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Xiaoyan Zhang

Publications and source records attributed to Xiaoyan Zhang.

At least 55 records · Page 3Linked to original sources

Streaming Algorithms for the $k$-Submodular Cover Problem

Given a natural number $k\ge 2$, we consider the $k$-submodular cover problem ($k$-SC). The objective is to find a minimum cost subset of a ground set $\mathcal{X}$ subject to the value of a $k$-submodular utility function being at least a certain predetermined value $τ$. For this problem, we design a bicriteria algorithm with a cost at most $O(1/ε)$ times the optimal value, while the utility is at least $(1-ε)τ/r$, where $r$ depends on the monotonicity of $g$.

cs.DS↗

Deformed relativistic Hartree-Bogoliubov theory in continuum with a point-coupling functional. II. Examples of odd Nd isotopes

The aim of this work is to extend the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) based on the point-coupling density functionals to odd-$A$ and odd-odd nuclei and examine its applicability by taking odd-$A$ Nd isotopes as examples. In the DRHBc theory, the densities and potentials with axial deformation are expanded in terms of Legendre polynomials, and the relativistic Hartree-Bogoliubov equations are solved in a Dirac Woods-Saxon basis to include the continuum effects. For an odd-$A$ or odd-odd nucleus, the blocking effect of unpaired nucleon(s) is taken into account with the equal filling approximation. To determine its ground state, an automatic blocking procedure is adopted, in which the orbital with the lowest quasiparticle energy is blocked during the iteration. This procedure is justified by comparing with the results from the orbital-fixed blocking calculations, in which the blocked orbital near the Fermi surface is fixed during the iteration. The ground states for both light and heavy nuclei can be provided by the automatic blocking procedure as the orbital-fixed blocking procedure, but with considerably reduced computational cost. The numerical details for even-even nuclei are found to be valid for odd-$A$ and odd-odd nuclei as well. Taking Nd isotopes including both even-even and odd-$A$ ones as examples, the calculated ground-state properties with PC-PK1 are in good agreement with the available experimental data. This work paves the way to construct the DRHBc mass table including all even-even, odd-$A$ and odd-odd nuclei in the nuclear chart.

nucl-th↗

The evolution of k-shell in syndication networks reveals financial performance of venture capital institutions

Venture capital (VC) is a relatively newly emergent industry that is still subject to large uncertainties in China. Therefore, building a robust social network with other VC institutions is a good way to share information, various resources, and benefit from skill and knowledge complementarity to against risks. Strong evidences indicate that better networked VC institutions are of a better financial performance, however, most of previous works overlook the evolution of VC institutions and only focus on some simple topology indicators of the static syndication network, which also neglects higher-order network structure and cannot give a comprehensive evaluation. In this paper, based on VC investment records in the Chinese market, we construct temporal syndication networks between VC institutions year by year. As k-shell decomposition considers higher-order connection patterns, we employ k-shell as an evaluation of the influence of VC institutions in syndication networks. By clustering time series of k-shell values, the VC institutions in China fall into five groups that are quite different from each other on financial performances and investment behaviors. This, in turn, proves the power of our method that only based on proper sequential network properties, we can reveal their financial investment performance. Compared to other network centrality measurements, k-shell is a better indicator that is indicated by a smaller intra-group distance and a larger inter-group distance.

physics.soc-ph↗

Acceleration for Timing-Aware Gate-Level Logic Simulation with One-Pass GPU Parallelism

Witnessing the advancing scale and complexity of chip design and benefiting from high-performance computation technologies, the simulation of Very Large Scale Integration (VLSI) Circuits imposes an increasing requirement for acceleration through parallel computing with GPU devices. However, the conventional parallel strategies do not fully align with modern GPU abilities, leading to new challenges in the parallelism of VLSI simulation when using GPU, despite some previous successful demonstrations of significant acceleration. In this paper, we propose a novel approach to accelerate 4-value logic timing-aware gate-level logic simulation using waveform-based GPU parallelism. Our approach utilizes a new strategy that can effectively handle the dependency between tasks during the parallelism, reducing the synchronization requirement between CPU and GPU when parallelizing the simulation on combinational circuits. This approach requires only one round of data transfer and hence achieves one-pass parallelism. Moreover, to overcome the difficulty within the adoption of our strategy in GPU devices, we design a series of data structures and tune them to dynamically allocate and store new-generated output with uncertain scale. Finally, experiments are carried out on industrial-scale open-source benchmarks to demonstrate the performance gain of our approach compared to several state-of-the-art baselines.

cs.DS↗

Toeplitz operators on $\mathcal L^p$-spaces of a tree

Let $T$ be a rooted, countable infinite tree without terminal vertices. In the present paper, we characterize the spectra, self-adjointness and positivity of Toeplitz operators on the spaces of $p$-summable functions on $T$. Moreover, we obtain a necessary and sufficient condition for Toeplitz operators to have finite rank on such function spaces.

math.FA↗

Bayesian Optimization of 2D Echocardiography Segmentation

Bayesian Optimization (BO) is a well-studied hyperparameter tuning technique that is more efficient than grid search for high-cost, high-parameter machine learning problems. Echocardiography is a ubiquitous modality for evaluating heart structure and function in cardiology. In this work, we use BO to optimize the architectural and training-related hyperparameters of a previously published deep fully convolutional neural network model for multi-structure segmentation in echocardiography. In a fair comparison, the resulting model outperforms this recent state-of-the-art on the annotated CAMUS dataset in both apical two- and four-chamber echo views. We report mean Dice overlaps of 0.95, 0.96, and 0.93 on left ventricular (LV) endocardium, LV epicardium, and left atrium respectively. We also observe significant improvement in derived clinical indices, including smaller median absolute errors for LV end-diastolic volume (4.9mL vs. 6.7), end-systolic volume (3.1mL vs. 5.2), and ejection fraction (2.6% vs. 3.7); and much tighter limits of agreement, which were already within inter-rater variability for non-contrast echo. These results demonstrate the benefits of BO for echocardiography segmentation over a recent state-of-the-art framework, although validation using large-scale independent clinical data is required.

eess.IV↗

See Blue Sky: Deep Image Dehaze Using Paired and Unpaired Training Images

The issue of image haze removal has attracted wide attention in recent years. However, most existing haze removal methods cannot restore the scene with clear blue sky, since the color and texture information of the object in the original haze image is insufficient. To remedy this, we propose a cycle generative adversarial network to construct a novel end-to-end image dehaze model. We adopt outdoor image datasets to train our model, which includes a set of real-world unpaired image dataset and a set of paired image dataset to ensure that the generated images are close to the real scene. Based on the cycle structure, our model adds four different kinds of loss function to constrain the effect including adversarial loss, cycle consistency loss, photorealism loss and paired L1 loss. These four constraints can improve the overall quality of such degraded images for better visual appeal and ensure reconstruction of images to keep from distortion. The proposed model could remove the haze of images and also restore the sky of images to be clean and blue (like captured in a sunny weather).

cs.CV↗

A minimum semi-degree sufficient condition for one-to-many disjoint path covers in semicomplete digraphs

Let $D$ be a digraph. We define the minimum semi-degree of $D$ as $δ^{0}(D) := \min \{δ^{+}(D), δ^{-}(D)\}$. Let $k$ be a positive integer, and let $S = \{s\}$ and $T = \{t_{1}, \dots ,t_{k}\}$ be any two disjoint subsets of $V(D)$. A set of $k$ internally disjoint paths joining source set $S$ and sink set $T$ that cover all vertices $D$ are called a one-to-many $k$-disjoint directed path cover ($k$-DDPC for short) of $D$. A digraph $D$ is semicomplete if for every pair $x,y$ of vertices of it, there is at least one arc between $x$ and $y$. In this paper, we prove that every semicomplete digraph $D$ of sufficiently large order $n$ with $δ^{0}(D) \geq \lceil (n+k-1)/2\rceil$ has a one-to-many $k$-DDPC joining any disjoint source set $S$ and sink set $T$, where $S = \{s\}, T = \{t_{1}, \dots, t_{k}\}$.

math.CO↗

Nuclear mass table in deformed relativistic Hartree-Bogoliubov theory in continuum: I. even-even nuclei

Ground-state properties of even-even nuclei with $8\le Z\le120$ from the proton drip line to the neutron drip line have been investigated using the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) with the density functional PC-PK1. With the effects of deformation and continuum included simultaneously, 2583 even-even nuclei are predicted to be bound. The calculated binding energies, two-nucleon separation energies, root-mean-square (rms) radii of neutron, proton, matter, and charge distributions, quadrupole deformations, and neutron and proton Fermi surfaces are tabulated and compared with available experimental data. The rms deviation from the 637 mass data is 1.518 MeV, providing one of the best microscopic descriptions for nuclear masses. The drip lines obtained from DRHBc calculations are compared with other calculations, including the spherical relativistic continuum Hartree-Bogoliubov (RCHB) and triaxial relativistic Hartree-Bogoliubov (TRHB) calculations with PC-PK1. The deformation and continuum effects on the limits of the nuclear landscape are discussed. Possible peninsulas consisting of bound nuclei beyond the two-neutron drip line are predicted. The systematics of the two-nucleon separation energies, two-nucleon gaps, rms radii, quadrupole deformations, potential energy curves, neutron densities, neutron mean-field potentials, and pairing energies in the DRHBc calculations are also discussed. In addition, the $α$ decay energies extracted are in good agreement with available data.

nucl-th↗

Exploring Optical and Electrical Gas Detection Based on Zinc-Tetraphenylporphyrin Sensitizer

We developed optical waveguide (OWG), ultraviolet-visible spectrophotometry (UV-vis), and electrically operated gas sensors by utilizing zinc-tetraphenylporphyrin (ZnTPP) as sensitizer. Strikingly, ZnTPP thin-film/K+-exchanged glass optical waveguide (OWG) sensing element exhibits a superior signal-to-noise ratio (SNR) of 109.6 upon 1 ppm NO2 gas injection, which is 29.5 and 3.8 times larger than that of UV-vis (absorbance at wavelength of 438 nm) and ZnTPP electrical sensing elements prepared on an alumina ceramic tube, respectively. Further results on Fourier Infrared spectra (FT-IR) and UV-vis spectra, confirm a strong chemical adsorption of NO2 gas on ZnTPP. Therefore, our studies highlight the selection of suitable detection technique for analyte sensing with ZnTPP.

physics.optics↗

Packing Strong Subgraph in Digraphs

In this paper, we study two types of strong subgraph packing problems in digraphs, including internally disjoint strong subgraph packing problem and arc-disjoint strong subgraph packing problem. These problems can be viewed as generalizations of the famous Steiner tree packing problem and are closely related to the strong arc decomposition problem. We first prove the NP-completeness for the internally disjoint strong subgraph packing problem restricted to symmetric digraphs and Eulerian digraphs. Then we get inapproximability results for the arc-disjoint strong subgraph packing problem and the internally disjoint strong subgraph packing problem. Finally we study the arc-disjoint strong subgraph packing problem restricted to digraph compositions and obtain some algorithmic results by utilizing the structural properties.

math.CO↗

Component factors in $K_{1,r}$-free graphs

A graph is said to be $K_{1,r}$-free if it does not contain an induced subgraph isomorphic to $K_{1,r}$. An $\mathcal{F}$-factor is a spanning subgraph $H$ such that each connected component of $H$ is isomorphic to some graph in $\mathcal{F}$. In particular, $H$ is called an $\{P_2,P_3\}$-factor of $G$ if $\mathcal{F}=\{P_2,P_3\}$; $H$ is called an $\mathcal{S}_n$-factor of $G$ if $\mathcal{F}=\{K_{1,1},K_{1,2},K_{1,3},...,K_{1,n}\}$, where $n\geq2$. A spanning subgraph of a graph $G$ is called a $\mathcal{P}_{\geq k}$-factor of $G$ if its each component is isomorphic to a path of order at least $k$, where $k\geq2$. A graph $G$ is called a $\mathcal{F}$-factor covered graph if there is a $\mathcal{F}$-factor of $G$ including $e$ for any $e\in E(G)$. In this paper, we give a minimum degree condition for a $K_{1,r}$-free graph to have an $\mathcal{S}_n$-factor and a $\mathcal{P}_{\geq 3}$-factor, respectively. Further, we obtain sufficient conditions for $K_{1,r}$-free graphs to be $\mathcal{P}_{\geq 2}$-factor, $\mathcal{P}_{\geq 3}$-factor or $\{P_2,P_3\}$-factor covered graphs. In addition, examples show that our results are sharp.

math.CO↗

Ultrasensitive Field-Effect Biosensors Enabled by the Unique Electronic Properties of Graphene

This review provides a critical overview of current developments on nanoelectronic biochemical sensors based on graphene. Composed of a single layer of conjugated carbon atoms, graphene has outstanding high carrier mobility and low intrinsic electrical noise, but a chemically inert surface. Surface functionalization is therefore crucial to unravel graphene sensitivity and selectivity for the detection of targeted analytes. To achieve optimal performance of graphene transistors for biochemical sensing, the tuning of the graphene surface properties via surface functionalization and passivation is highlighted, as well as the tuning of its electrical operation by utilizing multifrequency ambipolar configuration and a high frequency measurement scheme to overcome the Debye screening to achieve low noise and highly sensitive detection. Potential applications and prospectives of ultrasensitive graphene electronic biochemical sensors ranging from environmental monitoring and food safety, healthcare and medical diagnosis, to life science research, are presented as well.

cond-mat.mtrl-sci↗

Facile and Ultraclean Graphene-on-Glass Nanopores by Controlled Electrochemical Etching

A wide range of approaches have been explored to meet the challenges of graphene nanostructure fabrication, all requiring complex and high-end nanofabrication platform and suffering from surface contaminations, potentially giving electrical noise and increasing the thickness of the atomically thin graphene membrane. Here, with the use of an electrical pulse on a low capacitance graphene-on-glass (GOG) membrane, we fabricated clean graphene nanopores on commercially available glass substrates with exceptionally low electrical noise. In situ liquid AFM studies and electrochemical measurements revealed that both graphene nanopore nucleation and growth stem from the electrochemical attack on carbon atoms at defect sites, ensuring the creation of a graphene nanopore. Strikingly, compared to conventional TEM drilled graphene nanopores on SiN supporting membranes, GOG nanopores featured an order-of-magnitude reduced broadband noise, which we ascribed to the electrochemical refreshing of graphene nanopore on mechanically stable glass chips with negligible parasitic capacitance (1 pF). Further experiments on double-stranded DNA translocations demonstrated a greatly reduced current noise, and also confirmed the activation of single nanopores. Therefore, the exceptionally low noise and ease of fabrication will facilitate the understanding of the fundamental property and the application of such atomically thin nanopore sensors.

cond-mat.mtrl-sci↗

Approximation algorithms for general cluster routing problem

Graph routing problems have been investigated extensively in operations research, computer science and engineering due to their ubiquity and vast applications. In this paper, we study constant approximation algorithms for some variations of the general cluster routing problem. In this problem, we are given an edge-weighted complete undirected graph $G=(V,E,c),$ whose vertex set is partitioned into clusters $C_{1},\dots ,C_{k}.$ We are also given a subset $V'$ of $V$ and a subset $E'$ of $E.$ The weight function $c$ satisfies the triangle inequality. The goal is to find a minimum cost walk $T$ that visits each vertex in $V'$ only once, traverses every edge in $E'$ at least once and for every $i\in [k]$ all vertices of $C_i$ are traversed consecutively.

cs.DS↗

Electrical probing of COVID-19 spike protein receptor binding domain via a graphene field-effect transistor

Here, in an effort towards facile and fast screening/diagnosis of novel coronavirus disease 2019 (COVID-19), we combined the unprecedently sensitive graphene field-effect transistor (Gr-FET) with highly selective antibody-antigen interaction to develop a coronavirus immunosensor. The Gr-FET immunosensors can rapidly identify (about 2 mins) and accurately capture the COVID-19 spike protein S1 (which contains a receptor binding domain, RBD) at a limit of detection down to 0.2 pM, in a real-time and label-free manner. Further results ensure that the Gr-FET immunosensors can be promisingly applied to screen for high-affinity antibodies (with binding constant up to 2*10^11 M^-1 against the RBD) at concentrations down to 0.1 pM. Thus, our developed electrical Gr-FET immunosensors provide an appealing alternative to address the early screening/diagnosis as well as the analysis and rational design of neutralizing-antibody locking methods of this ongoing public health crisis.

physics.app-ph↗

The core inverse and constrained matrix approximation problem

In this paper,we study the constrained matrix approximation problem in the Frobenius norm by using the core inverse:\begin{align}\nonumber \left\|{Mx - b} \right\|_F=\min\ \ {\rm subject\ to} \ \ {x\in\mathcal{R}(M)} ,\end{align} where $M\in\mathbb{C}^{\texttt{CM}}_n$. We get the unique solution to the problem, provide two Cramer's rules for the unique solution, and establish two new expressions for the core inverse.

math.RA↗