Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant ad...Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant advantages of GAs,including improved clarity,increased reader engagement,and enhanced visibility of research findings.By transforming intricate scientific data into accessible visual formats,these abstracts facilitate quick and effective knowledge transfer,crucial in clinical decision-making and patient care.However,challenges such as potential data misrepresentation due to oversimplification,the skill gap in graphic design among researchers,and the lack of standardized creation guidelines pose barriers to their widespread adoption.Additionally,while software such as Adobe Illustrator,BioRender,and Canva are commonly employed to create these visuals,not all researchers may be proficient in their use.To address these issues,we recommend that academic journals establish clear guidelines and provide necessary design training to researchers.This proactive approach will ensure the creation of high-quality GAs,promote their standardization,and expand their use in clinical reporting,ultimately benefiting the medical community and improving healthcare outcomes.展开更多
The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become critical for sharing opinions and...The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become critical for sharing opinions and insights, influencing daily habits, and driving business, political, and economic decisions. Text posts are particularly significant, and natural language processing (NLP) has emerged as a powerful tool for analyzing such data. While traditional NLP methods have been effective for structured media, social media content poses unique challenges due to its informal and diverse nature. This has spurred the development of new techniques tailored for processing and extracting insights from unstructured user-generated text. One key application of NLP is the summarization of user comments to manage overwhelming content volumes. Abstractive summarization has proven highly effective in generating concise, human-like summaries, offering clear overviews of key themes and sentiments. This enhances understanding and engagement while reducing cognitive effort for users. For businesses, summarization provides actionable insights into customer preferences and feedback, enabling faster trend analysis, improved responsiveness, and strategic adaptability. By distilling complex data into manageable insights, summarization plays a vital role in improving user experiences and empowering informed decision-making in a data-driven landscape. This paper proposes a new implementation framework by fine-tuning and parameterizing Transformer Large Language Models to manage and maintain linguistic and semantic components in abstractive summary generation. The system excels in transforming large volumes of data into meaningful summaries, as evidenced by its strong performance across metrics like fluency, consistency, readability, and semantic coherence.展开更多
This study systematically analyzes the genre structure and linguistic features of 42 English abstracts from six internationally renowned medical journals,based on the revised CARS model proposed by Swales.The research...This study systematically analyzes the genre structure and linguistic features of 42 English abstracts from six internationally renowned medical journals,based on the revised CARS model proposed by Swales.The research findings indicate that medical abstracts typically follow a three-step structure:“Establishing a Research Territory-Establishing a Research Niche-Occupying the Niche”,where the steps“Research Purpose”and“Research Results”are the most frequently utilized,forming the core content of the abstracts.Within the sequence of moves,81%conform to conventional patterns,while a minority of samples exhibit unconventional structures such as inversion,cycling,and repetition.In terms of linguistic features,the present simple tense and active voice are predominantly used,reflecting the universality of the research and the author’s agency;conversely,the simple past tense and passive voice are primarily employed to describe research methods and processes.This study reveals the writing conventions of medical abstracts,providing empirical evidence and genre reference for non-native scholars in the preparation and publication of their work in international journals.展开更多
Knowledge graphs convey precise semantic information that can be effectively interpreted by neural networks,and generating descriptive text based on these graphs places significant emphasis on content consistency.Howe...Knowledge graphs convey precise semantic information that can be effectively interpreted by neural networks,and generating descriptive text based on these graphs places significant emphasis on content consistency.However,knowledge graphs are inadequate for providing additional linguistic features such as paragraph structure and expressive modes,making it challenging to ensure content coherence in generating text that spans multiple sentences.This lack of coherence can further compromise the overall consistency of the content within a paragraph.In this work,we present the generation of scientific abstracts by leveraging knowledge graphs,with a focus on enhancing both content consistency and coherence.In particular,we construct the ACL Abstract Graph Dataset(ACL-AGD)which pairs knowledge graphs with text,incorporating sentence labels to guide text structure and diverse expressions.We then implement a Siamese network to complement and concretize the entities and relations based on paragraph structure by accomplishing two tasks:graph-to-text generation and entity alignment.Extensive experiments demonstrate that the logical paragraphs generated by our method exhibit entities with a uniform position distribution and appropriate frequency.In terms of content,our method accurately represents the information encoded in the knowledge graph,prevents the generation of irrelevant content,and achieves coherent and non-redundant adjacent sentences,even with a shared knowledge graph.展开更多
English for Specific Academic Purposes(ESAP)focuses on English language skills in specific disciplines or research fields,and has played an important role in international communication in recent years.This paper aims...English for Specific Academic Purposes(ESAP)focuses on English language skills in specific disciplines or research fields,and has played an important role in international communication in recent years.This paper aims to explore the relationship between ESAP,the output of academic paper abstracts,and international communication effectiveness,so as to provide new ideas for enhancing international communication effectiveness.Through a questionnaire survey and combined with the structural equation model analysis method,the results show that the improvement of ESAP has a positive effect on the output of academic paper abstracts and international communication effectiveness;the output of academic paper abstracts can also positively enhance international communication effectiveness;meanwhile,the output of academic paper abstracts has a significant mediating effect.展开更多
Exogenous organic input impacts soil phosphorus transformation.Meanwhile,dissolved organic matter(DOM)is crucial for biogeochemical functions.Nevertheless,the interaction between the structural composition of DOM and ...Exogenous organic input impacts soil phosphorus transformation.Meanwhile,dissolved organic matter(DOM)is crucial for biogeochemical functions.Nevertheless,the interaction between the structural composition of DOM and phosphorus during the soil formation process of phosphogypsum(PG)remains unknown.This study explores the interaction between the structural composition of DOM and phosphorus in enhanced PG under the participation of fungal microorganisms through different application amounts of exogenous organic matter and culture time.Results show that application of exogenous organic matter led to varying degrees of increase in dissolved organic carbon(DOC)concentration and humification extent in the soil-like substrate.Additionally,the relative abundance of protein-like component C3 exhibited a trend of initial increase followed by decline over time.The contents of available phosphorus(AP),microbial biomass phosphorus(MBP),and active phosphorus pools(Active-P)in the soil-like substrate are all enhanced overall.Furthermore,a significant correlation exists between DOC and AP as well as MBP.This suggests that DOM is a crucial factor in enhancing the phosphorus availability of the soil-like substrate.The enrichment of known phosphate-solubilizing fungi in culturing favors the decomposition,activation and utilization of hard-to-mineralize phosphorus components in the soil-like substrate.These findings help understand DOM’s biogeochemical behavior and offer insights into PG utilization and the sustainable development of China’s phosphorus industry.展开更多
A new type of asymmetric hydrogen atom abstraction catalysts,originated from the cinchona alkaloid family of natural products,has been successfully developed to access enantioselective epimerizations of meso-diols.Aft...A new type of asymmetric hydrogen atom abstraction catalysts,originated from the cinchona alkaloid family of natural products,has been successfully developed to access enantioselective epimerizations of meso-diols.After undergoing single-electron oxidation,the catalyst fulfills desymmetrization of meso-diols by selectively traping a hydrogen atom from a carbon center,which subsequently recaptures a hydrogen atom via abstraction from a thiol.The publication of this work will have a significant influence in the field of asymmetric radical chemistry.展开更多
International Journal of Minerals,Metallurgy and Materials is dedicated to the publication and the dissemination of original research articles(and occasional invited reviews)in the fields of Minerals,Metallurgy and Ma...International Journal of Minerals,Metallurgy and Materials is dedicated to the publication and the dissemination of original research articles(and occasional invited reviews)in the fields of Minerals,Metallurgy and Materials.It is covered by EI Compendex,SCI Expanded,Chemical Abstract,etc.展开更多
The exponential growth of video content has driven significant advancements in video summarization techniques in recent years. Breakthroughs in deep learning have been particularly transformative, enabling more effect...The exponential growth of video content has driven significant advancements in video summarization techniques in recent years. Breakthroughs in deep learning have been particularly transformative, enabling more effective detection of key information and creating new possibilities for video synopsis. To summarize recent progress and accelerate research in this field,this paper provides a comprehensive review of deep learningbased video summarization methods developed over the past decade. We begin by examining the research landscape of video abstraction technologies and identifying core challenges in video summarization. Subsequently, we systematically analyze prevailing deep learning frameworks and methodologies employed in current video summarization systems, offering researchers a clear roadmap of the field's evolution. Unlike previous review works,we first classify research papers based on the structural hierarchy of the video(from frame-level to shot-level to video-level),then further categorize them according to the summary backbone model(feature extraction and spatiotemporal modeling).This approach provides a more systematic and hierarchical organization of the documents. Following this comprehensive review,we summarize the benchmark datasets and evaluation metrics commonly employed in the field. Finally, we analyze persistent challenges and propose insightful directions for future research,providing a forward-looking perspective on video summarization technologies. This systematic literature review is of great reference value to new researchers exploring the fields of deep learning and video summarization.展开更多
General Information Journal of Chinese Pharmaceutical Sciences(JCPS)is a peer-reviewed bimonthly journal founded in 1992.JCPS has been indexed in the Core Journals of China's science and technology field.At presen...General Information Journal of Chinese Pharmaceutical Sciences(JCPS)is a peer-reviewed bimonthly journal founded in 1992.JCPS has been indexed in the Core Journals of China's science and technology field.At present it has been included by Chemical Abstracts(CA),UIPD,Index of Copurnicus(IC),CABI,SCOPUS,JSTChina,DOAJ,EBSCO,CSTPCD,Chinese Science Citation Database(CSCD),the Chinese National Knowledge Infrastructure(CNKI)and World Journal Clout Index(WJCI)Report.展开更多
The Chinese Journal of Natural Medicines(CJNM,ISSN 2095-6975),founded in 2003 and sponsored by China Pharmaceutical University,is a peer-reviewed journal published monthly in print by Science Press and online by Elsev...The Chinese Journal of Natural Medicines(CJNM,ISSN 2095-6975),founded in 2003 and sponsored by China Pharmaceutical University,is a peer-reviewed journal published monthly in print by Science Press and online by Elsevier.CJNM is currently indexed in Science Citation Index Expanded(SCIE),MEDLINE,BIOSIS Previews,BIOSIS Toxicology,CAB Abstracts.展开更多
Pentachlorophenol, a widespread environmental pollutant that is possibly carcinogenic to humans, is metabolically oxidized to tetrachloroquinone （TCBQ） which can result in DNA damage. We have investigated the photoc...Pentachlorophenol, a widespread environmental pollutant that is possibly carcinogenic to humans, is metabolically oxidized to tetrachloroquinone （TCBQ） which can result in DNA damage. We have investigated the photochemical reaction dynamics of TCBQ with two pyrimidine type nucleobases （thymine and uracil） upon UVA （355 ran） excitation using the technique of nanosecond time-resolved laser flash photolysis. It has been found that 355 nm excitation populates TCBQ molecules to their triplet state 3TCBQ＊, which are highly reactive towards thymine or uracil and undergo two parallel reactions, the hydrogen abstraction and electron transfer, leading to the observed photoproducts of TCBQH. and TCBQ.- in transient absorption spectra. The concomitantly produced nucleobase radicals and radical cations are expected to induce a series of oxidative or strand cleavage damage to DNA afterwards. By characterizing the photochemical hydrogen abstraction and electron transfer reactions, our results provide potentially important molecular reaction mechanisms for understanding the carcinogenic effects of pentachlorophenol and its metabolites TCBQ.展开更多
presented The conceptions of abstract default reasoning frameworks （ADRFs） and D-consequence relations are Based on representation properties of D-consequence relations, it proves that any cumulative nonmonotonic co...presented The conceptions of abstract default reasoning frameworks （ADRFs） and D-consequence relations are Based on representation properties of D-consequence relations, it proves that any cumulative nonmonotonic consequence relation with the connective-free form can be represented by ADRFs.展开更多
Image is an important and creative way to express poets＂ feelings in both Chinese and English poetry. There are concrete representations and abstract concept in image. They are two key notions in Poetics and Aestheti...Image is an important and creative way to express poets＂ feelings in both Chinese and English poetry. There are concrete representations and abstract concept in image. They are two key notions in Poetics and Aesthetics. This paper is to show the different versions of ＂tress＂ in poems and to explore the exact nature of concepts of sensitive affection in English and Chinese, so as to appreciate the artistic beauty of images.展开更多
Purpose:Mo ve recognition in scientific abstracts is an NLP task of classifying sentences of the abstracts into different types of language units.To improve the performance of move recognition in scientific abstracts,...Purpose:Mo ve recognition in scientific abstracts is an NLP task of classifying sentences of the abstracts into different types of language units.To improve the performance of move recognition in scientific abstracts,a novel model of move recognition is proposed that outperforms the BERT-based method.Design/methodology/approach:Prevalent models based on BERT for sentence classification often classify sentences without considering the context of the sentences.In this paper,inspired by the BERT masked language model(MLM),we propose a novel model called the masked sentence model that integrates the content and contextual information of the sentences in move recognition.Experiments are conducted on the benchmark dataset PubMed 20K RCT in three steps.Then,we compare our model with HSLN-RNN,BERT-based and SciBERT using the same dataset.Findings:Compared with the BERT-based and SciBERT models,the F1 score of our model outperforms them by 4.96%and 4.34%,respectively,which shows the feasibility and effectiveness of the novel model and the result of our model comes closest to the state-of-theart results of HSLN-RNN at present.Research limitations:The sequential features of move labels are not considered,which might be one of the reasons why HSLN-RNN has better performance.Our model is restricted to dealing with biomedical English literature because we use a dataset from PubMed,which is a typical biomedical database,to fine-tune our model.Practical implications:The proposed model is better and simpler in identifying move structures in scientific abstracts and is worthy of text classification experiments for capturing contextual features of sentences.Originality/value:T he study proposes a masked sentence model based on BERT that considers the contextual features of the sentences in abstracts in a new way.The performance of this classification model is significantly improved by rebuilding the input layer without changing the structure of neural networks.展开更多
文摘Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant advantages of GAs,including improved clarity,increased reader engagement,and enhanced visibility of research findings.By transforming intricate scientific data into accessible visual formats,these abstracts facilitate quick and effective knowledge transfer,crucial in clinical decision-making and patient care.However,challenges such as potential data misrepresentation due to oversimplification,the skill gap in graphic design among researchers,and the lack of standardized creation guidelines pose barriers to their widespread adoption.Additionally,while software such as Adobe Illustrator,BioRender,and Canva are commonly employed to create these visuals,not all researchers may be proficient in their use.To address these issues,we recommend that academic journals establish clear guidelines and provide necessary design training to researchers.This proactive approach will ensure the creation of high-quality GAs,promote their standardization,and expand their use in clinical reporting,ultimately benefiting the medical community and improving healthcare outcomes.
文摘The rise of social media platforms has revolutionized communication, enabling the exchange of vast amounts of data through text, audio, images, and videos. These platforms have become critical for sharing opinions and insights, influencing daily habits, and driving business, political, and economic decisions. Text posts are particularly significant, and natural language processing (NLP) has emerged as a powerful tool for analyzing such data. While traditional NLP methods have been effective for structured media, social media content poses unique challenges due to its informal and diverse nature. This has spurred the development of new techniques tailored for processing and extracting insights from unstructured user-generated text. One key application of NLP is the summarization of user comments to manage overwhelming content volumes. Abstractive summarization has proven highly effective in generating concise, human-like summaries, offering clear overviews of key themes and sentiments. This enhances understanding and engagement while reducing cognitive effort for users. For businesses, summarization provides actionable insights into customer preferences and feedback, enabling faster trend analysis, improved responsiveness, and strategic adaptability. By distilling complex data into manageable insights, summarization plays a vital role in improving user experiences and empowering informed decision-making in a data-driven landscape. This paper proposes a new implementation framework by fine-tuning and parameterizing Transformer Large Language Models to manage and maintain linguistic and semantic components in abstractive summary generation. The system excels in transforming large volumes of data into meaningful summaries, as evidenced by its strong performance across metrics like fluency, consistency, readability, and semantic coherence.
文摘This study systematically analyzes the genre structure and linguistic features of 42 English abstracts from six internationally renowned medical journals,based on the revised CARS model proposed by Swales.The research findings indicate that medical abstracts typically follow a three-step structure:“Establishing a Research Territory-Establishing a Research Niche-Occupying the Niche”,where the steps“Research Purpose”and“Research Results”are the most frequently utilized,forming the core content of the abstracts.Within the sequence of moves,81%conform to conventional patterns,while a minority of samples exhibit unconventional structures such as inversion,cycling,and repetition.In terms of linguistic features,the present simple tense and active voice are predominantly used,reflecting the universality of the research and the author’s agency;conversely,the simple past tense and passive voice are primarily employed to describe research methods and processes.This study reveals the writing conventions of medical abstracts,providing empirical evidence and genre reference for non-native scholars in the preparation and publication of their work in international journals.
文摘Knowledge graphs convey precise semantic information that can be effectively interpreted by neural networks,and generating descriptive text based on these graphs places significant emphasis on content consistency.However,knowledge graphs are inadequate for providing additional linguistic features such as paragraph structure and expressive modes,making it challenging to ensure content coherence in generating text that spans multiple sentences.This lack of coherence can further compromise the overall consistency of the content within a paragraph.In this work,we present the generation of scientific abstracts by leveraging knowledge graphs,with a focus on enhancing both content consistency and coherence.In particular,we construct the ACL Abstract Graph Dataset(ACL-AGD)which pairs knowledge graphs with text,incorporating sentence labels to guide text structure and diverse expressions.We then implement a Siamese network to complement and concretize the entities and relations based on paragraph structure by accomplishing two tasks:graph-to-text generation and entity alignment.Extensive experiments demonstrate that the logical paragraphs generated by our method exhibit entities with a uniform position distribution and appropriate frequency.In terms of content,our method accurately represents the information encoded in the knowledge graph,prevents the generation of irrelevant content,and achieves coherent and non-redundant adjacent sentences,even with a shared knowledge graph.
基金This paper is part of the research results of the National Social Science Fund Project(Project No.:21XYY015)Hainan Provincial Education Reform Project(Project No.:Hnjg2023-136)。
文摘English for Specific Academic Purposes(ESAP)focuses on English language skills in specific disciplines or research fields,and has played an important role in international communication in recent years.This paper aims to explore the relationship between ESAP,the output of academic paper abstracts,and international communication effectiveness,so as to provide new ideas for enhancing international communication effectiveness.Through a questionnaire survey and combined with the structural equation model analysis method,the results show that the improvement of ESAP has a positive effect on the output of academic paper abstracts and international communication effectiveness;the output of academic paper abstracts can also positively enhance international communication effectiveness;meanwhile,the output of academic paper abstracts has a significant mediating effect.
基金supported by the Science and Technology Major Program of Yunnan(No.202402AG0500103)the Industrial Innovation Talent Project of Yunnan(No.XDYC-CYCX-2023007)the National Key Research and Development Program of China(No.2023YFC3709100).
文摘Exogenous organic input impacts soil phosphorus transformation.Meanwhile,dissolved organic matter(DOM)is crucial for biogeochemical functions.Nevertheless,the interaction between the structural composition of DOM and phosphorus during the soil formation process of phosphogypsum(PG)remains unknown.This study explores the interaction between the structural composition of DOM and phosphorus in enhanced PG under the participation of fungal microorganisms through different application amounts of exogenous organic matter and culture time.Results show that application of exogenous organic matter led to varying degrees of increase in dissolved organic carbon(DOC)concentration and humification extent in the soil-like substrate.Additionally,the relative abundance of protein-like component C3 exhibited a trend of initial increase followed by decline over time.The contents of available phosphorus(AP),microbial biomass phosphorus(MBP),and active phosphorus pools(Active-P)in the soil-like substrate are all enhanced overall.Furthermore,a significant correlation exists between DOC and AP as well as MBP.This suggests that DOM is a crucial factor in enhancing the phosphorus availability of the soil-like substrate.The enrichment of known phosphate-solubilizing fungi in culturing favors the decomposition,activation and utilization of hard-to-mineralize phosphorus components in the soil-like substrate.These findings help understand DOM’s biogeochemical behavior and offer insights into PG utilization and the sustainable development of China’s phosphorus industry.
基金supported by the National Natural Science Foundation of China(No.22208302)the Natural Science Foundation of Zhejiang Province of China(LQ21B020006).
文摘A new type of asymmetric hydrogen atom abstraction catalysts,originated from the cinchona alkaloid family of natural products,has been successfully developed to access enantioselective epimerizations of meso-diols.After undergoing single-electron oxidation,the catalyst fulfills desymmetrization of meso-diols by selectively traping a hydrogen atom from a carbon center,which subsequently recaptures a hydrogen atom via abstraction from a thiol.The publication of this work will have a significant influence in the field of asymmetric radical chemistry.
文摘International Journal of Minerals,Metallurgy and Materials is dedicated to the publication and the dissemination of original research articles(and occasional invited reviews)in the fields of Minerals,Metallurgy and Materials.It is covered by EI Compendex,SCI Expanded,Chemical Abstract,etc.
基金supported by UKRI(EP/Z000025/1)Horizon Europe Programme under the MSCA grant for the ACMod project(101130271)。
文摘The exponential growth of video content has driven significant advancements in video summarization techniques in recent years. Breakthroughs in deep learning have been particularly transformative, enabling more effective detection of key information and creating new possibilities for video synopsis. To summarize recent progress and accelerate research in this field,this paper provides a comprehensive review of deep learningbased video summarization methods developed over the past decade. We begin by examining the research landscape of video abstraction technologies and identifying core challenges in video summarization. Subsequently, we systematically analyze prevailing deep learning frameworks and methodologies employed in current video summarization systems, offering researchers a clear roadmap of the field's evolution. Unlike previous review works,we first classify research papers based on the structural hierarchy of the video(from frame-level to shot-level to video-level),then further categorize them according to the summary backbone model(feature extraction and spatiotemporal modeling).This approach provides a more systematic and hierarchical organization of the documents. Following this comprehensive review,we summarize the benchmark datasets and evaluation metrics commonly employed in the field. Finally, we analyze persistent challenges and propose insightful directions for future research,providing a forward-looking perspective on video summarization technologies. This systematic literature review is of great reference value to new researchers exploring the fields of deep learning and video summarization.
文摘General Information Journal of Chinese Pharmaceutical Sciences(JCPS)is a peer-reviewed bimonthly journal founded in 1992.JCPS has been indexed in the Core Journals of China's science and technology field.At present it has been included by Chemical Abstracts(CA),UIPD,Index of Copurnicus(IC),CABI,SCOPUS,JSTChina,DOAJ,EBSCO,CSTPCD,Chinese Science Citation Database(CSCD),the Chinese National Knowledge Infrastructure(CNKI)and World Journal Clout Index(WJCI)Report.
文摘The Chinese Journal of Natural Medicines(CJNM,ISSN 2095-6975),founded in 2003 and sponsored by China Pharmaceutical University,is a peer-reviewed journal published monthly in print by Science Press and online by Elsevier.CJNM is currently indexed in Science Citation Index Expanded(SCIE),MEDLINE,BIOSIS Previews,BIOSIS Toxicology,CAB Abstracts.
基金This work was supported by the National Natural Science Foundation of China （No.20903104, No.2107320L and No.20733005） and the Chinese Academy of Sciences.
文摘Pentachlorophenol, a widespread environmental pollutant that is possibly carcinogenic to humans, is metabolically oxidized to tetrachloroquinone （TCBQ） which can result in DNA damage. We have investigated the photochemical reaction dynamics of TCBQ with two pyrimidine type nucleobases （thymine and uracil） upon UVA （355 ran） excitation using the technique of nanosecond time-resolved laser flash photolysis. It has been found that 355 nm excitation populates TCBQ molecules to their triplet state 3TCBQ＊, which are highly reactive towards thymine or uracil and undergo two parallel reactions, the hydrogen abstraction and electron transfer, leading to the observed photoproducts of TCBQH. and TCBQ.- in transient absorption spectra. The concomitantly produced nucleobase radicals and radical cations are expected to induce a series of oxidative or strand cleavage damage to DNA afterwards. By characterizing the photochemical hydrogen abstraction and electron transfer reactions, our results provide potentially important molecular reaction mechanisms for understanding the carcinogenic effects of pentachlorophenol and its metabolites TCBQ.
文摘presented The conceptions of abstract default reasoning frameworks （ADRFs） and D-consequence relations are Based on representation properties of D-consequence relations, it proves that any cumulative nonmonotonic consequence relation with the connective-free form can be represented by ADRFs.
文摘Image is an important and creative way to express poets＂ feelings in both Chinese and English poetry. There are concrete representations and abstract concept in image. They are two key notions in Poetics and Aesthetics. This paper is to show the different versions of ＂tress＂ in poems and to explore the exact nature of concepts of sensitive affection in English and Chinese, so as to appreciate the artistic beauty of images.
基金supported by the project “The demonstration system of rich semantic search application in scientific literature” (Grant No. 1734) from the Chinese Academy of Sciences
文摘Purpose:Mo ve recognition in scientific abstracts is an NLP task of classifying sentences of the abstracts into different types of language units.To improve the performance of move recognition in scientific abstracts,a novel model of move recognition is proposed that outperforms the BERT-based method.Design/methodology/approach:Prevalent models based on BERT for sentence classification often classify sentences without considering the context of the sentences.In this paper,inspired by the BERT masked language model(MLM),we propose a novel model called the masked sentence model that integrates the content and contextual information of the sentences in move recognition.Experiments are conducted on the benchmark dataset PubMed 20K RCT in three steps.Then,we compare our model with HSLN-RNN,BERT-based and SciBERT using the same dataset.Findings:Compared with the BERT-based and SciBERT models,the F1 score of our model outperforms them by 4.96%and 4.34%,respectively,which shows the feasibility and effectiveness of the novel model and the result of our model comes closest to the state-of-theart results of HSLN-RNN at present.Research limitations:The sequential features of move labels are not considered,which might be one of the reasons why HSLN-RNN has better performance.Our model is restricted to dealing with biomedical English literature because we use a dataset from PubMed,which is a typical biomedical database,to fine-tune our model.Practical implications:The proposed model is better and simpler in identifying move structures in scientific abstracts and is worthy of text classification experiments for capturing contextual features of sentences.Originality/value:T he study proposes a masked sentence model based on BERT that considers the contextual features of the sentences in abstracts in a new way.The performance of this classification model is significantly improved by rebuilding the input layer without changing the structure of neural networks.
