bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sub-millinewton thrust stand and wireless power coupler for microwave-powered small satellite thrusters
Authors: Wachs Benjamin N. , Jorns Benjamin A. 
Published: August 2022

The design and performance of a thrust stand for characterizing low-power electric propulsion thrusters are presented. The thrust stand is capable of sub-millinewton resolution for devices on the order of 1 kg. The architecture is based on a counter-weighted hanging pendulum design, a variant of the standard hanging pendulum that employs a counterweight to increase force resolution. Thrust is measured in a displacement mode using the change in position of the pendulum arm as measured by an optical displacement sensor. Passive eddy-current damping is used to offset oscillations and decrease setting time. An in situ calibration rig using known masses is used to calculate thrust. The thrust stand features an adjustable counterweight for in-vacuum sensitivity adjustment. In addition, the design of a broadband (600–2490 MHz) wireless microwave power coupler is presented. The device eliminates stiffness and thermal drift introduced by coaxial cables—typically the leading source of error in testing low-power microwave and radio frequency-powered thrusters. The thrust stand and coupler were tested using an electron cyclotron resonance magnetic nozzle thruster operating with xenon at flow rates from 1 to 10 sccm and powers ranging from zero (cold gas thrust) to 40 W. The resulting measurements showed a force resolution of ∼10μN over a range of thrusts from ∼14 to 600 µN.
On a nonlinear model in domains with cavities arising from cardiac electrophysiology
Authors: Beretta Elena , Cerutti M Cristina , Pierotti Dario 
Published: August 2022

Abstract
In this paper we deal with the problem of determining perfectly insulating regions (cavities) from boundary measurements in a nonlinear elliptic equation arising from cardiac electrophysiology. With minimal regularity assumptions on the cavities, we first show well-posedness of the direct problem and then prove uniqueness for the inverse problem.
A comprehensive review of organic-inorganic composites based piezoelectric nanogenerators through material structure design
Authors: Lu Haowei , Zheng Haiwu 
Published: August 2022

Abstract
With the development and popularization of Internet of things, how to provide energy for distributed sensors, portable and embedded electronic devices have become a challenge. People’s requirements for power supply equipment are portable, sustainable and free maintenance. Therefore, organic–inorganic composites based on piezoelectric nanogenerator (PENG) is becoming one of promising solutions due to these advantages of low cost, excellent mechanical property and environmental adaptability, which can effectively harvest ubiquitous micro-nano mechanical high entropy energy and convert it into electricity to power electronics and nano-systems. In this study, the development of PENGs based on organic–inorganic composites have been reviewed and several strategies toward high output performance of PENGs, including various materials, piezoelectric fillers modification and structural design are summarized and discussed. The effects of different optimization methods on short circuit current (I
SC), open circuit voltage (V
OC) and output power of various PENGs as well as current difficulty for improving performance have been discussed. Meanwhile, some specific application scenarios in previous reports are also presented. Finally, we have proposed an outlook about future developments of flexible PENG and authors hope that this review can help researchers better understand this field and facilitate the improvement of flexible PENG to realize a broader application in self-powered system.
Effect of PbPc on electron structure and carrier dynamics of black phosphorus
Authors: Zhang Jianhua , Wang Shitan , Yang Baopeng , Niu Dongmei , Gao Yongli 
Published: August 2022

Abstract
Using lead phthalocyanine (PbPc) as surface doping material on black phosphorous (BP) we observe enhanced photo-excited carriers in the PbPc/BP heterostructure. The interfacial energy level alignment is investigated with ultra violet photoemission spectroscopy (UPS) and x-ray photoemission spectroscopy (XPS). The heterojunction is type I with gap of BP nested in that of PbPc, facilitating confinement of electrons and holes in BP. Ultrafast time-resolved two-photon photoemission (TR-2PPE) spectroscopy is used to study the influence of PbPc on the photo excited unoccupied electronic states and the dynamics of the relaxation processes. Monolayer PbPc can greatly increase the pump excited hot electrons and the 2 photon emission of BP. The enhanced population in the intermediate states is attributed to the straddling of the band alignment which benefits the photo excited electrons in PbPc transferring to BP. Density functional theory calculations supported the interface dipole and charge redistribution. Our results provide a fundamental understanding of the excellent opto-electrical response of PbPc/BP interface of promising application in the high efficient photo detectors.
Quantum quench of photoinduced semi-Dirac materials: Hall response
Authors: Aftab Tayyaba , Sabeeh Kashif 
Published: August 2022

Abstract
In this work, far from equilibrium Hall response of semi-Dirac materials is studied. This required preparing the system in non-equilibrium states through a quantum quench protocol. We show that in the non-equilibrium setting, there is non-zero Hall response even when instantaneous time reversal symmetry (TRS) is present and the Hall current persists for long times. This is in contrast to the equilibrium case where the system is required to break TRS for a Hall response. This highlights unique features of far from equilibrium response in semi-Dirac materials that are not present in the corresponding equilibrium state.
Quantum nonlocality and topological quantum phase transitions in the extended Ising chain
Authors: Dong Luzhao , Bao Jia , Guo Bin , Sun Zhaoyu 
Published: August 2022

Abstract
We use two-site quantum nonlocality to identify the topological quantum phase transitions (TQPTs) of the extended Ising model driven by varying system parameters. We investigate how the system parameters, including the anisotropies of the nearest-neighbor and the next-nearest-neighbor spin pairs, the transverse magnetic field, and the three-spin interaction, affect the quantum nonlocality. We show that the nonlocality cannot mark any TQPTs while its first derivative can perfectly characterize the TQPTs. By making the influences of the thermal fluctuations and the site distance of spin pairs on the critical behavior of the TQPTs analysis, we show that the sufficiently low temperature has a slight impact on the features of nonlocality and its first derivative while the site distance of spin pairs can significantly alter the properties of nonlocality and its first derivative. We further present the energy spectra and the trajectories of the winding vectors of the model to demonstrate that the quantum nonlocality can be employed to successfully signalize the TQPTs.
Deep neural networks based predictive-generative framework with data augmentation for designing composite materials
Authors: Ashank  , Chakravarty Soumen , Garg Pranshu , Kumar Ankit , Agnihotri Prabhat K , Agrawal Manish 
Published: August 2022

Abstract
Designing composite materials according to the need of applications is fundamentally a challenging and time-consuming task. A deep neural network-based computational framework is developed in this work to solve the forward (predictive) and the inverse (generative) composite design problem. The predictor model is based on the popular convolution neural network architecture and trained with the help of finite element simulations. Conventionally, a large amount of training data is required for accurate prediction from neural network models. A data augmentation strategy is proposed in this study which significantly saves computational resources in the training phase. It shown that the data augmentation approach is general and can be used in any setting involving periodic microstructures. We next use, the property predictor model as a feedback mechanism in the neural network-based generator model. The proposed predictive-generative model is used to obtain the composite microstructure for various requirements such as maximization of elastic properties, specified elastic constants, etc. The efficacy of the proposed predictive-generative model is demonstrated by solving certain class of problems. It is envisaged that the developed model coupled with data augmentation strategy will significantly reduce the cost and time associated with the composite material designing process for varying application requirements.
Selective area epitaxy of GaAs: the unintuitive role of feature size and pitch
Authors: Dede Didem , Glas Frank , Piazza Valerio , Morgan Nicholas , Friedl Martin , Güniat Lucas , Nur Dayi Elif , Balgarkashi Akshay , Dubrovskii Vladimir G , Fontcuberta i Morral Anna 
Published: August 2022

Abstract
Selective area epitaxy (SAE) provides the path for scalable fabrication of semiconductor nanostructures in a device-compatible configuration. In the current paradigm, SAE is understood as localized epitaxy, and is modelled by combining planar and self-assembled nanowire growth mechanisms. Here we use GaAs SAE as a model system to provide a different perspective. First, we provide evidence of the significant impact of the annealing stage in the calculation of the growth rates. Then, by elucidating the effect of geometrical constraints on the growth of the semiconductor crystal, we demonstrate the role of adatom desorption and resorption beyond the direct-impingement and diffusion-limited regime. Our theoretical model explains the effect of these constraints on the growth, and in particular why the SAE growth rate is highly sensitive to the pattern geometry. Finally, the disagreement of the model at the largest pitch points to non-negligible multiple adatom recycling between patterned features. Overall, our findings point out the importance of considering adatom diffusion, adsorption and desorption dynamics in designing the SAE pattern to create pre-determined nanoscale structures across a wafer. These results are fundamental for the SAE process to become viable in the semiconductor industry.
The art of building a smooth cosmic distance ladder in a perturbed universe
Authors: Umeh Obinna 
Published: August 2022

AbstractHow does a smooth cosmic distance ladder emerge from observations made from a single location in a lumpy Universe? Distances to the Type Ia supernova (SN1A) in the Hubble flow are anchored on local distance measurements to sources that are very nearby. We described how this configuration could be built in a perturbed universe where lumpiness is described as small perturbations on top of a flat Friedmann-Lemaıtre Robertson-Walker (FLRW) spacetime. We show that there is a non-negligible modification (about 11%) to the background FLRW area distance due to the presence of inhomogeneities in the immediate neighbourhood of an observer. We find that the modification is sourced by the electric part of the Weyl tensor indicating a tidal deformation of the local spacetime of the observer. We show in detail how it could impact the calibration of the SN1A absolute magnitude in the Hubble flow. We show that it could potentially resolve the SN1A absolute magnitude and Hubble tensions simultaneously without the need for early or late dark energy.
1 kHz, 12 MW, 300 ps microchip oscillator power amplifier system
Authors: Zhu Wentao , Yu Jun , He Huijun , Lin Qingdian , Guo Xiaoyang , Zhou Cangtao , Ruan Shuangchen 
Published: August 2022

Abstract
We report a diode-pumped passively Q-switched (PQS) sub-nanosecond master oscillator power amplifier system. The master oscillator is a PQS Nd:YAG/Cr:YAG monolithic microchip laser, yielding a pulse duration of ∼300 ps and pulse energy of 33 μJ at repetition frequency of 1 kHz. After passing two stages end pumped Nd:YVO4 amplifier, the pulse energy is boosted to 3.6 mJ and pulse peak power up to 12 MW with excellent stability (root mean square ∼ 0.14%) and high beam quality (M
2 < 1.22).
Design and Implementation of AGV Calling System Based on Android
Authors: Zhu Ouwen , Zhao Yuli 
Published: August 2022

Abstract
This paper designs and implements an AGV calling application based on Android. In the actual working environment, administrators need to call automatic guided vehicles to perform tasks and monitor them anytime and anywhere, so the AGV calling application based on Android came into being. Five business function modules of the system are realized: calling module, map monitoring module, task list module, node configuration module and communication configuration module. The application software is developed using Android Studio development tool, with the use of Vue framework and front-end HTML5+CSS+JavaScript technology to achieve interface rendering. TCP and HTTP protocols are used in the connection between the system and the central control system.
The Method for Automatic Adjustment of AGV’s PID Based on Deep Reinforcement Learning
Authors: Chen Yubin , Li Dancheng , Zhong Huagang , Zhao Ruihang 
Published: August 2022

Abstract
This paper proposes a method for automatic adjustment of PID(Proportion Integration Differentiation) based on deep reinforcement learning in order to solve the problem of smooth movement of AGV(Automated Guided Vehicle). First, based on reinforcement learning, the problem of AGV smooth operation is transformed into the solution of PID adjustment operation sequence. The action value model is constructed using the Deep Q-Learning Network(DQN) algorithm. Then, take the AGV adjustment PID as the research object. The goal is to achieve smooth movement of AGV. The specific design of AGV automatic PID adjustment method based on deep reinforcement learning is introduced. Finally, the simulation data is used to train the AGV action value network model. The method is validated in the ROS(Robot Operating System) simulation environment. Then compare with the actual environment. The results show that the automatic adjustment method of AGV’s PID based on deep reinforcement learning can adjust PID to the optimum without manual work. It can make AGV run smoothly. The feasibility and effectiveness of the method are illustrated and the problem of automatic PID determination in AGV movement control is solved.
Study of the IPOS DC/DC Converter for DC Offshore Wind Farm
Authors: Ding Huaxing , Zou Guibin , Ding Ning , Wang Chuanjie 
Published: August 2022

Abstract
With the development of the offshore wind farms, DC offshore wind farm topology is getting more attention due to its low loss and light weight, where the DC/DC converters with high voltage gain are key equipments. This paper studies the Input-Parallel-Output-Series(IPOS) converter based on Dual-Active-Bridge(DAB) topology, discusses the modulation and control method of the converter, and proposes a fault ride-through scheme. Simulation results validate the proposed topologies and control schemes.
Simulation Modeling of Switching over Current of Circuit Breaker in Intercity Train
Authors: Cao Weinan , Sun Ning , Wang Yong , Li Meng 
Published: August 2022

Abstract
The main interference source of axle counter is the over-current caused by the operation of circuit breaker by intercity train. This paper focuses on the simulation modeling technology of switching over-current of intercity train circuit breaker. Firstly, the mechanism of the interference when the circuit breaker is closed is studied by theoretical analysis; Then, the interference source model is established when the circuit breaker is closed, and the equivalent circuit model of interference path including vehicle body, vehicle body grounding system, traction network and high-voltage cable is obtained through calculation and analysis. The current of transformer primary grounding wire is measured on the actual vehicle, and the accuracy of the model is verified by comparing with the simulation model. Finally, the spectrum characteristics of the interference current in the rail are obtained by Fourier transform. In this paper, a simulation modeling method for analyzing the operating overcurrent of intercity vehicle circuit breaker is proposed, which can effectively evaluate the magnitude of the interference current generated by closing the circuit breaker into the rail, and provide a research basis for the follow-up study of the interference characteristics of the radiation field of rail current on the trackside axle counter.
Deep Supervised Cross-modal Hashing for Ship Image Retrieval
Authors: Guo Jiaen , Wang Haibin , Dan Bo , Lu Yu 
Published: August 2022

Abstract
The retrieval of multimodal ship images obtained by remote sensing satellites is an important content of remote sensing data analysis, which is of great significance to improve the ability of marine monitoring. In this paper, We propose a novel cross-modal ship image retrieval method, called Deep Supervised Cross-modal Hashing(DSCMH). It consists of a feature learning part and a hash learning part used for feature extraction and hash code generation separately, both two parts have modality-invariant constraints to keep the cross-modal invariability, and the label information is also brought to supervise the above process. Furthermore, we design a class attention module based on the cross-modal class center to strengthen class discrimination. The experiment results show that the proposed method can effectively improve the cross-modal retrieval accuracy of ship images and is better than several state-of-the-art methods.
An Image Encryption Scheme based on Adaptive Bit-Plane Division
Authors: Gu Jun , Xu Feng , Zeng Tao , Lyu Xin 
Published: August 2022

Abstract
With the application and popularization of digital images, the security of images has been paid more and more attention. The bit-level image encryption method has become one of the commonly used methods. It has the characteristic of changing the pixel value while disturbing the position of the pixel point, but at the same time it is accompanied by a higher computational complexity. In order to improve the efficiency of the encryption algorithm, according to the characteristic that the higher 4 of the 8 bit-planes of the grayscale image contain 94.125% of the information of the entire image, the encryption structure of higher 4 bit-planes and lower 4 bit-planes is widely used. But for different images, this characteristic is not accurately applicable. In response to this problem, we design a method of adaptive bit-plane division, which uses mutual information and Jensen-Shannon divergence to measure the amount of information of bit-planes and then divides bit-planes into two parts. The results of bit-plane division are different for different images. Based on this, we propose an image encryption scheme based on adaptive bit-plane division. Compared with the traditional higher 4-bits and lower 4-bits encryption method, this scheme reduces the encryption cost and improves the encryption efficiency. Experimental results show that the proposed scheme can effectively resist the chosen plain-image attacks and has sufficient security.
Transmission Line Foreign Body Fault Detection Using Multi-Feature Fusion Based on Modified YOLOv5
Authors: Wang Qianyue , Si Gangquan , Qu Kai , Gong Jiahui , Cui Lele 
Published: August 2022

Abstract
The particular work environment of transmission lines makes it liable to malfunction because of the foreign bodies attached to the power equipment. However, traditional detection methods are difficult to identify the exact category of foreign bodies and ignore the relationship between a foreign body and power equipment, which is correlated to determining whether there is a fault or not. In order to detect and distinguish the foreign bodies and give fault warnings automatically in transmission line patrol with high accuracy and efficiency, we improve the original YOLOv5 object detection model and propose a novel fusion detection model using multi-scale appearance and relationship features. The proposed model is capable of transmission line foreign body category detection and fault determination. By comparing with the original YOLOv5, the proposed model shows better accuracy and achieves the strong ability to give the fault determination simultaneously, which makes it convenient for power system operators and protects the safe and stable operation of the power system.
Cloud Resource Scheduling Method based on Markov Process and the Cuckoo Search
Authors: Qi Bin , Zhang Pan , Wu Hong , Yan Miao 
Published: August 2022

Abstract
With the rapid development of cloud computing, the computing reliability of cloud servers has become an important research area. To improve the load balancing capability of cloud servers, an autonomous adaptive architecture cloud computing framework based on software-defined networking and network function virtualization were proposed. And a cloud resource scheduling method based on the Markov process model and cuckoo search algorithm to realize the load balancing of cloud nodes was designed. The cloud platform verified by the experiment shows that the method can effectively guarantee the service reliability of cloud computing.
Macro-mechanical properties of magnetorheological fluids based on body-centered cubic structure
Authors: Chen Song , Cai Tianwu 
Published: August 2022

Abstract
This paper addresses the problem that the microstructure model of magnetorheological fluid established by traditional single-chain or multi-chain dense rows is unable to accurately describe the rheological behavior and the sudden change of macroscopic mechanical properties under the action of an applied magnetic field, and analyzes the stable cluster-like structure formed by a specific volume fraction of magnetorheological fluids in a micro-narrow channel under the action of external magnetic field and extrusion pressure. This paper also establishes the equations of motion and dynamics of magnetic particles under the action of external magnetic field, analyzes the dynamic evolution of particle microstructure, performs numerical simulations of two-dimensional chaining using Matlab, and establishes a microscopic observation test bench for comparison and verification; and it establishes a model of complex cluster-like structure of magnetorheological fluids body-centered cubic, and analyzes the system energy, stability and force of the body-centered cubic structure based on the minimum system energy theory and Hertzian contact theory; and further establishes a shear yield stress model based on the body-centered cubic microstructure to analyze the macroscopic mechanical properties of magnetorheological fluids, thereby enriching the theoretical system of extrusion strengthening of magnetorheological fluids in the microscale.