Objectives:Glioblastoma is a prevalent malignant brain tumor,and the actions of the long non-coding RNA HOXA10-AS in its invasion and migration remain unclear.Here,the function of HOXA10-AS in glioblastoma cell invasi...Objectives:Glioblastoma is a prevalent malignant brain tumor,and the actions of the long non-coding RNA HOXA10-AS in its invasion and migration remain unclear.Here,the function of HOXA10-AS in glioblastoma cell invasion and migration and associated mechanisms were investigated.Methods:HOXA10-AS was knocked down in glioblastoma cells,and Transwell and wound healing assays were conducted to elucidate its impacts on cell invasion and migration.Western blotting and quantitative reverse transcription polymerase chain reaction(qRTPCR)assessed HOXA10-AS’s impact on the epithelial-mesenchymal transition(EMT).Microarray analysis identified differentially expressed genes,complemented by bioinformatics approaches to explore potentialmolecular participants and pathways.Rescue experiments validated our findings.Results:HOXA10-AS knockdown significantly inhibits glioblastoma cell migration,invasion,and the EMT process.Specifically,HOXA10-AS siRNA transfection significantly reduced the migratory capacity of A172 cells by 50.5%and U251 cells by 61.4%,as well as their invasive capacities by 33.8%and 58.5%,respectively(all p<0.05).HOXA10-AS acts as anmiR-99a-3p sponge,and pathway analysis identified processes linked to tumorigenesis andmetastasis,alongwith nine hub genes.HOXA10-AS upregulates the expression of integrin subunit beta 5(ITGB5)through a competing endogenous RNAmechanism.Thereduced tumorigenic behavior of glioblastoma cells due toHOXA10-AS knockdown can be rescued by ITGB5 overexpression ormiR-99a-3p inhibitor.Conclusion:These results indicate thatHOXA10-AS promotes tumorigenic behavior in glioblastoma cells by regulating the EMT-like process and functioning as an miR-99a-3p sponge to modulate ITGB5 levels,providing insights into glioblastoma development and potential therapeutic targets.展开更多
Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potenti...Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.展开更多
The advancement of high-performance zinc-air battery systems necessitates the development of highly effective non-precious metal-based bifunctional electrocatalysts capable of synergistically enhancing both oxygen red...The advancement of high-performance zinc-air battery systems necessitates the development of highly effective non-precious metal-based bifunctional electrocatalysts capable of synergistically enhancing both oxygen reduction reaction(ORR)and oxygen evolution reaction(OER).To address the critical limitations of conventional non-precious catalysts in balancing multiple active sites and structural stability,we introduce an innovative in situ synthesis approach for constructing Fe_(2)P/FeNi bimetallic heterogeneous nanoparticles encapsulated within nitrogen-phosphorus dual-doped carbon matrices featuring interconnected leaf-like nanostructures(Fe_(2)P/FeNi@NPC).This architecturally optimized configuration not only mitigates transition metal degradation through protective carbon confinement but also facilitates rapid charge transfer kinetics and efficient mass diffusion pathways,substantially improving both catalytic efficiency and operational durability.Through comprehensive characterizations combining insitu monitoring and ex-situ analysis,the dynamic evolution of active sites during electrochemical operations is systematically tracked,and the genuine catalytic centers and spin state are identified.The optimized Fe_(2)P/FeNi@NPC composite exhibited remarkable electrochemical performance in alkaline media,achieving a superior ORR half-wave potential of 0.83 V and requiring only 1.62 V to achieve a current density of 10 mA cm^(-2)for OER.Notably,the assembled rechargeable zinc-air batteries(ZABs)exhibited a high specific capacity of 755.08 mAh g^(-1),a low charge-discharge voltage difference of 0.79 V,and exceptional cycling stability of over 1400 h.Furthermore,the flexible ZAB maintains excellent cycling performance even when subjected to various bending conditions.This work provides valuable insights into atomic-and electronic-scale dual-regulation strategy,offering a promising pathway to overcome current limitations in non-precious metal-based electrocatalysts for practical applications in metal-air battery systems.展开更多
U-shaped micro-nanochannels can generate significant flow disturbance as well as locally amplified electric field, which gives itself potential to be microfluidic mixers, electrokinetic pumps,and even cell lysis proce...U-shaped micro-nanochannels can generate significant flow disturbance as well as locally amplified electric field, which gives itself potential to be microfluidic mixers, electrokinetic pumps,and even cell lysis process. Numerical simulation is utilized in this work to study the hidden characteristics of the U-shaped micro-nanochannel system, and the effects of key controlling parameters(the external voltage and pressure) on the device output metrics(current, maximum values of electric field, shear stress and flow velocity) were evaluated. A large portion of current flowing through the whole system goes through the nanochannels, rather than the middle part of the microchannel, with its value increasing linearly with the increase of voltage. Due to the local ion depletion near micro-nanofluidic junction, significantly enhanced electric field(as much as 15 fold at V=1 V and P_0=0) as well as strong shear stress(leading to electrokinetic flow) is generated.With increasing external pressure, both electric field and shear stress can be increased initially(due to shortening of depletion region length), but are suppressed eventually at higher pressure due to the destruction of ion depletion layer. Insights gained from this study could be useful for designing nonlinear electrokinetic pumps and other systems.展开更多
Earthquake prediction practice and a large number of earthquake cases show that anomalous images of small earthquake belts may appear near the epicenter before strong earthquakes.Through the research of earthquake cas...Earthquake prediction practice and a large number of earthquake cases show that anomalous images of small earthquake belts may appear near the epicenter before strong earthquakes.Through the research of earthquake cases,researchers have a relatively consistent method to determine the clarity of an identified seismic belt,but there is still a lack of method on seismic belt identification from the distribution of scattered points.Due to the complexity of exhaustive algorithm,the rapid automatic identification technique of seismic belts has been progressing slowly.Visual recognition is still the basic method of seismic belt identification.Based on the algorithm of distance correlation,this paper presents a fast automatic identification method of seismic belts.The effectiveness of this method was proved by 100 random earthquakes and an example of seismic belts of magnitude 4.0 before the 2005 Jiujiang M5.7 earthquake.The results show that:①the automatic identification of seismic belts should first identify the"relational earthquake",then identify the"suspected seismic belt",and finally use the criterion of seismic belt clarity to determine;②random earthquakes and real earthquakes identification results show that the distance correlation method can realize the fast automatic identification of seismic belts by computer.展开更多
Circulating tumor cells(CTCs)are essential biomarkers for liquid biopsies,which are important in the early screening,prognosis,and real-time monitoring of cancer.However,CTCs are less abundant in the peripheral blood ...Circulating tumor cells(CTCs)are essential biomarkers for liquid biopsies,which are important in the early screening,prognosis,and real-time monitoring of cancer.However,CTCs are less abundant in the peripheral blood of patients,therefore,their isolation is necessary.Recently,the use of microfluidics for CTC sorting has become a research hotspot owing to its low cost,ease of integration,low sample consumption,and unique advantages in the manipulation of micron-sized particles.Herein,we review the latest research on microfluidics-based CTC sorting.Specifically,we consider active sorting using external fields(electric,magnetic,acoustic,and optical tweezers)and passive sorting using the flow effects of cells in specific channel structures(microfiltration sorting,deterministic lateral displacement sorting,and inertial sorting).The advantages and limitations of each method and their recent applications are summarized here.To conclude,a forward-looking perspective is presented on future research on the microfluidic sorting of CTCs.展开更多
Modelling,predicting and analysing driver behaviours are essential to advanced driver assistance systems(ADAS)and the comprehensive understanding of complex driving scenarios.Recently,with the development of deep lear...Modelling,predicting and analysing driver behaviours are essential to advanced driver assistance systems(ADAS)and the comprehensive understanding of complex driving scenarios.Recently,with the development of deep learning(DL),numerous driver behaviour learning(DBL)methods have been proposed and applied in connected vehicles(CV)and intelligent transportation systems(ITS).This study provides a review of DBL,which mainly focuses on typical applications in CV and ITS.First,a comprehensive review of the state-of-the-art DBL is presented.Next,Given the constantly changing nature of real driving scenarios,most existing learning-based models may suffer from the so-called“catastrophic forgetting,”which refers to their inability to perform well in previously learned scenarios after acquiring new ones.As a solution to the aforementioned issue,this paper presents a framework for continual driver behaviour learning(CDBL)by leveraging continual learning technology.The proposed CDBL framework is demonstrated to outperform existing methods in behaviour prediction through a case study.Finally,future works,potential challenges and emerging trends in this area are highlighted.展开更多
Due to the high mileage and heavy load capabilities of hybrid electric vehicles(HEVs),energy management becomes crucial in improving energy efficiency.To avoid the over-dependence on the hard-crafted models,deep reinf...Due to the high mileage and heavy load capabilities of hybrid electric vehicles(HEVs),energy management becomes crucial in improving energy efficiency.To avoid the over-dependence on the hard-crafted models,deep reinforcement learning(DRL)is utilized to learn more precise energy management strategies(EMSs),but cannot generalize well to different driving situations in most cases.When driving cycles are changed,the neural network needs to be retrained,which is a time-consuming and laborious task.A more efficient transferable way is to combine DRL algorithms with transfer learning,which can utilize the knowledge of the driving cycles in other new driving situations,leading to better initial performance and a faster training process to convergence.In this paper,we propose a novel transferable EMS by incorporating the DRL method and dueling network architecture for HEVs.Simulation results indicate that the proposed method can generalize well to new driving cycles,with comparably initial performance and faster convergence in the training process.展开更多
Background The clinical manifestations of cerebrovascular disease are known to differ between the Chinese and United States(US)populations as do the plaque features on imaging.Objectives The aim of this study was to i...Background The clinical manifestations of cerebrovascular disease are known to differ between the Chinese and United States(US)populations as do the plaque features on imaging.Objectives The aim of this study was to investigate and compare the histological features of excised carotid plaques from Chinese and US patients.Methods Carotid endarterectomy specimens collected from two prospective studies were included.The entire plaque was serially sectioned(10-µm thickness)at 0.5-1 mm intervals.Hematoxylin and eosin staining and Mallory’s trichrome staining were performed.The morphology and components of the plaques were measured and compared between the two groups.Results A total of 1152 histological sections from 75 Chinese patients and 1843 sections from 111 US patients were analyzed.The Chinese group had significantly smaller minimum lumen diameters(median:1.1 vs.1.3 mm,p=0.046)and a larger percent wall volume(median:74%vs.70%,p=0.018)than the US group.After adjusting for confounding factors,carotid plaques in the Chinese population had larger lipid pools(β=10.0%,95%CI:4.9 to 15.9%),more recent intraplaque hemorrhage(IPH;β=8.4%,95%CI:4.5 to 12.7%),less late IPH(β=-8.2%,95%CI:-11.3 to-5.4),and fewer fibrous cap disruptions(45%vs.67%,p=0.061).Chinese plaques were more homogeneous and had a higher percentage of plaques with features of xanthomas than did US plaques(20%vs 2.7%,p<0.001).Conclusions The histology of Chinese plaques differs significantly from that of U.S.plaques,suggesting substantial differences in the pathophysiology of atherosclerotic cerebrovascular disease between Chinese and North American populations,which indicates a need for a different management approach.展开更多
基金supported by the National Natural Science Foundation of China(No.82001243).
文摘Objectives:Glioblastoma is a prevalent malignant brain tumor,and the actions of the long non-coding RNA HOXA10-AS in its invasion and migration remain unclear.Here,the function of HOXA10-AS in glioblastoma cell invasion and migration and associated mechanisms were investigated.Methods:HOXA10-AS was knocked down in glioblastoma cells,and Transwell and wound healing assays were conducted to elucidate its impacts on cell invasion and migration.Western blotting and quantitative reverse transcription polymerase chain reaction(qRTPCR)assessed HOXA10-AS’s impact on the epithelial-mesenchymal transition(EMT).Microarray analysis identified differentially expressed genes,complemented by bioinformatics approaches to explore potentialmolecular participants and pathways.Rescue experiments validated our findings.Results:HOXA10-AS knockdown significantly inhibits glioblastoma cell migration,invasion,and the EMT process.Specifically,HOXA10-AS siRNA transfection significantly reduced the migratory capacity of A172 cells by 50.5%and U251 cells by 61.4%,as well as their invasive capacities by 33.8%and 58.5%,respectively(all p<0.05).HOXA10-AS acts as anmiR-99a-3p sponge,and pathway analysis identified processes linked to tumorigenesis andmetastasis,alongwith nine hub genes.HOXA10-AS upregulates the expression of integrin subunit beta 5(ITGB5)through a competing endogenous RNAmechanism.Thereduced tumorigenic behavior of glioblastoma cells due toHOXA10-AS knockdown can be rescued by ITGB5 overexpression ormiR-99a-3p inhibitor.Conclusion:These results indicate thatHOXA10-AS promotes tumorigenic behavior in glioblastoma cells by regulating the EMT-like process and functioning as an miR-99a-3p sponge to modulate ITGB5 levels,providing insights into glioblastoma development and potential therapeutic targets.
基金supported by the proactive SAFEty systems and tools for a constantly UPgrading road environment(SAFE-UP)projectfunding from the European Union’s Horizon 2020 Research and Innovation Program(861570)。
文摘Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.
基金supported by the National Natural Science Foundation of China(Nos.22008058,No 22279135)the Natural Science Foundation of Hubei Province(No.2023AFB1010)+1 种基金the Key Project of Scientific Plan of Education Department of Hubei Province(No.D20232501)the CAS Strategic Leading Science&Technology Program(B)(XDB1040203)。
文摘The advancement of high-performance zinc-air battery systems necessitates the development of highly effective non-precious metal-based bifunctional electrocatalysts capable of synergistically enhancing both oxygen reduction reaction(ORR)and oxygen evolution reaction(OER).To address the critical limitations of conventional non-precious catalysts in balancing multiple active sites and structural stability,we introduce an innovative in situ synthesis approach for constructing Fe_(2)P/FeNi bimetallic heterogeneous nanoparticles encapsulated within nitrogen-phosphorus dual-doped carbon matrices featuring interconnected leaf-like nanostructures(Fe_(2)P/FeNi@NPC).This architecturally optimized configuration not only mitigates transition metal degradation through protective carbon confinement but also facilitates rapid charge transfer kinetics and efficient mass diffusion pathways,substantially improving both catalytic efficiency and operational durability.Through comprehensive characterizations combining insitu monitoring and ex-situ analysis,the dynamic evolution of active sites during electrochemical operations is systematically tracked,and the genuine catalytic centers and spin state are identified.The optimized Fe_(2)P/FeNi@NPC composite exhibited remarkable electrochemical performance in alkaline media,achieving a superior ORR half-wave potential of 0.83 V and requiring only 1.62 V to achieve a current density of 10 mA cm^(-2)for OER.Notably,the assembled rechargeable zinc-air batteries(ZABs)exhibited a high specific capacity of 755.08 mAh g^(-1),a low charge-discharge voltage difference of 0.79 V,and exceptional cycling stability of over 1400 h.Furthermore,the flexible ZAB maintains excellent cycling performance even when subjected to various bending conditions.This work provides valuable insights into atomic-and electronic-scale dual-regulation strategy,offering a promising pathway to overcome current limitations in non-precious metal-based electrocatalysts for practical applications in metal-air battery systems.
基金supported by the Intergovernmental International Science,Technology and Innovation Cooperation Key Project of the National Key R&D Programme(2016YFE0105900)the National Natural Science Foundation of China(21576130and 11372229)Kuwait Foundation for the Advancement of Sciences(Kuwait-MIT signature project,Project code:P31475EC01)
文摘U-shaped micro-nanochannels can generate significant flow disturbance as well as locally amplified electric field, which gives itself potential to be microfluidic mixers, electrokinetic pumps,and even cell lysis process. Numerical simulation is utilized in this work to study the hidden characteristics of the U-shaped micro-nanochannel system, and the effects of key controlling parameters(the external voltage and pressure) on the device output metrics(current, maximum values of electric field, shear stress and flow velocity) were evaluated. A large portion of current flowing through the whole system goes through the nanochannels, rather than the middle part of the microchannel, with its value increasing linearly with the increase of voltage. Due to the local ion depletion near micro-nanofluidic junction, significantly enhanced electric field(as much as 15 fold at V=1 V and P_0=0) as well as strong shear stress(leading to electrokinetic flow) is generated.With increasing external pressure, both electric field and shear stress can be increased initially(due to shortening of depletion region length), but are suppressed eventually at higher pressure due to the destruction of ion depletion layer. Insights gained from this study could be useful for designing nonlinear electrokinetic pumps and other systems.
基金the Major State Basic Research Development Program of China(NO.2017YFC 1500502-05)the National Natural Science Foundation of China(No.11672258)We would like to thank Mingxiao Li,Zhiping Song,Gang Li and Yang Zang for the valuable discussions.
文摘Earthquake prediction practice and a large number of earthquake cases show that anomalous images of small earthquake belts may appear near the epicenter before strong earthquakes.Through the research of earthquake cases,researchers have a relatively consistent method to determine the clarity of an identified seismic belt,but there is still a lack of method on seismic belt identification from the distribution of scattered points.Due to the complexity of exhaustive algorithm,the rapid automatic identification technique of seismic belts has been progressing slowly.Visual recognition is still the basic method of seismic belt identification.Based on the algorithm of distance correlation,this paper presents a fast automatic identification method of seismic belts.The effectiveness of this method was proved by 100 random earthquakes and an example of seismic belts of magnitude 4.0 before the 2005 Jiujiang M5.7 earthquake.The results show that:①the automatic identification of seismic belts should first identify the"relational earthquake",then identify the"suspected seismic belt",and finally use the criterion of seismic belt clarity to determine;②random earthquakes and real earthquakes identification results show that the distance correlation method can realize the fast automatic identification of seismic belts by computer.
基金supported by the Science and Technology Project of the Hebei Education Department[No.BJK2023016]the Central Guidance on Local Science and Technology Development Fund[Grant No.226Z1701G].
文摘Circulating tumor cells(CTCs)are essential biomarkers for liquid biopsies,which are important in the early screening,prognosis,and real-time monitoring of cancer.However,CTCs are less abundant in the peripheral blood of patients,therefore,their isolation is necessary.Recently,the use of microfluidics for CTC sorting has become a research hotspot owing to its low cost,ease of integration,low sample consumption,and unique advantages in the manipulation of micron-sized particles.Herein,we review the latest research on microfluidics-based CTC sorting.Specifically,we consider active sorting using external fields(electric,magnetic,acoustic,and optical tweezers)and passive sorting using the flow effects of cells in specific channel structures(microfiltration sorting,deterministic lateral displacement sorting,and inertial sorting).The advantages and limitations of each method and their recent applications are summarized here.To conclude,a forward-looking perspective is presented on future research on the microfluidic sorting of CTCs.
基金Supported by the National Key Research and Development Program of China(No.2022ZD0115503).
文摘Modelling,predicting and analysing driver behaviours are essential to advanced driver assistance systems(ADAS)and the comprehensive understanding of complex driving scenarios.Recently,with the development of deep learning(DL),numerous driver behaviour learning(DBL)methods have been proposed and applied in connected vehicles(CV)and intelligent transportation systems(ITS).This study provides a review of DBL,which mainly focuses on typical applications in CV and ITS.First,a comprehensive review of the state-of-the-art DBL is presented.Next,Given the constantly changing nature of real driving scenarios,most existing learning-based models may suffer from the so-called“catastrophic forgetting,”which refers to their inability to perform well in previously learned scenarios after acquiring new ones.As a solution to the aforementioned issue,this paper presents a framework for continual driver behaviour learning(CDBL)by leveraging continual learning technology.The proposed CDBL framework is demonstrated to outperform existing methods in behaviour prediction through a case study.Finally,future works,potential challenges and emerging trends in this area are highlighted.
文摘Due to the high mileage and heavy load capabilities of hybrid electric vehicles(HEVs),energy management becomes crucial in improving energy efficiency.To avoid the over-dependence on the hard-crafted models,deep reinforcement learning(DRL)is utilized to learn more precise energy management strategies(EMSs),but cannot generalize well to different driving situations in most cases.When driving cycles are changed,the neural network needs to be retrained,which is a time-consuming and laborious task.A more efficient transferable way is to combine DRL algorithms with transfer learning,which can utilize the knowledge of the driving cycles in other new driving situations,leading to better initial performance and a faster training process to convergence.In this paper,we propose a novel transferable EMS by incorporating the DRL method and dueling network architecture for HEVs.Simulation results indicate that the proposed method can generalize well to new driving cycles,with comparably initial performance and faster convergence in the training process.
基金funded by the National Institutes of Health(R01 NS083503)the National Natural Science Foundation of China(81361120402 and 62271061)the Beijing Natural Science Foundation(L232130).
文摘Background The clinical manifestations of cerebrovascular disease are known to differ between the Chinese and United States(US)populations as do the plaque features on imaging.Objectives The aim of this study was to investigate and compare the histological features of excised carotid plaques from Chinese and US patients.Methods Carotid endarterectomy specimens collected from two prospective studies were included.The entire plaque was serially sectioned(10-µm thickness)at 0.5-1 mm intervals.Hematoxylin and eosin staining and Mallory’s trichrome staining were performed.The morphology and components of the plaques were measured and compared between the two groups.Results A total of 1152 histological sections from 75 Chinese patients and 1843 sections from 111 US patients were analyzed.The Chinese group had significantly smaller minimum lumen diameters(median:1.1 vs.1.3 mm,p=0.046)and a larger percent wall volume(median:74%vs.70%,p=0.018)than the US group.After adjusting for confounding factors,carotid plaques in the Chinese population had larger lipid pools(β=10.0%,95%CI:4.9 to 15.9%),more recent intraplaque hemorrhage(IPH;β=8.4%,95%CI:4.5 to 12.7%),less late IPH(β=-8.2%,95%CI:-11.3 to-5.4),and fewer fibrous cap disruptions(45%vs.67%,p=0.061).Chinese plaques were more homogeneous and had a higher percentage of plaques with features of xanthomas than did US plaques(20%vs 2.7%,p<0.001).Conclusions The histology of Chinese plaques differs significantly from that of U.S.plaques,suggesting substantial differences in the pathophysiology of atherosclerotic cerebrovascular disease between Chinese and North American populations,which indicates a need for a different management approach.
基金the funding support from the National Natural Science Foundation of China (22325903,22221003,and 22071225)the National Key Research and Development Program of China (2018YFA0702001)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project (202203a0520013 and 2021d05050006)the USTC Research Funds of the Double First-Class Initiative (YD2060002032)。
