Convolutional Neural Networks(CNNs)have recently attracted much attention in the ship detection from Synthetic Aperture Radar(SAR)images.However,compared with optical images,SAR ones are hard to understand.Moreover,du...Convolutional Neural Networks(CNNs)have recently attracted much attention in the ship detection from Synthetic Aperture Radar(SAR)images.However,compared with optical images,SAR ones are hard to understand.Moreover,due to the high similarity between the man-made targets near shore and inshore ships,the classical methods are unable to achieve effective detection of inshore ships.To mitigate the influence of onshore ship-like objects,this paper proposes an inshore ship detection method in SAR images by using hybrid features.Firstly,the sea-land segmentation is applied in the pre-processing to exclude obvious land regions from SAR images.Then,a CNN model is designed to extract deep features for identifying potential ship targets in both inshore and offshore water.On this basis,the high-energy point number of amplitude spectrum is further introduced as an important and delicate feature to suppress false alarms left.Finally,to verify the effectiveness of the proposed method,numerical and comparative studies are carried out in experiments on Sentinel-1 SAR images.展开更多
Background:Plasticity in response to environmental drivers can help trees cope with droughts.However,our understanding of the importance of plasticity and physiological adjustments in trees under global change is limi...Background:Plasticity in response to environmental drivers can help trees cope with droughts.However,our understanding of the importance of plasticity and physiological adjustments in trees under global change is limited.Methods:We used the International Tree-Ring Data Bank(ITRDB)to examine 20th century growth responses in conifer trees during(resistance)and following(resilience)years of severe soil and atmospheric droughts occurring in isolation or as compound events.Growth resilience indices were calculated using observed growth divided by expected growth to avoid spurious correlations,in which the expected values were obtained by the autoregressive moving average(ARIMA)model.We used high atmospheric vapour pressure deficit(VPD)to select years of atmospheric drought and low annual values of the Standardized Precipitation-Evapotranspiration Index(SPEI)to select years with soil drought.We acquired the sensitivities(i.e.,the slopes of the relationships)by fitting the resilience indices as a function of environmental drivers,and assessed how these sensitivities changed over time for different types of drought events using linear mixed models.We also checked whether plasticity in growth responses was sufficient to prevent long-term trends of growth reductions during or after severe droughts.We acknowledge that by focusing on the response of surviving trees from the ITRDB we are potentially biasing our results towards higher resilience,as stand level responses(e.g.,mortality)may result in lowered competition after the disturbance event.Results:Sensitivities of resilience to VPD and SPEI changed throughout the 20th century,with the directions of these changes often reversing in the second half of the century.For the 1961–2010 period,changing sensitivities had positive effects on resilience,especially following years of high-VPD and compound events,avoiding growth losses that would have occurred if sensitivities had remained constant.Despite sensitivity changes,resilience was still lower at the end of the 20th century compared to the beginning of the century.Conclusions:Future adjustments to low-SPEI and high-VPD events are likely to continue to compensate for the trends in climate only partially,leading to further generalized reductions in tree growth of conifers.An improved understanding of these plastic adjustments and their limits,as well as potential compensatory processes at the stand level,is needed to project forest responses to climate change.展开更多
Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistan...Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.展开更多
基金Aeronautical Science Foundation of China(No.2018ZC51022)。
文摘Convolutional Neural Networks(CNNs)have recently attracted much attention in the ship detection from Synthetic Aperture Radar(SAR)images.However,compared with optical images,SAR ones are hard to understand.Moreover,due to the high similarity between the man-made targets near shore and inshore ships,the classical methods are unable to achieve effective detection of inshore ships.To mitigate the influence of onshore ship-like objects,this paper proposes an inshore ship detection method in SAR images by using hybrid features.Firstly,the sea-land segmentation is applied in the pre-processing to exclude obvious land regions from SAR images.Then,a CNN model is designed to extract deep features for identifying potential ship targets in both inshore and offshore water.On this basis,the high-energy point number of amplitude spectrum is further introduced as an important and delicate feature to suppress false alarms left.Finally,to verify the effectiveness of the proposed method,numerical and comparative studies are carried out in experiments on Sentinel-1 SAR images.
基金TZ acknowledges contribution from the China Scholarship Council(CSC)MM and JM-V received support from the Spanish Ministry of Science and Innovation(MICINN)via competitive grant CGL2017-89149-C2-1-RAG and JJC were supported by the FUNDIVER project of the Spanish Ministry of Science and Innovation(CGL2015-69186-C2-1-R).
文摘Background:Plasticity in response to environmental drivers can help trees cope with droughts.However,our understanding of the importance of plasticity and physiological adjustments in trees under global change is limited.Methods:We used the International Tree-Ring Data Bank(ITRDB)to examine 20th century growth responses in conifer trees during(resistance)and following(resilience)years of severe soil and atmospheric droughts occurring in isolation or as compound events.Growth resilience indices were calculated using observed growth divided by expected growth to avoid spurious correlations,in which the expected values were obtained by the autoregressive moving average(ARIMA)model.We used high atmospheric vapour pressure deficit(VPD)to select years of atmospheric drought and low annual values of the Standardized Precipitation-Evapotranspiration Index(SPEI)to select years with soil drought.We acquired the sensitivities(i.e.,the slopes of the relationships)by fitting the resilience indices as a function of environmental drivers,and assessed how these sensitivities changed over time for different types of drought events using linear mixed models.We also checked whether plasticity in growth responses was sufficient to prevent long-term trends of growth reductions during or after severe droughts.We acknowledge that by focusing on the response of surviving trees from the ITRDB we are potentially biasing our results towards higher resilience,as stand level responses(e.g.,mortality)may result in lowered competition after the disturbance event.Results:Sensitivities of resilience to VPD and SPEI changed throughout the 20th century,with the directions of these changes often reversing in the second half of the century.For the 1961–2010 period,changing sensitivities had positive effects on resilience,especially following years of high-VPD and compound events,avoiding growth losses that would have occurred if sensitivities had remained constant.Despite sensitivity changes,resilience was still lower at the end of the 20th century compared to the beginning of the century.Conclusions:Future adjustments to low-SPEI and high-VPD events are likely to continue to compensate for the trends in climate only partially,leading to further generalized reductions in tree growth of conifers.An improved understanding of these plastic adjustments and their limits,as well as potential compensatory processes at the stand level,is needed to project forest responses to climate change.
基金supported by the National Key R&D Program,Intergovernmental Key Items for International Scientific and Technological Innovation Cooperation(2018YFE0107700)the National Natural Science Foundation of China(31771772)+2 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX19_2109)the National Key R&D Program for Breeding of Top-seven Crops(2017YFD0100801)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
文摘Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.
