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ABSTRACT Second/foreign language (L2) learning is not solely a cognitive/linguistic acquisition process but includes mixed emotional experiences. Understanding how these emotional experiences relate to resilience could help our understanding of how learners navigate fluctuations in emotions when learning an L2.
Xinjie Chen +5 more
wiley +1 more source
推广了通常的半群的强半格分解的定义 ,得到 ρG 强半格的定义 .并用 ρG 强半格分解研究了 Green关系H 分别是正则带同余、右 (左 )拟正规带同余和正规带同余的超富足半群的半格分解问题 .
孔祥智
doaj
应用Dancer全局分歧理论,研究奇异边值问题正解的存在性和多解性,其中f:[0,1]×[0,∞)→[0,∞)连续.给出了关于此类问题正解存在的充分条件,该充分条件与相应线性问题的第1个特征值有关,且所涉及的值是最优的.
YANDongming(闫东明)
doaj +1 more source
ABSTRACT Understanding learners’ English speaking self‐efficacy is essential for promoting effective oral communication in EFL contexts. However, variable‐centered research on English speaking self‐efficacy often overlooks heterogeneity among learners.
Cha Li, Lawrence Jun Zhang
wiley +1 more source
3.方程(1)在p≡17(mod24),q≡3(mod8)或p≡5(mod24),q≡23(mod24)或p≡5(mod24),q≡3(mod8),(p/q)=1时均无正整数解.4.当D=2p时,方程(1)除开有解p=3,x=7,y=20外,无其他的正整数解.5.方程(1)在p≡3(mod4),q≡3(mod4)时无正整数解.国外,Nagell,Ljunggren,Cohn等人有过不少工作,可参看文[4]所附文献.本文用不同于前面诸文的方法,对于D=pq的情形,得到进一步的结果 ...
柯召, 孙琦
doaj
ABSTRACT Grounded in social cognitive theory, this study investigated how high‐evidence factors jointly contribute to Chinese‐as‐a‐foreign‐language (CFL) speaking self‐efficacy. Data from 236 CFL learners in Beijing revealed a multifaceted pattern of associations.
Peijian Paul Sun +3 more
wiley +1 more source
本研究通过对被试求解换位棋过程的记录与分析,重点研究了问题表征在换位棋求解过程中的作用。实验结果表明:(1)正确表征问题规则是解题的必要前提.对问题规则信息的误解和遗漏,是影响解题正确率的重要因素。其中对非隐含问题规则的错误表征也占全部错误表征的很大比率。(2)“关键结构”的发现是解决换位棋的必要条件,对问题规则的错误表征影响“关键结构”的发现.(3 ...
王东晖, 傅小兰
core +1 more source
关于方程sum from j=0 to h(x+j)n=(x+h+1)n
我们曾证明6≤n≤33时,(1)无正整数解,以及其他若干结果。P.Erd?o对于x=1的情形,曾猜测(1)除开1+2=3外,无其他正整数解,L.Moser证明了这个猜测在h+2≤1010~6时成立。本文将证明:方程(1)在n是奇数时,除开已知的n=3,h=2,x=3和n=h=x=1外无其他正整数解,这个证明初等而简短。运用这个方法还可证明在2β|n,h(?)1,2(mod2β+3),β>0或n=2s,3·2s,s>1时,(1)均无正整数解。
柯召, 孙琦, 邹兆南
doaj
AI foundation models in plant biology
Foundation models decode genomes, engineer proteins, phenotype crops, and drive AI agents across plant biology. This figure was created in BioRender (BioRender.com/xcmmkel). Summary Rapid technological progress has enabled plant biologists to accumulate unprecedented volumes of multi‐scale, multi‐modal data, yet this abundance of data has intensified ...
Haopeng Yu
wiley +1 more source

