Linguistic Features of Oral English Corpora and Their Implications for English Teaching in Colleges and Universities

The main goal of English teaching in colleges and universities is to cultivate students’ability to use the language,but many students are still unable to complete oral communication fluently after years of study.For this reason,teachers need to deeply analyze and study the linguistic features of oral English corpora and formulate reasonable teaching strategies to improve students’oral expression skills.This paper outlines the linguistic features of oral English corpora,comparatively analyzes the differences between oral English corpora and written English corpora,and explores effective teaching strategies,hoping to provide guidelines for relevant teachers.

基于变形图匹配的知识图谱多跳问答

知识图谱问答(KGQA)是给定自然语言问题,对问题进行语义理解和解析,进而利用知识图谱进行查询、推理得出答案的过程。但知识图谱通常是不完整的,链接缺失给多跳问答带来许多挑战。许多方法在利用知识图谱嵌入时忽略了重要的路径信息来评估路径和多关系问题之间的相关性;且使用文本语料库也会限制文本增强模型的可扩展性。针对这些现有方法的缺陷,提出了基于变形图匹配的知识图谱问答(DGM-KGQA)模型,该模型同时利用问题和主题实体构建语义子图,与知识图谱的局部结构匹配并找到正确答案。在基准数据集MetaQA上的实验结果验证了DGM-KGQA的有效性,该模型在完整知识图谱上检索到的答案准确率分别比PullNet、EmbedKGQA增加了4.2%、0.8%;在完整度仅有一半的知识图谱上检索到的答案准确率分别比PullNet、EmbedKGQA增加了11.1%、0.5%。实验证明提出的变形图匹配模型能够有效地增强知识图谱的关联性及多跳问答的答案准确率。

面向煤矿机电设备领域的三元组抽取方法

针对机电设备领域相关语料匮乏、关系类型特征挖掘不充分以及文本包含重叠三元组的问题,提出一种融合提示学习与先验知识以迭代式对抗训练的三元组抽取方法TBPA(Triplet extraction Based on Prompt and Antagonistic training)。首先,利用BERT(Bidirectional Encoder Representations from Transformers)模型在自构语料库上进行微调,以获取输入文本的特征向量;接着,采用投影梯度下降(PGD)方法在嵌入层进行迭代式对抗训练,提高模型对干扰样本的抵御能力和对真实样本的泛化能力;然后,利用单层头尾指针网络识别出头实体,并结合提示学习模板获取头实体对应的领域先验特征,将字向量与Prompt模板中预测得到的提示向量相结合;最后,在分层标注框架下,使用单层头尾指针网络逐个识别预定义的所有关系类型所对应的尾实体。与基线模型CasRel相比,TBPA在精确率、召回率和F1值上分别提高了3.10、6.12、4.88个百分点。实验结果表明,TBPA在煤矿机电设备领域三元组抽取任务中具有一定的优势。

Breathe New Life into English Teaching:A Book Review of Using Corpora in the Language Classroom

The present article provides a critical review of Randi Reppen's impressing book Using Corpora in the Language Classroom.It's argued that Randi Reppen's book,despite a few slight flaws,has a strong practical orientation and is a laudable effort to make English language teachers to realize the importance and practicality of bringing corpora into classroom in digital age.The book is particularly worthy of reading for those language teachers(especially beginner teachers) who want to breathe new life into their English teaching.

基于语料库的纳西族英雄史诗《黑白之战》译本风格对比研究

本研究基于自建的《黑白之战》英汉平行语料库,借助Python的自然语言处理包,从语言特征(类符/形符比,平均词长,平均句长,词汇密度)对孙兴文译本和涂沙丽译本的翻译风格进行对比。研究发现,涂译本的类符/形符比,平均词长,词汇密度均高于孙译本,但平均句长小于孙译本,涂译异化程度更高,孙译则更加归化。

The Youth’s View of Marriage in Chinese Mainstream Media Discourse-A Corpus-assisted Three-dimensional Discourse Analysis

The rising of aging and the declining of birth rates have forced the public to focus on the youth’s view on marriage.Based on critical discourse analysis and combined with Fairclough’s three-dimensional discourse analysis model,this paper builds a“Chinese media News Report Corpus on the topic of‘marriage’”whose news are collected from China Daily.It is found that the discourses are neutral and objective with regard to the advantages and disadvantages of marriage,but in general,it is still a traditional view of marriage that is inevitable and closely related to fertility.Although this is controlled by the policies and the social reasons including declining fertility rate,it deviates from the current view of the youth towards marriage,resulting in many serious consequences such as young people’s rejection.In addition,this research found that male and female have great differences in their views on marriage,and men’s resistance to marriage is far greater than that of women,which is departure from the public’s cognition.The reasons behind this need to be explored in order to solve the marriage and love problems of young people in today’s era and realize the healthy development of young marriage.

Corpora research of language transfer

The paper firstly reviews the developments of language transfer research. Utilizing the results supplied by CEM and AntConc, the present writer conducts analyses of the lexicai errors committed by the students in TEM-8 test and reveals the contributions to SLA and EFL language teaching that language transfer may make.

基于语料库工具Wmatrix的商务语篇隐喻分析

隐喻作为一种认知工具,广泛地存在于商务语篇中,用以解释复杂且抽象的商业现象。本研究以概念隐喻理论为理论框架,以具有语义域赋码功能的Wmatrix5.0为检索工具,并结合MIPVU隐喻识别方法,对2021年《经济学人》中357篇商务专栏报道进行隐喻研究,分析商务经济话题中常见的概念隐喻现象。研究发现:商务语篇中最常用的五种隐喻分别为身体隐喻、战争隐喻、旅行隐喻、植物隐喻和建筑隐喻,它们又分别归属于结构隐喻、方位隐喻和本体隐喻。这表明,商务语篇使用的多是常规隐喻,是在人们普遍认知范围内进行的隐喻映射,意在用习以为常的概念来解释高度抽象且复杂的商业现象。

《1984》不同中文译本语料浅析

通过对《1984》董乐山译、孙仲旭译、富强译三个不同中文译本的语料进行浅析后发现,总体而言孙仲旭译本质量更高。在研究的过程中,发现了中英语言表达的不同以及文化方面的差异。用词上,原文中词汇较少重复,用词时而严肃、时而较为轻松。而译文中会出现重复用词的情况,以此使句子更为通顺、连贯;且译者在处理时尽可能做到保持译文前后风格一致。

Classroom Application of Corpora for Extending Knowledge of English Lexis

This paper examines the application of electronic corpora to English classroom of lexical learning.It starts with a literature review of basic issues on corpus linguistics and theories underlying lexical study,followed by discussion on the specific lexical learning aspects in which a corpus might provide some insight.Based other research like data-driven learning(DDL)in this area,the paper goes further by exploring the possibility and ways of applying corpora in vocabulary learning classroom.

A Novel Visualization Tool for Manual Annotation when Building Large Speech Corpora

A novel visualized sound description, called sound dendrogram is proposed to make manual annotation easier when building large speech corpora. It is a lattice structure built from a group of ＂seed regions＂ and through an iterative procedure of mergence. A simple but reliable extraction method of ＂seed regkms＂ and advanced distance metric are adopted to construct the sound dendrogram, so that it can present speech＇s structure character ranging from coarse to fine in a visualized way. Tests show that all phonemic boundaries are contained in the lattice structure of sound dendrogram and very easy to identify. Sound dendrogram can be a powerful assistant tool during the process of speech corporals manual annotation.

A protective role of resveratrol against the effects of immobilization stress in corpora lutea of mice in early pregnancy

In the present study,we aimed to investigate a protective role for resveratrol against the effects of immobilization stress on corpora lutea(CL)of mice in early pregnancy.A total of 45 early-pregnant mice were divided into no immobilization stress(NIS)group,immobilization stress(IS)group,and immobilization and resveratrol treatment(IS+RES)group(n=15).Mice were immobilized in plastic tubes(50 mL)for 3 h per day during day 1 to 7 of pregnancy.In the IS+RES group,5 mg kg-'d-1 of resveratrol was administered just prior to application of stress.We analyzed apoptotic activity in CL by Western botting analysis(WB),transmission electron microscopy(TEM),and immunohistochemistry(IHC).Serum progesterone levels were examined with radioimmunoassay(RIA).IHC results showed that the intensity of positive staining for Bax was increased,and for BcI-2 was decreased in CL after IS,while resveratrol treatment reversed the positive staining for Bax and Bcl-2.WB revealed that immobilization stress up-regulated the expression of Bax and caspase-9,and down-regulated Bcl-2 expression,while resveratrol treatment attenuated the effects of immobilization stress on the expression of Bax,Bcl-2 and caspase-9.According to our TEM results,apoptosis as defined by chromatin condensation was found in CL after immobilization stress,while resveratrol inhibited the apoptosis.We also demonstrated that immobilization stress decreased progesterone concentrations and ovarian expression of StAR,while resveratrol restored the concentrations of progesterone and expression of StAR back to normal.These results indicated that immobilization stress induced luteal regression while resveratrol inhibited luteal regression,suggesting that resveratrol plays a protective role on corpora lutea of mice during early pregnancy.

Standard NER Tagging Scheme for Big Data Healthcare Analytics built on Unified Medical Corpora

The motivation for this research comes from the gap found in discovering the common ground for medical context learning through analytics for different purposes of diagnosing,recommending,prescribing,or treating patients for uniform phenotype features from patients’profile.The authors of this paper while searching for possible solutions for medical context learning found that unified corpora tagged with medical nomenclature was missing to train the analytics for medical context learning.Therefore,here we demonstrated a mechanism to come up with uniform NER(Named Entity Recognition)tagged medical corpora that is fed with 14407 endocrine patients’data set in Comma Separated Values(CSV)format diagnosed with diabetes mellitus and comorbidity diseases.The other corpus is of ICD-10-CM coding scheme in text format taken from www.icd10data.com.ICD-10-CM corpus is to be tagged for understanding the medical context with uniformity for which we are conducting different experiments using common natural language programming(NLP)techniques and frameworks like TensorFlow,Keras,Long Short-Term Memory(LSTM),and Bi-LSTM.In our preliminary experiments,albeit label sets in form of(instance,label)pair were tagged with Sequential()model formed on TensorFlow.Keras and Bi-LSTM NLP algorithms.The maximum accuracy achieved for model validation was 0.8846.

Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

Digitalization has changed the way of information processing, and newtechniques of legal data processing are evolving. Text mining helps to analyze andsearch different court cases available in the form of digital text documents toextract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reducedtime. The rapid development of judicial ontologies seems to deliver interestingproblem solving to legal knowledge formalization. Mining context informationthrough ontologies from corpora is a challenging and interesting field. Thisresearch paper presents a three tier contextual text mining framework throughontologies for judicial corpora. This framework comprises on the judicial corpus,text mining processing resources and ontologies for mining contextual text fromcorpora to make text and data mining more reliable and fast. A top-down ontologyconstruction approach has been adopted in this paper. The judicial corpus hasbeen selected with a sufficient dataset to process and evaluate the results.The experimental results and evaluations show significant improvements incomparison with the available techniques.

Expression of insulin-like growth factor-1 mRNA and protein level of corpora striata in ischemic side at the early stage of middle cerebral artery ischemia/reperfusion in rhesus monkeys

BACKGROUND： Insulin-like growth factor-I（IGF-1）, as one of the important members of growth factor family, participants in the regulation of many physiological functions and behaviors, having very strong neuroprotective effect. However, the expression of IGF-1 following cerebral ischemia/reperfusion is still disputed. OBJECTIVE： To observe the expression of IGF-1 and protein of corpora striata in ischemic side at the early stage of middle cerebral artery ischemia/reperfusion in rhesus monkey. DESIGN ： A completely randomized grouping design, controlled animal experiment SETTING ： Institute of Cerebrovascular Disease, Affiliated Hospital of Medical College of Qingdao University MATERIALS： ① Totally 17 rhesus monkeys , of either gender, aged 4 to 5 years, were enrolled . Seven rhesus monkeys observed with gene chip were randomly divided into 2 groups： sham operation group （n=3） and ischemia/reperfusion group 〈n=4〉. Ten rhesus monkeys observed with in situ hybridization and immunohistochemistry method were randomly divided into 2 groups： sham operation group 〈n=3 〉and ischemia/reperfusion group （n=7）. Rhesus monkeys observed under microscope were divided into 2 groups： sham operation group （n=6） and ischamia/reperfusion group （n=-11）.②Materials used in the experiment： cresyl violet （Sigma Company, America）; immunohistochemical reagent kit （ Huamei Bio-engineering Company）; In situ hybridization reagent kit （Boshide Bio-engineering Co.Ltd, Wuhan）; 12 800 dots chip （Boxing Company, Shanghai）. METHODS ： This experiment was carried out at the Institute of Cerebrovascular Disease, Affiliated Hospital of Medical College of Qingdao University from January 2001 to December 2003.① The onset area of middle cerebral artery was blocked for 2 hours, middle cerebral artery ischemia/reperfusion models were created.② After ischemia/reperfusion for 24 hours, cerebral tissue sections of rhesus monkeys were prepared and stained with cresyl violet. Image analysis was performed with 5001W image analysis software. Morphological change of corpora striata of operative side was observed in the rhesus monkeys between two groups. Total RNA was extracted from cerebral tissue. ③ Detection of gene chip： Cy3-duTP and Cy5-duTP were used to respectively perform reverse transcription labeling. The sample was reversely transcribed into cDNA, then hybridized with cDNA of cerebral tissue. Genes with the separate absolute value of cy3 and cy5〉800, cY3/cy5 〉 2（high expression） or 〈 0.5 （low expression） were found out. Those were genes with differential expression. ④ The expressions of IGF-1 mRNA and protein level of corpora striata in ischemic side of rhe- sus monkeys were detected between sham operation group and ischemia/reperfusion group at 9 and 24 hours after ischemia/reperfusion with in situ hybridization method and immunohistochemical method. Brown granules were IGF-1 protein positive cells. ⑤ Analysis of variance was used in the difference comparison of measurement data among groups. MAIN OUTCOME MEASURES ： ① Change of morphological structure of corpora striata at ischemic side in rhesus monkeys. ② Change of cerebral gene expression profiles at ischemia/reperfusion in rhesus monkeys between two groups.③ Expression of IGF-1 mRNA and protein level of corpora striata at ischemia/reperfu- sion in rhesus monkeys between two groups. RESULTS ： ① Pathological change ： Obvious pathological change of cerebral infarction appeared in the ischemia and reperfusion group, while there was no such pathological change in the sham operation group.② Change of gene expression profile ： There were 4480 genes with difference expression in the ischemia/reperfusion group and sham-operation group, in which, 260 genes had high expression and their absolute value was over 800, and 63 genes had low expression, cy3/cy5 of IGF-1 was 0.379, being relative low ex- pression. ③ IGF-1 mRNA and protein positive cell counts in corpora striata at cerebral ischemic side[IGF-1 mRNA： 〈9.72±1.18）,（9.11 ±0.76）,（14.77±0.60） counts/field：lGF-1 protein： （15.11 ±1.83）,（15.39±0.78）, （34.62±0.97）counts/field, P 〈 0.05-0.01]. CONCLUSION： IGF-1 mRNA and protein are lowly expressed in middle cerebral artery of rhesus monkeys at ischemia/reperfusion.

基于ERNIE预训练的中医临床病历分类

将中医临床病历分为五大类问题,利用Transformers的双向编码器,在训练文本分类器之前,用未标注的临床语料库来微调ERNIE(Traditional Chinese Medicine-ERNIE)模型,精炼出一个针对中医知识领域的TCM-ERNIE模型,该语料库只使用临床记录文本中的汉字作为输入,无须再进行预处理或特征提取.最后采用基准数据集来评估TCM-ERNIE模型和传统文本分类器,取得了89.39%±0.35%的分类精度,Macro F1为88.64%±0.40%,Micro F1为89.39%±0.35%,还采用可视化的方法来显示注意力权重,进一步揭示临床病历文本中的指标性症状.

中华学术外译背景下汉译英学术文本的词汇丰富度研究

近年来,使用平行语料库进行汉译英研究已成为国内翻译学界的一大热点。本研究自建平行语料库,从词汇特征入手,对汉语学术著作《语言符号学》及其英译本,以及英语学术著作Handbook of Semiotics(以下简称Handbook)的词汇丰富度进行了比较研究。研究结果表明:1)《语言符号学》英译本的词汇多样性与Handbook比较接近,未呈现出词汇范围窄化的倾向;2)相对于原作,《语言符号学》英译本的词汇密度有所降低,连词、介词和代词存在扩增现象;3)《语言符号学》英译本的词汇复杂度低于Handbook,前者的阅读难度相对较低。

美国对华贸易政策情态系统的人际意义研究——基于评价理论视角

基于自建语料库,从评价理论角度研究美国对华贸易政策中情态系统的使用特征和人际意义。研究发现:(1)与特朗普对华贸易政策相比,拜登对华贸易政策中情态系统的使用率更高,且更多使用道义情态,而认识情态和意志情态的分布无明显差异,从量值的使用情况来看,拜登对华贸易政策更多使用高值情态词,较少使用中值和低值情态词;(2)美国对华贸易政策中使用不同的情态类型进行判断,使用不同量值的情态词调节评价语势,同时将评价性词汇资源与情态词搭配,转移压力来源,实现对话的扩张与收缩。因此,情态系统具有表达主体不同程度的态度和立场、转移情态责任、扩张与收缩对话空间的人际意义。

翻译过程中省译策略的运用及其认知研究

省译指译者在翻译过程中省去原文或部分原文未进行翻译,它属于译者常用翻译策略之一。目前,鲜有研究关注省译策略在翻译过程中的运用及其认知理据。本研究通过自建三个汉英英汉双语平行语料库,选择词和句子两类语言单位,以中文叠词和英文连词为研究窗口,考察省译在真实翻译情境中的使用情况。研究发现:(1)省译在词和句子层面大量存在;(2)翻译中文叠词和英文连词时,译者均倾向于采用省译策略来翻译,分别占比58.23%和56.55%。理论上翻译需要传递源语信息,达到交际的目的,即是要“译”。然而,译者如此频繁使用省译作为编码方式来加工原文,可能是其认知系统受到内外因素的制约所致。

Improved Ant Lion Optimizer with Deep Learning Driven Arabic Hate Speech Detection

Arabic is the world’s first language,categorized by its rich and complicated grammatical formats.Furthermore,the Arabic morphology can be perplexing because nearly 10,000 roots and 900 patterns were the basis for verbs and nouns.The Arabic language consists of distinct variations utilized in a community and particular situations.Social media sites are a medium for expressing opinions and social phenomena like racism,hatred,offensive language,and all kinds of verbal violence.Such conduct does not impact particular nations,communities,or groups only,extending beyond such areas into people’s everyday lives.This study introduces an Improved Ant Lion Optimizer with Deep Learning Dirven Offensive and Hate Speech Detection(IALODL-OHSD)on Arabic Cross-Corpora.The presented IALODL-OHSD model mainly aims to detect and classify offensive/hate speech expressed on social media.In the IALODL-OHSD model,a threestage process is performed,namely pre-processing,word embedding,and classification.Primarily,data pre-processing is performed to transform the Arabic social media text into a useful format.In addition,the word2vec word embedding process is utilized to produce word embeddings.The attentionbased cascaded long short-term memory(ACLSTM)model is utilized for the classification process.Finally,the IALO algorithm is exploited as a hyperparameter optimizer to boost classifier results.To illustrate a brief result analysis of the IALODL-OHSD model,a detailed set of simulations were performed.The extensive comparison study portrayed the enhanced performance of the IALODL-OHSD model over other approaches.