We report comprehensive angle-resolved photoemission investigations on the electronic structures and nematicity of the parent compounds of the iron-based superconductors including CeFeAsO, BaFe2As2, NaFeAs, FeSe and u...We report comprehensive angle-resolved photoemission investigations on the electronic structures and nematicity of the parent compounds of the iron-based superconductors including CeFeAsO, BaFe2As2, NaFeAs, FeSe and undoped FeSe/SrTiO3 films with 1, 2 and 20 layers. While the electronic structure near tile Brillouin zone center F varies dramatically among different materials, the electronic structure near the Brillouin zone corners （M points）, as well as their temperature dependence, are rather similar. The electronic structure near the zone corners is dominated by the electronic nematicity that gives rise to a band splitting of the dxz and dyz bands below the nematie transition temperature. A clear relation is observed between the band splitting magnitude arid the onset temperature of nematicity. Our results may shed light on the origin of nematicity, its effect on the electronic structures, and its relation with superconductivity in the iron-based superconductors.展开更多
Film is an art manifestation which originated from daily life.Besides it is also a mental product conveyed with various kinds of cultural,political,ideological elements.Film title,as the name card to a film,is short i...Film is an art manifestation which originated from daily life.Besides it is also a mental product conveyed with various kinds of cultural,political,ideological elements.Film title,as the name card to a film,is short in form but rich in meaning,has its own linguistic,cultural,aesthetic and commercial features.Film title translation is a unique field of translation practice but far less explored.In this essay,the author tries to explain the features and functions of film title with cases and provides a scan of film title translation study at home in order to assist translators to find the major difficulties in film title translation and to improve the overall quality of film title translation in the market.展开更多
A groundbreaking method is introduced to leverage machine learn-ing algorithms to revolutionize the prediction of success rates for science fiction films.In the captivating world of the film industry,extensive researc...A groundbreaking method is introduced to leverage machine learn-ing algorithms to revolutionize the prediction of success rates for science fiction films.In the captivating world of the film industry,extensive research and accurate forecasting are vital to anticipating a movie’s triumph prior to its debut.Our study aims to harness the power of available data to estimate a film’s early success rate.With the vast resources offered by the internet,we can access a plethora of movie-related information,including actors,directors,critic reviews,user reviews,ratings,writers,budgets,genres,Facebook likes,YouTube views for movie trailers,and Twitter followers.The first few weeks of a film’s release are crucial in determining its fate,and online reviews and film evaluations profoundly impact its opening-week earnings.Hence,our research employs advanced supervised machine learning techniques to predict a film’s triumph.The Internet Movie Database(IMDb)is a comprehensive data repository for nearly all movies.A robust predictive classification approach is developed by employing various machine learning algorithms,such as fine,medium,coarse,cosine,cubic,and weighted KNN.To determine the best model,the performance of each feature was evaluated based on composite metrics.Moreover,the significant influences of social media platforms were recognized including Twitter,Instagram,and Facebook on shaping individuals’opinions.A hybrid success rating prediction model is obtained by integrating the proposed prediction models with sentiment analysis from available platforms.The findings of this study demonstrate that the chosen algorithms offer more precise estimations,faster execution times,and higher accuracy rates when compared to previous research.By integrating the features of existing prediction models and social media sentiment analysis models,our proposed approach provides a remarkably accurate prediction of a movie’s success.This breakthrough can help movie producers and marketers anticipate a film’s triumph before its release,allowing them to tailor their promotional activities accordingly.Furthermore,the adopted research lays the foundation for developing even more accurate prediction models,considering the ever-increasing significance of social media platforms in shaping individ-uals’opinions.In conclusion,this study showcases the immense potential of machine learning algorithms in predicting the success rate of science fiction films,opening new avenues for the film industry.展开更多
The PZT thin films were prepared on （111）- Pt/Ti/SiO2/Si substrates by sol-gel method, and lead acetate [Pb（CH3COO）2], zirconium nitrate [Zr（NO3）4] were used as raw materials. The X-ray diffractometer （XRD） an...The PZT thin films were prepared on （111）- Pt/Ti/SiO2/Si substrates by sol-gel method, and lead acetate [Pb（CH3COO）2], zirconium nitrate [Zr（NO3）4] were used as raw materials. The X-ray diffractometer （XRD） and scanning electron microscopy （SEM） were used to characterize the phase structure and surface morphology of the films annealed at 650 ~C but with different holding time. Ferroelectric and dielectric properties of the films were measured by the ferroelectric tester and the precision impedance analyzer, respectively. The PZT thin films were constructed with epoxy resin as a composite structure, and the damping properties of the composite were tested by dynamic mechanical analyzer （DMA）. The results show that the films annealed for 90 minutes present a dense and compact crystal arrangement on the surface; moreover, the films also achieve their best electric quality. At the same time, the largest damping loss factor of the composite constructed with the 90 mins-annealed film shows peak value of 0.9, hi^her than the pure epoxy resin.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 11190022,11334010 and 11534007the National Basic Research Program of China under Grant No 2015CB921000the Strategic Priority Research Program(B)of Chinese Academy of Sciences under Grant No XDB07020300
文摘We report comprehensive angle-resolved photoemission investigations on the electronic structures and nematicity of the parent compounds of the iron-based superconductors including CeFeAsO, BaFe2As2, NaFeAs, FeSe and undoped FeSe/SrTiO3 films with 1, 2 and 20 layers. While the electronic structure near tile Brillouin zone center F varies dramatically among different materials, the electronic structure near the Brillouin zone corners （M points）, as well as their temperature dependence, are rather similar. The electronic structure near the zone corners is dominated by the electronic nematicity that gives rise to a band splitting of the dxz and dyz bands below the nematie transition temperature. A clear relation is observed between the band splitting magnitude arid the onset temperature of nematicity. Our results may shed light on the origin of nematicity, its effect on the electronic structures, and its relation with superconductivity in the iron-based superconductors.
文摘Film is an art manifestation which originated from daily life.Besides it is also a mental product conveyed with various kinds of cultural,political,ideological elements.Film title,as the name card to a film,is short in form but rich in meaning,has its own linguistic,cultural,aesthetic and commercial features.Film title translation is a unique field of translation practice but far less explored.In this essay,the author tries to explain the features and functions of film title with cases and provides a scan of film title translation study at home in order to assist translators to find the major difficulties in film title translation and to improve the overall quality of film title translation in the market.
文摘A groundbreaking method is introduced to leverage machine learn-ing algorithms to revolutionize the prediction of success rates for science fiction films.In the captivating world of the film industry,extensive research and accurate forecasting are vital to anticipating a movie’s triumph prior to its debut.Our study aims to harness the power of available data to estimate a film’s early success rate.With the vast resources offered by the internet,we can access a plethora of movie-related information,including actors,directors,critic reviews,user reviews,ratings,writers,budgets,genres,Facebook likes,YouTube views for movie trailers,and Twitter followers.The first few weeks of a film’s release are crucial in determining its fate,and online reviews and film evaluations profoundly impact its opening-week earnings.Hence,our research employs advanced supervised machine learning techniques to predict a film’s triumph.The Internet Movie Database(IMDb)is a comprehensive data repository for nearly all movies.A robust predictive classification approach is developed by employing various machine learning algorithms,such as fine,medium,coarse,cosine,cubic,and weighted KNN.To determine the best model,the performance of each feature was evaluated based on composite metrics.Moreover,the significant influences of social media platforms were recognized including Twitter,Instagram,and Facebook on shaping individuals’opinions.A hybrid success rating prediction model is obtained by integrating the proposed prediction models with sentiment analysis from available platforms.The findings of this study demonstrate that the chosen algorithms offer more precise estimations,faster execution times,and higher accuracy rates when compared to previous research.By integrating the features of existing prediction models and social media sentiment analysis models,our proposed approach provides a remarkably accurate prediction of a movie’s success.This breakthrough can help movie producers and marketers anticipate a film’s triumph before its release,allowing them to tailor their promotional activities accordingly.Furthermore,the adopted research lays the foundation for developing even more accurate prediction models,considering the ever-increasing significance of social media platforms in shaping individ-uals’opinions.In conclusion,this study showcases the immense potential of machine learning algorithms in predicting the success rate of science fiction films,opening new avenues for the film industry.
基金Supported by the National Natural Science Foundation of China (No. 50772083)China-Japan Cooperation Program(No. 2010DFA51270)the Fundamental Research Funds for the Central Universities
文摘The PZT thin films were prepared on （111）- Pt/Ti/SiO2/Si substrates by sol-gel method, and lead acetate [Pb（CH3COO）2], zirconium nitrate [Zr（NO3）4] were used as raw materials. The X-ray diffractometer （XRD） and scanning electron microscopy （SEM） were used to characterize the phase structure and surface morphology of the films annealed at 650 ~C but with different holding time. Ferroelectric and dielectric properties of the films were measured by the ferroelectric tester and the precision impedance analyzer, respectively. The PZT thin films were constructed with epoxy resin as a composite structure, and the damping properties of the composite were tested by dynamic mechanical analyzer （DMA）. The results show that the films annealed for 90 minutes present a dense and compact crystal arrangement on the surface; moreover, the films also achieve their best electric quality. At the same time, the largest damping loss factor of the composite constructed with the 90 mins-annealed film shows peak value of 0.9, hi^her than the pure epoxy resin.
