bluuebunny/crossref_metadata_2025 huggingface dataset:
Full fluid moment model for low temperature magnetized plasmas
Authors: Sahu Rupali , Mansour Adnan R , Hara Kentaro
Published: November 2020

A one-dimensional full fluid moment model is developed to study shear-induced electron transport in low-temperature, partially magnetized plasmas. Ions and electrons are treated as two different fluids that interact with each other through collisions and electromagnetic fields. Conservation of mass, momentum, and energy is solved for both the fluids and the Poisson equation is solved to obtain the electrostatic electric field. A global Lax–Friedrichs flux splitting scheme with a monotonic upwind scheme for conservation laws is used for the inviscid flux calculation. Moments of a shifted Maxwellian distribution that is constructed from the fluid quantities are taken to calculate fluxes at the boundaries, henceforth called the kinetic fluxes. Two full fluid moment models are developed based on the treatment of the electron energy: (i) the total energy and (ii) the internal energy, i.e., temperature. A DC low-temperature magnetized plasma in a Hall effect thruster is modeled using the full fluid moment model and the results are compared with drift-diffusion models that are commonly used for low-temperature plasmas, providing insights into nonclassical electron transport driven by the electron shear in cross-field devices.
Random growth networks with exponential degree distribution
Authors: Ma Fei , Luo Xudong , Wang Ping , Zhu Renbo
Published: November 2020

A great variety of complex networks can be well represented as random graphs with some constraints: for instance, a provided degree distribution, a smaller diameter, and a higher clustering coefficient. Among them, the degree distribution has attracted considerable attention from various science communities in the last few decades. In this paper, we focus mainly on a family of random graphs modeling complex networks that have an exponential degree distribution; i.e., P(k)∼ exp(αk), where k is the degree of a vertex, P(k) is a probability for choosing randomly a vertex with degree equal to k, and α is a constant. To do so, we first introduce two types of operations: type-A operation and type-B operation. By both the helpful operations, we propose an available algorithm A for a seminal model to construct exactly solvable random graphs, which are able to be extended to a graph space S(p,pc,t) with probability parameters p and pc satisfying p+pc=1. Based on the graph space S(p,pc,t), we discuss several topological structure properties of interest on each member N(p,pc,t) itself and find model N(p,pc,t) to exhibit the small-world property and assortative mixing. In addition, we also report a fact that in some cases, two arbitrarily chosen members might have completely different other topological properties, such as the total number of spanning trees, although they share a degree distribution in common. Extensive experimental simulations are in strong agreement with our analytical results.
Lock-in carrierography non-destructive imaging of silicon wafers and silicon solar cells
Authors: Song Peng , Yang Feng , Liu Junyan , Mandelis Andreas
Published: November 2020

Carrier transport and electrical properties are relevant to the performance of semiconductor materials and photovoltaic devices. In recent years, various kinds of high-resolution luminescence-based methods have been proposed to image these properties. Lock-in carrierography (LIC), as a dynamic photoluminescence-based method, has the advantages of self-calibration, higher signal to noise ratio than dc or transient modalities, and high-frequency imaging ability. At the present stage of development, LIC has evolved into homodyne lock-in carrierography and heterodyne lock-in carrierography. In this Perspective, we discuss the principles and theoretical background of both LIC modalities and review experimental systems and methods. In addition, we also provide a brief overview of key LIC applications and future outlook.
Reconstruction of compressed video via non-convex minimization
Authors: Ji Chao , Tian Jinshou , Sheng Liang , He Kai , Xin Liwei , Yan Xin , Xue Yanhua , Zhang Minrui , Chen Ping , Wang Xing
Published: November 2020

This paper studies the sparsity prior to compressed video reconstruction algorithms. An effective non-convex 3DTPV regularization (0 < p < 1) is proposed for sparsity promotion. Based on the augmented Lagrangian reconstruction algorithm, this paper analyzes and compares three non-convex proximity operators for the ℓp-norm function, and numerous simulation results confirmed that the 3DTPV regularization can gain higher video reconstruction quality than the existing convex regularization and is more competitive than the existing video reconstruction algorithms.
Ashok chakra-structured meta-structure as a perfect sound absorber for broadband low-frequency sound
Authors: Bhattacharya Shantanu , Kumar Sanjay , Singh Sanjeet Kumar , Bhushan Pulak , Sahu Megha , Prakash Om
Published: November 2020

We present thin acoustic meta-structures with subwavelength dimensions through which almost perfect sound absorption is achieved in the low-frequency domain. Our overall strategy builds on the fact that the sound absorption capabilities of the meta-structures primarily depend on the geometric dimensions and can easily be reconfigured as per requirements through a change of geometry. To analyze various possibilities, we optimize the geometric structure through hybrid regression analysis using the genetic algorithm approach and finite element-based numerical simulations so that the geometry is tuned for high attenuation of acoustic signals over a broad range of frequencies. Both theoretical and experimental data show good parity and are able to establish the meta-structure nature of the assembly with respect to different frequency bands in the low frequency domain.
Phase-field modeling of the non-congruent crystallization of a ternary Ge–Sb–Te alloy for phase-change memory applications
Authors: Bayle R. , Cueto O. , Blonkowski S. , Philippe T. , Henry H. , Plapp M.
Published: November 2020

The ternary alloy of germanium, antimony, and tellurium (GST) is widely used as a material for phase-change memories. In particular, the stoichiometric compound Ge2Sb2Te5 exhibits a rapid congruent crystallization. To increase the temperature at which spontaneous crystallization erases the stored information, alloys that are enriched in germanium have been investigated. Their crystallization is accompanied by segregation and eventually the nucleation of a new, germanium-rich phase. In order to model the redistribution of alloy components and the time evolution of the microstructure during device operations, we develop a multi-phase-field model for the crystallization of GST that includes segregation and couple it with orientation fields that describe the grain structure. We demonstrate that this model is capable to capture both the emergence of a two-phase polycrystalline structure starting from an initially amorphous material, and the melting and recrystallization during the SET and RESET operations in a memory cell of the “wall” type.
Implosion dynamics and radiation characteristics of preconditioned hybrid X-pinch driven by double pulse current
Authors: Chen Ziwei , Wu Jian , Zhang Daoyuan , Shi Huantong , Lu Yihan , Li Xingwen , Qiu Aici
Published: November 2020

Preconditioned hybrid X-pinch (HXP) experiments have been performed on the Qin-1 facility to investigate the effect of the prepulse current on the implosion dynamics and radiation characteristics. HXPs with molybdenum wires of ∼1.2 mm in length and 25 to 50 μm in diameter have been tested. Driven by the prepulse current, the molybdenum wire is heated to a core-corona structure with a Joule energy deposition of 0.5–4.8 eV/atom, which is smaller than its atomization enthalpy. The radial expansion velocity of the wire core is 0.5–3 km/s. The main current of 450 kA/400 ns is applied ∼610 ns after the prepulse current. The implosion dynamics of the preconditioned HXP is characterized by two-shell structure implosion. Immediately after the main current starts, the current mainly passes through the corona plasma located in a large radius, and the implosion of corona plasma lasts for ∼100 ns until the corona plasma collides with the wire core. Then, the current distribution switches from the corona plasma to the wire core, which results in the onset of implosion of the wire core. The implosion of the wire core generates hot spots and x-ray radiation. The calculated inductance and radius of the current sheath agree with the experimental results. The corona plasma performs as a current switch, which allows the main current passing through the wire core after 100 ns. It indirectly contributes to sharpening the main current used for implosion of the wire core. A single hot spot with x-rays over 2.5 keV is measured using the preconditioned HXP.
Attenuation of pulsation and oscillation using a disk at mid-section of spiked blunt body
Authors: Narayana Gopalakrishna , Selvaraj Saravanan
Published: November 2020

The two most important modes of flow instability are observed on a flat-faced cylinder fitted with a spike, namely, pulsation and oscillation. A new technique is proposed in this article to attenuate both pressure and aerothermal fluctuations over the cylinder by using a circular disk at the mid-length of the sharp-tipped spike, which splits the separation region in front of the cylinder. Shock tunnel experiments are carried out at a free stream Mach number of M∞ = 5.7 and a Reynolds number of RD = 0.5 × 106 (based on the cylinder diameter, D). Aeroheating is measured using platinum thin film sensors painted over the front face of the cylinder. It is shown that the flow pulsation can be totally mitigated for the ratio of spike length to diameter (L/D = 1.0) by using a disk of diameter d/D = 28% at the mid-section of the spike, and the oscillation flow is suppressed using the same disk diameter with L/D = 1.5. This phenomenon is well evident from the measured heat transfer and schlieren data. Besides, a similar analysis showed that the flow fluctuation over an aerospike mounted on a hemispherical blunt body can be diminished with the use of double-aerospike, which, in turn, decreases the heat flux peak in the proximity of the reattachment. This is an effective means of flow fluctuation mitigation and presents to be a good thermal protection for the fore body.
Influence of operating parameters in particle spreading, separation, and capturing in a hybrid free flow magnetophoretic bio-separator
Authors: Samanta Abhishek , Modak Nipu
Published: November 2020

In clinical applications, magnetic bead-based analyte separation has attracted interest over other types of separation techniques in the microfluidic protocol. The objective of the present study is to separate two different types of magnetic and one type of nonmagnetic particles from each other simultaneously with minimum cross-contamination in a microchannel. A numerical study is carried out for characterizing one hybrid microfluidic device. The device works on the principle of split-flow thin fractionation, field-flow fractionation, and free flow magnetophoresis. The geometry of the microfluidic bioreactor had been established by Samanta et al. in 2017, whereas the present research emphasized the impact of operating parameters in particle spreading, separation, and capture in the hybrid free flow magnetophoretic device. The impact of magnetic and fluidic forces on transport, separation, and capture of the three different types of particles is analyzed. The performance of the microfluidic device is checked by capture efficiency and separation indices for different operating conditions. Transport of the three different types of microspheres in the microchannel is prescribed following an Eulerian–Lagrangian model by using an in-house code. Two types of magnetic particles of diameters 2 µm and 1 µm and one nonmagnetic particle of 0.5 µm diameter are used. Some group variables comprising of magnetic and fluidic parameters are found as an exclusive function of capture efficiency and separation index. In addition, from curve fitting, the universal dependence of capture efficiency and separation index on the various group variables is recognized for different curves with a reasonably high degree of compliance.
Using a stochastic forest prediction model to predict the hazardous gas concentration in a one-way roadway
Authors: Xie Chengyu , Chao Lei , Qin Yaguang , Cao Jie , Li Yuhao
Published: November 2020

To accurately and quantitatively analyze the pollutant gas concentration in tunneling roadways, a prediction model of the pollutant gas concentration was proposed and established. Through downhole gas composition data acquisition and correlation analysis, the prediction variables of downhole gas pollution are obtained with both short-term and long-term memory neural network prediction methods and random forest regression modeling methods, making full use of historical target gas concentration data for the future in a short period of time to evaluate the model performance and prediction results. Compared with the results of the stochastic forest regression prediction and the long- and short-term memory neural network prediction, the stochastic forest regression prediction model has a good prediction effect and better generalization effect and is a reliable method with excellent performance for downhole gas concentration prediction. The analysis of the predicted results shows that the change in CO concentration is strongly correlated with CH4 and CO2 and strongly correlated with N2, making it possible to obtain the potential influencing factors of the target gas. These results provide a scientific basis for the prediction of underground pollution gas concentration and the protection and treatment of the atmospheric environment in mining areas.
Theory of molecular emission power spectra. I. Macroscopic quantum electrodynamics formalism
Authors: Wang Siwei , Lee Ming-Wei , Chuang Yi-Ting , Scholes Gregory D. , Hsu Liang-Yan
Published: November 2020

We study the emission power spectrum of a molecular emitter with multiple vibrational modes in the framework of macroscopic quantum electrodynamics. The theory we present is general for a molecular spontaneous emission spectrum in the presence of arbitrary inhomogeneous, dispersive, and absorbing media. Moreover, the theory shows that the molecular emission power spectra can be decomposed into the electromagnetic environment factor and lineshape function. In order to demonstrate the validity of the theory, we investigate the lineshape function in two limits. In the incoherent limit (single molecules in a vacuum), the lineshape function exactly corresponds to the Franck–Condon principle. In the coherent limit (single molecules strongly coupled with single polaritons or photons) together with the condition of high vibrational frequency, the lineshape function exhibits a Rabi splitting, the spacing of which is exactly the same as the magnitude of exciton–photon coupling estimated by our previous theory [S. Wang et al., J. Chem. Phys. 151, 014105 (2019)]. Finally, we explore the influence of exciton–photon and electron–phonon interactions on the lineshape function of a single molecule in a cavity. The theory shows that the vibronic structure of the lineshape function does not always disappear as the exciton–photon coupling increases, and it is related to the loss of a dielectric environment.
Understanding efficiency differences of betavoltaic batteries measured by electron gun mimicked source and radioactive β source
Authors: Zhao Chen , Liu Ao , Bai Song , Zhao Yiying
Published: November 2020

Electron guns have been widely used to mimic the radiation of radioactive β sources in many fields, including radiation effects and material modification, due to their unique advantages such as steerable irradiation area, adjustable electron energy, and flux. However, it is still unclear whether the results and conclusions drawn from the mimicking experiments can provide effective guidance and reference for real radiation. In this work, we systematically investigated the difference of electron guns and radioactive β sources on the efficiency measurement of betavoltaic batteries and gave a quantitative analysis on the causes. Geant 4 simulations of the energy deposition of electrons emitted from electron guns and 63Ni sources demonstrate that the energy dispersion and the incident direction distribution of electrons are the major causes of the difference of the energy deposition ratio and profile in energy conversion units. The single emission direction of electrons leads to an overestimation around 30% in the conversion efficiency measured using an electron gun. The device structure also contributes to the efficiency difference. The efficiency difference of three SiC samples with different structures measured under electron guns and 63Ni sources varies from 20.6% to 32.0% in three samples, which agrees very well with the simulation results. This work provides a valuable guidance to evaluate the results generated from electron-gun mimicked β sources. The physics discussed here would provide good references for other applications using mimicked β sources.
Active matter at high density: Velocity distribution and kinetic temperature
Authors: Caprini Lorenzo , Marini Bettolo Marconi Umberto
Published: November 2020

We consider the solid or hexatic non-equilibrium phases of an interacting two-dimensional system of active Brownian particles at high density and investigate numerically and theoretically the properties of the velocity distribution function and the associated kinetic temperature. We obtain approximate analytical predictions for the shape of the velocity distribution and find a transition from a Mexican-hat-like to a Gaussian-like distribution as the persistence time of the active force changes from the small to the large persistence regime. Through a detailed numerical and theoretical analysis of the single-particle velocity variance, we report an exact analytical expression for the kinetic temperature of dense spherical self-propelled particles that holds also in the non-equilibrium regimes with large persistence times and discuss its range of validity.
Inner and outer scales in turbulent Rayleigh–Bénard convection
Authors: Wei Tie , du Puits Ronald
Published: November 2020

As in other kinds of wall-bounded turbulence, flow and heat transport in turbulent Rayleigh–Bénard convection (RBC) can be divided into an inner layer and an outer layer. This paper refines the traditional inner scales, the Townsend inner scales, by determining the Prandtl number Pr effect, and proposes new scales for the outer layer. Major findings for the inner layer include (i) the mean modified pressure peaks in the inner layer, and the peak location scales with the Townsend inner length scale lν = ν/uinner, where ν is the kinematic viscosity and uinner is the Townsend inner velocity. (ii) The peak value of the mean modified pressure Pmax scales as ΨPρrefuinner2, where ρref is the fluid density and the coefficient ΨP is largely independent of the Reynolds number but is strongly influenced by the Prandtl number. (iii) The thickness of the thermal inner layer scales with a thermal diffusional length scale lα = Ψα α/uinner, where α is the thermal diffusivity and the coefficient Ψα is largely independent of the Reynolds number but is strongly influenced by the Prandtl number. Like passive scalar transport in a pressure-driven turbulent plane Poiseuille flow, the Prandtl number dependence of Ψα (and ΨP) can be approximated by a power law Ψα ∼ ΨP ∼ Prm, where m is a constant of about 0.5. In the outer layer, the vertical component of velocity fluctuation variance at the RBC midplane ⟨ww⟩mp is introduced as a new governing parameter in the scaling of flow and heat transfer. The new outer velocity and temperature scales for turbulent RBC are different from the Deardorff scales, which were developed for convective atmospheric boundary layers. The new outer scales are compared with direct numerical simulation data and experimental measurements.
Immobilisation of Homogeneous Pd Catalysts within a Type I Porous Liquid
Authors: Hemming Ellen B. , Masters Anthony F. , Maschmeyer Thomas
Published: November 2020

An N-heterocyclic carbene-based palladium complex was successfully immobilised on the inner surfaces of hollow silica nanospheres. The external surfaces of these spheres were functionalised with a corona-canopy to produce a Type I porous liquid. To confirm the successful immobilisation of the catalytic precursor, the porous liquid system was explored using the Heck reaction as a model reaction. This work demonstrated that homogeneous catalysts can be successfully immobilised within porous liquids in principle and that the approach used could be readily adapted for the immobilisation of other systems.
How apes get into and out of joint actions
Authors: Genty Emilie , Heesen Raphaela , Guéry Jean-Pascal , Rossano Federico , Zuberbühler Klaus , Bangerter Adrian
Published: November 2020

Compared to other animals, humans appear to have a special motivation to share experiences and mental states with others (Clark, 2006;Grice, 1975), which enables them to enter a condition of ‘we’ or shared intentionality (Tomasello & Carpenter, 2005). Shared intentionality has been suggested to be an evolutionary response to unique problems faced in complex joint action coordination (Levinson, 2006;Tomasello, Carpenter, Call, Behne, & Moll, 2005) and to be unique to humans (Tomasello, 2014). The theoretical and empirical bases for this claim, however, present several issues and inconsistencies. Here, we suggest that shared intentionality can be approached as an interactional achievement, and that by studying how our closest relatives, the great apes, coordinate joint action with conspecifics, we might demonstrate some correlate abilities of shared intentionality, such as the appreciation of joint commitment. We provide seven examples from bonobo joint activities to illustrate our framework.
Usage of social networks by digital natives as a new communication platform for interpersonal communication
Authors: Kahraman Ece , Gokasan Tutku Akter , Ozad Bahire Efe
Published: November 2020

Social Networking Sites (SNS), particularly Facebook (FB) have become extremely popular among digital natives, especially
university-level students. Moreover, they sometimes may see social networks as an extension of their lives (boyd, 2014) which can be called as a new communication platform for interpersonal communication. For the purpose
of the study, interpersonal communication skills (ICS) levels explored in four sub-sections both in the social and e-social
environments.1 Digital natives’ IPC skills were measured to figure out whether there is any
statistically difference between both environments. Interpersonal Communication Skills Inventory (Social Learning, 2002) is used as an
instrument for the present study.
Demystifying Zoophilia: Classification and Psychological Aspects of Humans Having Sexual Relationships with Animals
Authors: Emmett Lisa , Klamert Lisa , Stetina Birgit U.
Published: November 2020

In the course of the present study 445 users of zoophilia forums were asked to complete an online survey measuring social anxiety, self-esteem and empathy. Comparisons between the recruited sample and existing classifications of zoophilia demonstrated that only about a half of the sample (51.5%) stated engaging in sexual activity with animals by answering detailed questions about the nature of their sexual interaction. A large part of the sample for example reported high self-esteem (85.7%) which is inconsistent with previous findings linking zoosexuality to a deficit in selfesteem. In consideration of the findings a new classification of Zoophilia is proposed.
Quantum optics of an oscillator falling into a black hole
Authors: Raine Derek , Abel Paul G
Published: November 2020

We present a quantum optics treatment of the near horizon behaviour of a quantum oscillator freely-falling into a pre-existing Schwarzschild black hole. We use Painlevé–Gullstrand coordinates to define a global vacuum state. In contrast to an accelerated oscillator in the Minkowski vacuum, where there is no radiation beyond an initial transient, we find that the oscillator radiates positive energy to infinity and negative energy into the black hole as it attempts to come into equilibrium with the ambient vacuum. We discuss the relationship of the model to Hawking radiation.
Corrigendum: Motion of the gyroscope with equal conserved angular momenta (2020 Eur. J. Phys.
41 025004)
Authors: Tanrıverdi V
Published: November 2020

In the article ‘Motion of the gyroscope with equal conserved angular momenta’ (Tanrıverdi 2020 Eur. J. Phys.
41 025004), we have mentioned that spin reversal is possible, but it is only possible for a ‘pseudotop’ or ‘mathematical top’, not for a physical top.
Charge-induced high-performance actuation of borophene
Authors: Thanh Vuong V , Van Nguyen D , Truong Do V , Hung Nguyen T
Published: November 2020

Borophene, a two-dimensional material, has grown fast in the nanomaterials field because of its unique electronic and mechanical properties. In this work, we demonstrate that the unique properties of borophene make this material with a high-performance electromechanical actuator by using first-principles calculations. We find a high Young’s modulus about 376.55 N m−1 of a striped borophene, which is larger than that of graphene (∼336 N m−1) in the unit of N m−1. In addition, upon hole injection, maximum actuator strain is up to 1.67% that is over 7 times larger than that of graphene at the same value of hole doping (0.04 e/atom). Therefore, the striped borophene shows a high work-area-density per cycle of 22 MJ m−3·nm, it is approximately 28 and 11 times larger than that of graphene (0.78 MJ m−3·nm) and metallic 1T-MoS2 (2.05 MJ m−3·nm), respectively. Furthermore, the striped borophene still maintains the metal property under charge doping. Thus, an actuator device based on borophene can work under a low applied voltage. Finally, the charge doping effects on the mechanical strength of borophene are investigated. Interestingly, the mechanical strength is increased by 15.8% in the case of electron doping.
High-sensitivity photoelectrochemical visible-blind ultraviolet detector using SrTiO3 nanocrystalline for weak irradiation
Authors: Zhu Ziran , Wei Kun , Li Hui , Li Xiaopeng , Li Baoping , Gu Xiuyun , Chen Lulu , Zhou Jinyuan , Pan Xiaojun , Wang Youqing
Published: November 2020

We have demonstrated a photoelectrochemical solar-blind ultraviolet (UV) detector based on SrTiO3 (STO) nanocrystalline film in this work. The assembled UV detector presents a high on/off ratio of about 6433 under periodic UV irradiation, a high photocurrent density of 220.6 μA cm−2, and a fast response time of 9 ms. By introducing a block layer (BL) on fluorine-doped tin oxide substrate, the response and decay times are shortened to 6 ms and 8 ms, respectively. The BL plays a crucial part in hindering the recombination of electrons from electrolyte carriers and avoiding short circuits. Due to its excellent light capture capability, the detector based on SrTiO3 nanocrystalline exhibits high sensitivity to weak UV light (5 μW cm−2). Moreover, the detector also exhibits visible-blind characteristics and a good linear response.
Non-volatile reconfigurable spin logic device: parallel operations
Authors: Patra Moumita , Shukla Alok , Maiti Santanu K
Published: November 2020

A new proposal is given for designing a non-volatile, completely spin logic device, that can be reprogrammed for different functional classical logical operations. We use the concept of bias driven spin dependent circular current and current induced magnetic field in a quantum ring under asymmetric ring-to-electrode interface configuration to implement all the Boolean operations. We extend our idea to build two kinds of parallel computing architectures for getting parallelized operations, all at a particular time. For one case, different kinds of parallel operations are performed in a single device, whereas in the other type all the possible inputs of a logic gate are processed in parallel and all the outputs are read simultaneously. The performance and reliability are investigated in terms of power, delay and power-delay-product and finally the system temperature. We find that both the individual and simultaneous logic operations studied here are much superior compared to the operations performed in different conventional logic families like complementary metal oxide semiconductor logic, transistor-transistor logic, etc. The key advantage is that we can perform several logic operations, as many as we wish, repeating the same or different logic gates using a single setup, which indeed reduces wiring in the circuits and hence consumes much less power. Our analysis can be utilized to design optimized logic circuits an nano-scale level.
Current–voltage characteristics and photovoltaic effect of a Au/ZnFe2O4/GaN Schottky junction
Authors: Ghimire Santosh , Dho Joonghoe
Published: November 2020

A Au/ZnFe2O4/GaN Schottky junction with a semiconducting heteroepitaxial ZnFe2O4 insertion layer was prepared by using a combined synthesis process of pulsed laser deposition and sputtering. The current–voltage (I–V) and capacitance–voltage (C–V) characteristics of the Schottky junction, as well as its photovoltaic effect, were investigated under dark conditions or ultraviolet (UV) or blue illumination. Insertion of the semiconducting ZnFe2O4 interlayer clearly induced an increase in the rectification ratio. Based on I–V measurements in a forward bias region, the barrier height and ideality factor of the Au/ZnFe2O4/GaN junction were estimated to be about 0.89 eV and 1.58, respectively. On the other hand, C–V measurement in a reversed bias region suggested a relatively larger barrier height of ∼1.32 eV. The Au/ZnFe2O4/GaN junction showed an open-circuit voltage of ∼0.5 V under UV light and a clear switching photocurrent behavior with UV ON/OFF. A schematic band model with two interfaces, Au/ZnFe2O4 and ZnFe2O4/GaN, was proposed to explain the measured barrier heights in forward and reverse bias regions.
Effect of carbon nanotexture on the synthesis, initial growth mechanism and photoluminescence properties of SiC nanowires
Authors: Xie Xiangmin , Su Zhe’an , Huang Dong , Yang Cheng , Wang Yafeng , He Kejian , Huang Qizhong
Published: November 2020

Although the spontaneous vapor–solid growth of SiC nanowires is a well-established phenomenon, the exact mechanism by which nanowires grow on substrates is still poorly understood. Here, we studied the initial growth of SiC nanowires on carbon sources with different nanotextures via a catalyst-free vapor reaction between a polyacrylonitrile-based carbon fiber and a silicon powder. The results revealed that the SiC nanowires were preferentially formed on the carbon fiber with a higher degree of graphitization. Detailed analyses suggested that the growth behavior of the underlying SiC film formed on the carbon fibers, which is strongly affected by the microstructures of the carbon fibers, plays an important role in the formation of nanowires. In addition, the photoluminescence spectrum of SiC nanowires showed strong ultraviolet–visible emission peaks at an excitation wavelength of 250 nm, which may provide potential applications in the field of optoelectronic devices.
A nonexistence result for anisotropic problems
*
Authors: Le Phuong , Le Kim Anh T , Dinh Phuoc Vinh
Published: November 2020

We study the anisotropic problem

−

∑

i
=
1

N

∂

∂

x

i

∂
u

∂

x

i

p

i

−
2

∂
u

∂

x

i

=
w
f

(

u

)

in

Ω
,

u
=
0

on

∂
Ω
,

where p

i
⩾ 2, Ω is a domain of

R

N

, w is a nonnegative function and f is an increasing function. We prove that the problem has no nontrivial stable solution under various assumptions on p

i
, Ω, w and f.
Ab initio theory of the impact of grain boundaries and substitutional defects on superconducting Nb3Sn
Authors: Kelley Michelle M , Sitaraman Nathan S , Arias Tomás A
Published: November 2020

Grain boundaries play a critical role in superconducting applications of Nb3Sn: in dc applications, grain boundaries preserve the material’s inherently high critical current density by pinning flux, while in ac applications grain boundaries can provide weak points for flux entry leading to significant dissipation. We present the first ab initio study to investigate the physics of different grain boundary types in Nb3Sn and their impact on superconductivity using density-functional theory. We identify an energetically favorable selection of high-angle tilt and twist grain boundaries of distinct orientations. We find that clean grain boundaries free of point defects reduce the Fermi-level density of states by a factor of two, an effect that decays back to the bulk electronic structure ∼1–1.5 nm from the boundary. We further calculate the binding free-energies of tin substitutional defects to multiple boundaries, finding a strong electronic interaction that extends to a distance comparable to that of the reduction of density of states. Associated with this interaction, we discover a universal trend in defect electronic entropies near a boundary. We then probe the effects of defect segregation on grain boundary electronic structure and calculate the impact of substitutional impurities on the Fermi-level density of states in the vicinity of a grain boundary. We find that titanium and tantalum defects have little impact regardless of placement, whereas tin, copper, and niobium defects each have a significant impact but only on sites away from the boundary core. Finally, we introduce a model for a local superconducting transition temperature and consider how grain boundary composition affects

T

c

as a function of distance from the boundary plane. The methodology established in this manuscript can be applied to other A15 superconductors in addition to Nb3Sn.
Coupling between guided modes of two parallel nanofibers
Authors: Kien Fam Le , Ruks Lewis , Nic Chormaic Síle , Busch Thomas
Published: November 2020

We study the coupling between the fundamental guided modes of two identical parallel nanofibers analytically and numerically. We calculate the coefficients of directional coupling, butt coupling, and self coupling as functions of the fiber radius, the light wavelength, and the fiber separation distance. We show that, due to the symmetry of the system, a mode of a nanofiber with the principal quasilinear polarization aligned along the axis joining the nanofibers or the perpendicular axis is coupled only to the mode with the same corresponding principal polarization of the other nanofiber. We find that the effects of the butt coupling and the self coupling on the power transfer are significant when the fiber radius is small, the light wavelength is large, or the fiber separation distance is small. We show that the power transfer coefficient may achieve a local maximum or become zero as the fiber radius, the light wavelength, or the fiber separation distance varies.
Enhancing the EEG classification in RSVP task by combining interval model of ERPs with spatial and temporal regions of interest
Authors: Li Bowen , Lin Yanfei , Gao Xiaorong , Liu Zhiwen
Published: November 2020

Objective. Brain–computer interface (BCI) systemsdirectly translate human intentions to instructions for machines by decoding the neural signals. The rapid serial visual presentation (RSVP) task is a typical paradigm of BCIs, in which subjects can detect the targets in the high-speed serial images. There are still two main challenges in electroencephalography (EEG) classification for RSVP tasks: inter-trial variability of event-related potentials (ERPs) and limited trial number of EEG training data.
Approach.
This study proposed an algorithm of discriminant analysis and classification for interval ERPs (DACIE) in RSVP tasks. Firstly, an interval model of ERPs was exploited to solve the inter-trial variability problem. Secondly, a spatial structured sparsity regularization was utilized to reinforce the important channels, which provided a spatial region of interest (sROI). Meanwhile, a temporal auto-weighting technique was conducted to emphasize the important discriminant components, which obtained a temporal regions of interest (tROIs). Thirdly, classification features were obtained by the discriminant eigenvalue analysis to avoid the ill-conditioned estimation of covariance matrix caused by fewer training trials.
Main results.
EEG datasets of 12 subjects in RSVP tasks were analyzed to evaluate the classification performance of proposed algorithm. The average accuracy rate, true positive rate, false positive rate and AUC value are 96.9%, 81.6%, 2.8% and 0.938, respectively. Compared with several state-of-the-art algorithms, the proposed algorithm can provide significantly better classification performance.
Significance.
The interval model of ERPs was exploited in a spatial linear discriminant framework to overcome the inter-trial variability. The sROIs and tROIs were explored to reinforce the pivotal channels and temporal components. And the proposed algorithm can provide good performance with fewer training trials.
Predicting PTSD severity using longitudinal magnetoencephalography with a multi-step learning framework
Authors: Zhang Jing , Wong Simeon M , Richardson J Don , Jetly Rakesh , Dunkley Benjamin T
Published: November 2020

Objective. The present study explores the effectiveness of incorporating temporal information in predicting post-traumatic stress disorder (PTSD) severity using magnetoencephalography (MEG) imaging data. The main objective was to assess the relationship between longitudinal MEG functional connectome data, measured across a variety of neural oscillatory frequencies and collected at two timepoints (Phase I and II), against PTSD severity captured at the later time point. Approach. We used an in-house developed informatics solution, featuring a two-step process featuring pre-learn feature selection (CV-SVR-rRF-FS, cross-validation with support vector regression (SVR) and recursive random forest feature selection) and deep learning (long-short term memory recurrent neural network, LSTM-RNN) techniques. Main results. The pre-learn step selected a small number of functional connections (or edges) from Phase I MEG data associated with Phase II PTSD severity, indexed using the PTSD CheckList (PCL) score. This strategy identified the functional edges affected by traumatic exposure and indexed disease severity, either permanently or evolving dynamically over time, for optimal predictive performance. Using the selected functional edges, LSTM modelling was used to incorporate the Phase II MEG data into longitudinal regression models. Single timepoint (Phase I and Phase II MEG data) SVR models were generated for comparison. Assessed with holdout test data, alpha and high gamma bands showed enhanced predictive performance with the longitudinal models comparing to the Phase I single timepoint models. The best predictive performance was observed for lower frequency ranges compared to the higher frequencies (low gamma), for both model types. Significance. This study identified the neural oscillatory signatures that benefited from additional temporal information when estimating the outcome of PTSD severity using MEG functional connectome data. Crucially, this approach can similarly be applied to any other mental health challenge, using this effective informatics foundation for longitudinal tracking of pathological brain states and predicting outcome with a MEG-based neurophysiology imaging system.
Intermittent resetting potentials
Authors: Mercado-Vásquez Gabriel , Boyer Denis , Majumdar Satya N , Schehr Grégory
Published: November 2020

We study the non-equilibrium steady states (NESS) and first passage properties of a Brownian particle with position X subject to an external confining potential of the form V(X) = μ|X|, and that is switched on and off stochastically. Applying the potential intermittently generates a physically realistic diffusion process with stochastic resetting toward the origin, a topic which has recently attracted a considerable interest in a variety of theoretical contexts but has remained challenging to implement in lab experiments. The present system exhibits rich features, not observed in previous resetting models. The mean time needed by a particle starting from the potential minimum to reach an absorbing target located at a certain distance can be minimized with respect to the switch-on and switch-off rates. The optimal rates undergo continuous or discontinuous transitions as the potential strength μ is varied across non-trivial values. A discontinuous transition with metastable behavior is also observed for the optimal strength at fixed rates.
Prediction of learning behavior based on improved random forest algorithm
Authors: Xia Xiaona
Published: November 2020

The research of learning behaviors is the premise of improving the learning process and results. The scale, composition and quality of the corresponding dataset will have the key impacts on research methods. Based on big dataset of learning behaviors, this study demonstrates the rules of learning behaviors, uses intelligent learning algorithms to analyze data and predict trends. Based on data characteristics, this paper evolves random forest algorithm and constructs the data structure. Taking the assessment results of learners as the test targets, the data samples are divided into two parts: train set and test set. Through the train set, we design the data model. With the help of the test set, the optimal model is finally selected, that is, the learning interaction activities are predicted and estimated. The research shows that learning behaviors have predictability and guidance, transferability and adjustability, groupness and personality. Based on this conclusion, the data analysis scheme of learning platforms is designed, which will help to improve the platform construction and learning behaviors.
One target classification method based on target feature distribution fusion
Authors: Luan Zhuzheng , Gu Bing , Wang Jinfeng , Yu Chenglong , Xu Lei
Published: November 2020

Target classification technology is an important method to improve the operational performance of radar in complex electromagnetic environment, as well as an important means to reduce radar false alarm. In this paper, according to the randomness of target plot parameters, a feature prior model is established to fuse the features distribution of true/false targets based on Bayesian estimation so as to achieve intra-feature information fusion. Under the guidance of the classification hyper-plane, feature dimension reduction is conducted to multi-dimension Gauss distribution after fusion, so as to achieve inter-feature information fusion and obtain 1-D Gauss probability distribution of target features. The target probability is obtained according to the vector distance integral of the target, thus the target classification is completed according to the probability threshold. This paper makes analysis, calculation and simulation to target classification algorithm under the features of 1-D, 2-D, 3-D and multi-dimension so as to validate the effectiveness of the proposed method.
An improved priority heuristic for the fixed guillotine rectangular packing problem
Authors: Shang Zhengyang , Pan Mingming , Pan Jiabao
Published: November 2020

An improved priority heuristic (IPH) is presented for the guillotine rectangular packing problem with a fixed orientation constraint. This algorithm can continuously divide the remaining space into blocks and recursively layout the entire space by filling each current block. IPH inherits the placement method of PH and adopts an improved space partitioning rule. The partitioning rule comprehensively considers the effects of the newly generated block on subsequent item placement. Thus, the remaining space can be filled as much as possible from a probability perspective. Given the introduction and utilization of different solving parameters, the worst-case time complexity is O(40n
2). Computational results on benchmark datasets show that IPH outperforms existing heuristics on average. For large-scale instances, several perfect layouts can be obtained for the first time.
Single-phase ground fault identification method for distribution network based on inception model and sample expansion
Authors: Zhu Jiran , Chen Kai , Peng Zhonghan , Zhang Hailong , Wan Xingchen , Zhu Daoge
Published: November 2020

A single-phase ground fault identification method based on inception model and sample expansion was proposed in this paper. Based on the basic characteristics of the inception model, a hybrid inception model structure is constructed to enhance the width and depth of the network and reduce network parameters. Combined with the training sample expansion method, the model is fully trained to adapt to the single-phase ground-fault current characteristics of the distribution network. The experimental results show that the accuracy for the hybrid inception model structure to the single-phase ground-fault current of the distribution network is 94.21%. After the sample is expanded, the recognition accuracy rate can be further improved by 97.52%.
An empirical study on the evaluation of the open sharing capability of meteorological data based on the data of 5 provincial meteorological departments
Authors: Shen Danna , He Jieying , Li Yan , Lu Yicen
Published: November 2020

Data sharing benefit evaluation is an important guarantee for the continued stable construction and application of data sharing projects and an important basis for making data application policies. Although meteorological data is an essential part of the basic strategic resources of national big data, through domestic and foreign research, there is no comprehensive system research on the comprehensive capabilities of data sharing services, especially on the meteorological industry. Therefore, writers of this paper establish an evaluation model for open sharing of meteorological data, select the open sharing capability of meteorological data from five representative provincial meteorological departments in China for pilot evaluation and empirical analysis, and then propose the applicability of the meteorological data sharing policy, unified meteorological data sharing service platform, overall planning and allocation of meteorological data resources and other policy recommendations.
Research on stable control communication network platform for multi-source big data fusion
Authors: Gao Jian , Song Guorui , Xu Yujie , He Jinhong
Published: November 2020

With the rapid development of large power grid, the demand for real-time, efficient and reliable applications of different services is also increasing. In this paper, based on the architecture of control and protection private network, we studied the new stable control test system and communication network scheme, proposed the multi-source data real-time transmission and interactive processing architecture of machine side, network side and load side. And we built a digital analog hybrid simulation test platform to verify its overall architecture, functions and key technologies in the test environment. Finally, we tested the reliability and rapidity indexes of communication network transmission protocol, interface and information transmission, at the same time gave some feasible suggestions for engineering application in actual power grid by taking business flow simulation as an example. It lays a foundation for engineering application and popularization.