Off-line programming (OLP) system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the...Off-line programming (OLP) system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification (IGES) file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton's iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.展开更多
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.展开更多
Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site....Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site.The absence of spontaneous axonal regeneration after injury results from neuron-intrinsic and neuron-extrinsic parameters.Indeed,not only adult neurons display limited capability to regrow axons but also the injury environment contains inhibitors to axonal regeneration and a lack of growth-promoting factors.Amongst other cell populations that respond to the lesion,reactive astrocytes were first considered as only detrimental to spontaneous axonal regeneration.Indeed,astrocytes.展开更多
Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutic...Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutics are needed,understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment targets.This study aimed to provide an overview of transcriptional reprogramming during human osteoclast differentiation.Osteoclasts were differentiated from CD14+monocytes from eight female donors.RNA sequencing during differentiation revealed 8980 differentially expressed genes grouped into eight temporal patterns conserved across donors.These patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density SNPs.Network analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional networks.The donor-specific expression patterns revealed genes at the monocyte stage,such as filamin B(FLNB)and oxidized low-density lipoprotein receptor 1(OLR1,encoding LOX-1),that are predictive of the resorptive activity of mature osteoclasts.The expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation,and these receptors are associated with bone mineral density SNPs,suggesting that they play a pivotal role in osteoclast differentiation and activity.The regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1(C5AR1),somatostatin receptor 2(SSTR2),and free fatty acid receptor 4(FFAR4/GPR120).Activating C5AR1 enhanced osteoclast formation,while activating SSTR2 decreased the resorptive activity of mature osteoclasts,and activating FFAR4 decreased both the number and resorptive activity of mature osteoclasts.In conclusion,we report the occurrence of transcriptional reprogramming during human osteoclast differentiation and identified SSTR2 and FFAR4 as antiresorptive G-protein coupled receptors and FLNB and LOX-1 as potential molecular markers of osteoclast activity.These data can help future investigations identify molecular regulators of osteoclast differentiation and activity and provide the basis for novel antiosteoporotic targets.展开更多
Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenario...Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.展开更多
Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinea...Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.展开更多
Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conv...Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.展开更多
Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of ...Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.展开更多
The proportion of elderly patients in intensive care is increasing, and a significant proportion of them require mechanical ventilation. How to implement safe and effective mechanical ventilation for elderly patients,...The proportion of elderly patients in intensive care is increasing, and a significant proportion of them require mechanical ventilation. How to implement safe and effective mechanical ventilation for elderly patients, and when appropriate off-line is an important issue in the field of critical care medicine. Appropriate sedation can improve patient outcomes, but excessive sedation may lead to prolonged mechanical ventilation and increase the risk of complications. Elderly patients should be closely monitored and evaluated on an individual basis while offline, and the sedation regimen should be dynamically adjusted. This requires the healthcare team to consider the patient’s sedation needs, disease status, and pharmacodynamics and pharmacokinetics of the drug to arrive at the best strategy. Although the current research has provided valuable insights and strategies for sedation and off-line management, there are still many problems to be further explored and solved.展开更多
In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed metho...In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.展开更多
This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two algorithms: the weighted av...This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two algorithms: the weighted average and the cosine simplex algorithm. The first approach identifies binding constraints by using the weighted average of each constraint, whereas the second algorithm is based on the cosine similarity between the vector of the objective function and the constraints. These two approaches are complementary, and when used together, they locate the essential subset of initial constraints required for solving medium and large-scale linear programming problems. After reducing the dimension of the linear programming problem using the subset of the essential constraints, the solution method can be chosen from any suitable method for linear programming. The proposed approach was applied to a set of well-known benchmarks as well as more than 2000 random medium and large-scale linear programming problems. The results are promising, indicating that the new approach contributes to the reduction of both the size of the problems and the total number of iterations required. A tree-based classification model also confirmed the need for combining the two approaches. A detailed numerical example, the general numerical results, and the statistical analysis for the decision tree procedure are presented.展开更多
This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from g...This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.展开更多
Off line programming provides an essential link between CAD and CAM, whose development will result in greater use of robotic arc welding. An arc welding system with a robot and a rotating/tilting positioner is one of...Off line programming provides an essential link between CAD and CAM, whose development will result in greater use of robotic arc welding. An arc welding system with a robot and a rotating/tilting positioner is one of the most typical workcells. The inverse kinematics of robot and positioner is the foundation of the off line programming system. The previous researchers only focused on a special solution of the positioner inverse kinematics, which is the solution at down hand welding position. In this paper, we introduce a method for representing welding position. Then a general algorithm of rotating/tilting positioner inverse kinematics is presented, and an approach to find the unique solution of the inverse kinematics is discussed. The simulation experiment results show that the general algorithm can improve the ability of robotic arc welding off line programming system to program all types of welding positions.展开更多
As the end-effector of robot, the induction hard- ening tool is required to keep its orientations perpendicular to the fillets or chamfers of the mould at a distance during its uniform motion along the hardening traje...As the end-effector of robot, the induction hard- ening tool is required to keep its orientations perpendicular to the fillets or chamfers of the mould at a distance during its uniform motion along the hardening trajectory. This trajectory consists of a group of central curves which are parametric curves on the corresponding chamfers or fillets and between two edges of every chamfer or fillet. The trajectory points and the surface normal vectors at these points are obtained by parametric equations of the fillets or chamfers. This study is conducted to join each central curve into the entire hardening trajectory, including handling on the irregular surfaces and unifying the directions of hardening tool motion. According to kinematics of robot, the trajectory points in modeling coordinate system are transferred into the poses of the induction hardening tool in user frame of robot. The kinematical interference of the induction hardening tool and robot joints is checked by Robognide sim- ulation tool. The validity of the robotic off-line programming (OLP) system was verified by experiments.展开更多
Thick walled curve welding are usually joined by multi-layer and multi-pass welding, which quality and efficiency could be improved by off-line programming of robot welding. However, the precision of off-line programm...Thick walled curve welding are usually joined by multi-layer and multi-pass welding, which quality and efficiency could be improved by off-line programming of robot welding. However, the precision of off-line programming welding path was decreased due to the deviation between the off-line planned welding path and the actual welding path. A path planning algorithm and a path compensation algorithm of multi-layer and multi-pass curve welding seam for off-line programming of robot welding are developed in this paper. Experimental results show that the robot off-line programming improves the welding efftcieney and precision for thick walled curve welding seam.展开更多
This paper puts forward a communication programming method between robot and external computer based on RPC (Remote Produce Call) communication method, which realizes robot distributed controlling network system model...This paper puts forward a communication programming method between robot and external computer based on RPC (Remote Produce Call) communication method, which realizes robot distributed controlling network system model. And a new Robot off line programming method is built based on this communication method and network model. Further more, as an example, robot auto marking and auto cutting of shipbuilding profile system is developed, which proves the ideas of author’s off line programming and development methods of robot flexible automation system. As a result, this paper presents a new method for developing robot flexible automation system.展开更多
The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense ...The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense anti-missile targets defense problem is abstracted as a nonconvex constrained combinatorial optimization problem with the optimization objective of maximizing the degree of contribution of the processing scheme to non-cooperative targets, and the constraints mainly consider geographical conditions and anti-missile equipment resources. The grid discretization concept is used to partition the defense area into network nodes, and the overall defense strategy scheme is described as a nonlinear programming problem to solve the minimum defense cost within the maximum defense capability of the defense system network. In the solution of the minimum defense cost problem, the processing scheme, equipment coverage capability, constraints and node cost requirements are characterized, then a nonlinear mathematical model of the non-cooperative target distributed hybrid processing optimization problem is established, and a local optimal solution based on the sequential quadratic programming algorithm is constructed, and the optimal firepower processing scheme is given by using the sequential quadratic programming method containing non-convex quadratic equations and inequality constraints. Finally, the effectiveness of the proposed method is verified by simulation examples.展开更多
Cell replacement therapy has long been proposed as a treatment for the damaged nervous system.One of the most challenging aspects of such a strategy,however,is finding sources of donor cells for transplantation.Autolo...Cell replacement therapy has long been proposed as a treatment for the damaged nervous system.One of the most challenging aspects of such a strategy,however,is finding sources of donor cells for transplantation.Autologous neural cells are rarely an option as every cell in the nervous system has a defined function that would be lost if that cell was to be removed.One possibility would be sourcing precursor or differentiated cells from fetal tissues;however,aside from ethical issues,heterologous cells are at risk of immunological rejection in the long term.Methodological improvements over the past 15 years have led to the possibility that autologous non-neural cells could be used for cell transplantation through their conversion into neural derivatives.展开更多
Introduction:Ever since the discovery of neural stem cells(NSCs)in the adult mammalian brain,scientists have been trying to decipher which signals govern their turnover and lineage commitment to generate neurons and g...Introduction:Ever since the discovery of neural stem cells(NSCs)in the adult mammalian brain,scientists have been trying to decipher which signals govern their turnover and lineage commitment to generate neurons and glia.Understanding their role in nervous tissue homeostasis can provide new insights into the etiology of several neurological disorders,and might one day be turned to our advantage to promote endogenous brain injury repair.Others and we have identified thyroid hormone(TH)as a key factor transcriptionally regulating NSC behavior in the largest niche of the adult mammalian brain:the subventricular zone(SVZ).展开更多
The accumulation of anthocyanins is a well-known response to abiotic stresses in many plant species.However,the effects of anthocyanin accumulation on light absorbance and photosynthesis are unknown.Here,we addressed ...The accumulation of anthocyanins is a well-known response to abiotic stresses in many plant species.However,the effects of anthocyanin accumulation on light absorbance and photosynthesis are unknown.Here,we addressed this question using a promoter replacement line of tomato constitutively expressing a MYB transcription factor(ANTHOCYANIN1,ANT1)that leads to anthocyanin accumulation.ANT1-overexpressing plants displayed traits associated with shade avoidance response:thinner leaves,lower seed germination rate,suppressed side branching,increased chlorophyll concentration,and lower photosynthesis rates than the wild type.Anthocyanin-rich leaves exhibited higher absorbance of light in the blue and red ends of the spectrum,while higher anthocyanin content in leaves provided photoprotection to high irradiance.Analyses of gene expression and primary metabolites content showed that anthocyanin accumulation produces a reconfiguration of transcriptional and metabolic networks that is consistent with,but not identical to those described for the shade avoidance response.Our results provide novel insights about howanthocyanins accumulation affects the trade-off between photoprotection and growth.展开更多
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z2443)State Key Laboratory for Man ufacturing Systems Engineering of Xi’an Jiaotong University of China
文摘Off-line programming (OLP) system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification (IGES) file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton's iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.
基金supported in part by the National Natural Science Foundation of China(62222301, 62073085, 62073158, 61890930-5, 62021003)the National Key Research and Development Program of China (2021ZD0112302, 2021ZD0112301, 2018YFC1900800-5)Beijing Natural Science Foundation (JQ19013)。
文摘Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
基金supported by the patient organizations“Verticale”(to YNG and FEP).
文摘Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site.The absence of spontaneous axonal regeneration after injury results from neuron-intrinsic and neuron-extrinsic parameters.Indeed,not only adult neurons display limited capability to regrow axons but also the injury environment contains inhibitors to axonal regeneration and a lack of growth-promoting factors.Amongst other cell populations that respond to the lesion,reactive astrocytes were first considered as only detrimental to spontaneous axonal regeneration.Indeed,astrocytes.
基金funded by grants from the Novo Nordisk Foundation (NNF18OC0052699) (M.S.H.) and NNF18OC0055047 (M.F.)the Region of Southern Denmark (ref: 18/17553 (M.S.H.))+3 种基金Odense University Hospital (ref: A3147) (M.F.)a faculty fellowship from the University of Southern Denmark (K.M.), the Lundbeck Foundation (ref: R335-2019-2195) (K.M.and A.R.)an Academy of Medical Sciences Springboard Award supported by the British Heart Foundation, Diabetes UK, the Global Challenges Research Fund, the Government Department of Business, Energy and Industrial Strategy and the Wellcome Trust (ref: SBF004 | 1034, C.M.G)a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number 224155/Z/21/Z to C.M.G.).
文摘Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutics are needed,understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment targets.This study aimed to provide an overview of transcriptional reprogramming during human osteoclast differentiation.Osteoclasts were differentiated from CD14+monocytes from eight female donors.RNA sequencing during differentiation revealed 8980 differentially expressed genes grouped into eight temporal patterns conserved across donors.These patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density SNPs.Network analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional networks.The donor-specific expression patterns revealed genes at the monocyte stage,such as filamin B(FLNB)and oxidized low-density lipoprotein receptor 1(OLR1,encoding LOX-1),that are predictive of the resorptive activity of mature osteoclasts.The expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation,and these receptors are associated with bone mineral density SNPs,suggesting that they play a pivotal role in osteoclast differentiation and activity.The regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1(C5AR1),somatostatin receptor 2(SSTR2),and free fatty acid receptor 4(FFAR4/GPR120).Activating C5AR1 enhanced osteoclast formation,while activating SSTR2 decreased the resorptive activity of mature osteoclasts,and activating FFAR4 decreased both the number and resorptive activity of mature osteoclasts.In conclusion,we report the occurrence of transcriptional reprogramming during human osteoclast differentiation and identified SSTR2 and FFAR4 as antiresorptive G-protein coupled receptors and FLNB and LOX-1 as potential molecular markers of osteoclast activity.These data can help future investigations identify molecular regulators of osteoclast differentiation and activity and provide the basis for novel antiosteoporotic targets.
基金the Science and Technology Project of State Grid Corporation of China,Grant Number 5108-202304065A-1-1-ZN.
文摘Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.
基金The financial support provided by the Project of National Natural Science Foundation of China(U22A20415,21978256,22308314)“Pioneer”and“Leading Goose”Research&Development Program of Zhejiang(2022C01SA442617)。
文摘Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.
基金The authors gratefully acknowledge the support from the National Natural Science Foundation of China(Grant No.42377174)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2022ME198)the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(Grant No.Z020006).
文摘Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.
文摘Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.
文摘The proportion of elderly patients in intensive care is increasing, and a significant proportion of them require mechanical ventilation. How to implement safe and effective mechanical ventilation for elderly patients, and when appropriate off-line is an important issue in the field of critical care medicine. Appropriate sedation can improve patient outcomes, but excessive sedation may lead to prolonged mechanical ventilation and increase the risk of complications. Elderly patients should be closely monitored and evaluated on an individual basis while offline, and the sedation regimen should be dynamically adjusted. This requires the healthcare team to consider the patient’s sedation needs, disease status, and pharmacodynamics and pharmacokinetics of the drug to arrive at the best strategy. Although the current research has provided valuable insights and strategies for sedation and off-line management, there are still many problems to be further explored and solved.
基金supported by the National Science Fund for Distinguished Young Scholars (62225303)the Fundamental Research Funds for the Central Universities (buctrc202201)+1 种基金China Scholarship Council,and High Performance Computing PlatformCollege of Information Science and Technology,Beijing University of Chemical Technology。
文摘In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.
文摘This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two algorithms: the weighted average and the cosine simplex algorithm. The first approach identifies binding constraints by using the weighted average of each constraint, whereas the second algorithm is based on the cosine similarity between the vector of the objective function and the constraints. These two approaches are complementary, and when used together, they locate the essential subset of initial constraints required for solving medium and large-scale linear programming problems. After reducing the dimension of the linear programming problem using the subset of the essential constraints, the solution method can be chosen from any suitable method for linear programming. The proposed approach was applied to a set of well-known benchmarks as well as more than 2000 random medium and large-scale linear programming problems. The results are promising, indicating that the new approach contributes to the reduction of both the size of the problems and the total number of iterations required. A tree-based classification model also confirmed the need for combining the two approaches. A detailed numerical example, the general numerical results, and the statistical analysis for the decision tree procedure are presented.
文摘This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.
基金ThispaperissupportedbyNationalNatureScienceFoundation (No .5 96 35 16 0 )AdvancedUniversityDoctoralSubjectFoundation (No .980 2 1311)
文摘Off line programming provides an essential link between CAD and CAM, whose development will result in greater use of robotic arc welding. An arc welding system with a robot and a rotating/tilting positioner is one of the most typical workcells. The inverse kinematics of robot and positioner is the foundation of the off line programming system. The previous researchers only focused on a special solution of the positioner inverse kinematics, which is the solution at down hand welding position. In this paper, we introduce a method for representing welding position. Then a general algorithm of rotating/tilting positioner inverse kinematics is presented, and an approach to find the unique solution of the inverse kinematics is discussed. The simulation experiment results show that the general algorithm can improve the ability of robotic arc welding off line programming system to program all types of welding positions.
文摘As the end-effector of robot, the induction hard- ening tool is required to keep its orientations perpendicular to the fillets or chamfers of the mould at a distance during its uniform motion along the hardening trajectory. This trajectory consists of a group of central curves which are parametric curves on the corresponding chamfers or fillets and between two edges of every chamfer or fillet. The trajectory points and the surface normal vectors at these points are obtained by parametric equations of the fillets or chamfers. This study is conducted to join each central curve into the entire hardening trajectory, including handling on the irregular surfaces and unifying the directions of hardening tool motion. According to kinematics of robot, the trajectory points in modeling coordinate system are transferred into the poses of the induction hardening tool in user frame of robot. The kinematical interference of the induction hardening tool and robot joints is checked by Robognide sim- ulation tool. The validity of the robotic off-line programming (OLP) system was verified by experiments.
文摘Thick walled curve welding are usually joined by multi-layer and multi-pass welding, which quality and efficiency could be improved by off-line programming of robot welding. However, the precision of off-line programming welding path was decreased due to the deviation between the off-line planned welding path and the actual welding path. A path planning algorithm and a path compensation algorithm of multi-layer and multi-pass curve welding seam for off-line programming of robot welding are developed in this paper. Experimental results show that the robot off-line programming improves the welding efftcieney and precision for thick walled curve welding seam.
文摘This paper puts forward a communication programming method between robot and external computer based on RPC (Remote Produce Call) communication method, which realizes robot distributed controlling network system model. And a new Robot off line programming method is built based on this communication method and network model. Further more, as an example, robot auto marking and auto cutting of shipbuilding profile system is developed, which proves the ideas of author’s off line programming and development methods of robot flexible automation system. As a result, this paper presents a new method for developing robot flexible automation system.
基金supported by the National Natural Science Foundation of China (61903025)the Fundamental Research Funds for the Cent ral Universities (FRF-IDRY-20-013)。
文摘The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense anti-missile targets defense problem is abstracted as a nonconvex constrained combinatorial optimization problem with the optimization objective of maximizing the degree of contribution of the processing scheme to non-cooperative targets, and the constraints mainly consider geographical conditions and anti-missile equipment resources. The grid discretization concept is used to partition the defense area into network nodes, and the overall defense strategy scheme is described as a nonlinear programming problem to solve the minimum defense cost within the maximum defense capability of the defense system network. In the solution of the minimum defense cost problem, the processing scheme, equipment coverage capability, constraints and node cost requirements are characterized, then a nonlinear mathematical model of the non-cooperative target distributed hybrid processing optimization problem is established, and a local optimal solution based on the sequential quadratic programming algorithm is constructed, and the optimal firepower processing scheme is given by using the sequential quadratic programming method containing non-convex quadratic equations and inequality constraints. Finally, the effectiveness of the proposed method is verified by simulation examples.
基金supported by projects NDG09/014 and Proyecto VEXEM(to CLP),European Social Fund,YEI,(Nos.PEJ16/MED/AI-1153 and PEJD-2018-PRE/SAL-8532)of the Community of Madrid,SpainSAF-2016-78666-R,CP19-0010,and PID 2020-113014RB-I00 funded by MCIN/AEI/10.13039/501100011033(to JARN).
文摘Cell replacement therapy has long been proposed as a treatment for the damaged nervous system.One of the most challenging aspects of such a strategy,however,is finding sources of donor cells for transplantation.Autologous neural cells are rarely an option as every cell in the nervous system has a defined function that would be lost if that cell was to be removed.One possibility would be sourcing precursor or differentiated cells from fetal tissues;however,aside from ethical issues,heterologous cells are at risk of immunological rejection in the long term.Methodological improvements over the past 15 years have led to the possibility that autologous non-neural cells could be used for cell transplantation through their conversion into neural derivatives.
基金supported by the European Union’s Horizon 2020 contract ATHENA(grant No.666869)ENDpoiNTs(grant No.825759)+1 种基金supported by the European Thyroid Association(ETA)the Fondation pour la Recherche Médicale(FRM grant No.SPF201909009111)。
文摘Introduction:Ever since the discovery of neural stem cells(NSCs)in the adult mammalian brain,scientists have been trying to decipher which signals govern their turnover and lineage commitment to generate neurons and glia.Understanding their role in nervous tissue homeostasis can provide new insights into the etiology of several neurological disorders,and might one day be turned to our advantage to promote endogenous brain injury repair.Others and we have identified thyroid hormone(TH)as a key factor transcriptionally regulating NSC behavior in the largest niche of the adult mammalian brain:the subventricular zone(SVZ).
基金supported by a CAPES/Alexander von Humboldt Foundation Experienced Researcher Fellowship(88881.472837/2019-01)Foundation for Research Assistance of the Minas Gerais State(FAPEMIG,Brazil,APQ-01942-22)supported by the Major Special Projects and Key R&D Projects in Yunnan Province(202102AE090020 and 202102AE090054).
文摘The accumulation of anthocyanins is a well-known response to abiotic stresses in many plant species.However,the effects of anthocyanin accumulation on light absorbance and photosynthesis are unknown.Here,we addressed this question using a promoter replacement line of tomato constitutively expressing a MYB transcription factor(ANTHOCYANIN1,ANT1)that leads to anthocyanin accumulation.ANT1-overexpressing plants displayed traits associated with shade avoidance response:thinner leaves,lower seed germination rate,suppressed side branching,increased chlorophyll concentration,and lower photosynthesis rates than the wild type.Anthocyanin-rich leaves exhibited higher absorbance of light in the blue and red ends of the spectrum,while higher anthocyanin content in leaves provided photoprotection to high irradiance.Analyses of gene expression and primary metabolites content showed that anthocyanin accumulation produces a reconfiguration of transcriptional and metabolic networks that is consistent with,but not identical to those described for the shade avoidance response.Our results provide novel insights about howanthocyanins accumulation affects the trade-off between photoprotection and growth.