Integrated energy distribution system(IEDS)is one of the integrated energy and power system forms,which involves electricity/gas/cold/heat and other various energy forms.The energy coupling relationship is close and c...Integrated energy distribution system(IEDS)is one of the integrated energy and power system forms,which involves electricity/gas/cold/heat and other various energy forms.The energy coupling relationship is close and complex.IEDS is the focus of regional energy internet research and development at home and abroad.Compared with the traditional power distribution system,IEDS through the multi-energy coupling link comprehensive utilization,effectively improve the distribution system economy,safety,reliability,flexibility and toughness,but also to ease the regional energy system environmental pressure.IEDS is an important direction for the future development of energy systems,and its related research and practice on China’s energy system development also has important practical and strategic significance.This paper summarizes the related researches of the IEDS and explores the energy operation characteristics and coupling mechanisms.What’s more,the integrated model of IEDS is summarized.On these bases,this paper discusses and prospects some key issues such as joint planning,optimization control and security analysis,state estimation and situational awareness and generalized demand side management.展开更多
The outbreak of the 2019 novel coronavirus disease(COVID-19)has caused more than 100,000 people infected and thousands of deaths.Currently,the number of infections and deaths is still increasing rapidly.COVID-19 serio...The outbreak of the 2019 novel coronavirus disease(COVID-19)has caused more than 100,000 people infected and thousands of deaths.Currently,the number of infections and deaths is still increasing rapidly.COVID-19 seriously threatens human health,production,life,social functioning and international relations.In the fight against COVID-19,Geographic Information Systems(GIS)and big data technologies have played an important role in many aspects,including the rapid aggregation of multi-source big data,rapid visualization of epidemic information,spatial tracking of confirmed cases,prediction of regional transmission,spatial segmentation of the epidemic risk and prevention level,balancing and management of the supply and demand of material resources,and socialemotional guidance and panic elimination,which provided solid spatial information support for decision-making,measures formulation,and effectiveness assessment of COVID-19 prevention and control.GIS has developed and matured relatively quickly and has a complete technological route for data preparation,platform construction,model construction,and map production.However,for the struggle against the widespread epidemic,the main challenge is finding strategies to adjust traditional technical methods and improve speed and accuracy of information provision for social management.At the data level,in the era of big data,data no longer come mainly from the government but are gathered from more diverse enterprises.As a result,the use of GIS faces difficulties in data acquisition and the integration of heterogeneous data,which requires governments,businesses,and academic institutions to jointly promote the formulation of relevant policies.At the technical level,spatial analysis methods for big data are in the ascendancy.Currently and for a long time in the future,the development of GIS should be strengthened to form a data-driven system for rapid knowledge acquisition,which signifies ts that GIS should be used to reinforce the social operation parameterization of models and 展开更多
Recent advances in systemic and locoregional treatments for patients with unresectable or advanced hepatocellular carcinoma(HCC)have resulted in improved response rates.This has provided an opportunity for selected pa...Recent advances in systemic and locoregional treatments for patients with unresectable or advanced hepatocellular carcinoma(HCC)have resulted in improved response rates.This has provided an opportunity for selected patients with initially unresectable HCC to achieve adequate tumor downstaging to undergo surgical resection,a‘conversion therapy’strategy.However,conversion therapy is a new approach to the treatment of HCC and its practice and treatment protocols are still being developed.Review the evidence for conversion therapy in HCC and develop consensus statements to guide clinical practice.Evidence review:Many research centers in China have accumulated significant experience implementing HCC conversion therapy.Preliminary findings and data have shown that conversion therapy represents an important strategy to maximize the survival of selected patients with intermediate stage to advanced HCC;however,there are still many urgent clinical and scientific challenges for this therapeutic strategy and its related fields.In order to summarize and learn from past experience and review current challenges,the Chinese Expert Consensus on Conversion Therapy for Hepatocellular Carcinoma(2021 Edition)was developed based on a review of preliminary experience and clinical data from Chinese and non-Chinese studies in this field and combined with recommendations for clinical practice.Sixteen consensus statements on the implementation of conversion therapy for HCC were developed.The statements generated in this review are based on a review of clinical evidence and real clinical experience and will help guide future progress in conversion therapy for patients with HCC.展开更多
The aim of this study was to establish a method for discriminating Dendrobium officinale from four of its close relatives Den- drobium chrysanthum, Dendrobium erystallinum, Dendrobium aphyllum and Dendrobium devonianu...The aim of this study was to establish a method for discriminating Dendrobium officinale from four of its close relatives Den- drobium chrysanthum, Dendrobium erystallinum, Dendrobium aphyllum and Dendrobium devonianum based on chemical composition analysis. We analyzed 62 samples of 24 Dendrobium species. High performance liquid chromatography analysis confirmed that the four low molecular weight compounds 4＇,5,7-trihydroxyflavanone （naringenin）, 3,4-dihydroxy-4＇,5-dime- tboxybibenzyl （DDB^2）, 3＇,4-dihydroxy-3,5＇-dimethoxybibenzyl （gigantol）, and 4,4＇-dihydroxy-3,3＇,5-trimethoxybibenzyl （moscatilin）, were common in the genus. The phenol-sulfuric acid method was used to quantify polysaccharides, and the mon- osaccharide composition of the polysaccharides was determined by gas chromatography. Stepwise discriminant analysis was used to differentiate among the five closely related species based on the chemical composition analysis. This proved to be a simple and accurate approach for discriminating among these species. The results also showed that the polysaccharide content, the amounts of the four low molecular weight compounds, and the mannose to glucose ratio, were important factors for species discriminaut. Therefore, we propose that a chemical analysis based on quantification of naringenin, bibenzyl, and polysaccha- rides is effective for identifying D. officinale.展开更多
目的以导管测量血流储备分数(FFR)为金标准,评价基于血流动力学优化融合模型的CT血流储备分数(CT-FFR)对冠状动脉狭窄所致心肌缺血病变的诊断效能。方法前瞻性选择127例接受冠状动脉CT血管成像(CCTA)、1周内冠状动脉造影及经导管FFR测...目的以导管测量血流储备分数(FFR)为金标准,评价基于血流动力学优化融合模型的CT血流储备分数(CT-FFR)对冠状动脉狭窄所致心肌缺血病变的诊断效能。方法前瞻性选择127例接受冠状动脉CT血管成像(CCTA)、1周内冠状动脉造影及经导管FFR测量患者(152支血管),以CCTA观察病变狭窄程度,计算CT-FFR。以FFR<0.8为判断心肌缺血金标准,绘制CT-FFR及CCTA的ROC曲线,获得AUC。计算两种方法诊断心肌缺血的敏感度、特异度、阳性预测值、阴性预测值及准确率。结果 CT-FFR与导管测量FFR一致性良好,仅6.6%测量值在95%一致性界限之外。CT-FFR诊断心肌缺血AUC在患者水平(0.92 vs 0.69,P<0.001)和血管水平(0.93 vs 0.69,P<0.001)均优于CCTA。以患者水平CT-FFR<0.8诊断心肌缺血的敏感度、特异度和准确率分别为84.1%、90.6%和85.8%,CCTA>50%分别为82.5%、54.7%和68.5%;血管水平CT-FFR<0.8分别为88.0%、84.7%和84.9%,CCTA>50%分别为80.6%、57.7%和69.1%。CT-FFR对于血管水平狭窄程度30%~70%病变诊断效能仍佳。结论 CT-FFR对心肌缺血病变的诊断效能优于CCTA,有助于临床筛查心肌缺血病变。展开更多
This paper reports the variation rules for the typomorphic parameters of the pyrite and the gold enrichment rules of the Denggezhuang quartz vein gold deposit at a large-depth scale, providing the mineral signs for de...This paper reports the variation rules for the typomorphic parameters of the pyrite and the gold enrichment rules of the Denggezhuang quartz vein gold deposit at a large-depth scale, providing the mineral signs for deep prospecting prediction through detailed study of the characteristics of crystal＇ habits, chemical composition, the thermoelectricity of pyrites, and min- eralogical mapping. This paper primarily discusses the correlation between the mineralization intensity and the space-time evolution of the mineralogical parameters, clarifies the physicochemical conditions during gold mineralization, and provides information useful for deep mineralization prediction. We demonstrate that the crystal habits of the pyrites are very complex, primarily occurring as （ 100）, （210）, and their combinate form. （210） and （ 100）＋（210） have positive correlations with gold mineralization, and （ 100）＋（210） therefore can be useful for locating rich ore segments. The composition of pyrites is charac- teristically poor in S and rich in As. Their typical trace elements are composed of Mo, As, Pb, Cu, Bi, Zn, Au, Co, Se, Sb, Ag, Ni, Cr, and Te. The average contents of trace elements in pyrites from various stages show that the crystallizing temperature gradually decreased from an early stage to the metallogenic episodes. The precipitation and accumulation of Au and Ag occur primarily in the quartz-pyrite stage （III） and the polymetal minerals stage （IV）. The occurrence rate of P-type pyrites （P（%）） is 83.52%. There is a larger dispersion of the thermoelectrical coefficient of pyrite （a） in the Denggezhuang gold deposit than in other deposits in the Jiaodong Peninsula. The electrical conductivity assemblage of pyrites from I to V is characterized by P〉N〉P〉N〉P〉〉N〉P〉〉N〉P〉N, which is usually considered beneficial for mineralization. The relative contents of As＋Sb＋Se＋Te and Co＋Ni are closely correlated to P-type and N-type average values and their occurr展开更多
Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the m...Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means.It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph.Based on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists.We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among others.It will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research.展开更多
With the development of earth observation technologies,the acquired remote sensing images are increasing dramatically,and a new era of big data in remote sensing is coming.How to effectively mine these massive volumes...With the development of earth observation technologies,the acquired remote sensing images are increasing dramatically,and a new era of big data in remote sensing is coming.How to effectively mine these massive volumes of remote sensing data are new challenges.Deep learning provides a new approach for analyzing these remote sensing data.As one of the deep learning models,convolutional neural networks(CNNs)can directly extract features from massive amounts of imagery data and is good at exploiting semantic features of imagery data.CNNs have achieved remarkable success in computer vision.In recent years,quite a few researchers have studied remote sensing image classification using CNNs,and CNNs can be applied to realize rapid,economical and accurate analysis and feature extraction from remote sensing data.This paper aims to provide a survey of the current state-of-the-art application of CNN-based deep learning in remote sensing image classification.We first briefly introduce the principles and characteristics of CNNs.We then survey developments and structural improvements on CNN models that make CNNs more suitable for remote sensing image classification,available datasets for remote sensing image classification,and data augmentation techniques.Then,three typical CNN application cases in remote sensing image classification:scene classification,object detection and object segmentation are presented.We also discuss the problems and challenges of CNN-based remote sensing image classification,and propose corresponding measures and suggestions.We hope that the survey can facilitate the advancement of remote sensing image classification research and help remote-sensing scientists to tackle classification tasks with the state-of-art deep learning algorithms and techniques.展开更多
The turnip(Brassica rapa var. rapa) is a biennial crop that is planted in late summer/early fall and forms fleshy tubers for food in temperate regions. The harvested tubers then overwinter and are planted again the ne...The turnip(Brassica rapa var. rapa) is a biennial crop that is planted in late summer/early fall and forms fleshy tubers for food in temperate regions. The harvested tubers then overwinter and are planted again the next spring for flowering and seeds. FLOWERING LOCUS C(FLC) is a MADS-box transcription factor that acts as a major repressor of floral transition by suppressing the flowering promoters FT and SOC1. Here we show that vernalization effectively represses tuber formation and promotes flowering in Tibetan turnip. We functionally characterized four FLC homologues(BrrFLC1,FLC2, FLC3, and FLC5), and found that BrrFLC2 and BrrFLC1 play a major role in repressing flowering in turnip and in transgenic Arabidopsis. In contrast, tuber formation was correlated with BrrFLC1 expression in the hypocotyl and was repressed under cold treatment following the quantitative downregulation of BrrFLC1. Grafting experiments of non-vernalized and vernalized turnips revealed that vernalization independently suppressed tuberization in the tuber or hypocotyl of the rootstock or scion, which occurred in parallel with the reduction in BrrFLC1 activity. Together, our results demonstrate that the Tibetan turnip is highly responsive to cold exposure, which is associated with the expression levels of BrrFLC genes.展开更多
THE USE OF KNOWLEDGE GRAPH IN NATURAL SCIENCE Knowledge graph is a field of Artificial Intelligence(AI)that aims to represent knowledge in the form of graphs,consisting of nodes and edges which represent entities and ...THE USE OF KNOWLEDGE GRAPH IN NATURAL SCIENCE Knowledge graph is a field of Artificial Intelligence(AI)that aims to represent knowledge in the form of graphs,consisting of nodes and edges which represent entities and relationships between nodes respectively(Aidan et al.,2022).Although the knowledge graph was popularized recently due to use of this idea in Google’s search engine in 2012(Amit,2012),its root can be traced back to the emergence of the Semantic Web as well as earlier works in ontology(Aggarwal,2021).展开更多
Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this p...Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this paper,centrally-controlled air conditioners are considered as a virtual energy storage system(VESS).The optimal thermostat regulation is used to manage the charging/discharging power of the VESS within the customer comfort level range and the virtual state of charge(VSOC)is used to describe the charging/discharging power of the VESS.On this basis,the model of the hybrid energy storage system is built with a VESS and a battery storage system(BSS).Then,an optimal coordination control strategy(OCCS)for a hybrid energy storage system is developed considering the state-space equation to describe the OCCS,the constraints of the OCCS,and the objective function to express the optimal coordination control performance.Finally,the influence of the outdoor temperature and the deadband of air conditioners on the results of the OCCS is analyzed.Results show that the OCCS can realize optimal allocation of the storage response amount to trace the reference target accurately and guarantee both the state of charge(SOC)of the batteries in a reasonable range to prolong the battery life and ensure the level of comfort experienced by users.展开更多
基金This work was supported by the National High Technology Research and Development Program(863 Program)of China(2015AA050403)Natural Science Foundation of Tianjin(17JCQNJC06600)+2 种基金Independent Innovation Foundation of Tianjin University(Research on Key Technology of Distributed Demand Response)Ocean Engineering Equipment and Technical Think Tank Joint Project of Qingdao(201707071003)the Distributed Energy and Microgrid Project conducted in collaboration with APPLIED ENERGY UNiLAB-DEM.
文摘Integrated energy distribution system(IEDS)is one of the integrated energy and power system forms,which involves electricity/gas/cold/heat and other various energy forms.The energy coupling relationship is close and complex.IEDS is the focus of regional energy internet research and development at home and abroad.Compared with the traditional power distribution system,IEDS through the multi-energy coupling link comprehensive utilization,effectively improve the distribution system economy,safety,reliability,flexibility and toughness,but also to ease the regional energy system environmental pressure.IEDS is an important direction for the future development of energy systems,and its related research and practice on China’s energy system development also has important practical and strategic significance.This paper summarizes the related researches of the IEDS and explores the energy operation characteristics and coupling mechanisms.What’s more,the integrated model of IEDS is summarized.On these bases,this paper discusses and prospects some key issues such as joint planning,optimization control and security analysis,state estimation and situational awareness and generalized demand side management.
基金funded by the National Natural Science Foundation of China(41421001,42041001 and 41525004).
文摘The outbreak of the 2019 novel coronavirus disease(COVID-19)has caused more than 100,000 people infected and thousands of deaths.Currently,the number of infections and deaths is still increasing rapidly.COVID-19 seriously threatens human health,production,life,social functioning and international relations.In the fight against COVID-19,Geographic Information Systems(GIS)and big data technologies have played an important role in many aspects,including the rapid aggregation of multi-source big data,rapid visualization of epidemic information,spatial tracking of confirmed cases,prediction of regional transmission,spatial segmentation of the epidemic risk and prevention level,balancing and management of the supply and demand of material resources,and socialemotional guidance and panic elimination,which provided solid spatial information support for decision-making,measures formulation,and effectiveness assessment of COVID-19 prevention and control.GIS has developed and matured relatively quickly and has a complete technological route for data preparation,platform construction,model construction,and map production.However,for the struggle against the widespread epidemic,the main challenge is finding strategies to adjust traditional technical methods and improve speed and accuracy of information provision for social management.At the data level,in the era of big data,data no longer come mainly from the government but are gathered from more diverse enterprises.As a result,the use of GIS faces difficulties in data acquisition and the integration of heterogeneous data,which requires governments,businesses,and academic institutions to jointly promote the formulation of relevant policies.At the technical level,spatial analysis methods for big data are in the ascendancy.Currently and for a long time in the future,the development of GIS should be strengthened to form a data-driven system for rapid knowledge acquisition,which signifies ts that GIS should be used to reinforce the social operation parameterization of models and
文摘Recent advances in systemic and locoregional treatments for patients with unresectable or advanced hepatocellular carcinoma(HCC)have resulted in improved response rates.This has provided an opportunity for selected patients with initially unresectable HCC to achieve adequate tumor downstaging to undergo surgical resection,a‘conversion therapy’strategy.However,conversion therapy is a new approach to the treatment of HCC and its practice and treatment protocols are still being developed.Review the evidence for conversion therapy in HCC and develop consensus statements to guide clinical practice.Evidence review:Many research centers in China have accumulated significant experience implementing HCC conversion therapy.Preliminary findings and data have shown that conversion therapy represents an important strategy to maximize the survival of selected patients with intermediate stage to advanced HCC;however,there are still many urgent clinical and scientific challenges for this therapeutic strategy and its related fields.In order to summarize and learn from past experience and review current challenges,the Chinese Expert Consensus on Conversion Therapy for Hepatocellular Carcinoma(2021 Edition)was developed based on a review of preliminary experience and clinical data from Chinese and non-Chinese studies in this field and combined with recommendations for clinical practice.Sixteen consensus statements on the implementation of conversion therapy for HCC were developed.The statements generated in this review are based on a review of clinical evidence and real clinical experience and will help guide future progress in conversion therapy for patients with HCC.
基金supported by the National Natural Science Foundation of China (Grant Nos. 30830117 and 31170016) the Major Scientific and Technological Special Project for Significant New Drugs Creation (Grant No. 2012ZX09301002-001-031)
文摘The aim of this study was to establish a method for discriminating Dendrobium officinale from four of its close relatives Den- drobium chrysanthum, Dendrobium erystallinum, Dendrobium aphyllum and Dendrobium devonianum based on chemical composition analysis. We analyzed 62 samples of 24 Dendrobium species. High performance liquid chromatography analysis confirmed that the four low molecular weight compounds 4＇,5,7-trihydroxyflavanone （naringenin）, 3,4-dihydroxy-4＇,5-dime- tboxybibenzyl （DDB^2）, 3＇,4-dihydroxy-3,5＇-dimethoxybibenzyl （gigantol）, and 4,4＇-dihydroxy-3,3＇,5-trimethoxybibenzyl （moscatilin）, were common in the genus. The phenol-sulfuric acid method was used to quantify polysaccharides, and the mon- osaccharide composition of the polysaccharides was determined by gas chromatography. Stepwise discriminant analysis was used to differentiate among the five closely related species based on the chemical composition analysis. This proved to be a simple and accurate approach for discriminating among these species. The results also showed that the polysaccharide content, the amounts of the four low molecular weight compounds, and the mannose to glucose ratio, were important factors for species discriminaut. Therefore, we propose that a chemical analysis based on quantification of naringenin, bibenzyl, and polysaccha- rides is effective for identifying D. officinale.
文摘目的以导管测量血流储备分数(FFR)为金标准,评价基于血流动力学优化融合模型的CT血流储备分数(CT-FFR)对冠状动脉狭窄所致心肌缺血病变的诊断效能。方法前瞻性选择127例接受冠状动脉CT血管成像(CCTA)、1周内冠状动脉造影及经导管FFR测量患者(152支血管),以CCTA观察病变狭窄程度,计算CT-FFR。以FFR<0.8为判断心肌缺血金标准,绘制CT-FFR及CCTA的ROC曲线,获得AUC。计算两种方法诊断心肌缺血的敏感度、特异度、阳性预测值、阴性预测值及准确率。结果 CT-FFR与导管测量FFR一致性良好,仅6.6%测量值在95%一致性界限之外。CT-FFR诊断心肌缺血AUC在患者水平(0.92 vs 0.69,P<0.001)和血管水平(0.93 vs 0.69,P<0.001)均优于CCTA。以患者水平CT-FFR<0.8诊断心肌缺血的敏感度、特异度和准确率分别为84.1%、90.6%和85.8%,CCTA>50%分别为82.5%、54.7%和68.5%;血管水平CT-FFR<0.8分别为88.0%、84.7%和84.9%,CCTA>50%分别为80.6%、57.7%和69.1%。CT-FFR对于血管水平狭窄程度30%~70%病变诊断效能仍佳。结论 CT-FFR对心肌缺血病变的诊断效能优于CCTA,有助于临床筛查心肌缺血病变。
基金financially supported by the Key Program of National Natural Science Foundation of China(Grant No.90914002)the Ore-Prospecting Project for Critical Mines(Grant No.20089937)+1 种基金Scheduled Program of China Geological Survey(Grant No.1212011220926)the Institution of Higher Education Innovation and Intelligence Attraction Program(Grant No.B07011)
文摘This paper reports the variation rules for the typomorphic parameters of the pyrite and the gold enrichment rules of the Denggezhuang quartz vein gold deposit at a large-depth scale, providing the mineral signs for deep prospecting prediction through detailed study of the characteristics of crystal＇ habits, chemical composition, the thermoelectricity of pyrites, and min- eralogical mapping. This paper primarily discusses the correlation between the mineralization intensity and the space-time evolution of the mineralogical parameters, clarifies the physicochemical conditions during gold mineralization, and provides information useful for deep mineralization prediction. We demonstrate that the crystal habits of the pyrites are very complex, primarily occurring as （ 100）, （210）, and their combinate form. （210） and （ 100）＋（210） have positive correlations with gold mineralization, and （ 100）＋（210） therefore can be useful for locating rich ore segments. The composition of pyrites is charac- teristically poor in S and rich in As. Their typical trace elements are composed of Mo, As, Pb, Cu, Bi, Zn, Au, Co, Se, Sb, Ag, Ni, Cr, and Te. The average contents of trace elements in pyrites from various stages show that the crystallizing temperature gradually decreased from an early stage to the metallogenic episodes. The precipitation and accumulation of Au and Ag occur primarily in the quartz-pyrite stage （III） and the polymetal minerals stage （IV）. The occurrence rate of P-type pyrites （P（%）） is 83.52%. There is a larger dispersion of the thermoelectrical coefficient of pyrite （a） in the Denggezhuang gold deposit than in other deposits in the Jiaodong Peninsula. The electrical conductivity assemblage of pyrites from I to V is characterized by P〉N〉P〉N〉P〉〉N〉P〉〉N〉P〉N, which is usually considered beneficial for mineralization. The relative contents of As＋Sb＋Se＋Te and Co＋Ni are closely correlated to P-type and N-type average values and their occurr
基金supported by the National Natural Science Foundation of China(Grant Nos.41421001,42050101,and 42050105)。
文摘Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means.It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph.Based on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists.We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among others.It will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research.
基金This research was jointly funded by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA23100103)the 13th Five-year Informatization Plan of Chinese Academy of Sciences(No.XXH13505-07)State Key Laboratory of Resources and Environmental Information System(O88RA20CYA).
文摘With the development of earth observation technologies,the acquired remote sensing images are increasing dramatically,and a new era of big data in remote sensing is coming.How to effectively mine these massive volumes of remote sensing data are new challenges.Deep learning provides a new approach for analyzing these remote sensing data.As one of the deep learning models,convolutional neural networks(CNNs)can directly extract features from massive amounts of imagery data and is good at exploiting semantic features of imagery data.CNNs have achieved remarkable success in computer vision.In recent years,quite a few researchers have studied remote sensing image classification using CNNs,and CNNs can be applied to realize rapid,economical and accurate analysis and feature extraction from remote sensing data.This paper aims to provide a survey of the current state-of-the-art application of CNN-based deep learning in remote sensing image classification.We first briefly introduce the principles and characteristics of CNNs.We then survey developments and structural improvements on CNN models that make CNNs more suitable for remote sensing image classification,available datasets for remote sensing image classification,and data augmentation techniques.Then,three typical CNN application cases in remote sensing image classification:scene classification,object detection and object segmentation are presented.We also discuss the problems and challenges of CNN-based remote sensing image classification,and propose corresponding measures and suggestions.We hope that the survey can facilitate the advancement of remote sensing image classification research and help remote-sensing scientists to tackle classification tasks with the state-of-art deep learning algorithms and techniques.
基金supported by the National Science Foundation of China(No.31500221,31590823 and 31601999)the West Light Foundation of the Chinese Academy of Sciences by XXK
文摘The turnip(Brassica rapa var. rapa) is a biennial crop that is planted in late summer/early fall and forms fleshy tubers for food in temperate regions. The harvested tubers then overwinter and are planted again the next spring for flowering and seeds. FLOWERING LOCUS C(FLC) is a MADS-box transcription factor that acts as a major repressor of floral transition by suppressing the flowering promoters FT and SOC1. Here we show that vernalization effectively represses tuber formation and promotes flowering in Tibetan turnip. We functionally characterized four FLC homologues(BrrFLC1,FLC2, FLC3, and FLC5), and found that BrrFLC2 and BrrFLC1 play a major role in repressing flowering in turnip and in transgenic Arabidopsis. In contrast, tuber formation was correlated with BrrFLC1 expression in the hypocotyl and was repressed under cold treatment following the quantitative downregulation of BrrFLC1. Grafting experiments of non-vernalized and vernalized turnips revealed that vernalization independently suppressed tuberization in the tuber or hypocotyl of the rootstock or scion, which occurred in parallel with the reduction in BrrFLC1 activity. Together, our results demonstrate that the Tibetan turnip is highly responsive to cold exposure, which is associated with the expression levels of BrrFLC genes.
基金financially supported by the National Natural Science Foundation of China (Nos.42050102,42050101)。
文摘THE USE OF KNOWLEDGE GRAPH IN NATURAL SCIENCE Knowledge graph is a field of Artificial Intelligence(AI)that aims to represent knowledge in the form of graphs,consisting of nodes and edges which represent entities and relationships between nodes respectively(Aidan et al.,2022).Although the knowledge graph was popularized recently due to use of this idea in Google’s search engine in 2012(Amit,2012),its root can be traced back to the emergence of the Semantic Web as well as earlier works in ontology(Aggarwal,2021).
基金This work was supported by a project of State Grid Corporation of China(No.SGTJDK00KJJS1600035).
文摘Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this paper,centrally-controlled air conditioners are considered as a virtual energy storage system(VESS).The optimal thermostat regulation is used to manage the charging/discharging power of the VESS within the customer comfort level range and the virtual state of charge(VSOC)is used to describe the charging/discharging power of the VESS.On this basis,the model of the hybrid energy storage system is built with a VESS and a battery storage system(BSS).Then,an optimal coordination control strategy(OCCS)for a hybrid energy storage system is developed considering the state-space equation to describe the OCCS,the constraints of the OCCS,and the objective function to express the optimal coordination control performance.Finally,the influence of the outdoor temperature and the deadband of air conditioners on the results of the OCCS is analyzed.Results show that the OCCS can realize optimal allocation of the storage response amount to trace the reference target accurately and guarantee both the state of charge(SOC)of the batteries in a reasonable range to prolong the battery life and ensure the level of comfort experienced by users.
