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    Toxic effects of Cd2+ on the intestinal structure of Cypridopsis vidua (Ostracoda)
    CHEN Shi-mei, Li Dan-ni, Ding Qing-qing, YU Na
    Journal of East China Normal University(Natural Sc    2017, (4): 168-179.   DOI: 10.3969/j.issn.1000-5641.2017.04.015
    Abstract378)   HTML8)    PDF (1416KB)(943)      
    Cypridopsis vidua is one of the few ostracods which can surrive from heavy pollution water. The toxic effects of Cd2+ on C. vidua and its intestinal ultrastructure were examined using a static renewal system. The LC50 values for cadmium in C. vidua were 5.00, 2.01, 0.46 and 0.14 mg/L at 24, 48, 72 and 96 h exposure respectively, and the safe concentration of Cd2+ for long-term C. vidua survival was less than 0.014 mg/L. To observe the structure changes of its intestinal, four Cd2+ concentrations were set up, and two of them were below the safe concentration of Cd2+ (0.001 and 0.004 mg/L) and the other concentrations were above its safe concentration (0.016 and 0.064 mg/L). The experiment lasted for 7 days. When microstructure of C. vidua was observed, the gastrointestinal orga- nization was not damaged below the safe concentration; while the degree of injury showed a certain amount of time and dose effects in 24-72 hours above the safe concentration, and some structures among those surviving animals were slightly recovered in 7 days under same concentration. Sub-microscopic analysis of intestinal cells of C. vidua in two concentrations (0.004 and 0.064 mg/L) groups showed, different degrees of structure damage were found in the cell membrane, cytoplasm and organelles, which worsened with increasing Cd2+ con- centrations. Among these cellular structures, the damage to the membrane system of the cell was especially serious.
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    Recognition of classroom learning behaviors based on the fusion of human pose estimation and object detection
    Zejie WANG, Chaomin SHEN, Chun ZHAO, Xinmei LIU, Jie CHEN
    Journal of East China Normal University(Natural Science)    2022, 2022 (2): 55-66.   DOI: 10.3969/j.issn.1000-5641.2022.02.007
    Abstract1814)   HTML153)    PDF (1026KB)(1881)      

    As a result of ongoing advances in artificial intelligence technology, the potential for learning analysis in teaching evaluation and educational data mining is gradually being recognized. In classrooms, artificial intelligence technology can help to enable automated student behavior analysis, so that teachers can effectively and intuitively grasp students’ learning behavior engagement; the technology, moreover, can provide data to support subsequent improvements in learning design and implementation of teaching interventions. The main scope of the research is as follows: Construct a classroom student behavior dataset that provides a basis for subsequent research; Propose a behavior detection method and a set of feasible, high-precision behavior recognition models. Based on the global features of the human posture extracted from the Openpose algorithm and the local features of the interactive objects extracted by the YOLO v3 algorithm, student behavior can be identified and analyzed to help improve recognition accuracy; Improve the model structure, compress and optimize the model, and reduce the consumption of computing power and time. Four behaviors closely related to the state of learning engagement: listening, turning sideways, bowing, and raising hands are recognized. The accuracy of the detection and recognition method on the verification set achieves 95.45%. The recognition speed and accuracy of common behaviors, such as playing with mobile phones and writing, are greatly improved compared to the original model.

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    Structure-conductive property relationship of polypyrrole
    YU Bo, XU Xue-cheng
    Journal of East China Normal University(Natural Sc    2014, 2014 (4): 77-87.  
    Abstract2376)      PDF (1700KB)(4483)      
    Polypyrrole was synthesized by oxidative chemical polymerization. Samples presenting different conductivities were obtained by adjusting the preparing temperature. The polypyrrole samples have been investigated by means of four probe method, Solid state 13C NMR spectrum, XRD, FTIR spectroscopy, Raman spectrum and XPS, respectively. The experimental result suggested the fact that the conductivity of polypyrrole samples gradually decreases as the preparation temperature increases. The analysis indicates it is because the changing of internal structure follows the varying of external preparation conditions. The commonly structure of polypyrrole is a linear chain of monomers bonded by α-α carbons at a low preparation temperature. Through such a structure polypyrrole can form both a relatively planar configuration and a relatively planar conformation. This sort of structure provides the sample with a preferable regularity, a longer conjugated chain length and a higher conductivity. However, the ratio of α-α linkage drops as the preparation temperature increases, by which the structure of molecular is damaged, the degree of order declines. The carrier mobility of polypyrrole, as well as the conductive property, became lower.
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    Study of electronic structures and the micro-solvation effect of SO3 and HSO3 in atmospheric aerosols
    Jianan CHEN, Zhipeng LI, Yanrong JIANG, Zhubin HU, Haitao SUN, Zhenrong SUN
    Journal of East China Normal University(Natural Science)    2022, 2022 (1): 31-42.   DOI: 10.3969/j.issn.1000-5641.2022.01.005
    Abstract433)   HTML49)    PDF (942KB)(1036)      

    In this study, we used negative ion photoelectron spectroscopy (NIPES) combined with quantum chemical calculation to explore the electronic structures, micro-solvation effect, and stabilization mechanism of two compounds, SO3 and HSO3, that are readily abundant in the atmosphere. Vertical detachment energies of (3.31 ± 0.02) and (3.91 ± 0.02) eV and adiabatic detachment energies of (3.02 ± 0.05) and (3.56 ± 0.05) eV were measured for SO3 and HSO3, respectively. These results are reproduceable when using a nuclear ensemble approach and Dyson orbitals in the calculation. The typical density of states method, however, cannot demonstrate the nuclear vibration effect, ionization probability, and orbital relaxation effect during the ionization process. We studied the micro-solvation effect of HSO3·(H2O)n (n = 0 ~ 5) and found that system stability was enhanced by an increase in the surrounding water molecules, whereby electrostatic interaction played a dominant role and the induction effect made an increasingly important contribution. We believe this work will help improve the modeling of atmospheric sulfate aerosols and provide a scientific basis for the effective control of haze formation.

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    Survey of mainmemory database availability
    JIANG Ze-Yuan, LIU Hui-Lin, WU Gang, WANG Guo-Ren
    Journal of East China Normal University(Natural Sc    2014, 2014 (5): 82-88.   DOI: 10.3969/j.issn.10005641.2014.05.007
    Abstract1299)      PDF (712KB)(2893)      
    With the development of hardware technology, the cost of main memory is decreasing, which makes it possible to let DBMS (Database Management System) put the whole data into main memory. Compared to traditional DRDB (DiskResident Database), MMDB (MainMemory Database) provides much faster of data storage, higher throughput of applications, stronger ability on concurrent access, and meets the demand of timely response. However, due to its volatility, MMDB has differences on system availability with DRDB. The survey focuses on main strategies of improving the availability of MMDBs, including fast recovery, redundant backup and fault tolerance mechanism.
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    Methods and progress in deep neural network model compression
    LAI Yejing, HAO Shanfeng, HUANG Dingjiang
    Journal of East China Normal University(Natural Science)    2020, 2020 (5): 68-82.   DOI: 10.3969/j.issn.1000-5641.202091001
    Abstract542)   HTML52)    PDF (1132KB)(428)      
    The deep neural network (DNN) model achieves strong performance using substantial memory consumption and high computational power, which can be difficult to deploy on hardware platforms with limited resources. To meet these challenges, researchers have made great strides in this field and have formed a wealth of relevant literature and methods. This paper introduces four representative compression methods for deep neural networks used in recent years: network pruning, quantization, knowledge distillation, and compact network design; in particular, the article focuses on the characteristics of these representative models. Finally, evaluation criteria and research prospects of model compression are summarized.
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    Comprehensive review on green synthesis of bio-based 2,5-furandicarboxylic acid
    Lei ZHAO, Zelin LI, Bolong LI, Shuchang BIAN, Jianhua WANG, Hailan ZHANG, Chen ZHAO
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 160-169.   DOI: 10.3969/j.issn.1000-5641.2023.01.016
    Abstract2098)   HTML96)    PDF (1090KB)(1306)      

    Bio-based 2,5-furandicarboxylic acid (FDCA) is expected to partially replace petroleum-based terephthalic acid (PTA) for the synthesis of high-performance polymer materials. This review article summarizes the latest achievements on the various synthesis routes of FDCA from 5-hydroxymethylfurfural (HMF), furoic acid, furan, diglycolic acid, hexaric acid, 2,5-dimethylfuran, and 2-methylfuran. In particular, the direct oxidation, heterogeneous thermal catalytic oxidation, photoelectric catalytic oxidation of HMF and furoic acid carboxylation, disproportionation, carbonylation, and other routes to synthesize FDCA are reviewed in detail. Based on the comparative analysis of the advantages and disadvantages of each route, the HMF route and the furoic acid route are considered the most promising candidates for the large-scale production of FDCA. Further exploration and future research should be carried out to improve the catalytic production and separation efficiency of FDCA, simplify the reaction process, and reduce production wastes.

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    Prediction of remaining useful life of aeroengines based on the Transformer with multi-feature fusion
    Yilin MA, Huiling TAO, Qiwen DONG, Ye WANG
    Journal of East China Normal University(Natural Science)    2022, 2022 (5): 219-232.   DOI: 10.3969/j.issn.1000-5641.2022.05.018
    Abstract681)   HTML31)    PDF (1754KB)(627)      

    As the core components of aircraft, engines play a vital role during flight. Accurate prediction of the remaining useful life of the aeroengine can help prognostics and health management, thus preventing major accidents and saving maintenance costs. In view of the lack of consideration of different time steps and the relationship between different sensors and operating conditions in existing methods, a remaining useful life prediction method based on the Transformer was proposed, which fuses multi-feature outputs from different encoder layers. This method selects two input data with different time steps, analyzes the relationship between the sensors using permutation entropy, and extracts features independently from the operating condition data. The experimental results on the public aeroengine dataset CMAPSS (Commercial Modular Aero-Propulsion System Simulation) show that the proposed method is superior to other advanced remaining useful life prediction methods.

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    The development and application of a physical-biogeochemical coupling model based on FVCOM
    SHI Shenyang, GE Jianzhong, CHEN Jianzhong, ZHENG Xiaoqin, DING Pingxing
    Journal of East China Normal University(Natural Science)    2020, 2020 (3): 55-67.   DOI: 10.3969/j.issn.1000-5641.201941008
    Abstract704)   HTML162)    PDF (1395KB)(729)      
    By combining the hydrodynamic model FVCOM with the biological model ERSEM, based on FABM, this paper develops a new physical-biogeochemical model: FVCOM-FABM-ERSEM. The combined model is suitable for application to coastal areas and is one of the most comprehensive ecosystem models for the lower trophic levels of the marine food-web. Using the combined model, a one-dimensional vertical (1DV) model and a three-dimensional Changjiang Estuary model were established. The results of the 1DV model were consistent with observation data from the European L4 Station. This paper also simulates the physical and biogeochemical processes of Changjiang Estuary from 2013 to 2016 with the 3D Changjiang Estuary model. The distribution of temperature, salinity, nitrate, phosphate, and chlorophyll-a levels were all found to be consistent with observation data from cruises and MODIS data in the spring when algal blooms occur. The characteristics of the front dynamics of Changjiang Estuary were well represented. The relationship between salinity, turbidity, nutrients, and chlorophyll around the plume front was determined through modeling, indicating a significant co-occurrence effect along the front of physical and biological processes.
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    Survey of early time series classification methods
    Mengchen YANG, Xudong CHEN, Peng CAI, Lyu NI
    Journal of East China Normal University(Natural Science)    2021, 2021 (5): 115-133.   DOI: 10.3969/j.issn.1000-5641.2021.05.011
    Abstract1078)   HTML425)    PDF (1503KB)(1057)      

    With the increasing popularity of sensors, time-series data have attracted significant attention. Early time series classification (ETSC) aims to classify time-series data with the highest level of accuracy and smallest possible size. ETSC, in particular, plays a critical role in fintech. First, this paper summarizes the common classifiers for time-series data and reviews the current research progress on minimum prediction length-based, shapelet-based, and model-based ETSC frameworks. There are pivotal technologies, advantages, and disadvantages of the representative ETSC methods in separate frameworks. Next, we review public time-series datasets in fintech and commonly used performance evaluation criteria. Lastly, we explore future research directions pertinent to ETSC.

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    Study on the mechanism of methylene blue degradation by TiO2 photocatalyst
    ZHANG Dan, XU Bin, ZHU Pei-juan, LIAN Zheng-hao, ZHAO Ya-ping
    Journal of East China Normal University(Natural Sc    2013, 2013 (5): 35-42.  
    Abstract3888)      PDF (2193KB)(4445)      
    In order to carry out the study, the experiments of photodegradation of methylene blue under different conditions were conducted, using different kinds of free radical scavengers, such as (CH3)3OH, H2O2, KI, NaN3 and C6H4O2. The effects of these free radical scavengers were observed. The concentration of H2O2 generated during the photodegradation of methylene blue by TiO2 was also reported. And the results of these experiments indicated that the main active oxygen substances in the reaction are ·OH, O·-2 and 1O2.
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    Application of Cu-based catalysts in the electroreduction of carbon dioxide
    Jing TANG, Zining ZHANG, Xiang ZHENG
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 149-159.   DOI: 10.3969/j.issn.1000-5641.2023.01.015
    Abstract1167)   HTML39)    PDF (1081KB)(732)      

    To achieve the national strategy of carbon neutralization, the electroreduction of carbon dioxide into usable reagents via renewable energy has caused widespread concern in the scientific community. Cu-based electrocatalysts can reduce carbon dioxide to high value-added multi carbon products, but the catalytic mechanism still needs to be studied to improve its selectivity and efficiency. Depending on the state of the Cu, Cu-based catalysts can be divided into Cu alloy/composite catalysts, single-atom, oriented crystalline, and oxidized Cu-based catalysts. This paper introduced the common preparation methods, structural characteristics, effect of electro catalytic reduction of carbon dioxide, and possible catalytic mechanism of the four types of Cu-based catalysts mentioned above.

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    Review of deep learning in cognitive radio
    Bo LIU, Xiaodong BAI, Gengxin ZHANG, Jun SHEN, Jidong XIE, Laiding ZHAO, Tao HONG
    Journal of East China Normal University(Natural Science)    2021, 2021 (1): 36-52.   DOI: 10.3969/j.issn.1000-5641.201922017
    Abstract930)   HTML77)    PDF (1163KB)(647)      

    The development of wireless communication has made spectrum resources increasingly scarce. Existing spectrum resources, however, are not currently used in an efficient way. This contradiction can usually be attributed to the problem created by static spectrum allocation strategies. Cognitive radio (CR) is widely regarded as a feasible solution to solve the problem of static spectrum allocation. In recent years, deep learning, an emerging field of machine learning, has contributed to a number of notable research and application achievements. It has become one of the driving technologies behind artificial intelligence. In this paper, we investigated the application of deep learning to CR; this includes the development of cognitive radio and deep learning as well as the usage of deep learning models in key technologies for CR (such as spectrum prediction, spectrum environment sensing, signal analysis, etc.). Lastly, we summarize and discuss conclusions from this review.

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    Preparation and stability study of lyophilized lentiviral vector
    Hongwei SHEN, Minghao LI, Nan XU, Jiaqi SHAO, Jing WANG, Lei YU
    Journal of East China Normal University(Natural Science)    2021, 2021 (3): 114-127.   DOI: 10.3969/j.issn.1000-5641.2021.03.012
    Abstract965)   HTML57)    PDF (1003KB)(612)      

    In this paper, we studied a new preparation technique for lyophilized lentiviral vectors. We determined the optimal formulation for a freeze-drying protective agent by screening and optimizing potential candidates. The candidates were evaluated on the basis of physical and chemical properties of the freeze-drying process, including appearance, excipient, color, and solubility. The optimal formulation was determined to be trehalose 0.30 g/mL, L-histidine 0.31 mg/mL, L- alanine 0.178 mg/mL, CaCl2 0.020 mg/mL, and MgSO4 0.015 mg/mL. With this technique, the prepared lyophilized lentiviral vector had good appearance, low residual water content, intact structure, and good re-dispersibility. The biological titer of the lentiviral vector reached 9.37 × 107 IU/mL, and the recovery rate of the titer was 50.15%. We also conducted research on potential influencing factors, including a high temperature accelerated experiment and repeated freeze-thaw stability experiments. These experiments showed that the lyophilizing technology can be used for the preparation of lentiviral vector solids and can be effectively used to improve the storage of lentiviral vectors under different temperature conditions, exposure to repeated freeze-thaw cycles, and tolerance to adverse environments (e.g., high temperatures).

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    Anomaly detection algorithm based on improved K-means for electric power data
    WU Rui, ZHANG Anqin, TIAN Xiuxia, ZHANG Ting
    Journal of East China Normal University(Natural Science)    2020, 2020 (4): 79-87.   DOI: 10.3969/j.issn.1000-5641.201921012
    Abstract589)   HTML219)    PDF (836KB)(376)      
    Anomaly detection methods are widely used for applications in the field of electric power, such as equipment fault detection and abnormal electricity consumption detection. The proposed algorithm combines densities of data objects with the maximum neighborhood radius to select data points that are closer to actual cluster centers for the initial selection; this, in turn, improves random selection of the initial cluster centers. In addition, a new anomaly detection method based on an improved K-means algorithm for electric power data is proposed. Experiments show that the algorithm is more suitable in both clustering performance and anomaly detection. When this algorithm is applied to the field of electric power, abnormal data can be effectively detected.
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    Electrocatalytic coupling of CO2 with organic compounds to value-added chemicals
    Huan WANG, Jiaxing LU
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 140-148.   DOI: 10.3969/j.issn.1000-5641.2023.01.014
    Abstract414)   HTML14)    PDF (877KB)(512)      

    The efficient fixation and utilization of CO2 under mild conditions is one of the key components of green carbon science. The electrocatalytic coupling of CO2 and organic compounds can produce value-added chemicals, which is beneficial to sustainable development. In this review, we summarize the current methods of synthesizing carboxylic acids, organic carbonates, carbamates, and other chemicals via electrocatalytic CO2 coupling with organic compounds. We also present the latest research progress and opportunities in this field, such as asymmetric electrocarboxylation to construct chiral molecules, electrochemical ring-opening carboxylation, electrochemical N-methylation, electrocarboxylation with non-sacrificial anodes, and paired electrosynthesis.

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    Research progress on pollution and degradation of plastic waste
    Kaizhen MIAO, Jiaolong MENG, Xuefeng JIANG
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 170-176.   DOI: 10.3969/j.issn.1000-5641.2023.01.017
    Abstract876)   HTML47)    PDF (1177KB)(474)      

    Plastics are widely used in daily life owing to their light weight, portability, and affordability. However, post-consumer-waste plastics do not degrade easily in the natural environment, making plastic pollution a new global environmental issue. Thus, exploration in the field of plastic degradation has increased in recent years. To promote the treatment of plastic waste and provide a scientific reference for environmental protection and sustainable development, this study describes the current state of plastic pollution. It also systematically summarizes various research fields of plastic degradation and presents the development prospect of photocatalysis and bio-based plastics in the future.

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    XUE Peng
    Journal of East China Normal University(Natural Sc    2015, 2015 (S1): 180-184.   DOI: 10.3969/j.issn.1000-5641.2015.z1.029
    Abstract895)      PDF (573KB)(2288)      
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    A preliminary study on phytoplankton composition at Bashayer II marine oil terminal, Red Sea, Sudan
    Osama SAAD S., Amjed AHMED G.
    Journal of East China Normal University(Natural Science)    2020, 2020 (S1): 89-93.   DOI: 10.3969/j.issn.1000-5641.202092209
    Abstract386)   HTML15)    PDF (375KB)(581)      
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    Effects of nutrient management on nutrient utilization of N,P and nitrate accumulation in lettuce
    NIAN Yao-ping, XIA Ti-yuan, HE Ming-zhu,ZHANG Jun-guo, DA Liang-jun
    Journal of East China Normal University(Natural Sc    2011, 2011 (6): 47-56.  
    Abstract2996)      PDF (810KB)(2591)      
    By method of the field plot trial, the experiment was carried out in Dianchi Lake basin to study the influence of different nitrogen and phosphorus fertilizing on lettuce (Lactuca sativa var. ramosa) production, nitrate content and nutrient utilization of N, P. 9 treatments were denoted by T1-T9, respectively. The results showed that: ① The lettuce production of T3(N90P126K180) was higher than other treatments, reaching 28 968.75 kg/ha; except for treatment of T4(N180P126K180)、T5(N270P126K180) and T8(N180P189K180), the contamination levels of nitrate content of the others came out to be Lv.4; after comprehensive consideration on nutrient utilization of N, P, the nutrient utilization of Lettuce showed to be higher after treatments of T4(N180P126K180) and T9(N90P63K180) with 17.42%,2.10% and 20.14%,2.05% respectively. ② Under the same amount of potash fertilizer and the treatment of appropriate nitrogen and phosphorus fertilizers match fertilizing, the corresponding lettuce production, nitrate content and N, P fertilizer nutrient utilization were superior to treatments of partial fertilization or high fertilization. Therefore, control of nitrogen and phosphorus fertilizing, reasonable optimization of ratios of nitrogen and phosphorus will improve the nutrient utilization and vegetables quality, which is of great importance for source controlling the agricultural non-point pollution.
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