Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function...Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.展开更多
Through theoretical analysis,we construct a physical model that includes the influence of counter-external driven current opposite to the plasma current direction in the neoclassical tearing mode(NTM).The equation is ...Through theoretical analysis,we construct a physical model that includes the influence of counter-external driven current opposite to the plasma current direction in the neoclassical tearing mode(NTM).The equation is used with this model to obtain the modified Rutherford equation with co-current and counter-current contributions.Consistent with the reported experimental results,numerical simulations have shown that the localized counter external current can only partially suppress NTM when it is far from the resonant magnetic surface.Under some circumstances,the Ohkawa mechanism dominated current drive(OKCD)by electron cyclotron waves can concurrently create both co-current and counter-current.In this instance,the minimal electron cyclotron wave power that suppresses a particular NTM was calculated by the Rutherford equation.The result is marginally less than when taking co-current alone into consideration.As a result,to suppress NTM using OKCD,one only needs to align the co-current with a greater OKCD peak well with the resonant magnetic surface.The effect of its lower counter-current does not need to be considered because the location of the counter-current deviates greatly from the resonant magnetic surface.展开更多
The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly d...The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly distributing torques to minimize the power consumption,the driving range of 4WID-EV can be effectively improved.This paper proposes a model predictive control(MPC)-based torque distribution scheme,which minimizes the power consumption of 4WID-EVs while guaranteeing its tracking performance of planar motions.By incorporating the motor model considering iron losses,the optimal torque distribution can be achieved without an additional torque controller.Also,for this reason,the proposed control scheme is computationally efficient,since the power consumption term to be optimized,which is expressed as the product of the motor voltages and currents,is much simpler than that derived from the efficiency map.With reasonable simplification and linearization,the MPC problem is converted to a quadratic programming problem,which can be solved efficiently.The simulation results in MATLAB and CarSim co-simulation environments demonstrate that the proposed scheme effectively reduces power consumption with guaranteed tracking performance.展开更多
A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learnin...A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.展开更多
The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective ut...The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective utilization rate of energy is not high,which has become an important obstacle to its practical application.To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability.Based on the configuration and walking modes of robot,the mathematical model of the power consumption of mobile system is set up.In view of the tripod gait is often selected for the six-legged robots,the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot’s statically indeterminate problem and constructing the equal force distribution.Then,the power consumption of robot mobile system is solved under different working conditions.The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint,body height,and span.The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption.According to the walking experiments of prototype,the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio,body height,and span.Then,the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system.The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.展开更多
The hybrid beamforming is a promising technology for the millimeter wave MIMO system,which provides high spectrum efficiency,high data rate transmission,and a good balance between transmission performance and hardware...The hybrid beamforming is a promising technology for the millimeter wave MIMO system,which provides high spectrum efficiency,high data rate transmission,and a good balance between transmission performance and hardware complexity.The most existing beamforming systems transmit multiple streams by formulating multiple orthogonal beams.However,the Neural network Hybrid Beamforming(NHB)adopts a totally different strategy,which combines multiple streams into one and transmits by employing a high-order non-orthogonal modulation strategy.Driven by the Deep Learning(DL)hybrid beamforming,in this work,we propose a DL-driven nonorthogonal hybrid beamforming for the single-user multiple streams scenario.We first analyze the beamforming strategy of NHB and prove it with better Bit Error Rate(BER)performance than the orthogonal hybrid beamforming even with the optimal power allocation.Inspired by the NHB,we propose a new DL-driven beamforming scheme to simulate the NHB behavior,which avoids time-consuming neural network training and achieves better BERs than traditional hybrid beamforming.Moreover,our simulation results demonstrate that the DL-driven nonorthogonal beamforming outperforms its traditional orthogonal beamforming counterpart in the presence of subconnected schemes and imperfect Channel State Information(CSI).展开更多
Pancreatic cancer(PanCa)presents a catastrophic disease with poor overall survival at advanced stages,with immediate requirement of new and effective treatment options.Besides genetic mutations,epigenetic dysregulatio...Pancreatic cancer(PanCa)presents a catastrophic disease with poor overall survival at advanced stages,with immediate requirement of new and effective treatment options.Besides genetic mutations,epigenetic dysregulation of signaling pathway-associated enriched genes are considered as novel therapeutic target.Mechanisms beneath the deoxyribonucleic acid methylation and its utility in developing of epi-drugs in PanCa are under trails.Combinations of epigenetic medicines with conventional cytotoxic treatments or targeted therapy are promising options to improving the dismal response and survival rate of PanCa patients.Recent studies have identified potentially valid pathways that support the prediction that future PanCa clinical trials will include vigorous testing of epigenomic therapies.Epigenetics thus promises to generate a significant amount of new knowledge of biological and medical importance.Our review could identify various components of epigenetic mechanisms known to be involved in the initiation and development of pancreatic ductal adenocarcinoma and related precancerous lesions,and novel pharmacological strategies that target these components could potentially lead to breakthroughs.We aim to highlight the possibilities that exist and the potential therapeutic interventions.展开更多
While the Yagi-Uda array has been studied for decades, one issue appears to have received less attention than perhaps it should, namely, the effects on performance of the array’s driven element length and its length-...While the Yagi-Uda array has been studied for decades, one issue appears to have received less attention than perhaps it should, namely, the effects on performance of the array’s driven element length and its length-to-diameter ratio. This paper looks at that question. It shows that decreasing the L/D ratio increases impedance bandwidth, but it may shift the IBW band sufficiently far from the design frequency that other parameters such as gain and front-to-back ratio probably are adversely affected. It also shows that array performance is not relatively independent of element diameters. This paper also investigates the effect of lengthening the driven element, which can substantially improve IBW. Several iterations of a 3-element prototype and improved arrays are modeled with the Method of Moments and discussed in detail. A five step design procedure is recommended and applied to a Genetic Algorithm-optimized 3-element Yagi at 146 MHz. This array exhibits excellent performance in terms of gain, front-to-back ratio, and especially impedance bandwidth (nearly 14% for voltage standing wave ratio ≤ 2:1 with two frequencies at which 50 ? is almost perfectly matched). While the analysis and recommended design steps are applied to cylindrical array elements, which commonly are aluminum tubing for stand-alone VHF-SHF Yagis, they can be applied to other element geometries as well using equivalent cylindrical radii, for example, Printed Circuit Board traces for planar arrays. One consequence of lengthening the driven element while reducing its L/D ratio is that some reactance is introduced at the array feedpoint which must be tuned out, and two approaches for doing so are suggested.展开更多
The implosion plasma drive fusion pellet of inertial confinement is a concept related to nuclear fusion,a process in which atomic nuclei combine to form heavier nuclei,releasing a large amount of energy in the process...The implosion plasma drive fusion pellet of inertial confinement is a concept related to nuclear fusion,a process in which atomic nuclei combine to form heavier nuclei,releasing a large amount of energy in the process.The implosion plasma drive fusion pellet is a potential fuel source for achieving controlled nuclear fusion.ICF(inertial confinement fusion)is a technique used to achieve fusion by compressing a small target containing fusion fuel to extremely high densities and temperatures using lasers or other methods.The implosion plasma drive fusion pellet concept involves using a small pellet of deuterium and tritium(two isotopes of hydrogen)as fusion fuel,and then rapidly heating and compressing it using a pulsed power system.The implosion process creates a high-pressure plasma that ignites the fusion reactions,releasing energy in the form of neutrons and charged particles.The resulting energy can be captured and used for power generation.This technology is still in the experimental stage,and significant research and development is required to make it commercially viable.However,it has the potential to provide a virtually limitless source of clean energy with no greenhouse gas emissions or long-term radioactive waste.Be that as it may,ICF has to get exact control of the implosion process,mitigate insecurities,and create modern materials and advances to resist the extraordinary conditions of the combined response.展开更多
文摘Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.
基金Project supported by the National Key R&D Program of China(Grant Nos.2022YFE03070000 and 2022YFE03070003)the National Natural Science Foundation of China(Grant Nos.12375220 and 12075114)+3 种基金the Hunan Provincial Natural Science Foundation(Grant No.2021JJ30569)the Doctoral Initiation Fund Project of University of South China(Grant No.190XQD114)the Hunan Nuclear Fusion International Science and Technology Innovation Cooperation Base(Grant No.2018WK4009)the Hengyang Key Laboratory of Magnetic Confinement Nuclear Fusion Research(Grant No.2018KJ108)。
文摘Through theoretical analysis,we construct a physical model that includes the influence of counter-external driven current opposite to the plasma current direction in the neoclassical tearing mode(NTM).The equation is used with this model to obtain the modified Rutherford equation with co-current and counter-current contributions.Consistent with the reported experimental results,numerical simulations have shown that the localized counter external current can only partially suppress NTM when it is far from the resonant magnetic surface.Under some circumstances,the Ohkawa mechanism dominated current drive(OKCD)by electron cyclotron waves can concurrently create both co-current and counter-current.In this instance,the minimal electron cyclotron wave power that suppresses a particular NTM was calculated by the Rutherford equation.The result is marginally less than when taking co-current alone into consideration.As a result,to suppress NTM using OKCD,one only needs to align the co-current with a greater OKCD peak well with the resonant magnetic surface.The effect of its lower counter-current does not need to be considered because the location of the counter-current deviates greatly from the resonant magnetic surface.
基金supported in part by National Natural Science Foundation of China(NSFC)under Project No.51737010.
文摘The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly distributing torques to minimize the power consumption,the driving range of 4WID-EV can be effectively improved.This paper proposes a model predictive control(MPC)-based torque distribution scheme,which minimizes the power consumption of 4WID-EVs while guaranteeing its tracking performance of planar motions.By incorporating the motor model considering iron losses,the optimal torque distribution can be achieved without an additional torque controller.Also,for this reason,the proposed control scheme is computationally efficient,since the power consumption term to be optimized,which is expressed as the product of the motor voltages and currents,is much simpler than that derived from the efficiency map.With reasonable simplification and linearization,the MPC problem is converted to a quadratic programming problem,which can be solved efficiently.The simulation results in MATLAB and CarSim co-simulation environments demonstrate that the proposed scheme effectively reduces power consumption with guaranteed tracking performance.
文摘A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.
基金National Natural Science Foundation of China(Grant No.51505335)Industry University Cooperation Collaborative Education Project of the Department of Higher Education of the Ministry of Education of China(Grant No.202102517001)Doctor Startup Projects of TUTE of China(Grant No.KYQD1806)。
文摘The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective utilization rate of energy is not high,which has become an important obstacle to its practical application.To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability.Based on the configuration and walking modes of robot,the mathematical model of the power consumption of mobile system is set up.In view of the tripod gait is often selected for the six-legged robots,the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot’s statically indeterminate problem and constructing the equal force distribution.Then,the power consumption of robot mobile system is solved under different working conditions.The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint,body height,and span.The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption.According to the walking experiments of prototype,the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio,body height,and span.Then,the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system.The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.
基金This work is supported by Sichuan Science and Technology Program(NO.2021YFG0127).
文摘The hybrid beamforming is a promising technology for the millimeter wave MIMO system,which provides high spectrum efficiency,high data rate transmission,and a good balance between transmission performance and hardware complexity.The most existing beamforming systems transmit multiple streams by formulating multiple orthogonal beams.However,the Neural network Hybrid Beamforming(NHB)adopts a totally different strategy,which combines multiple streams into one and transmits by employing a high-order non-orthogonal modulation strategy.Driven by the Deep Learning(DL)hybrid beamforming,in this work,we propose a DL-driven nonorthogonal hybrid beamforming for the single-user multiple streams scenario.We first analyze the beamforming strategy of NHB and prove it with better Bit Error Rate(BER)performance than the orthogonal hybrid beamforming even with the optimal power allocation.Inspired by the NHB,we propose a new DL-driven beamforming scheme to simulate the NHB behavior,which avoids time-consuming neural network training and achieves better BERs than traditional hybrid beamforming.Moreover,our simulation results demonstrate that the DL-driven nonorthogonal beamforming outperforms its traditional orthogonal beamforming counterpart in the presence of subconnected schemes and imperfect Channel State Information(CSI).
文摘Pancreatic cancer(PanCa)presents a catastrophic disease with poor overall survival at advanced stages,with immediate requirement of new and effective treatment options.Besides genetic mutations,epigenetic dysregulation of signaling pathway-associated enriched genes are considered as novel therapeutic target.Mechanisms beneath the deoxyribonucleic acid methylation and its utility in developing of epi-drugs in PanCa are under trails.Combinations of epigenetic medicines with conventional cytotoxic treatments or targeted therapy are promising options to improving the dismal response and survival rate of PanCa patients.Recent studies have identified potentially valid pathways that support the prediction that future PanCa clinical trials will include vigorous testing of epigenomic therapies.Epigenetics thus promises to generate a significant amount of new knowledge of biological and medical importance.Our review could identify various components of epigenetic mechanisms known to be involved in the initiation and development of pancreatic ductal adenocarcinoma and related precancerous lesions,and novel pharmacological strategies that target these components could potentially lead to breakthroughs.We aim to highlight the possibilities that exist and the potential therapeutic interventions.
文摘While the Yagi-Uda array has been studied for decades, one issue appears to have received less attention than perhaps it should, namely, the effects on performance of the array’s driven element length and its length-to-diameter ratio. This paper looks at that question. It shows that decreasing the L/D ratio increases impedance bandwidth, but it may shift the IBW band sufficiently far from the design frequency that other parameters such as gain and front-to-back ratio probably are adversely affected. It also shows that array performance is not relatively independent of element diameters. This paper also investigates the effect of lengthening the driven element, which can substantially improve IBW. Several iterations of a 3-element prototype and improved arrays are modeled with the Method of Moments and discussed in detail. A five step design procedure is recommended and applied to a Genetic Algorithm-optimized 3-element Yagi at 146 MHz. This array exhibits excellent performance in terms of gain, front-to-back ratio, and especially impedance bandwidth (nearly 14% for voltage standing wave ratio ≤ 2:1 with two frequencies at which 50 ? is almost perfectly matched). While the analysis and recommended design steps are applied to cylindrical array elements, which commonly are aluminum tubing for stand-alone VHF-SHF Yagis, they can be applied to other element geometries as well using equivalent cylindrical radii, for example, Printed Circuit Board traces for planar arrays. One consequence of lengthening the driven element while reducing its L/D ratio is that some reactance is introduced at the array feedpoint which must be tuned out, and two approaches for doing so are suggested.
文摘The implosion plasma drive fusion pellet of inertial confinement is a concept related to nuclear fusion,a process in which atomic nuclei combine to form heavier nuclei,releasing a large amount of energy in the process.The implosion plasma drive fusion pellet is a potential fuel source for achieving controlled nuclear fusion.ICF(inertial confinement fusion)is a technique used to achieve fusion by compressing a small target containing fusion fuel to extremely high densities and temperatures using lasers or other methods.The implosion plasma drive fusion pellet concept involves using a small pellet of deuterium and tritium(two isotopes of hydrogen)as fusion fuel,and then rapidly heating and compressing it using a pulsed power system.The implosion process creates a high-pressure plasma that ignites the fusion reactions,releasing energy in the form of neutrons and charged particles.The resulting energy can be captured and used for power generation.This technology is still in the experimental stage,and significant research and development is required to make it commercially viable.However,it has the potential to provide a virtually limitless source of clean energy with no greenhouse gas emissions or long-term radioactive waste.Be that as it may,ICF has to get exact control of the implosion process,mitigate insecurities,and create modern materials and advances to resist the extraordinary conditions of the combined response.