Solar cycles are fundamental to astrophysics,space exploration,technological infrastructure,and Earth's climate.A better understanding of these cycles and their history can aid in risk mitigation on Earth,while al...Solar cycles are fundamental to astrophysics,space exploration,technological infrastructure,and Earth's climate.A better understanding of these cycles and their history can aid in risk mitigation on Earth,while also deepening our knowledge of stellar physics and solar system dynamics.Determining the solar cycles between 1600 and 1700-especially the post-1645 Maunder Minimum,characterized by significantly reduced solar activity-poses challenges to existing solar activity proxies.This study utilizes a new red equatorial auroral catalog from ancient Korean texts to establish solar cycle patterns from 1623 to 1700.Remarkably,a further reevaluation of the solar cycles between 1610 and 1755 identified a total of 13 cycles,diverging from the widely accepted record of 12 cycles during that time.This research enhances our understanding of historical solar activity,and underscores the importance of integrating diverse historical sources into modern analyses.展开更多
BACKGROUND Unraveling the pathogenesis of colorectal cancer(CRC)can aid in developing prevention and treatment strategies.Aurora kinase A(AURKA)is a key participant in mitotic control and interacts with its co-activat...BACKGROUND Unraveling the pathogenesis of colorectal cancer(CRC)can aid in developing prevention and treatment strategies.Aurora kinase A(AURKA)is a key participant in mitotic control and interacts with its co-activator,the targeting protein for Xklp2(TPX2)microtubule nucleation factor.AURKA is associated with poor clinical outcomes and high risks of CRC recurrence.AURKA/TPX2 co-overexpression in cancer may contribute to tumorigenesis.Despite its pivotal role in CRC development and progression,the action mechanism of AURKA remains unclear.Further research is needed to explore the complex interplay between AURKA and TPX2 and to develop effective targeted treatments for patients with CRC.AIM To compare effects of AURKA and TPX2 and their combined knockdown on CRC cells.METHODS We evaluated three CRC gene datasets about CRC(GSE32323,GSE25071,and GSE21510).Potential hub genes associated with CRC onset were identified using the Venn,search tool for the retrieval of interacting genes,and KOBAS platforms,with AURKA and TPX2 emerging as significant factors.Subsequently,cell models with knockdown of AURKA,TPX2,or both were constructed using SW480 and LOVO cells.Quantitative real-time polymerase chain reaction,western blotting,cell counting kit-8,cell cloning assays,flow cytometry,and Transwell assays were used.RESULTS Forty-three highly expressed genes and 39 poorly expressed genes overlapped in cancer tissues compared to controls from three datasets.In the protein-protein interaction network of highly expressed genes,AURKA was one of key genes.Its combined score with TPX2 was 0.999,and their co-expression score was 0.846.In CRC cells,knockdown of AURKA,TPX2,or both reduced cell viability and colony number,while blocking G0/G1 phase and enhancing cell apoptosis.Additionally,they were weakened cell proliferation and migration abilities.Furthermore,the expression levels of B-cell lymphoma-2-Associated X,caspase 3,and tumor protein P53,and E-cadherin increased with a decrease in B-cell lymphoma-2,N-cadherin,and vimentin proteins.These effects were amplified when both AURKA and TPX2 were concurrently downregulated.CONCLUSION Combined knockdown of AURKA and TPX2 was effective in suppressing the malignant phenotype in CRC.Coinhibition of gene expression is a potential developmental direction for CRC treatment.展开更多
Studying various aurora morphology helps us understand space's physical processes and the mechanisms behind these patterns.Auroral arcs are the brightest and most prominent auroral patterns.Due to the difficulty i...Studying various aurora morphology helps us understand space's physical processes and the mechanisms behind these patterns.Auroral arcs are the brightest and most prominent auroral patterns.Due to the difficulty in precisely defining auroral shape edges,auroral arc skeleton extraction is expected as an alternative representation for studying auroral morphology,resorting skeletons extract key morphological features from complex auroral shapes.Transformer models provide a better understanding of the relationship between the overall morphology and the details when processing image data,so we proposed a Transformer-based method for auroral arc skeleton extraction.Combined with ridge-guided annotation on all-sky images,a Transformer-based skeleton extractor is trained and used to estimate the number of auroral arcs.Experiments demonstrate that the Transformer-based model can more effectively capture structural information and local details of auroral arcs,which is suitable for complex auroral morphologies.展开更多
In this investigation,we meticulously annotated a corpus of 21,174 auroral images captured by the THEMIS All-Sky Imager across diverse temporal instances.These images were categorized using an array of descriptors suc...In this investigation,we meticulously annotated a corpus of 21,174 auroral images captured by the THEMIS All-Sky Imager across diverse temporal instances.These images were categorized using an array of descriptors such as'arc','ab'(aurora but bright),'cloudy','diffuse','discrete',and'clear'.Subsequently,we utilized a state-of-the-art convolutional neural network,ConvNeXt(Convolutional Neural Network Next),deploying deep learning techniques to train the model on a dataset classified into six distinct categories.Remarkably,on the test set our methodology attained an accuracy of 99.4%,a performance metric closely mirroring human visual observation,thereby underscoring the classifier’s competence in paralleling human perceptual accuracy.Building upon this foundation,we embarked on the identification of large-scale auroral optical data,meticulously quantifying the monthly occurrence and Magnetic Local Time(MLT)variations of auroras from stations at different latitudes:RANK(high-latitude),FSMI(mid-latitude),and ATHA(low-latitude),under different solar wind conditions.This study paves the way for future explorations into the temporal variations of auroral phenomena in diverse geomagnetic contexts.展开更多
The recently deployed Transition Region Explorer(TREx)-RGB(red-green-blue)all-sky imager(ASI)is designed to capture“true color”images of the aurora and airglow.Because the 557.7 nm green line is usually the brightes...The recently deployed Transition Region Explorer(TREx)-RGB(red-green-blue)all-sky imager(ASI)is designed to capture“true color”images of the aurora and airglow.Because the 557.7 nm green line is usually the brightest emission line in visible auroras,the green channel of a TREx-RGB camera is usually dominated by the 557.7 nm emission.Under this rationale,the TREx mission does not include a specific 557.7 nm imager and is designed to use the RGB green-channel data as a proxy for the 557.7 nm aurora.In this study,we present an initial effort to establish the conversion ratio or formula linking the RGB green-channel data to the absolute intensity of 557.7 nm auroras,which is crucial for quantitative uses of the RGB data.We illustrate two approaches:(1)through a comparison with the collocated measurement of green-line auroras from the TREx spectrograph,and(2)through a comparison with the modeled green-line intensity according to realistic electron precipitation flux measurements from low-Earth-orbit satellites,with the aid of an auroral transport model.We demonstrate the procedures and provide initial results for the TREx-RGB ASIs at the Rabbit Lake and Lucky Lake stations.The RGB response is found to be nonlinear.Empirical conversion ratios or formulas between RGB green-channel data and the green-line auroral intensity are given and can be applied immediately by TREx-RGB data users.The methodology established in this study will also be applicable to the upcoming SMILE ASI mission,which will adopt a similar RGB camera system in its deployment.展开更多
Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but...Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by sunlight.Nightglow emissions and scattered sunlight can contribute to the background signal.To fully utilize such images in space science,background contamination must be removed to isolate the auroral signal.Here we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical harmonics.The approach is robust,flexible,and iteratively deselects outliers,such as auroral emissions.The final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the dayglow.We demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)mission.The method can be applied to historical missions and is relevant for upcoming missions,such as the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.展开更多
Background: Cholangiocarcinoma(CCA), a malignancy that arises from biliary epithelial cells, has a dismal prognosis, and few targeted therapies are available. Aurora B, a key mitotic regulator, has been reported to be...Background: Cholangiocarcinoma(CCA), a malignancy that arises from biliary epithelial cells, has a dismal prognosis, and few targeted therapies are available. Aurora B, a key mitotic regulator, has been reported to be involved in the progression of various tumors, yet its role in CCA is still unclarified.Methods: Human CCA tissues and murine spontaneous CCA models were used to assess Aurora B expression in CCA. A loss-of-function model was constructed in CCA cells to determine the role of Aurora B in CCA progression. Subcutaneous and liver orthotopic xenograft models were used to assess the therapeutic potential of Aurora B inhibitors in CCA.Results: In murine spontaneous CCA models, Aurora B was significantly upregulated. Elevated Aurora B expression was also observed in 62.3% of human specimens in our validation cohort(143 CCA specimens), and high Aurora B expression was positively correlated with pathological parameters of tumors and poor survival. Knockdown of Aurora B by siRNA and heteroduplex oligonucleotide(HDO)or an Aurora B kinase inhibitor(AZD1152) significantly suppressed CCA progression via G2/M arrest induction. An interaction between Aurora B and c-Myc was found in CCA cells. Targeting Aurora B significantly reduced this interaction and accelerated the proteasomal degradation of c-Myc, suggesting that Aurora B promoted the malignant properties of CCA by stabilizing c-Myc. Furthermore, sequential application of AZD1152 or Aurora B HDO drastically improved the efficacy of gemcitabine in CCA.Conclusions: Aurora B plays an essential role in CCA progression by modulating c-Myc stability and represents a new target for treatment and chemosensitization in CCA.展开更多
本文总结在电力电子系统中,通过实时数字仿真器(Real Time Digital Simulator,简称RTDS)进行模拟电网的各种工况,通过将静止无功发生器(SVG)实际控制器和RTDS完成物理在线高效实时闭环仿真联合仿真。其中,实际的SVG设备的控制箱和RTDS...本文总结在电力电子系统中,通过实时数字仿真器(Real Time Digital Simulator,简称RTDS)进行模拟电网的各种工况,通过将静止无功发生器(SVG)实际控制器和RTDS完成物理在线高效实时闭环仿真联合仿真。其中,实际的SVG设备的控制箱和RTDS系统通过aurora协议交互功率阀组模型实时仿真多模块功率单元信息,这种仿真系统运行效率高、占用RTDS硬件资源少,弥补了现有链式SVG闭环实时仿真系统方案的不足,准确实现了实际功率阀组模块数量完全一致的链式SVG系统。联合仿真SVG设备时,通过手动测试,高低穿测试完成RTDS闭环测试,验证了仿真系统的有效性和准确性。在中国电科院及其它电科院进行过验证,具有真实的测试意义。展开更多
基金supported by the National Natural Science Foundation of China (42388101)the CAS Youth Interdisciplinary Team (JCTD-2021-05)funded by the Youth Innovation Promotion Association, Chinese Academy of Sciences.
文摘Solar cycles are fundamental to astrophysics,space exploration,technological infrastructure,and Earth's climate.A better understanding of these cycles and their history can aid in risk mitigation on Earth,while also deepening our knowledge of stellar physics and solar system dynamics.Determining the solar cycles between 1600 and 1700-especially the post-1645 Maunder Minimum,characterized by significantly reduced solar activity-poses challenges to existing solar activity proxies.This study utilizes a new red equatorial auroral catalog from ancient Korean texts to establish solar cycle patterns from 1623 to 1700.Remarkably,a further reevaluation of the solar cycles between 1610 and 1755 identified a total of 13 cycles,diverging from the widely accepted record of 12 cycles during that time.This research enhances our understanding of historical solar activity,and underscores the importance of integrating diverse historical sources into modern analyses.
文摘BACKGROUND Unraveling the pathogenesis of colorectal cancer(CRC)can aid in developing prevention and treatment strategies.Aurora kinase A(AURKA)is a key participant in mitotic control and interacts with its co-activator,the targeting protein for Xklp2(TPX2)microtubule nucleation factor.AURKA is associated with poor clinical outcomes and high risks of CRC recurrence.AURKA/TPX2 co-overexpression in cancer may contribute to tumorigenesis.Despite its pivotal role in CRC development and progression,the action mechanism of AURKA remains unclear.Further research is needed to explore the complex interplay between AURKA and TPX2 and to develop effective targeted treatments for patients with CRC.AIM To compare effects of AURKA and TPX2 and their combined knockdown on CRC cells.METHODS We evaluated three CRC gene datasets about CRC(GSE32323,GSE25071,and GSE21510).Potential hub genes associated with CRC onset were identified using the Venn,search tool for the retrieval of interacting genes,and KOBAS platforms,with AURKA and TPX2 emerging as significant factors.Subsequently,cell models with knockdown of AURKA,TPX2,or both were constructed using SW480 and LOVO cells.Quantitative real-time polymerase chain reaction,western blotting,cell counting kit-8,cell cloning assays,flow cytometry,and Transwell assays were used.RESULTS Forty-three highly expressed genes and 39 poorly expressed genes overlapped in cancer tissues compared to controls from three datasets.In the protein-protein interaction network of highly expressed genes,AURKA was one of key genes.Its combined score with TPX2 was 0.999,and their co-expression score was 0.846.In CRC cells,knockdown of AURKA,TPX2,or both reduced cell viability and colony number,while blocking G0/G1 phase and enhancing cell apoptosis.Additionally,they were weakened cell proliferation and migration abilities.Furthermore,the expression levels of B-cell lymphoma-2-Associated X,caspase 3,and tumor protein P53,and E-cadherin increased with a decrease in B-cell lymphoma-2,N-cadherin,and vimentin proteins.These effects were amplified when both AURKA and TPX2 were concurrently downregulated.CONCLUSION Combined knockdown of AURKA and TPX2 was effective in suppressing the malignant phenotype in CRC.Coinhibition of gene expression is a potential developmental direction for CRC treatment.
基金supported by the National Natural Science Foundation of China(Grant no.41874173)。
文摘Studying various aurora morphology helps us understand space's physical processes and the mechanisms behind these patterns.Auroral arcs are the brightest and most prominent auroral patterns.Due to the difficulty in precisely defining auroral shape edges,auroral arc skeleton extraction is expected as an alternative representation for studying auroral morphology,resorting skeletons extract key morphological features from complex auroral shapes.Transformer models provide a better understanding of the relationship between the overall morphology and the details when processing image data,so we proposed a Transformer-based method for auroral arc skeleton extraction.Combined with ridge-guided annotation on all-sky images,a Transformer-based skeleton extractor is trained and used to estimate the number of auroral arcs.Experiments demonstrate that the Transformer-based model can more effectively capture structural information and local details of auroral arcs,which is suitable for complex auroral morphologies.
基金supported by the General Program of the National Natural Science Foundation of China(Grant No.42374212)the National Magnetic Confinement Fusion Energy Research and Development Program of China(Grant No.2024YFE03020004).
文摘In this investigation,we meticulously annotated a corpus of 21,174 auroral images captured by the THEMIS All-Sky Imager across diverse temporal instances.These images were categorized using an array of descriptors such as'arc','ab'(aurora but bright),'cloudy','diffuse','discrete',and'clear'.Subsequently,we utilized a state-of-the-art convolutional neural network,ConvNeXt(Convolutional Neural Network Next),deploying deep learning techniques to train the model on a dataset classified into six distinct categories.Remarkably,on the test set our methodology attained an accuracy of 99.4%,a performance metric closely mirroring human visual observation,thereby underscoring the classifier’s competence in paralleling human perceptual accuracy.Building upon this foundation,we embarked on the identification of large-scale auroral optical data,meticulously quantifying the monthly occurrence and Magnetic Local Time(MLT)variations of auroras from stations at different latitudes:RANK(high-latitude),FSMI(mid-latitude),and ATHA(low-latitude),under different solar wind conditions.This study paves the way for future explorations into the temporal variations of auroral phenomena in diverse geomagnetic contexts.
基金jointly funded by the Canada Foundation for Innovationthe Alberta Economic Development and Trade organization+1 种基金the University of Calgarysupported by the Canadian Space Agency。
文摘The recently deployed Transition Region Explorer(TREx)-RGB(red-green-blue)all-sky imager(ASI)is designed to capture“true color”images of the aurora and airglow.Because the 557.7 nm green line is usually the brightest emission line in visible auroras,the green channel of a TREx-RGB camera is usually dominated by the 557.7 nm emission.Under this rationale,the TREx mission does not include a specific 557.7 nm imager and is designed to use the RGB green-channel data as a proxy for the 557.7 nm aurora.In this study,we present an initial effort to establish the conversion ratio or formula linking the RGB green-channel data to the absolute intensity of 557.7 nm auroras,which is crucial for quantitative uses of the RGB data.We illustrate two approaches:(1)through a comparison with the collocated measurement of green-line auroras from the TREx spectrograph,and(2)through a comparison with the modeled green-line intensity according to realistic electron precipitation flux measurements from low-Earth-orbit satellites,with the aid of an auroral transport model.We demonstrate the procedures and provide initial results for the TREx-RGB ASIs at the Rabbit Lake and Lucky Lake stations.The RGB response is found to be nonlinear.Empirical conversion ratios or formulas between RGB green-channel data and the green-line auroral intensity are given and can be applied immediately by TREx-RGB data users.The methodology established in this study will also be applicable to the upcoming SMILE ASI mission,which will adopt a similar RGB camera system in its deployment.
基金supported by the Research Council of Norway under contracts 223252/F50 and 300844/F50the Trond Mohn Foundation。
文摘Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by sunlight.Nightglow emissions and scattered sunlight can contribute to the background signal.To fully utilize such images in space science,background contamination must be removed to isolate the auroral signal.Here we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical harmonics.The approach is robust,flexible,and iteratively deselects outliers,such as auroral emissions.The final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the dayglow.We demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)mission.The method can be applied to historical missions and is relevant for upcoming missions,such as the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.
基金supported by National Natural Science Foundation of ChinaGrant/Award Number:82172602+1 种基金Guang Dong Basic and Applied Basic Research FoundationGrant/Award Number:2023A1515011892。
文摘Background: Cholangiocarcinoma(CCA), a malignancy that arises from biliary epithelial cells, has a dismal prognosis, and few targeted therapies are available. Aurora B, a key mitotic regulator, has been reported to be involved in the progression of various tumors, yet its role in CCA is still unclarified.Methods: Human CCA tissues and murine spontaneous CCA models were used to assess Aurora B expression in CCA. A loss-of-function model was constructed in CCA cells to determine the role of Aurora B in CCA progression. Subcutaneous and liver orthotopic xenograft models were used to assess the therapeutic potential of Aurora B inhibitors in CCA.Results: In murine spontaneous CCA models, Aurora B was significantly upregulated. Elevated Aurora B expression was also observed in 62.3% of human specimens in our validation cohort(143 CCA specimens), and high Aurora B expression was positively correlated with pathological parameters of tumors and poor survival. Knockdown of Aurora B by siRNA and heteroduplex oligonucleotide(HDO)or an Aurora B kinase inhibitor(AZD1152) significantly suppressed CCA progression via G2/M arrest induction. An interaction between Aurora B and c-Myc was found in CCA cells. Targeting Aurora B significantly reduced this interaction and accelerated the proteasomal degradation of c-Myc, suggesting that Aurora B promoted the malignant properties of CCA by stabilizing c-Myc. Furthermore, sequential application of AZD1152 or Aurora B HDO drastically improved the efficacy of gemcitabine in CCA.Conclusions: Aurora B plays an essential role in CCA progression by modulating c-Myc stability and represents a new target for treatment and chemosensitization in CCA.
文摘本文总结在电力电子系统中,通过实时数字仿真器(Real Time Digital Simulator,简称RTDS)进行模拟电网的各种工况,通过将静止无功发生器(SVG)实际控制器和RTDS完成物理在线高效实时闭环仿真联合仿真。其中,实际的SVG设备的控制箱和RTDS系统通过aurora协议交互功率阀组模型实时仿真多模块功率单元信息,这种仿真系统运行效率高、占用RTDS硬件资源少,弥补了现有链式SVG闭环实时仿真系统方案的不足,准确实现了实际功率阀组模块数量完全一致的链式SVG系统。联合仿真SVG设备时,通过手动测试,高低穿测试完成RTDS闭环测试,验证了仿真系统的有效性和准确性。在中国电科院及其它电科院进行过验证,具有真实的测试意义。
