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    “第四屆中國大學生5分鐘科研英語演講大賽(東華大學賽區)”暨“東華大學第二屆學術英語演講大賽”初賽通知

    發布時間:2021-05-21瀏覽次數:10

     “第四屆中國大學生5分鐘科研英語演講大賽(東華大學賽區)”

    暨“東華大學第二屆學術英語演講大賽”初賽通知


    為響應國家培養具有國際競爭力的新工科、新醫科、新農科、新文科的創新人才,用英語講科研的能力,繼在2020年成功舉辦“第三屆中國大學生5分鐘科研英語演講大賽(東華大學賽區)”暨“東華大學第一屆學術英語演講大賽”后,我們決定在20215月至202112月繼續舉辦“第四屆中國大學生5分鐘科研英語演講大賽(東華大學賽區)”暨“東華大學第二屆學術英語演講大賽”。


    賽事目的:提高本校本科生和研究生用英語從事專業學習、科研創新和學術交流的能力,幫助我國未來的科研工作者有效地向國際同行介紹自己的學術思想和科研成果。


    參賽對象:東華大學全體在校本科生和研究生,報名分為本科組和研究生組。


    參賽要求:

    參賽選手需用易于理解的英語、在5分鐘時間內向沒有專業背景的聽眾(這是判斷演講成功有否的一個重要標準)介紹一項與自己專業相關(包括專業科普類)的研究。

    一.研究形式可以介紹自己已經發表或撰寫中的科研論文,也可以介紹尚處于想法階段的科研計劃(但不能重復前三屆的獲獎作品)。

    二.演講的具體內容包括:1.論文標題和研究領域;2.研究現狀;3.研究目的問題或假設);4.研究方法;5.研究結果(或預期結果);6.結果討論和研究意義;7.參考文獻(可放在視頻的PPT上)。

    三.作品形式是5分鐘的視頻和200-250詞左右的英文論文摘要(結構按學科不同,見附錄摘要樣本)。

    四.參賽選手需遵守學術道德,不得出現以下學術不端行為:

    1.抄襲、剽竊、侵吞他人學術成果;2.篡改他人學術成果;3.偽造或者篡改數據、文獻,捏造事實;4.未參加創作,在他人學術成果上署名。如發現選手有上述行為,組委會將取消選手的參賽資格。


    賽事規則注意事項:

    1.上傳的視頻為5分鐘(誤差不超過1分鐘)。

    2.視頻為MP4格式,大小在100M以內。

    3.視頻應在靜止的位置上進行連續錄制,無剪輯,無中斷。視頻畫面可進   行縮放。

    4.選手需在視頻中面對觀眾,保證95%以上時間是在與觀眾交流,而不是背對觀眾解釋PPT。

    5.演講可使用PPT作為輔助材料,但頁數不能超過5(不包括參考文獻頁)。

    6.演講中不能使用其他的電子媒體素材,如聲音或視頻等;也不要使用道具類的輔助手段。

    7.演講語言應為口語,不包括詩歌朗誦、說唱樂、歌曲等語言形式。

    8.選手不得介紹自己學校和姓名,同時不出現在PPT標題頁。


    本次大賽秉承公正、公開、公平的原則,邀請專家(專業教師和英語教師)共同進行評審,最終經復賽,落地決賽決出本科組和研究生組特等獎一名、一等獎、二等獎、三等獎若干名,所有獲獎者將獲得證書和獎金。


    初賽報名截止時間:2021620

    初賽形式:視頻提交,由專家(語言教師和專業教師)網上審評(可參考往屆視頻)

    初賽資料

    1. 附錄一的大賽作品報名表(作品標題必須和論文摘要,演講視頻,PPT及演講稿一致,以便識別);

    2. 一個5分鐘演講視頻(不得出現學校和本人姓名,MP4文件格式,大小在100M以內);

    3. 200-250詞左右的英文論文摘要(參見附錄二摘要樣本)(不得出現學校和本人姓名);

    4. PPT及演講稿(PPT展示內容,頁數控制在不超過5頁,不得出現學校和本人姓名);

    *請在規定時間內,將以上資料傳到指定的郵箱。


    初賽提交作品命名方式:選手姓名+專業+推薦老師姓名


    接收作品郵箱(本科生)

    composition2021@163.com

    接收作品郵箱(碩士生)

    freelancer2021@163.com



    大賽咨詢群

    QQ799470493











    附錄一

     

    2021年度“中國大學生5分鐘科研英語演講”比賽報名表

    姓名

     

    性別

     

    年級(本科或研究生)

     

    研究方向

     

    學校

     

    學院

     

    E-mail地址

     

    聯系電話

     

    專業指導教師(無就不填)

     

    英語指導教師(無就不填)

     

    英語摘要(Abstract

    [英語摘要約200-250詞,包括:

    (1) Title (capturing the essence of your research work in a succinct

    way)

    (2) Background (showing how your study builds on and extends prior

    work)

    (3) Purpose (identifying the research questions to be investigated)

    (4) Methods (describing the methods used for data collection and

    analysis)

    (5) Findings (the findings can be complete, preliminary, or hypothetical, depending on the status of your research)

    (6) Conclusion and implications (indicating the significance of your

    research in a larger context)


    附錄二

    摘要樣本


    Understanding Service Integration of Online Social Networks: A Data-Driven Study

      

    The cross-site linking function is widely adopted by online social networks (OSNs). This function allows a user to link her account on one OSN to her accounts on other OSNs. Thus, users are able to sign in with the linked accounts, share contents among these accounts and import friends from them. It leads to the service integration of different OSNs. This integration not only provides convenience for users to manage accounts of different OSNs, but also introduces usefulness to OSNs that adopt the cross-site linking function. In this paper, we investigate this usefulness based on users’ data collected from a popular OSN called Medium. We conduct a thorough analysis on its social graph, and find that the service integration brought by the cross site linking function is able to change Medium’s social graph structure and attract a large number of new users. However, almost none of the new users would become high Page Rank users (PageRank is used to measure a user’s influence in an OSN). To solve this problem, we build a machine-learning-based model to predict high PageRank users in Medium based on their Twitter data only. This model achieves a high F1-score of 0.942and a high area under the curve (AUC) of 0.986. Based on it, we design a system to assist new OSNs to identify and attract high PageRank users from other well-established OSNs through the cross-site linking function.

      


    Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

      

    BACKGROUND 

    The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the Epidemiologic characteristics of NCIP.

    METHODS 

    We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number.

    RESULTS 

    Among the first 425 patients with confirmed NCIP, the median age was 59 Years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9).

    CONCLUSIONS 

    On the basis of this information, there is evidence that human-to-human Transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)


    往屆視頻參見:


    第一屆視頻

    http://www.sentbase.com/cn5mrp1/?content-app-content&contentid=613

    第二屆視頻

    http://sentbase.com/cn5mrp/?content-app-content&contentid=6233

    第三屆視頻

    http://sentbase.com/cn5mrp/?content-app-content&contentid=632



    東華大學外國語學院


    2021.5.18



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