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Extracting B_2O_3 from calcined boron mud using molten sodium hydroxide

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Rare Metals 2015年第10期34卷 744-751页

作者： Zhi-Qiang Ning Yu-Chun Zhai qiu-shi Song School of Materials and Metallurgy Northeastern University

Extracting B2O3 from calcined boron mud(CBM) was studied. The effect of factors such as reaction temperature and NaO H-to-CBM mass ratio on B2O3 extraction efficiency was investigated. The results show that increasing reaction temperature and NaO H-to-CBM mass ratio increases B2O3 extraction efficiency. There are two stages for the B2O3 extracting process: 0–20 min is the first stage, which is rapid; 20–50 min is the second stage, which is slower than the first stage. The overall extracting process follows the shrinking core model, and the first and second stages are determined to obey the surface chemical reaction model and the diffusion through the products layer model,respectively. The activation energies of the first and second stages are calculated to be 41.74 and 15.43 kJ·mol-1,respectively. The B2O3 extracting kinetics equations of the first and second stages are also obtained.

关键词： Boron mud Sodium hydroxide Boron oxide Kinetics

Multilevel Attention Unet Segmentation Algorithmfor Lung Cancer Based on CT Images

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Computers, Materials & Continua 2024年第2期78卷 1569-1589页

作者： Huan Wang shi qiu Benyue Zhang Lixuan Xiao Xi’an Institute of Optics and Precision Mechanics Chinese Academy of SciencesXi’anChina School of Biomedical Engineering Fourth Military Medical UniversityXi’anChina University of Illinois at Urbana Champion ChampaignUSA

Lung cancer is a malady of the lungs that gravely jeopardizes human ***,early detection and treatment are paramount for the preservation of human *** computed tomography(CT)image sequences can explicitly delineate the pathological condition of the *** meet the imperative for accurate diagnosis by physicians,expeditious segmentation of the region harboring lung cancer is of utmost *** utilize computer-aided methods to emulate the diagnostic process in which physicians concentrate on lung cancer in a sequential manner,erect an interpretable model,and attain segmentation of lung *** specific advancements can be encapsulated as follows:1)Concentration on the lung parenchyma region:Based on 16-bit CT image capturing and the luminance characteristics of lung cancer,we proffer an intercept histogram algorithm.2)Focus on the specific locus of lung malignancy:Utilizing the spatial interrelation of lung cancer,we propose a memory-based Unet architecture and incorporate skip connections.3)Data Imbalance:In accordance with the prevalent situation of an overabundance of negative samples and a paucity of positive samples,we scrutinize the existing loss function and suggest a mixed loss *** results with pre-existing publicly available datasets and assembled datasets demonstrate that the segmentation efficacy,measured as Area Overlap Measure(AOM)is superior to 0.81,which markedly ameliorates in comparison with conventional algorithms,thereby facilitating physicians in diagnosis.

关键词： Lung cancer computed tomography computer-aided diagnosis Unet segmentation

Mural Anomaly Region Detection Algorithm Based on Hyperspectral Multiscale Residual Attention Network

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Computers, Materials & Continua 2024年第10期81卷 1809-1833页

作者： Bolin Guo shi qiu Pengchang Zhang Xingjia Tang Key Laboratory of Spectral Imaging Technology CAS Xi’an Institute of Optics and Precision MechanicsChinese Academy of SciencesXi’an710119China School of Optoelectronics University of Chinese Academy of SciencesBeijing100408China Institute of Culture and Heritage Northwest Polytechnic UniversityXi’an710072China

Mural paintings hold significant historical information and possess substantial artistic and cultural ***,murals are inevitably damaged by natural environmental factors such as wind and sunlight,as well as by human *** this reason,the study of damaged areas is crucial for mural *** damaged regions differ significantly from undamaged areas and can be considered abnormal *** manual visual processing lacks strong characterization capabilities and is prone to omissions and false *** imaging can reflect the material properties more effectively than visual characterization ***,this study employs hyperspectral imaging to obtain mural information and proposes a mural anomaly detection algorithm based on a hyperspectral multi-scale residual attention network(HM-MRANet).The innovations of this paper include:(1)Constructing mural painting hyperspectral datasets.(2)Proposing a multi-scale residual spectral-spatial feature extraction module based on a 3D CNN(Convolutional Neural Networks)network to better capture multiscale information and improve performance on small-sample hyperspectral datasets.(3)Proposing the Enhanced Residual Attention Module(ERAM)to address the feature redundancy problem,enhance the network’s feature discrimination ability,and further improve abnormal area detection *** experimental results show that the AUC(Area Under Curve),Specificity,and Accuracy of this paper’s algorithm reach 85.42%,88.84%,and 87.65%,respectively,on this *** results represent improvements of 3.07%,1.11%and 2.68%compared to the SSRN algorithm,demonstrating the effectiveness of this method for mural anomaly detection.

关键词： Murals anomaly detection hyperspectral 3D CNN(Convolutional Neural Networks) residual network

Effects of Electrically Inert Fillers on the Properties of Poly(m-xylene adipamide)/Multiwalled Carbon Nanotube Composites

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Chinese Journal of Polymer Science 2016年第8期34卷 1032-1038页

作者： Bo-yuan Zhang qiu-shi Ge 郭朝霞于建 Key Laboratory of Advanced Materials(MOE) Department of Chemical EngineeringTsinghua UniversityBeijing 100084China

The effects of three types of electrically-inert fillers, calcium carbonate （CaCO_3）, talc and glass fiber （GF）, on electrical resistivity, crystallization behavior and dynamic mechanical properties of poly（m-xylene adipamide）（MXD6）/multiwalled carbon nanotube （MWCNT） composites are investigated. The electrical resistivity of MXD6/MWCNT composites is significantly reduced with the addition of inert fillers due to the volume-exclusion effect that leads to increased effective concentration of MWCNTs in MXD6 matrix and also due to improved MWCNT dispersion. The crystallization temperature of MXD6 increases with the addition of MWCNTs, indicating that MWCNTs can act as nucleating agent and induce crystallization of MXD6. The incorporation of inert fillers has no further effect on crystallization behavior of MXD6, but significantly improves the storage modulus of MXD6/MWCNT composite, demonstrating that CaCO_3, talc and GF filled MXD6/MWCNT composites are very promising materials with not only improved electrical property but also excellent mechanical properties.

关键词： Poly(m-xylene diamide) Multiwalled carbon nanotubes Inert fillers Electrical conductivity.

Stealth-ACK: stealth transmissions of No C acknowledgements

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Science China(Information Sciences) 2017年第9期60卷 21-35页

作者： Jinhua TAO shi qiu Shaoli LIU Tianshi CHEN Rui MAO Institute of Computing Technology Chinese Academy of Sciences College of Computer Science and Software Engineering Shenzhen University

Network-on-Chip(No C) is a promising replacement of bus architecture due to its better *** state-of-the-art No Cs, each packet contains several fixed-length flits, which facilitates allocations of network resources but brings in many unused bits. In this paper, we propose a novel technique called Stealth-ACK to effectively address the above problem. Stealth-ACK leverages unused bits in head flits of non-ACK packets to carry and stealthily transmit ACK information. Such stealth transmissions of ACK information effectively reduce not only the amount of dedicated ACK packets on No C, but also the number of unused bits in head flits of non-ACK packets, which significantly reduces wastes on No C bandwidth. Experimental results show that Stealth-ACK averagely increases the throughput of 16 × 16 2-D mesh No C by 11.9%, and averagely reduces the No C latency by 34.8% on application traces of SPLASH-2. Moreover, Stealth-ACK only requires trivial hardware modification to basic router architectures, which incurs negligible power consumption and area cost.

关键词： networks-on-chip acknowledgement packet router architecture optimisation routing algorithm

Theoretical Characterization of Chiral Carbon Nanotube Encapsulating Ellipsoidal C70

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Chinese Journal of Chemical Physics 2013年第6期26卷 780-783,I0005页

作者： Er-jun Kan qiu-shi Yao Department of Applied Physics and Key Laboratory of 5oft Chemistry and Functional MaterialsMinistry of Education Nanjing University of Science and Technology Nanjing 210094 China

The molecular orientation of ellipsoidal C70 in carbon nanotubes is carefully studied by first principles calculations. Using （14, 7） single-wall carbon nanotube （SWCNT） as a prototype material, we explored that the weak chemical interaction between SWCNT and C70 was the crucial factor to determine the molecular orientation. However, the small energy difference makes the distinguishment of two possible molecular orientations difficult. By simulating scanning tunneling microscope images and optical properties, we found that local electronic states sensitively depended on the molecular orientation of ellipsoidal C70, which provided a practical way of using scanning tunneling microscope to recognize the molecular orientation of ellipsoidal C70.

关键词： Electronic structure Chiral carbon nanotube Density functional theory

Optimal Multi-impulse Linear Rendezvous via Reinforcement Learning

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Space(Science & Technology) 2023年第1期3卷 362-373页

作者： Longwei Xu Gang Zhang shi qiu Xibin Cao Research Center of Satellite Technology Harbin Institute of TechnologyHarbin 150001PR China

A reinforcement learning-based approach is proposed to design the multi-impulse rendezvous trajectories in linear relative *** the relative motion in elliptical orbits,the relative state propagation is obtained directly from the state transition *** rendezvous problem is constructed as a Markov decision process that reflects the fuel consumption,the transfer time,the relative state,and the dynamical *** actor-critic algorithm is used to train policy for generating rendezvous *** results of the numerical optimization(e.g.,differential evolution)are adopted as the expert data set to accelerate the training *** deploying a policy network,the multi-impulse rendezvous trajectories can be obtained on ***,the proposed approach is also applied to generate a feasible solution for many impulses(e.g.,20 impulses),which can be used as an initial value for further *** numerical examples with random initial states show that the proposed method is much faster and has slightly worse performance indexes when compared with the evolutionary algorithm.

关键词： optimization process Optimal

Multi-View Auxiliary Diagnosis Algorithm for Lung Nodules

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Computers, Materials & Continua 2022年第9期72卷 4897-4910页

作者： shi qiu Bin Li Tao Zhou Feng Li Ting Liang Key Laboratory of Spectral Imaging Technology CAS Xi’an Institute of Optics and Precision MechanicsChinese Academy of SciencesXi’an710119P.R.China School of Information Science and Technology Northwest UniversityXi’an710127P.R.China School of Computer Science and Engineering North Minzu UniversityYinchuan750021P.R.China Institute of Education University College LondonLondonThe United Kingdom Department of Radiology The First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an10061P.R.China

Lung is an important organ of human *** and more people are suffering from lung diseases due to air *** diseases are usually highly *** as lung tuberculosis,novel coronavirus COVID-19,*** nodule is a kind of high-density globular lesion in the *** need to spend a lot of time and energy to observe the computed tomography image sequences to make a diagnosis,which is *** this reason,the use of computer-assisted diagnosis of lung nodules has become the current main *** the process of computer-aided diagnosis,how to reduce the false positive rate while ensuring a low missed detection rate is a difficulty and focus of current *** solve this problem,we propose a three-dimensional optimization model to achieve the extraction of suspected regions,improve the traditional deep belief network,and to modify the dispersion matrix between *** construct a multi-view model,fuse local three-dimensional information into two-dimensional images,and thereby to reduce the complexity of the *** alleviate the problem of unbalanced training caused by only a small number of positive *** show that the false positive rate of the algorithm proposed in this paper is as low as 12%,which is in line with clinical application standards.

关键词： Lung nodules deep belief network computer-aided diagnosis multi-view

Colorectal Cancer Segmentation Algorithm Based on Deep Features from Enhanced CT Images

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Computers, Materials & Continua 2024年第8期80卷 2495-2510页

作者： shi qiu Hongbing Lu Jun Shu Ting Liang Tao Zhou School of Biomedical Engineering Fourth Military Medical UniversityXi’an710119China Department of Radiology Xijing HospitalFourth Military Medical UniversityXi’an710032China Department of Radiology The First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an710061China School of Computer Science and Engineering North Minzu UniversityYinchuan750030China

Colorectal cancer,a malignant lesion of the intestines,significantly affects human health and life,emphasizing the necessity of early detection and *** segmentation of colorectal cancer regions directly impacts subsequent staging,treatment methods,and prognostic *** colonoscopy is an effective method for detecting colorectal cancer,its data collection approach can cause patient *** address this,current research utilizes Computed Tomography(CT)imaging;however,conventional CT images only capture transient states,lacking sufficient representational capability to precisely locate colorectal *** study utilizes enhanced CT images,constructing a deep feature network from the arterial,portal venous,and delay phases to simulate the physician’s diagnostic process and achieve accurate cancer *** innovations include:1)Utilizing portal venous phase CT images to introduce a context-aware multi-scale aggregation module for preliminary shape extraction of colorectal cancer.2)Building an image sequence based on arterial and delay phases,transforming the cancer segmentation issue into an anomaly detection problem,establishing a pixel-pairing strategy,and proposing a colorectal cancer segmentation algorithm using a Siamese *** with 84 clinical cases of colorectal cancer enhanced CT data demonstrated an Area Overlap Measure of 0.90,significantly better than Fully Convolutional Networks(FCNs)at *** research will explore the relationship between conventional and enhanced CT to further reduce segmentation time and improve accuracy.

关键词： Colorectal cancer enhanced CT multi-scale siamese network segmentation