bluuebunny/crossref_metadata_2025 huggingface dataset:
Os Autores brasileiros não citam os autores brasileiros: Nada mudou desde 1994
Authors: Giordano Vincenzo , Lyra Juliana , Bonadiman João Artur , Lech Osvandré
Published: April 2021

Objetivo Observar o perfil de autocitações da Revista Brasileira de Ortopedia (Rev Bras Ortop) e de citações deste periódico em outras revistas médicas de ortopedia de conteúdo geral ou específico de uma determinada área de conhecimento da especialidade.

Métodos Trata-se de estudo observacional transversal da frequência de autocitações e citações da Rev Bras Ortop em outros cinco periódicos médicos de ortopedia de diferentes países, todas publicadas em língua inglesa. Foram analisados os 15 últimos artigos publicados em 2020 em cada uma das seis revistas estudadas. As referências usadas em cada um delas foi avaliada para identificação do periódico em que foram publicadas originalmente. A distribuição de frequência dos quatro principais periódicos citados, sua posição e o percentual relativo ao total de citações foram observados e registrados em cada uma das seis revistas. O número de vezes em que a Rev Bras Ortop foi citada em cada um dos periódicos estrangeiros selecionados foi avaliado por meio de suas frequências absoluta e relativa.

Resultados O total de citações avaliadas neste estudo foi de 2527 (variando de 386 a 486 por revista). A Rev Bras Ortop apresentou baixa taxa de autocitação (2,6%), sendo citada na própria revista na sexta posição (10 de um total de 386 referências). No período estudado, a Rev Bras Ortop não foi citada em nenhum dos outros cinco periódicos médicos incluídos no estudo (frequência absoluta 0, frequência relativa 0).

Conclusão Observou-se que a Rev Bras Ortop apresenta baixa referência de si própria, com taxa de autocitação de 2,6% no período estudado, mostrando que de fato o ortopedista brasileiro não cita o ortopedista brasileiro que publica na revista. Sugerimos a elaboração e a implementação de estratégias fortes de melhora da visibilidade do periódico no cenário acadêmico-científico mundial. Além disso, é fundamental que os ortopedistas brasileiros entendam esta realidade e auxiliem direta e efetivamente em sua mudança.
Do Tar Roads Bring Tourism? Growth Corridor Policy and Tourism Development in the Zambezi region, Namibia
Authors: Kalvelage Linus , Revilla Diez Javier , Bollig Michael
Published: April 2021

There are high aspirations to foster growth in Namibia’s Zambezi region via the development of tourism. The Zambezi region is a core element of the Kavango-Zambezi Transfrontier Conservation Area (KAZA), a mosaic of areas with varying degrees of protection, which is designed to combine nature conservation and rural development. These conservation areas serve as a resource base for wildlife tourism, and growth corridor policy aims to integrate the region into tourism global production networks (GPNs) by means of infrastructure development. Despite the increasing popularity of growth corridors, little is known about the effectiveness of this development strategy at local level. The mixed-methods approach suggests a link between a tandem of infrastructure development and tourism-oriented policies on the one hand, and increased value creation from tourism in the region on the other hand. Yet, the promises of tourism-driven development reach only a very limited number of rural residents.
Comparative study of data-driven short-term wind power forecasting approaches for the Norwegian Arctic region
Authors: Chen Hao , Birkelund Yngve , Anfinsen Stian Normann , Yuan Fuqing
Published: April 2021

This paper conducts a systemic comparative study on univariate and multivariate wind power forecasting for five wind farms inside the Arctic area. The development of wind power in the Arctic can help reduce greenhouse gas emissions in this environmentally fragile region. In practice, wind power forecasting is essential to maintain the grid balance and optimize electricity generation. This study first applies various learning methods for wind power forecasting. It comprehensively compares the performance of models categorized by whether considering weather factors in the Arctic. Nine different representative types of machine-learning algorithms make several univariate time series forecasting, and their performance is evaluated. It is demonstrated that machine-learning approaches have an insignificant advantage over the persistence method in the univariate situation. With numerical weather prediction wind data and wind power data as inputs, the multivariate forecasting models are established and made one to six h in advance predictions. The multivariate models, especially with the advanced learning algorithms, show their edge over the univariate model based on the same algorithm. Although weather data are mesoscale, they can contribute to improving the wind power forecasting accuracy. Moreover, these results are generally valid for the five wind farms, proving the models' effectiveness and universality in this regional wind power utilization. Additionally, there is no clear evidence that predictive model performance is related to wind farms' topographic complexity.
Reaction zone structure and detonation parameters of nitromethane/polymethylmethacrylate and its mixture with microballoons
Authors: Mochalova Valentina , Utkin Alexander , Shakula Mikhail , Lavrov Vladimir , Savchenko Andrey , Yakushev Vladislav
Published: April 2021

In the present work, the detonation wave structure and detonation parameters for nitromethane (NM) and its mixtures with polymethylmethacrylate (PMMA) and glass microballoons (GMB) were studied by a velocity interferometer system for any reflector laser interferometer. The PMMA concentration varied from 2% to 4%. It is shown that PMMA additives lead to a change in the reaction zone structure, which can be observed as an appearance of a cellular instability of the detonation front. The detonation parameters of the mixture up to 3% PMMA are close to those of pure nitromethane and reduced when 4% PMMA is added. The addition of 2% GMB to the NM/PMMA mixture leads to the formation of a detonation front with a characteristic size of heterogeneities on the order of GMB diameter. In this case, the detonation parameters are reduced, and the values of the detonation velocity decrease by about 10% compared to NM/PMMA mixtures.
Geometric and energy-aware decomposition of the Navier–Stokes equations: A port-Hamiltonian approach
Authors: Califano Federico , Rashad Ramy , Schuller Frederic P. , Stramigioli Stefano
Published: April 2021

A port-Hamiltonian model for compressible Newtonian fluid dynamics is presented in entirely coordinate-independent geometric fashion. This is achieved by the use of tensor-valued differential forms that allow us to describe the interconnection of the power preserving structure which underlies the motion of perfect fluids to a dissipative port which encodes Newtonian constitutive relations of shear and bulk stresses. The relevant diffusion and the boundary terms characterizing the Navier–Stokes equations on a general Riemannian manifold arise naturally from the proposed construction.
Habitat use over winter by short-beaked echidnas (
Authors: Lawes Jasmin C. , Croft David B.
Published: April 2021

The heterogeneity of resource distribution in arid environments plays an important role in habitat selection by consumers. The productivity of the riparian zones of intermittently flowing creeks is typically prolonged, relative to the hinterland, as moisture and nutrients concentrate there. Short-beaked echidnas, Tachyglossus aculeatus, sustain arid populations, attributed to ant and termite availability, low predation, and an ability to exploit habitat remnants. However, the scale of their movements in arid habitats is poorly understood. Thus, we investigated echidna home ranges and the importance of food and shelter availability in habitat selection over one winter. We focussed on the riparian zone of a creek at Mount Wood in Sturt National Park, north-western New South Wales, Australia. Radio tracking (VHF and GPS), scat and habitat selection analyses were conducted. Mean core and peripheral home range areas were 0.16 and 1.042 km2, respectively, with a mean home range overlap of 0.56 km2. Habitat selection differed between juveniles and adults and may have been driven by prey availability (predominantly ants). The preferred shelter was thick leaf litter. We concluded that habitat selection patterns were driven by prey availability (ants) and shelter (leaf litter).
Drought stress affects the germination of four co-occurring
Authors: Emery Nathan J. , Collette Justin C.
Published: April 2021

The interactive effect of seasonal temperatures and water potential (Ψ) were examined on the germination of four co-occurring Eucalyptus species (Eucalyptus melanophloia F.Muell., E. pilligaensis Maiden, E. populnea subsp. bimbil L.A.S.Johnson & K.D.Hill and E. viridis R.T.Baker) from the Brigalow Belt South bioregion of New South Wales. These eucalypts are important canopy species, and are a key inclusion for restoring native vegetation to areas that have had significant landscape modification. Final germination, time to first germination, and time to 50% germination were recorded at three alternating temperature regimes for winter (day/night, 19/5°C), spring–autumn (27/12°C) and summer (34/20°C), and eight different Ψ treatments between saturation point (0 MPa) and permanent wilting point (–1.5 MPa) under controlled laboratory conditions. Final germination was highest in all species when seeds were incubated at winter conditions, but spring–autumn and summer temperatures had mixed effects on final germination, depending on the species. Final germination consistently declined with lower Ψ across all temperatures for E. pilliagaensis, E. populnea subsp. bimbil and E. viridis, whereas E. melanophloia displayed a mixed response to temperature and Ψ. No germination occurred when Ψ was lower than –0.25 MPa. Time to first germination and time to reach 50% germination (t50) were lowest at summer temperatures for all species, and all species except E. pilligaensis experienced higher time to first germination and t50 (i.e. slower germination rates) as Ψ decreased from 0 to –0.25 MPa. Our results indicate that all four eucalypts should be treated as drought-sensitive species with a higher probability of field recruitment during cooler and wet conditions.
CAM photosynthesis in desert blooming
Authors: Holtum Joseph A. M. , Hancock Lillian P. , Edwards Erika J. , Winter Klaus
Published: April 2021

When plants of the Atacama desert undergo episodic blooms, among the most prominent are succulent-leaved Cistanthe (Montiaceae). We demonstrate that two Cistanthe species, the perennial Cistanthe sp. aff. crassifolia and the annual/biannual Cistanthe sp. aff. longiscapa, can exhibit net CO2 uptake and leaf acidification patterns typical of crassulacean acid metabolism (CAM). In C. sp. aff. crassifolia leaves, CAM expression was facultative. CAM-type nocturnal net CO2 uptake and acid accumulation occurred in drought-stressed but not in well-watered plants. By contrast, CAM expression in C. sp. aff. longiscapa was largely constitutive. Nocturnal acid accumulation was present in leaves of well-watered and in droughted plants. Following water-deficit stress, net nocturnal CO2 uptake was induced and the level of acid accumulated increased. Neither nocturnal CO2 uptake nor acid accumulation was reduced when the plants were re-watered. δ13C values of a further nine field-collected Cistanthe species are consistent with a contribution of CAM to their carbon pools. In the Portulacinae, a suborder with eight CAM-containing families, Cistanthe becomes the sixth genus with CAM within the family Montiaceae, and it is likely that the ancestor of all Portulacineae also possessed CAM photosynthesis. In the stochastic rainfall landscape of the Atacama, carbon uptake in the dark is a water-use efficient mechanism that increases the carbon pool available for seed production or dormancy. The next rain event may be years away.
Divergent low-density lipoprotein receptor (LDLR) linked to low VSV G-dependent viral infectivity and unique serum lipid profile in zebra finches
Authors: Velho Tarciso A. F. , Lovell Peter V. , Friedrich Samantha R. , Olson Christopher R. , Miles Joshua , Mueller Paul A. , Tavori Hagai , Fazio Sergio , Lois Carlos , Mello Claudio V.
Published: April 2021

The low-density lipoprotein receptor (LDLR) is key to cellular cholesterol uptake and is also the main receptor for the vesicular stomatitis virus glycoprotein (VSV G). Here we show that in songbirds LDLR is highly divergent and lacks domains critical for ligand binding and cellular trafficking, inconsistent with universal structure conservation and function across vertebrates. Linked to the LDLR functional domain loss, zebra finches show inefficient infectivity by lentiviruses (LVs) pseudotyped with VSV G, which can be rescued by the expression of human LDLR. Finches also show an atypical plasma lipid distribution that relies largely on high-density lipoprotein (HDL). These findings provide insights into the genetics and evolution of viral infectivity and cholesterol transport mechanisms in vertebrates.
Time-invariant discord and steady-state entanglement in engineered non-equilibrium dephasing environments
Authors: Basit Abdul , Ali Hamad , Yang Xiao-Fei , Ge Guo-Qin
Published: April 2021

We study theoretically the dynamics of quantum and classical correlations in the two-qubit system, locally experiencing a one-sided engineered pure dephasing non-equilibrium environment with an Ohmic class spectrum. The environmental non-equilibrium nature is characterized by random perturbations with non-stationary statistics. Particularly, we investigate the influence of the non-equilibrium feature on the protection of these correlations and, more specifically, its effect on the non-trivial phenomenon of time-invariant discord. Remarkably, we show that in the presence of this engineered non-equilibrium environment, time-invariant discord with a significantly larger magnitude exists for all Ohmic spectral densities, i.e., sub-Ohmic, Ohmic, and super-Ohmic without zero-temperature restriction. Additionally, we also show that our engineered non-equilibrium model provides a promising tool for trapping entanglement in a steady-state with a higher magnitude. Moreover, our proposed model also renders new insights for controlling decoherence through engineering the relative initial phases of the bath modes without performing any artificial operations on the main quantum system.
Superconductivity in an intermetallic oxide Hf3Pt4Ge2O*
Authors: Xu Chengchao , Wang Hong , Tian Huanfang , Shi Youguo , Li Zi-An , Xiao Ruijuan , Shi Honglong , Yang Huaixin , Li Jianqi
Published: April 2021

Discovery of a new superconductor with distinct crystal structure and chemistry often provides great opportunity for further expanding superconductor material base, and also leads to better understanding of superconductivity mechanisms. Here, we report the discovery of superconductivity in a new intermetallic oxide Hf3Pt4Ge2O synthesized through a solid-state reaction. The Hf3Pt4Ge2O crystallizes in a cubic structure (space group Fm-3m) with a lattice constant of a = 1.241 nm, whose stoichiometry and atomic structure are determined by electron microscopy and x-ray diffraction techniques. The superconductivity at 4.1 K and type-II superconducting nature are evidenced by the electrical resistivity, magnetic susceptibility, and specific heat measurements. The intermetallic oxide Hf3Pt4Ge2O system demonstrates an intriguing structural feature that foreign oxygen atoms can be accommodated in the interstitial sites of the ternary intermetallic framework. We also successfully synthesized a series of Hf3Pt4Ge2O1 + δ
(–0.25 ≤ δ ≤ 0.5), and found the δ-dependent superconducting transition temperature T
c. The atomic structure and the electronic structure are also substantiated by first-principles calculations. Our results present an entirely new family of superconductors with distinct structural and chemical characteristics, and could attract research interest in further finding new superconductors and exploring novel physics pertaining to the 5d-electron in these intermetallic compound systems.
Terahertz radiation generation by beating of two chirped laser pulses in a warm collisional magnetized plasma
Authors: Arefnia Motahareh , Sharifian Mehdi , Ghorbanalilu Mohammad
Published: April 2021

Analytical equations of terahertz (THz) radiation generation based on beating of two laser beams in a warm collisional magnetized plasma with a ripple density profile are developed. In this regard, the effects of frequency chirp on the field amplitude of the terahertz radiation as well as the temperature and collision parameters are investigated. The ponderomotive force is generated in the frequency chirp of beams. Resonant excitation depends on tuning of the plasma beat frequency, magnetic field frequency, thermal velocity, collisional frequency, and effect of the frequency chirp with the plasma density. For optimum parameters of frequency and temperature the maximum THz amplitude is obtained.
Chiral symmetry restoration and deconfinement in the contact interaction model of quarks with parallel electric and magnetic fields
Authors: Ahmad Aftab
Published: April 2021

We study the impact of steady, homogeneous, and external parallel electric and magnetic field strengths (

) on the chiral symmetry breaking-restoration and confinement-deconfinement phase transition. We also sketch the phase diagram of quantum chromodynamics (QCD) at a finite temperature T and in the presence of background fields. The unified formalism for this study is based on the Schwinger-Dyson equations, symmetry preserving vector-vector contact interaction model of quarks, and an optimal time regularization scheme. At

, in the purely magnetic case (i.e.,

), we observe the well-known magnetic catalysis effect. However, in a pure electric field background (

), the electric field tends to restore the chiral symmetry and deconfinement above the pseudo-critical electric field

. In the presence of both

and

, we determine the magnetic catalysis effect in the particular region where

dominates over

, whereas we observe the chiral inhibition (or electric chiral rotation) effect when

overshadows eB. At finite T, in the pure electric field case, the phenomenon of inverse electric catalysis appears to exist in the proposed model. Conversely, for a pure magnetic field background, we observe the magnetic catalysis effect in the mean-field approximation and inverse magnetic catalysis with

-dependent coupling. The combined effects of

and

on the pseudo-critical

yields an inverse electromagnetic catalysis, with and without an

-dependent effective coupling of the model. The findings of this study agree well with the already predicted results obtained via lattice simulations and other reliable effective models of QCD.
The impact of synchronous versus asynchronous electrical stimulation in artificial vision
Authors: Moleirinho Susana , Whalen Andrew J , Fried Shelley I , Pezaris John S
Published: April 2021

Visual prosthesis devices designed to restore sight to the blind have been under development in the laboratory for several decades. Clinical translation continues to be challenging, due in part to gaps in our understanding of critical parameters such as how phosphenes, the electrically-generated pixels of artificial vision, can be combined to form images. In this review we explore the effects that synchronous and asynchronous electrical stimulation across multiple electrodes have in evoking phosphenes. Understanding how electrical patterns influence phosphene generation to control object binding and perception of visual form is fundamental to creation of a clinically successful prosthesis.
Geometric compression of invariant manifolds in neural networks
Authors: Paccolat Jonas , Petrini Leonardo , Geiger Mario , Tyloo Kevin , Wyart Matthieu
Published: April 2021

We study how neural networks compress uninformative input space in models where data lie in d dimensions, but the labels of which only vary within a linear manifold of dimension d
∥ < d. We show that for a one-hidden-layer network initialized with infinitesimal weights (i.e. in the feature learning regime) trained with gradient descent, the first layer of weights evolves to become nearly insensitive to the d
⊥ = d − d
∥ uninformative directions. These are effectively compressed by a factor

λ
∼

p

, where p is the size of the training set. We quantify the benefit of such a compression on the test error ϵ. For large initialization of the weights (the lazy training regime), no compression occurs and for regular boundaries separating labels we find that ϵ ∼ p
−β
, with β
Lazy = d/(3d − 2). Compression improves the learning curves so that β
Feature = (2d − 1)/(3d − 2) if d
∥ = 1 and β
Feature = (d + d
⊥/2)/(3d − 2) if d
∥ > 1. We test these predictions for a stripe model where boundaries are parallel interfaces (d
∥ = 1) as well as for a cylindrical boundary (d
∥ = 2). Next, we show that compression shapes the neural tangent kernel (NTK) evolution in time, so that its top eigenvectors become more informative and display a larger projection on the labels. Consequently, kernel learning with the frozen NTK at the end of training outperforms the initial NTK. We confirm these predictions both for a one-hidden-layer fully connected network trained on the stripe model and for a 16-layer convolutional neural network trained on the Modified National Institute of Standards and Technology database (MNIST), for which we also find β
Feature > β
Lazy. The great similarities found in these two cases support the idea that compression is central to the training of MNIST, and puts forward kernel principal component analysis on the evolving NTK as a useful diagnostic of compression in deep networks.
Real-Time Earthquake Forecasting using Multidimensional Hierarchical Graph Neuron (mHGN)
Authors: Benyamin Nasution Benny
Published: April 2021

Various earthquake forecasting technologies have been introduced for a while, but the quality of the results is not yet convincing. The attempt to achieve a stable technology is still very demanding, due to increasing number of earthquake incidences lately. Since it is not trivial working on complex—with numerous parameters—and big data, the research on discovering such earthquake forecast system takes long and winding roads. It is still very difficult to establish a sophisticated system that can be used to forecast earthquake effectively, but the concept of Multidimensional Hierarchical Graph Neuron (mHGN) has opened up a new opportunity to forecast earthquake not only effectively but also in real-time manner. The 91% of its accuracy in recognizing almost 11% distorted/incomplete patterns has given a strong indication that the accuracy of mHGN in forecasting earthquake will be high as well.
Design and Development of Mobile Application in Indonesian Language Learning For Foreign Speakers Level A1
Authors: Seri Ermyna , Sutrisno Wiwinta
Published: April 2021

This paper describes about the design and development of Android mobile platform application in the learning of Indonesian Language for Foreign Speakers as the term used Bahasa Indonesia bagi Penutur Asing or as abbreviated BIPA. The Android Studio is used to create and set up a set of application programming interfaces (APIs) and Kernel Linux Platform. The interface program was designed to give effectiveness and flexibilities required in the process of learning. The program code was written and installed in the users Smart Phone. The official language programming used for Android development is Java to make the program running easily for the users to use the application because the mobile application does not use many resources. Once the application was ready, then installed into various types of Smart Phone with various Android platforms, and tested. The program was tested to BIPA foreign students who were learning BIPA Level A1 to see if the program ran well. This aimed to test its effectiveness and impact. The data of pre-test and interview were collected from foreign students who have already learned Indonesian language before and who were never in order to see the baseline of respondents competencies. Pre-test, Post-test and interview test scores were compared to see if there was an increase in respondents competencies. The research findings shows that there was a significant increase on the foreign students’ skills. The increase on the written test through pre-test and post-test showed by 30% and 18 % on the interview. In contrast, the most significant increase was occurred in the group of students who never learned before. This increase showed by 56%, whereas the increase in the group of foreign students who have already learned Indonesian language showed by 12%. Furthermore, this increase significantly also occurred in interview at 32% to the group of foreign students who never learned Indonesian language before and 8% to the group of foreign students who already learned Indonesian language. This findings shows that Mobile Application provides effectiveness, efficiency, flexibilities, and accelerated learning to the group of foreign speakers who never learned BIPA before.
Application of C4.5 and Naïve Bayes Algorithm for Detection of Potential Increased Case Fatality Rate Diarrhea
Authors: Wahyudi Mochamad , Andriani Anik
Published: April 2021

Case Fatality Rate or mortality percentage due to some extraordinary events (outbreaks) diarrhea in Indonesia is still above target expected by the government. Several factors have been known to be the cause of diarrhea, but the most influential factor to increase Case Fatality Rate of diarrhea is not known. Therefore, the purpose of this research is to create classification from diarrhea outbreaks data to obtain the data patterns in the form of classification rule that can be applied to detect Case Fatality Rate of diarrhea. Classification used the C4.5 algorithm and Naïve Bayes algorithm. C4.5 algorithm is a popular algorithm with decision tree approach, while Naïve Bayes algorithm is a popular with probabilistic approach in classification. Research implementation uses the stages in Knowledge Discovery in Databases. After obtaining the classification rule, this rule evaluated by Confussion Matrix and Receiver Operating Characteristic Curve. The evaluation was done by using training data and testing data. The evaluation result in this case indicates that C4.5 algorithm has a higher accuracy level than Naïve Bayes. While the factors that most influence in the Case Fatality Rate increase in diarrhea diseases are shelter and sanitation.
Find the Best Rule of Time Series Data Mining with Cluster Analysis
Authors: Buaton Relita , Zarlis Muhammad , Mawengkang Herman , Efendi Syahril
Published: April 2021

Data mining is an analytical process of knowledge discovery in large and complex data sets. Many studies wish to explore data, to find information so that knowledge can be obtained through the grouping process, classification, rules discovery, associations and data mining visualization which shows similarity. Periodic data often occurs in business applications and sciences that has big size, high dimension and continuously updated. The similarity in periodic data is based on several approaches. One of common approaches is to transform periodic series into other domains so that dimensions are reduced, followed by index mechanism. Many studies of time series do not give optimal result because limited to extracting data not able to represent time series and its pattern which is then change into rules. Rules can be found in time series data, but they are still constrained by over fitting and difficult to present. It causes time series data and non linier function of data mining decision can’t be optimal. The basic idea in the method proposed is to do periodic discretization for sub-sequential formation. These sub-sequences are grouped through a measure of similarity. The simple rule-finding technique is applied to obtain hidden rules in the temporal pattern. The optimal time series data expected to generate the uncertainty trend, previously unknown and can be used to make decisions or forecasting in the future.
Mathematical Modeling of Facilitated Transport of Eu(III) ion by CMPO in Modified diluents as Extractant
Authors: Kumar Rohit , Kandwal Pankaj
Published: April 2021

A simplified model has been developed to model the pertraction of Eu(III) through the flat-sheet supported liquid membrane (FSSLM) impregnated with CMPO in modified diluents as extractant. The solvent extraction studies of europium were performed under different experimental conditions and some of solvent extraction (SX) data were taken from literature as required to obtain some basic parameters of mathematical modelling for the mass-transfer process. The metal ion transport through liquid membrane is facilitated by diffusion and formulation of model is, therefore, governed by law of diffusion. Effect of various parameters on transport rate of Eu(III) ion, such as ligand concentration, feed acidity, diluent composition etc., has been predicted.
Single Valued Neutrosophic Numbers and Applications in Selection Criteria
Authors: Gahlot Sapna , Saraswat R. N.
Published: April 2021

A SVNN is just a common number whose exact worth is to some degree dubious from a philosophical perspective. Presented single valued neutrosophic numbers (SVNN) which is a speculation of fuzzy numbers and intuitionistic fuzzy numbers. Here, we will discuss about special types of SVNN. Additionally, presented a few procedures on single valued trapezoidal. At last, developed single valued trapezoidal neutrosophic measure and its applications in multi-criteria decision making.
An investigation on existence and uniqueness of solution for Integro differential equation with fractional order
Authors: Sarkar Nimai , Sen Mausumi
Published: April 2021

Present article deals with some theoretical results regarding the solution of integro differential equation with integral boundary condition. Main idea is to covert the integro differential equation into corresponding integral equation. Then we adopt a suitable transformation to implement Banach contraction and Schaefer-Krasnoselskii fixed point Theorem. Finally by properties of fractional calculus and fixed point theory we derive the main results. An example is considered for the verification of theoretical work.
Entropy generation in thermal radiative oscillatory MHD couette flow in the influence of heat source
Authors: Sharma Tarun , Sharma Pooja , Kumar Navin
Published: April 2021

Entropy generation and their minimization for magnetohydrodynamic oscillatory couette flow through a vertical channel, soaked with a porous medium in the existence of heat source and thermal radiation has been deliberated. In the present analysis, flow governing equations are elucidated and extricated with the help of analytical technique for the fluid velocity profile, temperature field, irreversibility distribution and Bejan number. Also, the numerical value of dimensionless shearing stress and heat transfer coefficient are obtained and presented through tables with reference to flow governing parameters. It has noticed that entropy generation can be regulated or minimized with the change in the applied magnetic field and thermal radiation, and this result is useful in several thermodynamic industries and engineering field for attaining the high performance of devices with minimum heat loss.
Studies on the interaction of Na+ ion with binary mixture of carbonate-ester solvents: A density functional theory approach
Authors: Tiwari Sakshi , Gupta Abhishek Kumar , Gupta Shivani , Gupta Sarvesh Kumar , Chaurasia Sujeet Kumar
Published: April 2021

The advancement of sodium-ion batteries as an alternative to lithium-ion batteries presents a viable way to make energy storage cost-efficient. However, the inherent properties of Na+ are not quite well understood as it is for Li+, which also include solvation of Na+ in non-aqueous electrolyte for its application in electrochemical devices. Here, a comprehensive study of Na+ solvation in the binary mixture of ethylene carbonate (EC) and propylene carbonate (PC) in different ratios is reported, using density functional theory calculation. The optimised structure of cluster of binary mixture EC-PC-Na+ in three different ratios (1:1, 2:1 and 3:1) of EC: PC is analysed. Binding and Gibbs free energy of Na+ solvated by EC and PC and charge on Na+ is calculated. The calculated results favour the stability of binary mixtures containing higher concentration of ethylene carbonate. In infrared (IR) vibrational spectra, substantial changes are observed in the IR active modes of the solvent because of cation-solvent interaction.
The First Principle Investigation for the Structural and Optoelectronics Properties of Tetragonal Compound CaCN2
Authors: Khan K , Gaur A , Ahuja U , Soni A , Sahariya J
Published: April 2021

The present study deals with the structural, electronic and optical properties of CaCN2 ternary compound. For the computation of structural, electronic and optical properties of the CaCN2, the Perdew-Burke-Ernzerhof generalized gradient approximation (PBE-GGA) exchange correlation within the framework of density functional theory as available in Wien2k code is used. Wien2k code is based on full potential linearized augmented plane wave method. The electronic properties are investigated in terms of energy band structure, partial and total density of states. Our investigation reveals the direct band gap nature of CaCN2 with band gap of 1.66 eV. The optical behaviour CaCN2 is explained through dielectric tensor, absorption, reflection and refraction spectra which show the utility of this compound in photovoltaic applications.
Power Optimal Control Method of Network Big Data for Mechanical Vibration Wireless Sensor
Authors: Wang Kai
Published: April 2021

With the gradual deepening of research on wireless sensor networks at home and abroad in recent years, some wireless sensor network application systems have emerged in the fields of academic research and engineering applications. Especially in the industrial field, wireless sensor network, as a new information perception technology, has attracted more and more attention due to its advantages of self-organization, flexible deployment, strong scalability, and on-chip processing capabilities. The purpose of this paper is to study the power optimization control method of wireless sensor of mechanical vibration by network big data. In view of the current problem of power control of mechanical vibration wireless sensor network nodes, first, under the premise of ensuring the accuracy of data collection, the key factors affecting the power control of mechanical vibration wireless sensor network nodes are analyzed, the wireless sensor power control model is designed, and the network big data is proposed. Impact on the power of wireless sensors; finally, based on the above research, the fuzzy power control algorithm and its simulation are specifically studied. First, a point-to-point transmission power control system model is designed, and the fuzzy logic controller module is designed in detail, including fuzzy Part of the membership function design, fuzzy rule determination and the use of defuzzification methods. Then use simulation tools to build a point-to-point simulation model and a simulated network simulation model. Finally, these two models are used to compare the performance of fuzzy power control algorithm and fixed power method. The experimental results show that the network survival time using fuzzy power control algorithm is twice that of the fixed power method. The fuzzy power control algorithm has great advantages in both effective communication distance and network survival time.
A Device Used for The Elevator Shaft Wall out of Tolerance Measurement Based on The Laser Ranging Technology
Authors: Lin Yang
Published: April 2021

The national safety technical specifications and standards have clear provisions on the distance between the elevator car and the well wall facing the car entrance. Current measuring methods are lower measurement efficient and accuracy, and poor repeatability. With the increasing number of elevators, this traditional method is far from meeting the requirements of practical work. This paper studied on the Laser ranging technology applied to the distance measurement aiming to overcome those problems. The new measuring equipment was consisted of the laser ranging module, rotary encoder and Bluetooth module, which can measure and record all data related to the distance between the car and the car entrance shaft wall. The advantages of the new device are higher repeatability and reliability, which greatly improve the measurement efficiency. It is suitable for measuring the distance between elevator car and shaft well of high-rise building, thus the inspectors can be free from the heavy work of measurement.
Application and Development Trend of Artificial Intelligence in Enterprise Marketing
Authors: Li Runfa , Cao Zheng , Ye Huan , Yue Xianghua
Published: April 2021

Technology changes life. At present, the application of “artificial intelligence” is becoming more and more popular in enterprise marketing. The application and planning of artificial intelligence has gradually become the core competitiveness of some enterprises in the development process. This paper focuses on “research background”, “application of artificial intelligence in enterprise marketing” and “development trend of artificial intelligence in enterprise marketing”. It is hoped that “artificial intelligence” will be taken as the breakthrough point to further explore the marketing mode of enterprises in the new era in China, and gradually standardize the application and development of artificial intelligence.
Application Research of Power System Automation Based on Electrical Automation Technology
Authors: Li Xuxin
Published: April 2021

Power is an indispensable energy in our daily life, and the power system is to manage and maintain the normal supply of electricity, which directly affects the stability of the entire power network. At present, China’s power network is in an important upgrading stage, from the traditional power system to intelligent power system, in this process, automatic electrical technology plays an important role. Therefore, based on electrical automation technology, this paper puts forward the application research of power system automation. This paper deeply studies the power system and the application of automation technology in power system in China. It is considered that PLC and automatic power detection technology, which are extended from electrical automation technology, play an important role in the whole power system operation process. But at present, there are still many deficiencies in the power system based on electrical automation technology, including the problem of large measurement error. Therefore, this paper proposes an improved optimization method. The experiment shows that the maximum error of the improved method is 0.125%, especially in the case of synchronous current power grid frequency of 50 Hz, the error rate is 0. The results show that the optimized method has good measurement accuracy. According to the actual application of the existing electrical automation technology in the power system, this paper puts forward the optimization and improvement measures, and forecasts and analyzes the future application development trend.
Optimal Energy Dispatch of Integrated Electricity Substation Considering the Operational Uncertainties in an Edge-Cloud Environment
Authors: Cheng Zhihua , Wang Honggang , Yang Chengyue , Ji Xin , Zhao Xiaolong
Published: April 2021

Along with the increasing challenge of optimal energy dispatch in an integrated electric power substation, this work presents a model to construct a typical substation system. Based on the solution framework of model predictive control, the joint scheduling problem of stochastic renewable energy and battery energy storage in the substation is effectively solved. Through the substation optimal operation model, the economic operation of the substation is realized. At the same time, the randomness and robustness of the model are studied through simulation It only includes wind turbine, gas turbine, battery energy storage and other equipment, but the scheduling model can be easily extended to more complex substation system with more distributed energy.
Deep Reinforcement Learning based Applications in Smart Power Systems
Authors: Chen Yong , Peng Xiangjun , Xu Xianchao , Wu Hao
Published: April 2021

Due to the complexity, uncertainty and the increase of data dimension in power systems, conventional methods often encounter bottlenecks when trying to solve decision-making and control problems. Therefore, data-driven methods to solve these problems are being widely studied. Deep reinforcement learning (DRL) is one of these data-driven methods and is regarded as true artificial intelligence (AI). It has been applied to solve a series of complex sequential decision-making problems, including those in the power system. This paper first reviews the basic idea, model, algorithm and technology of DRL. Then its application in power systems is considered, such as energy management, demand response, electricity market, and operation control. Also, the latest development of DRL in the power system is discussed.
Wide Application of Computer Information Technology in the Practice of Physical Education
Authors: Liu Chunding
Published: April 2021

With the rapid development of high and new technology, leading the 21st reality, computer information technology has increasingly taken up an irreplaceable role in all aspects and has become one of the most basic tools in all walks of life. Physical education practice is one of the most important links in the education system of our country. Of course, computer information technology was introduced to support education. Based on computer information technology, this paper analyzes the university physical education and summarizes its development trend. First of all, by explaining the current situation of physical education technology and the characteristics of network education, this paper puts forward the idea of College Physical Education under the network information education environment of organically integrating high education concepts and information techniques. The integration of network teaching into physical education has affected the traditional concepts of physical education and promoted the reform of physical education. It analyzes the application prospects of computer information technology in improving work efficiency, scientific management and improving teaching methods in physical education practice, and proposes that computer information technology will show a broad development space for physical education. And this article selects 100 students from two classes of physical education major of the University of Physical Education to conduct a practical investigation. The experimental research results show that in recent years, people have made continuous efforts to explore and research, apply computer information technology to physical education, and have achieved relatively good results. Based on the analysis of the advantages of computer information technology in physical education, this article further explores how to make full use of the advantages of computer information technology to provide an effective basis for the optimization and improvement of physical education in my country.
Development Mode of Internet Economy Based on Artificial Intelligence Technology
Authors: He Jiangnan , Yin Xiaoyin
Published: April 2021

Based on the background of artificial intelligence technology, there are different situations in the mutual development of the Internet economy and artificial intelligence technology, which has a relatively large impact on the healthy development of my country’s Internet economy. Whether it is Internet economy or artificial intelligence technology, their ultimate development goal is to achieve the rapid development of our country’s economy. This article will conduct an in-depth analysis of the role of artificial intelligence technology in the development of the Internet economy and study its huge commercial value in the development of the Internet economy. This article first analyzes the relevant concepts and characteristics of artificial intelligence technology in the development of the Internet economy, briefly describes the analysis of the development of my country’s network market economy, and compares the development of artificial intelligence technology in the market Internet economy with the traditional substantive economic development model. Subsequently, it demonstrated the necessity and feasibility of implementing artificial intelligence technology for the development of the Internet economy, and conducted investigations and studies on the way that 10 Internet companies in the east coast of China used artificial intelligence technology to improve economic development. Finally, it puts forward a targeted strategy for accelerating the improvement of Internet companies in the network economy market and future development goals. The experimental research results show that the application of the Internet and artificial intelligence technology has brought us great convenience, and at the same time promoted the growth of our country’s economy, and created huge economic benefits for our country.
Acupuncture and Moxibustion Treatment of Mild Cognitive Impairment Based on Data Mining
Authors: Yang Yuzhu , Yang Shuang , Ma Xunyuan , Yu Mei , Pan Jianli
Published: April 2021

Acupuncture and moxibustion therapy, as a traditional medical treatment method of the motherland, is widely used in the treatment of mild cognitive dysfunction, with remarkable curative effect, and is increasingly recognized by the medical community. However, so far, there is no acupuncture prescription and acupoint usage rules for acupuncture treatment of mild cognitive impairment. Therefore, it is of great significance to collect, organize and data mining related data in order to summarize the relationship between acupuncture points and mild cognitive dysfunction, and to provide references for clinical treatment. This article standardizes the acupuncture points in the database. This paper uses Excel and SPS software to carry out frequency analysis, cluster analysis and association rules, and draws the rules of acupoints, meridians, positions, frequency of specific acupoints, clustering of acupoints and compatibility. In this paper, the number of cases in the treatment group and the control group, the main acupoints and matching points of the acupuncture prescription, the treatment methods, the efficacy evaluation indicators, and the total effective rate of the treatment group and the control group are extracted into the Excel table to form a mild cognition of acupuncture treatment Prescription database for dysfunction. This article studies the rules and characteristics of acupuncture points derived from data mining, takes the general rules and characteristics of clinical acupuncture and moxibustion treatment as a reference for clinical acupuncture and moxibustion, and verifies it with the results obtained. The experimental results show that in the analysis of association rules, taking Baihui and Shenting as examples, the support degree indicates that the probability that the two acupoints appear in the 126 heads at the same time is 51.83%, and the confidence and support for the occurrence of Baihui and Shenting are relatively high. High, it is considered to be a common compatible point pair for acupuncture treatment of mild cognitive dysfunction.