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作者： Yunlong Zeng Xiafei Li Chunran Tang Haowen Huang Yajing Wang Zhonghua Su Huan Zhao Yamei Hu Jin Li Key Laboratory of Theoretical Chemistry and Molecular Simulation of Ministry of Education of China School of Chemistry and Chemical Engineering Hunan University of Science and Technology State Key Laboratory for Chemo/Biosensing and Chemometrics College of Chemistry and Chemical Engineering Hunan University

A simple A green protocol for synthesis of high quality, water-soluble and biocompatible Cd S QDs have been developed in aqueous solution with amylum as stabilizing agentThe QDs were characterized by AMF and spectral methodsA fluorescence quenching method was developed for determination of iron(ΙΙΙ) with water soluble Cd S quantum dots(QDs) as fluorescence probeIn p H 8.5 boric acid–borax buffer solution, the QDs show a high selective to ferric ionThe common cations, such as Ca2+, Mg2+, Zn2+, Fe2+ et al, have no effect on interference but copper ionThe fluorescence intensity of the QDs decreased linearly with the iron(QDs) concentration in the range of 200 μM to 60 n M with a detection limit of 20 n MIt has been applied to determinate of iron in Angelica, Astragalus, Shouwu, ligusticum wallichii and radix rehmanniae recen.

关键词： Trace iron chinese herbal medicine quantum dots fluorescence probe amylum modified cds quantum dots

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A computationally-efficient sandbox algorithm for multifractal analysis of large-scale complex networks with tens of millions of nodes

arXiv

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arXiv 2020年

作者： Ding, Yuemin Liu, Jin-Long Li, Xiaohui Tian, Yu-Chu Yu, Zu-Guo School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science Queensland University of Technology BrisbaneQLD4000 Australia Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan411105 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan Hubei430081 China

The fractality of complex networks has attracted much attention with extensive investigations over the last 15 years. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful tool to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. One of the widely used methods for fractal analysis is box-covering. It uses the minimum number of covering boxes to calculate the fractal dimension of complex networks, and is known to be NP-hard. More severely, in comparison with fractal analysis algorithms, MFA algorithms have much higher computational complexity. Among various MFA algorithms for complex networks, the sandbox MFA algorithm behaves with the best computational efficiency. However, the existing sandbox algorithm is still computationally expensive. Thus, so far it has only been applied to small-scale complex networks of the size of about tens of thousands of nodes. It becomes challenging to implement the MFA for large-scale networks with tens of millions of nodes. It is also not clear whether or not MFA results can be improved by a largely increased size of a theoretical network. To tackle these challenges, a computationally-efficient sandbox algorithm (CESA) is presented in this paper for MFA of large-scale networks. Distinct from the existing sandbox algorithm that uses the shortest-path distance matrix to obtain the required information for MFA of complex networks, our CESA employs the breadth-first search (BFS) technique to directly search the neighbor nodes of each layer of center nodes, and then to retrieve the required information. Our CESA's input is a sparse data structure derived from the compressed sparse row (CSR) format designed for compressed storage of the adjacency matrix of large-scale network. A theoretical analysis reveals that the CESA reduces the time complexity of the existing sandbox algorithm from cubic to quadratic, and also improves the space complexity from quadratic

关键词： computational efficiency

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Micro-nanobubble–assisted As(III) removal from water by Ni-doped MOF materials

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Environmental science and Pollution Research 2024年第31期31卷 43913-43926页

作者： Ye, Jian Zuo, Yize Chen, Qiang Yang, Zhiming Liu, Shaobo Yang, Chunping Tan, Xiaofei Hunan University Changsha410082 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China Shenzhen Research Institute of Hunan University Shenzhen518055 China School of Architecture and Art Central South University Changsha410083 China Academy of Environmental and Resource Sciences School of Environmental Science and Engineering Guangdong University of Petrochemical Technology Guangdong Maoming525000 China Hunan Chuke Taiyan New Materials Co. Ltd. Jishou416000 China

Micro-nanobubbles (MNBs) can form reactive oxygen species (ROS) with high oxidizing potential. In this study, nickel-doped metal–organic framework materials (MOFs) capable of activating molecular oxygen were synthesized using trivalent arsenic (As(III)) as a target pollutant and combined with peroxymonosulfate (PMS) to construct a MOF/MNB/PMS system. The results included the rapid oxidation of As(III), the successful absorption of oxidized As(V), and finally the efficient removal of As. The effects of pH, amount of PMS used, and preparation time of MNBs on the As removal performance of the MOF/MNB/PMS system were investigated experimentally. The changes in the properties of the materials before and after the reaction were analyzed by XPS, and it was found that the main active sites on the surface of the MOFs were the metal elements and the pyridine nitrogen near the carbon atom. The regular morphology and elemental composition of the MOFs were determined by TEM scanning and EDS test, which indicated the presence of nickel. XRD tests before and after the reaction showed that the MOFs were structurally stable. The results of the free radical burst experiments show that the single linear oxygen (1O2) is the main active substance in the system, and that the MNBs are key factors by which the system achieves efficient oxidation performance. In addition to providing a sustainable supply of molecular oxygen to the MOFs during the reaction process, coupling the MNBs with PMS was found to improve the oxidation capacity of the system. The results of this study thus provide a new concept for As removal and advanced oxidation in water bodies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Molecular oxygen

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Determination of Hydrogen Peroxide Residue in Food Using CdS Quantum Dots as Fluorescence Probes

Determination of Hydrogen Peroxide Residue in Food Using CdS...

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2011 SSITE International Conference on Future Material Research and Industry Application(FMRIA 2011)

作者： Yunlong Zeng Yajing Wang Zhonghua Su Chunran Tang Key Laboratory of Theoretical Chemistry and Molecular Simulation of Ministry of Education of China School of Chemistry and Chemical Engineering Hunan University of Science and Technology State Key Laboratory for Chemo/Biosensing and Chemometrics College of Chemistry and Chemical Engineering Hunan University

A simple and accurate method for determination of hydrogen peroxide(H2O2) using carboxymethyl cellulose coated Cd S quantum dots(QDs) as a fluorescence probe was establishedThe influence factors of the fluorescence quenching system and the optimum conditions were investigated for analysis of hydrogen peroxideIt was found that the maximum relative fluorescence quenching intensity produced at p H 8.5 in 0.035 mol/L KH2PO4-Na2HPO4, when the concentration of Cd S QDs was 1.9×10-3 mol/L and the reacting time and temperature were 45 minutes and 30℃, respectivelyUnder the optimum conditions, the relative fluorescence quenching intensity has a linear relationship with the logarithmic concentration of H2O2 in the range from 3×10-5 to 5×10-2 mol/LThe limit of the detection is 2.3×10-6 mol/L for H2O2The method was used to determinate the amount of remained H2O2 in milk and Calcium Tablets successfully.

关键词： Food health food trace hydrogen peroxide carboxymethyl cellulose coated cds qds fluorescence quenching

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A decoupling two-grid method for the time-dependent poisson-nernst-planck equations

arXiv

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arXiv 2018年

作者： Shen, Ruigang Shu, Shi Yang, Ying Lu, Benzhuo School of Mathematics and Computational Science Xiangtan University Xiangtan Hunan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan411105 China School of Mathematics and Computational Science Guangxi Colleges Universities Key Laboratory of Data Analysis and Computation Guangxi Key Laboratory of Cryptography and information Security Guilin University of Electronic Technology Guilin Guangxi541004 China Institute of Computational Mathematics and Scientific/Engineering Computing National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

We study a two-grid strategy for decoupling the time-dependent Poisson-Nernst-Planck equations describing the mass concentration of ions and the electrostatic potential. The computational system is decoupled to smaller systems by using coarse space solutions at each time level, which can speed up the solution process compared with the finite element method combined with the Gummel iteration. We derive the optimal error estimates in L2 norm for both semi- and fully discrete finite element approximations. Based on the a priori error estimates, the error estimates in H1 norm are presented for the two-grid algorithm. The theoretical results indicate this decoupling method can retain the same accuracy as the finite element method. Numerical experiments including the Poisson-Nernst-Planck equations for an ion channel show the efficiency and effectiveness of the decoupling two-grid method. Copyright © 2018, The Authors. All rights reserved.

关键词： Finite element method

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Two-Relaxation-Time Regularized Lattice Boltzmann Model for Navier-Stokes Equations

SSRN

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SSRN 2024年

作者： Yu, Yuan Qin, Zuojian Gu, Qingqing Chen, Siwei Shu, Shi Yuan, Hai-Zhuan School of Mathematics and Computational Science Xiangtan University Xiangtan411105 China National Center for Applied Mathematics in Hunan Xiangtan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan411105 China School of Energy and Power Engineering University of Shanghai for Science and Technology Shanghai200093 China

In this paper, we develop a two-relaxation-time regularized lattice Boltzmann (TRT-RLB) model for simulating weakly compressible isothermal flows, which demonstrates superior stability and accuracy over existing models such as the regularized lattice Boltzmann (RLB) and two-relaxation-time (TRT) models. In this model, a free relaxation parameter, τs,2, is employed to relax the regularized non-equilibrium third-order terms. Chapman-Enskog analysis reveals that our model can accurately recover the Navier-Stokes equations. Theoretical analysis and numerical experiments both confirm the model’s ability to eliminate non-physical numerical slip associated with the half-way bounce-back scheme. Our simulations of the double shear layer problem and Taylor-Green vortex flow exhibit pronounced advantages in terms of stability and accuracy, even under super-high Reynolds numbers as high as Re = 107. Additionally, the simulation of creeping flow around a square cylinder showcases the model’s precision in computing ultra-low Reynolds numbers down to Re = 10−7. This robust capability confirms the proposed model as a highly effective and adaptable tool in computational fluid dynamics. © 2024, The Authors. All rights reserved.

关键词： Navier Stokes equations

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Paired 2-Disjoint Path Covers of Burnt Pancake Graphs with Faulty Elements

SSRN

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SSRN 2024年

作者： Li, Pingshan Chen, Congzhen Liu, Xianglin Xiangtan University China School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China Key Laboratory of Intelligent Computing & Information Processing of Education China Key Laboratory for Computation and Simulation in Science and Engineering China National Center for Applied Mathematics in Hunan China Guangxi Vocational University of Agriculture Guangxi Nanning530007 China

It is a key issue in parallel processing to find $k$-disjoint paths in the underlying graph of an interconnected network such that these disjoint paths pass through all vertices of the network, this is known as paired $k$-disjoint path cover problems or unpaired $k$-disjoint path cover problems. In 2024, Dvo\v{r}\'{a}k and Gu (Theoretical Computer science, $986 (2024) 114327$) showed that there exist two disjoint paths whose vertices partition the vertex of the burnt pancake graph even if it contains at most $n-4$ faulty elements (vertices or edges) and they proposed an open problem: is it possible to improve the upper bound $n-4$ to $n-3$? In this paper, we provide a positive answer to this problem. © 2024, The Authors. All rights reserved.

关键词： Hamiltonians

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PRISTA-Net: Deep Iterative Shrinkage Thresholding Network for Coded Diffraction Patterns Phase Retrieval

arXiv

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arXiv 2023年

作者： Liu, Aoxu Fan, Xiaohong Yang, Yin Zhang, Jianping The School of Mathematics and Computational Science Xiangtan University Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan411105 China The School of Mathematics and Computational Science Xiangtan University the Key Laboratory of Intelligent Computing & Information Processing the Ministry of Education Xiangtan411105 China The School of Mathematics and Computational Science Xiangtan University the National Center for Applied Mathematics in Hunan Xiangtan411105 China

The problem of phase retrieval (PR) involves recovering an unknown image from limited amplitude measurement data and is a challenge nonlinear inverse problem in computational imaging and image processing. However, many of the PR methods are based on black-box network models that lack interpretability and plug-and-play (PnP) frameworks that are computationally complex and require careful parameter tuning. To address this, we have developed PRISTA-Net, a deep unfolding network (DUN) based on the first-order iterative shrinkage thresholding algorithm (ISTA). This network utilizes a learnable nonlinear transformation to address the proximal-point mapping sub-problem associated with the sparse priors, and an attention mechanism to focus on phase information containing image edges, textures, and structures. Additionally, the fast Fourier transform (FFT) is used to learn global features to enhance local information, and the designed logarithmic-based loss function leads to significant improvements when the noise level is low. All parameters in the proposed PRISTA-Net framework, including the nonlinear transformation, threshold parameters, and step size, are learned end-to-end instead of being manually set. This method combines the interpretability of traditional methods with the fast inference ability of deep learning and is able to handle noise at each iteration during the unfolding stage, thus improving recovery quality. Experiments on Coded Diffraction Patterns (CDPs) measurements demonstrate that our approach outperforms the existing state-of-the-art methods in terms of qualitative and quantitative evaluations. Our source codes are available at https://***/liuaxou/PRISTA-Net. Copyright © 2023, The Authors. All rights reserved.

关键词： Mapping

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