bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of actuation mode on plasma-induced spanwise flow oscillations
Authors: Hehner Marc T , Gatti Davide , Kotsonis Marios , Kriegseis Jochen 
Published: February 2022

Abstract
Two different plasma actuation strategies for producing near-wall flow oscillations, namely the burst-modulation and beat-frequency mode, are characterized with planar particle image velocimetry in quiescent air. Both concepts are anticipated to work as non-mechanical surrogates of oscillating walls aimed at turbulent flow drag reduction, with the added benefit of no moving parts, as the fluid is purely manipulated by plasma-generated body forces. The current work builds upon established flow-control and proof-of-concept demonstrators, as such, delivering an in-depth characterization of cause and impact of the plasma-induced flow oscillations. Various operational parameter combinations (oscillation frequency, duty cycle and input body force) are investigated. A universal performance diagram that is valid for plasma-based oscillations, independent of the actuation concept is derived. Results show that selected combinations of body force application methods suffice to reproduce oscillating wall dynamics from experimental data. Accordingly, the outcomes of this work can be exploited to create enhanced actuation models for numerical simulations of plasma-induced flow oscillations, by considering the body force as a function of the oscillation phase. Furthermore, as an advantage over physically displaced walls, the exerted body force appears not to be hampered by resonances and therefore remains constant independent of the oscillation frequency. Hence, the effects of individual parameter changes on the plasma actuator performance and fluid response as well as strategies to avoid undesired effects can be determined.
Polarised superlocalization in magnetic nanoparticle hyperthermia
Authors: Iszály Zsofia , Gresits Iván , Márián István Gábor , Thuróczy György , Sági Oliver , Márkus Bence Gábor , Simon Ferenc , Nandori Istvan 
Published: February 2022

Abstract
Magnetic hyperthermia is an adjuvant therapy for cancer where injected magnetic nanoparticles are used to transfer energy from the time-dependent applied magnetic ﬁeld into the surrounding medium. Its main importance is to be able to increase the temperature of the human body locally. This localization can be further increased by using a combination of static and alternating external magnetic ﬁelds. For example, if the static ﬁeld is inhomogeneous and the alternating ﬁeld is oscillating then the energy transfer and consequently, the heat generation is non-vanishing only where the gradient ﬁeld is zero which results in superlocalization. Our goal here is to study theoretically and experimentally whether the perpendicular or parallel combination of static and oscillating ﬁelds produce a better superlocalization. A considerable polarisation eﬀect in superlocalization for small frequencies and large ﬁeld strengths which are of great importance in practice is found.
H2O2 adsorption and dissociation on various CeO2 (111) surface models: a first-principles study
Authors: Brugnoli Luca , Urata Shingo , Pedone Alfonso 
Published: February 2022

Abstract
Periodic density functional theory (DFT) calculations using the hybrid PBE0 functional and atom-centered Gaussian functions as basis sets were carried out to investigate the absorption and the first steps involved in the decomposition of hydrogen peroxide (H2O2) on three different models of the ceria (111) surface. One of the models is a clean surface, and the others are defective and partially hydroxylated ceria surfaces. On the clean surface, we found that the minimum energy path of hydrogen peroxide decomposition involves a three-step process, i.e., adsorption, deprotonation, and formation of the peroxide anion, stabilized through its interaction with the surface at a Ce (IV) site, with activation barriers of less than about 0.5 eV. The subsequent formation of superoxide anions and molecular oxygen species is attributed to electron transfer from the reactants to the Ce (IV) ions underneath. On the defective surface, H2O2 dissociation is an energetically downhill reaction thermodynamically driven by the healing of the O vacancies, after the reduction and decomposition of H2O2 into oxygen and water. On the hydroxylated surface, H2O2 is first adsorbed by forming a favorable H-bond and then undergoes heterolytic dissociation, forming two hydroxyl groups at two vicinal Ce sites.
N, P, O-codoped biochar from phytoremediation residues: a promising cathode material for Li–S batteries
Authors: Zhong Mei’e , Sun Jingchun , Shu Xiaoqing , Guan Jindiao , Tong Gongsong , Ding Hao , Chen Liying , Zhou Nan , Shuai Yi 
Published: February 2022

Abstract
Environment and energy are two key issues in today’s society. In terms of environmental protection, the treatment of phytoremediation residues has become a key problem to be solved urgently, while for energy storage, it tends to utilize low-cost and high specific energy storage materials (i.e. porous carbon). In this study, the phytoremediation residues is applied to the storage materials with low-cost and high specific capacity. Firstly, the phosphorous acid assisted pyrolysis of oilseed rape stems from phytoremediation is effective in the removal of Zn, Cu, Cd and Cr from the derived biochar. Moreover, the derived biochar from phytoremediation residues shows abundant porous structure and polar groups (–O/–P/–N), and it can deliver 650 mAh g−1 with 3.0 mg cm−2
sulfur, and keeps 80% capacity after 200 cycles when employing it as a sulfur host for lithium–sulfur (Li–S) batteries. Hence, phosphorous acid assisted pyrolysis and application in Li–S battery is a promising approach for the disposal of phytoremediation residues, which is contributed to the environmental protection as well as energy storage.
Surface amorphous coating for an economical and high-stability current collector for rechargeable aluminum-ion batteries
Authors: Guo Hanlin , Zhou Rui , Li Xu , Li Zhenhu , Liu Shuangyi 
Published: February 2022

Abstract
Rechargeable aluminum-ion batteries (AIBs) are regarded as the next-generation energy storage devices due to their low flammability, low cost and high power density as well as abundant aluminum (Al) reserves. However, these popular ionic liquid electrolytes contain highly corrosive acid, which always corrodes the most used positive current collector, thus hindering the commercialization of AIBs. This study proposes an efficient and economical method of coating amorphous Ni3S2 compound on a nickel metal current collector (Ni-S/Ni). The conductivity and the onset oxidation potential of amorphous Ni3S2 coating can be up to 2.3 × 106 S m−1 and 2.7 V respectively. A Ni-S/Ni current collector can provide excellent cycling stability with no electrochemical corrosion in the AIBs. The AIBs fabricated using a Ni-S/Ni current collector exhibits a specific capacity of 65 mAh/g at 1 A g−1, high coulombic efficiency of 99% and cyclability of at least 2000 cycles. Moreover, the total cost of the Ni-S/Ni current collector can be limited to less than 3.3 USD/m2. The comprehensive performances of these AIBs are better than most reported results so far, which indicates that this method can advance the commercialization of AIBs.
Long-range medical image registration through generalized mutual information (GMI): towards a fully automatic volumetric alignment
Authors: Vianna Vinicius Pavanelli , Murta Luiz Otavio 
Published: February 2022

Abstract

Objective. Mutual information (MI) is consolidated as a robust similarity metric often used for medical image registration. Although MI provides a robust registration, it usually fails when the transform needed to register an image is too large due to MI local minima traps. This paper proposes and evaluates Generalized MI (GMI), using Tsallis entropy, to improve affine registration. Approach. We assessed the GMI metric output space using separable affine transforms to seek a better gradient space. The range used was 150 mm for translations, 360° for rotations, [0.5, 2] for scaling, and [−1, 1] for skewness. The data were evaluated using 3D visualization of gradient and contour curves. A simulated gradient descent algorithm was also used to calculate the registration capability. The improvements detected were then tested through Monte Carlo simulation of actual registrations with brain T1 and T2 MRI from the HCP dataset. Main results. Results show significantly prolonged registration ranges, without local minima in the metric space, with a registration capability of 100% for translations, 88.2% for rotations, 100% for scaling and 100% for skewness. Tsallis entropy obtained 99.75% success in the Monte Carlo simulation of 2000 translation registrations with 1113 double randomized subjects T1 and T2 brain MRI against 56.5% success for the Shannon entropy. Significance. Tsallis entropy can improve brain MRI MI affine registration with long-range translation registration, lower-cost interpolation, and faster registrations through a better gradient space.
Quantum corrected polymer black hole thermodynamics: mass relations and logarithmic entropy correction
Authors: Mele Fabio M. , Münch Johannes , Pateloudis Stratos 
Published: February 2022

Abstract
In this paper, we continue the analysis of the effective model of quantum Schwarz­schild black holes recently proposed by some of the authors in [1,2]. In the resulting quantum-corrected spacetime the central singularity is resolved by a black-to-white hole bounce, quantum effects become relevant at a unique mass-independent curvature scale, while they become negligible in the low curvature region near the horizon and classical Schwarzschild geometry is approached asymptotically. This is the case independently of the relation between the black and white hole masses, which are thus freely specifiable independent observables. A natural question then arises about the phenomenological implications of the resulting non-singular effective spacetime and whether some specific relation between the masses can be singled out from a phenomenological perspective. Here we focus on the thermodynamic properties of the effective polymer black hole and analyze the corresponding quantum corrections as functions of black and white hole masses. The study of the relevant thermodynamic quantities such as temperature, specific heat, and horizon entropy reveals that the effective spacetime generically admits an extremal minimal-sized configuration of quantum-gravitational nature characterized by vanishing temperature and entropy. For large masses, the classically expected results are recovered at leading order and quantum corrections are negligible, thus providing us with a further consistency check of the model. The explicit form of the corrections depends on the specific relationship among the masses. In particular, a first-order logarithmic correction to the black hole entropy is obtained for a quadratic mass relation. The latter corresponds to the case of proper finite-length effects which turn out to be compatible with a minimal length generalized uncertainty principle associated with an extremal Planck-sized black hole.
Representation of the coherent state for a beam splitter operator and its applications
Authors: Zhan Mingxia , Jia Fang , Huang Jiali , Zhang Huan , Hu Liyun 
Published: February 2022

Abstract
A beam splitter operator is a very important linear device in the field of quantum optics and quantum information. It can not only be used to prepare complete representations of quantum mechanics, entangled state representation, but it can also be used to simulate the dissipative environment of quantum systems. In this paper, by combining the transform relation of the beam splitter operator and the technique of integration within the product of the operator, we present the coherent state representation of the operator and the corresponding normal ordering form. Based on this, we consider the applications of the coherent state representation of the beam splitter operator, such as deriving some operator identities and entangled state representation preparation with continuous-discrete variables. Furthermore, we extend our investigation to two single and two-mode cascaded beam splitter operators, giving the corresponding coherent state representation and its normal ordering form. In addition, the application of a beam splitter to prepare entangled states in quantum teleportation is further investigated, and the fidelity is discussed. The above results provide good theoretical value in the fields of quantum optics and quantum information.
Resolving challenges of monitoring PV systems: a case study for three 1.5 kW generators in Lima, Peru
Authors: Berastain A E , Conde L A , Angulo J , Carhuavilca A M , García M , Sevillano-Bendezú M A , Montes-Romero J , De la Casa J , Chirinos L , Töfflinger J A 
Published: February 2022

Abstract
This paper addresses challenges from monitoring three grid-connected PV systems with different module technologies in Lima, Peru, following the International Electrotechnical Commission (IEC) standards. Missing and erroneous data due to sensor malfunction or partial shadowing can negatively impact the measured data quality. We developed a program to automatically detect erroneous measurements, enhance the data quality, and calculate PV performance parameters following the IEC-61724 standard to resolve these challenges. The program includes mathematical methods to replace faulty or missing measurements. Finally, we present the impact of the algorithms for erroneous data detection, deletion, and correction on performance calculations.
Global solar radiation time series forecasting using different architectures of the multilayer perceptron model
Authors: Peñalva J J , Lozano D A , Murillo J C , Ortega F M 
Published: February 2022

Abstract
In this work, the multilayer perceptron model was used to forecast the time series of global solar radiation for a near future about a week. Different architectures of this model were built through varying its different hyperparameters such as optimizers, activation functions, number of neurons and neuron dropout in which their performance was evaluated using error metrics. It was found that the architectures (60, SGD, Sigmoid), (10, Adam, Relu) and (60, SGD, Sigmoid) presented an R2 around 0.877, 0.873 and 0.872, respectively. The architecture with neuron dropout (150, SGD, Sigmoid, 0.2) presented a higher performance among all the architectures evaluated and its R2 value was 0.884. Architectures with higher performance are used to predict future values of solar radiation.
Application of machine learning and deep learning in mask detection
Authors: Wang Zihan , Xu Xuefei 
Published: February 2022

Abstract
The world witnessed the outbreak of coronavirus disease (COVID-19) at the end of 2019. Even in the 2021, this disease still caused difficulties and inconvenience to millions of people. COVID-19 pandemic has made it a necessity for almost everyone to wear a facial mask as a protective measure. There are several methods to detect masked face, including deep learning and machine learning, which constitutes an integral part on people’s normal life. In order to find a faster and more convenient way to detect whether people wearing masks, this paper compared advantages and disadvantages between deep learning and machine learning based on existing literature, and proposed the most suitable method for detecting masks under different practical conditions. Therefore, we can monitor whether people wear masks correctly and give them timely guidance.
Research on path planning algorithm of intelligent inspection robot
Authors: Wang Yuechao , Mai Ying , Wen Weijian 
Published: February 2022

Abstract
With the development of intelligent inspection robot technology, inspection robots are widely used in substations to complete the inspection work of substations and move toward intelligent inspection. At present, substations begin to reduce the number of inspection personnel, reduce labor costs, and improve inspection efficiency and ensure the safe operation of electrical equipment in substations by using inspection robots to conduct intelligent inspection of substation equipment. The algorithm is used to realize the path planning of the inspection robot and model the substation environment.
RGBD salient object detection based on depth feature enhancement
Authors: Shi Yue , Yu Wanjun , Guan Qianxun 
Published: February 2022

Abstract
The depth map contains spatial location information, which has been proven to be beneficial for RGBD salient object detection. However, the quality of the depth map will directly affect the accuracy of RGBD saliency detection. In order to solve the problem of different quality of depth maps, a detection model based on depth enhancement is designed to enhance the available depth information and filter low-quality depth maps. By comparing four evaluation indicators with five advanced models, the experimental results show that the model in this paper is advanced.
Dynamic effectiveness evaluation of weapon system based on PFCSM method
Authors: Hu Lei , Yi Guoxing , Nan Yi , Zhao Hui , Wang Hao , Cao Zhihui 
Published: February 2022

Abstract
Aiming at the problem of weapon system dynamic effectiveness evaluation, this paper proposes the weapon system dynamic effectiveness evaluation method based on probability finite combination state machine. The method can formally describe the key nodes in the whole process of weapon system operation in the way that states, inputs and transfer functions were applied to characterize the dynamic evolution of weapon system operation effectiveness, consequently, the operation effectiveness of the whole life cycle of weapon system can be evaluated. Taking the sea-skimming missile attacking warship as an example, we dynamically evaluate the operational effectiveness of the anti-ship missile in the whole life cycle and find the key nodes which cause the change of operational effectiveness, consequently, the dynamic effectiveness evaluation can provide auxiliary decision-making support for the optimization of combat planning. The reliability, dynamics, applicability and expansibility of the proposed method were analysed in conclusion.
Quality Evaluation Method for Settlement Data Matching Based on Grey Correlation Analysis
Authors: Jiao Yangyang , liu Pingzhi , Qi Peixin 
Published: February 2022

Abstract
To solve the problem that the quality of spatial data matching is difficult to evaluate, this paper proposes a method of matching quality evaluation based on grey correlation machine learning analysis, it’s a method that takes settlement data for example and utilizes the weight of matching index. The method can be performed through the following steps: first, measure the location, area, orientation delta of the settlement entity, and analyzes its grey correlation relationship, then the paper gets the weight of each kind of graphic data delta; second, calculate the graphic data delta of identical entity in original matching data to judge whether the matching relationship is correct. Experiments illustrate that the method is more feasible and practical, for it can measure the graphic data delta and weight effectively and practically and detect the mistakes of original matching data.
Study on fault feature extraction of ECS turbine bearing by combination of EEMD and HMM
Authors: Yan Jianqiang , Yu Jiangyun , Zhuang Weidong , Li Long , Chen Yongwei 
Published: February 2022

Abstract
According to nonstationary characteristics of aircraft environment control system turbine bearings, the objective in the paper is to present EEMD and HMM method to extract characteristic quantities. Firstly, vibration signals under different operating conditions, such as normal bearing and cage fracture under partial load condition, are decomposited by EEMD to filter noise signal and advance signal-to-noise. Then HMM of those signals is calculated, contrasted and analyzed after space reconstruction. The experimental result show that the HMM can be used as the characteristic quantity of ECS turbine bearing on running state. Moreover, this method can accurately and effectively identify the running state of the bearing.
CFETR Nb3Sn coil in heat treatment deformation analysis and fixture designing
Authors: Song Jian , Wu Yu , Han Houxiang 
Published: February 2022

Abstract
According to the research, it is found that the Hybrid Magnet coils, JT-60SA, ITER and CSMC coils are fixed by coils during heat treatment in order to prevent the coils deforming due to the release of residual stress. Since the penultimate process step of CFETR CSMC Nb3Sn coil manufacturing process is the final assembly of the coil, the theoretical value of the initial unilateral gap between Nb3Sn inner and outer coils is 27.4mm, and the theoretical value of the initial unilateral gap between Nb3Sn outer coil and NbTi coil is 50mm. This gap will be reduced in each process of coil manufacturing process. In order to successfully assemble the coil, it is of great significance to analyze and develop a set of tooling to reduce coil deformation in heat treatment process.
Study on Vibration and Heat Transfer Performances of a Modified Elastic Tube Bundle Heat Exchanger
Authors: Ji Jiadong , Deng Xu , Zhang Jingwei , Li Feiyang , Zhou Rong 
Published: February 2022

Abstract
Based on the bi-directional fluid-structure coupling method, the vibration and heat transfer performances of a modified elastic tube bundle heat exchanger are studied. The vibration frequency and amplitude of tube bundle are compared between different directions and tube row spacing. Furthermore, the Nusselt number of tube bundle are studied in vibrational and non-vibrational cases. The numerical results represent that the vibration amplitude of tube bundle is the largest in the z direction, which is 7.25 times that in the y direction (direction of the smallest amplitude). In the calculation scope, the vibration frequency and amplitude promote with tube row spacing. From 50 mm to 90 mm spacing, the vibration frequency and amplitude increase by 21.88% and 10.65%, respectively. The Nusselt number under the fluid-induced vibration increases up to 11.67% compared with non-vibration. Besides, the Nusselt number of tube bundle in the middle part is lower than that at the two ends. Within 50-90 mm interval, the enhanced heat transfer effect rises along with tube row spacing. The rising rate of the Nusselt number increases by 52.4%. in the range of computation.
Research on Fault Feature Extraction of Rolling Bearing Based on dFIF
Authors: Chen Xueliang , Chen Baojia , Chen Zhengkun 
Published: February 2022

Abstract
Aiming at the problems that the traditional adaptive mode decomposition method has low decomposition efficiency, poor ability of anti-mode mixing and decomposition accuracy, a rolling bearing fault feature recognition method based on direct fast iterative filtering (dFIF) and the crest factor of envelope spectrum is proposed. dFIF first decomposes the raw rolling bearing vibration signal into a set of intrinsic mode function (IMFs), then the optimal component is chosen based on the maximal crest factor of envelope spectrum, and finally the bearing fault characteristic frequency and its frequency multiplication are extracted using envelope demodulation analysis. It is demonstrated by relevant experimental data that the proposed method has efficient decomposition speed, accurate decomposition accuracy, and the accurate selection of effective components, and can effectively realize rolling bearing fault detection.