Sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method

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.

Impedance control of multi-arm space robot for the capture of non-cooperative targets

Robotic systems are expected to play an increasingly important role in future space activities. The robotic on-orbital service, whose key is the capturing technology, becomes a research hot spot in recent years. This paper studies the dynamics modeling and impedance control of a multi-arm free-flying space robotic system capturing a non-cooperative target. Firstly, a control-oriented dynamics model is essential in control algorithm design and code realization. Unlike a numerical algorithm, an analytical approach is suggested. Using a general and a quasi-coordinate Lagrangian formulation, the kinematics and dynamics equations are derived.Then, an impedance control algorithm is developed which allows coordinated control of the multiple manipulators to capture a target.Through enforcing a reference impedance, end-effectors behave like a mass-damper-spring system fixed in inertial space in reaction to any contact force between the capture hands and the target. Meanwhile, the position and the attitude of the base are maintained stably by using gas jet thrusters to work against the manipulators' reaction. Finally, a simulation by using a space robot with two manipulators and a free-floating non-cooperative target is illustrated to verify the effectiveness of the proposed method.

Design of a Flexible Capture Mechanism Inspired by Sea Anemone for Non-cooperative Targets

Robotic grippers have been used in industry as end-effectors but are usually limited to operations in pre-defined workspace.However,few devices can capture irregularly shaped dynamic targets in space,underwater and other unstructured environments.In this paper,a novel continuum arm group mechanism inspired by the morphology and motions of sea anemones is proposed.It is able to dissipate and absorb the kinetic energy of a fast moving target in omni-direction and utilize multiple arms to wrap and lock the target without accurate positioning control.Wire-driven actuation systems are implemented in the individual continuum arms,achieving both bending motion and stiffness regulation.Through finite element method,the influence of different configurations of the continuum arm group on the capture performance is analyzed.A robotic prototype is constructed and tested,showing the presented arm group mechanism has high adaptability to capture targets with different sizes,shapes,and incident angles.

Non-cooperative target pose estimation based on improved iterative closest point algorithm

For localisation of unknown non-cooperative targets in space,the existence of interference points causes inaccuracy of pose estimation while utilizing point cloud registration.To address this issue,this paper proposes a new iterative closest point(ICP)algorithm combined with distributed weights to intensify the dependability and robustness of the non-cooperative target localisation.As interference points in space have not yet been extensively studied,we classify them into two broad categories,far interference points and near interference points.For the former,the statistical outlier elimination algorithm is employed.For the latter,the Gaussian distributed weights,simultaneously valuing with the variation of the Euclidean distance from each point to the centroid,are commingled to the traditional ICP algorithm.In each iteration,the weight matrix W in connection with the overall localisation is obtained,and the singular value decomposition is adopted to accomplish high-precision estimation of the target pose.Finally,the experiments are implemented by shooting the satellite model and setting the position of interference points.The outcomes suggest that the proposed algorithm can effectively suppress interference points and enhance the accuracy of non-cooperative target pose estimation.When the interference point number reaches about 700,the average error of angle is superior to 0.88°.

Design of a Non-cooperative Target Capture Mechanism

A passive compliant non-cooperative target capture mechanism is designed to maintain the non-cooperative target on-orbit. When the relative position between capture mechanism and satellite is confirmed,a pair of four-bar linkages lock the docking ring,which is used for connecting the satellite and the rocket. The mathematical model of capture mechanism and capture space is built by the Denavit-Hartenberg(D-H)method,and the torque of each joint is analyzed by the Lagrange dynamic equation. Besides,the capture condition and the torque of every joint under different capture conditions are analyzed by simulation in MSC. Adams. The results indicate that the mechanism can capture the non-cooperative target satellite in a wide range. During the process of capture,the passive compliant mechanism at the bottom can increase capture space,thereby reducing the difficulty and enhance stability of the capture.

A grasp planning algorithm under uneven contact point distribution scenario for space non-cooperative target capture

The contact point configuration should be carefully chosen to ensure a stable capture,especially for the non-cooperative target capture mission using multi-armed spacecraft.In this work scenario,the contact points on the base and on the arms are distributed on the opposite side of the target.Otherwise,large forces will be needed.To cope with this problem,an uneven-oriented distribution union criterion is proposed.The union criterion contains a virtual symmetrical criterion and a geometry criterion.The virtual symmetrical contact point criterion is derived from the proof of the force closure principle using computational geometry to ensure a stable grasp,and the geometry criterion is calculated by the volume of the minimum polyhedron formed by the contact points to get a wide-range distribution.To further accelerate the optimization rate and enhance the global search ability,a line array modeling method and a continuous-discrete global search algorithm are proposed.The line array modeling method reduces the workload of calculating the descent direction and the gradient available,while the continuous-discrete global search algorithm reducing the optimization dimension.Then a highly efficient grasping is achieved and the corresponding contact point is calculated.Finally,an exhaustive verification is conducted to numerically analyze the disturbance resistance ability,and simulation results demonstrate the effectiveness of the proposed algorithms.

Photonics-based real-time and high-resolution ISAR imaging of non-cooperative target

Real-time and high-resolution imaging is demonstrated based on field trial detection of a non-cooperative target using a photonics-based inverse synthetic aperture radar(ISAR).By photonic generation and de-chirping of broadband linear frequency modulation signals,the radar can achieve a high range resolution thanks to the large instantaneous bandwidth(8 GHz at the K band),as well as real-time ISAR imaging using low-speed analog-to-digital conversion(25 MSa/s).A small-size unmanned aerial vehicle is employed as the noncooperative target,and ISAR imaging is realized with a resolution far better than those achieved by the previously reported photonics-based ISARs.The capability for real-time ISAR imaging is also verified with an imaging frame rate of 25 fps.These results validate that the photonics-based radar is feasible in practical real-time and highresolution ISAR imaging applications.

A Method to Obtain the Moving Speed of Uncooperative Target Based on Only Two Measurements

The existing research results show that a fixed single station must conduct three consecutive frequency shift measurements and obtain the target’s moving speed by constructing two frequency difference equations. This article proposes a new method that requires only two consecutive measurements. While using the azimuth measurement to obtain the angular difference between two radial distances, it also conducts two consecutive Doppler frequency shift measurements at the same target azimuth. On the basis of this measurement, a frequency difference equation is first constructed and solved jointly with the Doppler frequency shift equation. By eliminating the velocity variable and using the measured angular difference to obtain the target’s lead angle, the target’s velocity can be solved by using the Doppler frequency shift equation again. The new method avoids the condition that the target must move equidistantly, which not only provides an achievable method for engineering applications but also lays a good foundation for further exploring the use of steady-state signals to achieve passive positioning.

Non-Cooperative Game of Coordinated Scheduling of Parallel Machine Production and Transportation in Shared Manufacturing

Given the challenges of manufacturing resource sharing and competition in the modern manufacturing industry,the coordinated scheduling problem of parallel machine production and transportation is investigated.The problem takes into account the coordination of production and transportation before production as well as the disparities in machine spatial position and performance.A non-cooperative game model is established,considering the competition and self-interest behavior of jobs from different customers for machine resources.The job from different customers is mapped to the players in the game model,the corresponding optional processing machine and location are mapped to the strategy set,and the makespan of the job is mapped to the payoff.Then the solution of the scheduling model is transformed into the Nash equilibrium of the non-cooperative game model.A Nash equilibrium solution algorithm based on the genetic algorithm(NEGA)is designed,and the effective solution of approximate Nash equilibrium for the game model is realized.The fitness function,single-point crossover operator,and mutation operator are derived from the non-cooperative game model’s characteristics and the definition of Nash equilibrium.Rules are also designed to avoid the generation of invalid offspring chromosomes.The effectiveness of the proposed algorithm is demonstrated through numerical experiments of various sizes.Compared with other algorithms such as heuristic algorithms(FCFS,SPT,and LPT),the simulated annealing algorithm(SA),and the particle swarm optimization algorithm(PSO),experimental results show that the proposed NE-GA algorithm has obvious performance advantages.

Peer-to-Peer Energy Trading Method of Multi-Virtual Power Plants Based on Non-Cooperative Game

The current electricity market fails to consider the energy consumption characteristics of transaction subjects such as virtual power plants.Besides,the game relationship between transaction subjects needs to be further explored.This paper proposes a Peer-to-Peer energy trading method for multi-virtual power plants based on a non-cooperative game.Firstly,a coordinated control model of public buildings is incorporated into the scheduling framework of the virtual power plant,considering the energy consumption characteristics of users.Secondly,the utility functions of multiple virtual power plants are analyzed,and a non-cooperative game model is established to explore the game relationship between electricity sellers in the Peer-to-Peer transaction process.Finally,the influence of user energy consumption characteristics on the virtual power plant operation and the Peer-to-Peer transaction process is analyzed by case studies.Furthermore,the effect of different parameters on the Nash equilibrium point is explored,and the influence factors of Peer-to-Peer transactions between virtual power plants are summarized.According to the obtained results,compared with the central air conditioning set as constant temperature control strategy,the flexible control strategy proposed in this paper improves the market power of each VPP and the overall revenue of the VPPs.In addition,the upper limit of the service quotation of the market operator have a great impact on the transaction mode of VPPs.When the service quotation decreases gradually,the P2P transaction between VPPs is more likely to occur.

Non-Cooperative Behavior Management in Large-Scale Group Decision-Making Considering the Altruistic Behaviors of Experts and Its Application in Emergency Alternative Selection

Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooperative behavior management assumed that the maximumdegree of cooperation of experts is to totally accept the revisions suggested by the moderator,which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process.In addition,when grouping a large group into subgroups by clustering methods,existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously.In this study,we introduce a clustering method considering the similarity of evaluation values and the trust relations of experts and then develop a consensusmodel taking into account the altruistic behaviors of experts.First,we cluster experts into subgroups by a constrained Kmeans clustering algorithm according to the opinion similarity and trust relationship of experts.Then,we calculate the weights of experts and clusters based on the centrality degrees of experts.Next,to enhance the quality of consensus reaching,we identify three kinds of non-cooperative behaviors and propose corresponding feedback mechanisms relying on the altruistic behaviors of experts.A numerical example is given to show the effectiveness and practicality of the proposed method in emergency decision-making.The study finds that integrating altruistic behavior analysis in group decision-making can safeguard the interests of experts and ensure the integrity of decision-making information.

Coordinated Scheduling of Two-Agent Production and Transportation Based on Non-Cooperative Game

A two-agent production and transportation coordinated scheduling problem in a single-machine environment is suggested to compete for one machine from different downstream production links or various consumers.The jobs of two agents compete for the processing position on a machine,and after the pro-cessed,they compete for the transport position on a transport vehicle to be trans-ported to two agents.The two agents have different objective functions.The objective function of the first agent is the sum of the makespan and the total trans-portation time,whereas the objective function of the second agent is the sum of the total completion time and the total transportation time.Given the competition between two agents for machine resources and transportation resources,a non-cooperative game model with agents as game players is established.The job pro-cessing position and transportation position corresponding to the two agents are mapped as strategies,and the corresponding objective function is the utility func-tion.To solve the game model,an approximate Nash equilibrium solution algo-rithm based on an improved genetic algorithm(NE-IGA)is proposed.The genetic operation based on processing sequence and transportation sequence,as well as the fitness function based on Nash equilibrium definition,are designed based on the features of the two-agent production and transportation coordination scheduling problem.The effectiveness of the proposed algorithm is demonstrated through numerical experiments of various sizes.When compared to heuristic rules such as the Longest Processing Time first(LPT)and the Shortest Processing Time first(SPT),the objective function values of the two agents are reduced by 4.3%and 2.6% on average.

Inertial parameter estimation and control of non-cooperative target with unilateral contact constraint

In this paper, the relative sliding motion between the target and the manipulator’s endeffector is considered and characterized as a unilateral contact constraint. A new possible solution is presented to estimate the inertial parameters of a non-cooperative target while the relative sliding motion exists. First, the detailed analysis of the dynamical model is presented, and a parameterexplicit linear time-varying model is obtained. Then, an extended state observer is constructed based on the new model, which can effectively estimate the unknown inertial parameters of the target when relative sliding motion exists. As the modified reactionless controller requires the knowledge of inertial parameters, a hybrid post-capture control scheme is also established based on the switch law between different controllers. The correctness and efficiency of the proposed algorithm are validated by numerical simulation, which proves a potential framework for the non-cooperative target postcapture operation.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

Target Detection Algorithm in Foggy Scenes Based on Dual Subnets

Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the image by the universal detection network.Thus,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this paper.Firstly,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy scenes.In the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the model.Secondly,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous fog.Finally,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is redesigned.In this way,the feature extraction ability of the network for deep-level information can be enhanced.The experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection model.The DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.

Improved Weighted Local Contrast Method for Infrared Small Target Detection

In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).

Distinct molecular targets of ProEGCG from EGCG and superior inhibition of angiogenesis signaling pathways for treatment of endometriosis

Endometriosis is a common chronic gynecological disease with endometrial cell implantation outside the uterus.Angiogenesis is a major pathophysiology in endometriosis.Our previous studies have demonstrated that the prodrug of epigallocatechin gallate(ProEGCG)exhibits superior anti-endometriotic and anti-angiogenic effects compared to epigallocatechin gallate(EGCG).However,their direct binding targets and underlying mechanisms for the differential effects remain unknown.In this study,we demonstrated that oral ProEGCG can be effective in preventing and treating endometriosis.Additionally,1D and 2D Proteome Integral Solubility Alteration assay-based chemical proteomics identified metadherin(MTDH)and PX domain containing serine/threonine kinase-like(PXK)as novel binding targets of EGCG and ProEGCG,respectively.Computational simulation and BioLayer interferometry were used to confirm their binding affinity.Our results showed that MTDH-EGCG inhibited protein kinase B(Akt)-mediated angiogenesis,while PXK-ProEGCG inhibited epidermal growth factor(EGF)-mediated angiogenesis via the EGF/hypoxia-inducible factor(HIF-1a)/vascular endothelial growth factor(VEGF)pathway.In vitro and in vivo knockdown assays and microvascular network imaging further confirmed the involvement of these signaling pathways.Moreover,our study demonstrated that ProEGCG has superior therapeutic effects than EGCG by targeting distinct signal transduction pathways and may act as a novel antiangiogenic therapy for endometriosis.

The functions of exosomes targeting astrocytes and astrocyte-derived exosomes targeting other cell types

Astrocytes are the most abundant glial cells in the central nervous system;they participate in crucial biological processes,maintain brain structure,and regulate nervous system function.Exosomes are cell-derived extracellular vesicles containing various bioactive molecules including proteins,peptides,nucleotides,and lipids secreted from their cellular sources.Increasing evidence shows that exosomes participate in a communication network in the nervous system,in which astrocyte-derived exosomes play important roles.In this review,we have summarized the effects of exosomes targeting astrocytes and the astrocyte-derived exosomes targeting other cell types in the central nervous system.We also discuss the potential research directions of the exosome-based communication network in the nervous system.The exosome-based intercellular communication focused on astrocytes is of great significance to the biological and/or pathological processes in different conditions in the brain.New strategies may be developed for the diagnosis and treatment of neurological disorders by focusing on astrocytes as the central cells and utilizing exosomes as communication mediators.

Spatial and temporal evolution of electromagnetic pulses from solid target irradiated with multi-hundred-terawatt laser pulse inside target chamber

Giant electromagnetic pulses(EMPs) induced by high-power laser irradiating solid targets interfere with various experimental diagnoses and even damage equipment,so unveiling the evolution of EMPs inside the laser chamber is crucial for designing effective EMP shielding.In this work,the transmission characteristics of EMPs as a function of distances from the target chamber center(TCC) are studied using B-dot probes.The mean EMP amplitude generated by picosecond laser-target interaction reaches 561 kV m^(-1),357 kV m^(-1),395 kV m^(-1),and 341 kV m^(-1)at 0.32 m,0.53 m,0.76 m,and 1 m from TCC,which decreases dramatically from 0.32 m to 0.53 m.However,it shows a fluctuation from 0.53 m to 1 m.The temporal features of EMPs indicate that time-domain EMP signals near the target chamber wall have a wider full width at half maximum compared to that close to TCC,mainly due to the echo oscillation of electromagnetic waves inside the target chamber based on simulation and experimentation.The conclusions of this study will provide a new approach to mitigate strong electromagnetic pulses by decreasing the echo oscillation of electromagnetic waves inside the target chamber during laser coupling with targets.

A food-grade and senescent cell-targeted fisetin delivery system based on whey protein isolate-galactooligosaccharides Maillard conjugate

Cellular senescence is the results of aging and age-related diseases,and the development of anti-aging methods may improve health and extend longevity.The natural flavonol fisetin has been shown to antagonize senescence in vitro and increases longevity in vivo,but has poor water solubility and limited bioavailability.In this study,a food-grade and senescent cell-targeted delivery system for fisetin was developed based on whey protein isolate-galactooligosaccharides(WPI-GOS)Maillard conjugate,which could recognize senescence associatedβ-galactosidase in senescent cells.The fisetin nanoparticles possessed a high encapsulation efficiency,excellent dispersibility in water,good storage stability and well biocompatibility.Moreover,they could effectively accumulate and retain in senescent cells with excellent senescent cell-targeting efficacy,and inhibit the oxidative stress-induced cellular senescence in vitro.Thus,this novel nanoparticle system based on WPI-GOS Maillard conjugate showed promise to deliver hydrophobic bioactive ingredients like fisetin to senescent cells to improve their bioavailability and anti-senescence effect.