intelligence and machine learning.
Application of the fractional-order model in the problems of identification and order reduction for the controlled processes
Authors: Ayazyan G K , Tausheva E V 
Published: February 2021

Abstract
In the paper, the problems of an identification and order reduction of the dynamics models of controlled processes are solved by applying of fractional-order transfer functions of the form an aperiodic (non-oscillatory) system of the nth order with time delay, and an aperiodic system of the nth order with an integrator and delay, where n generally is a positive fractional constant. The solution of the problem is based on the method of moments. The problem is reduced to solving four polynomial equations with respect to the four coefficients of the model. In the symbolic computing environment Maple, an identification and order reduction program has been developed that implements the described algorithm. The efficiency of the algorithm was tested on test models.
Evaluation of the effectiveness of geographic information systems adaptation to destabilizing factors
Authors: Burlov V G , Gryzunov V V 
Published: February 2021

Abstract
Formulation of the problem. Geographic information systems are becoming an integral part of many automated control systems. The quality of the made management decision depends on their ability to work. At the same time, geoinformation systems operate in conditions of destabilizing factors reducing the quality of services provided. The existing indicators of the efficiency of the functioning of geoinformation systems do not allow to quickly and comprehensively assess the ability of geoinformation systems to adapt to the action of destabilizing factors, and therefore, to understand how the system is able to satisfied the requirements of its users.
Purpose. To propose performance indicators that allow assessing the “usefulness” of geoinformation systems for the consumer in conditions of destabilizing factors.
Results. Non-stochastic indicators of efficiency have been developed: integral and differential, a theorem has been formulated and proved about the independence of events in solving tasks for any directed graph, examples are given and conditions for the expediency of using the proposed indicators for the evaluating of the effectiveness of geographic information systems adaptation are given to the destabilizing factors action.
Practical significance. The proposed indicators can be used to synthesize the structure and functions of geographic information systems in real time.
Software model of a highly undetectable stegosystem – ⊕HUGO model
Authors: Kustov V N , Krasnov A G 
Published: February 2021

Abstract
The article is devoted to the research of a software model of the hidden message transmission process using one of the new methods of steganography proposed by the authors. The presented model implements a hard-to-detect method for embedding hidden messages in digital still images used as covering objects (containers). The main principle of using the model is to minimize adequately specified distortion using a new efficient encoding algorithm. Distortion is defined as an operation ⊕ (excluding OR - XOR) between the next half-byte of the hidden message and the right half-byte of the specially selected byte of the covering object, which is selected from the condition for minimizing the penalty function calculated on some selected neighbourhood of this byte. This allows authors to keep the original image almost unchanged and make it indistinguishable from the original, even after large payloads are embedded in it. Thus, the embedded hidden message may not be visible when the steganalysis even for the experienced steganalytic. The ⊕ operation has the property of bijectivity (it is reversible), which makes quite easy to use it to extract a hidden message on the recipient’s side, if the recipient has key information. The stegosystem model is called the ⊕Highly Undetectable SteGOsystem model. In short, it can be referred to as the ⊕HUGO model.
Dark energy as the information field of the universe
Authors: Bogomolov A I 
Published: February 2021

Abstract
Using modern theories of the origin and expansion of the Universe, recent discoveries in astronomy and quantum physics, the article proposes the hypothesis to add to attributes of the nascent universe such as “space” and “time” of the attribute “information,” which finds its embodiment from a physical point of view in the form dark energy. With the development of the Universe, the volume of information grows and, accordingly, the mass of dark energy increases, turning into an information field or noosphere, which provides for the expansion of the Universe. An analogy is made between the Big Bang and the expansion of the Universe in the process of its evolution, due to the increase in the amount of dark energy and between the birth of Man from singularity (egg) and the growth of his information and knowledge in the process of his life.
The use of a neural network model for the analysis of tourism development in the regions of the country
Authors: Kazak A N , Oleinikov N N , Chetyrbok P V , Shamaeva N P , Alexandrova E V 
Published: February 2021

Abstract
Neurocomputer and neural network technologies are one of the most effective artificial intelligence strategies. A neural network model has been developed, designed to assess the prospects of tourism development in certain regions of the Russian Federation. In particular, the Krasnodar Territory was chosen for analysis as one of the most popular resorts in terms of the level of domestic tourism development. Using the neural network model built in Matlab, the impact of individual economic indicators on the number of tourist visits to this resort was evaluated. This kind of analytical activity is important for adjusting regional policies in the field of tourism and recreational activities and will allow relevant experts to improve the quality of management decisions and strategies being developed. Thus, the competitiveness of the regions increases and a new approach to the development of the recreational sphere is introduced.
Recognition of emotions in human speech with deep learning models
Authors: Shchetinin E Yu 
Published: February 2021

Abstract
The paper investigates the architecture of deep neural networks for recognizing human emotions from speech. Convolutional neural networks and recurrent neural networks with an LSTM memory cell were used as models of deep neural networks. An ensemble of neural networks was also built on their basis. Computer experiments on the use of the proposed deep learning models and basic machine learning algorithms for recognizing emotions in human speech contained in the RAVDESS audio database were conducted. The results obtained showed high efficiency of neural network models, and accuracy estimates for individual emotions were 92%.
Possible directions in the development of Russian low-cost airlines
Authors: Melekhina T L , Pozdeeva S N 
Published: February 2021

Abstract
Having carried out a comparative analysis of the development of low-cost airlines in European and Asian countries, the authors used a correlation-regression analysis for financial forecasting of the activities of the “Pobeda” air carrier. The article defines the factors that affect the profit and built a multi-factor regression model that allowed to calculate the forecast value of revenue. There are prospects for development and stable functioning in the market, and this is only the beginning of the transition to a new level of development in the field of transport services.
Validation of an image-analysis-based method of measurement of the overall dimensions of seeds
Authors: Gierz Ł , Markowski P , Chmielewski B 
Published: February 2021

Abstract
Due to agricultural producers’ increasing awareness and the introduction of increasingly restrictive crop protection standards, producers have to use new technologies that are safer for consumers and the environment. In order to meet the requirements of these standards, it is necessary to take the physical properties of crops and agricultural raw materials (basic geometric parameters, shape factors, and equivalent spherical diameters) into account when designing machinery for the harvesting, transport, and processing of agricultural produce. When designing machinery, methods used for calculating the strength of the machine construction and the discrete element method (DEM) used in computer simulations of processes involving seeds or particles require the provision of the exact geometrical dimensions of particles and seeds. The aim of the study was to develop a universal method of measurement of the overall dimensions of granular material particles using a widely available application based on image analysis. The study presents the possibility of using a new method of measuring overall dimensions by means of the widely available ImageJ application on a specially designed test facility.
Analysis of the influence of gear tooth friction on dynamic force in a spur gear
Authors: Jedliński Ł 
Published: February 2021

Abstract
The main objective of this paper is to investigate the influence of tooth friction on the dynamic force of the gearbox. This is one of the most insignificantly investigated aspects of the gearbox work, despite both experimental and theoretical research conducted. For this reason, it is not entirely possible to establish the friction force determining the friction coefficient due to the complexity of the process. Currently, various approaches are taken in calculating dynamic models, among others excluding friction, Coulomb models, models in which the value of the friction coefficient depends on the sliding velocity, and the application of complex elastohydrodynamic models. Due to such different approaches, it was decided to examine the influence of tooth friction on the dynamic force for the stationary work conditions of the gearbox. Moreover, a new gear tooth friction model was developed, based on the Coulomb model of friction and rolling friction. The results were obtained for four friction models and, in the fifth case, without including it. Furthermore, the influence of torsional vibration on the friction lever arm was analysed.
Detection of measurement noise in surface topography analysis
Authors: Podulka P 
Published: February 2021

AbstractVarious types of measurement noise detection from the results of surface topography measurements are presented and compared. The types of considered surface textures are: honed, turned, ground, laser-melted, milled, composite, ceramic and isotropic topographies. The measurements are carried out using the stylus (Talyscan 150) or non-contact – optical (white light interferometer Talysurf CCI Lite) equipment. It was assumed that for certain stratified textures, power spectral density assessment would be sufficient, otherwise, the multi-threaded analysis was required. It was also found that certain frequency errors in measurement can be readily detected with profile analysis. Nonetheless, when measurement noise amplitudes are relatively small, e.g. root mean square height (Sq) < 10%, then the isometric view detection is nearly impossible. For the detection of high-frequency measurement noise, the power spectral density analysis is required; for this type of texture, the high-frequency measurement noise surface (HFNS) is described using the regular spline filter. It is indicated that the HFNS should be observed if the machining marks are visible in the isometric view. Secondly, accurately defined HFNS should contain only the high-frequency rather than low-frequency details.