Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal ballistics.We evaluate the performance of four popular ML-based regression mode...Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal ballistics.We evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite thickness.To achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release sources.We demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this range.Although extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is required.To circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss function.The physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when not.The resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical approach.Compared with numerical analysis tools such as finite element solvers the ML models run orders of magnitude faster.We provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballistics problems.展开更多
Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electroche...Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electrochemical and colorimetric dual-mode detection for NoV based on the excellent dual catalytic properties of copper peroxide/COF-NH_(2)nanocomposite(CuO_(2)@COF-NH_(2)).For the colorimetric detection,NoV can be directly detected by the naked eye based on CuO_(2)@COF-NH_(2)as a laccase-like nonazyme using“peptide-NoV-antibody”recognition mode.The colorimetric assay displayed a wide and quality linear detection range from 1 copy/mL to 5000 copies/mL of NoV with a low limit of detection(LOD)of 0.125 copy/mL.For the electrochemical detection of NoV,CuO_(2)@COF-NH_(2)showed an oxidation peak of copper ion from Cu^(+)to Cu^(2+)using“peptide-NoV-antibody”recognition mode.The electrochemical assay showed a linear detection range was 1-5000 copies/mL with a LOD of 0.152 copy/mL.It's worthy to note that this assay does not need other electrical signal molecule,which provide the stable and sensitive electrochemial detection for NoV.The electrochemical and colorimetric dual-mode detection was used to detect NoV in foods and faceal samples,which has the potential for improving food safety and diagnosing of NoV-infected diarrhea.展开更多
Nowadays, the global climate is constantly being destroyed and the fluctuations in ambient temperature are becoming more frequent. However, conventional single-mode thermal management strategies(heating or cooling) fa...Nowadays, the global climate is constantly being destroyed and the fluctuations in ambient temperature are becoming more frequent. However, conventional single-mode thermal management strategies(heating or cooling) failed to resolve such dynamic temperature changes. Moreover, developing thermal management devices capable of accommodating these temperature variations while remaining simple to fabricate and durable has remained a formidable obstacle. To address these bottlenecks, we design and successfully fabricate a novel dual-mode hierarchical(DMH) composite film featuring a micronanofiber network structure, achieved through a straightforward two-step continuous electrospinning process. In cooling mode, it presents a high solar reflectivity of up to 97.7% and an excellent atmospheric transparent window(ATW) infrared emissivity of up to 98.9%. Noted that this DMH film could realize a cooling of 8.1 ℃ compared to the ambient temperature outdoors. In heating mode, it also exhibits a high solar absorptivity of 94.7% and heats up to 11.9 ℃ higher than black cotton fabric when utilized by individuals. In practical application scenarios, a seamless transition between efficient cooling and heating is achieved by simply flipping the film. More importantly, the DMH film combining the benefits of composites demonstrates portability, durability, and easy-cleaning, promising to achieve large-scale production and use of thermally managed textiles in the future. The energy savings offered by film applications provide a viable solution for the early realization of carbon neutrality.展开更多
We investigate the behavior of edge modes in the presence of different edge terminations and long-range(LR)hopping.Here,we mainly focus on such model crystals with two different types of structures(type I:“…-P-Q-P-Q...We investigate the behavior of edge modes in the presence of different edge terminations and long-range(LR)hopping.Here,we mainly focus on such model crystals with two different types of structures(type I:“…-P-Q-P-Q-…”and type II:“…=P-Q=P-Q=…”),where P and Q represent crystal lines(CLs),while the symbols“-”and“=”denote the distance between the nearest neighbor(NN)CLs.Based on the lattice model Hamiltonian with LR hopping,the existence of edge modes is determined analytically by using the transfer matrix method(TMM)when different edge terminals are taken into consideration.Our findings are consistent with the numerical results obtained by the exact diagonalization method.We also notice that edge modes can exhibit different behaviors under different edge terminals.Our result is helpful in solving novel edge modes in honeycomb crystalline graphene and transition metal dichalcogenides with different edge terminals.展开更多
This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a termi...This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.展开更多
针对弱引力场不规则小行星探测器安全下降与着陆,提出了一种基于比例微分(PD,Proportional plus Derivative)及非奇异Terminal滑模的连续控制方法.在着陆点坐标系下推导了探测器的动力学方程,设计了开环燃料次最优多项式标称轨迹制导方...针对弱引力场不规则小行星探测器安全下降与着陆,提出了一种基于比例微分(PD,Proportional plus Derivative)及非奇异Terminal滑模的连续控制方法.在着陆点坐标系下推导了探测器的动力学方程,设计了开环燃料次最优多项式标称轨迹制导方法.针对下降和着陆两个不同阶段提出了PD和非奇异Terminal滑模变结构连续控制方法.将PD控制的易操作性与非奇异Terminal滑模控制收敛速度快、调整时间短有效结合,保证了探测器安全着陆.仿真结果表明了提出方法的可行性和有效性.展开更多
文摘Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal ballistics.We evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite thickness.To achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release sources.We demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this range.Although extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is required.To circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss function.The physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when not.The resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical approach.Compared with numerical analysis tools such as finite element solvers the ML models run orders of magnitude faster.We provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballistics problems.
基金financially supported by National Key Research and Development Program of China(2022YFC2601604)Major science and technology project of Yunnan Province(202202AE090085)+9 种基金the National Natural Science Foundation of China(3216059732160236)Science and technology talent and platform plan of YunnanKey Scientific and Technology Project of Yunnan(202203AC100010)Spring City Plan:the High-level Talent Promotion and Training Project of Kunming(2022SCP001)the second phase of“Double-First Class”program construction of Yunnan Universitygrants from State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan,Yunnan University(2021KF005)Key Scientific and Technology Project of Yunnan(202002AE320005)Program for Excellent Young Talents of Yunnan Universitythe Program for Donglu Scholars of Yunnan University。
文摘Norovirus(NoV)is regarded as one of the most common causes of foodborne diarrhea in the world.It is urgent to identify the pathogenic microorganism of the diarrhea in short time.In this work,we developed an electrochemical and colorimetric dual-mode detection for NoV based on the excellent dual catalytic properties of copper peroxide/COF-NH_(2)nanocomposite(CuO_(2)@COF-NH_(2)).For the colorimetric detection,NoV can be directly detected by the naked eye based on CuO_(2)@COF-NH_(2)as a laccase-like nonazyme using“peptide-NoV-antibody”recognition mode.The colorimetric assay displayed a wide and quality linear detection range from 1 copy/mL to 5000 copies/mL of NoV with a low limit of detection(LOD)of 0.125 copy/mL.For the electrochemical detection of NoV,CuO_(2)@COF-NH_(2)showed an oxidation peak of copper ion from Cu^(+)to Cu^(2+)using“peptide-NoV-antibody”recognition mode.The electrochemical assay showed a linear detection range was 1-5000 copies/mL with a LOD of 0.152 copy/mL.It's worthy to note that this assay does not need other electrical signal molecule,which provide the stable and sensitive electrochemial detection for NoV.The electrochemical and colorimetric dual-mode detection was used to detect NoV in foods and faceal samples,which has the potential for improving food safety and diagnosing of NoV-infected diarrhea.
基金financially Fundamental Research Funds for the Central Universities (2232021G-04 and 2232020D-20)Student Innovation Fund of Donghua University (GSIF-DH-M-2021003)。
文摘Nowadays, the global climate is constantly being destroyed and the fluctuations in ambient temperature are becoming more frequent. However, conventional single-mode thermal management strategies(heating or cooling) failed to resolve such dynamic temperature changes. Moreover, developing thermal management devices capable of accommodating these temperature variations while remaining simple to fabricate and durable has remained a formidable obstacle. To address these bottlenecks, we design and successfully fabricate a novel dual-mode hierarchical(DMH) composite film featuring a micronanofiber network structure, achieved through a straightforward two-step continuous electrospinning process. In cooling mode, it presents a high solar reflectivity of up to 97.7% and an excellent atmospheric transparent window(ATW) infrared emissivity of up to 98.9%. Noted that this DMH film could realize a cooling of 8.1 ℃ compared to the ambient temperature outdoors. In heating mode, it also exhibits a high solar absorptivity of 94.7% and heats up to 11.9 ℃ higher than black cotton fabric when utilized by individuals. In practical application scenarios, a seamless transition between efficient cooling and heating is achieved by simply flipping the film. More importantly, the DMH film combining the benefits of composites demonstrates portability, durability, and easy-cleaning, promising to achieve large-scale production and use of thermally managed textiles in the future. The energy savings offered by film applications provide a viable solution for the early realization of carbon neutrality.
基金supported by the National Natural Science Foundation of China(Grant No.11847061)Domestic Visiting Program for Young and Middle-aged Teachers in Shanghai Universities.
文摘We investigate the behavior of edge modes in the presence of different edge terminations and long-range(LR)hopping.Here,we mainly focus on such model crystals with two different types of structures(type I:“…-P-Q-P-Q-…”and type II:“…=P-Q=P-Q=…”),where P and Q represent crystal lines(CLs),while the symbols“-”and“=”denote the distance between the nearest neighbor(NN)CLs.Based on the lattice model Hamiltonian with LR hopping,the existence of edge modes is determined analytically by using the transfer matrix method(TMM)when different edge terminals are taken into consideration.Our findings are consistent with the numerical results obtained by the exact diagonalization method.We also notice that edge modes can exhibit different behaviors under different edge terminals.Our result is helpful in solving novel edge modes in honeycomb crystalline graphene and transition metal dichalcogenides with different edge terminals.
文摘This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.
文摘针对弱引力场不规则小行星探测器安全下降与着陆,提出了一种基于比例微分(PD,Proportional plus Derivative)及非奇异Terminal滑模的连续控制方法.在着陆点坐标系下推导了探测器的动力学方程,设计了开环燃料次最优多项式标称轨迹制导方法.针对下降和着陆两个不同阶段提出了PD和非奇异Terminal滑模变结构连续控制方法.将PD控制的易操作性与非奇异Terminal滑模控制收敛速度快、调整时间短有效结合,保证了探测器安全着陆.仿真结果表明了提出方法的可行性和有效性.
