Due to the strong penetrability,long-wavelength synthetic aperture radar(SAR)can provide an opportunity to reconstruct the three-dimensional structure of the penetrable media.SAR tomography(TomoSAR)technology can resy...Due to the strong penetrability,long-wavelength synthetic aperture radar(SAR)can provide an opportunity to reconstruct the three-dimensional structure of the penetrable media.SAR tomography(TomoSAR)technology can resynthesize aperture perpendicular to the slant-range direction and then obtain the tomographic profile consisting of power distribution of different heights,providing a powerful technical tool for reconstructing the three-dimensional structure of the penetrable ground objects.As an emerging technology,it is different from the traditional interferometric SAR(InSAR)technology and has advantages in reconstructing the three-dimensional structure of the illuminated media.Over the past two decades,many TomoSAR methods have been proposed to improve the vertical resolution,aiming to distinguish the locations of different scatters in the unit pixel.In order to cope with the forest mission of European Space Agency(ESA)that is designed to provide P-band SAR measurements to determine the amount of biomass and carbon stored in forests,it is necessary to systematically evaluate the performance of forest height and underlying topography inversion using TomoSAR technology.In this paper,we adopt three typical algorithms,namely,Capon,Multiple Signal Classification(MUSIC),and Compressed Sensing(CS),to evaluate the performance in forest height and underlying topography inversion.The P-band airborne full-polarization(FP)SAR data of LopèNational Park in the AfriSAR campaign implemented by ESA in 2016 is adopted to verify the experiment.Furthermore,we explore the effects of different baseline designs and filter methods on the reconstruction of the tomographic profile.The results show that a better tomographic profile can be obtained by using Hamming window filter and Capon algorithm in uniform baseline distribution and a certain number of acquisitions.Compared with LiDAR results,the root-mean-square error(RMSE)of forest height and underlying topography obtained by Capon algorithm is 2.17 m and 1.58 m,which performs the best among the three algorithms.展开更多
This paper is intended to summarize the research conducted during the first 2 years of the Dragon 5 project 59,332(geophysical and atmospheric retrieval from Synthetic Aperture Radar(SAR)data stacks over natural scena...This paper is intended to summarize the research conducted during the first 2 years of the Dragon 5 project 59,332(geophysical and atmospheric retrieval from Synthetic Aperture Radar(SAR)data stacks over natural scenarios).Monitoring atmospheric phenomena,encompassing both tropospheric and ionospheric conditions,holds pivotal significance for various scientific and practical applications.In this paper,we present an exploration of advanced techniques for estimating tropospheric and ionospheric phase screens using stacks of Synthetic Aperture Radar(SAR)images.Our study delves into the current state-of-the-art in atmospheric monitoring with a focus on spaceborne SAR systems,shedding light on their evolving capabilities.For tropospheric phase screen estimation,we propose a novel approach that jointly estimates the tropospheric component from all the images.We discuss the methodology in detail,highlighting its ability to recover accurate tropospheric maps.Through a series of quantitative case studies using real Sentinel-1 satellite data,we demonstrate the effectiveness of our technique in capturing tropospheric variability over different geographical regions.Concurrently,we delve into the estimation of ionospheric phase screens utilizing SAR image stacks.The intricacies of ionospheric disturbances pose unique challenges,necessitating specialized techniques.We dissect our approach,showcasing its capacity to mitigate ionospheric noise and recover precise phase information.Real data from the Sentinel-1 satellite are employed to showcase the efficacy of our method,unraveling ionospheric perturbations with improved accuracy.The integration of our techniques,though presented separately for clarity,collectively contributes to a comprehensive framework for atmospheric monitoring.Our findings emphasize the potential of SAR-based approaches in advancing our knowledge of atmospheric processes,thus fostering advancements in weather prediction,geophysics,and environmental management.展开更多
The Shilu Fe-polymetallic ore deposit,a famous hematite-rich Fe-ore deposit,is situated at the western Hainan Province of south China.The deposit characterizes the upper Fe ores and the lower Co-Cu ores,which are main...The Shilu Fe-polymetallic ore deposit,a famous hematite-rich Fe-ore deposit,is situated at the western Hainan Province of south China.The deposit characterizes the upper Fe ores and the lower Co-Cu ores,which are mainly hosted within a low-grade to medium-grade,dominantly submarine metamorphosed siliciclastic and carbonate sedimentary succession of the Neoproterozoic Shilu Group.Three facies types of metamorphosed BIFs,i.e.the oxide facies,the silicate-oxide facies and the sulfide-carbonate facies BIFs,are identified within the sixth sequence of the Shilu Group.The oxide facies BIF(i.e.the Fe-rich itabirites or ores)consists of alternating hematite-rich microbands with quartz-rich microbands;the silicate-oxide facies BIF(i.e.the Fe-poor itabirites or ores)comprises alternating millimeter-to a few tens meter-scale,magnetite-hematite-rich bands with calcsilicate-rich(garnet+actinolite+diopside+epidote+quartz)meso-to microbands;and the sulfide-carbonate facies BIF(i.e.the Co-Cu ores)contains alternating macro-to mesobands of Co-bearing pyrite and pyrrhotite,and chalcopyrite with mesobands of dolomite+calcite+diopside+quartz and/or chlorite+sericite+quartz.The blastooolitic,blastopelletoid blastocolloidal and blastopsammitic textures,and blasobedding structures which most likely represent primary sedimentation are often observed in these BIF facies.The interbedded host rocks with the BIFs mainly are the pyroxene-amphibole rocks and the banded or impure dolostones,and also contain banded or laminated structures,and lepido-gra-noblastic,nematoblastic and/or blastoclastic textures.Compositionally,the main host rocks,the pyroxene-amphibole rocks contain basic-intermediate SiO_2(~54.00 wt.%),CaO(~14.19 wt.%),MgO(~9.68 wt.%)and Al_2O_3(~8.49 wt.%)with a positive correlation between Al_2O_3 and TiO_2.The UCC-like Zr and Hf abundances,high Ba content andεNd(t)value(^-5.99)as well as the ratios of La/YbPAAS(0.17~1.00),δEuPAAS(0.88~1.12)andδCePAAS(0.93~1.13)commonly reveal that the protoliths to this type rocks are hydrogenic with a large contribution of terrigenous sediments and minor hydrothermal input.The high CaO+MgO+LOI contents and the extremely low trace element and REEconcentrations as well as the ratios of Y/Ho(44~45),δEuPAAS(1.13~1.57)andδCePAAS(0.69~0.98)reflect a marine origin with minor terrigenous materials for the banded or impure dolostones.Moreover,this type rocks also account for a negativeεNd(t)value(^-7.49).The oxide facies BIF is dominated by Fe_2O_3+FeO(~75.59wt.%)and SiO_2(~20.47 wt.%)with aεNd(t)value of^-6.10.The variable contents in Al_2O_3,TiO 2,K2O,Na2O,Zr,Hf and∑REE,and variable ratios of Y/Ho(24~39)andδEuPAAS(0.86~11.07)suggest the precursor sediments to this facies BIF are admixtures of sea-floor hydrothermal fluids and seawaters with minor involvement of detrital components.Compared to the oxide facies BIF,the silicate-oxide facies BIF is lower in Fe_2O_3+Fe O(~39.81wt.%)and Ba but higher in SiO_2(~42.54 wt.%),Al2O3(~3.60 wt.%),TiO_2(~0.19 wt.%),MgO(~1.12 wt.%),CaO(~9.06 wt.%),K_2O(~0.98 wt.%),Mn and Zr.The ratios of Y/Ho(25~34),La/YbPAAS(0.14-0.74)andδEuPAAS(0.91~1.12)most likely are linked to higher degree of detrital contamintants.While the sulfide-caronate facies BIF is main but variable in Fe_2O_3+Fe O(15.79~57.91 wt.%),SiO 2(0.54~61.52 wt.%),MgO(0.12~16.09wt.%),CaO(0.17~23.41 wt.%)and LOI(8.28-30.06 wt.%).The generally low contents in trace elements(including REE)except for an obvious enrichment in Pb,and the positive Ce anomalies(δCePAAS=1.04~1.95)and negative Pr anomalies(δPrPAAS=0.67~0.93),as well as the variable ratios ofδEuPAAS(0.72~1.71),La/YbPAAS(0.26~1.60)and Y/Ho(26~57)suggest that the precursors to the sulfide-carbonate facies BIF mainly are metalliferious sediments from deep-marine hydrotheral source with minor detrital components.The T2DM ages(ca.2.0 Ga)imply that the Shilu BIFs and interbedded host rocks contain a component with Paleoproterozoic crustal residence age due to a significant crustal accretion event at ca.2.0 Ga in Hainan Island.In connection with the petrographical and mineralogical relationship,we conclude that the precursor precipitates to the Shilu BIFs are variable degree of admixtures of the Fe-Co-Cu-(Si)-rich hydrothermal fluids and detrital components from seawater and fresh water carring continental landmass;whereas the protolith to the main interbedded host rocks,i.e.the pyroxene-amphibole rocks,most likely was terrigenous,fine-grained clastic-sediments but with significant input of hydrothermal fluids in a seawater environment.As a result,a continent marginal marine basin is proposed for deposition of the Shilu BIFs and interbedded host rocks.Sea-level fluctuations caused by marine transgression–regressions possibly contributed to changes in the composition and varied input of the terrigenous sediments.展开更多
Objective:Through integrated bioinformatics analysis,the goal of this work was to find new,characterised N7-methylguanosine modification-related long non-coding RNAs(m7G-lncRNAs)that might be used to predict the progn...Objective:Through integrated bioinformatics analysis,the goal of this work was to find new,characterised N7-methylguanosine modification-related long non-coding RNAs(m7G-lncRNAs)that might be used to predict the prognosis of laryngeal squamous cell carcinoma(LSCC).Methods:The clinical data and LSCC gene expression data for the current investigation were initially retrieved from the TCGA database&sanitised.Then,using co-expression analysis of m7G-associated mRNAs&lncRNAs&differential expression analysis(DEA)among LSCC&normal sample categories,we discovered lncRNAs that were connected to m7G.The prognosis prediction model was built for the training category using univariate&multivariate COX regression&LASSO regression analyses,&the model’s efficacy was checked against the test category data.In addition,we conducted DEA of prognostic m7G-lncRNAs among LSCC&normal sample categories&compiled a list of co-expression networks&the structure of prognosis m7G-lncRNAs.To compare the prognoses for individuals with LSCC in the high-&low-risk categories in the prognosis prediction model,survival and risk assessments were also carried out.Finally,we created a nomogram to accurately forecast the outcomes of LSCC patients&created receiver operating characteristic(ROC)curves to assess the prognosis prediction model’s predictive capability.Results:Using co-expression network analysis&differential expression analysis,we discovered 774 m7G-lncRNAs and 551 DEm7G-lncRNAs,respectively.We then constructed a prognosis prediction model for six m7G-lncRNAs(FLG−AS1,RHOA−IT1,AC020913.3,AC027307.2,AC010973.2 and AC010789.1),identified 32 DEPm7G-lncRNAs,analyzed the correlation between 32 DEPm7G-lncRNAs and 13 DEPm7G-mRNAs,and performed survival analyses and risk analyses of the prognosis prediction model to assess the prognostic performance of LSCC patients.By displaying ROC curves and a nomogram,we finally checked the prognosis prediction model's accuracy.Conclusion:By creating novel predictive lncRNA signatures for clinical diagnosis&therapy,our findings will contribute to understanding the pathogenetic process of LSCC.展开更多
基金supported by ESA-MOST Dragon Programme 5[grant number 59332].
文摘Due to the strong penetrability,long-wavelength synthetic aperture radar(SAR)can provide an opportunity to reconstruct the three-dimensional structure of the penetrable media.SAR tomography(TomoSAR)technology can resynthesize aperture perpendicular to the slant-range direction and then obtain the tomographic profile consisting of power distribution of different heights,providing a powerful technical tool for reconstructing the three-dimensional structure of the penetrable ground objects.As an emerging technology,it is different from the traditional interferometric SAR(InSAR)technology and has advantages in reconstructing the three-dimensional structure of the illuminated media.Over the past two decades,many TomoSAR methods have been proposed to improve the vertical resolution,aiming to distinguish the locations of different scatters in the unit pixel.In order to cope with the forest mission of European Space Agency(ESA)that is designed to provide P-band SAR measurements to determine the amount of biomass and carbon stored in forests,it is necessary to systematically evaluate the performance of forest height and underlying topography inversion using TomoSAR technology.In this paper,we adopt three typical algorithms,namely,Capon,Multiple Signal Classification(MUSIC),and Compressed Sensing(CS),to evaluate the performance in forest height and underlying topography inversion.The P-band airborne full-polarization(FP)SAR data of LopèNational Park in the AfriSAR campaign implemented by ESA in 2016 is adopted to verify the experiment.Furthermore,we explore the effects of different baseline designs and filter methods on the reconstruction of the tomographic profile.The results show that a better tomographic profile can be obtained by using Hamming window filter and Capon algorithm in uniform baseline distribution and a certain number of acquisitions.Compared with LiDAR results,the root-mean-square error(RMSE)of forest height and underlying topography obtained by Capon algorithm is 2.17 m and 1.58 m,which performs the best among the three algorithms.
基金prepared to summarize the research conducted during the first 2 years of research at the mid-term stage of the Dragon 5 project 59332(Geophysical and atmospheric retrieval from SAR data stacks over natural scenarios)funded by the European Space Agency under contract[4000136890/21/I-NB].
文摘This paper is intended to summarize the research conducted during the first 2 years of the Dragon 5 project 59,332(geophysical and atmospheric retrieval from Synthetic Aperture Radar(SAR)data stacks over natural scenarios).Monitoring atmospheric phenomena,encompassing both tropospheric and ionospheric conditions,holds pivotal significance for various scientific and practical applications.In this paper,we present an exploration of advanced techniques for estimating tropospheric and ionospheric phase screens using stacks of Synthetic Aperture Radar(SAR)images.Our study delves into the current state-of-the-art in atmospheric monitoring with a focus on spaceborne SAR systems,shedding light on their evolving capabilities.For tropospheric phase screen estimation,we propose a novel approach that jointly estimates the tropospheric component from all the images.We discuss the methodology in detail,highlighting its ability to recover accurate tropospheric maps.Through a series of quantitative case studies using real Sentinel-1 satellite data,we demonstrate the effectiveness of our technique in capturing tropospheric variability over different geographical regions.Concurrently,we delve into the estimation of ionospheric phase screens utilizing SAR image stacks.The intricacies of ionospheric disturbances pose unique challenges,necessitating specialized techniques.We dissect our approach,showcasing its capacity to mitigate ionospheric noise and recover precise phase information.Real data from the Sentinel-1 satellite are employed to showcase the efficacy of our method,unraveling ionospheric perturbations with improved accuracy.The integration of our techniques,though presented separately for clarity,collectively contributes to a comprehensive framework for atmospheric monitoring.Our findings emphasize the potential of SAR-based approaches in advancing our knowledge of atmospheric processes,thus fostering advancements in weather prediction,geophysics,and environmental management.
文摘The Shilu Fe-polymetallic ore deposit,a famous hematite-rich Fe-ore deposit,is situated at the western Hainan Province of south China.The deposit characterizes the upper Fe ores and the lower Co-Cu ores,which are mainly hosted within a low-grade to medium-grade,dominantly submarine metamorphosed siliciclastic and carbonate sedimentary succession of the Neoproterozoic Shilu Group.Three facies types of metamorphosed BIFs,i.e.the oxide facies,the silicate-oxide facies and the sulfide-carbonate facies BIFs,are identified within the sixth sequence of the Shilu Group.The oxide facies BIF(i.e.the Fe-rich itabirites or ores)consists of alternating hematite-rich microbands with quartz-rich microbands;the silicate-oxide facies BIF(i.e.the Fe-poor itabirites or ores)comprises alternating millimeter-to a few tens meter-scale,magnetite-hematite-rich bands with calcsilicate-rich(garnet+actinolite+diopside+epidote+quartz)meso-to microbands;and the sulfide-carbonate facies BIF(i.e.the Co-Cu ores)contains alternating macro-to mesobands of Co-bearing pyrite and pyrrhotite,and chalcopyrite with mesobands of dolomite+calcite+diopside+quartz and/or chlorite+sericite+quartz.The blastooolitic,blastopelletoid blastocolloidal and blastopsammitic textures,and blasobedding structures which most likely represent primary sedimentation are often observed in these BIF facies.The interbedded host rocks with the BIFs mainly are the pyroxene-amphibole rocks and the banded or impure dolostones,and also contain banded or laminated structures,and lepido-gra-noblastic,nematoblastic and/or blastoclastic textures.Compositionally,the main host rocks,the pyroxene-amphibole rocks contain basic-intermediate SiO_2(~54.00 wt.%),CaO(~14.19 wt.%),MgO(~9.68 wt.%)and Al_2O_3(~8.49 wt.%)with a positive correlation between Al_2O_3 and TiO_2.The UCC-like Zr and Hf abundances,high Ba content andεNd(t)value(^-5.99)as well as the ratios of La/YbPAAS(0.17~1.00),δEuPAAS(0.88~1.12)andδCePAAS(0.93~1.13)commonly reveal that the protoliths to this type rocks are hydrogenic with a large contribution of terrigenous sediments and minor hydrothermal input.The high CaO+MgO+LOI contents and the extremely low trace element and REEconcentrations as well as the ratios of Y/Ho(44~45),δEuPAAS(1.13~1.57)andδCePAAS(0.69~0.98)reflect a marine origin with minor terrigenous materials for the banded or impure dolostones.Moreover,this type rocks also account for a negativeεNd(t)value(^-7.49).The oxide facies BIF is dominated by Fe_2O_3+FeO(~75.59wt.%)and SiO_2(~20.47 wt.%)with aεNd(t)value of^-6.10.The variable contents in Al_2O_3,TiO 2,K2O,Na2O,Zr,Hf and∑REE,and variable ratios of Y/Ho(24~39)andδEuPAAS(0.86~11.07)suggest the precursor sediments to this facies BIF are admixtures of sea-floor hydrothermal fluids and seawaters with minor involvement of detrital components.Compared to the oxide facies BIF,the silicate-oxide facies BIF is lower in Fe_2O_3+Fe O(~39.81wt.%)and Ba but higher in SiO_2(~42.54 wt.%),Al2O3(~3.60 wt.%),TiO_2(~0.19 wt.%),MgO(~1.12 wt.%),CaO(~9.06 wt.%),K_2O(~0.98 wt.%),Mn and Zr.The ratios of Y/Ho(25~34),La/YbPAAS(0.14-0.74)andδEuPAAS(0.91~1.12)most likely are linked to higher degree of detrital contamintants.While the sulfide-caronate facies BIF is main but variable in Fe_2O_3+Fe O(15.79~57.91 wt.%),SiO 2(0.54~61.52 wt.%),MgO(0.12~16.09wt.%),CaO(0.17~23.41 wt.%)and LOI(8.28-30.06 wt.%).The generally low contents in trace elements(including REE)except for an obvious enrichment in Pb,and the positive Ce anomalies(δCePAAS=1.04~1.95)and negative Pr anomalies(δPrPAAS=0.67~0.93),as well as the variable ratios ofδEuPAAS(0.72~1.71),La/YbPAAS(0.26~1.60)and Y/Ho(26~57)suggest that the precursors to the sulfide-carbonate facies BIF mainly are metalliferious sediments from deep-marine hydrotheral source with minor detrital components.The T2DM ages(ca.2.0 Ga)imply that the Shilu BIFs and interbedded host rocks contain a component with Paleoproterozoic crustal residence age due to a significant crustal accretion event at ca.2.0 Ga in Hainan Island.In connection with the petrographical and mineralogical relationship,we conclude that the precursor precipitates to the Shilu BIFs are variable degree of admixtures of the Fe-Co-Cu-(Si)-rich hydrothermal fluids and detrital components from seawater and fresh water carring continental landmass;whereas the protolith to the main interbedded host rocks,i.e.the pyroxene-amphibole rocks,most likely was terrigenous,fine-grained clastic-sediments but with significant input of hydrothermal fluids in a seawater environment.As a result,a continent marginal marine basin is proposed for deposition of the Shilu BIFs and interbedded host rocks.Sea-level fluctuations caused by marine transgression–regressions possibly contributed to changes in the composition and varied input of the terrigenous sediments.
基金supported by a grant Hebei Provincial Health Commission project from the Foundation of Basic Research(No.20191843).
文摘Objective:Through integrated bioinformatics analysis,the goal of this work was to find new,characterised N7-methylguanosine modification-related long non-coding RNAs(m7G-lncRNAs)that might be used to predict the prognosis of laryngeal squamous cell carcinoma(LSCC).Methods:The clinical data and LSCC gene expression data for the current investigation were initially retrieved from the TCGA database&sanitised.Then,using co-expression analysis of m7G-associated mRNAs&lncRNAs&differential expression analysis(DEA)among LSCC&normal sample categories,we discovered lncRNAs that were connected to m7G.The prognosis prediction model was built for the training category using univariate&multivariate COX regression&LASSO regression analyses,&the model’s efficacy was checked against the test category data.In addition,we conducted DEA of prognostic m7G-lncRNAs among LSCC&normal sample categories&compiled a list of co-expression networks&the structure of prognosis m7G-lncRNAs.To compare the prognoses for individuals with LSCC in the high-&low-risk categories in the prognosis prediction model,survival and risk assessments were also carried out.Finally,we created a nomogram to accurately forecast the outcomes of LSCC patients&created receiver operating characteristic(ROC)curves to assess the prognosis prediction model’s predictive capability.Results:Using co-expression network analysis&differential expression analysis,we discovered 774 m7G-lncRNAs and 551 DEm7G-lncRNAs,respectively.We then constructed a prognosis prediction model for six m7G-lncRNAs(FLG−AS1,RHOA−IT1,AC020913.3,AC027307.2,AC010973.2 and AC010789.1),identified 32 DEPm7G-lncRNAs,analyzed the correlation between 32 DEPm7G-lncRNAs and 13 DEPm7G-mRNAs,and performed survival analyses and risk analyses of the prognosis prediction model to assess the prognostic performance of LSCC patients.By displaying ROC curves and a nomogram,we finally checked the prognosis prediction model's accuracy.Conclusion:By creating novel predictive lncRNA signatures for clinical diagnosis&therapy,our findings will contribute to understanding the pathogenetic process of LSCC.
