Chinese Culture in ELT Classroom—The Influence of Chinese Culture on Students' Answering Questions

Based on personal observation and students’ self-reports, this article studies the characteristics presented by students in answering questions. It is found that Chinese culture plays an important part in explaining their specific behaviors. Hence, in order to lessen the negative effect of it, the author offers her own suggestions.

The most important questions in cancer research and clinical oncology Question 2-5.Obesity-related cancers:more questions than answers

Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy(metabolically healthy obese, MHO), so which fat deposition(subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers(ORCs) share a molecular signature? Are there common(overlapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse efect of obesity on human condition.

PAL-BERT:An Improved Question Answering Model

In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant attention.However,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has surfaced.Consequently,model training has become more costly and less efficient.To enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language model.Firstly,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is formed.Then,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the performance.Finally,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training efficiency.Compared with traditional models,PAL-BERT significantly improves the NLP task’s performance.

MKEAH:Multimodal knowledge extraction and accumulation based on hyperplane embedding for knowledge-based visual question answering

Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding approaches are deficient in representing some complex relations,resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.Methods To this end,we propose MKEAH:Multimodal Knowledge Extraction and Accumulation on Hyperplanes.To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information,two losses are proposed to learn the triplet representations from the complementary views:range loss and orthogonal loss.To interpret the capability of extracting topic-related knowledge,we present the Topic Similarity(TS)between topic and entity-relations.Results Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering.Our model outperformed state-of-the-art methods by 2.12%and 3.24%on two challenging knowledge-request datasets:OK-VQA and KRVQA,respectively.Conclusions The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.

Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

DPAL-BERT:A Faster and Lighter Question Answering Model

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems.However,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced efficiency.This study aims to minimize the inference time of such models while maintaining computational performance.It also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and DPAL-BERTC.This research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge transfer.The experimental results showed that the distilled models greatly outperform models trained from scratch.In addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the original.This demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.

Fatigue sensation following peripheral viral infection is triggered by neuroinflammation: who will answer these questions?

Fatigue is best defined as difficulty in initiating or sustaining voluntary activities, and is thought to be accompanied by deterioration of performance. Fatigue can be caused by many factors such as physical and mental stress, disturbance in the circadian rhythm, and various diseases. For example, following the flu or other types of infections, everyone has experienced a sense of fatigue that can last for days or weeks. The fatigue sensation is thought to be one of the signals for the body to suppress physical activity in order to regain health. The mechanism of induction of the fatigue sensation following viral infection has not been well understood. Although fatigue was once thought to be caused by fever, our recent study with an animal model of viral infection demonstrated that the fatigue sensation is caused not by fever, but rather,

Questions and Answers

How to Differentiate and Treat Bi-syndrome by Acupuncture and Moxibustion?Bi-syndrome is the syndrome due to invasion of the exogenous pathogenic factors of wind, cold and dampness, which obstruct the channels and collaterals, leading to stagnated flow of qi and blood, characterized by such clinical manifestations as aching pain, numbness, heaviness, limited flexion and extension of the muscles, tendons and joints, or swelling and burning heat of the joints. This syndrome includes rheumatic arthritis, rheumatoid arthritis, osseous arthritis, and various neuralgia. The endogenous causative factors for the occurrence of Bi-syndrome are insufficiency of yang-qi, essence and blood, while the exogenous causative factors are the pathogenic wind, cold, and dampness. At the initial stage of the disease, the excessiveness of pathogen usually prevails, and the disease tends to be located in the limbs, skin and muscles, and channels and collaterals; while at the chronic stage, there often exists deficiency of the vital-qi or deficiency and excess intermixed, and the disease tends to be located deeper in the tendons and bones or in the zang-fu organs.

Minister Shi Dazhen Answers the Reporters' (of Britain "Financial Times") Questions

On June 3 1996, Minister of Electric Power Shi Dazhen accepted news-covering of Britain "Financial Times" resident reporter in Beijing Tony Walker, resident reporter in Hong Kong John Ridding and Asian Editor Peter Montagnon, and answered their questions in the aspects of the 9th Five-year Development Planning of China’s Electric Power and some related issues.

Funny Questions and Answers

一个魔术师拿着一个装满了的水杯。把它举过头顶，然后让它落在地毯上。没有溅出一滴水。他是怎样做到从6英尺高的地方让水杯落下却没溅出一滴水的昵？

Funny Questions and Quick Answers

1.Harry’s mom has three boys.The first boy’s name is Tom.the second boy’s named is David.What is the third boy’s name?2.How can you make a fire with two sticks?3.A boy fell off a 100-foot ladder and did not get hurt.How can this be?4.I’m full when I am gone.and I’m empty when I am here.What am I?5.What kind of key can not open doors?

MOFCOM Answered Questions by Reporters Concerning First Batch of Rare Earth Export Quotas in 2012

Source:MOFCOM website The Ministry of Commerce released on December 27 the first batch of rare earth export quotas in 2012. Head of Department of Foreign Trade of MOFCOM answered questions put up by reporters. According to the Head,the Chinese government has taken management measures over the exploration,production and export of rare earth,as required in protection of resources and the environment.In May,2011,the State

Question classification in question answering based on real-world web data sets

To improve question answering （QA） performance based on real-world web data sets,a new set of question classes and a general answer re-ranking model are defined.With pre-defined dictionary and grammatical analysis,the question classifier draws both semantic and grammatical information into information retrieval and machine learning methods in the form of various training features,including the question word,the main verb of the question,the dependency structure,the position of the main auxiliary verb,the main noun of the question,the top hypernym of the main noun,etc.Then the QA query results are re-ranked by question class information.Experiments show that the questions in real-world web data sets can be accurately classified by the classifier,and the QA results after re-ranking can be obviously improved.It is proved that with both semantic and grammatical information,applications such as QA, built upon real-world web data sets, can be improved,thus showing better performance.

Automatic Question Answering from Web Documents

A passage retrieval strategy for web-based question answering （QA） systems is proposed in our QA system. It firstly analyzes the question based on semantic patterns to obtain its syntactic and semantic information and then form initial queries. The queries are used to retrieve documents from the World Wide Web （WWW） using the Google search engine. The queries are then rewritten to form queries for passage retrieval in order to improve the precision. The relations between keywords in the question are employed in our query rewrite method. The experimental result on the question set of the TREC-2003 passage task shows that our system performs well for factoid questions.

Analysis of community question-answering issues via machine learning and deep learning:State-of-the-art review

Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.

Query Expansion Based on Semantics and Statistics in Chinese Question Answering System

In Chinese question answering system, because there is more semantic relation in questions than that in query words, the precision can be improved by expanding query while using natural language questions to retrieve documents. This paper proposes a new approach to query expansion based on semantics and statistics Firstly automatic relevance feedback method is used to generate a candidate expansion word set. Then the expanded query words are selected from the set based on the semantic similarity and seman- tic relevancy between the candidate words and the original words. Experiments show the new approach is effective for Web retrieval and out-performs the conventional expansion approaches.