Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to asse...Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to assess this complex toxicity endpoint and will be valuable for screening emerging pollutants as well as for m anaging new chemicals in China.Currently,there are few published DART prediction models in China,but many related research and development projects are in progress.In 2013,WU et al.published an expert rule-based DART decision tree(DT).This DT relies on known chemical structures linked to DART to forecast DART potential of a given chemical.Within this procedure,an accurate DART data interpretation is the foundation of building and expanding the DT.This paper excerpted case studies demonstrating DART data curation and interpretation of four chemicals(including 8-hydroxyquinoline,3,5,6-trichloro-2-pyridinol,thiacloprid,and imidacloprid)to expand the existing DART DT.Chemicals were first selected from the database of Solid Waste and Chemicals Management Center,Ministry of Ecology and Environment(MEESCC)in China.The structures of these 4 chemicals were analyzed and preliminarily grouped by chemists based on core structural features,functional groups,receptor binding property,metabolism,and possible mode of actions.Then,the DART conclusion was derived by collecting chemical information,searching,integrating,and interpreting DART data by the toxicologists.Finally,these chemicals were classified into either an existing category or a new category via integrating their chemical features,DART conclusions,and biological properties.The results showed that 8-hydroxyquinoline impacted estrous cyclicity,s exual organ weights,and embryonal development,and 3,5,6-trichloro-2-pyridinol caused central nervous system(CNS)malformations,which were added to an existing subcategory 8e(aromatic compounds with multi-halogen and nitro groups)of the DT.Thiacloprid caused dystocia and fetal skeletal malformation,and imidacloprid disrupted the endocrine system and male fertility.They both contain 2-chloro-5-methylpyridine substituted imidazolidine c yclic ring,which were expected to create a new category of neonicotinoids.The current work delineates a t ransparent process of curating toxicological data for the purpose of DART data interpretation.In the presence of sufficient related structures and DART data,the DT can be expanded by iteratively adding chemicals within the a pplicable domain of each category or subcategory.This DT can potentially serve as a tool for screening emerging pollutants and assessing new chemicals in China.展开更多
To ensure the dimensional accuracy of the final blade profile,it is necessary for precision Electrochemical Machining(ECM)of blade profile to come into an equilibrium state.However,after Electrochemical Trepanning(ECT...To ensure the dimensional accuracy of the final blade profile,it is necessary for precision Electrochemical Machining(ECM)of blade profile to come into an equilibrium state.However,after Electrochemical Trepanning(ECTr),the cascade channel of the blisk is narrow,and the blank allowance distribution is uneven,making it difficult for the precision ECM to become balanced.In blisk production,the two-step method cannot make precision ECM enter equilibrium for some blisk types.A three-step processing method is proposed to overcome this problem.The threestep method adds Electrochemical Homogenizing Machining(ECHM)between the ECTr and precision ECM steps so that the blank allowance can be homogenized quickly without unduly affecting the minimum allowance.Comparative machining experiments of the two-and three-step methods were performed to verify the improvement to blade machining accuracy.The processing results show that the contour parameters of the blade after the three-step method implementation are much better.The allowance difference of the concave(convex)side decreased by 70.5%(65%).In addition,the current in the three-step method is stable at 110 A at the end of precision ECM,verifying successfully entering the equilibrium state.展开更多
Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal research.Most of the existing r...Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal research.Most of the existing research works on Legal Judgment Prediction(LJP)use traditional optimization algorithms in deep learning techniques falling into local optimization.This research article focuses on using the modified Pelican Optimization method which mimics the collective behavior of Pelicans in the exploration and exploitation phase during cooperative food searching.Typically,the selection of search agents within a boundary is done randomly,which increases the time required to achieve global optimization.To address this,the proposed Chaotic Opposition Learning-based Pelican Optimization(COLPO)method incorporates the concept of Opposition-Based Learning combined with a chaotic cubic function,enabling deterministic selection of random numbers and reducing the number of iterations needed to reach global optimization.Also,the LJP approach in this work uses improved semantic similarity and entropy features to train a hybrid classifier combining Bi-GRU and Deep Maxout.The output scores are fused using improved score level fusion to boost prediction accuracy.The proposed COLPO method experiments with real-time Madras High Court criminal cases(Dataset 1)and the Supreme Court of India database(Dataset 2),and its performance is compared with nature-inspired algorithms such as Sparrow Search Algorithm(SSA),COOT,Spider Monkey Optimization(SMO),Pelican Optimization Algorithm(POA),as well as baseline classifier models and transformer neural networks.The results show that the proposed hybrid classifier with COLPO outperforms other cutting-edge LJP algorithms achieving 93.4%and 94.24%accuracy,respectively.展开更多
This article utilizes Katherine Mansfield’s short story The Garden Party as the research object to explore the narrative generation conditions of ethical experience in the text. Through a close analysis of the novel...This article utilizes Katherine Mansfield’s short story The Garden Party as the research object to explore the narrative generation conditions of ethical experience in the text. Through a close analysis of the novel’s narrative structure and key scenes, the article argues that ethical discomfort does not evolve into enduring moral judgments within the text;rather, it is continually managed and deferred through the interplay of aesthetic order, familial discourse, and the distribution of social roles. The novel eschews a linear trajectory of ethical awakening, instead crafting a narrative mechanism that keeps ethical experience palpable yet inarticulable. The female subject is given the role of sensing ethical incongruity, but lacks the narrative position from which to articulate it as judgment. Consequently, ethics remains confined to the level of personalization and unimplementability. Far from a narrative of moral growth or awakening, The Garden Party exposes why ethical judgment has become structurally unrealizable in modern narratives.展开更多
文摘Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to assess this complex toxicity endpoint and will be valuable for screening emerging pollutants as well as for m anaging new chemicals in China.Currently,there are few published DART prediction models in China,but many related research and development projects are in progress.In 2013,WU et al.published an expert rule-based DART decision tree(DT).This DT relies on known chemical structures linked to DART to forecast DART potential of a given chemical.Within this procedure,an accurate DART data interpretation is the foundation of building and expanding the DT.This paper excerpted case studies demonstrating DART data curation and interpretation of four chemicals(including 8-hydroxyquinoline,3,5,6-trichloro-2-pyridinol,thiacloprid,and imidacloprid)to expand the existing DART DT.Chemicals were first selected from the database of Solid Waste and Chemicals Management Center,Ministry of Ecology and Environment(MEESCC)in China.The structures of these 4 chemicals were analyzed and preliminarily grouped by chemists based on core structural features,functional groups,receptor binding property,metabolism,and possible mode of actions.Then,the DART conclusion was derived by collecting chemical information,searching,integrating,and interpreting DART data by the toxicologists.Finally,these chemicals were classified into either an existing category or a new category via integrating their chemical features,DART conclusions,and biological properties.The results showed that 8-hydroxyquinoline impacted estrous cyclicity,s exual organ weights,and embryonal development,and 3,5,6-trichloro-2-pyridinol caused central nervous system(CNS)malformations,which were added to an existing subcategory 8e(aromatic compounds with multi-halogen and nitro groups)of the DT.Thiacloprid caused dystocia and fetal skeletal malformation,and imidacloprid disrupted the endocrine system and male fertility.They both contain 2-chloro-5-methylpyridine substituted imidazolidine c yclic ring,which were expected to create a new category of neonicotinoids.The current work delineates a t ransparent process of curating toxicological data for the purpose of DART data interpretation.In the presence of sufficient related structures and DART data,the DT can be expanded by iteratively adding chemicals within the a pplicable domain of each category or subcategory.This DT can potentially serve as a tool for screening emerging pollutants and assessing new chemicals in China.
基金supported by the National Natural Science Foundation of China(No.52075253)the Innovation Research Team of the National Natural Science Foundation of China(No.51921003)。
文摘To ensure the dimensional accuracy of the final blade profile,it is necessary for precision Electrochemical Machining(ECM)of blade profile to come into an equilibrium state.However,after Electrochemical Trepanning(ECTr),the cascade channel of the blisk is narrow,and the blank allowance distribution is uneven,making it difficult for the precision ECM to become balanced.In blisk production,the two-step method cannot make precision ECM enter equilibrium for some blisk types.A three-step processing method is proposed to overcome this problem.The threestep method adds Electrochemical Homogenizing Machining(ECHM)between the ECTr and precision ECM steps so that the blank allowance can be homogenized quickly without unduly affecting the minimum allowance.Comparative machining experiments of the two-and three-step methods were performed to verify the improvement to blade machining accuracy.The processing results show that the contour parameters of the blade after the three-step method implementation are much better.The allowance difference of the concave(convex)side decreased by 70.5%(65%).In addition,the current in the three-step method is stable at 110 A at the end of precision ECM,verifying successfully entering the equilibrium state.
文摘Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal research.Most of the existing research works on Legal Judgment Prediction(LJP)use traditional optimization algorithms in deep learning techniques falling into local optimization.This research article focuses on using the modified Pelican Optimization method which mimics the collective behavior of Pelicans in the exploration and exploitation phase during cooperative food searching.Typically,the selection of search agents within a boundary is done randomly,which increases the time required to achieve global optimization.To address this,the proposed Chaotic Opposition Learning-based Pelican Optimization(COLPO)method incorporates the concept of Opposition-Based Learning combined with a chaotic cubic function,enabling deterministic selection of random numbers and reducing the number of iterations needed to reach global optimization.Also,the LJP approach in this work uses improved semantic similarity and entropy features to train a hybrid classifier combining Bi-GRU and Deep Maxout.The output scores are fused using improved score level fusion to boost prediction accuracy.The proposed COLPO method experiments with real-time Madras High Court criminal cases(Dataset 1)and the Supreme Court of India database(Dataset 2),and its performance is compared with nature-inspired algorithms such as Sparrow Search Algorithm(SSA),COOT,Spider Monkey Optimization(SMO),Pelican Optimization Algorithm(POA),as well as baseline classifier models and transformer neural networks.The results show that the proposed hybrid classifier with COLPO outperforms other cutting-edge LJP algorithms achieving 93.4%and 94.24%accuracy,respectively.
文摘This article utilizes Katherine Mansfield’s short story The Garden Party as the research object to explore the narrative generation conditions of ethical experience in the text. Through a close analysis of the novel’s narrative structure and key scenes, the article argues that ethical discomfort does not evolve into enduring moral judgments within the text;rather, it is continually managed and deferred through the interplay of aesthetic order, familial discourse, and the distribution of social roles. The novel eschews a linear trajectory of ethical awakening, instead crafting a narrative mechanism that keeps ethical experience palpable yet inarticulable. The female subject is given the role of sensing ethical incongruity, but lacks the narrative position from which to articulate it as judgment. Consequently, ethics remains confined to the level of personalization and unimplementability. Far from a narrative of moral growth or awakening, The Garden Party exposes why ethical judgment has become structurally unrealizable in modern narratives.
