The internal structures of cells as the basic units of life are a major wonder of the microscopic world.Cellular images provide an intriguing window to help explore and understand the composition and function of these...The internal structures of cells as the basic units of life are a major wonder of the microscopic world.Cellular images provide an intriguing window to help explore and understand the composition and function of these structures.Scientific imagery combined with artistic expression can further expand the potential of imaging in educational dissemination and interdisciplinary applications.展开更多
The recently developed Frequency-Bessel(F-J) transform array technique has significantly advanced multi-mode surface wave tomography, providing precise constraints on shear wave velocity(V_(S)) models of the crust and...The recently developed Frequency-Bessel(F-J) transform array technique has significantly advanced multi-mode surface wave tomography, providing precise constraints on shear wave velocity(V_(S)) models of the crust and uppermost mantle.This technique has primarily focused on extracting inter-station surface waves from ambient noise cross-correlation. Energetic typhoons generate abundant surface wave signals, prompting growing interest in utilizing these signals to investigate subsurface structures. This study explores the feasibility and application of using microseisms excited by strong typhoons for F-J transform surface wave tomography. By analyzing microseisms recorded by a broadband seismic array in Mongolia during energetic typhoons, we observed multi-mode surface waves with high signal-to-noise ratios. Our analysis revealed that the sources of these waves closely correspond to typhoon tracks, confirming that they were primarily excited by typhoons. We successfully extracted multi-mode dispersion curves for imaging the V_(S) structure beneath the array using the F-J transform. Additionally, we derived multi-mode dispersion curves from a two-year noise dataset recorded by the same array, which were also used to invert for the V_(S) structure. Comparison of V_(S) models derived from typhoon-induced microseisms and the two-year noise dataset showed negligible differences within the depth range of 0–140 km. Our findings demonstrate the potential value of microseisms generated by energetic typhoons in precisely probing the V_(S)structure of the crust and uppermost mantle.展开更多
The promising prospect of a terahertz metasurface in sensing and detection applications has attracted increasing attention because of its ability to overcome the classical diffraction limit and the enhancement of fiel...The promising prospect of a terahertz metasurface in sensing and detection applications has attracted increasing attention because of its ability to overcome the classical diffraction limit and the enhancement of field intensity.In this work,a novel scheme based on an all-silicon terahertz plasmon metasurface is proposed and experimentally demonstrated to be a highly sensitive biosensor for the Bacillus thuringiensis Cry1Ac toxin.The regression coefficients between Bacillus thuringiensis protein concentrations and the spectral resonance intensity and frequency were 0.8988 and 0.9238,respectively.The resonance amplitude variation and frequency shift of the metasurface were investigated in terms of both thickness and permittivity change of the analyte,which reflected the protein residue in the actual process.Moreover,the reliability and stability of the metasurface chip were verified by time period,temperature,and humidity control.These results promise the ability of the proposed metasurface chip as a Bacillus thuringiensis protein sensor with high sensitivity and stability.In addition,this novel device strategy provides opportunities for the advancement of terahertz functional applications in the fields of biochemical sensing and detection.展开更多
Bacterial blight poses a threat to rice production and food security,which can be controlled through large-scale breeding efforts toward resistant cultivars.Unmanned aerial vehicle(UAV)remote sensing provides an alter...Bacterial blight poses a threat to rice production and food security,which can be controlled through large-scale breeding efforts toward resistant cultivars.Unmanned aerial vehicle(UAV)remote sensing provides an alternative means for the infield phenotype evaluation of crop disease resistance to relatively time-consuming and laborious traditional methods.However,the quality of data acquired by UAV can be affected by several factors such as weather,crop growth period,and geographical location,which can limit their utility for the detection of crop disease and resistant phenotypes.Therefore,a more effective use of UAV data for crop disease phenotype analysis is required.In this paper,we used time series UAV remote sensing data together with accumulated temperature data to train the rice bacterial blight severity evaluation model.The best results obtained with the predictive model showed an R_(p)^(2) of 0.86 with an RMSE_(p) of 0.65.Moreover,model updating strategy was used to explore the scalability of the established model in different geographical locations.Twenty percent of transferred data for model training was useful for the evaluation of disease severity over different sites.In addition,the method for phenotypic analysis of rice disease we built here was combined with quantitative trait loci(QTL)analysis to identify resistance QTL in genetic populations at different growth stages.Three new QTLs were identified,and QTLs identified at different growth stages were inconsistent.QTL analysis combined with UAV high-throughput phenotyping provides new ideas for accelerating disease resistance breeding.展开更多
Spontaneous rupture and hemorrhage of hepatocellular carcinoma(HCC)is one of the serious complications leading to death in patients with primary liver cancer.Approximately 9-10%of those patients with liver cancer die ...Spontaneous rupture and hemorrhage of hepatocellular carcinoma(HCC)is one of the serious complications leading to death in patients with primary liver cancer.Approximately 9-10%of those patients with liver cancer die of from spontaneous rupture and hemorrhage,which is often accompanied by abdominal metastasis and seriously affects their prognosis(1).展开更多
Currently,the presence of genetically modified(GM)organisms in agro-food markets is strictly regulated by enacted legislation worldwide.It is essential to ensure the traceability of these transgenic products for food ...Currently,the presence of genetically modified(GM)organisms in agro-food markets is strictly regulated by enacted legislation worldwide.It is essential to ensure the traceability of these transgenic products for food safety,consumer choice,environmental monitoring,market integrity,and scientific research.However,detecting the existence of GM organisms involves a combination of complex,time-consuming,and labor-intensive techniques requiring high-level professional skills.In this paper,a concise and rapid pipeline method to identify transgenic rice seeds was proposed on the basis of spectral imaging technologies and the deep learning approach.The composition of metabolome across 3 rice seed lines containing the cry1Ab/cry1Ac gene was compared and studied,substantiating the intrinsic variability induced by these GM traits.Results showed that near-infrared and terahertz spectra from different genotypes could reveal the regularity of GM metabolic variation.The established cascade deep learning model divided GM discrimination into 2 phases including variety classification and GM status identification.It could be found that terahertz absorption spectra contained more valuable features and achieved the highest accuracy of 97.04%for variety classification and 99.71%for GM status identification.Moreover,a modified guided backpropagation algorithm was proposed to select the task-specific characteristic wavelengths for further reducing the redundancy of the original spectra.The experimental validation of the cascade discriminant method in conjunction with spectroscopy confirmed its viability,simplicity,and effectiveness as a valuable tool for the detection of GM rice seeds.This approach also demonstrated its great potential in distilling crucial features for expedited transgenic risk assessment.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.226-2024-00038),China.
文摘The internal structures of cells as the basic units of life are a major wonder of the microscopic world.Cellular images provide an intriguing window to help explore and understand the composition and function of these structures.Scientific imagery combined with artistic expression can further expand the potential of imaging in educational dissemination and interdisciplinary applications.
基金supported by the National Natural Science Foundation of China (Grant No. 92155307)the Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology (Grant No. 2022B1212010002)+2 种基金the ShenzhenScienceandTechnologyProgram(GrantNo. KQTD20170810111725321)the Shenzhen Key Laboratory of Deep Offshore Oil and Gas Exploration Technology (Grant No. ZDSYS20190902093007855)the National Natural Science Foundation of China (Grant No. 42374072)。
文摘The recently developed Frequency-Bessel(F-J) transform array technique has significantly advanced multi-mode surface wave tomography, providing precise constraints on shear wave velocity(V_(S)) models of the crust and uppermost mantle.This technique has primarily focused on extracting inter-station surface waves from ambient noise cross-correlation. Energetic typhoons generate abundant surface wave signals, prompting growing interest in utilizing these signals to investigate subsurface structures. This study explores the feasibility and application of using microseisms excited by strong typhoons for F-J transform surface wave tomography. By analyzing microseisms recorded by a broadband seismic array in Mongolia during energetic typhoons, we observed multi-mode surface waves with high signal-to-noise ratios. Our analysis revealed that the sources of these waves closely correspond to typhoon tracks, confirming that they were primarily excited by typhoons. We successfully extracted multi-mode dispersion curves for imaging the V_(S) structure beneath the array using the F-J transform. Additionally, we derived multi-mode dispersion curves from a two-year noise dataset recorded by the same array, which were also used to invert for the V_(S) structure. Comparison of V_(S) models derived from typhoon-induced microseisms and the two-year noise dataset showed negligible differences within the depth range of 0–140 km. Our findings demonstrate the potential value of microseisms generated by energetic typhoons in precisely probing the V_(S)structure of the crust and uppermost mantle.
基金Natural Science Foundation of Shaanxi Province(2020JZ-48)Youth Innovation Team of Shaanxi Universities(21JP084)+1 种基金National Natural Science Foundation of China(31801257,61975163)Open Project of Key Laboratory of Engineering Dielectrics and Its Applications,Ministry of Education(KEY1805).
文摘The promising prospect of a terahertz metasurface in sensing and detection applications has attracted increasing attention because of its ability to overcome the classical diffraction limit and the enhancement of field intensity.In this work,a novel scheme based on an all-silicon terahertz plasmon metasurface is proposed and experimentally demonstrated to be a highly sensitive biosensor for the Bacillus thuringiensis Cry1Ac toxin.The regression coefficients between Bacillus thuringiensis protein concentrations and the spectral resonance intensity and frequency were 0.8988 and 0.9238,respectively.The resonance amplitude variation and frequency shift of the metasurface were investigated in terms of both thickness and permittivity change of the analyte,which reflected the protein residue in the actual process.Moreover,the reliability and stability of the metasurface chip were verified by time period,temperature,and humidity control.These results promise the ability of the proposed metasurface chip as a Bacillus thuringiensis protein sensor with high sensitivity and stability.In addition,this novel device strategy provides opportunities for the advancement of terahertz functional applications in the fields of biochemical sensing and detection.
基金funded by the Planned Science and Technology Project of Guangdong Province,China(grant no.2021A0505030075)Key R&D Projects in Huzhou City(grant no.2021ZD2037)State Key Laboratory for managing biotic and chemical treats to the quality and safety of agro-products(grant no.2022KF03).
文摘Bacterial blight poses a threat to rice production and food security,which can be controlled through large-scale breeding efforts toward resistant cultivars.Unmanned aerial vehicle(UAV)remote sensing provides an alternative means for the infield phenotype evaluation of crop disease resistance to relatively time-consuming and laborious traditional methods.However,the quality of data acquired by UAV can be affected by several factors such as weather,crop growth period,and geographical location,which can limit their utility for the detection of crop disease and resistant phenotypes.Therefore,a more effective use of UAV data for crop disease phenotype analysis is required.In this paper,we used time series UAV remote sensing data together with accumulated temperature data to train the rice bacterial blight severity evaluation model.The best results obtained with the predictive model showed an R_(p)^(2) of 0.86 with an RMSE_(p) of 0.65.Moreover,model updating strategy was used to explore the scalability of the established model in different geographical locations.Twenty percent of transferred data for model training was useful for the evaluation of disease severity over different sites.In addition,the method for phenotypic analysis of rice disease we built here was combined with quantitative trait loci(QTL)analysis to identify resistance QTL in genetic populations at different growth stages.Three new QTLs were identified,and QTLs identified at different growth stages were inconsistent.QTL analysis combined with UAV high-throughput phenotyping provides new ideas for accelerating disease resistance breeding.
基金This study was supported by Sichuan University from 0 to 1 project(No.2022SCUH0017)Sichuan Science and Technology Plan Project“International cooperation in science and technology innovation/technological innovation cooperation in Hong Kong,Macao and Taiwan”(No.2021YFH0095).
文摘Spontaneous rupture and hemorrhage of hepatocellular carcinoma(HCC)is one of the serious complications leading to death in patients with primary liver cancer.Approximately 9-10%of those patients with liver cancer die of from spontaneous rupture and hemorrhage,which is often accompanied by abdominal metastasis and seriously affects their prognosis(1).
基金supported by the National Key Research and Development Program of China(2021ZD0113601)Key Research and Development Projects of Huzhou City(2021ZD2037).
文摘Currently,the presence of genetically modified(GM)organisms in agro-food markets is strictly regulated by enacted legislation worldwide.It is essential to ensure the traceability of these transgenic products for food safety,consumer choice,environmental monitoring,market integrity,and scientific research.However,detecting the existence of GM organisms involves a combination of complex,time-consuming,and labor-intensive techniques requiring high-level professional skills.In this paper,a concise and rapid pipeline method to identify transgenic rice seeds was proposed on the basis of spectral imaging technologies and the deep learning approach.The composition of metabolome across 3 rice seed lines containing the cry1Ab/cry1Ac gene was compared and studied,substantiating the intrinsic variability induced by these GM traits.Results showed that near-infrared and terahertz spectra from different genotypes could reveal the regularity of GM metabolic variation.The established cascade deep learning model divided GM discrimination into 2 phases including variety classification and GM status identification.It could be found that terahertz absorption spectra contained more valuable features and achieved the highest accuracy of 97.04%for variety classification and 99.71%for GM status identification.Moreover,a modified guided backpropagation algorithm was proposed to select the task-specific characteristic wavelengths for further reducing the redundancy of the original spectra.The experimental validation of the cascade discriminant method in conjunction with spectroscopy confirmed its viability,simplicity,and effectiveness as a valuable tool for the detection of GM rice seeds.This approach also demonstrated its great potential in distilling crucial features for expedited transgenic risk assessment.
