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2022, Vol. 39 No. 5

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15 September 2022

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  • Innovation Article
    An experimental investigation on the breakup characteristics of liquid metal free jet under a horizontal magnetic field
    DONG Quanrun, YANG Juancheng, NI Mingjiu
    2022, 39 (5): 577-585.  DOI: 10.7523/j.ucas.2022.029
    Abstract ( 298 ) PDF (0KB) ( 0 )
    Based on a high-speed photographic system, experiments on three-dimensional free jets of liquid metal in the absence of a magnetic field and in a horizontal magnetic field have been carried out to observe the process of liquid GaInSn jet breakup and droplet formation in an oxygen-free environment with a maximum We of 400 and a maximum Ha of 30. From the results on jet morphology, surface disturbance, and breakup length, we analyzed the characteristics of jet breakup. In the absence of magnetic field, the jet shows nine different morphologies, and the surface disturbance shows two forms:expansion wave and sinusoidal wave; with the increase of We, the disturbance amplitude first decreases and then increases, and the breakup length first increases and then decreases. When a horizontal magnetic field is imposed, the jet shows four typical morphologies, with the leading edge of the jet being flattened in the direction of the vertical magnetic field line and elliptical along the magnetic field line. As the Ha number increases, the jet break length tends to increase overall, but decreases in some operating conditions. The results of this paper have enriched the phenomenon of liquid metal jets under magnetohydrodynamic effects.
    Research Articles
    Signed-rank-based test for high dimensional mean vector
    LIU Yan, LI Shiming, ZHANG Sanguo
    2022, 39 (5): 586-592.  DOI: 10.7523/j.ucas.2020.0059
    Abstract ( 248 ) PDF (0KB) ( 0 )
    This work is concerned with tests for one-sample mean vectors under high dimensional cases. Existing high dimensional tests for mean vectors base on the assumption of elliptical distribution have been proposed recently. To extend to more distributions, we propose a signed-rank-based test. The proposed test statistic is robust and scalar-invariant. Asymptotic properties of the test statistic are established. Numerical studies show that the proposed test has a good control of the type-I error and is more efficiency. We also employ the proposed method to analyze an ophthalmic data.
    Momentum strategy, momentum crashes, and risk management: an empirical research based on Chinese commodity futures market
    WEI Yongfeng, ZHAO Wei
    2022, 39 (5): 593-614.  DOI: 10.7523/j.ucas.2020.0049
    Abstract ( 230 ) PDF (0KB) ( 0 )
    This article aims to study the effectiveness of momentum strategies in Chinese commodity futures market, and after judging the existence and causes of momentum crashes, puts forward effective methods to manage the risk of momentum crashes. In this paper, considering the transaction costs, the commodity futures momentum strategy can continuously obtain significant risk-adjusted returns, and further empirical discovery of the momentum crashes phenomenon in Chinese commodity futures market. The reason of momentum crashes is that the loser portfolio has the nature of option-like is more sensitive to market portfolio volatility, which in turn leads to the crashes of momentum portfolios. In order to carry out the risk management of momentum crashes, this paper proposes to construct a dynamic weighted momentum strategy based on target condition stop to manage the risk of momentum crashes. The results show that this method effectively avoids the extreme risk brought about by momentum crashes and obtains higher momentum return and Sharpe ratio.
    Predicting sunspot variations through neural network
    CHENG Shu, SHI Yaolin, ZHANG Huai
    2022, 39 (5): 615-626.  DOI: 10.7523/j.ucas.2021.0068
    Abstract ( 425 ) PDF (0KB) ( 0 )
    Sunspot variations are the sun's symptoms of strong magnetic perturbations. In this paper, we use long short-term memory neural network and one-dimensional convolution neural network to detect sunspot variations. Here we use three different datasets, including the yearly mean sunspot number (YSSN) from 1700 to 2020, the monthly mean sunspot number (MSSN) from 1749 to 2021 and the monthly mean sunspot areas (MSSA) from 1874 to 2021. First, based on the YSSN dataset, we obtain YSSN for 2021 and the predicted YSSN in the 25th solar cycle appears at 2025 which equals 163.4; Then, based on the MSSN dataset, we obtain MSSN for June 2021 and the predicted YSSN in the 25th solar cycle appears in October 2024 which equals 245.9; Next, based on the MSSA dataset, the predicted MSSA for June 2021 is 73.1; Finally, the latitude is divided into 13 partitions to predict the butterfly diagram, and still, neural network can reconstruct the butterfly diagram. Therefore, neural network can provide a physical perspective for sunspot investigation.
    The b-value spatiotemporal evolution in southeastern Tibetan Plateau and its implications on regional stress field characteristics
    GAO Yajing, LUO Gang, WANG Shaopo, ZHOU Yuanze
    2022, 39 (5): 627-638.  DOI: 10.7523/j.ucas.2021.0037
    Abstract ( 189 ) PDF (0KB) ( 0 )
    Stress field is an important factor to assess regional seismic risk. We collected the seismic catalogue data from 1970 to 2019 in southeastern Tibetan Plateau, used the maximum likelihood method to calculate regional b values, and then obtained the spatial and temporal distribution of b values of this region. Based on the negative correlation between seismic b value and stress, we analyzed the stress distribution and variation on the major fault zones in southeastern Tibetan Plateau. The results are as follows. 1) In the center of Xianshuihe-Xiaojiang fault system, the b value of Daliangshan fault zone is lower than that of Anninghe-Zemuhe fault zone. This indicates that the stress on Daliangshan fault zone is greater and its seismic risk is relatively high in the future. 2) The b values in shallow layer (0-20 km) are higher than those of deep layer (20-40 km), which is consistent with the characteristics that confining pressure is low and rock tends to brittle fracture in the shallow, while confining pressure is high and rock tends to ductile deformation in the deep. 3) Before and after the 2008 Wenchuan earthquake, b value of epicenter area had a decrease-rise-decrease process, and this showed the accumulation-release-accumulation process of regional stress. The larger the magnitude of earthquake, the longer the decreasing trend of b value before the earthquake, the greater the impact of earthquake on b value. The closer to the epicenter, the greater the decrease of b value. 4) The b value of Longmenshan fault zone is relatively low at present and this shows that Longmenshan fault zone is accumulating stress.
    PolSAR terrain classification based on image segmentation and EM algorithm
    CAO Zhe, FENG Shanshan, SUN Xian, HONG Wen
    2022, 39 (5): 639-647.  DOI: 10.7523/j.ucas.2021.0011
    Abstract ( 183 ) PDF (0KB) ( 0 )
    In the study of the terrain classification based on the polarimetric synthetic aperture radar (PolSAR), the image segmentation algorithm based on deep neural network has the disadvantages of fuzzy classification boundary, low classification accuracy and complicated calculation caused by the redundancy of high-dimensional feature information. This paper proposes a lightweight segmentation network based on convolutional neural network and EM algorithm called low-rank-reconstruction-net (LRR-Net), which is applied to the terrain classification of fully PolSAR images. Starting from the idea of polarimetric target decomposition, LRR-Net uses the EM algorithm to perform low-rank reconstruction of features, maps the features from high-dimensional space to low-dimensional space, achieving higher classification accuracy while reducing parameters. The model is trained and evaluated in GF-3 fully PolSAR dataset, and the results show that the model complexity is reduced under the guarantee of the classification accuracy.
    Fine process method for Gaofen-3 L1A-level image
    FANG Hankang, ZHANG Bo, CHEN Weirong, WU Fan, WANG Chao
    2022, 39 (5): 648-657.  DOI: 10.7523/j.ucas.2021.0005
    Abstract ( 282 ) PDF (0KB) ( 0 )
    Level one A (L1A) product of Gaofen-3 SAR satellite is the primary image set delivering for customer. This paper presents a complete workflow to facilitate the post-process of GF-3 L1A images for follow-up scientific research or value-added applications, where robust and precise processing is essential to generate the advanced high-level product concerning radiometric correction and geometric correction. Firstly, to eliminate the statistical bias caused by the null and zero pixel values induced in the quantization of the L1A product, an improved radiometric correction formula is derived based on the equivalent noise coefficient of Gaofen-3 images. Then, to determine the coordinates of image corners, an inverse algorithm supported by RPC parameters is proposed for geometric correction. This algorithm is robust by counting on the orbit direction, look direction, and sampling interval provided in an XML metadata file. Finally, a SAR filter operator is introduced into the resampling step of output results to improve the equivalent look number. Experimental results comparing with the radiometric values of a sentinel-1 image and the geometric accuracy of a sentinel-2 optical image, respectively, validate the accuracy and reliability of this method for L1A product processing.
    Road information extraction and application in the suburban mountainous area based on remote sensing images
    CHEN Ruonan, PENG Ling, LIU Yufei, WEI Zhichao, LYU Beiru, CHEN Deyue
    2022, 39 (5): 658-667.  DOI: 10.7523/j.ucas.2021.0004
    Abstract ( 211 ) PDF (0KB) ( 0 )
    In recent years, suburban mountain areas have become a good choice for urban residents to go outing. Intensive tourist outings and villagers' production activities bring fire safety hazards to mountains and forests. And road information is vital information for forest fire prevention emergency. However, due to the problems of occlusion, shadow, narrow and multiple branches in suburban mountainous roads, conventional urban road extraction algorithms have poor performance in suburban mountain areas. This paper proposes a road semantic segmentation model and a training method that transforms the binary into a multi-class classification problem, forcing the model to focus on learning spatial distance information to generate road results with better spatial continuity. Then, experiments were carried out on the Yajishan road dataset made by ourselves and the Massachusetts public road dataset respectively to verify the effectiveness of our model and training method. In addition, it is verified that the training method is also applicable to other commonly used semantic segmentation models such as U-Net and DeepLabV3. Finally, this paper also conducts post-processing research based on the above road extraction results to output road surface, road centerline vector data with road width information, and conducts fire truck traffic analysis application in Beijing Yaji Mountain. The research results have alleviated the problem of insufficient road information for commercial electronic maps in the suburban mountain areas with few people, and provided information technology support for forest fire emergency rescue.
    3D rock mass point cloud holes detection and filling method based on plane extraction
    MA Zhaoyue, XIAO Jun, WANG Ying
    2022, 39 (5): 668-676.  DOI: 10.7523/j.ucas.2020.0032
    Abstract ( 139 ) PDF (0KB) ( 0 )
    In rock engineering, the rock point cloud data scanned by a laser scanner always contains holes because of the scanning measurement angle, shadow, occlusion of obstacles, and other factors, which will affect the result of subsequent 3D reconstruction. The existing filling methods mainly focus on the regular point cloud data, and the point cloud hole is filled according to the neighborhood information of the holes, and the experiment result of rock point cloud holes detection and filling are not effective and low efficiency. In this paper, we propose an algorithm for detecting and filling rock point cloud holes based on the plane extraction leverage the characteristics of rock point cloud data. Firstly, an optimized region growing algorithm is applied to extract the plane of the rock point cloud. Then, we traverse all point clouds and retrieve their K-neighborhood point sets. These points are mapped to the corresponding plane, and we calculate the neighborhood angle to detect holes. Finally, we classify the point cloud holes according to the number of corresponding planes of the boundary point set, and the point cloud holes are filled by adding sampling points on the corresponding planes. Our algorithm realizes the process of denoising and plane fitting of point cloud data by plane extraction, simplifys the subsequent hole filling process and reduces the time complexity. Experimental results demonstrate that our algorithm has a higher accuracy of detection and filling, higher operation efficiency, and better filling result for rock-mass point cloud compared to the state-of-the-art approaches.
    Accuracy analysis of 3D object detection based on stereo point cloud
    LIU Wangchao, LOU Xin
    2022, 39 (5): 677-683.  DOI: 10.7523/j.ucas.2020.0042
    Abstract ( 216 ) PDF (0KB) ( 0 )
    3D object detection is a crucial task in autonomous driving. Recently, the accuracy of LiDAR-based 3D object detection algorithms have improved dramatically. However, if we replace the LiDAR data with the depth map that generates from stereo cameras, the detection performance drops a lot. In a recent research, it is found that by transforming the stereo-based depth map to point cloud representation, referred to as pseudo-LiDAR, the performance of 3D object detection can be improved significantly. However, there is still a big gap of accuracy between LiDAR-based and stereo-based algorithms. One of the main reasons is that there are error points in the transformed pseudo-LiDAR data. To study this, we use the LiDAR points cloud to correct the pseudo-LiDAR data, i.e., to detect and exclude the error points. Then we use the optimized pseudo-LiDAR to perform 3D object detection. Experimental results show that the detection accuracy can be improved by as much as 21.02%.
    Hyperspectral target detection method based on filter tensor analysis
    YANG Shuai, JI Luyan, GENG Xiurui
    2022, 39 (5): 684-694.  DOI: 10.7523/j.ucas.2020.0060
    Abstract ( 112 ) PDF (0KB) ( 0 )
    Most of the existing target detection algorithms for hyperspectral images treat each band indiscriminately, so the physical information of the image band cannot be fully utilized. In this paper, the hyperspectral images are firstly divided into several different waveband ranges (such as visible light, near infrared, shortwave infrared, etc.) according to the different imaging mechanisms. A recently developed multi-temporal target detection algorithm:FTA (filter tensor analysis) is introduced into the hyperspectral target detection by combining the different waveband ranges of the hyperspectral images with the time-phase dimension of multi-temporal remote sensing data correspondingly. Based on the new approach, a band-divided FTA algorithm for single-temporal hyperspectral images is proposed. Experiments on hyperspectral images prove that the band-divided FTA algorithm can achieve better results in target detection than the traditional single-phase target detection algorithm.
    A saliency-based ship target detection method in high sea state SAR images
    ZHANG Ziqi, WANG Xiaolong
    2022, 39 (5): 695-703.  DOI: 10.7523/j.ucas.2020.0050
    Abstract ( 200 ) PDF (0KB) ( 0 )
    In this study, a ship target detection method in high sea state SAR image, named Itti-SAR, based on saliency is proposed, which consists of two stages:saliency image extraction and connectivity judgment. In the stage of saliency map extraction, taking the characteristics of SAR images into consideration, the improved direction feature and consistency feature are introduced into the traditional visual attention model to construct a saliency model suitable for SAR images, which realizes the extraction of ship target saliency maps for high sea state SAR images. In the stage of connectivity judgment, the density constraint is used to judge the connectivity of salient areas to prevent the detection of a single target into multiple, thereby further reducing false alarms. The experimental results on several SAR images verify the effectiveness of the method. The experimental results show that compared with the classical CFAR algorithm, the proposed method has the advantages of high precision, high recall rate and independent of prior knowledge.
    Throughput analysis of UAV-assisted cellular networks by Matern hardcore point processes
    LIU Mengbing, QIU Ling, LIANG Xiaowen
    2022, 39 (5): 704-711.  DOI: 10.7523/j.ucas.2020.0053
    Abstract ( 154 ) PDF (0KB) ( 0 )
    Unmanned aerial vehicles (UAVs) have been expected to coexist with conventional terrestrial cellular networks and become an important component to support high rate transmissions. This paper presents an analytical framework for evaluating the throughput performance of a downlink two-tier heterogeneous network. The locations of terrestrial base stations (BSs) are modeled by Poisson point processes. Considering the minimum distance constraint among UAVs, Matern hardcore point processes is utilized to model the locations of UAVs. Tools of stochastic geometry are invoked to derive more tractable expressions for average data rates of users. With the analytical results, we discuss the optimal combinations of UAVs' height and power control factor. The result shows that an appropriate power control factor can effectively maximize UAV users' average data rate as well as guaranteeing the BS users' performance under our proposed model.
    Spoon network: a new network structure for Landsat imagery cloud detection
    WANG Shuli, TANG Hairong, JI Luyan
    2022, 39 (5): 712-720.  DOI: 10.7523/j.ucas.2020.0036
    Abstract ( 210 ) PDF (0KB) ( 0 )
    In view of the shortcomings of the neural network model for remote sensing image cloud detection, such as the loss of detail information, the high cloud miss detection rate and the complexity of calculation caused by the insufficient utilization of spectral information, this paper proposes a new and lightweight network called spoon net (S-Net), which is applied to the cloud detection of Landsat remote sensing image. S-Net is divided into two stages. In the first stage, the convolution kernel of 1×1 is used to extract image spectral features to avoid image details being blurred; in the second stage, the encoder decoder framework is used to extract image spatial features, and group convolution is introduced to convolute each layer of spectral channels extracted in the first stage separately to maintain spectral features and reduce model parameters. The model is trained and evaluated in Landsat8 biome dataset, and the results show that the model has a great advantage in memory and time, and achieves an accuracy of 95%.
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    Analysis of Shanghai and Shenzhen stock market using Copula-VaR method
    Hao Li-Xiang, Cheng Xi-Jun
    2008, 25 (5): 682-686. DOI: 10.7523/j.issn.2095-6134.2008.5.017
    Abstract ( 1331 ) PDF ( 727KB ) ( 16986 )
    Risk analysis of Portfolio is studied ,by comparing Copula functions and the traditional VaR methods,mixing copula is made. By backtesting ,the empirical research shows that mixing Copula method makes better VaR model .
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    Shape-dependent effects of nanoceria on the activity of Pd/CeO 2 catalysts for CO oxidation
    WANG Lei, MAO Junyi, YUAN Qing, HUANG Tao
    2015, 32 (5): 594-604. DOI: 10.7523/j.issn.2095-6134.2015.05.004
    Abstract ( 377 ) PDF ( 9359KB ) ( 14876 )

    The redox property of palladium nanoparticles (NPs) is pivotal to CeO2 supported Pd catalysts in oxidation reactions and is closely related to the structure of Pd-CeO2 interface. Herein, we report that low-temperature CO oxidation activity of Pd/CeO2 highly depends on the shape and crystal plane of CeO2 supports. Pd/CeO2 catalysts with CeO2 nanoocthedrons (NOCs) and nanocubes (NCs) as supports were prepared by colloidal-deposition method. Results show that Pd/CeO2 NOCs with ceria {111} facets enclosed exhibited much higher catalytic activity than Pd/CeO2NCs with ceria {100} facets exposed. DFT calculations revealed that the redox property of surface Pd species may play important roles in determining the reducibility and activity of catalysts. The PdOx to Pd cycle is more facile on Pd4@CeO2(111) than on Pd4@CeO2(100), which is dictated by the Pd-ceria interaction in the end. Our results show that the redox property of surface Pd is pivotal to the reducibility and activity of Pd/ceria catalysts, which could be tuned by manipulation of the Pd-CeO2 interaction via tuning the exposed facets of ceria support.

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    Advances in light field photography technique
    NIE Yun-Feng, XIANGLI Bin, ZHOU Zhi-Liang
    2011, 28 (5): 563-572. DOI: 10.7523/j.issn.2095-6134.2011.5.001
    Abstract ( 2612 ) PDF ( 1045KB ) ( 6127 )

    Light field is a representation of full four-dimensional radiance of all rays with spatial and angular information in free space, and capture of light field data enables many new development potentials for computational imaging. The historical development of light field photography is summarized, and typical light field photography devices are categorized in view of capture methods for 4D light field. Based on the principles of light field camera, computational imaging theorem, refocusing theory, synthetic aperture refocusing algorithm, and light field microscopic technology are emphatically described. Finally, the promising application perspectives and existing critical issues of light field imaging are discussed.

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    Upstream promoter sequences of Arabidopsis GH3 gene family
    SUN Tao, CHAI Tuan-Yao, ZHANG Yu-Xiu
    2010, 27 (6): 847-852. DOI: 10.7523/j.issn.2095-6134.2010.6.017
    Abstract ( 2048 ) PDF ( 154KB ) ( 5555 )

    GH3 genes belong to a primary auxin-response gene family. The 10 promoter sequences of Arabidopsis GH3 genes were analyzed using bioinformatics method. The results show that the transcription start site of these genes is generally 65~145bp away from the start codon, and the TATA boxes are located in the (-24)-(-40)bp. MDB and MatInspector analyses show that most upstream regions of these GH3 genes contain the cis-elements required for tissue and organ-specific expression responding to phytohormones and external environment, indicating that the expressions of GH3 genes are strictly controlled by multi-factors. Gene chip data show that AuxREs is very important for GH3 genes in response to IAA treatment,but it is not the unique cis-element for auxin response.

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    Quality Evaluation for Three Textual Document Clustering Algorithms
    LIU Wu-Hua, LUO Tie-Jian, WANG Wen-Jie
    2006, 23 (5): 640-646. DOI: 10.7523/j.issn.2095-6134.2006.5.012
    Abstract ( 2639 ) PDF ( 832KB ) ( 5230 )
    Textual document clustering is one of the effective approaches to establish a classification instance of huge textual document set. Clustering Validation or Quality Evaluation techniques can be used to assess the efficiency and effective of a clustering algorithm. This paper presents the quality evaluation criterions from outer and inner. Based on these criterions we take three typical textual document clustering algorithms for assessment with experiments. The comparison results show that STC(Suffix Tree Clustering) algorithm is better than k-Means and Ant-Based clustering algorithms. The better performance of STC algorithm comes from that it takes accounts the linguistic property when processing the documents. Ant-Based clustering algorithm’s performance variation is affected by the input variables. It is necessary to adopt linguistic properties to improve the Ant-Based text clustering’s performance.
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    Investigation on the Preparation of μ-Sized PMMA Microspheres by the Dispersion Polymerization
    WU Shao-Gui, LIU Bai-Ling
    2006, 23 (3): 323-330. DOI: 10.7523/j.issn.2095-6134.2006.3.007
    Abstract ( 1857 ) PDF ( 1120KB ) ( 4343 )
    The micron-grade PMMA microspheres with narrow size distribution were prepared by dispersion polymerization. The mechanism of the dispersion polymerization was discussed. The factors influencing both the size and size distribution of the microspheres including initial concentrations of the initiator, monomer, stabilizer, the polarity of the medium and the reaction conditions were studied. The results indicated that the size and size distribution of microspheres both increased with initial concentrations of initiator and monomer. Increasing the amount of the stabilizer resulted in decreasing size and narrowing size distribution of microspheres. Other factors such as the polarity of medium and the reaction temperature had great influences too. By controlling these factors, the desired-size monodisperse microspheres could be obtained.
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    Software protection method based on self-modification mechanism
    WANG Xiang-Gen, SI Duan-Feng, FENG Deng-Guo, SU Pu-Rui
    2009, 26 (5): 688-694. DOI: 10.7523/j.issn.2095-6134.2009.5.015
    Abstract ( 1430 ) PDF ( 173KB ) ( 3994 )

    In this paper, we present a new method based on self-modification mechanism to protect softwares against illegal acts of hacking. The key idea is to converse key codes into data in the original program so as to make programs harder to analyze correctly. Then, we translate data to executable codes by enabling the virtual memory page which stores the hidden code to be executable at run-time. Our experiments demonstrate that the method is practical and efficient.

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    SA-DBSCAN:A self-adaptive density-based clustering algorithm
    XIA Lu-Ning, JING Ji-Wu
    2009, 26 (4): 530-538. DOI: 10.7523/j.issn.2095-6134.2009.4.015
    Abstract ( 2645 ) PDF ( 268KB ) ( 3906 )

    DBSCAN is a classic density-based clustering algorithm. It can automatically determine the number of clusters and treat clusters of arbitrary shapes. In the clustering process of DBSCAN, two parameters, Eps and minPts,have to be specified by uses. In this paper an adaptive algorithm named SA-DBSCAN was introduced to determine the two parameters automatically via analysis of the statistical characteristics of the dataset, which enabled clustering process of DBSCAN fully automated. Experimental results indicate that SA-DBSCAN can select appropriate parameters and gain a rather high validity of clustering.

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    A block Gram-Schmidt algorithm with its application
    ZHAO Tao, JIANG Jin-Rong
    2009, 26 (2): 224-229. DOI: 10.7523/j.issn.2095-6134.2009.2.011
    Abstract ( 2358 ) PDF ( 820KB ) ( 3817 )

    Gram-Schmidt algorithm is one of the fundamental methods in linear algebra, which is mainly used to compute QR decomposition. The classical and modified Gram-Schmidt are both based on level 1 or level 2 BLAS operations which have low cache reuse. In this paper, a new block Gram-Schmidt algorithm is proposed. The new algorithm ensures the orthogonality of resulting matrix Q is close to machine precision and improves performance because of using level 3 BLAS. Numerical experiments confirm the favorable numerical stability of the new algorithm and its effectiveness on modern computers.

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    Design of high resolution camera system based on full frame CCDs
    LIU Guang-Lin, YANG Shi-Hong, WU Qin-Zhang, XIA Mo
    2007, 24 (3): 320-324. DOI: 10.7523/j.issn.2095-6134.2007.3.008
    Abstract ( 2333 ) PDF ( 1138KB ) ( 3760 )
    A design of high resolution camera system based on DALSA’ s CCD evaluation kit EKxxxx was presented. It was composed of a pulse pattern generator (SAA8103), a vertical line driver (TDA9991), four analog-to-digital interfaces (TDA9965) and a system controller (P89LV51RD2). Camera link with medium configuration was adopted to transfer digital images. The software for controlling and debugging the camera was developed. To correct the non-uniformity of 4 outputs, a method based on two-point correction was described. The system can acquire ultra high resolution pictures at a high frame rate thus it is suitable for aero photography.
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    A CMOS high performance 50MSPS sample/hold circuit
    LI Tie, GUO Li, BAI Xue-fei
    2007, 24 (6): 788-793. DOI: 10.7523/j.issn.2095-6134.2007.6.010
    Abstract ( 2500 ) PDF ( 1540KB ) ( 3526 )
    A high performance CMOS sample/hold circuit is presented, which achieves the precision of 10-bit over Nyquist band in 50-MHz sampling frequency at 3.3-V supply. This circuit uses full differential circuits, bottom-plate sampling, bootstrap circuits and high performance gain-boost operational amplifier. Simulation in 0.35-μm CMOS process shows the circuit consumes 18-mW of power.
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    An easy-to-deploy behavior monitoring scheme for Android applications
    WANG Xueqiang, LEI Lingguang, WANG Yuewu
    2015, 32 (5): 689-694. DOI: 10.7523/j.issn.2095-6134.2015.05.016
    Abstract ( 699 ) PDF ( 1223KB ) ( 3512 )

    Malicious applications pose tremendous threats to Android platform. More than 90% of malicious codes are introduced in the form of Android apps. Hence, behavior monitoring scheme for Android applications are required in order to resolve the problem. However, most of the schemes are based on system customization and hard to deploy on devices for Android's fragmentation problem. In this paper, an easy-to-deploy Android application monitoring method on the basis of process hijacking is proposed after analysis of Android process model and code execution details. The method depends on Dalvik interpreter entry point and system call interception. The authors created a fully usable prototype of the system, and the evaluation results show that the system is easy to deploy, provides a whole-scale behavior of Android applications, and incurs little performance overhead.

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    Heavy metals in aerosol in China: pollution, sources,and control strategies
    TAN Ji-Hua, DUAN Jing-Chun
    2013, 30 (2): 145-155. DOI: 10.7523/j.issn.1002-1175.2013.02.001
    Abstract ( 3002 ) PDF ( 1395KB ) ( 3453 )

    In recent years, the heavy metal pollution incidents in China were frequently reported. However, studies on pollution, sources, and control strategies of atmospheric heavy metals in China are rare. We summarize the research results reported in recent years. The features of pollution level, seasonal variation, regional differences, size distribution of the atmospheric heavy metal elements including Pb, V, As, Mn, Ni, Cr, and Cd in China are analyzed. The main sources, current control status, and control technologies of atmospheric heavy metals are discussed. Comprehensive suggestions for China's heavy metal pollution control are put forward based on the summarization of the progress and experience of the atmospheric heavy metal pollution control in other countries and regions.

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    Optimized Regulation Model of Human-Earth System Based on System Dynamics
    CHENG Ye-Qing
    2006, 23 (1): 83-90. DOI: 10.7523/j.issn.2095-6134.2006.1.016
    Abstract ( 1884 ) PDF ( 816KB ) ( 3268 )
    study of human-earth system is the most important content in geography; regional sustainable development relies on the reasonable structure optimal model and effective regulation of regional human-earth system. County region is a complex and opening human-earth system, taking Huangling county as an example, the environment, resources exploitation, economic development and structure evolvement of industry were systematically analyzed. And the systematical dynamic model was established and multi-projects were simulated with the theory and method of system dynamic. Optimized regulation models of human-earth system evolvement were educed based on three projects: (1) Traditional evolvement method. The intensity of resource exploitation and environment pollution is the least, but the speed of its economy development is the lowest, which restrict social sustainable development and economic reproduction. (2) Economy development method. The intensity of resource exploitation and environment pollution is the worst, economic development mostly depends on higher investment and pollution, which is a traditional mode of unsustainable development. (3) Harmonious development mode. The mode considers not only economic sustainable development and natural recourses utilizing reasonably, but also gives more attention to environment protection and harmonious development of industry, agriculture, tourism and so on. It is the optimized mode of the human-earth system evolvement.
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    Rice Varietal Improvement and Rice Production in China
    LI Hai-Ming
    2007, 24 (1): 1-8. DOI: 10.7523/j.issn.2095-6134.2007.1.001
    Abstract ( 1670 ) PDF ( 832KB ) ( 3235 )
    The specific objective of the study is to analyse the adoption of improved varieties and the changes in characteristics of varieties across China. It also estimates the contribution of varietal improvement to rice production in China. The results indicated that the story of rice improvement over the past 50 years stood as an enormous success. Nearly 30% of the net gain in rice production came from varietal improvement. Compared with the beginning of 1980s, the numbers of released varieties have been improved by 1. 5 times, the share of total rice area planted to varieties with resistances has increased 10%, and the planting area of high-quality varieties has increased 50%. However, the declining contribution of varietal improvement since 1997 pointed out that government should encourage breeders to explore elite germplasm, improve breeding level, and break through yield stagnates so that varietal improvement can contribute greater to rice production.
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    Experiment and numerical simulation of thermal conductivity of uranium dioxide
    WANG Zeng-Hui, HUANG Xiao-Feng
    2009, 26 (3): 415-418. DOI: 10.7523/j.issn.2095-6134.2009.3.017
    Abstract ( 1994 ) PDF ( 929KB ) ( 3192 )

    Uranium dioxide is a kind of steady nuclear fuel that has the characteristic of high melting point and steady property. The thermal conductivity of uranium dioxide can directly influence the temperature distribution of nuclear fuel and the max temperature of the center of nuclear fuel. The experimental results and expression of thermal conductivity have been compared in the paper. The deviation between the experiment results has decreased. The non-equilibrium molecular dynamics simulation results are in good agreement with the experiment results in medium temperature region. In low temperature region, it is necessary to add the quantum correction to the kinetic energy computation of phonon. In high temperature region, it is needed to use the accurate potential model and build up the electron gas energy transport model and photon radiation energy transport to study the thermal conductivity well and truly for the nuclear reactor safety design and uranium dioxide engineering application.

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    Spectrophotometric determination of polyphenols in Quercus mongolicus Fisch leaves by means of Folin-ciocalteu reagent
    ZHANG Guo-You, TANG Ling, CHEN Wei, HE Xing-Yuan, HUANG Wei
    2009, 26 (3): 319-322. DOI: 10.7523/j.issn.2095-6134.2009.3.005
    Abstract ( 1631 ) PDF ( 152KB ) ( 3129 )

    The total polyphenols(TP)content of Quercus mongolicus Fisch leaves extracts was analyzed by Folin-ciocalteu colorimetry,with gallic acid as standard.The method was improved and verified in the aspects of stability, linearity,precision and accuracy.The results showed that the total polyphenols content of Quercus mongolicus Fisch leaves extracts could be well calculated according to their colorimetric absorption at 760nm by applying Folin-ciocalteu reagent (1mol/L) 0.15mL and 10% volume fraction of Na2CO3 0.15mL at 25℃ for 80min. The (TP)content in Quercus mongolicus Fisch leaves determinated by the method was 6.39% and RSD was 1.90%.

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    An Improved K-means Algorithm Based on Optimizing Initial Points
    QIN Yu, JING Ji-Wu, XIANG Ji, ZHANG Ai-Hua
    2007, 24 (6): 771-777. DOI: 10.7523/j.issn.2095-6134.2007.6.008
    Abstract ( 2524 ) PDF ( 833KB ) ( 3079 )
    K-means is an important clustering algorithm. It is widely used in Internet information processing technologies. Because the procedure terminates at a local optimum, K-means is sensitive to initial starting condition. An improved algorithm is proposed, which searches for the relative density parts of the database and then generates initial points based on them. The method can achieve higher clustering accuracies by well excluding the effects of edge points and outliers, as well as adapt to databases which have very skewed density distributions.
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    MEIL--A routing protocol with high throughput over wireless mesh network
    ZHANG Rui, HONG Pei-Lin ,LU Han-Cheng , ZHANG Xing
    2007, 24 (4): 473-479. DOI: 10.7523/j.issn.2095-6134.2007.4.011
    Abstract ( 2140 ) PDF ( 977KB ) ( 2986 )
    Because of the unique characteristics over wireless mesh networks, such as multi-radio multi-channel and static nodes, traditional Ad hoc network routing protocols can not work very well, which are based on the condition of “shortest path”. This paper presents a novel routing protocol named MEIL for wireless mesh networks. It designs routing metrics according to the wireless link loss, interference between channels and the load of wireless mesh nodes. MEIL chooses the route with lower loss, smaller interference and lighter load, so it can improve the throughput of the network efficiently. The simulation results show that MEIL performs much better than the AODV routing protocol and the DSDV+ETX algorithm under the circumstances of various services, and it is suitable for wireless mesh networks.
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    Cytotoxicity of ZnO nanoparticles in human lung cancer cell lines A549
    WANG Lin , WANG Li-juan , ZHANG Fang , DING Wen-jun
    2009, 26 (1): 83-90. DOI: 10.7523/j.issn.2095-6134.2009.1.012
    Abstract ( 2148 ) PDF ( 1035KB ) ( 2819 )
    The aim of the study was to investigate the toxic effects of nanosized ZnO in vitro. Characterization of ZnO nanoparticles was carried out by atomic force microscope (AFM), transmission electron microscope (TEM) and X-ray diffraction (XRD). In this study, lung cancer cell lines A549 were exposed to 0mmol/L, 0.1mmol/L, 0.5mmol/L, 1mmol/L, 5mmol/L, 10mmol/L of ZnO nanoparticles, respectively. MTT assay was performed to evaluate the viabilities of ZnO-treated cells after 12h, 24h, 36h and 48h exposure. The activities of lactate dehydrogenase (LDH), cellular superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA) were determined after exposure to 1mmol/L ZnO for 24 h. Moreover, apoptotic characteristics and reactive oxygen species (ROS) production in A549 cells were measured. ZnO nanoparticles were needlelike crystals (75 nm length; 20 nm diameter). The viability of A549 cells were reduced after exposure to ZnO nanoparticles in a dose-dependent manner. The activities of LDH and the levels of MDA were significantly increased (P < 0.05, P < 0.01), respectively. However, the activities of CAT were significantly decreased (P < 0.01). No significant difference in the activities of SOD was observed between the ZnO-treated cells and the controls. ZnO nanoparticles at 1mmol/L induced apoptosis in A549 cells. The levels of ROS in ZnO-treated cells were significantly higher than that in controls. These results suggested that ZnO nanoparticles could result in apoptosis in A549 cells through oxidative stress.
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    Application of LSTM neural network for intermediate-term earthquake prediction: retrospective prediction of 2008 Wenchuan M S8.0 Earthquake
    SHI Yaolin, LI Linfang, CHENG Shu
    2022, 39 (1): 1-12. DOI: 10.7523/j.ucas.2021.0063
    Abstract ( 577 ) PDF ( 9879KB ) ( 350 )
    Earthquake prediction is a difficult problem in contemporary science, and applications of machine learning methods in the prediction have drawn intensive attention. Large earthquakes can cause huge casualties and economic losses, and are the main goals of earthquake prediction. We studies intermediate-term (one-year) earthquake prediction in Sichuan and Yunnan provinces using the earthquake catalogue since 1970 by the sliding time-space window technique and LSTM(long short-term memory) neural networks. Sixteen earthquake prediction indexes that reflect the temporal and spatial features of earthquake sequences were used in the neural network. The neural network was trained using data sets from 1970 to 2004 (70% of all earthquake catalogues). Retrospective prediction tests were conducted on earthquakes after 2005, the accuracy rate (actual magnitude fell within ±0.5 of the predicted magnitude) was 70.2%, over-prediction rate was 18.7%, and under-prediction rate was 11.1%. The 2008 Wenchuan M S8.0 earthquake was retrospectively predicted. In order to understand the robustness of the model, we have done some tests, such as to expand the study area, change the weights of large earthquakes in calculation of the mean square error, etc. The LSTM neural network model still performed well in the tests.
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    Predicting sunspot variations through neural network
    CHENG Shu, SHI Yaolin, ZHANG Huai
    2022, 39 (5): 615-626. DOI: 10.7523/j.ucas.2021.0068
    Abstract ( 425 ) PDF ( 16219KB ) ( 333 )
    Sunspot variations are the sun's symptoms of strong magnetic perturbations. In this paper, we use long short-term memory neural network and one-dimensional convolution neural network to detect sunspot variations. Here we use three different datasets, including the yearly mean sunspot number (YSSN) from 1700 to 2020, the monthly mean sunspot number (MSSN) from 1749 to 2021 and the monthly mean sunspot areas (MSSA) from 1874 to 2021. First, based on the YSSN dataset, we obtain YSSN for 2021 and the predicted YSSN in the 25th solar cycle appears at 2025 which equals 163.4; Then, based on the MSSN dataset, we obtain MSSN for June 2021 and the predicted YSSN in the 25th solar cycle appears in October 2024 which equals 245.9; Next, based on the MSSA dataset, the predicted MSSA for June 2021 is 73.1; Finally, the latitude is divided into 13 partitions to predict the butterfly diagram, and still, neural network can reconstruct the butterfly diagram. Therefore, neural network can provide a physical perspective for sunspot investigation.
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    A new joint model for extracting overlapping relations based on deep learning
    ZHAO Minjun, ZHAO Yawei, ZHAO Yajie, LUO Gang
    2022, 39 (2): 240-251. DOI: 10.7523/j.ucas.2020.0026
    Abstract ( 394 ) PDF ( 4199KB ) ( 143 )
    With the rapid developments of Internet technologies and popularization of Internet among daily activities, we are surrounded by all kinds of information every moment. Hence, to mine valuable information from massive data has always been a hotspot of research at home and abroad. In this environment, relationship extraction is an important subtask of information extraction, which purpose is to identify the relationship between entities from the text, so as to mine the structured information in the text, that is, fact triplet. In the text, entity overlapping and relationship overlapping are very common phenomena, but the existing joint extraction model cannot effectively solve such problems, so the paper proposes a new joint extraction model, which regards the relationship extraction task as consisting of entity recognition and relationship recognition of two subtasks. The two subtasks are identified using sequence labeling method and multi-classification method, respectively. In the joint extraction process, in order to fully mine the semantic information of the text, the part of speech (POS) and syntactic dependency (Deprel) features were added to the input layer of the model. Attention mechanism is also introduced in the model, which can eliminate the problem of long-distance dependence as sentence length increases. Finally, the paper conducts relationship extraction experiments on the NYT dataset and the WebNLG dataset. The experimental results show that the model proposed in the paper can effectively solve the problem of overlapping relationships and obtain the best extraction effect.
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    Spatiotemporal variation of grassland aboveground biomass in Inner Mongolia from 2000 to 2019
    YUE Rongwu, ZHANG Na, WANG Jingjie, LI Zhenyu, YAN Zhihui, FENG Yiming
    2022, 39 (1): 21-33. DOI: 10.7523/j.ucas.2020.0047
    Abstract ( 377 ) PDF ( 14030KB ) ( 300 )
    Based on the acquisition of a large number of grassland aboveground biomass (AGB) field sampling data and the corresponding remote sensing indices, random forest (RF) models were constructed for different grassland types in Inner Mongolia. After validating the reliability of the models, the maximum AGB values from 2000 to 2019 were simulated. The results showed that the average annual maximum AGB was (82.74±56.34)g/m 2, gradually declining from northeast to southwest. The grassland types in the order of decreasing AGB:temperate meadow steppe, lowland meadow, temperate typical steppe, temperate desert steppe, temperate steppe desert, and temperate desert. From 2000 to 2019, the maximum AGB showed an overall significantly rising trend, and increased most significantly for lowland meadow and temperate typical steppe. The maximum AGB exhibited increasing trend for 70.62% of Inner Mongolia, and increased significantly for 16.28% of the area. The area with significantly increasing AGB was larger than that with significantly decreasing AGB for all the grassland types. However, the maximum AGB for all grassland types was on the fluctuant increase, and the temperature desert steppe had the largest interannual fluctuation while temperature desert the smallest. The interaction between summer air temperature and accumulated precipitation had the greatest positive effect on AGB, followed by the total precipitation from January to August, while summer air temperature had little negative effect on AGB.
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    Robust ordinal mislabel logistic regression based on γ-divergence
    GUO Meijun, REN Mingyang, LI Shiming, ZHANG Sanguo
    2022, 39 (3): 289-301. DOI: 10.7523/j.ucas.2020.0056
    Abstract ( 375 ) PDF ( 1540KB ) ( 126 )
    Ordinal multi-classification methods have been studied widely. Traditional ordinal multi-classification methods assume that the sample label is not mislabeled. Due to the complexity of the real data and the limited artificial experience, it is unrealistic to obtain completely accurate labels, in which conventional methods perform poorly. In this article, we propose an ordinal mislabel logistic regression method based on γ-divergence, which possessing strong robustness when dealing with ordinal mislabeled response data. That is to say, when mislabeled, the weight of the sample in parameter estimation equation diminish compared to the case that the sample is properly labeled. Our method not only possesses the robustness but also can ignore the mislabel probabilities in the model. We construct the model by minimizing γ-divergence estimation and solve the model by gradient descent algorithm. Both simulation studies and real data analysis demonstrate that the method, namely robust ordinal mislabel logistic regression, is efficient to analyze ordinal mislabeled response data.
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    Removing highlights from single image via an attention-auxiliary generative adversarial network
    ZHAO Xinchi, JIANG Ce, HE Wei
    2022, 39 (4): 524-531. DOI: 10.7523/j.ucas.2020.0018
    Abstract ( 372 ) PDF ( 10210KB ) ( 119 )
    The highlights in the image will degrade the image quality to some extent. In this paper, we focus on visually removing the highlights from degraded images and generating clean images. In order to solve this problem, we present an attention-auxiliary generative adversarial networks. It mainly consists of the convolutional long short term memory network with squeeze-and-excitation (SE) block and the map-auxiliary module. Map-auxiliary can instruct the autoencoder to generate clean images. The injection of SE block and map-auxiliary module to the generator is the main contribution of this paper. And our proposed deep learning-based approach can be easily ported to handle other similar image recovery problems. Experiments prove that the network architecture is effective and makes a lot of sense.
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    Building extraction based on UNet++ network with different backbones
    GU Yumin, YAN Fuli
    2022, 39 (4): 512-523. DOI: 10.7523/j.ucas.2020.0040
    Abstract ( 368 ) PDF ( 55188KB ) ( 417 )
    Automatic building extraction methods based on deep learning theory have the technical characteristics of high accuracy and speed,and are of great significance in industrial applications, such as urban planning,disaster prevention and mitigation. This paper introduces the deep learning modules and the traditional remote sensing validation section in the proposed building extraction method in high-resolution remote sensing imageries, forming an operational deep-learning-theory based building extraction technical system that integrates different backbone modules, UNet + + networks,and remote sensing authenticity verification modules. The basic network is transformed through the traditional convolutional network model backbones,such as VGG,ResNet, and Inception to improve the model operational efficiency,strengthen the model feature learning capabilities,verify the effectiveness and applicability of the algorithm through authenticity validation. Taking the Massachusetts building dataset published by Mnih as the data source,a comparative analysis was carried out with the traditional non-full convolutional network model and full convolutional network model. The results show that an increasing in the depth and width of the model can substantially improve the building extraction results. The InceptionV3-UNet + + backbone model has the best performance in recall rate,accuracy,CSI, F1 score,Kappa coefficients, and total accuracy,reaching 85. 14%,90. 50%,0. 781 6,0. 877 4,0. 850 4, and 95. 57%,respectively,and its robustness is also verified on the WHU datasets. This method has significantly improved the extraction accuracy and the details of the buildings extracted, especially on complex and irregular buildings, which will facilitate the building extraction applications in real, complex, and large scene of high-resolution remote sensing imageries.
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    Tracking hot spots of sustainable development research in domestic and foreign literature in the past twenty-five years: bibliometric analysis based on CiteSpace
    ZHANG Xiaoping, ZHAO Yanyan, JIN Fengjun, SUN Wei
    2022, 39 (1): 55-63. DOI: 10.7523/j.ucas.2020.0006
    Abstract ( 356 ) PDF ( 5318KB ) ( 179 )
    Sustainable development is a theme concerned worldwide and has gained much attention from both domestic and foreign research fields. Based on the core databases of CNKI and WOS (Web of Science) and CiteSpace software, this paper tracks the research hotspots of sustainable development at home and abroad from 1994 to 2018. The results showed that:1) Research hotspots in common focused on multi-dimensional and multi-scale research on resources, environment and economy, sustainability evaluation, sustainable development strategy and policy, but the emphasis and perspective were different. 2) The research cooperation among international institutions was closely linked, while the cooperation between domestic institutions was relatively scattered and independent. 3) In contrast to Chinese literature focusing more on macro and regional scales, the research literature published in English from micro perspective on communities was relatively abundant. 4) Domestic studies tended to reveal problems in sustainable development, while foreign studies emphasized the role of science and technology, information and innovation in promoting regional sustainability. The comparative analysis of research hotspots at home and abroad is expected to shed new lights on future studies concerning sustainable development in China.
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    Review of studies on electrical conductivity of hydrous minerals
    WANG Libing, WANG Duojun, SHEN Kewei
    2022, 39 (4): 433-448. DOI: 10.7523/j.ucas.2022.027
    Abstract ( 338 ) PDF ( 5955KB ) ( 153 )
    Hydrous minerals play a vital role in the Earth's interior water cycle. The path of water cycle and the change of composition in the Earth's interior can be estimated by the electrical conductivity of typical hydrous minerals. In this paper, we summarized the electrical conductivities, conduction mechanisms, dehydration mechanisms and geophysical implications for typical hydrous minerals before and after dehydration under high temperatures and pressures. The electrical conductivities of most hydrous minerals before dehydration are generally distributed at 10 -4S/m, and increase significantly after dehydration. There are differences in the electrical conductivities of different hydrous minerals. The coupling of dehydration mechanisms and conduction mechanisms may determine the electrical conductivity of hydrous minerals during dehydration. The electrical conductivity of hydrous minerals after dehydration generally depends on the composition and connectivity of the fluid. The changes of electrical conductivities of hydrous minerals before and after dehydration provide experimental constraints for the high-conductivity anomalies at different depths in subduction zones. In addition, the determination of the composition of the fluid derived from the dehydration of the hydrous minerals enriched our knowledge of material circulation in subduction zones. Based on the recent progress, the potential research directions of the electrical conductivity of hydrous minerals are prospected.
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    Spatio-temporal change of ecological land in lake-basin of Yangtze River system
    CHEN Zhongyuan, GAO Yongnian
    2022, 39 (2): 172-184. DOI: 10.7523/j.ucas.2021.0045
    Abstract ( 333 ) PDF ( 16565KB ) ( 356 )
    The area of lake type watershed (LTW) accounts for more than 30% of the Yangtze River basin, and the change of its ecological land plays an important role in regulating the water ecological environment of the Yangtze River. Based on the land use data of 229 LTWs in the Yangtze River system from 1980 to 2015, the temporal and spatial change characteristic of ecological land in recent decades was analyzed by using the methods of ecological land area and its proportion, improved comprehensive dynamic degree, transfer matrix, and spatial operation. The results showed that the change of ecological land use in the LTWs presented a three-stage trend of "first gradually increasing, then fluctuating and stable, and finally rapidly decreasing"; Woodland and grassland showed a downward trend, while wetland showed an upward trend; The comprehensive dynamic degree of ecological land in the LTWs presented a state of "wave-like vibration". From the perspective of lake size classification, the total area of ecological land in the four types of LTW was quite different. The watershed ecological land corresponding to small lakes was the least, followed by large and medium-sized lakes, while the watershed ecological land area of super large lakes was the largest. Although the ecological land change trend in different types of LTWs was first rising and then declining, the corresponding turning points appeared in different years. From the perspective of different regions of the Yangtze River system, compared with 1980, the ecological land of the LTW in the source, middle, and lower regions increased in 2015, while the ecological land of the LTW in the upper regions decreased; The transfer amount within ecological land was the least, and the transfer amount between ecological land and non-ecological land and the transfer amount within nonecological land accounted for more than 42% of the total transfer amount. The transfer of ecological land was the most complex and intense in the middle region, followed by the lower region, the source region and the upper region were relatively gentle and simple. Before 2000, the main reasons for the change of ecological land were cutting trees, developing agriculture and animal husbandry and reclaiming land from lakes. After 2000, the main reasons were returning farmland to forests and building reservoirs. The increase of construction land, i. e., urban expansion, was one of the main reasons for the decrease of ecological land for most LTWs from 2010 to 2015.
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    DFT mechanistic insight into the modular strategy involved in the palladium-catalyzed synthesis of cyclopentenones from α,β-unsaturated acid chlorides and alkynes
    ZHONG Liang, ZHAO Ruihua, WANG Zhixiang
    2022, 39 (2): 145-153. DOI: 10.7523/j.ucas.2021.0046
    Abstract ( 320 ) PDF ( 8789KB ) ( 144 )
    Cyclopentenones are important synthetic building blocks and as motifs appear in bioactive molecules and natural products. We applied density functional theory (DFT) calculations to gain insight into the modular strategy involved in the palladium-catalyzed synthesis of cyclopentenone from α,β-unsaturated acid chlorides and alkynes in the presence of hydrosilane. The study unveils that the transformation proceeds via the sequence:the disassembly of α,β-unsaturated acid chloride into vinyl, carbonyl, and Cl fragments with the palladium catalyst; carbon monoxide release; coupling of alkyne with vinyl group; carbon monoxide re-coordination and migratory insertion to form another C-C bond with alkyne, ring-closure via C=C bond insertion, transmetalation with hydrosilane, C, H-reductive elimination to release the product. Different from the mechanism proposed by the experimentalists, the CO group is involved in the reaction via separate liberation and re-coordination in the solvent cage, rather than persistent coordination with palladium. The transmetalation for H/Cl exchange takes place at the late stage and is a bottleneck of the transformation, instead of at early disassembly stage.
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    Transport pathways and potential source regions of PM 2.5 in Wuhai City of northwest arid area
    YU Chuang, CHEN Wei, ZHANG Yuxiu
    2022, 39 (1): 43-54. DOI: 10.7523/j.ucas.2020.0055
    Abstract ( 307 ) PDF ( 10150KB ) ( 99 )
    Wuhai was one of the major coal industry cities in northwest arid area of China, the concentration variation characteristics, transport pathways, and the potential source regions of PM 2.5 were unclear. The transport pathways and the potential source regions of PM 2.5 in Wuhai were discussed by cluster analysis, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods based on the hourly monitoring data of PM 2.5 mass concentration in Wuhai from 2016 to 2018. Results showed that the average annual concentration of PM 2.5 had a downward trend during 2016-2018, with the highest concentration in winter and the lowest in summer. Cluster analysis showed that the northwesterly pathways were the major transport pathway of PM 2.5 for all seasons. The long-distance transport airflow mostly occurred in spring, autumn, and winter, the concentration of PM 2.5 in four trajectories was about 97.96-151.33μg·m -3, while the short-distance transport airflow was main pathway in summer, its concentration of PM 2.5 was about 87.11-96.88μg·m -3. The PSCF and CWT analysis indicated that the potential source regions of PM 2.5 were the largest in winter, mainly occurred in Kumtag Desert, Qaidam Basin, Tengger Desert, Badain Jaran Desert, and Hexi Corridor Area. The main potential source regions in spring and autumn were located in Kumtag Desert, and Hexi Corridor Area. The potential source region was the smallest in summer, mainly came from Hexi Corridor Area. During the heavy pollution period, the main transport pathways of PM 2.5 came from northwest also, the potential source regions were mainly located in the border area of Qinghai and Gansu, parts of eastern Xinjiang and southern Wuhai. These results showed that the potential source regions of PM 2.5 in Wuhai were mainly located in the northwest arid desert area. Therefore, the implementation of wind prevention, sand fixation, and desertification control could effectively improve the air quality of Wuhai and the northwestern area of China.
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    Comparison of natural 15N abundance technique and 15N dilution technique in the determination of plant nitrogen fixation
    LI Runfu, NIU Haishan, KONG Qian, LIU Qiang
    2022, 39 (1): 34-42. DOI: 10.7523/j.ucas.2021.0008
    Abstract ( 304 ) PDF ( 1995KB ) ( 139 )
    Biological nitrogen fixation (BNF) is an important source of nitrogen in ecosystem, therefore, several experimental techniques and calculating methods have been developed to quantify the contribution of BNF to plants and vegetations. In this study, percentage of plant N derived from N 2-fixation (%Ndfa) was evaluated for a leguminous species, Astragalus arnoldii, in an alpine steppe in Qinghai-Tibet Plateau in order to compare two dominant in situ experimental techniques with different calculating approaches, reference plants, and sampling times. The δ 15N values of four reference plants, i.e., Stipa purpurea, Kobresia pygmaea, Leontopodium nanum, and Carex moorcroftii, were significantly lower in late August than in late July ( P<0.05). However, they were significantly higher in later August, 30 days after application of ( 15NH 4) 2SO 4 to soil, than late July which was 24h after labeling ( P<0.05). In either site with or without ( 15NH 4) 2SO 4 application, δ 15N of A. arnoldii did not differ in the two sampling times. Besides,%Ndfa of A. arnoldii did not differ between calculation based on 15N excess relative to atmospheric N 2 and that relative to unlabeled plants. Nevertheless,%Ndfa measured by natural abundance technique was significantly higher than that by isotope dilution technique ( P<0.05) except for L. nanum as the reference species. The sampling time had a significant effect on estimated%Ndfa values in both the naturalabundance technique ( F=89.906, P<0.01), and isotope dilution technique ( F=496.712, P<0.01).
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    Driving forces for ongoing northward indentation of India into Asia: insight from 3D numerical modeling of mantle dynamics
    ZHENG Qunfan, SHI Yaolin
    2021, 38 (6): 721-728. DOI: 10.7523/j.issn.2095-6134.2021.06.001
    Abstract ( 303 ) PDF ( 7739KB ) ( 406 )
    The collision between the Indian and Asian plates started about 60 Ma ago. It has continued to shorten the Asian side by at least 1 000 km, and thus formed the huge Qinghai-Tibetan Plateau. One important lithospheric dynamical issue is what kind of force could overcome such huge resistance from the Asian plate and from the Qinghai-Tibetan Plateau and drive the Indian plate continuously moving northward for such a long time. We performed 3D numerical modeling to reveal the role of mantle flow for the dynamics of the India-Asia collision by considering the global temperature structure converted from the seismic tomographic model S20RTS as initial temperature and the absolute plate motion velocities as initial surficial velocity boundary conditions. Our results suggest that drags from the moving asthenospheric mantle could be the main cause for transporting Indian plate northward.
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    An experimental investigation on the breakup characteristics of liquid metal free jet under a horizontal magnetic field
    DONG Quanrun, YANG Juancheng, NI Mingjiu
    2022, 39 (5): 577-585. DOI: 10.7523/j.ucas.2022.029
    Abstract ( 298 ) PDF ( 10358KB ) ( 369 )
    Based on a high-speed photographic system, experiments on three-dimensional free jets of liquid metal in the absence of a magnetic field and in a horizontal magnetic field have been carried out to observe the process of liquid GaInSn jet breakup and droplet formation in an oxygen-free environment with a maximum We of 400 and a maximum Ha of 30. From the results on jet morphology, surface disturbance, and breakup length, we analyzed the characteristics of jet breakup. In the absence of magnetic field, the jet shows nine different morphologies, and the surface disturbance shows two forms:expansion wave and sinusoidal wave; with the increase of We, the disturbance amplitude first decreases and then increases, and the breakup length first increases and then decreases. When a horizontal magnetic field is imposed, the jet shows four typical morphologies, with the leading edge of the jet being flattened in the direction of the vertical magnetic field line and elliptical along the magnetic field line. As the Ha number increases, the jet break length tends to increase overall, but decreases in some operating conditions. The results of this paper have enriched the phenomenon of liquid metal jets under magnetohydrodynamic effects.
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    Fine process method for Gaofen-3 L1A-level image
    FANG Hankang, ZHANG Bo, CHEN Weirong, WU Fan, WANG Chao
    2022, 39 (5): 648-657. DOI: 10.7523/j.ucas.2021.0005
    Abstract ( 282 ) PDF ( 9292KB ) ( 73 )
    Level one A (L1A) product of Gaofen-3 SAR satellite is the primary image set delivering for customer. This paper presents a complete workflow to facilitate the post-process of GF-3 L1A images for follow-up scientific research or value-added applications, where robust and precise processing is essential to generate the advanced high-level product concerning radiometric correction and geometric correction. Firstly, to eliminate the statistical bias caused by the null and zero pixel values induced in the quantization of the L1A product, an improved radiometric correction formula is derived based on the equivalent noise coefficient of Gaofen-3 images. Then, to determine the coordinates of image corners, an inverse algorithm supported by RPC parameters is proposed for geometric correction. This algorithm is robust by counting on the orbit direction, look direction, and sampling interval provided in an XML metadata file. Finally, a SAR filter operator is introduced into the resampling step of output results to improve the equivalent look number. Experimental results comparing with the radiometric values of a sentinel-1 image and the geometric accuracy of a sentinel-2 optical image, respectively, validate the accuracy and reliability of this method for L1A product processing.
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    A LiDAR data visualized management and analysis system for power line inspection application based on B/S architecture
    LIANG Lei, XI Xiaohuan, WANG Cheng, WANG Jinliang, HUANG Youju
    2022, 39 (2): 201-207. DOI: 10.7523/j.ucas.2020.0044
    Abstract ( 277 ) PDF ( 12077KB ) ( 319 )
    LiDAR, being an active remote sensing technology, can obtain 3D information of surface feature and has extensive applications in power line fields, such as construction line selection, digital management, safety inspection, etc. However, the software visualized management ability is a serious limitation of its widespread use. In this paper, we built the overall and functional design of a LiDAR data visualized management and analysis system based on B/S architecture, focusing on electric power line inspection application requirements. WebGL was applied to develop this system and points cloud data were stored and indexed by an improved modifiable nested octree, and rendered by Levels of Detail and other technologies. A lot of practical function and tools, such as interaction in 3D scene, managing data of power line features, editing point cloud attribute, 3D measurement, clipping, profile map and points cloud filtering were all achieved. The research results show that LiDAR electric power line inspection in web browser is applicable and effective, and has prospective application in future.
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    Hot spots tracking of nighttime light data application in research of urbanization and its resource and environmental effects
    ZHANG Xiaoping, GAO Shanshan, CHEN Mingxing, ZHAO Yanyan
    2022, 39 (4): 490-501. DOI: 10.7523/j.ucas.2021.0010
    Abstract ( 274 ) PDF ( 4386KB ) ( 167 )
    Being closely related to human socioeconomic activity and its footprints, nighttime light (NTL) data shows great advantages in urbanization and socioeconomic development research, especially in densely populated cities. Based on CiteSpace software and the core databases of CNKI (China National Knowledge Infrastructure) and WOS (Web of Science), this paper tracked the hot spots of NTL data in the study of urbanization and related resource consumption and environmental effects from 2000 to 2019. The main results are as follows. 1) Urbanization was the main focus of the application of NTL data, but the researches on the resource consumption and environmental effects caused by urbanization were slightly weak, which was more obvious in Chinese literature. 2) Researches of urban expansion and urban form evolution focused on process of land expansion based on different features of NTL datasets, while in researches of population, socioeconomic development, electricity consumption and carbon emissions, NTL data usually played the role as a supporting tool to explore spatiotemporal characteristics and mechanism. 3) In regards of air pollution and urban heat island induced by urbanization, NTL datasets were usually used to represent factors related to human activities and their impacts. 4) Urbanization process and its impacts on resource and environment are complex, the improved spatial resolution and integrated multi-source data, along with new methods as machine learning, will make the urbanization related research be more precise and scientific. Finally, the paper summarizes the possible new directions of the application of NTL data in urban geography.
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    The recognition and utilization of Cannabis sativa in ancient Xinjiang viewed from plant remains
    LIU Yan, GU Man, CHEN Tao, WANG Binghua, JIANG Hong'en
    2022, 39 (4): 567-576. DOI: 10.7523/j.ucas.2020.0048
    Abstract ( 271 ) PDF ( 4845KB ) ( 261 )
    Xinjiang is an important area connecting the east and west alongside the Silk Road. As a result of its dry weather and less rainfall, plant remains were well preserved, including hemp ( Cannabis sativa). The history of Cannabis recognition and utilization in ancient Xinjiang could be roughly divided into two stages. Due to inherent advantages of the geographical environment, Xinjiang was firstly affected by the ancient civilization of Central Asia in the prehistoric period, mainly retaining the hallucinogenic tradition of Cannabis. During the historical period, the beginning of the Silk Road promoted exchanges between the Western Regions and the interior areas. The edible and fiber values of Cannabis were gradually accepted. Therefore, in terms of Cannabis usage, ancestors generally had a transformation from psychoactive agents to food crops, fiber crops, and even medicinal plants. In this study, we reviewed the Cannabis researches in Xinjiang during the past years, summarizing the ways and differences of Cannabis utilization, especially their causes in different periods. Meanwhile, we restudied Cannabis remains in Turpan with plant identification and radiocarbon dating, comprehensively sorting out the handed-down and unearthed documents, to explore not only the utilization of Cannabis medicinal value, but also to provide new clues for the spread of Chinese medicine in ancient Xinjiang.
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    Ab initio simulations of NO adsorption on hematite (0001) surface: PBE versus PBE+U
    WU Cuixia, SUN Tao, FABRIS Stefano, DU Lin
    2022, 39 (2): 193-200. DOI: 10.7523/j.ucas.2020.0041
    Abstract ( 268 ) PDF ( 4596KB ) ( 101 )
    NO x( x=1,2) are major air-pollutants detrimental to human health and much effort has been devoted to find efficient photocatalysts capable of removing NO x from air (de-NO x). Recent experiments indicate that hematite (α-Fe 2O 3) is a promising de-NO x photocatalyst. However some key features of the NO adsorption on the hematite surface remain unclear, hindering further comprehension of the photocatalytic process. Here we study the adsorption of NO on the hematite (0001) surface using the PBE+U method with a dispersion correction (vdw) in the framework of density functional theory (DFT). We find the addition of a Hubbard U term in the DFT Hamiltonian strongly affects the adsorption properties, with the adsorption energy (-0.64eV) decreased by 50% with respect to those of PBE (-1.31eV). This decrease is attributed to two factors:(i) the U term shifts the energy of Fe 3d orbitals away from the valence band maximum, making them chemically less active; (ii) the NO molecule has an unpaired π * electron and is more sensitive to the electronic structure of the substrate. In contrast to the inclusion of U, the dispersion correction causes little change to the adsorption properties except increases the adsorption energy by about -0.18eV. We use the Langmuir formula to calculate the thermal equilibrium coverage of NO on the hematite (0001) surface and find predictions made with the PBE+U vdw are more consistent with experiments. These results highlight the importance of strong electronic correlations in describing the hematite surface reactions, and may serve as a starting point to unravel the complete photocatalytic mechanism.
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