學術文獻：研究前沿/研究熱點

　　研究前沿為研究領域內最新文獻⛳️；

　　研究熱點為研究領域內高被引文獻；

　　每期會選擇一類文獻進行推送，本期為“研究前沿”。

　　1.Heavymetal pollution risk of desulfurized steel slag as a soil amendment in cyclinguse of solid wastes

　　Abstracts：Theby-product of wet flue gas desulfurization, desulfurized steel slag (DS), hadchemical characteristics like natural gypsum that can be used to improvesaline-sodic soil. However, contamination risk of heavy metals for cyclingutilization of DS in agriculture was concerned mostly. Both pot and fieldexperiments were conducted for evaluating the potential pollution risk of DS asthe amendment of saline-sodic soil. Results showed that application of DSdecreased the contents of Cd, Cu, Zn, and Pb, while significantly increasingchromium (Cr) content in DS-amended soils. The field experiment demonstratedthat the migration of heavy metals (Cd, Zn, Cu, and Pb) in the soil profile wasnegligible. The application of DS at the dosage of 22.5-225 tons/hasignificantly increased the Cr content in alfalfa (Medicago sativa L.) butlower than the national standard for feed in China (GB 13078-2017). DS alteredthe chemical fraction of heavy metals (Zn, Cu, and Pb), transferredexchangeable, reducible into oxidizable and residual forms in DS-amended soil.Application of DS combined with fulvic acid (FA) could effectively reduce themovement of heavy metals in soil and the accumulation of Cr in alfalfa. Basedon our results, DS was a safe and feasible material for agricultural use andpresented relatively little pollution risk of heavy metals. However, theresults also showed that DS to a certain extent had a potential environmentalrisk of Cr if larger dosages of DS were used.

　　2.Efficient adsorption and reduction of Cr(VI) by a novel polyaniline modifiedmagnetic iron-based waterworks sludge from aqueous solution

　　Abstracts👩🏼‍🦳：As amajor solid waste from the waterworks, the iron-based waterworks sludge (IBWS)was currently disposed of in landfills or discharged into water body, causingland consumption and environment contamination. This work investigated a novelreclamation of IBWS to create a composite for aqueous Cr(VI) adsorption andreduction. IBWS was magnetized by calcination and further modified withpolyaniline (PANI) to get PANI@MIBWS for enhanced adsorbent separation andCr(VI) removal. After being characterized using advanced techniques, thecomposite was employed in aqueous Cr(VI) removal studies. PANI@MIBWS removedCr(VI) in a pH-dependent manner, with the highest Cr(VI) removal at pH 2. Thespontaneous and endothermic Cr(VI) elimination process by the composite wasbest explained by pseudo-second-order and Langmuir models. In the sequence ofCl-< SO42-of IBWS, but also useful information for Cr(VI)-bearing wastewatertreatment.

　　3.Fabrication of anovel composite gel bead to reclaim methyl orange from a binary dye mixture: Anactive role of adsolubilization phenomenon

　　Abstracts：Thepresent work demonstrates a novel protocol in accordance with the reduce,reuse, and recycle principle of waste management rules for dye wastewatertreatment as well as selective extraction of desired dye. Here two model dyesviz., methyl orange (MO) (an anionic dye) and methylene blue (MB) (a cationicdye) have been considered as the components of dye wastewater, andalginate-xanthan (Alg-Xan) biopolymer composite hydrogel beads modified with acationic surfactant such as cetylpyridinium chloride (CPC), as the sorbentma-terial. CPC bilayers on Alg-Xan composite surface showed excellent MO uptakeperformance (>85-90%) via adsolubilization when the MO is present alone orin a binary mixture with MB. On the other hand, MB got partially transferred(-30-50%) to the solid surface through diffusion phenomenon both in thepresence (-50%) and absence (-30%) of MO. After the accumulation of the dyemolecules, MO can be easily reclaimed (>90%) using 1-butanol as theextracting solvent; however, no detachment of MB from the solid surface takesplace. The stability and suitability of the hydrogel beads were investigatedunder different operating conditions. Further-more, Alg-Xan-CPC composite beadshave been characterized using FTIR, SEM analysis, and particle sizedis-tribution. The newly developed Alg-Xan-CPC composite beads show goodreusability up to four cycles and they perform well in real wastewater (-95%recovery of MO). The novelty of the current research includes the synthesis ofa CPC micelle anchored biopolymer adsorbent, which is capable of attractingboth the cationic and anionic dyes from water bodies, followed by extractivereclamation of the anionic dye only. The application of biopolymers forwastewater treatment and resource recovery from the waste stream is undoubtedlya sustainable environmental remediation option. Hence, this research work isexpected to present a novel application of biopolymers for dye wastewatermitigation as well as reclamation of desired useful dye.

　　1.A review ofelectrical and thermal conductivities of epoxy resin systems reinforced withcarbonnanotubesand graphene-based nanoparticles

　　Abstracts：Epoxy(EP) resins exhibit desirable mechanical and thermal properties, low shrinkageduring cuing, and high chemical resistance. Therefore, they are useful forvarious applications, such as coatings, adhesives, paints, etc. On the otherhand, carbon nanotubes (CNT), graphene (Gr), and theirderivatives have become reinforcements of choice for EP-based nanocompositesbecause of their extraordinary mechanical, thermal, and electrical properties.Herein, we provide an overview of the last decade???s advances in research onimproving the thermal and electrical conductivities of EP resin systemsmodified with CNT, Gr, their derivatives, and hybrids. We further report on thesurface modification of these reinforcements as a means to improve thenanofiller dispersion in the EP resins, thereby enhancing the thermal andelectrical conductivities of the resulting nanocomposites.

　　2.2Dmaterials and heterostructures for photocatalytic water-splitting: atheoretical perspective

　　Abstracts：Photocatalyticwater-splitting for hydrogen generation by sunlight provides a new route toaddress energy and environmental problems. In recent years, tremendous effortshave been devoted to designing highly efficient water-splitting photocatalysts(PCs). Adequate light absorption, effective photogenerated carrier separation,and sufficiently large overpotentials for water redox are crucial in achievinghigh solar-to-hydrogen (STH) efficiency. These parameters thus stronglyinfluence the design of novel photocatalytic materials. Two-dimensional (2D)PCs have flourished because of their large specific surface area ratio, shortcarrier migration distance compared to bulk PCs, enormous design flexibility viavan der Waals heterostructure (HS) engineering and many other uniquecapabilities that meet the criteria for high-efficiency STH conversion. In thisreview, we summarize the recent developments of 2D materials and HSs forwater-splitting applications from a theoretical perspective. Specifically, wefirst discuss a number of 2D materials and HSs employed for water-splitting. Wereview various strategies of material design to modulate and enhance thephotocatalytic performance via improving light harvesting and carrierseparation, such as the introduction of defects and dopants, and theapplication of strain, external electric field, rotation angles andferroelectric switching. We then discuss the methods to evaluate hydrogenevolution reaction, oxygen evolution reaction and STH efficiency. Finally, theopportunities and challenges of designing 2D materials and HSs forwater-splitting are presented.

　　3.Greensynthesis of DyBa2Fe3O7.988/DyFeO3 nanocomposites using almond extract withdual eco-friendly applications: Photocatalytic and antibacterial activities

　　Abstracts🦁：For thefirst time, photocatalytical and antibacterial activities ofDyBa2Fe3O7.988/DyFeO3 (Dy-Ba-Fe-O) nanocomposites as eco-friendly applicationsof this compound was studied in the same time. Since the applications of thiscompound are eco-friendly, ultrasound technique was chosen as the synthesismethod. Achieving the pure product with good crystallinity with the lowestenergy consumption can be considered as one of the advantages of this work.Using the almond core extract as a natural reagent was another reason forconsideration this method as a green process. Band gap of this nanocompositewas estimated about 2.6 eV that showed this product can be used as avisible-active photo catalyst. Rhodamin-B dye as an organic pollutant modelusing the as-prepared nano composite was degraded about 72% that was aconsiderable result under visible irradiation. Elimination of microorganismswas studied by disc diffusion to recognize the sensitivity of bacterial(Staphylococcus aureus, Bacillus subtilis, E. coli, K. pneumonia and P.aeruginosa) strains the manufactured. The results confirmed thatDyBa2Fe3O7.988/DyFeO3 (DBFeO) nanocomposites can be used as an antibacterialagent because of the manifested strong antibacterial ability upon Gram-negativepathogens such as K. pneumonia and E. coli. The properties of this product werecharacterized by different analyses including SEM, XRD, EDS, FT-IR, DRS andTEM. (c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. Allrights reserved.

　　4.PolycrystallineSnSe with a thermoelectric figure of merit greater than the single crystal

　　Abstracts🪞：Thermoelectricmaterials generate electric energy from waste heat, with conversion efficiencygoverned by the dimensionless figure of merit, ZT. Single-crystal tin selenide(SnSe) was discovered to exhibit a high ZT of roughly 2.2-2.6 at 913 K, butmore practical and deployable polycrystal versions of the same compound sufferfrom much poorer overall ZT, thereby thwarting prospects for cost-effectivelead-free thermoelectrics. The poor polycrystal bulk performance is attributedto traces of tin oxides covering the surface of SnSe powders, which increasesthermal conductivity, reduces electrical conductivity and thereby reduces ZT.Here, we report that hole-doped SnSe polycrystalline samples with reagentscarefully purified and tin oxides removed exhibit an ZT of roughly 3.1 at 783K. Its lattice thermal conductivity is ultralow at roughly 0.07 W m(-1) K-1 at783 K, lower than the single crystals. The path to ultrahigh thermoelectricperformance in polycrystalline samples is the proper removal of the deleteriousthermally conductive oxides from the surface of SnSe grains. These resultscould open an era of high-performance practical thermoelectrics from thishigh-performance material.

　　SnSehas a very high thermoelectric figure of merit ZT, but uncommonlypolycrystalline samples have higher lattice thermal conductivity than singlecrystals. Here, by controlling Sn reagent purity and removing SnOx impurities,a lower thermal conductivity is achieved, enabling ZT of 3.1 at 783 K.

　　1.Asurvey on vision guided robotic systems with intelligentcontrol strategies for autonomous tasks

　　Abstracts🌶：TheVision Guided Robotic systems (VGR) is an essential aspect of modernintelligent robotics. The VGR is rapidly transforming manufacturing processesby enabling robots to be highly adaptable and intelligent reducing the cost andcomplexity. For any sensor-based intelligent robots, vision-based planning isconsidered as one of the most prominent steps followed by controlled actionsusing visual feedback. To develop robust vision-based autonomous systems inrobotic applications, path-planning and localization can be implemented alongwith Visual Servoing (VS) for robust feedback control. In the availableliterature, most of the reviews are focused on a particular module ofautonomous systems like path planning, motion planning strategies, or VisualServoing techniques. In this paper overall review of different modules invision-guided robotic systems is presented. So, this review providesresearchers with broader in-depth knowledge about different modules that existin the vision-guided autonomous system. The review also includes differentvision sensors that are commonly used in industries covering theircharacteristics and applications. In this work, overall, 227 research papers inpath planning and vision-based control algorithms are reviewed with recentintelligent techniques based on optimization and learning-based approaches. Thegraphical analysis illustrating the advancements of research in the field ofvision-based robotics using Artificial Intelligence (AI) is also discussed.Lastly, this paper concludes by discussing some of the research gaps,challenges, and future directions existing in vision-based planning andcontrol.

　　2.Ahierarchical intelligent control strategy for greenhouse gasreduction in wastewater treatment process of paper mill

　　Abstracts：Due tothe huge amounts of wastewater discharge and the high pollution loads inpapermaking industry, many greenhouse gases (GHG) are emitted in thepapermaking wastewater treatment process. The wastewater dis-solved oxygen (DO)control has been considered as the most cost-effective control solution for GHGreduction in wastewater treatment plants (WWTP). However, the competitionbetween contaminant removal efficiency and GHG reduction hinders the drasticreduction of GHG emissions from WWTP. In this study, based on the estab-lishedintegrated GHG emission model, explicitly considering the total GHG reductiontargets on the premise of effluent compliance, an intelligent control schemehas been developed for an activated sludge process in a paper mill. RegardingDO as the controlled variable, the proposed hierarchical optimalproportional-integral (HOPI) control scheme was established consisting of threelayers: 1) Layer 1 for the effluent quality estimation, 2) Layer 2 for theoptimal DO set point determined by genetic algorithm with the influentvariations to obey discharging norms and reduce GHG emissions, 3) Layer 3 forthe DO tracking proportional integral (PI) control with the controllerparameters adjusted by the back propagation neural network to track thedynamically optimized DO set points. The simulation results showed that,compared with the open-loop (OL) operation (averaged aeration, 10/h), theproposed HOPI control (averaged aeration, 7.9/h) reduced the GHG emissions by12.54% under the premise of discharging norms, which was mainly attributed tothe reduction of the aeration electricity con-sumption. In contrast, the PIcontrol (averaged aeration, 12.9/h) increased the GHG emissions by 7.48%compared with the OL operation. Thus, the proposed HOPI control strategy hasdemonstrated potential for the application of GHG reduction in industrial WWTPs.

　　3.Intelligentcontrol of nanoparticle synthesis on microfluidic chips with machine learning

　　Abstracts🥽：Nanoparticlesplay irreplaceable roles in optoelectronic sensing, medical therapy, materialscience, and chemistry due to their unique properties. There are many syntheticpathways used for the preparation of nanoparticles, and different syntheticpathways can produce nanoparticles with different properties. Therefore, it iscrucial to control the properties of nanoparticles precisely to impart thedesired functions. In general, the properties of nanoparticles are influencedby their sizes and morphologies. Current technology for the preparation ofnanoparticles on microfluidic chips requires repeated experimental debuggingand significant resources to synthesize nanoparticles with precisely thedesired properties. Machine learning-assisted synthesis of nanoparticles is asensible choice for addressing this challenge. In this paper, we review manyrecent studies on syntheses of nanoparticles assisted by machine learning.Moreover, we describe the working steps of machine learning, the main algorithms,and the main ways to obtain datasets. Finally, we discuss the current problemsof this research and provide an outlook.

　　1.State-of-the-artapplications of machine learning in the life cycle of solid wastemanagement

　　Abstracts：Due tothe superiority of machine learning (ML) data processing, it is widely used inresearch of solid waste (SW). This study analyzed the research anddevelopmental progress of the applications of ML in the life cycle of SW.Statistical analyses were undertaken on the literature published between 1985and 2021 in the Science Citation Index Expanded and Social Sciences CitationIndex to provide an overview of the progress. Based on the articles considered,a rapid upward trend from 1985 to 2021 was found and international cooperativeswere found to have strengthened. The three topics of ML, namely, SW categories,ML algorithms, and specific applications, as applied to the life cycle of SWwere discussed. ML has been applied during the entire SW process, therebyaffecting its life cycle. ML was used to predict the generation andcharacteristics of SW, optimize its collection and transportation, and modelthe processing of its energy utilization. Finally, the current challenges ofapplying ML to SW and future perspectives were discussed. The goal is toachieve high economic and environmental benefits and carbon reduction duringthe life cycle of SW. ML plays an important role in the modernization andintellectualization of SW management. It is hoped that this work would behelpful to provide a constructive overview towards the state-of-the-artdevelopment of SW disposal.

　　2.Asurvey on machine learning for recurring concept drifting datastreams

　　Abstracts：Theproblem of concept drift has gained a lot of attention in recent years. Thisaspect is key in many domains exhibiting non-stationary as well as cyclicpatterns and structural breaks affecting their generative processes. In thissurvey, we review the relevant literature to deal with regime changes in thebehaviour of continuous data streams. The study starts with a generalintroduction to the field of data stream learning, describing recent works onpassive or active mechanisms to adapt or detect concept drifts, frequentchallenges in this area, and related performance metrics. Then, differentsupervised and non-supervised approaches such as online ensembles,meta-learning and model-based clustering that can be used to deal withseasonalities in a data stream are covered. The aim is to point out newresearch trends and give future research directions on the usage of machinelearning techniques for data streams which can help in the event of shifts andrecurrences in continuous learning scenarios in near real-time.

　　3.Identificationand classification of coronavirus genomic signals based on linear predictivecoding and machine learning methods

　　Abstracts：Coronadisease has become one of the problems and challenges of humankind over thepast two years. One of the problems that existed from the first days of thisepidemic was clinical symptoms similar to other infectious vi-ruses such ascolds and influenza. Therefore, diagnosis of this disease and its coping andtreatment approaches is also been difficult. In this study, Attempts has beenmade to investigate the origin of this disease and the genetic structure of thevirus leading to it. For this purpose, signal processing and linear predictivecoding approaches were used which are widely used in data compression. Apattern recognition model was presented for the detection and separation ofcovid samples from the influenza virus case studies. This model, which wasbased on support vector machine classifier, was tested successfully on severaldatasets collected from different countries. The obtained results performed onall datasets by more than 98% accuracy. The proposed model, in addition to itsgood performance accuracy, can be a step forward in quantifying and digitizingmedical big data information.

　　Keywords💁🏼‍♀️：Linearpredictive codingCoronaDNA SequenceSupportvector machineSignalprocessingMachinelearning

　　1.Theimpact of internet penetration on venture capital investments: Evidence from aquasi-natu

　　Abstracts：Thisstudy investigates the relationship between interne ral experimentt penetrationand venture capital (VC) investment in China. Exploiting staggered inclusion indemonstration cities under the Broadband China strategy as a positive shock tointernet penetration, our difference-in-differences analysis shows that thispolicy shock results in an increase in VC investments in demonstration citiesrelative to others. Moreover, the increase in VC investments is concentrated inearly stage financing and young start-ups. In terms of VC fundsources, we find a stronger effect on foreign and independent VCs. Ourmechanism analysis suggests that the effect of the broadband rollout is mainlydriven by cities with higher ex-ante costs of information acquisition and thatsuch costs are reduced by the improvement of internet-based networkinfrastructure. Finally, we provide additional evidence on the benefits toestablished companies by showing that broadband rollout improves the informationenvironment of listed firms. Our study sheds new light on the economicconsequences of infrastructure development that reduces information acquisitioncosts in China.

　　2.TheBurden of Cold Agglutinin Disease on Patients' Daily Life: Web-BasedCross-sectional Survey of 50 American Patients

　　Abstracts：Background:Cold agglutinin disease (CAD) is a rare disorder, affecting 15% of patientswith autoimmune hemolytic anemia. Few studies have assessed CAD symptoms andtheir impact on daily life, but these studies did not address the patients'perspectives.

　　Objective:The aims of this study were to increase the knowledge about CAD through apatient-centric survey and to gain a better understanding of the burden of thisdisease. Methods: We conducted an internet-based survey in September2020 among American patients registered on the CAD Unraveled website andmembers of the Cold Agglutinin Disease Foundation.

　　Results:A total of 50 respondents were included in this study. Totally, 90% (45/50) ofthe patients reported having experienced fatigue. Fatigue was mainly reportedon a daily basis, and approximately one-third of these patients (13/45, 29%)said that their fatigue was constant throughout the day. It has also been shownthat CAD has a great impact on patients' physical well-being, emotionalwell-being, social life, and household finances. The disease varies over time,with or without symptoms. A total of 88% (44/50) of the patients reported previousepisodes of the increased intensity or sensitivity of their CAD symptoms, witha mean of 4.5 (SD 5.4) episodes reported during the past year. More than halfof the patients (27/50, 54%) considered their disease to be moderate or severe,and 42% (21/50) of the study group reported that their symptoms had worsenedsince the time of diagnosis.

　　Conclusions:Our study has provided new data on CAD symptoms, particularly data on theimportance and type of fatigue and the fluctuation of CAD symptoms.

　　3.Paralyzed by shock: the portfolio formation behavior of peer-to-businesslending investors

　　Abstracts👩🏽‍🔧：Weexamine investor behavior on a leading peer-to-business lending platform andidentify an investment mistake that we refer to as default shock bias. First,we find that investors stop investing in new loans and cease diversifying theirportfolio after experiencing a loan default. The default shock significantlyworsens the risk-return profile of investors' loan portfolios. The defaultsinvestors experience are often not beyond what would have been expected fromthe information that was provided by the platform ex ante. Second, investmentexperience on the platform is related to better investment decisions ingeneral, but it does not reduce the default shock bias. These findings haveimportant implications not only for the behavioral finance literature but alsomore generally for new forms of Internet-based finance.

　　1. 基於“少數派報告”的協同過濾模型

　　摘要🥵：協同過濾是在線推薦系統最重要的組成模塊之一🌅🦸🏽，為實現面向用戶的個性化廣告投放功能提供了關鍵的技術支持。然而🤙🏿，在協同過濾系統的具體實現中🧎🏻‍♀️，研究者卻不加區分的對所有目標用戶都使用相同的訓練流程。較之“個性化的預測結果”的預期🤛🏿🕧，上述“一般化的訓練過程”使得結果模型相對於待預測的目標過於普適🪘，缺乏必要的針對性。本文提出一個“以個性化的訓練過程得到個性化的預測結果”的協同過濾預測模型（MORE）：對給定的目標用戶🍴，MORE將使用彈性網絡模型（ElasticNet），從現有的用戶全集中選出若幹用戶構成與之對應的“專家”集合，並基於目標用戶與專家已有的評分🙍，生成對目標用戶的缺失評分的預測。本文報告了MORE在不同的協同過濾預測模型上的應用結果，在真實評分數據集上的實驗結果表明，較之使用全量數據訓練得到的預測模型，基於MORE的模型有更好的表現。 

　　2.  人員流動與城市間商品價格差異:來自高鐵開通的證據

　　摘要👨🏻‍🚒：本文以中國高鐵開通這一自然實驗，采用2001-2016年172個地級市的微觀商品價格數據，運用倍差法研究人員流動對城市間商品價格差異的影響。研究表明，高鐵開通帶來的人員流動，能通過促進要素市場一體化和地區間商務往來📋，顯著降低城市間商品價格差異，由此促進地區間產品市場的一體化🧚🏻。通過更換多個代理變量、控製時間趨勢、使用基於隨機模擬方法的安慰劑檢驗和事件分析法等多種方法進行穩健性檢驗，並分別構建了基於最低成本原則和最短距離原則的最小生成樹作為兩個工具變量來處理內生性問題後，研究結論依然成立🌘。進一步研究表明🧑‍🦰，高鐵開通能推動區域內、區域間以及不同行政級別城市間的經濟一體化；高鐵站的合理選址與高鐵線路的合理設計對充分發揮高鐵開通的作用有重要影響🦏。

　　3.  建設有中國特色的比較教育學：動因、邏輯與路徑轉向

　　摘要：建設有中國特色的比較教育學是中國比較教育工作者現在及未來所要承載的重要任務和使命。比較教育學科自身的文化屬性、現代化社會的發展需求、中國特色社會主義理論的提出與發展以及中國比較教育學者危機心理的產生😄，共同構成了中國特色比較教育學科建設的動因。要進一步推動中國特色比較教育學科建設☝🏻，一方面要在學科生成邏輯上理清其內在的哲學邏輯、文化邏輯👩🏻‍🦯‍➡️、實踐邏輯以及價值邏輯，另一方面則要在縱向時間序列上明晰中國特色比較教育學科建設的路徑轉向，以便更好地推動中國比較教育學的高質量發展。 

　　4.  高校VR英語課堂構建——評《基於虛擬現實的計算機輔助語言教學研究》

　　摘要🎽：當今科技領域最火的概念,無疑就是“元宇宙”,其概念最早出自1992年的美國科幻小說《雪崩》,2018年著名導演斯皮爾伯格的《頭號玩家》生動展示了元宇宙的一種可能形態。元宇宙是一個“去意昂2化”的,具有超強沉浸感的大型虛擬世界,是一種操作系統級別的存在。所有接入元宇宙的應用程序都必須遵循一套相同的底層協議,在元宇宙中所有數據都是真實的,包括個人的經濟👵🏿、身份和影響力等👷🏿‍♂️。元宇宙包括了目前已知的所有高端科技和概念,如AlⓂ️、VR、AR、MR🙆🏽、區塊鏈、NFT和5G等,VR+教育、VR+社交、VR+購物🤶🏿、VR+旅遊和VR+運動等都是元宇宙的一部分。元宇宙與現實世界實時交互,在元宇宙中所發生的一切都是真實的🫡。VR+教育是元宇宙的重要組成部分,將虛擬現實技術應用於外語教學領域也引發了廣大教育工作者的關註,深入研究“VR+外語教育”已成為科技和時代發展的必然。馬沖宇著作的《基於虛擬現實的計算機輔助語言教學研究》一書有助於高校外語教師研究如何利用虛擬現實技術來構建VR英語課堂🚧。

　　1.對外話語體系視域下漢碩留學生高質量培養探究

　　摘要⚛️：本研究采用“對外話語體系”理論作為分析的切入點,分別從話語主體🏉、話語內容、話語方式三個層面對漢碩留學生的培養問題進行分析,以期展現培養中所面臨的問題及應對策略,從一個更全面的角度揭示漢碩留學生人才培養的實施情況。具體而言,在話語主體層面,學校容易忽略留學生在文化選擇上的諸多不同,走進同質化的培養誤區;在話語內容層面,教材選擇存在著國內外生源重重交叉,內容有傳統化傾向,缺少現當代中國文化的融入,時代性🏄🏼👨🏼‍🦰、針對性、靈活性等明顯不足;在話語方式層面,教學話語單一化、互動性不足,缺少分析留學生學情,出現了“課堂焦慮”問題。為此提出如下對策:（1）明確對外話語主體的重點,立足於留學生的文化背景,進行細致的話語主體分類,突出培養重點的群體效應;（2）增強教材話語內容的豐富性,體現多元的國別化特色,以美好生活為引領,尋找中外語言文化的共通點;（3）增添教學話語風格的多樣性,融合不同的話語形態和敘述視角,以對話交流增強教學話語的互動性;（4）通過教師話語人才專業能力的整體提升來促進教學質量的有效落實。

　　2.國際中文新、熟手教師課堂指令語類型對比研究

　　摘要：選取5名新手和5名熟手國際中文教師，運用課堂觀察、訪談和錄音對兩者課堂指令語類型進行對比研究🔩。兩者的共性是傾向於使用簡潔👷🏻、直接的形式，回避語義復雜、可能造成學生誤解的形式。差異性是新手頻繁使用單一類型的指令語，指令語氣過於強硬🧍🏻‍♀️，禮貌程度較低。熟手則能夠利用豐富多變的指令語為學生提供與其中文水平相匹配的語言輸入。造成兩者課堂指令語差異的主要因素包括教學經驗😇、實踐性知識、自信心🍰、對教師權威的認知、對課堂角色的定位等。新手應加強對學生學習情緒和體驗的關註；利用撰寫教學日誌等方法反思自身指令語的使用情況；發揮非言語交際手段的輔助作用；在教師共同體中學習熟手使用指令語的經驗🪈，以促進課堂教學效率的提升。

　　3.現代漢語工具動量詞的指稱功能考察：認知語法視角

　　摘要🚲：語法學界一般認為，現代漢語工具動量詞的作用是作為動量標記或分類標記。本文在大規模真實語料中觀察後提出🐋，工具動量詞一個重要的語義功能是通過概念轉喻的機製實現動作事件的指稱，其作用與動作動詞的名物化形式相當。專用動量詞也可以指稱動作🔏，但使用頻率和概念自主程度都很低🧊。工具動量詞的事件指稱功能在以往研究中一直沒有受到重視，但它是漢語區別於英語等印歐語的一個重要個性。

08外語與文化傳播學院

　　Abstracts：Presentstudy reveals the flow of a classical non-Newtonian fluid based on theWilliamson model through a vertical flat plate. The free convective flow isgenerated because of the effect of buoyancy relating to the temperature. Inaddition to that, the influence of thermal radiation and heat source/sink inconjunction with the dissipative heat enhances the efficiency of transportphenomenon within the bounding surface. Well-proposed similarity transformationis used to transform the governing equation into ordinary.However, due to the dissipation, the nonlinear coupled problems are complex.For the solution, a semi-analytical approach suchas differential transformation method (DTM) in association with thePade approximant method is used instead of traditional numerical technique.Pade-approximant is useful to get a non-iterative solution without imposing themissing boundary conditions. It is a simple and effective way to determine thesolutions of complex nonlinear problems with assumed boundary conditions atinfinity. The physical significance of all the contributing parametersdistinguished the flow properties are achieved and accessible graphically.Moreover, the validation of the present methodology with the traditionalnumerical technique is obtained, showing an excellent correlation in particularcases.

　　Abstracts👨‍👩‍👦🫰🏻：Weconsider the Cauchy problem for a first-order evolution equation withmemory in a finite-dimensional Hilbert space when the integral term is relatedto the time derivative of the solution. The main problems of the approximatesolution of such nonlocal problems are due to the necessity to work with theapproximate solution for all previous time moments. We propose a transformationof the first-order in-tegrodifferential equation to a system of localevolutionary equations. We use the approach known in the theory of Volterraintegral equations with an approximation of the difference kernel by the sum ofexponents. We formulate a local problem for a weakly coupled system ofequations with additional ordinary differential equations. We havegiven estimates of the stability of the solution by initial data and theright-hand side for the solution of the corresponding Cauchy problem. Theprimary attention is paid to constructing and investigating the stability oftwo-level difference schemes, which are convenient for computationalimplementation. The numerical solution of a two-dimensional model problem forthe evolution equation of the first order, when the Laplace operatorconditions the dependence on spatial variables, is presented. (c) 2022 ElsevierB.V. All rights reserved.

　　Abstracts🧑🏼‍🍳：In this study, a variable step size formulation ofmulti-step general Runge-Kutta- Nystrom (MSGN) methods to directly integrategeneral second-order initial value prob-lems (IVPs) is considered. This formulais carried out using an embedded explicit pair where: the higher-order formulais an accurate and the lower-order formula uses to estimate the local error.Numerical results show that the new methods perform much better in terms offunctions evaluations, implementation cost and execution time compared to otherexisting high quality embedded Runge-Kutta (ERK) methods in the literature.(c)2022 Elsevier B.V. All rights reserved.