# X. H. Yang - Yunnan University, Yunnan, P.R. China

## Contact Details

NameX. H. Yang |
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AffiliationYunnan University, Yunnan, P.R. China |
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CityKunming Shi |
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CountryChina |
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## Pubs By Year |
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## Pub CategoriesMathematics - Numerical Analysis (12) Computer Science - Computer Vision and Pattern Recognition (7) Physics - Materials Science (6) Physics - Mesoscopic Systems and Quantum Hall Effect (4) Computer Science - Cryptography and Security (3) Quantum Physics (3) Physics - Chemical Physics (2) Computer Science - Learning (2) Computer Science - Networking and Internet Architecture (2) Mathematics - Classical Analysis and ODEs (2) Astrophysics of Galaxies (2) Computer Science - Robotics (2) Physics - Instrumentation and Detectors (1) Computer Science - Data Structures and Algorithms (1) Mathematics - Algebraic Geometry (1) Mathematics - Complex Variables (1) High Energy Physics - Experiment (1) Computer Science - Computational Complexity (1) Computer Science - Discrete Mathematics (1) Computer Science - Computation and Language (1) Physics - Classical Physics (1) Computer Science - Computational Geometry (1) Statistics - Methodology (1) Computer Science - Artificial Intelligence (1) Cosmology and Nongalactic Astrophysics (1) Quantitative Biology - Populations and Evolution (1) Physics - Biological Physics (1) Quantitative Biology - Molecular Networks (1) Computer Science - Programming Languages (1) Physics - Fluid Dynamics (1) Mathematics - Information Theory (1) Computer Science - Information Theory (1) Physics - Plasma Physics (1) |

## Publications Authored By X. H. Yang

A variety of real-world processes (over networks) produce sequences of data whose complex temporal dynamics need to be studied. More especially, the event timestamps can carry important information about the underlying network dynamics, which otherwise are not available from the time-series evenly sampled from continuous signals. Moreover, in most complex processes, event sequences and evenly-sampled times series data can interact with each other, which renders joint modeling of those two sources of data necessary. Read More

In this paper, we present an efficient energy stable scheme to solve a phase field model incorporating contact line condition. Instead of the usually used Cahn-Hilliard type phase equation, we adopt the Allen-Cahn type phase field model with the static contact line boundary condition that coupled with incompressible Navier-Stokes equations with Navier boundary condition. The projection method is used to deal with the Navier-Stokes equa- tions and an auxiliary function is introduced for the non-convex Ginzburg-Landau bulk potential. Read More

Topological states emerge at the boundary of solids as a consequence of the nontrivial topology of the bulk. Recently, theory predicts a topological edge state on single layer transition metal dichalcogenides with 1T' structure. However, its existence still lacks experimental proof. Read More

Uncovering the mechanisms that control size, growth, and division rates of systems reproducing through binary division means understanding basic principles of their life cycle. Recent work has focused on how division rates are regulated in bacteria and yeast, but this question has not yet been addressed in more complex, multicellular organisms. We have acquired a unique large-scale data set on the growth and asexual reproduction of two freshwater planarian species, Dugesia japonica and Dugesia tigrina, which reproduce by transverse fission and succeeding regeneration of head and tail pieces into new planarians. Read More

**Affiliations:**

^{1}ZJUT,

^{2}SJTU,

^{3}SHAO,

^{4}SJTU

**Category:**Cosmology and Nongalactic Astrophysics

We propose an Analytical method of Blind Separation (ABS) of cosmic magnification from the intrinsic fluctuations of galaxy number density in the observed (lensed) galaxy number density distribution. The ABS method utilizes the different dependences of the signal (cosmic magnification) and contamination (galaxy intrinsic clustering) on galaxy flux, to separate the two. It works directly on the measured cross galaxy angular power spectra between different flux bins. Read More

In this paper, we consider the numerical approximations for solving a hydrodynamics coupled phase field model consisting of incompressible Navier-Stokes equations with generalized Navier boundary conditions, and the Cahn-Hilliard equation with dynamic moving contact line boundary conditions. The main challenging issue for solving this model numerically is the time marching problem, i.e. Read More

In this paper, we consider the numerical approximations for a hydrodynamical model of smetic-A liquid crystals. The model, derived from the variational approach of the modified Oseen-Frank energy, is a highly nonlinear system that couples the incompressible Navier-Stokes equations and a constitutive equation for the layer variable. We develop two linear, second-order time-marching schemes based on the Invariant Energy Quadratization method for nonlinear terms in the constitutive equation, the projection method for the Navier-Stokes equations, and some subtle implicit-explicit treatments for the convective and stress terms. Read More

In this study, a multi-task deep neural network is proposed for skin lesion analysis. The proposed multi-task learning model solves different tasks (e.g. Read More

We have developed a method to improve the doping computation efficiency, this method is based on first principles calculations and cluster expansion. First principles codes produce highly accurate total energies and optimized geometries for any given structure. Cluster expansion method constructs a cluster expansion using partial first principles results and computes the energies for other structures derived from a parent lattice. Read More

Robot awareness of human actions is an essential research problem in robotics with many important real-world applications, including human-robot collaboration and teaming. Over the past few years, depth sensors have become a standard device widely used by intelligent robots for 3D perception, which can also offer human skeletal data in 3D space. Several methods based on skeletal data were designed to enable robot awareness of human actions with satisfactory accuracy. Read More

Apprenticeship learning has recently attracted a wide attention due to its capability of allowing robots to learn physical tasks directly from demonstrations provided by human experts. Most previous techniques assumed that the state space is known a priori or employed simple state representations that usually suffer from perceptual aliasing. Different from previous research, we propose a novel approach named Sequence-based Multimodal Apprenticeship Learning (SMAL), which is capable to simultaneously fusing temporal information and multimodal data, and to integrate robot perception with decision making. Read More

**Authors:**Si-Yu Li, Ke-Qin Liu, Long-Jin Yin, Wen-Xiao Wang, Xu-Qin Yang, Jun-Kai Yang, Haiwen Liu, Hua Jiang, Lin He

A variety of new and interesting correlated states have been predicted in graphene monolayer doped to Van Hove singularities (VHSs) of its density-of-state (DOS)1-6. However, tuning the Fermi energy to reach a VHS of graphene by either gating or chemical doping is prohibitively difficult, owning to their large energy distance (3 eV)7. Therefore, these correlated states, which arise from effects of strong electron-electron interactions at the VHSs, have remained experimentally so elusive. Read More

The "unidentified" infrared emission (UIE) features at 3.3, 6.2, 7. Read More

The so-called unidentified infrared emission (UIE) features at 3.3, 6.2, 7. Read More

The contribution of this paper contains two parts: first, we prove a supercloseness result for the partially penalized immersed finite element (PPIFE) method in [T. Lin, Y. Lin, and X. Read More

Background: MicroRNAs (miRNAs) play multiple roles in tumor biology [1]. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration [2]. Specifically, computational models predicted [3, 4] and experimental assays confirmed [5, 6] that miRNA activity is dependent on miRNA target abundance, and consequently, changes to the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. Read More

In this paper, we consider the numerical approximations for the fourth order Cahn-Hilliard equation with concentration dependent mobility, and the logarithmic Flory-Huggins potential. One challenge in solving such a diffusive system numerically is how to develop proper temporal discretization for nonlinear terms in order to preserve the energy stability at the time-discrete level. We resolve this issue by developing a set of the first and second order time marching schemes based on a novel, called "Invariant Energy Quadratization" approach. Read More

In this paper, we consider the numerical solution of a binary fluid-surfactant phase field model, in which the free energy contains a nonlinear coupling entropy, a Ginzburg-Landau double well potential, and a logarithmic Flory-Huggins potential. The resulting system consists of two coupled, nonlinear Cahn-Hilliard type equations. We develop a set of first and second order time marching schemes for this system using the "Invariant Energy Quadratization" approach, in particular, the system is transformed into an equivalent one by introducing appropriate auxiliary variables and all nonlinear terms are then treated semi-explicitly. Read More

How to develop efficient numerical schemes while preserving the energy stability at the discrete level is a challenging issue for the three component Cahn-Hilliard phase-field model. In this paper, we develop first and second order temporal approximation schemes based on the "Invariant Energy Quadratization" approach, where all nonlinear terms are treated semi-explicitly. Consequently, the resulting numerical schemes lead to a well-posed linear system with the symmetric positive definite operator to be solved at each time step. Read More

In this paper, we consider the numerical approximations for the commonly used binary fluid-surfactant phase field model that consists two nonlinearly coupled Cahn-Hilliard equations. The main challenge in solving the system numerically is how to develop easy-to-implement time stepping schemes while preserving the unconditional energy stability. We solve this issue by developing two linear and decoupled, first order and a second order time-stepping schemes using the so-called "Invariant Energy Quadratization" approach for the double well potentials and a subtle explicit-implicit technique for the nonlinear coupling potential. Read More

We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their eigen-coordinates, while the refined atomic eigen-subspace projection array adopted in our approach is demonstrated to be a competent invariant in structure comparison. Furthermore, a visual eigen-subspace projection function (EPF) is derived to characterize the surrounding configuration of an atom naturally. Read More

In this paper, we consider numerical approximations for the model of smectic-A liquid crystal flows. The model equation, that is derived from the variational approach of the de Gennes free energy, is a highly nonlinear system that couples the incompressible Navier-Stokes equations, and two nonlinear coupled second-order elliptic equations. Based on some subtle explicit--implicit treatments for nonlinear terms, we develop a unconditionally energy stable, linear and decoupled time marching numerical scheme. Read More

We address the person re-identification problem by effectively exploiting a globally discriminative feature representation from a sequence of tracked human regions/patches. This is in contrast to previous person re-id works, which rely on either single frame based person to person patch matching, or graph based sequence to sequence matching. We show that a progressive/sequential fusion framework based on long short term memory (LSTM) network aggregates the frame-wise human region representation at each time stamp and yields a sequence level human feature representation. Read More

In this paper, we consider numerical approximations of a hydrodynamically coupled phase field diblock copolymer model, in which the free energy contains a kinetic potential, a gradient entropy, a Ginzburg-Landau double well potential, and a long range nonlocal type potential. We develop a set of second order time marching schemes for this system using the "Invariant Energy Quadratization" approach for the double well potential, the projection method for the Navier-Stokes equation, and a subtle implicit-explicit treatment for the stress and convective term. The resulting schemes are linear and lead to symmetric positive definite systems at each time step, thus they can be efficiently solved. Read More

The verification of linearizability -- a key correctness criterion for concurrent objects -- is based on trace refinement whose checking is PSPACE-complete. This paper suggests to use \emph{branching} bisimulation instead. Our approach is based on comparing an abstract specification in which object methods are executed atomically to a real object program. Read More

In this paper, considering multiple interference regions simultaneously, an optimal antenna deployment problem for distributed Multi-Input Multi-Output (MIMO) radar is investigated. The optimal antenna deployment problem is solved by proposing an antenna deployment method based on Multi-Objective Particle Swarm Optimization (MOPSO). Firstly, we construct a multi-objective optimization problem for MIMO radar antenna deployment by choosing the interference power densities of different regions as objective functions. Read More

In this paper, we construct the simultaneous confidence band (SCB) for the nonparametric component in partially linear panel data models with fixed effects. We remove the fixed effects, and further obtain the estimators of parametric and nonparametric components, which do not depend on the fixed effects. We establish the asymptotic distribution of their maximum absolute deviation between the estimated nonparametric component and the true nonparametric component under some suitable conditions, and hence the result can be used to construct the simultaneous confidence band of the nonparametric component. Read More

We consider the numerical approximations of a two-phase hydrodynamics coupled phase-field model that incorporates the variable densities, viscosities and moving contact line boundary conditions. The model is a nonlinear, coupled system that consists of incompressible Navier--Stokes equations with the generalized Navier boundary condition, and the Cahn--Hilliard equations with moving contact line boundary conditions. By some subtle explicit--implicit treatments to nonlinear terms, we develop two efficient, unconditionally energy stable numerical schemes, in particular, a linear decoupled energy stable scheme for the system with static contact line condition, and a nonlinear energy stable scheme for the system with dynamic contact line condition. Read More

Mobile Crowdsourcing is a promising service paradigm utilizing ubiquitous mobile devices to facilitate largescale crowdsourcing tasks (e.g. urban sensing and collaborative computing). Read More

Decoherence due to charge noise is one of the central challenges in using spin qubits in semiconductor quantum dots as a platform for quantum information processing. Recently, it has been experimentally demonstrated in both Si and GaAs singlet-triplet qubits that the effects of charge noise can be suppressed if qubit operations are implemented using symmetric barrier control instead of the standard tilt control. Here, we investigate the key issue of whether the benefits of barrier control persist over the entire set of single-qubit gates by performing randomized benchmarking simulations. Read More

Actuator line model has been widely employed in wind turbine simulations. However, the standard actuator line model does not include a model for the turbine nacelle which can significantly impact turbine wake characteristics as shown in the literature (e.g. Read More

It is shown by particle-in-cell simulation that intense circularly polarized (CP) laser light can be contained in the cavity of a solid-density circular Al-plasma shell for hundreds of light-wave periods before it is dissipated by laser-plasma interaction. A right-hand CP laser pulse can propagate almost without reflection into the cavity through a highly magnetized overdense H-plasma slab filling the entrance hole. The entrapped laser light is then multiply reflected at the inner surfaces of the slab and shell plasmas, gradually losing energy to the latter. Read More

Mobile Crowdsensing is a promising paradigm for ubiquitous sensing, which explores the tremendous data collected by mobile smart devices with prominent spatial-temporal coverage. As a fundamental property of Mobile Crowdsensing Systems, temporally recruited mobile users can provide agile, fine-grained, and economical sensing labors, however their self-interest cannot guarantee the quality of the sensing data, even when there is a fair return. Therefore, a mechanism is required for the system server to recruit well-behaving users for credible sensing, and to stimulate and reward more contributive users based on sensing truth discovery to further increase credible reporting. Read More

In this paper, we consider the numerical approximations for the fourth order viscous Cahn-Hilliard equation with the hyperbolic relaxation. The main challenge in solving such a diffusive system numerically is how to develop high order temporal discretization for the hyperbolic and nonlinear terms that allows large time step while preserving the unconditional energy stability, i.e. Read More

**Affiliations:**

^{1}China University of Mining and Technology,

^{2}China University of Mining and Technology,

^{3}Polytechnic of Porto, Portugal,

^{4}Cankya University, Turkey

In this paper, a new fractional derivative involving the normalized sinc function without singular kernel is proposed. The Laplace transform is used to find the analytical solution of the anomalous heat-diffusion problems. The comparative results between classical and fractional-order operators are presented. Read More

We propose a scheme to realize fast generation of three-dimensional entanglement between two atoms via superadiabatic-based shortcuts in an atom-cavity-fiber system. The scheme is experimentally feasible because of the same form of the counterdiabatic Hamiltonian as that of the effective Hamiltonian. Besides, numerical simulations are given to prove that the scheme is strongly robust against variations in various parameters and decoherence. Read More

Secret sharing, in which a dealer wants to split a secret in such a way that any unauthorized subset of parties is unable to reconstruct it, plays a key role in cryptography. The security of quantum protocols for the task is guaranteed by the fact that Eve's any strategies to obtain secret information from encoded quantum states should cause a disturbance in the signal. Here, we propose a quantum secret sharing (classical information) scheme for $N$ parties based on totally different principle in which monitoring signal disturbance is no longer need. Read More

**Authors:**Maddalena Antonello, Bagdat Baibussinov, Vincenzo Bellini, Pietro Angelo Benetti, Fabrizio Boffelli, Arkadiusz Bubak, Elio Calligarich, Sandro Centro, Tommaso Cervi, Alessandra Cesana, Krzysztof Cieslik, Alfredo G. Cocco, Anna Dabrowska, Alexander Dermenev, Andrea Falcone, Christian Farnese, Angela Fava, Alfredo Ferrari, Daniele Gibin, Sergei Gninenko, Alberto Guglielmi, Malgorzata Haranczyk, Jacek Holeczek, Michal Janik, Mikhail Kirsanov, Jan Kisiel, Iza Kochanek, Justyna Lagoda, Alessandro Menegolli, Guang Meng, Claudio Montanari, Stanislaw Otwinowski, Pio Picchi, Francesco Pietropaolo, Piotr Plonski, Andrea Rappoldi, Gianluca Raselli, Massimo Rossella, Carlo Rubbia, Paola Sala, Alberto Scaramelli, Franco Sergiampietri, Maura Spanu, Dorota Stefan, Robert Sulej, Monika Szarska, Mario Terrani, Marta Torti, Francesco Tortorici, Filippo Varanini, Sandro Ventura, Chiara Vignoli, Hanguo Wang, Xiaofeng Yang, Agnieszka Zalewskag, Andrea Zani, Krzysztof Zaremba

The measurement of muon momentum by Multiple Coulomb Scattering is a crucial ingredient to the reconstruction of {\nu}{\mu} CC events in the ICARUS-T600 liquid argon TPC in absence of magnetic field, as in the search for sterile neutrinos at Fermilab where ICARUS will be exposed to ~1 GeV Booster neutrino beam. A sample of ~1000 stopping muons produced by charged current interactions of CNGS {\nu}{\mu} in the surrounding rock at the INFN Gran Sasso underground Laboratory provides an ideal benchmark in the few-GeV range since their momentum can be directly and independently obtained by the calorimetric measurement. Stopping muon momentum in the 0. Read More

We present a novel {\em ab initio} approach for computing intramolecular charge and energy transfer rates based upon a projection operator scheme that parses out specific internal nuclear motions that accompany the electronic transition. Our approach concentrates the coupling between the electronic and nuclear degrees of freedom into a small number of reduced harmonic modes that can be written as linear combinations of the vibrational normal modes of the molecular system about a given electronic minima. Using a time-convolutionless master-equation approach, parameterized by accurate quantum-chemical methods, we benchmark the approach against experimental results and predictions from Marcus theory for triplet energy transfer for a series of donor-bridge-acceptor systems. Read More

Numerous single-image super-resolution algorithms have been proposed in the literature, but few studies address the problem of performance evaluation based on visual perception. While most super-resolution images are evaluated by fullreference metrics, the effectiveness is not clear and the required ground-truth images are not always available in practice. To address these problems, we conduct human subject studies using a large set of super-resolution images and propose a no-reference metric learned from visual perceptual scores. Read More

Chiral anomaly induced negative magnetoresistance (NMR) has been widely used as a critical transport evidence on the existence of Weyl fermions in topological semimetals. In this mini review, we discuss the general observation of the NMR phenomena in non-centrosymmetric NbP and NbAs. We show that NMR can be contributed by intrinsic chiral anomaly of Weyl fermions and/or extrinsic effects, such as superimposition of Hall signals, field-dependent inhomogeneous current flow in the bulk, i. Read More

High-dimensional crowdsourced data collected from a large number of users produces rich knowledge for our society. However, it also brings unprecedented privacy threats to participants. Local privacy, a variant of differential privacy, is proposed as a means to eliminate the privacy concern. Read More

We investigate local fractional nonlinear Riccati differential equations (LFNRDE) by transforming them into local fractional linear ordinary differential equations. The case of LFNRDE with constant coefficients is considered and non-differentiable solutions for special cases obtained. Read More

In the present paper, we address a class of the fractional derivatives of constant and variable orders for the first time. Fractional-order relaxation equations of constants and variable orders in the sense of Caputo type are modeled from mathematical view of point. The comparative results of the anomalous relaxation among the various fractional derivatives are also given. Read More

Boundary incompleteness raises great challenges to automatic prostate segmentation in ultrasound images. Shape prior can provide strong guidance in estimating the missing boundary, but traditional shape models often suffer from hand-crafted descriptors and local information loss in the fitting procedure. In this paper, we attempt to address those issues with a novel framework. Read More

Natural language understanding and dialogue policy learning are both essential in conversational systems that predict the next system actions in response to a current user utterance. Conventional approaches aggregate separate models of natural language understanding (NLU) and system action prediction (SAP) as a pipeline that is sensitive to noisy outputs of error-prone NLU. To address the issues, we propose an end-to-end deep recurrent neural network with limited contextual dialogue memory by jointly training NLU and SAP on DSTC4 multi-domain human-human dialogues. Read More

The number balancing (NBP) problem is the following: given real numbers $a_1,\ldots,a_n \in [0,1]$, find two disjoint subsets $I_1,I_2 \subseteq [n]$ so that the difference $|\sum_{i \in I_1}a_i - \sum_{i \in I_2}a_i|$ of their sums is minimized. An application of the pigeonhole principle shows that there is always a solution where the difference is at most $O(\frac{\sqrt{n}}{2^n})$. Finding the minimum, however, is NP-hard. Read More

We present a theoretical study of a four-electron four-quantum-dot system based on molecular orbital methods, which hosts a pair of singlet-triplet spin qubits. We explicitly take into account of the admixture of electron wave functions in all dots, and have found that this mixing of wave functions has consequences on the energy spectrum, exchange interaction and the gate crosstalk of the system. Specifically, we have found that when the two singlet-triplet qubits are close enough, some of the states are no longer dominated by the computational basis states and the exchange interaction can not be understood as the energy difference between the singlet and triplet states. Read More

In this paper, we first establish an $L^2$-type Dolbeault isomorphism for logarithmic differential forms by H\"{o}rmander's $L^2$-estimates. By using this isomorphism and the construction of smooth Hermitian metrics, we obtain a number of new vanishing theorems for sheaves of logarithmic differential forms on compact K\"ahler manifolds with simple normal crossing divisors, which generalize several classical vanishing theorems, including Norimatsu's vanishing theorem, Gibrau's vanishing theorem, Le Potier's vanishing theorem and a version of the Kawamata-Viehweg vanishing theorem. Read More

Physical library collections are valuable and long standing resources for knowledge and learning. However, managing books in a large bookshelf and finding books on it often leads to tedious manual work, especially for large book collections where books might be missing or misplaced. Recently, deep neural models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) have achieved great success for scene text detection and recognition. Read More