bluuebunny/crossref_metadata_2025_split huggingface dataset:
An ADMM-LAP method for total variation myopic deconvolution of adaptive optics retinal images
Authors: Chen Xiaotong , Herring James L , Nagy James G , Xi Yuanzhe , Yu Bo 
Published: September 2020

Abstract
Adaptive optics corrected flood imaging of the retina is a popular technique for studying the retinal structure and function in the living eye. However, the raw retinal images are usually of poor contrast and the interpretation of such images requires image deconvolution. Different from standard deconvolution problems where the point spread function (PSF) is completely known, the PSF in these retinal imaging problems is only partially known which leads to the more complicated myopic (mildly blind) deconvolution problem. In this paper, we propose an efficient numerical scheme for solving this myopic deconvolution problem with total variational (TV) regularization. First, we apply the alternating direction method of multipliers (ADMM) to tackle the TV regularizer. Specifically, we reformulate the TV problem as an equivalent equality constrained problem where the objective function is separable, and then minimize the augmented Lagrangian function by alternating between two (separated) blocks of unknowns to obtain the solution. Due to the structure of the retinal images, the subproblems with respect to the fidelity term appearing within each ADMM iteration are tightly coupled and a variation of the linearize and project method is designed to solve these subproblems efficiently. The proposed method is called the ADMM-LAP method. Theoretically, we establish the subsequence convergence of the ADMM-LAP method to a stationary point. Both the theoretical complexity analysis and numerical results are provided to demonstrate the efficiency of the ADMM-LAP method.
Thermal oxidation of AlGaN nanowires for sub-250 nm deep ultraviolet photodetection
Authors: Zhang Xiaodong , He Tao , Tang Wenbo , Ma Yongjian , Wei Xing , Wang Danhao , Zhang Haochen , Sun Haiding , Fan Yaming , Cai Yong , Zhang Baoshun 
Published: September 2020

Abstract
In this work, we demonstrated a thermal oxidation process for AlGaN nanowires and revealed the underlying mechanism of AlGaN to AlGaO transition for sub-250 nm deep ultraviolet photodetection. When the AlGaN nanowires were exposed to oxygen atmosphere below a temperature of 700 °C, only the Al–N bond was oxidized while the Ga–N bond remained intact, and thereafter, the AlGaN nanowires were slowly oxidized to AlGaON complex. However, as the oxidation temperature was elevated to above 700 °C, the AlGaN complex was transformed into AlGaO complex. Using this method, photodetectors based on AlGaON nanowires were fabricated and compared with its AlGaN counterpart. The AlGaON photodetector showed a response peak at deep ultraviolet of 242 nm with a high responsivity of 726 mA W−1, compared with the response peak at 276 nm in AlGaN nanowires. This work offers an alternative method towards the realization of high performance sub-250 nm deep ultraviolet photodetection.
Optical characterization of nanostructured β − FeSi2 layers obtained by Fe+ implantation
Authors: Salinas-Fuentes Cecilia , Hernández-Zanabria Angélica , Kudriavtsev Yuriy , Cheang-Wong Juan-Carlos 
Published: September 2020

Abstract
In this work, we present a comprehensive analysis of nanostructured β − FeSi2 layers obtained by 40 keV Fe ion implantation in silicon, followed by rapid thermal annealing. A series of chemical, structural and optical characterizations of the samples were performed. Our results establish the formation of a 26.6 nm thick layer consisting of β − FeSi2 nanocrystals, with an average size of 4.8 nm, embedded in the Si substrate. Optical excitation of the sample leads to a photoluminescence signal with an extremely narrow peak (1 nm full width at half maximum) at 1456 nm. This sharp emission is comparable with the radiation of semiconductor lasers and therefore, this β − FeSi2 nanostructured layer is of interest for the fabrication of new optoelectronic devices in the near-infrared region.
Tunable strain effects on the electronic structures and mobility properties of InP/InAs lateral heterostructure
Authors: Lin Long , Li Shaofei , Yao Linwei , Yu Weiyang , Cai Xiaolin , Zhang Liwei , Zhang Wei-Bing , Zhang Zhanying , Tao Hualong 
Published: September 2020

Abstract
Two-dimensional lateral heterostructures (LHSs) carry unconventional physical properties due to their excellent adjustable band-offset and sensitive interface characteristics. In this paper, we have designed two kinds of seamless LHSs with excellent stabilities, the zigzag-zigzag (Z-Z) InP/InAs LHS and the armchair-armchair (A-A) InP/InAs LHS, and the changes in lattice structures and electronic properties under different strains are studied systematically by employing first-principles calculations based on density functional theory. Our results indicate that the Z-Z and A-A InP/InAs LHSs are indirect-bandgap semiconductors with a moderate bandgap. Surprisingly, it is found that the carrier mobility of holes for the Z-Z InP/InAs LHS is as high as 6.954 × 103cm2· V−1· s−1. The established Z-Z and A-A InP/InAs LHSs exhibit superior properties under uniaxial strains (a-direction and b-direction) and biaxial strain (ab-direction). It is found that the conduction bands of Z-Z and A-A InP/InAs LHSs occur with an intriguing downward (upward) transfer under compressive (tensile) strain along the b- and ab-directions, respectively. Moreover, when more than 2% of the tensile strain along the ab-direction is applied, the Z-Z and A-A InP/InAs LHS change from an indirect bandgap semiconductor to a direct bandgap semiconductor, and the Z-Z InAs/InP LHS changes into type-II heterostructure. Based on the calculated band structures, the effect of uniaxial strain on effective mass is anisotropic. Especially when tensile strain is applied, the effective mass of electrons in Z-Z and A-A InP/InAs LHSs will be reduced, which is consistent with the change in band structures under strain. The strain tunability of direct bandgap, type-II band alignment, and high carrier mobility mean Z-Z and A-A InP/InAs LHSs have potential applications in optoelectronic, photovoltaic, and flexible electronic devices.
No evidence for room temperature ferromagnetism in the high temperature metal-organic material: Ni2TCNQ
Authors: Berlie Adam , Terry Ian , Szablewski Marek , Quinn Kimberly 
Published: September 2020

Abstract
The search for ferromagnetic organic-based compounds has been a particular challenge to both chemists and physicists over the past few decades. The synthesis of the Ni2A, where A is an organic acceptor; tetracyanoethene (TCNE), 3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) or 7,7,8,8-tetracyanoquinodimethane (TCNQ) (Jain et al 2007 Nature
445 291), was reported to be a great advancement with claims that the ferromagnetism persisted to well above room temperature. There were, however some substantial flaws in the methodology associated with the synthesis and physical characterisation. Our work solely studies the Ni2TCNQ compound where we find no evidence for the existence of inherent ferromagnetism within the material that was reported in the original paper. Instead, we find that the magnetism is due to superparamagnetic nickel nanoparticles embedded in an amorphous matrix. It is hoped that our work will also show that one must be careful when using Ni(COD)2 as a precursor in the synthesis of magnetic materials and that the usefulness of the reported synthetic method is extremely limited.
Dimension of Gibbs measures with infinite entropy
Authors: Pérez Pereira Felipe 
Published: September 2020

Abstract
We study the Hausdorff dimension of Gibbs measures with infinite entropy with respect to maps of the interval with countably many branches. We show that under simple conditions, such measures are symbolic-exact dimensional, and provide an almost sure value for the symbolic dimension. We also show that the lower local dimension dimension is almost surely equal to zero, while the upper local dimension is almost surely equal to the symbolic dimension. In particular, we prove that a large class of Gibbs measures with infinite entropy for the Gauss map have Hausdorff dimension zero and packing dimension equal to 1/2, and so such measures are not exact dimensional.
A sufficient and necessary condition of PS-ergodicity of periodic measures and generated ergodic upper expectations
Authors: Feng Chunrong , Qu Baoyou , Zhao Huaizhong 
Published: September 2020

Abstract
This paper contains two parts. In the first part, we study the ergodicity of periodic measures of random dynamical systems on a separable Banach space. We obtain that the periodic measure of the continuous time skew-product dynamical system generated by a random periodic path is ergodic if and only if the underlying noise metric dynamical system at discrete time of integral multiples of the period is ergodic. For the Markov random dynamical system case, we prove that the periodic measure of a Markov semigroup is PS-ergodic if and only if the trace of the random periodic path at integral multiples of period either entirely lies on a Poincaré section or completely outside a Poincaré section almost surely. In the second part of this paper, we construct sublinear expectations from periodic measures and obtain the ergodicity of the sublinear expectations from the ergodicity of periodic measures. We give some examples including the ergodicity of the discrete time Wiener shift of Brownian motions. The latter result would have some independent interests.
Dynamic modelling and control of shear-mode rotational MR damper for mitigating hazard vibration of building structures
Authors: Yu Yang , Royel Sayed , Li Yancheng , Li Jianchun , Yousefi Amir M , Gu Xiaoyu , Li Shaoqi , Li Huan 
Published: September 2020

Abstract
Magneto-rheological (MR) materials and their devices are being rapidly developed and have drawn surge of interest for the potential application in vibration control. Among them, a novel shear-mode rotational MR damper (SM-RMRD) with adaptive variable stiffness and damping was developed for adaptive structural control in real-time against different types of earthquakes. To make use of this innovative device perfectly, a robust and reliable model should be developed to simulate the nonlinear and hysteretic behaviours for the application in adaptive control. Accordingly, this research initially presents a new phenomenological model to describe the force response of the SM-RMRD. Then, model parameters are estimated based on experimental data of force, displacement and velocity, which were directly or indirectly obtained from the device under different loading protocols. The field dependence of each model parameter is also investigated so that a general model with current-related parameters is acquired for designing the control strategy. Using the current-dependent model of SM-RMRD, a semi-active controller is developed and implemented to the SM-RMRD to produce the feedback control for the structures in real-time. Finally, the effectiveness of proposed control method is appraised by a numerical study, in which an SM-RMRDs-incorporated three-storey building model with different control strategies are subjected to various scaled benchmark earthquakes. The comparison result verifies the excellent capacity of the proposed controller based on the developed phenomenological model in terms of reducing the storey acceleration and inter-storey drift.
Mechanically robust, intrinsically self-healing crosslinked polymer enabled by dynamic urea bond exchange reaction
Authors: Zhou Zhongqun , Zeng Yanning , Yu Caili , Chen Haibo , Zhang Faai 
Published: September 2020

Abstract
Designing a crosslinked polymer with self-healing, recyclable, and mechanical properties is a significant challenge in the field of self-healing chemistry. Herein, robust, intrinsically self-healing, crosslinked polyureas (C-PUs) are prepared via a facile one-pot photo-induced copolymerization to address the aforementioned limitation. The key strategy involves the introduction of a synthetic monomer with reversible urea bonds into the polymer network as a versatile dynamic crosslinker. The resultant C-PUs are a class of resource-saving materials with a combination of excellent intrinsic self-healing capability with outstanding mechanical robustness. Notably, the properties of the materials can be easily tuned by simply adjusting the dynamic crosslinker content. In addition, an environmentally friendly polymer reprocessing is achieved and the potential of the materials in the smart anticorrosion application is investigated. These desirable properties are attributed to the underlying topological network rearrangement enabled by the dynamic urea bond exchange reaction, which is confirmed by stress relaxation tests. Therefore, the resulting self-healing C-PUs can serve as models to extend the scope of applications in smart protective materials or ocean engineering.
Data augmentation for enhancing EEG-based emotion recognition with deep generative models
Authors: Luo Yun , Zhu Li-Zhen , Wan Zi-Yu , Lu Bao-Liang 
Published: September 2020

Abstract

Objective. The data scarcity problem in emotion recognition from electroencephalography (EEG) leads to difficulty in building an affective model with high accuracy using machine learning algorithms or deep neural networks. Inspired by emerging deep generative models, we propose three methods for augmenting EEG training data to enhance the performance of emotion recognition models. Approach. Our proposed methods are based on two deep generative models, variational autoencoder (VAE) and generative adversarial network (GAN), and two data augmentation ways, full and partial usage strategies. For the full usage strategy, all of the generated data are augmented to the training dataset without judging the quality of the generated data, while for the partial usage, only high-quality data are selected and appended to the training dataset. These three methods are called conditional Wasserstein GAN (cWGAN), selective VAE (sVAE), and selective WGAN (sWGAN). Main results. To evaluate the effectiveness of these proposed methods, we perform a systematic experimental study on two public EEG datasets for emotion recognition, namely, SEED and DEAP. We first generate realistic-like EEG training data in two forms: power spectral density and differential entropy. Then, we augment the original training datasets with a different number of generated realistic-like EEG data. Finally, we train support vector machines and deep neural networks with shortcut layers to build affective models using the original and augmented training datasets. The experimental results demonstrate that our proposed data augmentation methods based on generative models outperform the existing data augmentation approaches such as conditional VAE, Gaussian noise, and rotational data augmentation. We also observe that the number of generated data should be less than 10 times of the original training dataset to achieve the best performance. Significance. The augmented training datasets produced by our proposed sWGAN method significantly enhance the performance of EEG-based emotion recognition models.
Deep brain stimulation: a review of the open neural engineering challenges
Authors: Vissani Matteo , Isaias Ioannis U , Mazzoni Alberto 
Published: September 2020

Abstract

Objective. Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on ‘sensing mode’ to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy. Approach. We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS. Main results. We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns. Significance. This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.
Consistency of local activation parameters at sensor- and source-level in neural signals
Authors: Rodríguez-González Víctor , Gómez Carlos , Shigihara Yoshihito , Hoshi Hideyuki , Revilla-Vallejo Marcos , Hornero Roberto , Poza Jesús 
Published: September 2020

Abstract

Objective. Although magnetoencephalography and electroencephalography (M/EEG) signals at sensor level are robust and reliable, they suffer from different degrees of distortion due to changes in brain tissue conductivities, known as field spread and volume conduction effects. To estimate original neural generators from M/EEG activity acquired at sensor level, diverse source localisation algorithms have been proposed; however, they are not exempt from limitations and usually involve time-consuming procedures. Connectivity and network-based M/EEG analyses have been found to be affected by field spread and volume conduction effects; nevertheless, the influence of the aforementioned effects on widely used local activation parameters has not been assessed yet. The goal of this study is to evaluate the consistency of various local activation parameters when they are computed at sensor- and source-level. Approach. Six spectral (relative power, median frequency, and individual alpha frequency) and non-linear parameters (Lempel-Ziv complexity, sample entropy, and central tendency measure) are computed from M/EEG signals at sensor- and source-level using four source inversion methods: weighted minimum norm estimate (wMNE), standardised low-resolution brain electromagnetic tomography (sLORETA), linear constrained minimum variance (LCMV), and dynamical statistical parametric mapping (dSPM). Main results. Our results show that the spectral and non-linear parameters yield similar results at sensor- and source-level, showing high correlation values between them for all the source inversion methods evaluated and both modalities of signal, EEG and MEG. Furthermore, the correlation values remain high when performing coarse-grained spatial analyses. Significance. To the best of our knowledge, this is the first study analysing how field spread and volume conduction effects impact on local activation parameters computed from resting-state neural activity. Our findings evidence that local activation parameters are robust against field spread and volume conduction effects and provide equivalent information at sensor- and source-level even when performing regional analyses.
Manipulation of E×B drifts in a slot divertor with advanced shaping to optimize detachment
Authors: Du Hailong , Guo H.Y. , Stangeby P.C. , Bonnin Xavier , Zheng Guoyao , Duan Xuru , Xu Min 
Published: September 2020

Abstract
SOLPS-ITER edge code analysis including drifts shows that optimization of divertor target shaping in a small angle slot (SAS) can strongly influence E× B drift particle fluxes, potentially improving divertor detachment for both toroidal field directions. This is enabled by directing recycling neutrals toward the separatrix from both the common flux region (CFR) and the private flux region (PFR) walls of the slot with a V-shape target in the slot (SAS-V), leading to two separate reinforcing effects, each individually involving positive feed-back: (a) increase of neutral recycling at the PFR wall of the slot due to—and causing—strong radial E× B ion flux from the CFR to the PFR; (b) decrease of E× B loss of ions out of the outer divertor into the inner divertor via the PFR due to reduction of the radial gradient of electron temperature at the outer target caused by the increased particle retention in the outer divertor. This circumvents the general problem for divertor operation with ion B ×∇B toward the X-point: E× B loss of particles from the outer divertor CFR plasma tends to keep it hot and attached. This work identifies a strong interaction between divertor geometry and drifts, a potentially important effect for optimizing advanced divertors for power exhaust in fusion reactors.
Operation improvement measures of dry type air-core reactor in severe cold environment
Authors: Wang Lin , Hao Wenguang , Deng Junyu , Wang Hongyu 
Published: September 2020

Abstract
In severe cold environment, the surface of dry type air-core reactor would easily be cracked, once natural contamination accumulated on the cracks, surface flashover would have more possibility to happen, leading to more serious reactor faults. The most commonly used methods to avoid reactor surface discharge includes RTV coating and surface decontamination using water-based cleaning agent, yet the effects of these methods, as well as possible impact on reactor performance have not been fully studied. In this paper, RTV coating and decontamination tests were carried out to evaluate the effect of the methods, also the impact of these two methods on reactor electrical performance were analyzed. The research result showed that: (1)Water-based cleaning agent was effective in removing contamination on insulation paint surface, but less effective in removing contamination on RTV coated surface; However, the water-based cleaning agent would cause damping between the winding strands, and damping recovery degree was not easy to control. Therefore, water-based cleaning agent was not suitable to solve surface flashover problem of dry type air-core reactors. (2) The overall coating for reactor surface and air duct could be realized by special spraying equipment. The adhesion test showed that RTV was of good covering and adhesion performance, and had little impact on reactor temperature rise, indicating that RTV could be an effective measure to improve operation quality of dry type air-core reactor in extreme cold environment.
Research of auxiliary frequency modulation in smart microgrid
Authors: Yu Qingguang , Jiang Zhicheng , Ma Yingxin , Long Gaoxiang , Liu Yuming 
Published: September 2020

Abstract
In this paper, the component model of bidirectional converter and inverter is established, and the precise control of input and output power of the energy storage system is realized by using dual loop control strategy and PQ control strategy. the control strategy of the energy storage system is proposed to improve the performance of the primary frequency modulation process. The grid interconnection model of offshore oil platform is established. The frequency variation in primary and secondary frequency modulation is simulated to verify the effectiveness of the control strategy.