Topography-induced potential vorticity （PV） banners over a mesoscale topography （Dabie Mountain, hereafter DM） in eastern China, under an idealized dry adiabatic flow, are studied with a mesoscale numerical model,...Topography-induced potential vorticity （PV） banners over a mesoscale topography （Dabie Mountain, hereafter DM） in eastern China, under an idealized dry adiabatic flow, are studied with a mesoscale numerical model, ARPS. PV banners generate over the leeside of the DM with a maximal intensity of ～1.5 PVU, and extend more than 100 km downstream, while the width varies from several to tens of kilometers, which contrasts with the half-width of the peaks along the ridge of the DM. Wave breaking occurs near the leeside surface of the DM, and leads to a strong PV generation. Combining with the PV generation, due to the friction and the flow splitting upstream, the PV is advected downstream, and then forms the PV banners over the DM. The PV banners are sensitive to the model resolution, Coriolis force, friction, subgrid turbulent mixing, stratification, the upstream wind speed and wind direction. The negative PV banners have a more compact connection with the low level turbulent kinetic energy. The PV banners are built up by the baroclinic and barotropic components. The barotropic-associated PV can identify the distribution of the PV banners, while the baroclinic one only has important contributions on the flanks and on the leeside near the topography. PV fluxes are diagnosed to investigate the influence of friction on the PV banners. Similar patterns are found between the total PV flux and the advective PV flux, except near the surface and inside the dipole of the PV banners, where the nonadvective PV flux associated with the friction has a net negative contribution.展开更多
As China＇s convention and exhibition industry strides forward to internationalization, Chinese-English translation of banners for conventions and exhibitions is more frequent than ever before. Based on Vermeer＇s sko...As China＇s convention and exhibition industry strides forward to internationalization, Chinese-English translation of banners for conventions and exhibitions is more frequent than ever before. Based on Vermeer＇s skopos theory, the core theory of functionalist approaches, the paper analyzes authentic examples and highlights the techniques of translation for this type. With representative examples, the paper illustrates the necessity of adopting skopos theory in Chinese-English translation of banners for conventions and exhibitions.展开更多
Machine learning(ML)efficiently and accurately processes dense seismic array data,improving earthquake catalog creation,which is crucial for understanding earthquake sequences and fault systems;analyzing its reliabili...Machine learning(ML)efficiently and accurately processes dense seismic array data,improving earthquake catalog creation,which is crucial for understanding earthquake sequences and fault systems;analyzing its reliability is also essential.An M5.8 earthquake struck Alxa Left Banner,Inner Mongolia,China on April 15,2015,a region with limited CENC monitoring capabilities,making analysis challenging.However,abundant data from ChinArray provided valuable observations for assessing the event.This study leveraged ChinArray data from the 2015 Alxa Left Banner earthquake sequence,employing machine learning(specifically PhaseNet,a deep learning method,and GaMMA,a Bayesian approach)for automated seismic phase picking,association,and location analysis.Our generated catalog,comprising 10,432 phases from 708 events,is roughly ten times larger than the CENC catalog,encompassing all CENC events with strong consistency.A slight magnitude overestimation is observed only at lower magnitudes.Furthermore,the catalog adheres to the Gutenberg-Richter and Omori laws spatially,temporally,and in magnitude distribution,demonstrating its high reliability.Double-difference tomography refined locations for 366 events,yielding a more compact spatial distribution with horizontal errors within 100m,vertical errors within 300m,and travel-time residuals within 0.05s.Depths predominantly range from 10-30km.Aftershocks align primarily NEE,with the mainshock east of the aftershock zone.The near-vertical main fault plane dips northwestward,exhibiting a Y-shaped branching structure,converging at depth and expanding towards the surface.FOCMEC analysis,using first motion and amplitude ratios,yielded focal mechanism solutions for 10 events,including the mainshock.These solutions consistently indicate a strike-slip mechanism with a minor extensional component.Integrating the earthquake sequence's spatial distribution and focal mechanisms suggests the seismogenic structure is a negative flower structure,consistent with the Dengkou-Benjing fault.Comparing the CENC and ML-generated catalogs using the maximum curvature(MAXC)method reveals a 0.6 decrease in completeness magnitude(M_(C)).However,magnitude-frequency distribution discrepancies above the MAXC-estimated M_(C)suggest MAXC may underestimate both M_(C)and the b-value.This study analyzes the 2015 Alxa Left Banner M5.8 earthquake using a reliable,MLgenerated earthquake catalog,revealing detailed information about the sequence,faulting structure,aftershock distribution,and stress characteristics.展开更多
Urban squares are significant nodes of urban spaces, which should be able to improve urban ecological environment and provide residents with outdoor activity spaces. The authors studied some excellent square designs i...Urban squares are significant nodes of urban spaces, which should be able to improve urban ecological environment and provide residents with outdoor activity spaces. The authors studied some excellent square designs in Inner Mongolia, China and even overseas countries, summarized the standards of "best urban squares" in vision, culture, craft, human-concerned design, science and technology, and then applied such standards in the landscape design of Central Plaza in Zhungeer Banner. Through analyzing surrounding environment and constructions, design schemes with regional and cultural features were created to provide references for designing better green square landscapes which can demonstrate local cultural context and regional cultures, are moderate in size, diversified in spatial form and closely integrated with the social life of citizens.展开更多
In the contemporary world, digital content that is subject to copyright is facing significant challenges against the act of copyright infringement.Billions of dollars are lost annually because of this illegal act. The...In the contemporary world, digital content that is subject to copyright is facing significant challenges against the act of copyright infringement.Billions of dollars are lost annually because of this illegal act. The currentmost effective trend to tackle this problem is believed to be blocking thosewebsites, particularly through affiliated government bodies. To do so, aneffective detection mechanism is a necessary first step. Some researchers haveused various approaches to analyze the possible common features of suspectedpiracy websites. For instance, most of these websites serve online advertisement, which is considered as their main source of revenue. In addition, theseadvertisements have some common attributes that make them unique ascompared to advertisements posted on normal or legitimate websites. Theyusually encompass keywords such as click-words (words that redirect to installmalicious software) and frequently used words in illegal gambling, illegal sexual acts, and so on. This makes them ideal to be used as one of the key featuresin the process of successfully detecting websites involved in the act of copyrightinfringement. Research has been conducted to identify advertisements servedon suspected piracy websites. However, these studies use a static approachthat relies mainly on manual scanning for the aforementioned keywords. Thisbrings with it some limitations, particularly in coping with the dynamic andever-changing behavior of advertisements posted on these websites. Therefore,we propose a technique that can continuously fine-tune itself and is intelligentenough to effectively identify advertisement (Ad) banners extracted fromsuspected piracy websites. We have done this by leveraging the power ofmachine learning algorithms, particularly the support vector machine with theword2vec word-embedding model. After applying the proposed technique to1015 Ad banners collected from 98 suspected piracy websites and 90 normal orlegitimate websites, we were able to successfully identify Ad banners extractedfrom suspected piracy websites with an accuracy of 97%. We present thistechnique with the hope that it will be a useful tool for various effective piracywebsite detection approaches. To our knowledge, this is the first approachthat uses machine learning to identify Ad banners served on suspected piracywebsites.展开更多
基金supported bythe National Key Scientific and Technological Project2006BAC02B03, 2004CB418300, GYHY2000706033 under the FANEDD 200325the Specialized Research Fund for the Doctoral Program of Higher Education (No.20080284019)National Natural Science Foundation of China under Grant Nos. 40705019, 40325014 and 40333031
文摘Topography-induced potential vorticity （PV） banners over a mesoscale topography （Dabie Mountain, hereafter DM） in eastern China, under an idealized dry adiabatic flow, are studied with a mesoscale numerical model, ARPS. PV banners generate over the leeside of the DM with a maximal intensity of ～1.5 PVU, and extend more than 100 km downstream, while the width varies from several to tens of kilometers, which contrasts with the half-width of the peaks along the ridge of the DM. Wave breaking occurs near the leeside surface of the DM, and leads to a strong PV generation. Combining with the PV generation, due to the friction and the flow splitting upstream, the PV is advected downstream, and then forms the PV banners over the DM. The PV banners are sensitive to the model resolution, Coriolis force, friction, subgrid turbulent mixing, stratification, the upstream wind speed and wind direction. The negative PV banners have a more compact connection with the low level turbulent kinetic energy. The PV banners are built up by the baroclinic and barotropic components. The barotropic-associated PV can identify the distribution of the PV banners, while the baroclinic one only has important contributions on the flanks and on the leeside near the topography. PV fluxes are diagnosed to investigate the influence of friction on the PV banners. Similar patterns are found between the total PV flux and the advective PV flux, except near the surface and inside the dipole of the PV banners, where the nonadvective PV flux associated with the friction has a net negative contribution.
文摘As China＇s convention and exhibition industry strides forward to internationalization, Chinese-English translation of banners for conventions and exhibitions is more frequent than ever before. Based on Vermeer＇s skopos theory, the core theory of functionalist approaches, the paper analyzes authentic examples and highlights the techniques of translation for this type. With representative examples, the paper illustrates the necessity of adopting skopos theory in Chinese-English translation of banners for conventions and exhibitions.
基金funded by the Inner Mongolia Natural Science Foundation(No.2024MS04021)the Science and Technology Plan of Inner Mongolia Autonomous Region(No.2023YFSH0004)the Director Fund of the Inner Mongolia Autonomous Region Seismological Bureau(No.2023GG01,No.2023GG02,No.2023MS05,No.2023QN13)。
文摘Machine learning(ML)efficiently and accurately processes dense seismic array data,improving earthquake catalog creation,which is crucial for understanding earthquake sequences and fault systems;analyzing its reliability is also essential.An M5.8 earthquake struck Alxa Left Banner,Inner Mongolia,China on April 15,2015,a region with limited CENC monitoring capabilities,making analysis challenging.However,abundant data from ChinArray provided valuable observations for assessing the event.This study leveraged ChinArray data from the 2015 Alxa Left Banner earthquake sequence,employing machine learning(specifically PhaseNet,a deep learning method,and GaMMA,a Bayesian approach)for automated seismic phase picking,association,and location analysis.Our generated catalog,comprising 10,432 phases from 708 events,is roughly ten times larger than the CENC catalog,encompassing all CENC events with strong consistency.A slight magnitude overestimation is observed only at lower magnitudes.Furthermore,the catalog adheres to the Gutenberg-Richter and Omori laws spatially,temporally,and in magnitude distribution,demonstrating its high reliability.Double-difference tomography refined locations for 366 events,yielding a more compact spatial distribution with horizontal errors within 100m,vertical errors within 300m,and travel-time residuals within 0.05s.Depths predominantly range from 10-30km.Aftershocks align primarily NEE,with the mainshock east of the aftershock zone.The near-vertical main fault plane dips northwestward,exhibiting a Y-shaped branching structure,converging at depth and expanding towards the surface.FOCMEC analysis,using first motion and amplitude ratios,yielded focal mechanism solutions for 10 events,including the mainshock.These solutions consistently indicate a strike-slip mechanism with a minor extensional component.Integrating the earthquake sequence's spatial distribution and focal mechanisms suggests the seismogenic structure is a negative flower structure,consistent with the Dengkou-Benjing fault.Comparing the CENC and ML-generated catalogs using the maximum curvature(MAXC)method reveals a 0.6 decrease in completeness magnitude(M_(C)).However,magnitude-frequency distribution discrepancies above the MAXC-estimated M_(C)suggest MAXC may underestimate both M_(C)and the b-value.This study analyzes the 2015 Alxa Left Banner M5.8 earthquake using a reliable,MLgenerated earthquake catalog,revealing detailed information about the sequence,faulting structure,aftershock distribution,and stress characteristics.
基金Supported by Tianjin Municipal Artistic and Scientific Planning Foundation (C08054)~~
文摘Urban squares are significant nodes of urban spaces, which should be able to improve urban ecological environment and provide residents with outdoor activity spaces. The authors studied some excellent square designs in Inner Mongolia, China and even overseas countries, summarized the standards of "best urban squares" in vision, culture, craft, human-concerned design, science and technology, and then applied such standards in the landscape design of Central Plaza in Zhungeer Banner. Through analyzing surrounding environment and constructions, design schemes with regional and cultural features were created to provide references for designing better green square landscapes which can demonstrate local cultural context and regional cultures, are moderate in size, diversified in spatial form and closely integrated with the social life of citizens.
基金This research project was supported by the Ministry of Culture,Sports,and Tourism(MCST)and the Korea Copyright Commission in 2021(2019-PF-9500).
文摘In the contemporary world, digital content that is subject to copyright is facing significant challenges against the act of copyright infringement.Billions of dollars are lost annually because of this illegal act. The currentmost effective trend to tackle this problem is believed to be blocking thosewebsites, particularly through affiliated government bodies. To do so, aneffective detection mechanism is a necessary first step. Some researchers haveused various approaches to analyze the possible common features of suspectedpiracy websites. For instance, most of these websites serve online advertisement, which is considered as their main source of revenue. In addition, theseadvertisements have some common attributes that make them unique ascompared to advertisements posted on normal or legitimate websites. Theyusually encompass keywords such as click-words (words that redirect to installmalicious software) and frequently used words in illegal gambling, illegal sexual acts, and so on. This makes them ideal to be used as one of the key featuresin the process of successfully detecting websites involved in the act of copyrightinfringement. Research has been conducted to identify advertisements servedon suspected piracy websites. However, these studies use a static approachthat relies mainly on manual scanning for the aforementioned keywords. Thisbrings with it some limitations, particularly in coping with the dynamic andever-changing behavior of advertisements posted on these websites. Therefore,we propose a technique that can continuously fine-tune itself and is intelligentenough to effectively identify advertisement (Ad) banners extracted fromsuspected piracy websites. We have done this by leveraging the power ofmachine learning algorithms, particularly the support vector machine with theword2vec word-embedding model. After applying the proposed technique to1015 Ad banners collected from 98 suspected piracy websites and 90 normal orlegitimate websites, we were able to successfully identify Ad banners extractedfrom suspected piracy websites with an accuracy of 97%. We present thistechnique with the hope that it will be a useful tool for various effective piracywebsite detection approaches. To our knowledge, this is the first approachthat uses machine learning to identify Ad banners served on suspected piracywebsites.
