The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.展开更多
This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has ...This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.展开更多
Dear Editor,This letter focuses on the remaining useful life(RUL)prediction task under limited labeled samples.Existing machine-learning-based RUL prediction methods for this task usually pay attention to mining degra...Dear Editor,This letter focuses on the remaining useful life(RUL)prediction task under limited labeled samples.Existing machine-learning-based RUL prediction methods for this task usually pay attention to mining degradation information to improve the prediction accuracy of degradation value or health indicator for the next epoch.However,they ignore the cumulative prediction error caused by iterations before reaching the failure point.展开更多
Micro-Doppler parameter estimation is crucial for moving targets.However,conventional methods face limitations like inadequate time-frequency(TF)resolution and poor generalization,while existing deep learning approach...Micro-Doppler parameter estimation is crucial for moving targets.However,conventional methods face limitations like inadequate time-frequency(TF)resolution and poor generalization,while existing deep learning approaches often treat TF analysis as a fixed preprocessing step.To overcome these challenges,this paper introduces a radar micro-Doppler parameter estimation method based on a gated dual-path dynamic-wavelet convolutional network(GDWCN).The GDWCN is an end-to-end deep learning framework that maps raw radar signals to micro-motion parameters by integrating clutter suppression,gated dual-path module,feature extraction,and parameter regression.Its core innovation is a gated dual-path module that combines dynamic convolution and learnable wavelet convolution,selecting the optimal processing path based on input signal characteristics.For the Inspire 2 drone,GDWCN reduced the mean absolute error(MAE)of frequency estimation by approximately 38%compared to the enhanced time-frequency micro-Doppler network,and its relative error by approximately 69%compared to the short-time Fourier transform(STFT),and 58%over the local maximum synchroextracting transform.Ablation studies further confirm the efficacy of the clutter suppression module and the attention mechanism.展开更多
The kagome lattice,characterized by a hexagonal arrangement of corner-sharing equilateral triangles,has garnered significant attention as a fascinating quantum material system that hosts exotic magnetic and electronic...The kagome lattice,characterized by a hexagonal arrangement of corner-sharing equilateral triangles,has garnered significant attention as a fascinating quantum material system that hosts exotic magnetic and electronic properties.The identification and characterization of this class of materials are critical for advancing our understanding of their role in emergent phenomena such as superconductivity.In this study,we developed a high-throughput screening framework for the systematic identification and classification of superconducting materials with kagome lattices,integrating them into established materials databases.Leveraging the Materials Project(MP)database and the MDR Super Con dataset,we analyzed over 150000 inorganic compounds and cross-referenced 26000 known superconductors.Using geometry-based structural modeling and experimental validation,we identified 129 kagome superconductors belonging to 17 distinct structural families,many of which had not previously been recognized as kagome systems.The materials are further classified into three categories in terms of topological flat bands,clean band structures,and coexisting magnetic or charge density wave(CDW)orderings.Based on these results,we established a database comprising 129 kagome superconductors,including the detailed crystallographic,electronic,and superconducting properties of these materials.展开更多
Objective： To compare the survival outcomes of transabdominal （TA） and transthoracic （TT） surgical approaches in patients with Siewert-II/III esophagogastric junction adenocarcinoma. Methods： This retrospective ...Objective： To compare the survival outcomes of transabdominal （TA） and transthoracic （TT） surgical approaches in patients with Siewert-II/III esophagogastric junction adenocarcinoma. Methods： This retrospective study was conducted in patients with Siewert-II/III esophagogastric junction adenocarcinoma who underwent either TT or TA operations in the West China Hospital between January 2006 and December 2009. Results： A total of 308 patients （109 in the TT and 199 in the TA groups） were included in this study with a follow-up rate of 87.3%. The median （P25, P75） number of harvested perigastric lymph nodes was 8 （5, 10） in the TT group and 23 （16, 34） in the TA group （P〈0.001）, and the number of positive perigastric lymph nodes was 2 （0, 5） in the TT group and 3 （1, 8） in the TA group （P〈0.004）. The 5-year overall survival （OS） rate was 36% in the TT group and 51% in the TA group （P=0.005）. Subgroup analysis by Siewert classification showed that 5-year OS rates for patients with Siewert II tumors were 38% and 48% in TT and TA groups, respectively （P=0.134）, whereas the 5-year OS rate for patients with Siewert III tumors was significantly lower in the TT group than that in the TA group （33% vs. 53%; P=0.010）. Multivariate analysis indicated that N2 and N3 stages, RI/R2 resection and a TT surgical approach were prognostic factors for poor OS. Conclusions： Improved perigastric lymph node dissection may be the main reason for better survival outcomes observed with a TA gastrectomy approach than with TT gastrectomy for Siewert III tumor patients.展开更多
The Coupled Model Intercomparison Project （CMIP） is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Impro...The Coupled Model Intercomparison Project （CMIP） is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Improving the performance of climate models over East Asia and the western North Pacific has been a challenge for the climate-modeling community. In this paper, we provide a synthesis robustness analysis of the climate models participating in CMIP-Phase 5 （CMIP5）. The strengths and weaknesses of the CMIP5 models are assessed from the perspective of climate mean state, interannual variability, past climate change during the mid-Pliocene （MP） and the last millennium, and climate projection. The added values of regional climate models relative to the driving global climate models are also assessed. Although an encouraging increase in credibility and an improvement in the simulation of mean states, interannual variability, and past climate changes are visible in the progression from CMIP3 to CMIPS, some previously noticed biases such as the ridge position of the western North Pacific subtropical high and the associated rainfall bias are still evident in CMIP5 models. Weaknesses are also evident in simulations of the interannual amplitude, such as El Nino- Southern Oscillation （ENSO）-monsoon relationships. Coupled models generally show better results than standalone atmospheric models in simulating both mean states and interannual variability. Multi-model intercomparison indicates significant uncertainties in the future projection of climate change, although precipitation increases consistently across models constrained by the Clausius-Clapeyron relation. Regional ocean-atmosphere coupled models are recommended for the dynamical downscaling of climate change oroiections over the East Asia-western North Pacific domain.展开更多
The Delta-like ligand 4/Notch signaling pathway was shown to participate in the process of retinal development and angiogenesis. However, the function of the Delta-like ligand 4/Notch signaling pathway in retinopathy ...The Delta-like ligand 4/Notch signaling pathway was shown to participate in the process of retinal development and angiogenesis. However, the function of the Delta-like ligand 4/Notch signaling pathway in retinopathy of prematurity requires further study. Retinopathy of prematurity was induced in 5-day-old Sprague-Dawley rats exposed to hyperoxia for 7 days, and then returned to room air. Reverse transcription-PCR and western blot revealed that Delta-like ligand 4 levels decreased at postnatal day 12 and increased at postnatal day 17 in retinopathy of prematurity rats. Flat-mounted adenosine diphosphatase stained retina and hematoxylin-eosin stained retinal tissue slices showed that the clock hour scores and the nuclei counts in retinopathy of prematurity rats were significantly different compared to normal control rats. After retinopathy of prematurity rats were intravitreally injected with Delta-like ligand 4 monoclonal antibody to inhibit the Delta-like ligand 4/Notch signaling pathway, there was a significant increase in the severity of retinal neovascularization （clock hours） in the intravitreally injected eyes. The nuclei count was highly correlated with the clock hour score. These results suggest that Delta-like ligand 4/Notch signaling plays an essential role in the process of physiological and pathological angiogenesis in the retina.展开更多
The unprecedented Zhengzhou heavy rainfall in July 2021 occurred under the background of a northward shift of the western Pacific subtropical high(WPSH).Although the occurrence of this extreme event could not be captu...The unprecedented Zhengzhou heavy rainfall in July 2021 occurred under the background of a northward shift of the western Pacific subtropical high(WPSH).Although the occurrence of this extreme event could not be captured by seasonal predictions,a skillful prediction of the WPSH variation might have warned us of the increased probability of extreme weather events in Central and Northern China.However,the mechanism for the WPSH variation in July 2021 and its seasonal predictability are still unknown.Here,the observed northward shift of the WPSH in July 2021 is shown to correspond to a meridional dipole pattern of the 850-hPa geopotential height to the east of China,the amplitude of which became the strongest since 1979.The meridional dipole pattern is two nodes of the Pacific–Japan pattern.To investigate the predictability of the WPSH variation,a 21-member ensemble of seasonal predictions initiated from the end of June 2021 was conducted.The predictable and unpredictable components of the meridional dipole pattern were identified from the ensemble simulations.Its predictable component is driven by positive precipitation anomalies over the tropical western Pacific.The positive precipitation anomalies are caused by positive horizonal advection of the mean moist enthalpy by southwesterly anomalies to the northwestern flank of anticyclonic anomalies excited by the existing La Niña,which is skillfully predicted by the model.The leading mode of the unpredictable component is associated with the atmospheric internal intraseasonal oscillations,which are not initialized in the simulations.The relative contributions of the predictable and unpredictable components to the observed northward shift of the WPSH at 850 hPa are 28.0%and 72.0%,respectively.展开更多
An undersea volcano at Hunga Tonga-Hunga Ha'apai(HTHH)near the South Pacific island nation of Tonga,erupted violently on 15 January 2022.Potential climate impact of the HTHH volcanic eruption is of great concern t...An undersea volcano at Hunga Tonga-Hunga Ha'apai(HTHH)near the South Pacific island nation of Tonga,erupted violently on 15 January 2022.Potential climate impact of the HTHH volcanic eruption is of great concern to the public;here,we intend to size up the impact of the HTHH eruption from a historical perspective.The influence of historical volcanic eruptions on the global climate are firstly reviewed,which are thought to have contributed to decreased surface temperature,increased stratospheric temperature,suppressed global water cycle,weakened monsoon circulation and El Niño-like sea surface temperature.Our understanding of the impacts of past volcanic eruptions on global-scale climate provides potential implication to evaluate the impact of the HTHH eruption.Based on historical simulations,we estimate that the current HTHH eruption with an intensity of 0.4 Tg SO_(2)injection will decrease the global mean surface temperature by only 0.004℃in the first year after eruption,which is within the amplitude of internal variability at the interannual time scale and thus not strong enough to have significant impacts on the global climate.展开更多
This paper focuses on the problem of the adaptive robust control of a lower limbs rehabilitation robot(LLRR) that is a nonlinear system running under passive training mode. In reality, uncertainties including modeling...This paper focuses on the problem of the adaptive robust control of a lower limbs rehabilitation robot(LLRR) that is a nonlinear system running under passive training mode. In reality, uncertainties including modeling error, initial condition deviation, friction force and other unknown external disturbances always exist in a LLRR system. So, it is necessary to consider the uncertainties in the unilateral man-machine dynamical model of the LLRR we described. In the dynamical model, uncertainties are(possibly fast) time-varying and bounded. However, the bounds are unknown. Based on the dynamical model, we design an adaptive robust control with an adaptive law that is leakagetype based and on the framework of Udwadia-Kalaba theory to compensate for the uncertainties and to realize tracking control of the LLRR. Furthermore, the effectiveness of designed control is shown with numerical simulations.展开更多
Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a centra...Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a central focus of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences(LASG/IAP) since the establishment of the laboratory in 1985. In China, many pioneering component models and fully coupled models of the climate system have been developed by LASG/IAP. The fully coupled climate system developed in the recent decade is named FGOALS(Flexible Global Ocean-Atmosphere-Land System Model). In this paper, an application-oriented review of the LASG/IAP FGOALS model is presented. The improved model performances are demonstrated in the context of cloud-radiation processes, Asian monsoon, ENSO phenomena, Atlantic Meridional Overturning Circulation(AMOC) and sea ice. The FGOALS model has contributed to both CMIP5(Coupled Model Intercomparison Project-phase 5) and IPCC(Intergovernmental Panel on Climate Change) AR5(the Fifth Assessment Report). The release of FGOALS data has supported the publication of nearly 500 papers around the world. The results of FGOALS are cited ~106 times in the IPCC WG1(Working Group 1) AR5. In addition to the traditional long-term simulations and projections, near-term decadal climate prediction is a new set of CMIP experiment, progress of LAGS/IAP in the development of nearterm decadal prediction system is reviewed. The FGOALS model has supported many Chinese national-level research projects and contributed to the national climate change assessment report. The crucial role of FGOALS as a modeling tool for supporting climate sciences is highlighted by demonstrating the model's performances in the simulation of the evolution of Earth's climate from the past to the future.展开更多
A super-large ensemble simulation dataset with 110 members has been produced by the fully coupled model FGOALS-g3 developed by researchers at the Institute of Atmospheric Physics,Chinese Academy of Sciences.This is th...A super-large ensemble simulation dataset with 110 members has been produced by the fully coupled model FGOALS-g3 developed by researchers at the Institute of Atmospheric Physics,Chinese Academy of Sciences.This is the first dataset of large ensemble simulations with a climate system model developed by a Chinese modeling center.The simulation has the largest realizations up to now worldwide in terms of single-model initial-condition large ensembles.Each member includes a historical experiment(1850-2014)and an experiment(2015-99)under the very high greenhouse gas emissions Shared Socioeconomic Pathway scenario(SSP5-8.5).The dataset includes monthly and daily temperature,precipitation,and other variables,requiring storage of 275 TB.Additionally,the surface air temperature(SAT)and land precipitation simulated by the FGOALS-g3 super-large ensemble have been validated and projected.The ensemble can capture the response of SAT and land precipitation to external forcings well,and the internal variabilities can be quantified.The availability of more than 100 realizations will help researchers to study rare events and improve the understanding of the impact of internal variability on forced climate changes.展开更多
Summer precipitation anomalies over eastern China axe characterized spatially by meridionally banded structnres fluctu- ating on interannual and interdecadal timescales, leading to regional droughts and floods. In add...Summer precipitation anomalies over eastern China axe characterized spatially by meridionally banded structnres fluctu- ating on interannual and interdecadal timescales, leading to regional droughts and floods. In addition to long-term trends, how these patterns may change under global warming has important implications for agricultural planning and water resources over this densely populated area. Using the latest Hadley Centre climate model, HadGEM3-GC2, this paper investigates the potential response of summer precipitation patterns over this region, by comparing the leading modes between a 4×CQ simulation and the model＇s pre-industrial control simulation. Empirical Orthogonal Function （EOF） analyses show that the first two leading modes account for about 20% of summer rainfall variability. EOF1 is a monopole mode associated with the developing phase of ENSO events and EOF2 is a dipole mode associated with the decaying phase of ENSO. Under 4×CO2 forcing, the dipole mode with a south-north orientation becomes dominant because of a strengthened influence from exces- sive warming of the Indian Ocean. On interdecadal time scales, the first EOF looks very different from the control simulation, showing a dipole mode of east-west contrast with enhanced influence from high latitudes.展开更多
Heavy metal pollution is a major issue after tailing pond failure accident.It is important to predict pollution trends for limited data of pollution sources.A simple phase separation heavy metal model was built for ea...Heavy metal pollution is a major issue after tailing pond failure accident.It is important to predict pollution trends for limited data of pollution sources.A simple phase separation heavy metal model was built for early warning simulation of heavy metal pollution accidents.Based on this,a new simulation framework has been developed to predict the pollution trends of the downstream according to the measured data at upstream sections.By setting the upstream monitoring date as the inflow boundary condition,the changing processes of heavy metal manganese(Mn) with different phases in the downstream can be accurately simulated and forecasted.Results showed that the concentration of the suspended phase in the downstream was larger than that in the aqueous phase and sediment phase.With this,the early warning of pollution trends after accidents could be made a few days ahead.It indicates that the impact of sediment on heavy metal should not be ignored in the early warning of tailing pond failure accidents.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.42422502 and 42275038)the China Meteorological Administration Climate Change Special Program (Grant No.QBZ202306)funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)。
文摘This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.
基金supported in part by the National Natural Science Foundation of China(U2034209)the Postdoctoral Science Foundation of Chongqing(cstc2021jcyj-bsh X0047)+1 种基金the Fundamental Research Funds for the Central Universities(2022CDJJMRH-008)the National Natural Science Foundation of China(62203075)
文摘Dear Editor,This letter focuses on the remaining useful life(RUL)prediction task under limited labeled samples.Existing machine-learning-based RUL prediction methods for this task usually pay attention to mining degradation information to improve the prediction accuracy of degradation value or health indicator for the next epoch.However,they ignore the cumulative prediction error caused by iterations before reaching the failure point.
基金supported in part by the National Natural Science Foundation of China(No.62222120)the National Key Research and Development Program of China(No.2024YFB3909804)the Shandong Provincial Natural Science Foundation(No.ZR2024JQ003).
文摘Micro-Doppler parameter estimation is crucial for moving targets.However,conventional methods face limitations like inadequate time-frequency(TF)resolution and poor generalization,while existing deep learning approaches often treat TF analysis as a fixed preprocessing step.To overcome these challenges,this paper introduces a radar micro-Doppler parameter estimation method based on a gated dual-path dynamic-wavelet convolutional network(GDWCN).The GDWCN is an end-to-end deep learning framework that maps raw radar signals to micro-motion parameters by integrating clutter suppression,gated dual-path module,feature extraction,and parameter regression.Its core innovation is a gated dual-path module that combines dynamic convolution and learnable wavelet convolution,selecting the optimal processing path based on input signal characteristics.For the Inspire 2 drone,GDWCN reduced the mean absolute error(MAE)of frequency estimation by approximately 38%compared to the enhanced time-frequency micro-Doppler network,and its relative error by approximately 69%compared to the short-time Fourier transform(STFT),and 58%over the local maximum synchroextracting transform.Ablation studies further confirm the efficacy of the clutter suppression module and the attention mechanism.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFE0202600)the National Natural Science Foundation of China(Grant No.52272268)+3 种基金the Key Research Program of Frontier SciencesCAS(Grant No.QYZDJ-SSWSLH013)the Informatization Plan of Chinese Academy of Sciences(Grant No.CAS-WX2021SF-0102)the Youth Innovation Promotion Association of CAS(Grant No.2019005)。
文摘The kagome lattice,characterized by a hexagonal arrangement of corner-sharing equilateral triangles,has garnered significant attention as a fascinating quantum material system that hosts exotic magnetic and electronic properties.The identification and characterization of this class of materials are critical for advancing our understanding of their role in emergent phenomena such as superconductivity.In this study,we developed a high-throughput screening framework for the systematic identification and classification of superconducting materials with kagome lattices,integrating them into established materials databases.Leveraging the Materials Project(MP)database and the MDR Super Con dataset,we analyzed over 150000 inorganic compounds and cross-referenced 26000 known superconductors.Using geometry-based structural modeling and experimental validation,we identified 129 kagome superconductors belonging to 17 distinct structural families,many of which had not previously been recognized as kagome systems.The materials are further classified into three categories in terms of topological flat bands,clean band structures,and coexisting magnetic or charge density wave(CDW)orderings.Based on these results,we established a database comprising 129 kagome superconductors,including the detailed crystallographic,electronic,and superconducting properties of these materials.
基金supported by National Natural Science Foundation of China(No.81372344)
文摘Objective： To compare the survival outcomes of transabdominal （TA） and transthoracic （TT） surgical approaches in patients with Siewert-II/III esophagogastric junction adenocarcinoma. Methods： This retrospective study was conducted in patients with Siewert-II/III esophagogastric junction adenocarcinoma who underwent either TT or TA operations in the West China Hospital between January 2006 and December 2009. Results： A total of 308 patients （109 in the TT and 199 in the TA groups） were included in this study with a follow-up rate of 87.3%. The median （P25, P75） number of harvested perigastric lymph nodes was 8 （5, 10） in the TT group and 23 （16, 34） in the TA group （P〈0.001）, and the number of positive perigastric lymph nodes was 2 （0, 5） in the TT group and 3 （1, 8） in the TA group （P〈0.004）. The 5-year overall survival （OS） rate was 36% in the TT group and 51% in the TA group （P=0.005）. Subgroup analysis by Siewert classification showed that 5-year OS rates for patients with Siewert II tumors were 38% and 48% in TT and TA groups, respectively （P=0.134）, whereas the 5-year OS rate for patients with Siewert III tumors was significantly lower in the TT group than that in the TA group （33% vs. 53%; P=0.010）. Multivariate analysis indicated that N2 and N3 stages, RI/R2 resection and a TT surgical approach were prognostic factors for poor OS. Conclusions： Improved perigastric lymph node dissection may be the main reason for better survival outcomes observed with a TA gastrectomy approach than with TT gastrectomy for Siewert III tumor patients.
基金This work is jointly supported by the National Natural Science Foundation of China （41420104006 and 41330423）, and by the R＆D Special Fund for Public Welfare Industry （Meteorology） （GYHY201506012）.
文摘The Coupled Model Intercomparison Project （CMIP） is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Improving the performance of climate models over East Asia and the western North Pacific has been a challenge for the climate-modeling community. In this paper, we provide a synthesis robustness analysis of the climate models participating in CMIP-Phase 5 （CMIP5）. The strengths and weaknesses of the CMIP5 models are assessed from the perspective of climate mean state, interannual variability, past climate change during the mid-Pliocene （MP） and the last millennium, and climate projection. The added values of regional climate models relative to the driving global climate models are also assessed. Although an encouraging increase in credibility and an improvement in the simulation of mean states, interannual variability, and past climate changes are visible in the progression from CMIP3 to CMIPS, some previously noticed biases such as the ridge position of the western North Pacific subtropical high and the associated rainfall bias are still evident in CMIP5 models. Weaknesses are also evident in simulations of the interannual amplitude, such as El Nino- Southern Oscillation （ENSO）-monsoon relationships. Coupled models generally show better results than standalone atmospheric models in simulating both mean states and interannual variability. Multi-model intercomparison indicates significant uncertainties in the future projection of climate change, although precipitation increases consistently across models constrained by the Clausius-Clapeyron relation. Regional ocean-atmosphere coupled models are recommended for the dynamical downscaling of climate change oroiections over the East Asia-western North Pacific domain.
文摘The Delta-like ligand 4/Notch signaling pathway was shown to participate in the process of retinal development and angiogenesis. However, the function of the Delta-like ligand 4/Notch signaling pathway in retinopathy of prematurity requires further study. Retinopathy of prematurity was induced in 5-day-old Sprague-Dawley rats exposed to hyperoxia for 7 days, and then returned to room air. Reverse transcription-PCR and western blot revealed that Delta-like ligand 4 levels decreased at postnatal day 12 and increased at postnatal day 17 in retinopathy of prematurity rats. Flat-mounted adenosine diphosphatase stained retina and hematoxylin-eosin stained retinal tissue slices showed that the clock hour scores and the nuclei counts in retinopathy of prematurity rats were significantly different compared to normal control rats. After retinopathy of prematurity rats were intravitreally injected with Delta-like ligand 4 monoclonal antibody to inhibit the Delta-like ligand 4/Notch signaling pathway, there was a significant increase in the severity of retinal neovascularization （clock hours） in the intravitreally injected eyes. The nuclei count was highly correlated with the clock hour score. These results suggest that Delta-like ligand 4/Notch signaling plays an essential role in the process of physiological and pathological angiogenesis in the retina.
基金supported by the National Natural Science Foundation of China under Grant No.41988101the Chinese Academy of Sciences under Grant XDA20060102the China Postdoctoral Science Foundation under Grant No.2022T150638 and K.C.Wong Education Foundation.
文摘The unprecedented Zhengzhou heavy rainfall in July 2021 occurred under the background of a northward shift of the western Pacific subtropical high(WPSH).Although the occurrence of this extreme event could not be captured by seasonal predictions,a skillful prediction of the WPSH variation might have warned us of the increased probability of extreme weather events in Central and Northern China.However,the mechanism for the WPSH variation in July 2021 and its seasonal predictability are still unknown.Here,the observed northward shift of the WPSH in July 2021 is shown to correspond to a meridional dipole pattern of the 850-hPa geopotential height to the east of China,the amplitude of which became the strongest since 1979.The meridional dipole pattern is two nodes of the Pacific–Japan pattern.To investigate the predictability of the WPSH variation,a 21-member ensemble of seasonal predictions initiated from the end of June 2021 was conducted.The predictable and unpredictable components of the meridional dipole pattern were identified from the ensemble simulations.Its predictable component is driven by positive precipitation anomalies over the tropical western Pacific.The positive precipitation anomalies are caused by positive horizonal advection of the mean moist enthalpy by southwesterly anomalies to the northwestern flank of anticyclonic anomalies excited by the existing La Niña,which is skillfully predicted by the model.The leading mode of the unpredictable component is associated with the atmospheric internal intraseasonal oscillations,which are not initialized in the simulations.The relative contributions of the predictable and unpredictable components to the observed northward shift of the WPSH at 850 hPa are 28.0%and 72.0%,respectively.
基金supported by the National Natural Science Foundation of China(Grant Nos.41988101,,42105047).
文摘An undersea volcano at Hunga Tonga-Hunga Ha'apai(HTHH)near the South Pacific island nation of Tonga,erupted violently on 15 January 2022.Potential climate impact of the HTHH volcanic eruption is of great concern to the public;here,we intend to size up the impact of the HTHH eruption from a historical perspective.The influence of historical volcanic eruptions on the global climate are firstly reviewed,which are thought to have contributed to decreased surface temperature,increased stratospheric temperature,suppressed global water cycle,weakened monsoon circulation and El Niño-like sea surface temperature.Our understanding of the impacts of past volcanic eruptions on global-scale climate provides potential implication to evaluate the impact of the HTHH eruption.Based on historical simulations,we estimate that the current HTHH eruption with an intensity of 0.4 Tg SO_(2)injection will decrease the global mean surface temperature by only 0.004℃in the first year after eruption,which is within the amplitude of internal variability at the interannual time scale and thus not strong enough to have significant impacts on the global climate.
基金supported by the National Natural Science Foundation of China(51505116)the Fundamental Research Funds for the Central Universities(JZ2016HGTB0716)+2 种基金Natural and Science Foundation of Anhui Province(1508085SME221)China Postdoctoral Science Foundation(2016M590563)the Science and Technology Public Relations Project of Anhui Province(1604a0902181)
文摘This paper focuses on the problem of the adaptive robust control of a lower limbs rehabilitation robot(LLRR) that is a nonlinear system running under passive training mode. In reality, uncertainties including modeling error, initial condition deviation, friction force and other unknown external disturbances always exist in a LLRR system. So, it is necessary to consider the uncertainties in the unilateral man-machine dynamical model of the LLRR we described. In the dynamical model, uncertainties are(possibly fast) time-varying and bounded. However, the bounds are unknown. Based on the dynamical model, we design an adaptive robust control with an adaptive law that is leakagetype based and on the framework of Udwadia-Kalaba theory to compensate for the uncertainties and to realize tracking control of the LLRR. Furthermore, the effectiveness of designed control is shown with numerical simulations.
基金supported by the National Natural Science Foundation of China (Grant No. 41330423, 41420104006 & 41530426 )the International Partnership Program of Chinese Academy of Sciences under Grant No.134111KYSB20160031
文摘Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a central focus of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences(LASG/IAP) since the establishment of the laboratory in 1985. In China, many pioneering component models and fully coupled models of the climate system have been developed by LASG/IAP. The fully coupled climate system developed in the recent decade is named FGOALS(Flexible Global Ocean-Atmosphere-Land System Model). In this paper, an application-oriented review of the LASG/IAP FGOALS model is presented. The improved model performances are demonstrated in the context of cloud-radiation processes, Asian monsoon, ENSO phenomena, Atlantic Meridional Overturning Circulation(AMOC) and sea ice. The FGOALS model has contributed to both CMIP5(Coupled Model Intercomparison Project-phase 5) and IPCC(Intergovernmental Panel on Climate Change) AR5(the Fifth Assessment Report). The release of FGOALS data has supported the publication of nearly 500 papers around the world. The results of FGOALS are cited ~106 times in the IPCC WG1(Working Group 1) AR5. In addition to the traditional long-term simulations and projections, near-term decadal climate prediction is a new set of CMIP experiment, progress of LAGS/IAP in the development of nearterm decadal prediction system is reviewed. The FGOALS model has supported many Chinese national-level research projects and contributed to the national climate change assessment report. The crucial role of FGOALS as a modeling tool for supporting climate sciences is highlighted by demonstrating the model's performances in the simulation of the evolution of Earth's climate from the past to the future.
基金supported by the National Key Program for Developing Basic Sciences (Grant No. 2020YFA0608902)the National Natural Science Foundation of China (Grant Nos. 41976026 and 41931183)the technical support from the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (Earth Lab)
文摘A super-large ensemble simulation dataset with 110 members has been produced by the fully coupled model FGOALS-g3 developed by researchers at the Institute of Atmospheric Physics,Chinese Academy of Sciences.This is the first dataset of large ensemble simulations with a climate system model developed by a Chinese modeling center.The simulation has the largest realizations up to now worldwide in terms of single-model initial-condition large ensembles.Each member includes a historical experiment(1850-2014)and an experiment(2015-99)under the very high greenhouse gas emissions Shared Socioeconomic Pathway scenario(SSP5-8.5).The dataset includes monthly and daily temperature,precipitation,and other variables,requiring storage of 275 TB.Additionally,the surface air temperature(SAT)and land precipitation simulated by the FGOALS-g3 super-large ensemble have been validated and projected.The ensemble can capture the response of SAT and land precipitation to external forcings well,and the internal variabilities can be quantified.The availability of more than 100 realizations will help researchers to study rare events and improve the understanding of the impact of internal variability on forced climate changes.
基金jointly sponsored by the National Key R&D Program of China(Grant No.2016YFA0600404)the National Natural Science Foundation of China(Grant Nos.41530532 and 41605057)+1 种基金the China Special Fund for Meteorological Research in the Public Interest(Grant No.GYHY201506001-1)the Jiangsu Collaborative Innovation Center for Climate Change,and the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP) China as part of the Newton Fund
文摘Summer precipitation anomalies over eastern China axe characterized spatially by meridionally banded structnres fluctu- ating on interannual and interdecadal timescales, leading to regional droughts and floods. In addition to long-term trends, how these patterns may change under global warming has important implications for agricultural planning and water resources over this densely populated area. Using the latest Hadley Centre climate model, HadGEM3-GC2, this paper investigates the potential response of summer precipitation patterns over this region, by comparing the leading modes between a 4×CQ simulation and the model＇s pre-industrial control simulation. Empirical Orthogonal Function （EOF） analyses show that the first two leading modes account for about 20% of summer rainfall variability. EOF1 is a monopole mode associated with the developing phase of ENSO events and EOF2 is a dipole mode associated with the decaying phase of ENSO. Under 4×CO2 forcing, the dipole mode with a south-north orientation becomes dominant because of a strengthened influence from exces- sive warming of the Indian Ocean. On interdecadal time scales, the first EOF looks very different from the control simulation, showing a dipole mode of east-west contrast with enhanced influence from high latitudes.
基金supported by the National Nature Science Foundation of China (No.41807471)the Fundamental Research Funds for the Central Universities,China University of Geosciences (Wuhan)(Nos.G1323519399 and 162301182698)。
文摘Heavy metal pollution is a major issue after tailing pond failure accident.It is important to predict pollution trends for limited data of pollution sources.A simple phase separation heavy metal model was built for early warning simulation of heavy metal pollution accidents.Based on this,a new simulation framework has been developed to predict the pollution trends of the downstream according to the measured data at upstream sections.By setting the upstream monitoring date as the inflow boundary condition,the changing processes of heavy metal manganese(Mn) with different phases in the downstream can be accurately simulated and forecasted.Results showed that the concentration of the suspended phase in the downstream was larger than that in the aqueous phase and sediment phase.With this,the early warning of pollution trends after accidents could be made a few days ahead.It indicates that the impact of sediment on heavy metal should not be ignored in the early warning of tailing pond failure accidents.
