the widely discussed study of word class categorization has a long history of more than 2000 years,which is known as the study of the“God Particles”in language.As a typical analytic language,Modern Chinese,due to it...the widely discussed study of word class categorization has a long history of more than 2000 years,which is known as the study of the“God Particles”in language.As a typical analytic language,Modern Chinese,due to its lack of morphological changes,is challenged by a thorny problem of word classes especially when it comes to the criteria for word class identification and the treat⁃ment of multiple class membership.As such,all the controversies eventually give rise to some contradiction and confusion in word class labeling in Modern Chinese and Chinese-English dictionaries.As an important grammatical means in Chinese and the focus of lexicology and rhetorics,total reduplication lexemes serve as an essential part of Chinese-English dictionaries with complex and diverse word classes.Guided by the Two-level Word Class Categorization Theory,this thesis focuses on the word class labeling of total reduplication lexemes in New Century Chinese-English Dictionary(2nd edition)backed by large-scale balanced Modern Chi⁃nese corpora.With an innovative theoretical perspective,this study not only contributes to the word class labeling of total reduplica⁃tion lexemes and even sheds light on the compilation of Chinese-English dictionaries,but also drives the study of Modern Chinese word classes in the long term.展开更多
Thermally activated delayed fluorescence(TADF)molecules have outstanding potential for applications in organic light-emitting diodes(OLEDs).Due to the lack of systematic studies on the correlation between molecular st...Thermally activated delayed fluorescence(TADF)molecules have outstanding potential for applications in organic light-emitting diodes(OLEDs).Due to the lack of systematic studies on the correlation between molecular structure and luminescence properties,TADF molecules are far from meeting the needs of practical applications in terms of variety and number.In this paper,three twisted TADF molecules are studied and their photophysical properties are theoretically predicted based on the thermal vibrational correlation function method combined with multiscale calculations.The results show that all the molecules exhibit fast reverse intersystem crossing(RISC)rates(kRISC),predicting their TADF luminescence properties.In addition,the binding of DHPAzSi as the donor unit with different acceptors can change the dihedral angle between the ground and excited states,and the planarity of the acceptors is positively correlated with the reorganization energy,a property that has a strong influence on the non-radiative process.Furthermore,a decrease in the energy of the molecular charge transfer state and an increase in the kRISC were observed in the films.This study not only provides a reliable explanation for the observed experimental results,but also offers valuable insights that can guide the design of future TADF molecules.展开更多
This case study examines the use of LDOCE4 on CD-ROM in EFL students’writing.Four participants at different proficiency levels were invited to write a composition on a given title.They were then asked to revise their...This case study examines the use of LDOCE4 on CD-ROM in EFL students’writing.Four participants at different proficiency levels were invited to write a composition on a given title.They were then asked to revise their compositions twice,first using the paper dictionary,and secondly using the CD-ROM.Based on a comparison of the two versions,the following conclusions were drawn:1 The CD-ROM is generally more beneficial to EFL students’writing than the paper dictionary.2 Al though the CD-ROM is helpful,it is not a panacea.3 The CD-ROM can provide little help to lower intermediate learners.展开更多
Catalytic ozonation is regarded as a promising technology in the advanced treatment of refractory organic wastewater.Packed-bed reactors are widely used in practical applications due to simple structures,installation ...Catalytic ozonation is regarded as a promising technology in the advanced treatment of refractory organic wastewater.Packed-bed reactors are widely used in practical applications due to simple structures,installation and operation.However,mass transfer of packed-bed reactors is relatively restrained and amplified deviations usually occurred in scale-up application.Herein,a multi-scale packed-bed model of catalytic ozonation was established to guide pilot tests.First,a laboratory-scale test was conducted to obtain kinetic parameters needed for modeling.Then,a multi-scale packed-bed model was developed to research the effects of water distribution structure,catalyst particle size,and hydraulic retention time(HRT)on catalytic ozonation.It was found that the performance of packed bed reactor was increased with evenly distributed water inlet,HRT of 60 min,and catalyst diameter of about 3-7 mm.Last,an optimized reactor was manufactured and a pilot-scale test was conducted to treat kitchen wastewater using catalytic ozonation process.In the pilot-scale test with an ozone dosage of 50 mg/L and HRT of 60 min,the packed-bed reactor filled with catalysts I was able to reduce chemical oxygen demand(COD)from 117 to 59 mg/L.The performance of the catalytic ozonation process in the packed-bed reactor for the advanced treatment of actual kitchen wastewater was investigated via both multi-scale simulation and pilot-scale tests in this study,which provided a practical method for optimizing the reactors of treating refractory organic wastewater.展开更多
Recently, dictionary learning(DL) based methods have been introduced to compressed sensing magnetic resonance imaging(CS-MRI), which outperforms pre-defined analytic sparse priors. However, single-scale trained dictio...Recently, dictionary learning(DL) based methods have been introduced to compressed sensing magnetic resonance imaging(CS-MRI), which outperforms pre-defined analytic sparse priors. However, single-scale trained dictionary directly from image patches is incapable of representing image features from multi-scale, multi-directional perspective, which influences the reconstruction performance. In this paper, incorporating the superior multi-scale properties of uniform discrete curvelet transform(UDCT) with the data matching adaptability of trained dictionaries, we propose a flexible sparsity framework to allow sparser representation and prominent hierarchical essential features capture for magnetic resonance(MR) images. Multi-scale decomposition is implemented by using UDCT due to its prominent properties of lower redundancy ratio, hierarchical data structure, and ease of implementation. Each sub-dictionary of different sub-bands is trained independently to form the multi-scale dictionaries. Corresponding to this brand-new sparsity model, we modify the constraint splitting augmented Lagrangian shrinkage algorithm(C-SALSA) as patch-based C-SALSA(PB C-SALSA) to solve the constraint optimization problem of regularized image reconstruction. Experimental results demonstrate that the trained sub-dictionaries at different scales, enforcing sparsity at multiple scales, can then be efficiently used for MRI reconstruction to obtain satisfactory results with further reduced undersampling rate. Multi-scale UDCT dictionaries potentially outperform both single-scale trained dictionaries and multi-scale analytic transforms. Our proposed sparsity model achieves sparser representation for reconstructed data, which results in fast convergence of reconstruction exploiting PB C-SALSA. Simulation results demonstrate that the proposed method outperforms conventional CS-MRI methods in maintaining intrinsic properties, eliminating aliasing, reducing unexpected artifacts, and removing noise. It can achieve comparable performance of reconstruction with the state-of-the-art methods even under substantially high undersampling factors.展开更多
文摘the widely discussed study of word class categorization has a long history of more than 2000 years,which is known as the study of the“God Particles”in language.As a typical analytic language,Modern Chinese,due to its lack of morphological changes,is challenged by a thorny problem of word classes especially when it comes to the criteria for word class identification and the treat⁃ment of multiple class membership.As such,all the controversies eventually give rise to some contradiction and confusion in word class labeling in Modern Chinese and Chinese-English dictionaries.As an important grammatical means in Chinese and the focus of lexicology and rhetorics,total reduplication lexemes serve as an essential part of Chinese-English dictionaries with complex and diverse word classes.Guided by the Two-level Word Class Categorization Theory,this thesis focuses on the word class labeling of total reduplication lexemes in New Century Chinese-English Dictionary(2nd edition)backed by large-scale balanced Modern Chi⁃nese corpora.With an innovative theoretical perspective,this study not only contributes to the word class labeling of total reduplica⁃tion lexemes and even sheds light on the compilation of Chinese-English dictionaries,but also drives the study of Modern Chinese word classes in the long term.
文摘Thermally activated delayed fluorescence(TADF)molecules have outstanding potential for applications in organic light-emitting diodes(OLEDs).Due to the lack of systematic studies on the correlation between molecular structure and luminescence properties,TADF molecules are far from meeting the needs of practical applications in terms of variety and number.In this paper,three twisted TADF molecules are studied and their photophysical properties are theoretically predicted based on the thermal vibrational correlation function method combined with multiscale calculations.The results show that all the molecules exhibit fast reverse intersystem crossing(RISC)rates(kRISC),predicting their TADF luminescence properties.In addition,the binding of DHPAzSi as the donor unit with different acceptors can change the dihedral angle between the ground and excited states,and the planarity of the acceptors is positively correlated with the reorganization energy,a property that has a strong influence on the non-radiative process.Furthermore,a decrease in the energy of the molecular charge transfer state and an increase in the kRISC were observed in the films.This study not only provides a reliable explanation for the observed experimental results,but also offers valuable insights that can guide the design of future TADF molecules.
文摘This case study examines the use of LDOCE4 on CD-ROM in EFL students’writing.Four participants at different proficiency levels were invited to write a composition on a given title.They were then asked to revise their compositions twice,first using the paper dictionary,and secondly using the CD-ROM.Based on a comparison of the two versions,the following conclusions were drawn:1 The CD-ROM is generally more beneficial to EFL students’writing than the paper dictionary.2 Al though the CD-ROM is helpful,it is not a panacea.3 The CD-ROM can provide little help to lower intermediate learners.
基金supported by the“Explorer 100”cluster system of Tsinghua HPC Platform.
文摘Catalytic ozonation is regarded as a promising technology in the advanced treatment of refractory organic wastewater.Packed-bed reactors are widely used in practical applications due to simple structures,installation and operation.However,mass transfer of packed-bed reactors is relatively restrained and amplified deviations usually occurred in scale-up application.Herein,a multi-scale packed-bed model of catalytic ozonation was established to guide pilot tests.First,a laboratory-scale test was conducted to obtain kinetic parameters needed for modeling.Then,a multi-scale packed-bed model was developed to research the effects of water distribution structure,catalyst particle size,and hydraulic retention time(HRT)on catalytic ozonation.It was found that the performance of packed bed reactor was increased with evenly distributed water inlet,HRT of 60 min,and catalyst diameter of about 3-7 mm.Last,an optimized reactor was manufactured and a pilot-scale test was conducted to treat kitchen wastewater using catalytic ozonation process.In the pilot-scale test with an ozone dosage of 50 mg/L and HRT of 60 min,the packed-bed reactor filled with catalysts I was able to reduce chemical oxygen demand(COD)from 117 to 59 mg/L.The performance of the catalytic ozonation process in the packed-bed reactor for the advanced treatment of actual kitchen wastewater was investigated via both multi-scale simulation and pilot-scale tests in this study,which provided a practical method for optimizing the reactors of treating refractory organic wastewater.
基金Project supported by the National Natural Science Foundation of China(Nos.61175012 and 61201422)the Natural Science Foundation of Gansu Province of China(No.1208RJ-ZA265)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.2011021111-0026)the Fundamental Research Funds for the Central Universities of China(Nos.lzujbky-2015-108 and lzujbky-2015-197)
文摘Recently, dictionary learning(DL) based methods have been introduced to compressed sensing magnetic resonance imaging(CS-MRI), which outperforms pre-defined analytic sparse priors. However, single-scale trained dictionary directly from image patches is incapable of representing image features from multi-scale, multi-directional perspective, which influences the reconstruction performance. In this paper, incorporating the superior multi-scale properties of uniform discrete curvelet transform(UDCT) with the data matching adaptability of trained dictionaries, we propose a flexible sparsity framework to allow sparser representation and prominent hierarchical essential features capture for magnetic resonance(MR) images. Multi-scale decomposition is implemented by using UDCT due to its prominent properties of lower redundancy ratio, hierarchical data structure, and ease of implementation. Each sub-dictionary of different sub-bands is trained independently to form the multi-scale dictionaries. Corresponding to this brand-new sparsity model, we modify the constraint splitting augmented Lagrangian shrinkage algorithm(C-SALSA) as patch-based C-SALSA(PB C-SALSA) to solve the constraint optimization problem of regularized image reconstruction. Experimental results demonstrate that the trained sub-dictionaries at different scales, enforcing sparsity at multiple scales, can then be efficiently used for MRI reconstruction to obtain satisfactory results with further reduced undersampling rate. Multi-scale UDCT dictionaries potentially outperform both single-scale trained dictionaries and multi-scale analytic transforms. Our proposed sparsity model achieves sparser representation for reconstructed data, which results in fast convergence of reconstruction exploiting PB C-SALSA. Simulation results demonstrate that the proposed method outperforms conventional CS-MRI methods in maintaining intrinsic properties, eliminating aliasing, reducing unexpected artifacts, and removing noise. It can achieve comparable performance of reconstruction with the state-of-the-art methods even under substantially high undersampling factors.
