Abstract:In this paper,an optimized backstepping tracking control method based on a reinforcement learning strategy is proposed for a single-link flexible-joint robotic arm system.Firstly,the actor-critic ar-chitecture is employed at each backstepping step to implement the reinforcement learning strategy,thereby obtaining the optimal virtual controller for each subsystem and ultimately deriving the system's optimal controller.Then,based on the defined Lyapunov function,it is demonstrated that all signals of the single-link flexible-joint robotic arm system are bounded,proving the stability of the designed control method.Finally,simulation experiments verify the effectiveness of the optimized backstepping tracking control based on reinforcement learning strategy in a single-link flexible-joint robotic arm system.

Abstract:Salicylic acid(SA),as a key regulator in plants,is of great significance for plant growth regula-tion.In this study,18 SA derivatives were synthesized around the hydroxyl and carboxyl groups based on the structure of SA,aiming to explore new herbicides by regulating the SA signaling pathway.In the pre-liminary screening of oilseed rape and barnyardgrass seeds at 10 Pg/L and 100 Pg/L,SA-1 and SA-8 were found to inhibit the germination rate of weed seeds in a small-cup-and-pan-dish experiment.In order to further verify the inhibitory effect of SA derivatives on root length,apple seedlings were treated with 10 Pg/L,and it was confirmed that SA-1,SA-2 and SA-8 had significant inhibitory effects on root length.The results showed that SA-1,SA-2 and SA-8 exhibited superior herbicidal activities compared with SA,and the herbicidal activities of SA-1,SA-2 and SA-8 were also tested in a scaled-up experiment,in which oilseed rape,amaranth,barnyardgrass,and marestail were sprayed at the doses of 375 g/ha,750 g/ha,and 1 500 g/ha.The results showed that SA-1,SA-2 and SA-8 exhibited superior herbicidal activities com-pared with SA.In this study,SA-1,SA-2 and SA-8 were selected as three compounds with significant in-hibitory effects on weeds by taking SA signaling pathway as the entry point,which opens up a new path for the research and development of new herbicides.

Abstract:In recent years,transition metal carbonates have been considered as promising anode materials for lithium-ion batteries(LIBs)due to their ease of preparation and low cost.However,its cationic radius is small which resulting in strong cationic polarization and their poor structural stability and rate perform-ance have hindered the full realization of their high-performance capabilities.In this study,based on MnCO3,a bimetallic carbonates strategy was employed to incorporate nickel metal ions(x=0.2,0.25,0.5)in MnCO3 using a simple solvothermal method and NixMn1-xCO3(x=0.2,0.25,0.5)materials were synthesized.The structure and morphology of the synthesized NixMn1-xCO3 materials were charac-terized using X-ray diffraction,X-ray photoelectron spectroscopy,and scanning electron microscopy.As anode materials for LIBs,the electrochemical performance of the as-prepared NixMn1-xCO3 materials were also investigated.The results indicate that the morphology of the NixMn1-xCO3 materials change with the incorporation of nickel ions.Bimetallic synergistic effect improves the electrochemical performance of the nickel-doped carbonate materials.When x is 0.25,the as-prepared Ni0.25Mn0.75CO3 material exhibits the smallest particle size and the best electrochemical performance.At a current density of 1 A/g,the Ni0.25Mn0.75CO3 electrode maintains a reversible specific capacity of 595 mA·h·g-1 after 500 cycles,demonstrating the superiority of the bimetallic carbonate strategy.This work provides theoretical evidence for the development of new inorganic carbonate-based anode materials for LIBs with high specific capacity and stable cycling performance.

Abstract:Microcapsules that encapsulate functional components have attracted extensive attention because of their advantages of easy preparation and strong designability,and the use of microcapsules to construct functional coatings can easily realize functional imparting,which effectively expands the application scenar-ios of coatings.At present,the research of microcapsule technology in the field of coating continues to ad-vance,and the purpose of this paper is to systematically elaborate the composition and construction strate-gy of microcapsules,and analyze the advantages and disadvantages of various preparation processes such as in-situ polymerization,solvent evaporation,and photopolymerization.In addition,the research status of functional coatings such as self-healing coatings,anti-corrosion coatings,self-lubricating coatings,fire-proof coatings,antibacterial coatings,and thermal insulation coatings based on microcapsules is expoun-ded,so as to provide theoretical reference and technical reference for further research and industrial appli-cation of microcapsules in the field of functional coatings.It is expected that the development of functional microcapsules and coatings in the future will mainly focus on the construction strategy of high-performance microcapsules,multi-functional integration,and the promotion of customization of microcapsules.

Abstract:To address the challenge of fault diagnosis under limited labeled data,this paper proposes a lightweight Siamese network tailored for few-shot bearing condition monitoring.Raw one-dimensional vi-bration signals are first converted into two-dimensional time-frequency images via Continuous Wavelet Transform,enabling effective denoising and salient feature representation.A metric learning paradigm constructs positive and negative pairs to enhance data diversity and model generalization.The network le-verages MobileNetV3S as the backbone,augmented with an Efficient Channel Attention mechanism to se-lectively emphasize informative channels while maintaining low complexity.Additionally,skip connections in deep Bneck modules are incorporated to improve feature propagation,and global average pooling re-places fully connected layers to further reduce parameters.Experimental validation shows that the pro-posed approach achieves 91.67%accuracy with only 1.16 M parameters and 0.05 GFLOPs,demonstrating superior performance in accuracy,efficiency,and real-time applicability under extreme sample constraints.

Abstract:The mitochondrial electron transport chain(ETC)transfers electrons from reducing donors to oxygen through four enzyme complexes,while driving proton translocation across the inner membrane to create a proton gradient.The F1F0 ATP synthase utilizes this gradient to synthesize ATP,completing the cellular energy conversion process.During electron transfer,a small fraction of electrons may leak from the ETC,leading to the generation of reactive oxygen species(ROS).ROS play crucial physiological roles in stem cell proliferation,differentiation,and self-renewal,making the precise regulation of ROS levels essential for maintaining stem cell homeostasis and function.Investigating how the ETC regulates stem cell fate through ROS generation is of great significance for understanding stem cell regulatory mecha-nisms.This review primarily discusses the structure and function of ETC complexes,the mechanisms by which the ETC generates ROS,and how ROS mediate the regulation of stem cell fate,and specifically fo-cuses on the pathway by which ETC generates ROS and regulates stem cell fate.Exploring this mecha-nism not only provides new perspectives for oxygen radical research but also offers potential therapeutic targets for the clinical management of tumors,aging-related conditions,neurodegenerative diseases,and other diseases related to stem cell function.

Abstract:This paper proposes a predefined-time tracking control scheme to address the trajectory tracking problem of unmanned helicopters subject to time-varying disturbances.To overcome the dependence of finite-time control on initial states and the conservatism of fixed-time control in estimating the convergence time upper bound,the predefined-time theory is introduced.This approach enables the precise presetting of the system convergence time using a single control parameter,eliminating the need for complex parame-ter tuning.First,a nonlinear dynamic model of the unmanned helicopter is established,and a time-varying gain disturbance observer is designed to estimate unknown time-varying disturbances.Second,utilizing a disturbance compensation mechanism,a sliding mode-based predefined-time controller is developed to en-sure that the helicopter's attitude and altitude strictly converge to the desired trajectory within a preset time window,independent of the initial system states.Rigorous analysis based on Lyapunov stability theo-ry verifies the predefined-time convergence characteristics of the closed-loop system.Finally,comparative simulation experiments demonstrate that the proposed strategy offers superior performance over existing methods in terms of convergence time controllability,tracking error suppression,and steady-state robust-ness.

Abstract:Dissolution testing of oral solid dosage forms represents a critical component in pharmaceutical development and quality control.The selection of an appropriate dissolution method to accurately charac-terize drug release behavior is essential for ensuring the consistency of drug product quality and clinical ef-ficacy.In recent years,dissolution methodologies have undergone continuous refinement,with selection criteria increasingly prioritizing biological relevance to better simulate the in vivo environment.To com-prehensively investigate the characteristics of diverse dissolution testing approaches,this paper analyzes the features of methods for oral solid dosage forms based on the working principles and hydrodynamic characteristics of dissolution apparatuses.Building upon this foundation,the study focuses on factors in-fluencing dissolution outcomes and the assessment of dissolution curve similarity.Furthermore,it system-atically examines the application of dissolution testing methods and elucidates the principles underlying in vitro-in vivo correlation(IVIVC).

Abstract:Based on the unique phase transition characteristics of vanadium dioxide(VO2),a metamaterial terahertz multifunctional device with absorption-sensing function was designed.The device is composed of five layers,from top to bottom are VO2 pattern layer,PTFE dielectric layer,VO2 pattern layer,PTFE dielectric layer and the bottom metal layer.The results show that when VO2 is in the all-metal state(con-ductivity is 200 000 S·m-1),the device has the absorption function,the absorption rate exceeds 90%and the relative bandwidth reaches 116.6%in the frequency range of 3.9 Thz～14.8 THz.In particular,the absorption rate at 6.4 THz,9.8 THz and 11.0 THz exceeds 99%,achieving perfect absorption.When the conductivity of VO2 is changed so that VO2 is in an insulating state,the design structure can be used as a biosensor with a narrow band absorption peak at 16.26 THz.The absorption rate is close to 90%,the sensitivity reaches 972 GHz/RIU,and the Q value is 81.3.

Abstract:The training and enhancement effect of supervised learning relies on paired datasets,but most of the data sets are synthetic datasets,which are poorly recovered and weakly generalized when migrated to real images.Based on the above problems,this paper proposes an unsupervised low-light image enhance-ment model with a joint physical model and multiple priors.First,supervised pre-training is performed on the synthetic dataset to meet the demand of the model to the low illumination;second,the model is fur-ther unsupervised,trained,and optimized on the real dataset and jointly with multiple physical a priori knowledge to better adapt it to the actual low illumination situation.The experiments show that the de-tails and illumination of the images are restored while the dependence on paired datasets is somewhat elimi-nated.

Abstract:The trajectory tracking control problem of unmanned surface vehicles(USVs)with unknown stochastic environmental disturbances was studied.Firstly,based on the theory of stochastic differential e-quations,a system dynamic model incorporating stochastic disturbance terms is established to accurately characterize the influence of environmental disturbances on the USVs motion trajectory.Secondly,a ro-bust trajectory tracking controller is designed based on the backstepping control method.The designed controller can ensure that the actual trajectory of the USVs asymptotically tracks any given reference traj-ectory with the desired precision.Then,it is rigorously proven that all signals in the closed-loop system satisfy global uniform ultimate boundedness.Finally,numerical simulations are conducted to verify the ef-fectiveness and robustness of the trajectory tracking controller.

Abstract:A spoof surface plasmon polaritons(SSPPs)based ultra-wideband Vivaldi antenna integrated with a director was proposed in this paper.To address the low gain limitation of conventional Vivaldi antennas,a performance breakthrough was achieved through the synergistic integration of SSPPs waveguides and director loading structures.Initially,an SSPPs waveguide structure featuring periodic grooves was incorporated into the traditional Vivaldi antenna.By optimizing the elliptical gradient matc-hing design,the surface SSPPs mode was effectively excited,yielding significant gain enhancement while preserving ultra-wideband characteristics.Furthermore,a concave-shaped directional array was implemen-ted on the SSPPs-enhanced ultra-wideband Vivaldi antenna.Through meticulous optimization of unit dimensions and periodic arrangement,surface current distribution was precisely controlled and surface wave suppression was achieved,resulting in a peak gain of 12.28 dBi,radiation efficiency up to 98%,and an operational bandwidth spanning 14.63～36.54 GHz.The proposed configuration employs a low-loss Rogers RT5880 dielectric substrate,realizing low-profile geometry,high impedance matching,and stable end-fire radiation characteristics.Simulation results demonstrate that this design simultaneously achieves ultra-wideband operation,high gain,and superior efficiency in millimeter-wave frequencies,providing a novel paradigm for high-performance antenna development in next-generation millimeter-wave.

Abstract:Aiming at the problems of residual metal catalysts and limited substrate applicability in tradi-tional surface-initiated atomic transfer radical polymerization(SI-ATRP),this work proposes a new strat-egy of surface-initiated metal-free ATRP(metal-free ATRP)based on polydopamine-assisted.Firstly,the polydopamine(PDA)coating was formed on the glass substrates through the self-polymerization of dopa-mine.Subsequently,the surface was functionalized with 2-bromoisobutyryl bromide to obtain the bromi-nated initiator layer(Glass@PDA-Br).Using Glass@PDA-Br as the initiator and methyl methacrylate(MMA)as the monomer,the surface-initiated metal-free ATRP was conducted under 365 nm UV irradia-tion.The resulting products were characterized and analyzed by X-ray photoelectron spectroscopy,scan-ning electron microscopy,and gel permeation chromatography.The results indicated that poly(methyl methacrylate)(PMMA)was successfully grafted from the glass surface.The water contact angle of the PMMA-grafted glass slide reached 136.9°,exhibiting a markedly hydrophobic state.Furthermore,the metal-free ATRP of MMA from the glass surface possessed the characteristics of a"living"/controlled rad-ical polymerization.This method achieves the controlled hydrophobic modification of glass surfaces and is expected to broaden the pathways for functionalizing solid substrates and the application prospects of met-al-free ATRP.

Abstract:This paper investigates the adaptive intelligent tracking control problem for a class of nonlinear systems,aiming to address challenges such as unknown parameters and the compatibility between control laws and the conditions of Barbalat's lemma.Within the framework of Barbalat's lemma and the back-stepping control technique,a novel intelligent control algorithm is proposed.By introducing suitable tun-ing functions and employing online estimation strategies,the method effectively avoids the over-parame-terization issue commonly encountered in conventional approaches.The resulting intelligent controller not only exhibits a simple structure but also demonstrates the capability to rapidly respond to reference sig-nals.This improvement overcomes limitations of traditional Lyapunov-based controller design methods,such as structural complexity,high computational burden,and insufficient robustness.Simulation results are provided to verify the effectiveness of the proposed control algorithm in nonlinear systems.

Abstract:Rare earth elements(REEs)demonstrate significant potential in tailoring microstructures and improving the mechanical properties of titanium alloys produced by additive manufacturing(AM).Appro-priate addition of REEs in raw materials presents a novel approach to enhance the microstructure and me-chanical properties of AM titanium alloys.This review investigates the mechanisms and performance effects of yttrium,lanthanum,cerium,and erbium REEs in current mainstream AM methods.The effects of rare earth content additions on material strength,hardness,and wear resistance are summarized.Ex-cessive additions induce more brittle phases,segregation,and porosity defects,leading to reduced plastici-ty.Rare earth doping offers a viable pathway for high-performance AM titanium alloys,but requires bal-ancing rare earth composition,process parameters,and thermal history to achieve synergistic optimization of strength,plasticity,and stability.

Abstract:Fuzzy logic operations play a crucial role in fuzzy control.This paper aims to define the fuzzy Peirce arrow operation,and incorporate the fuzzy Sheffer stroke operation and the fuzzy Peirce arrow oper-ation into a unified framework,namely defining the HP operation.It will further analyze the structure of the HP operation,discuss its relationships with the fuzzy weak HP operation,the fuzzy Sheffer stroke op-eration and the fuzzy Peirce arrow operation,as well as construct and characterize the non-trivial HP oper-ation.Finally,two special operations are proposed on certain non-trivial HP operation sets,through which a semigroup and a commutative monoid can be obtained,respectively.

Abstract:Backscatter communication(BackCom),as a potential key technology for next-generation low-power Internet of Things(IoT)networks,has garnered significant attention due to low-power wireless in-formation and power transfer.The performance enhancement of BackCom is limited by the dual-channel fading effects.To this end,this paper proposes a linear minimum mean square error-based channel estima-tion and phase-shift optimization algorithm.Then,the channel models of both direct links and the casca-ded links are established,where a closed-form estimator is designed by utilizing channel statistical charac-teristics.Meanwhile,the phase shift matrix of RIS is optimized in a low computational complexity way.Simulation results validate the superiority of the proposed scheme in the channel estimation accuracy com-pared to the benchmark schemes.

Abstract:To improve the efficiency of urban traffic management,the application of intelligent transporta-tion systems(ITS)has become a practical and effective approach.Real-time traffic flow monitoring tech-nology provides essential data support for such systems.This study focuses on enhancing the performance of terminal devices used for real-time traffic monitoring and proposes a method based on the YOLO object detection algorithm.By incorporating image preprocessing techniques,the system achieves improved de-tection accuracy while reducing computational resource consumption at the terminal.The research utilizes a subset of the COCO public dataset to construct a customized training dataset suitable for this task.YOLOv5s and YOLOv8s models were trained and comprehensively evaluated across various scenarios,in-cluding dynamic video and real-time video streams.Techniques such as background subtraction,Contrast Limited Adaptive Histogram Equalization(CLAHE),and median filtering were applied to enhance input image quality.Experimental results demonstrate that these preprocessing methods improve detection accu-racy by approximately 1.2%to 1.8%under different testing conditions and environmental complexities,while also reducing resource usage.This study systematically analyzes key components including model training,image processing,and performance evaluation.Through a series of video-based and real-world simulation experiments,the proposed approach is shown to have practical value for intelligent traffic appli-cations.