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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
    Abstract1409)   HTML77)    PDF (1090KB)(853)      

    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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    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
    Abstract1195)   HTML111)    PDF (1026KB)(1367)      

    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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    Survey of few-shot instance segmentation methods
    Xueming ZHOU, Dingjiang HUANG
    Journal of East China Normal University(Natural Science)    2022, 2022 (5): 136-146.   DOI: 10.3969/j.issn.1000-5641.2022.05.012
    Abstract739)   HTML21)    PDF (968KB)(286)      

    Instance segmentation is an important task in computer vision. In recent years, the development of meta- and few-shot learning has promoted the combination of computer vision learning tasks, which has overcome the bottleneck of detection and classification with regard to objects that are difficult to manually label and those with high labeling costs. Although great progress has been made with few-shot semantic segmentation and object detection, instance segmentation based on few-shot learning has not become a research hotspot until very recently. Beginning with an overview of few-shot instance segmentation, existing approaches are divided into categories of anchor-based and anchor-free algorithms. The architectures and primary technologies behind those approaches are respectively discussed, and common datasets and evaluation indices are described. Additionally, advantages and disadvantages of algorithm performance are analyzed, and future development directions and challenges are presented.

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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
    Abstract718)   HTML28)    PDF (1081KB)(441)      

    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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    Natural products: A bridge between new targets and novel pesticide discovery
    Zhengqi FANG, Shuanhu GAO, Haibing HE
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 21-30.   DOI: 10.3969/j.issn.1000-5641.2023.01.003
    Abstract659)   HTML28)    PDF (3235KB)(356)      

    Pesticides are important tools to control crop diseases and pest hazards, guaranteeing the crop harvest. Natural products and their derivatives are major sources of novel pesticides and play indispensable roles in various fields, such as insecticide, fungicide, plant growth regulation, immune regulation and so on. In recent years, numerous fields of biotechnology have made great progress, like genomics, proteomics and structural biology. And thus, the identification of pesticide targets based on natural products and the creation of novel pesticide molecules based on target structures developed rapidly. The concept, rational design, received more attention in pesticide creation. In this article, the discovery of active natural products based on existed targets or novel targets verifying by natural products were demonstrated by several cases, and the subsequent progress in the development of new pesticides were also discussed. The cases explained the important role of natural products in bridging new targets and novel pesticides.

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    Research progress of microplastics and attached organisms in marine environment
    Daoji LI, Xuri DONG
    Journal of East China Normal University(Natural Science)    2022, 2022 (3): 1-7.   DOI: 10.3969/j.issn.1000-5641.2022.03.001
    Abstract626)   HTML900)    PDF (475KB)(412)      

    In recent years, white pollution caused by waste plastics has attracted widespread attention. Microplastics, which are smaller than 5 mm, are widely distributed in the marine environment. The organisms attached to microplastic surfaces include potential pathogenic bacteria that are harmful to marine life and even human health, as well as plastic-degrading bacteria that can reduce their pollution. Microplastics are difficult to degrade, so they can exist in the aquatic environment for a long time, and the microorganisms attached to their surface can also live stably. In addition, microplastics may pass through the food chain to organisms at higher nutritional levels, and may be eaten by fish and affect fish growth. This paper reviews the distribution of microplastics in the ocean and the potential effects of harmful substances contained or attached to the microplastic surface on organisms. The ecological effects of pathogenic microorganisms attached to the surface of microplastics and plastic decomposition microorganisms, as well as the potential of microplastic transmission to high nutritional levels through the food chain were discussed. The ecological risk of microplastic distribution and surface-attached organisms was analyzed. Furtherly, it is still necessary to understand the impact of plastic waste and microplastics on the marine ecosystem, so as to fully understand the ecological effects of marine microplastics and their attachments, and provide a scientific basis for marine plastic pollution control.

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    Review of zeolite-confined subnanometric cluster catalysts
    Yue MA, Hao XU, Yueming LIU, Kun ZHANG, Peng WU, Mingyuan HE
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 82-94.   DOI: 10.3969/j.issn.1000-5641.2022.00.009
    Abstract542)   HTML26)    PDF (5085KB)(336)      

    The design of efficient and stable supported metal catalysts to prevent metal species from sintering into large nanoparticles under harsh preparation and reaction conditions is key for various important processes, including the conversion of C1 resources and dehydrogenation of low carbon alkanes to C2 and C3 olefins. Zeolites with uniform subnano micropores and various three-dimensional crystalline structures have been proven as ideal supports for preparing highly efficient and stable metal catalysts via encapsulating subnanometric metal clusters within their pores, cages, and channels. Interactions between metal clusters and the zeolite skeleton can regulate their geometric and electronic structure. The development of zeolite-confined subnanometric cluster catalysts aims to take advantage of this joint confinement effect and induce synergy between guest metal species and active sites in host zeolite frameworks. This can further improve the catalytic activity of resultant composite catalysts, for applications in multiple catalytic reaction processes . In this review, typical preparation methods of zeolite-confined subnanometric clusters and their catalytic applications in selective hydrogenation of CO2 and alkynes, hydrogen generation by formic acid decomposition and ammonia borane hydrolysis, and propane dehydrogenation to propene are discussed.

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    3D obstacle-avoidance for a unmanned aerial vehicle based on the improved artificial potential field method
    Lanfeng ZHOU, Mingyue KONG
    Journal of East China Normal University(Natural Science)    2022, 2022 (6): 54-67.   DOI: 10.3969/j.issn.1000-5641.2022.06.007
    Abstract535)   HTML17)    PDF (2858KB)(281)      

    This paper aims to address the challenge of seeking an optimal safe path for a UAV (unmanned aerial vehicle) from an initial position to a target position, while avoiding all obstacles in a three-dimensional environment. An improved APF (artificial potential field) method combined with the regular hexagon guidance method is proposed to solve unreachable and local minimum problems near obstacles as observed with traditional artificial potential field methods. First, we add a distance correction factor to the repulsive potential field function to solve problems associated with unreachable targets. Then, a regular hexagon-guided method is proposed to improve the local minimum problem. This method can judge the environment when the UAV is trapped in a local minimum point or trap area and select the appropriate planning method to guide the UAV to escape from the local minimum area. Then, 3D modeling and simulation were carried out via Matlab, taking into account a variety of scenes involving complex obstacles. The results show that this method has good feasibility and effectiveness in real-time path planning of UAVs. Lastly, we demonstrate the performance of the proposed method in a real environment, and the experimental results show that the proposed method can effectively avoid obstacles and find the optimal path.

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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
    Abstract524)   HTML33)    PDF (1177KB)(293)      

    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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    Research on user behavior portrait and subject mining in the express logistics field during Coronavirus epidemic
    Jiling LI, Baolin LI, Songru YAN
    Journal of East China Normal University(Natural Science)    2022, 2022 (5): 100-114.   DOI: 10.3969/j.issn.1000-5641.2022.05.009
    Abstract493)   HTML17)    PDF (1321KB)(171)      

    Based on logistics-field blog post data from Weibo from November 2019 to May 2022, the user behaviors of express logistics services in the context of the Coronavirus epidemic are profiled. Using grounded theory and abstract clustering methods, five user behaviors and 22 subject contents are abstracted, and the corresponding user profile is generated. This paper further discusses the subject contents, the subject evolution, and the analysis of group differences. The results show that user satisfaction with logistics services was similar, and the dissatisfaction was diversified with obvious escalation. Variables of transportation efficiency and logistics guarantee were the main factors affecting the evaluation, and the development of the epidemic affected the concerns and attitudes of the subject contents, which had obvious group differences at different degrees.

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    Optically mediated entanglement between Bose-Einstein condensates
    Shuai GAO, Matthew PREST, Ebubechukwu O. ILO-OKEKE, Manikandan KONDAPPAN, Juan E. ARISTIZABAL-ZULUAGA, Valentin IVANNIKOV, Tim BYRNES
    Journal of East China Normal University(Natural Science)    2022, 2022 (2): 93-105.   DOI: 10.3969/j.issn.1000-5641.2022.02.011
    Abstract489)   HTML46)    PDF (1315KB)(187)      

    This paper explores a method for generating optically mediated entanglement between Bose-Einstein condensates (BECs). Using a quantum nondemolition Hamiltonian with BECs placed in a Mach-Zehnder configuration, it is shown that entangled states can be induced by performing measurement on light. In particular, the effects of the entangled state in the presence of decoherence were analyzed. The behavior of the entangled state was found to be sensitive to the atom-light interaction time. The entangled state is relatively stable when the dimensionless interaction time $ \tau \lesssim \frac{1}{\sqrt{N}} $ and relatively fragile when the time is greater.

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    Research on diagnosis of leukemia by flow detection based on quantum dot coded microspheres
    Junfei YANG, Yeying WANG, Jing’e ZHOU, Jing WANG, Zhiqiang YAN, Lei YU
    Journal of East China Normal University(Natural Science)    2022, 2022 (6): 139-149.   DOI: 10.3969/j.issn.1000-5641.2022.06.014
    Abstract472)   HTML5)    PDF (2251KB)(121)      

    In this work, micro-scale porous carboxyl polystyrene microspheres (PS) were prepared using seed polymerization. Quantum dots (QDs) were used as fluorescent molecules to synthesize QDs with different emission wavelengths and successfully loaded into porous microspheres to form fluorescent coding microspheres (QDs@PS). Subsequently, serum samples of patients with acute leukemia (AL) were detected, and the antigen in the serum was quantitatively analyzed using flow cytometry. Scanning electron microscope (SEM) and flow cytometry images showed that the microspheres were regular and uniform in size. Fluorescence microscopy showed that the QDs permeated uniformly into the whole microsphere. In addition, QDs@PS showed good fluorescence stability, no QD leakage was observed, and the QDs@PS maintained its fluorescence for a period of at least two weeks. The use of fluorescence spectroscopic analysis for the detection of human immunoglobulin G (IgG) showed that the carboxyl groups on the surface of fluorescent microspheres are beneficial for the efficient covalent binding of biological macromolecules, which can be used for sandwich immunosandwich reaction coupling with leukemic high expression antigen interleukin 6 (IL-6). Combined with serum samples from leukemia patients, the fluorescence of QDs was detected by flow cytometry, and the mean fluorescence intensity (MFI) was calculated to determine the content of IL-6 in the serum. These results indicate that the designed optically-encoded microcarrier can be successfully applied to high-throughput and multichannel biomolecular analysis and has great potential in blood disease detection and diagnosis.

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    Progress in synthesis of methyl glyoxylate by selective oxidation of methyl glycolate with molecular oxygen
    Hao WANG, Guofeng ZHAO, Yong LU
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 104-113.   DOI: 10.3969/j.issn.1000-5641.2023.01.011
    Abstract466)   HTML7)    PDF (834KB)(271)      

    Methyl glyoxylate is widely used in organic synthesis and chemical production. The application of traditional preparation methods is limited by high cost, low efficiency, and significant environmental pollution. During the coal to ethylene glycol process, methyl glycolate is produced as an intermediate product of the hydrogenation of dimethyl oxalate (DMO) to ethylene glycol. Methyl glycolate can be selectively obtained from DMO via hydrogenation, and therefore, has the potential to serve as raw material for methyl glyoxylate. However, only few studies have considered this process. Herein , the applications, traditional preparation methods, and state-of-the-art research progress of methyl glycolate oxidation are reviewed. Recent research on selective oxidation of related alcohols (such as ethanol) to aldehydes and ketones is also summarized.

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    Modeling and simulation technology of roads for a battlefield environment
    Shucheng LU, Yan GAO, Changbo WANG
    Journal of East China Normal University(Natural Science)    2022, 2022 (4): 79-94.   DOI: 10.3969/j.issn.1000-5641.2022.04.008
    Abstract447)      PDF (3909KB)(160)      

    Battlefield environments are combat spaces that contain geographic elements such as terrain and roads. Road modeling and simulation is an important part of battlefield simulation and plays a key role in complex combat decision-making. Traditional road modeling is unable to handle the complex terrain conditions present in the field; hence, this paper proposes road modeling and simulation method for field environments. In particular, in order to support road modeling and simulation of complex terrain environments, road construction designs oriented to typical battlefield environments are proposed. This method divides the road network into different sub-models according to their characteristics and models them separately, improving the demand for realism in battlefield simulation. Then, the proposed method uses OpenStreetMap geographic information data to drive road network construction. The model offers real-time, high accuracy road information content and complete classification that can meet the needs of military operations and modeling simulations for typical battlefield environments. Secondly, using terrain elevation data, road construction rules, and other auxiliary information, the road height is adjusted to adapt to the complex terrain conditions of the battlefield and possible multi-level road network structures. Lastly, the introduction of a $ {G}^{2} $ continuous Hermite interpolation spline can flexibly represent the center line of the road and improves the reusability of the road model through grid deformation. Experiments show that the proposed simulation method can more reliably restore the real details of a road network to effectively fit complex terrain and improve the reusability of road models. Finally, it provides a feasible analysis angle and modeling method for researching geographic elements in battlefield environments.

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    Electrodeposition performance of a copper-based catalyst for the electroreduction of CO2
    Meng’en CHU, Chunjun CHEN, Haihong WU, Mingyuan HE, Buxing HAN
    Journal of East China Normal University(Natural Science)    2023, 2023 (1): 129-139.   DOI: 10.3969/j.issn.1000-5641.2023.01.013
    Abstract434)   HTML16)    PDF (4857KB)(281)      

    To improve the catalytic performance of copper-based catalysts in the electroreduction of CO2, nitrotriacetic acid (NTA) was used as an additive to prepare copper-based catalysts having a three-dimensional structure by applying electrodeposition. The prepared catalysts exhibited excellent selectivity and activity for the electroreduction of CO2 to multi-carbon (C2+) products. At –1.26 V vs. RHE, the faradaic efficiency of C2H4 and C2+ products over the Cu-0.5/CP electrode reached 44.0% and 61.6%, respectively, and the total current density reached 12.3 mA·cm–2. In addition, Pd- and Zn-based catalysts were prepared by employing electrodeposition; the results showed that their selectivity for CO was significantly improved, proving that NTA has a certain universality in the preparation of electrocatalysts by using electrodeposition.

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    Assembly optimization of an AES-128-CTR algorithm based on a Cortex-M4 core
    Dongxuan YANG, Ganggang ZHANG, Xinliang LIU
    Journal of East China Normal University(Natural Science)    2022, 2022 (4): 67-78.   DOI: 10.3969/j.issn.1000-5641.2022.04.007
    Abstract420)   HTML35)    PDF (920KB)(178)      

    With the rapid development of the Internet of Things, embedded hardware products face great challenges in data security. The AES (Advanced Encryption Standard) algorithm has the advantages of strong attack resistance, fast operation speed and flexible block length in the field of data encryption and decryption. The speed of this algorithm on microcontroller platforms is far inferior to general-purpose CPUs (Central Processing Units) which have an extended instruction set for AES encryption. To solve this problem, a speed optimized AES algorithm in CTR (Counter) mode based on the Cortex-M4 core instruction set is implemented using assembly language. The kernel’s unique barrel shifter and three-stage pipeline are used to optimize the round transformation of the algorithm, and the number of instruction cycles is reduced. Testing on an FRDM-K82F development board shows that the assembly optimization of the algorithm is substantially more efficient than the code implemented using the C language, and it offers more advantages in both cost and power consumption compared to hardware encryption based on the coprocessor.

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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
    Abstract410)   HTML21)    PDF (1754KB)(393)      

    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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    Trends, challenges, and mitigation strategies for the use of sand and gravel resources in China
    Shurong ZHUANG, Aurora TORRES, Ruishan CHEN, Chao YE
    Journal of East China Normal University(Natural Science)    2022, 2022 (3): 137-147.   DOI: 10.3969/j.issn.1000-5641.2022.03.014
    Abstract408)   HTML79)    PDF (1177KB)(166)      

    Sand, gravel, and crushed rock—together referred to as construction aggregates—are the world’s most extracted solid materials by mass. China’s annual consumption of construction aggregates reached over 20 billion tons in 2018, accounting for nearly half of global consumption. This article provides an overview of the use of sand and gravel in China, including current supply and demand conflicts and the impacts of mining, transportation, and use. We highlight that: ① the national demand for sand and gravel has continued to grow in the last two decades; crushed rock has become the main source of construction aggregates, whereas the supply of river sand has significantly declined; and ② there are significant environmental, economic, and social challenges associated with sand and gravel mining, transportation, and use, including the emergence of illicit supply networks. We then discuss opportunities to ensure sand and gravel supply, minimize mining impacts, and promote sustainable trajectories for the Chinese aggregates industry. First, the quantification of the material flows and stocks of construction aggregates that includes geological and anthropogenic stocks is crucial to identify supply bottlenecks and ensure more efficient use of resources. This requires establishing a reliable data monitoring system. Second, the government should increase investment and establish relevant institutions to optimize supply systems and minimize their impacts, strengthen the regulatory framework, promote the uptake of alternative materials, and establish standards and implement best practices in the aggregates industry. Finally, interdisciplinary integrated research is needed to analyze the existing challenges associated with the supply of sand and gravel resources as well as the potential and risks of adaptation strategies.

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    Personalized course recommendations based on a learner’s knowledge and personality
    Qimin BAN, Wen WU, Wenxin HU, Hui LIN, Wei ZHENG, Liang HE
    Journal of East China Normal University(Natural Science)    2022, 2022 (6): 87-101.   DOI: 10.3969/j.issn.1000-5641.2022.06.010
    Abstract400)   HTML7)    PDF (1363KB)(145)      

    Adaptive learning is an educational method that uses computer algorithms to coordinate interaction with learners, and provides customized learning resources and learning activities to address the unique needs of each learner. With the impact of COVID-19, adaptive learning has become increasingly important. One of the challenges with adaptive learning is how to provide personalized learning resources for learners—i.e., how to generate personalized recommendation for learners from a large set of learning resources. Existing methodologies mainly generate recommendations based on a learner’s knowledge level; however, this approach has some limitations. Firstly, when assessing a learner’s knowledge level, learners’ forgetting phenomenon has to date not been well modeled. Secondly, recommendations are generated separately from knowledge tracing tasks, ignoring the interconnectedness between these aspects. In addition, learners’ preferences for the type of learning resources and learning strategies is normally ignored if the knowledge level alone is used. To solve the aforementioned problems, this paper proposes a knowledge and personality incorporated multi-task learning framework (KPM) to boost course recommendations (i.e., the above-mentioned learning resources); the proposed method regards an enhanced knowledge tracing task (EKTT) as an auxiliary task to assist the primary course recommendation task (CRT). Specifically, using EKTT, we design a personalized forgetting controller to enhance the deep knowledge tracing model for accurately assessing a learner’s knowledge level. With CRT, we combine the learner’s knowledge level and sequential behavior with their personality adapted to the specific context to obtain learner’s profile; this data is subsequently used to generate a course recommendation list. Experimental results on real-world educational datasets demonstrate the superiority of our proposed method in terms of hit ratio (HR), normalized discounted cumulative gain (NDCG), and precision, indicating that our method can generate more personalized recommendations.

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    Infinite dimensional 3-Pre-Lie algebras
    Ruipu BAI, Shan LIU
    Journal of East China Normal University(Natural Science)    2022, 2022 (2): 1-8.   DOI: 10.3969/j.issn.1000-5641.2022.02.001
    Abstract382)   HTML298)    PDF (625KB)(235)      

    Constructing 3-Pre-Lie algebras has always been a difficult problem; until now, there have been very few examples of 3-Pre-Lie algebras. In this paper, we use homogenous Rota-Baxter operators of weight zero on the infinite dimensional 3-Lie algebra $A_{\omega}=\langle L_m | m\in {\mathbb{Z}}\rangle$ to construct 3-Pre-Lie algebras $B_k,~0\leqslant k\leqslant 4$ , and we subsequently discuss the structure. It is shown that $B_2$ and $B_4$ are non-isomorphic simple 3-Pre-Lie algebras, $B_1$ is an indecomposable 3-Pre-Lie algebra with infinitely many one-dimensional ideals, and $B_3$ is an indecomposable 3-Pre-Lie algebra with finitely many ideals.

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