Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta...Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.展开更多
In recent years,the research on superconductivity in one-dimensional(1D)materials has been attracting increasing attention due to its potential applications in low-dimensional nanodevices.However,the critical temperat...In recent years,the research on superconductivity in one-dimensional(1D)materials has been attracting increasing attention due to its potential applications in low-dimensional nanodevices.However,the critical temperature(T_(c))of 1D superconductors is low.In this work,we theoretically investigate the possible high T_(c) superconductivity of(5,5)carbon nanotube(CNT).The pristine(5,5)CNT is a Dirac semimetal and can be modulated into a semiconductor by full hydrogenation.Interestingly,by further hole doping,it can be regulated into a metallic state with the sp3-hybridized𝜎electrons metalized,and a giant Kohn anomaly appears in the optical phonons.The two factors together enhance the electron–phonon coupling,and lead to high-T_(c) superconductivity.When the hole doping concentration of hydrogenated-(5,5)CNT is 2.5 hole/cell,the calculated T_(c) is 82.3 K,exceeding the boiling point of liquid nitrogen.Therefore,the predicted hole-doped hydrogenated-(5,5)CNT provides a new platform for 1D high-T_(c) superconductivity and may have potential applications in 1D nanodevices.展开更多
Compared to the well-studied two-dimensional(2D)ferroelectricity,the appearance of 2D antiferroelectricity is much rarer,where local dipoles from the nonequivalent sublattices within 2D monolayers are oppositely orien...Compared to the well-studied two-dimensional(2D)ferroelectricity,the appearance of 2D antiferroelectricity is much rarer,where local dipoles from the nonequivalent sublattices within 2D monolayers are oppositely oriented.Using NbOCl_(2) monolayer with competing ferroelectric(FE)and antiferroelectric(AFE)phases as a 2D material platform,we demonstrate the emergence of intrinsic antiferroelectricity in NbOCl_(2) monolayer under experimentally accessible shear strain,along with new functionality associated with electric field-induced AFE-to-FE phase transition.Specifically,the complex configuration space accommodating FE and AFE phases,polarization switching kinetics,and finite temperature thermodynamic properties of 2D NbOCl_(2) are all accurately predicted by large-scale molecular dynamics simulations based on deep learning interatomic potential model.Moreover,room temperature stable antiferroelectricity with low polarization switching barrier and one-dimensional collinear polarization arrangement is predicted in shear-deformed NbOCl_(2) monolayer.The transition from AFE to FE phase in 2D NbOCl_(2) can be triggered by a low critical electric field,leading to a double polarization–electric(P–E)loop with small hysteresis.A new type of optoelectronic device composed of AFE-NbOCl_(2) is proposed,enabling electric“writing”and nonlinear optical“reading”logical operation with fast operation speed and low power consumption.展开更多
SrRuO_(3)is a canonical itinerant ferromagnet,yet its properties in the extreme two-dimensional limit on a(111)crystal plane remain largely unexplored.Here,we demonstrate a complete transformation of its ground state ...SrRuO_(3)is a canonical itinerant ferromagnet,yet its properties in the extreme two-dimensional limit on a(111)crystal plane remain largely unexplored.Here,we demonstrate a complete transformation of its ground state driven by dimensional reduction.As the thickness of(111)-oriented SrRuO_(3)films is reduced to a few unit cells,the system transitions from a metallic ferromagnet to a semiconducting antiferromagnet.This emergent antiferromagnetism is evidenced by a vanishing magnetic remanence and most strikingly,by the appearance of an unconventional twelve-fold anisotropic magnetoresistance.First-principles calculations confirm that an A-type antiferromagnetic order is the stable ground state in the ultrathin limit.Our findings establish(111)dimensional engineering as a powerful route to manipulate correlated electron states and uncover novel functionalities for antiferromagnetic spintronics.展开更多
Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by ...Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by enlarging the receptive field,which indicates how the convolution process extracts features in a high dimensional feature space.However,its functionality is restricted to the spatial dimension and network depth,limiting further improvements in network performance due to insufficient information interaction and representation.Crucially,the potential of high dimensional feature space in the channel dimension and the exploration of network width/resolution remain largely untapped.In this paper,we consider nonlinear transforms from the perspective of feature space,defining high-dimensional feature spaces in different dimensions and investigating the specific effects.Firstly,we introduce the dimension increasing and decreasing transforms in both channel and spatial dimensions to obtain high dimensional feature space and achieve better feature extraction.Secondly,we design a channel-spatial fusion residual transform(CSR),which incorporates multi-dimensional transforms for a more effective representation.Furthermore,we simplify the proposed fusion transform to obtain a slim architecture(CSR-sm),balancing network complexity and compression performance.Finally,we build the overall network with stacked CSR transforms to achieve better compression and reconstruction.Experimental results demonstrate that the proposed method can achieve superior ratedistortion performance compared to the existing LIC methods and traditional codecs.Specifically,our proposed method achieves 9.38%BD-rate reduction over VVC on Kodak dataset.展开更多
Flexible X-ray detectors have garnered considerable attention owing to their extensive applications in three-dimensional (3D) image reconstruction, disease diagnosis and nondestructive testing^([1-3]). Conventional X-...Flexible X-ray detectors have garnered considerable attention owing to their extensive applications in three-dimensional (3D) image reconstruction, disease diagnosis and nondestructive testing^([1-3]). Conventional X-ray detectors typically employ active-matrix backplanes fabricated on rigid glass substrates, which integrate switching transistors and photodetectors^([4, 5]).展开更多
The phenomenon of photothermally induced transparency(PTIT)arises from the nonlinear behavior of an optical cavity,resulting from the heating of mirrors.By introducing a coupling field in the form of a standing wave,P...The phenomenon of photothermally induced transparency(PTIT)arises from the nonlinear behavior of an optical cavity,resulting from the heating of mirrors.By introducing a coupling field in the form of a standing wave,PTIT can be transitioned into photothermally induced grating(PTIG).A two-dimensional(2D)diffraction pattern is achieved through the adjustment of key parameters such as coupling strength and effective detuning.Notably,we observe first,second,and third-order intensity distributions,with the ability to transfer probe energy predominantly to the third order by fine-tuning the coupling strength.The intensity distribution is characterized by(±m,±n),where m,n=1,2,3.This proposed 2D grating system offers a novel platform for manipulating PTIG,presenting unique possibilities for enhanced functionality and control.展开更多
BACKGROUND Intraoperative determination of resection margin and adequate residual liver parenchyma are the key points of hepatectomy for the treatment of liver tumors.Intraoperative ultrasound and indocyanine green fl...BACKGROUND Intraoperative determination of resection margin and adequate residual liver parenchyma are the key points of hepatectomy for the treatment of liver tumors.Intraoperative ultrasound and indocyanine green fluorescence navigation are the most commonly used methods at present,but the technical barriers limit their promotion.AIM To evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.METHODS From September 2020 to January 2022,8 patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocar-cinoma,and gastric cancer liver metastasis were included in this study.All patients underwent 3D-LAST in precise resection of liver tumors.RESULTS All patients(8/8,100%)underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.CONCLUSION In conclusion,the 3D-LAST is a safe and effective new method for liver intraop-erative navigation,which is practical and easy to promote.Core Tip:The aim of this study is to evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.Eight patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocarcinoma,and gastric cancer liver metastasis underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.In conclusion,the 3D-LAST is a safe and effective new method for liver intraoperative navigation,which is practical and easy to promote.INTRODUCTION Hepatectomy is widely used for the treatment of liver tumors.In recent decades,the concept and practice of hepatectomy have developed from irregular,regular and anatomical to the current precise resection.Necessary assistive technologies have enabled these advances.Intraoperative ultrasound(IOUS)localization and indocyanine green(ICG)fluorescence imaging guidance are two frequently-used approaches for laparoscopic hepatectomy[1,2].IOUS is an invaluable auxiliary means widely accepted in surgery for real-time diagnostic information to determine resection range and navigate the surgical path[3].However,the major limitation of IOUS is the time cost during the procedure for paging the sono-graphers and the difficulty of deciphering two dimensional images[4].ICG is a non-toxic water-soluble fluorophore that reveals fluorescence under the near-infrared spectrum[5].Since liver tissue penetration is limited to 5 to 10 mm,that restricted the visualization of deeper tumors by ICG excitation,thereby interfering with its application in laparoscopic hepatectomy[6].IOUS and ICG navigation require specific technical equipment,making implementation difficult in many centers.And these techniques will significantly increase the operation time.Three-dimensional(3D)visualization involves extracting features and producing volumetric images based on computed tomography(CT)through a computer postprocessing technique.This tool offers a reasonable approach to the clinical decision for the potential to display the complex internal anatomy in an intuitive and stereoscopic manner[7].In the past few decades,applying 3D simulation software for liver volume calculation,virtual simulation surgery,portal hypertension monitor,and surgical navigation has proven to be safe and effective[8].Therefore,we propose a new method to find obvious anatomical markers and calculate the resection range according to 3D positioning before operation.During the operation,the scope of resection was delineated with silk thread,and resection was performed.This is a new practical approach,which we named as 3D location approach with silk thread(3D-LAST).RESULTS During the study period from September 2020 to January 2022,5 patients with hepatocellular carcinoma,1 patient with intrahepatic cholangiocarcinoma,1 patient with hilar cholangiocarcinoma,and 1 patient with gastric cancer liver metastasis were assessed for liver resection.There were 5 males and 3 females.The mean age of these patients was 54.3±10.2 years(34-66 years).Preoperative 3D positioning was conducted and the scope of resection was delineated with a surgical suture successfully performed in all 8 patients without complications.The treatment results of these 8 patients are shown in Table 1.The 90-day operative mortality was zero.Complications worse than Dindo-Clavien IIIa was not observed at a mean follow-up time of 8.7 months(4-16 months),there was no evidence of tumor recurrence or extrahepatic metastasis.At the time of reporting,the patients are all alive and lead normal lives.We take one patient as an example,58-year-old male,who found a liver lesion 10 months after gastric cancer surgery.Enhanced CT showed that the lesion was located in the liver S5,about 1.5 cm in diameter,and considered metastatic lesions.We performed 3D-LAST guided hepatectomy on this patient(Figure 1).Other representative 3D-LAST surgical procedures are shown in Figure 2.展开更多
Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability ...Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability and validity of the DARS among Chinese individuals with major depressive disorder(MDD)and its treatment sensitivity in a prospective clinical study.Methods Data were from a multicentre,prospective clinical study(NCT03294525),which recruited both patients with MDD,who were followed for 8 weeks,and healthy controls(HCs),assessed at baseline only.The analysis included confirmatory factor analysis,validity and sensitivity to change.Results Patients’mean(standard deviation(SD))age was 34.8(11.0)years,with 68.7%being female.75.2%of patients with MDD had melancholic features,followed by 63.8%with anxious distress.Patients had experienced MDD for a mean(SD)of 9.2(18)months.DARS scores covered the full range of severity with no major floor or ceiling effects.Confirmatory factor analysis showed adequate fit statistics(comparative fit index 0.976,goodness-of-fit index 0.935 and root mean square error of approximation 0.055).Convergent validity with anhedonia-related measures was confirmed.While the correlation between the DARS and the Hamilton Depression Rating Scale was not strong(r=0.31,baseline),the DARS was found to differentiate between levels of depression.Greater improvements in DARS scores were seen with the Hamilton Rating Scale for Depression responder group(effect size 1.16)compared with the non-responder group(effect size 0.46).Conclusions This study comprehensively evaluated the measurement properties of the DARS using a Chinese population with MDD.Overall,the Chinese version of DARS demonstrates good psychometric properties and has been found to be responsive to change during antidepressant treatment.The DARS is a suitable scale for assessing patient-reported anhedonia in future clinical trials.展开更多
Low-dimensional physics provides profound insights into strongly correlated interactions,leading to enhancedquantum effects and the emergence of exotic quantum states.The Ln_(3)ScBi_(5)family stands out as a chemicall...Low-dimensional physics provides profound insights into strongly correlated interactions,leading to enhancedquantum effects and the emergence of exotic quantum states.The Ln_(3)ScBi_(5)family stands out as a chemicallyversatile kagome platform with mixed low-dimensional structural framework and tunable physical properties.Ourresearch initiates with a comprehensive evaluation of the currently known Ln_(3)ScBi_(5)(Ln=La-Nd,Sm)materials,providing a robust methodology for assessing their stability frontiers within this system.Focusing on Pr_(3)ScBi_(5),we investigate the influence of the zigzag chains of quasi-one-dimensional(Q1D)motifs and the distorted kagomelayers of quasi-two-dimensional(Q2D)networks in the mixed-dimensional structure on the intricate magneticground states and unique spin fluctuations.Our study reveals that the noncollinear antiferromagnetic(AFM)moments of Pr^(3+)ions are confined within the Q2D kagome planes,displaying minimal in-plane anisotropy.Incontrast,a strong AFM coupling is observed within the Q1D zigzag chains,significantly constraining spin motion.Notably,magnetic frustration is partially a consequence of coupling to conduction electrons via Ruderman-Kittel-Kasuya-Yosida interaction,highlighting a promising framework for future investigations into mixed-dimensional frustration in Ln_(3)ScBi_(5) systems.展开更多
The interplay between dimensionality and superconductivity is a central theme in understanding the behavior of low-dimensional superconductors. In this work, we investigate the dimensional crossover from quasi-two-dim...The interplay between dimensionality and superconductivity is a central theme in understanding the behavior of low-dimensional superconductors. In this work, we investigate the dimensional crossover from quasi-two-dimensional(quasi-2D) to three-dimensional(3D) superconductivity in(Li,Fe)OHFeSe_(1-x)S_(x) single crystals driven by sulfur doping.Through detailed structural, electrical, and magnetic characterization, we identify a critical doping level(x = 0.53) where the system transitions from quasi-2D to 3D superconducting behavior. Reduced superconducting fluctuations and nonFermi liquid behavior near this critical point suggest the presence of competition between intralayer and interlayer pairing mechanisms. Fluctuation conductivity analysis reveals that the coherence length along the c-axis, ζ_(c)(0), and the interlayer coupling strength, Γ, increase significantly at x = 0.53, marking the onset of 3D superconductivity. These findings provide new insights into the role of dimensionality and interlayer coupling in modulating superconducting properties, positioning(Li,Fe)OHFeSe_(1-x)S_(x) as a unique platform for exploring crossover physics in iron-based superconductors.展开更多
The inversion of large sparse matrices poses a major challenge in geophysics,particularly in Bayesian seismic inversion,significantly limiting computational efficiency and practical applicability to largescale dataset...The inversion of large sparse matrices poses a major challenge in geophysics,particularly in Bayesian seismic inversion,significantly limiting computational efficiency and practical applicability to largescale datasets.Existing dimensionality reduction methods have achieved partial success in addressing this issue.However,they remain limited in terms of the achievable degree of dimensionality reduction.An incremental deep dimensionality reduction approach is proposed herein to significantly reduce matrix size and is applied to Bayesian linearized inversion(BLI),a stochastic seismic inversion approach that heavily depends on large sparse matrices inversion.The proposed method first employs a linear transformation based on the discrete cosine transform(DCT)to extract the matrix's essential information and eliminate redundant components,forming the foundation of the dimensionality reduction framework.Subsequently,an innovative iterative DCT-based dimensionality reduction process is applied,where the reduction magnitude is carefully calibrated at each iteration to incrementally reduce dimensionality,thereby effectively eliminating matrix redundancy in depth.This process is referred to as the incremental discrete cosine transform(IDCT).Ultimately,a linear IDCT-based reduction operator is constructed and applied to the kernel matrix inversion in BLI,resulting in a more efficient BLI framework.The proposed method was evaluated through synthetic and field data tests and compared with conventional dimensionality reduction methods.The IDCT approach significantly improves the dimensionality reduction efficiency of the core inversion matrix while preserving inversion accuracy,demonstrating prominent advantages in solving Bayesian inverse problems more efficiently.展开更多
With the exponential growth of the internet of things,artificial intelligence,and energy-efficient high-volume data digital communications,there is an urgent demand to develop new information technologies with high st...With the exponential growth of the internet of things,artificial intelligence,and energy-efficient high-volume data digital communications,there is an urgent demand to develop new information technologies with high storage capacity.This needs to address the looming challenge of conventional Von Neumann architecture and Moore's law bottleneck for future data-intensive computing applications.A promising remedy lies in memristors,which offer distinct advantages of scalability,rapid access times,stable data retention,low power consumption,multistate storage capability and fast operation.Among the various materials used for active layers in memristors,low dimensional perovskite semiconductors with structural diversity and superior stability exhibit great potential for next generation memristor applications,leveraging hysteresis characteristics caused by ion migration and defects.In this review the progress of low-dimensional perovskite memory devices is comprehensively summarized.The working mechanism and fundamental processes,including ion migration dynamics,charge carrier transport and electronic resistance that underlies the switching behavior of memristors are discussed.Additionally,the device parameters are analyzed with special focus on the effective methods to improve electrical performance and operational stability.Finally,the challenges and perspective on major hurdles of low-dimensional perovskite memristors in the expansive application domains are provided.展开更多
Gas turbine rotors are complex dynamic systems with high-dimensional,discrete,and multi-source nonlinear coupling characteristics.Significant amounts of resources and time are spent during the process of solving dynam...Gas turbine rotors are complex dynamic systems with high-dimensional,discrete,and multi-source nonlinear coupling characteristics.Significant amounts of resources and time are spent during the process of solving dynamic characteristics.Therefore,it is necessary to design a lowdimensional model that can well reflect the dynamic characteristics of high-dimensional system.To build such a low-dimensional model,this study developed a dimensionality reduction method considering global order energy distribution by modifying the proper orthogonal decomposition theory.First,sensitivity analysis of key dimensionality reduction parameters to the energy distribution was conducted.Then a high-dimensional rotor-bearing system considering the nonlinear stiffness and oil film force was reduced,and the accuracy and the reusability of the low-dimensional model under different operating conditions were examined.Finally,the response results of a multi-disk rotor-bearing test bench were reduced using the proposed method,and spectrum results were then compared experimentally.Numerical and experimental results demonstrate that,during the dimensionality reduction process,the solution period of dynamic response results has the most significant influence on the accuracy of energy preservation.The transient signal in the transformation matrix mainly affects the high-order energy distribution of the rotor system.The larger the proportion of steady-state signals is,the closer the energy tends to accumulate towards lower orders.The low-dimensional rotor model accurately reflects the frequency response characteristics of the original high-dimensional system with an accuracy of up to 98%.The proposed dimensionality reduction method exhibits significant application potential in the dynamic analysis of highdimensional systems coupled with strong nonlinearities under variable operating conditions.展开更多
In this paper,the physics informed neural network(PINN)deep learning method is applied to solve two-dimensional nonlocal equations,including the partial reverse space y-nonlocal Mel'nikov equation,the partial reve...In this paper,the physics informed neural network(PINN)deep learning method is applied to solve two-dimensional nonlocal equations,including the partial reverse space y-nonlocal Mel'nikov equation,the partial reverse space-time nonlocal Mel'nikov equation and the nonlocal twodimensional nonlinear Schr?dinger(NLS)equation.By the PINN method,we successfully derive a data-driven two soliton solution,lump solution and rogue wave solution.Numerical simulation results indicate that the error range between the data-driven solution and the exact solution is relatively small,which verifies the effectiveness of the PINN deep learning method for solving high dimensional nonlocal equations.Moreover,the parameter discovery of the partial reverse space-time nonlocal Mel'nikov equation is analysed in terms of its soliton solution for the first time.展开更多
The size effects were experimentally investigated and the underlying mechanism was analyzed.The results reveal that,as the specimen size increases,the interconnectivity of macropores slightly decreases.This in turn co...The size effects were experimentally investigated and the underlying mechanism was analyzed.The results reveal that,as the specimen size increases,the interconnectivity of macropores slightly decreases.This in turn constrains the diffusion of CO_(2) and moisture in the specimens,resulting in an increase in the discrepancy between the internal and external carbonation degrees.An increase in cement paste thickness simultaneously decreases the quantity,average size,and interconnectivity of macropores,lowering the diffusion efficacy of CO_(2) and moisture and exacerbating the overall heterogeneity in carbonation.Moreover,the gradual blockage of macropores leads to the emergence of localized ‘occluded zones’ with much lower carbonation degree.The reduction in aggregate size significantly alters the average diameter and connectivity of macropores,leading to notable change to overall non-uniformity.This study provides insight into improving the CO_(2) curing effect of pervious concrete products and developing uniform curing methods.展开更多
On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on ...On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.The forum was organised by the China Writers Association and co-organised by China National Publications Import&Export(Group)Corporation.展开更多
This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effec...This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effects of dimensional parameters on the local and whole mechanisms in the design of hybrid humanoid robotic legs.It sequentially optimizes the dimensional parameters of the local and whole mechanism,thereby balancing the motion performance requirements of both.Additionally,it considers the assignment of efficient performance resources between the Local Functional Workspace(LFW)and the Whole Available Workspace(WAW).To facilitate the modeling and optimization process,a local/whole Equivalent Configuration Framework(ECF)is introduced.By decoupling the hybrid mechanism into a whole mechanism and multiple local mechanisms,the ECF enhances the efficiency of design,modeling,and performance evaluation.Prototype experiments are conducted to validate the effectiveness of LDSOS.This research provides an effective configuration framework for humanoid robotic leg design,establishing a theoretical and practical foundation for future optimized designs of humanoid robotic legs and pioneering novel approaches to the design of complex hybrid humanoid robotic legs.展开更多
基金funded by National Natural Science Foundation of China(Nos.12402142,11832013 and 11572134)Natural Science Foundation of Hubei Province(No.2024AFB235)+1 种基金Hubei Provincial Department of Education Science and Technology Research Project(No.Q20221714)the Opening Foundation of Hubei Key Laboratory of Digital Textile Equipment(Nos.DTL2023019 and DTL2022012).
文摘Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.
基金supported by the National Natural Science Foundation of China (Grant Nos.12074213 and 11574108)the Major Basic Program of Natural Science Foundation of Shandong Province (Grant No.ZR2021ZD01)the Natural Science Foundation of Shandong Province (Grant No.ZR2023MA082)。
文摘In recent years,the research on superconductivity in one-dimensional(1D)materials has been attracting increasing attention due to its potential applications in low-dimensional nanodevices.However,the critical temperature(T_(c))of 1D superconductors is low.In this work,we theoretically investigate the possible high T_(c) superconductivity of(5,5)carbon nanotube(CNT).The pristine(5,5)CNT is a Dirac semimetal and can be modulated into a semiconductor by full hydrogenation.Interestingly,by further hole doping,it can be regulated into a metallic state with the sp3-hybridized𝜎electrons metalized,and a giant Kohn anomaly appears in the optical phonons.The two factors together enhance the electron–phonon coupling,and lead to high-T_(c) superconductivity.When the hole doping concentration of hydrogenated-(5,5)CNT is 2.5 hole/cell,the calculated T_(c) is 82.3 K,exceeding the boiling point of liquid nitrogen.Therefore,the predicted hole-doped hydrogenated-(5,5)CNT provides a new platform for 1D high-T_(c) superconductivity and may have potential applications in 1D nanodevices.
基金supported by the National Natural Science Foundation of China (Grant No.11574244 for G.Y.G.)the XJTU Research Fund for AI Science (Grant No.2025YXYC011 for G.Y.G.)the Hong Kong Global STEM Professorship Scheme (for X.C.Z.)。
文摘Compared to the well-studied two-dimensional(2D)ferroelectricity,the appearance of 2D antiferroelectricity is much rarer,where local dipoles from the nonequivalent sublattices within 2D monolayers are oppositely oriented.Using NbOCl_(2) monolayer with competing ferroelectric(FE)and antiferroelectric(AFE)phases as a 2D material platform,we demonstrate the emergence of intrinsic antiferroelectricity in NbOCl_(2) monolayer under experimentally accessible shear strain,along with new functionality associated with electric field-induced AFE-to-FE phase transition.Specifically,the complex configuration space accommodating FE and AFE phases,polarization switching kinetics,and finite temperature thermodynamic properties of 2D NbOCl_(2) are all accurately predicted by large-scale molecular dynamics simulations based on deep learning interatomic potential model.Moreover,room temperature stable antiferroelectricity with low polarization switching barrier and one-dimensional collinear polarization arrangement is predicted in shear-deformed NbOCl_(2) monolayer.The transition from AFE to FE phase in 2D NbOCl_(2) can be triggered by a low critical electric field,leading to a double polarization–electric(P–E)loop with small hysteresis.A new type of optoelectronic device composed of AFE-NbOCl_(2) is proposed,enabling electric“writing”and nonlinear optical“reading”logical operation with fast operation speed and low power consumption.
基金supported by the National Natural Science Foundation of China(Grant Nos.12204521,12250710675,and 12504198)the National Key R&D Program of China(Grant No.2022YFA1403000)。
文摘SrRuO_(3)is a canonical itinerant ferromagnet,yet its properties in the extreme two-dimensional limit on a(111)crystal plane remain largely unexplored.Here,we demonstrate a complete transformation of its ground state driven by dimensional reduction.As the thickness of(111)-oriented SrRuO_(3)films is reduced to a few unit cells,the system transitions from a metallic ferromagnet to a semiconducting antiferromagnet.This emergent antiferromagnetism is evidenced by a vanishing magnetic remanence and most strikingly,by the appearance of an unconventional twelve-fold anisotropic magnetoresistance.First-principles calculations confirm that an A-type antiferromagnetic order is the stable ground state in the ultrathin limit.Our findings establish(111)dimensional engineering as a powerful route to manipulate correlated electron states and uncover novel functionalities for antiferromagnetic spintronics.
基金supported by the Key Program of the National Natural Science Foundation of China(Grant No.62031013)Guangdong Province Key Construction Discipline Scientific Research Capacity Improvement Project(Grant No.2022ZDJS117).
文摘Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by enlarging the receptive field,which indicates how the convolution process extracts features in a high dimensional feature space.However,its functionality is restricted to the spatial dimension and network depth,limiting further improvements in network performance due to insufficient information interaction and representation.Crucially,the potential of high dimensional feature space in the channel dimension and the exploration of network width/resolution remain largely untapped.In this paper,we consider nonlinear transforms from the perspective of feature space,defining high-dimensional feature spaces in different dimensions and investigating the specific effects.Firstly,we introduce the dimension increasing and decreasing transforms in both channel and spatial dimensions to obtain high dimensional feature space and achieve better feature extraction.Secondly,we design a channel-spatial fusion residual transform(CSR),which incorporates multi-dimensional transforms for a more effective representation.Furthermore,we simplify the proposed fusion transform to obtain a slim architecture(CSR-sm),balancing network complexity and compression performance.Finally,we build the overall network with stacked CSR transforms to achieve better compression and reconstruction.Experimental results demonstrate that the proposed method can achieve superior ratedistortion performance compared to the existing LIC methods and traditional codecs.Specifically,our proposed method achieves 9.38%BD-rate reduction over VVC on Kodak dataset.
文摘Flexible X-ray detectors have garnered considerable attention owing to their extensive applications in three-dimensional (3D) image reconstruction, disease diagnosis and nondestructive testing^([1-3]). Conventional X-ray detectors typically employ active-matrix backplanes fabricated on rigid glass substrates, which integrate switching transistors and photodetectors^([4, 5]).
文摘The phenomenon of photothermally induced transparency(PTIT)arises from the nonlinear behavior of an optical cavity,resulting from the heating of mirrors.By introducing a coupling field in the form of a standing wave,PTIT can be transitioned into photothermally induced grating(PTIG).A two-dimensional(2D)diffraction pattern is achieved through the adjustment of key parameters such as coupling strength and effective detuning.Notably,we observe first,second,and third-order intensity distributions,with the ability to transfer probe energy predominantly to the third order by fine-tuning the coupling strength.The intensity distribution is characterized by(±m,±n),where m,n=1,2,3.This proposed 2D grating system offers a novel platform for manipulating PTIG,presenting unique possibilities for enhanced functionality and control.
文摘BACKGROUND Intraoperative determination of resection margin and adequate residual liver parenchyma are the key points of hepatectomy for the treatment of liver tumors.Intraoperative ultrasound and indocyanine green fluorescence navigation are the most commonly used methods at present,but the technical barriers limit their promotion.AIM To evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.METHODS From September 2020 to January 2022,8 patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocar-cinoma,and gastric cancer liver metastasis were included in this study.All patients underwent 3D-LAST in precise resection of liver tumors.RESULTS All patients(8/8,100%)underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.CONCLUSION In conclusion,the 3D-LAST is a safe and effective new method for liver intraop-erative navigation,which is practical and easy to promote.Core Tip:The aim of this study is to evaluate the value of the three-dimensional location approach with silk thread(3D-LAST)in precise resection of liver tumors.Eight patients with liver tumors including hepatocellular carcinoma,intrahepatic cholangiocarcinoma,hilar cholangiocarcinoma,and gastric cancer liver metastasis underwent the operation successfully without any complications.During the mean follow-up of 8.7 months,all patients survived without tumor recurrence.In conclusion,the 3D-LAST is a safe and effective new method for liver intraoperative navigation,which is practical and easy to promote.INTRODUCTION Hepatectomy is widely used for the treatment of liver tumors.In recent decades,the concept and practice of hepatectomy have developed from irregular,regular and anatomical to the current precise resection.Necessary assistive technologies have enabled these advances.Intraoperative ultrasound(IOUS)localization and indocyanine green(ICG)fluorescence imaging guidance are two frequently-used approaches for laparoscopic hepatectomy[1,2].IOUS is an invaluable auxiliary means widely accepted in surgery for real-time diagnostic information to determine resection range and navigate the surgical path[3].However,the major limitation of IOUS is the time cost during the procedure for paging the sono-graphers and the difficulty of deciphering two dimensional images[4].ICG is a non-toxic water-soluble fluorophore that reveals fluorescence under the near-infrared spectrum[5].Since liver tissue penetration is limited to 5 to 10 mm,that restricted the visualization of deeper tumors by ICG excitation,thereby interfering with its application in laparoscopic hepatectomy[6].IOUS and ICG navigation require specific technical equipment,making implementation difficult in many centers.And these techniques will significantly increase the operation time.Three-dimensional(3D)visualization involves extracting features and producing volumetric images based on computed tomography(CT)through a computer postprocessing technique.This tool offers a reasonable approach to the clinical decision for the potential to display the complex internal anatomy in an intuitive and stereoscopic manner[7].In the past few decades,applying 3D simulation software for liver volume calculation,virtual simulation surgery,portal hypertension monitor,and surgical navigation has proven to be safe and effective[8].Therefore,we propose a new method to find obvious anatomical markers and calculate the resection range according to 3D positioning before operation.During the operation,the scope of resection was delineated with silk thread,and resection was performed.This is a new practical approach,which we named as 3D location approach with silk thread(3D-LAST).RESULTS During the study period from September 2020 to January 2022,5 patients with hepatocellular carcinoma,1 patient with intrahepatic cholangiocarcinoma,1 patient with hilar cholangiocarcinoma,and 1 patient with gastric cancer liver metastasis were assessed for liver resection.There were 5 males and 3 females.The mean age of these patients was 54.3±10.2 years(34-66 years).Preoperative 3D positioning was conducted and the scope of resection was delineated with a surgical suture successfully performed in all 8 patients without complications.The treatment results of these 8 patients are shown in Table 1.The 90-day operative mortality was zero.Complications worse than Dindo-Clavien IIIa was not observed at a mean follow-up time of 8.7 months(4-16 months),there was no evidence of tumor recurrence or extrahepatic metastasis.At the time of reporting,the patients are all alive and lead normal lives.We take one patient as an example,58-year-old male,who found a liver lesion 10 months after gastric cancer surgery.Enhanced CT showed that the lesion was located in the liver S5,about 1.5 cm in diameter,and considered metastatic lesions.We performed 3D-LAST guided hepatectomy on this patient(Figure 1).Other representative 3D-LAST surgical procedures are shown in Figure 2.
基金supported by the National Natural Science Foundation of China(No.82371530,82171529)the Capital Health Development Special Research Project(2022-1-4111)the National Key Technology R and D Program(No.2015BAI13B01).
文摘Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability and validity of the DARS among Chinese individuals with major depressive disorder(MDD)and its treatment sensitivity in a prospective clinical study.Methods Data were from a multicentre,prospective clinical study(NCT03294525),which recruited both patients with MDD,who were followed for 8 weeks,and healthy controls(HCs),assessed at baseline only.The analysis included confirmatory factor analysis,validity and sensitivity to change.Results Patients’mean(standard deviation(SD))age was 34.8(11.0)years,with 68.7%being female.75.2%of patients with MDD had melancholic features,followed by 63.8%with anxious distress.Patients had experienced MDD for a mean(SD)of 9.2(18)months.DARS scores covered the full range of severity with no major floor or ceiling effects.Confirmatory factor analysis showed adequate fit statistics(comparative fit index 0.976,goodness-of-fit index 0.935 and root mean square error of approximation 0.055).Convergent validity with anhedonia-related measures was confirmed.While the correlation between the DARS and the Hamilton Depression Rating Scale was not strong(r=0.31,baseline),the DARS was found to differentiate between levels of depression.Greater improvements in DARS scores were seen with the Hamilton Rating Scale for Depression responder group(effect size 1.16)compared with the non-responder group(effect size 0.46).Conclusions This study comprehensively evaluated the measurement properties of the DARS using a Chinese population with MDD.Overall,the Chinese version of DARS demonstrates good psychometric properties and has been found to be responsive to change during antidepressant treatment.The DARS is a suitable scale for assessing patient-reported anhedonia in future clinical trials.
基金supported by the National Key R&D Program of China(Grant Nos.2024YFA1408400 and 2021YFA1400401)the National Natural Science Foundation of China(Grant Nos.U22A6005 and 52271238)+2 种基金the China Postdoctoral Science Foundation(Grant No.2025M770186)the Center for Materials Genome,and the Synergetic Extreme Condition User Facility(SECUF)supported by the AI-driven experiments,simulations and model training on the robotic AI-Scientist platform from Chinese Academy of Sciences and the Research Funds for the Central Universities(Grant No.N25ZLE007).
文摘Low-dimensional physics provides profound insights into strongly correlated interactions,leading to enhancedquantum effects and the emergence of exotic quantum states.The Ln_(3)ScBi_(5)family stands out as a chemicallyversatile kagome platform with mixed low-dimensional structural framework and tunable physical properties.Ourresearch initiates with a comprehensive evaluation of the currently known Ln_(3)ScBi_(5)(Ln=La-Nd,Sm)materials,providing a robust methodology for assessing their stability frontiers within this system.Focusing on Pr_(3)ScBi_(5),we investigate the influence of the zigzag chains of quasi-one-dimensional(Q1D)motifs and the distorted kagomelayers of quasi-two-dimensional(Q2D)networks in the mixed-dimensional structure on the intricate magneticground states and unique spin fluctuations.Our study reveals that the noncollinear antiferromagnetic(AFM)moments of Pr^(3+)ions are confined within the Q2D kagome planes,displaying minimal in-plane anisotropy.Incontrast,a strong AFM coupling is observed within the Q1D zigzag chains,significantly constraining spin motion.Notably,magnetic frustration is partially a consequence of coupling to conduction electrons via Ruderman-Kittel-Kasuya-Yosida interaction,highlighting a promising framework for future investigations into mixed-dimensional frustration in Ln_(3)ScBi_(5) systems.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 52272268, 52250308, and 52102338)Beijing National Laboratory for Condensed Matter Physics (Grant No. 2024BNLCMPKF016)Fundamental Research Funding of Universities directly under the Chinese Central Government (Grant No. 2-9-2022-038)。
文摘The interplay between dimensionality and superconductivity is a central theme in understanding the behavior of low-dimensional superconductors. In this work, we investigate the dimensional crossover from quasi-two-dimensional(quasi-2D) to three-dimensional(3D) superconductivity in(Li,Fe)OHFeSe_(1-x)S_(x) single crystals driven by sulfur doping.Through detailed structural, electrical, and magnetic characterization, we identify a critical doping level(x = 0.53) where the system transitions from quasi-2D to 3D superconducting behavior. Reduced superconducting fluctuations and nonFermi liquid behavior near this critical point suggest the presence of competition between intralayer and interlayer pairing mechanisms. Fluctuation conductivity analysis reveals that the coherence length along the c-axis, ζ_(c)(0), and the interlayer coupling strength, Γ, increase significantly at x = 0.53, marking the onset of 3D superconductivity. These findings provide new insights into the role of dimensionality and interlayer coupling in modulating superconducting properties, positioning(Li,Fe)OHFeSe_(1-x)S_(x) as a unique platform for exploring crossover physics in iron-based superconductors.
基金partly supported by Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City(2021JJLH0052)National Natural Science Foundation of China(42274154,42304116)+2 种基金Natural Science Foundation of Heilongjiang Province,China(LH2024D013)Heilongjiang Postdoctoral Fund(LBHZ23103)Hainan Yazhou Bay Science and Technology City Jingying Talent Project(SKJC-JYRC-2024-05)。
文摘The inversion of large sparse matrices poses a major challenge in geophysics,particularly in Bayesian seismic inversion,significantly limiting computational efficiency and practical applicability to largescale datasets.Existing dimensionality reduction methods have achieved partial success in addressing this issue.However,they remain limited in terms of the achievable degree of dimensionality reduction.An incremental deep dimensionality reduction approach is proposed herein to significantly reduce matrix size and is applied to Bayesian linearized inversion(BLI),a stochastic seismic inversion approach that heavily depends on large sparse matrices inversion.The proposed method first employs a linear transformation based on the discrete cosine transform(DCT)to extract the matrix's essential information and eliminate redundant components,forming the foundation of the dimensionality reduction framework.Subsequently,an innovative iterative DCT-based dimensionality reduction process is applied,where the reduction magnitude is carefully calibrated at each iteration to incrementally reduce dimensionality,thereby effectively eliminating matrix redundancy in depth.This process is referred to as the incremental discrete cosine transform(IDCT).Ultimately,a linear IDCT-based reduction operator is constructed and applied to the kernel matrix inversion in BLI,resulting in a more efficient BLI framework.The proposed method was evaluated through synthetic and field data tests and compared with conventional dimensionality reduction methods.The IDCT approach significantly improves the dimensionality reduction efficiency of the core inversion matrix while preserving inversion accuracy,demonstrating prominent advantages in solving Bayesian inverse problems more efficiently.
基金supported by funding from the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)under Germany's Excellence Strategy-EXC 2089/1-390776260(e-conversion)via the International Research Training Group 2022 Alberta/Technical University of Munich International Graduate School for Environmentally Responsible Functional Hybrid Materials(ATUMS).
文摘With the exponential growth of the internet of things,artificial intelligence,and energy-efficient high-volume data digital communications,there is an urgent demand to develop new information technologies with high storage capacity.This needs to address the looming challenge of conventional Von Neumann architecture and Moore's law bottleneck for future data-intensive computing applications.A promising remedy lies in memristors,which offer distinct advantages of scalability,rapid access times,stable data retention,low power consumption,multistate storage capability and fast operation.Among the various materials used for active layers in memristors,low dimensional perovskite semiconductors with structural diversity and superior stability exhibit great potential for next generation memristor applications,leveraging hysteresis characteristics caused by ion migration and defects.In this review the progress of low-dimensional perovskite memory devices is comprehensively summarized.The working mechanism and fundamental processes,including ion migration dynamics,charge carrier transport and electronic resistance that underlies the switching behavior of memristors are discussed.Additionally,the device parameters are analyzed with special focus on the effective methods to improve electrical performance and operational stability.Finally,the challenges and perspective on major hurdles of low-dimensional perovskite memristors in the expansive application domains are provided.
基金supported by the China Postdoctoral Science Foundation(No.2024M764171)the Postdoctoral Research Start-up Funds,China(No.AUGA5710027424)+1 种基金the National Natural Science Foundation of China(No.U2341237)the Development and construction funds for the School of Mechatronics Engineering of HIT,China(No.CBQQ8880103624)。
文摘Gas turbine rotors are complex dynamic systems with high-dimensional,discrete,and multi-source nonlinear coupling characteristics.Significant amounts of resources and time are spent during the process of solving dynamic characteristics.Therefore,it is necessary to design a lowdimensional model that can well reflect the dynamic characteristics of high-dimensional system.To build such a low-dimensional model,this study developed a dimensionality reduction method considering global order energy distribution by modifying the proper orthogonal decomposition theory.First,sensitivity analysis of key dimensionality reduction parameters to the energy distribution was conducted.Then a high-dimensional rotor-bearing system considering the nonlinear stiffness and oil film force was reduced,and the accuracy and the reusability of the low-dimensional model under different operating conditions were examined.Finally,the response results of a multi-disk rotor-bearing test bench were reduced using the proposed method,and spectrum results were then compared experimentally.Numerical and experimental results demonstrate that,during the dimensionality reduction process,the solution period of dynamic response results has the most significant influence on the accuracy of energy preservation.The transient signal in the transformation matrix mainly affects the high-order energy distribution of the rotor system.The larger the proportion of steady-state signals is,the closer the energy tends to accumulate towards lower orders.The low-dimensional rotor model accurately reflects the frequency response characteristics of the original high-dimensional system with an accuracy of up to 98%.The proposed dimensionality reduction method exhibits significant application potential in the dynamic analysis of highdimensional systems coupled with strong nonlinearities under variable operating conditions.
文摘In this paper,the physics informed neural network(PINN)deep learning method is applied to solve two-dimensional nonlocal equations,including the partial reverse space y-nonlocal Mel'nikov equation,the partial reverse space-time nonlocal Mel'nikov equation and the nonlocal twodimensional nonlinear Schr?dinger(NLS)equation.By the PINN method,we successfully derive a data-driven two soliton solution,lump solution and rogue wave solution.Numerical simulation results indicate that the error range between the data-driven solution and the exact solution is relatively small,which verifies the effectiveness of the PINN deep learning method for solving high dimensional nonlocal equations.Moreover,the parameter discovery of the partial reverse space-time nonlocal Mel'nikov equation is analysed in terms of its soliton solution for the first time.
基金Funded by the National Natural Science Foundation of China (No.22203066)the 6th Young Elite Scientist Sponsorship Program by China Association for Science and Technology (No.2020QNRC001)。
文摘The size effects were experimentally investigated and the underlying mechanism was analyzed.The results reveal that,as the specimen size increases,the interconnectivity of macropores slightly decreases.This in turn constrains the diffusion of CO_(2) and moisture in the specimens,resulting in an increase in the discrepancy between the internal and external carbonation degrees.An increase in cement paste thickness simultaneously decreases the quantity,average size,and interconnectivity of macropores,lowering the diffusion efficacy of CO_(2) and moisture and exacerbating the overall heterogeneity in carbonation.Moreover,the gradual blockage of macropores leads to the emergence of localized ‘occluded zones’ with much lower carbonation degree.The reduction in aggregate size significantly alters the average diameter and connectivity of macropores,leading to notable change to overall non-uniformity.This study provides insight into improving the CO_(2) curing effect of pervious concrete products and developing uniform curing methods.
文摘On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.The forum was organised by the China Writers Association and co-organised by China National Publications Import&Export(Group)Corporation.
文摘This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effects of dimensional parameters on the local and whole mechanisms in the design of hybrid humanoid robotic legs.It sequentially optimizes the dimensional parameters of the local and whole mechanism,thereby balancing the motion performance requirements of both.Additionally,it considers the assignment of efficient performance resources between the Local Functional Workspace(LFW)and the Whole Available Workspace(WAW).To facilitate the modeling and optimization process,a local/whole Equivalent Configuration Framework(ECF)is introduced.By decoupling the hybrid mechanism into a whole mechanism and multiple local mechanisms,the ECF enhances the efficiency of design,modeling,and performance evaluation.Prototype experiments are conducted to validate the effectiveness of LDSOS.This research provides an effective configuration framework for humanoid robotic leg design,establishing a theoretical and practical foundation for future optimized designs of humanoid robotic legs and pioneering novel approaches to the design of complex hybrid humanoid robotic legs.
