The rapid development of high-throughput sequencing techniques has led biology into the big-data era.Data analyses using various bioinformatics tools rely on programming and command-line environments,which are challen...The rapid development of high-throughput sequencing techniques has led biology into the big-data era.Data analyses using various bioinformatics tools rely on programming and command-line environments,which are challenging and time-consuming for most wet-lab biologists.Here,we present TBtools(a Toolkit for Biologists integrating various biological data-handling tools),a stand-alone software with a userfriendly interface.The toolkit incorporates over 130 functions,which are designed to meet the increasing demand for big-data analyses,ranging from bulk sequence processing to interactive data visualization.A wide variety of graphs can be prepared in TBtools using a new plotting engine("JIGplot")developed to maximize their interactive ability;this engine allows quick point-and-click modification of almost every graphic feature.TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer.It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.展开更多
A comprehensive but simple-to-use software package called DPS （Data Pro- cessing System） has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics an...A comprehensive but simple-to-use software package called DPS （Data Pro- cessing System） has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical sottware. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology.展开更多
With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society...With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence （AI） has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage： AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the develoDment of Al 2.0 are given.展开更多
Impervious surfaces are the most significant feature of human settlements. Timely, accurate, and frequent information on impervious surfaces is critical in both social-economic and natural environment applications. Ov...Impervious surfaces are the most significant feature of human settlements. Timely, accurate, and frequent information on impervious surfaces is critical in both social-economic and natural environment applications. Over the past 40 years, impervious surface areas in China have grown rapidly. However,annual maps of impervious areas in China with high spatial details do not exist during this period. In this paper, we made use of reliable impervious surface mapping algorithms that we published before and the Google Earth Engine(GEE) platform to address this data gap. With available data in GEE, we were able to map impervious surfaces over the entire country circa 1978, and during 1985–2017 at an annual frequency. The 1978 data were at 60-m resolution, while the 1985–2017 data were in 30-m resolution.For the 30-m resolution data, we evaluated the accuracies for 1985, 1990, 1995, 2000, 2005, 2010, and2015. Overall accuracies reached more than 90%. Our results indicate that the growth of impervious surface in China was not only fast but also considerably exceeding the per capita impervious surface area in developed countries like Japan. The 40-year continuous and consistent impervious surface distribution data in China would generate widespread interests in the research and policy-making community. The impervious surface data can be freely downloaded from http://data.ess.tsinghua.edu.cn.展开更多
Edge detection and enhancement techniques are commonly used in recognizing the edge of geologic bodies using potential field data. We present a new edge recognition technology based on the normalized vertical derivati...Edge detection and enhancement techniques are commonly used in recognizing the edge of geologic bodies using potential field data. We present a new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative which has the functions of both edge detection and enhancement techniques. First, we calculate the total horizontal derivative （THDR） of the potential-field data and then compute the n-order vertical derivative （VDRn） of the THDR. For the n-order vertical derivative, the peak value of total horizontal derivative （PTHDR） is obtained using a threshold value greater than 0. This PTHDR can be used for edge detection. Second, the PTHDR value is divided by the total horizontal derivative and normalized by the maximum value. Finally, we used different kinds of numerical models to verify the effectiveness and reliability of the new edge recognition technology.展开更多
基金This work was funded by the National Key Research and Developmental Program of China(2018YFD1000104)This work is also supported by awards to R.X.,Y.H.,and H.C.from the National Key Research and Developmental Program of China(2017YFD0101702,2018YFD1000500,2019YFD1000500)+4 种基金the National Science Foundation of China(#31872063)the Special Support Program of Guangdong Province(2019TX05N193)the Key-Area Research and Development Program of Guangdong Province(2018B020202011)the Guangzhou Science and Technology Key Project(201804020063)Support to M.H.F.comes from the NSF Faculty Early Career Development Program(IOS-1942437).
文摘The rapid development of high-throughput sequencing techniques has led biology into the big-data era.Data analyses using various bioinformatics tools rely on programming and command-line environments,which are challenging and time-consuming for most wet-lab biologists.Here,we present TBtools(a Toolkit for Biologists integrating various biological data-handling tools),a stand-alone software with a userfriendly interface.The toolkit incorporates over 130 functions,which are designed to meet the increasing demand for big-data analyses,ranging from bulk sequence processing to interactive data visualization.A wide variety of graphs can be prepared in TBtools using a new plotting engine("JIGplot")developed to maximize their interactive ability;this engine allows quick point-and-click modification of almost every graphic feature.TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer.It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
文摘A comprehensive but simple-to-use software package called DPS （Data Pro- cessing System） has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical sottware. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology.
文摘With the popularization of the Intemet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence （AI） has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage： AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the develoDment of Al 2.0 are given.
基金partially supported by the National Research Program of the Ministry of Science and Technology of China(2016YFA0600104)
文摘Impervious surfaces are the most significant feature of human settlements. Timely, accurate, and frequent information on impervious surfaces is critical in both social-economic and natural environment applications. Over the past 40 years, impervious surface areas in China have grown rapidly. However,annual maps of impervious areas in China with high spatial details do not exist during this period. In this paper, we made use of reliable impervious surface mapping algorithms that we published before and the Google Earth Engine(GEE) platform to address this data gap. With available data in GEE, we were able to map impervious surfaces over the entire country circa 1978, and during 1985–2017 at an annual frequency. The 1978 data were at 60-m resolution, while the 1985–2017 data were in 30-m resolution.For the 30-m resolution data, we evaluated the accuracies for 1985, 1990, 1995, 2000, 2005, 2010, and2015. Overall accuracies reached more than 90%. Our results indicate that the growth of impervious surface in China was not only fast but also considerably exceeding the per capita impervious surface area in developed countries like Japan. The 40-year continuous and consistent impervious surface distribution data in China would generate widespread interests in the research and policy-making community. The impervious surface data can be freely downloaded from http://data.ess.tsinghua.edu.cn.
基金supported by the National Science and Technology Major Projects (2008ZX05025)the Project of National Oil and Gas Resources Strategic Constituency Survey and Evaluation of the Ministry of Land and Resources,China (XQ-2007-05)
文摘Edge detection and enhancement techniques are commonly used in recognizing the edge of geologic bodies using potential field data. We present a new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative which has the functions of both edge detection and enhancement techniques. First, we calculate the total horizontal derivative （THDR） of the potential-field data and then compute the n-order vertical derivative （VDRn） of the THDR. For the n-order vertical derivative, the peak value of total horizontal derivative （PTHDR） is obtained using a threshold value greater than 0. This PTHDR can be used for edge detection. Second, the PTHDR value is divided by the total horizontal derivative and normalized by the maximum value. Finally, we used different kinds of numerical models to verify the effectiveness and reliability of the new edge recognition technology.
