检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Zhao, Wenyu Li, Jing Liu, Mengyue Wang, Rui Zhang, Boxuan Meng, Xiang-Zhou Zhang, ShengWei School of Hydraulic and Environmental Engineering Changsha University of Science & Technology Changsha410114 China Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province School of Hydraulic and Environmental Engineering Changsha University of Science and Technology Changsha410004 China State Key Laboratory of Water Environment Simulation School of Environment Beijing Normal University Beijing100875 China State Key Laboratory of Pollution Control and Resources Reuse College of Environmental Science and Engineering Tongji University Shanghai200092 China

While the Xiangjiang (XJ) River acts as an inland drinking water source, it may experience microplastics emissions originating from Changsha (CS) City. The aim of this study was to characterize the occurrence and distribution of microplastics in the XJ River during both the flooding and dry periods. Samples of surface river water and sediment of the XJ River in CS City were collected in August and December, 2020 and analyzed for composition of microplastics. The results showed ubiquitous presence of microplastics in surface water and sediment of the XJ River at abundances of 0.72–18.6 (7.32 ± 2.36) items L−1 and 26.3–302 (150 ± 75.6) items kg−1 dry weight (dw), respectively, during the flooding period, lower than those of 2.88–17.7 (11.0 ± 3.08) items L−1 and 27.0–651 (249 ± 182) items kg−1 dw during the dry period. Higher microplastic abundance was found mainly in urban centers as well as downstream of wastewater treatment plants, implying anthropogenic activities to be a source of microplastics. The high variances in the shapes, color, and types of microplastics in surface waters and sediments implied the action of specific enrichment processes and long-term sources of microplastics pollution. Most (60%) of microplastics particles in both the river water and sediment were in the size range of 50–100 μm. Fourier transform infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) indicated that microplastics were subjected to weathering in the environment, contributing to the production of oxygen-containing functional groups and surface cleavage features. Energy Dispersive Spectroscopy (EDS) showed that microplastics bonded to multiple heavy metals, emphasizing the complex nature of microplastics pollution. The results indicate concerning levels of microplastics in the XJ River, despite its status as a high-quality water source. © 2023, The Authors. All rights reserved.

关键词： Sediments

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Analysis of Image Lag Degradation in PPD CISs Induced by Total Ionizing Dose and Displacement Radiation Damage

Analysis of Image Lag Degradation in PPD CISs Induced by Tot...

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European Conference on Radiation and its Effects on Components and Systems (RADECS)

作者： Zujun Wang Yuanyuan Xue Jing Liu Wei Chen Wuying Ma Baoping He Zhibin Yao Jiangkun Sheng State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear Technology P.O. Box 69-10 Xi’an of Shaanxi Province China School of materials science and engineering Xiangtan University Hunan China

ISBN: (纸本)9781538612620;9781538612613

The experiments of the total ionizing dose (TID) and displacement radiation effects on the pinned photodiode (PPD) CMOS image sensors (CISs) are presented. The CISs are manufactured using a standard 0.18 μm CMOS technology with 4 Megapixels and 4-transistor PPD pixel architecture. The image lag degradation induced by TID damage is analyzed by exposing the 60 Co γ rays with different biased conditions. The experimental results show that the degradation of the biased CIS are more severe than that of the unbiased CIS. The image lag degradation versus the TID at the dose rates of 0.1, 1.0 and 10.0 rad(Si)/s are compared. The image lag degradation induced by displacement damage is also investigated by the proton and neutron radiation. The image lag degradation mechanisms caused by 60 Co γ ray, proton, and neutron radiation are analyzed with the TCAD simulation and the radiation particle transportation simulation using GEANT 4.

关键词： Degradation Protons Neutrons Electric potential Total ionizing dose Analytical models

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Amyloid-β peptide (1-42) aggregation induced by copper ions under acidic conditions

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生物化学与生物物理学报（英文版） 2013年第7期45卷 570-577页

作者： Yannan Bin Xia Li Yonghui He Shu Chen Juan Xiang Institute of Surface Analysis and Biosensing College of Chemistry and Chemical Engineering Central South University Changsha 410083 China 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 Xiangtan 411201 China Institute of Surface Analysis and Biosensing College of Chemistry and Chemical Engineering Central South University Changsha 410083 China Institute of Surface Analysis and Biosensing College of Chemistry and Chemical Engineering Central South University Changsha 410083 China Key Laboratory of Resources Chemistry of Nonferrous Metals Ministry of Education Central South University Changsha 410083 China

It is well known that the aggregation of amyloid-β peptide (Aβ) induced by Cu2+ is related to incubation time, solution pH, and temperature. In this work, the aggregation of Aβ1–42 in the presence of Cu2+ under acidic conditions was studied at different incubation time and temperature (e.g. 25 and 37°C). Incubation temperature, pH, and the presence of Cu2+ in Aβ solution were confirmed to alter the morphology of aggregation (fibrils or amorphous aggregates), and the morphology is pivotal for Aβ neurotoxicity and Alzheimer disease (AD) development. The results of atomic force microscopy (AFM) indicated that the formation of Aβ fibrous morphology is preferred at lower pH, but Cu2+ induced the formation of amorphous aggregates. The aggregation rate of Aβ was increased with the elevation of temperature. These results were further confirmed by fluorescence spectroscopy and circular dichroism spectroscopy and it was found that the formation of β-sheet structure was inhibited by Cu2+ binding to Aβ. The result was consistent with AFM observation and the fibrillation process was restrained. We believe that the local charge state in hydrophilic domain of Aβ may play a dominant role in the aggregate morphology due to the strong steric hindrance. This research will be valuable for understanding of Aβ toxicity in AD.

关键词： amyloid-β peptide copper ions atomic force microscopy acidic pH morphology

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The improved Hagedorn wavepacket method for semiclassical Schrödinger equation

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International Journal of Modeling, simulation, and Scientific Computing 2014年第4期5卷

作者： Xueyang Li Aiguo Xiao Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan P. R. China

The Hagedorn wavepacket method is an important numerical method for solving the semiclassical time-dependent Schrödinger equation. In this paper, a new semi-discretization in space is obtained by wavepacket operator. In a sense, such semi-discretization is equivalent to the Hagedorn wavepacket method, but this discretization is more intuitive to show the advantages of wavepacket methods. Moreover, we apply the multi-time-step method and the Magnus-expansion to obtain the improved algorithms in time-stepping computation. The improved algorithms are of the Gauss–Hermite spectral accuracy to approximate the analytical solution of the semiclassical Schrödinger equation. And for the given accuracy, the larger time stepsize can be used for the higher oscillation in the semiclassical Schrödinger equation. The superiority is shown by the error estimation and numerical experiments.

关键词： High oscillation semiclassical Schrödinger equation Hagedorn wavepacket multi-time-step method Magnus-expansion

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TDCA: Improved Optimization Algorithm with Degree Distribution and Communication Traffic for the Deployment of Software Components Base on AUTOSAR Architecture

Research Square

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Research Square 2021年

作者： Zhang, Kunpeng Liu, Yanheng Zhang, Jindong Zhang, Guanhua Jin, Jingyi Li, Yunhao Tang, Fengmin College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbol Computation and Knowledge Engineering The Ministry of Education Jilin University Changchun China State Key Laboratory of Automobile Simulation and Control Jilin University Changchun China College of Mechanical Engineering Hebei University of Technology Tianjin300132 China China Automotive Technology and Research Center Tianjin300300 China

AUTOSAR (Automotive Open System Architecture), as an open, standardized framework for automotive electronic software development, has gradually become the standard followed by major automotive manufacturers and automotive electronic device suppliers. The electronic software system problem improves the development efficiency and portability of the system by reducing the development cost of automotive electronic software while ensuring the quality of products and services, which is beneficial for subsequent upgrades and updates of the system. In order to improve the reliability of the software component deployment algorithm based on AUTOSAR architecture, we proposed the TDCA algorithm. During the execution of the algorithm, communication volume and communication degree are introduced to improve the accuracy of the deployment plan by optimizing the bus load and ECU balancing. Algorithm comparison experiments show that comparing heuristic and linear optimization algorithms, the TDCA algorithm proposed in this paper has significant advantages in reducing bus load and ECU utilization. The algorithm can reduce the communication between cores and balance ECU load according to the constraints of AUTOSAR architecture. © 2021, CC BY.

关键词： Equalizers

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A priori subcell limiting based on compact nonuniform nonlinear weighted schemes of high-order CPR method for hyperbolic conservation laws

arXiv

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arXiv 2021年

作者： Zhu, Huajun Liu, Huayong Yan, Zhen-Guo Shi, Guoquan Deng, Xiaogang State Key Laboratory of Aerodynamics Sichuan Mianyang621000 China Tianfu Engineering-Oriented Numerical Simulation & Software Innovation Center Sichuan University Sichuan Chengdu610000 China College of Aerospace Science and Engineering National University of Defense Technology Hunan Changsha410073 China Chinese Academy of Military Science Beijing100071 China

This paper develops a shock capturing approach for high-order correction procedure via reconstruction (CPR) method with Legendre-Gauss solution points. Shock regions are treated by novel compact nonuniform nonlinear weighted (CNNW) schemes, which have the same solution points as the CPR method. CNNW schemes are constructed by discretizing flux derivatives based on Riemann fluxes at flux points in one cell and using nonuniform nonlinear weighted (NNW) interpolations to obtain the left and right values at flux points. Then, a priori subcell p-adaptive CNNW limiting of the CPR method is proposed for hyperbolic conservation laws. Firstly, a troubled cell indicator is used to detect shock regions and to quantify solution smoothness. Secondly, according to the magnitude of the indicator, CNNW schemes with varying accuracy orders are chosen adaptively for the troubled cells. The spectral property and discrete conservation laws are mathematically analyzed. Various numerical experiments show that the CPR method with subcell CNNW limiting has superiority in satisfying discrete conservation laws and in good balance between resolution and shock capturing robustness. Copyright © 2021, The Authors. All rights reserved.

关键词： Numerical methods

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Inferring microRNA-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network

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Scientific reports 2019年第1期9卷 2474页

作者： Dong-Ling Yu Yuan-Lin Ma Zu-Guo Yu Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 P.R. China. Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 P.R. China. yuzuguo@***. School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Q4001 Australia. yuzuguo@***.

More and more research works have indicated that microRNAs (miRNAs) play indispensable roles in exploring the pathogenesis of diseases. Detecting miRNA-disease associations by experimental techniques in biology is expensive and time-consuming. Hence, it is important to propose reliable and accurate computational methods to exploring potential miRNAs related diseases. In our work, we develop a novel method (BRWHNHA) to uncover potential miRNAs associated with diseases based on hybrid recommendation algorithm and unbalanced bi-random walk. We first integrate the Gaussian interaction profile kernel similarity into the miRNA functional similarity network and the disease semantic similarity network. Then we calculate the transition probability matrix of bipartite network by using hybrid recommendation algorithm. Finally, we adopt unbalanced bi-random walk on the heterogeneous network to infer undiscovered miRNA-disease relationships. We tested BRWHNHA on 22 diseases based on five-fold cross-validation and achieves reliable performance with average AUC of 0.857, which an area under the ROC curve ranging from 0.807 to 0.924. As a result, BRWHNHA significantly improves the performance of inferring potential miRNA-disease association compared with previous methods. Moreover, the case studies on lung neoplasms and prostate neoplasms also illustrate that BRWHNHA is superior to previous prediction methods and is more advantageous in exploring potential miRNAs related diseases. All source codes can be downloaded from https://***/myl446/BRWHNHA .

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Superconvergence for General Convex Optimal Control Problems Governed by Semilinear Parabolic Equations

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International Scholarly Research Notices 2014年第1期2014卷

作者： Yongquan Dai Yanping Chen Hunan Key Laboratory for Computation and Simulation in Science and Engineering Department of Mathematics Xiangtan University Xiangtan Hunan 411105 *** School of Mathematical Sciences South China Normal University Guangzhou Guangdong 510631 ***

We will investigate the superconvergence for the semidiscrete finite element approximation of distributed convex optimal control problems governed by semilinear parabolic equations. The state and costate are approximated by the piecewise linear functions and the control is approximated by piecewise constant functions. We present the superconvergence analysis for both the control variable and the state variables.

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Naive gabor networks for hyperspectral image classification

arXiv

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arXiv 2019年

作者： Liu, Chenying Li, Jun He, Lin Plaza, Antonio Li, Shutao Li, Bo Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation School of Geography and Planning Sun Yat-sen University Guangzhou510275 China School of Automation Science and Engineering South China University of Technology Guangzhou510640 China College of Electrical and Information Engineering Hunan University Changsha410082 China Hyperspectral Computing Laboratory Department of Technology of Computers and Communications Escuela Politécnica University of Extremadura CáceresE-10071 Spain Beijing Key Laboratory of Digital Media School of Computer Science and Engineering State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

Recently, many convolutional neural network (CNN) methods have been designed for hyperspectral image (HSI) classification since CNNs are able to produce good representations of data, which greatly benefits from a huge number of parameters. However, solving such a high-dimensional optimization problem often requires a large amount of training samples in order to avoid overfitting. Additionally, it is a typical non-convex problem affected by many local minima and flat regions. To address these problems, in this paper, we introduce naive Gabor Networks or Gabor-Nets which, for the first time in the literature, design and learn CNN kernels strictly in the form of Gabor filters, aiming to reduce the number of involved parameters and constrain the solution space, and hence improve the performances of CNNs. Specifically, we develop an innovative phase-induced Gabor kernel, which is trickily designed to perform the Gabor feature learning via a linear combination of local low-frequency and high-frequency components of data controlled by the kernel phase. With the phase-induced Gabor kernel, the proposed Gabor-Nets gains the ability to automatically adapt to the local harmonic characteristics of the HSI data and thus yields more representative harmonic features. Also, this kernel can fulfill the traditional complex-valued Gabor filtering in a real-valued manner, hence making Gabor-Nets easily perform in a usual CNN thread. We evaluated our newly developed Gabor-Nets on three well-known HSIs, suggesting that our proposed Gabor-Nets can significantly improve the performance of CNNs, particularly with a small training set. Copyright © 2019, The Authors. All rights reserved.

关键词： Spectroscopy

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Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-based Clustering for Many-objective Optimization

arXiv

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arXiv 2022年

作者： Kinoshita, Takato Masuyama, Naoki Liu, Yiping Nojima, Yusuke Ishibuchi, Hisao Graduate School of Engineering Osaka Prefecture University 1-1 Gakuen-cho Naka-ku Sakai-Shi Osaka599-8531 Japan Graduate School of Informatics Osaka Metropolitan University 1-1 Gakuen-cho Naka-ku Sakai-Shi Osaka599-8531 Japan College of Computer Science and Electronic Engineering Hunan University Hunan 410082 China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

Decomposition-based multiobjective evolutionary algorithms (MOEAs) with clustering-based reference vector adaptation show good optimization performance for many-objective optimization problems (MaOPs). Especially, algorithms that employ a clustering algorithm with a topological structure (i.e., a network composed of nodes and edges) show superior optimization performance to other MOEAs for MaOPs with irregular Pareto optimal fronts (PFs). These algorithms, however, do not effectively utilize information of the topological structure in the search process. Moreover, the clustering algorithms typically used in conventional studies have limited clustering performance, inhibiting the ability to extract useful information for the search process. This paper proposes an adaptive reference vector-guided evolutionary algorithm using an adaptive resonance theory-based clustering with a topological structure. The proposed algorithm utilizes the information of the topological structure not only for reference vector adaptation but also for mating selection. The proposed algorithm is compared with 8 state-of-the-art MOEAs on 78 test problems. Experimental results reveal the outstanding optimization performance of the proposed algorithm over the others on MaOPs with various properties. © 2022, CC BY-NC-ND.

关键词： Clustering algorithms

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