A bimorph piezoelectric beam with periodically variable cross-sections is used for the vibration energy harvesting. The effects of two geometrical parameters on the first band gap of this periodic beam are investigate...A bimorph piezoelectric beam with periodically variable cross-sections is used for the vibration energy harvesting. The effects of two geometrical parameters on the first band gap of this periodic beam are investigated by the generalized differential quadrature rule （GDQR） method. The GDQR method is also used to calculate the forced vibration response of the beam and voltage of each piezoelectric layer when the beam is subject to a sinusoidal base excitation. Results obtained from the analytical method are compared with those obtained from the finite element simulation with ANSYS, and good agreement is found. The voltage output of this periodic beam over its first band gap is calculated and compared with the voltage output of the uniform piezoelectric beam. It is concluded that this periodic beam has three advantages over the uniform piezoelectric beam, i.e., generating more voltage outputs over a wide frequency range, absorbing vibration, and being less weight.展开更多
The scroll expander,as the core component of the micro-compressed air energy storage and power generation system,directly affects the output efficiency of the system.Meanwhile,the scroll profile plays a central role i...The scroll expander,as the core component of the micro-compressed air energy storage and power generation system,directly affects the output efficiency of the system.Meanwhile,the scroll profile plays a central role in determining the output performance of the scroll expander.In this study,in order to investigate the output characteristics of a variable cross-section scroll expander,numerical simulation and experimental studies were con-ducted by using Computational Fluid Dynamics(CFD)methods and dynamic mesh techniques.The impact of critical parameters on the output performance of the scroll expander was analyzed through the utilization of the control variable method.It is found that increasing the inlet pressure and temperature within a certain range can improve the output power of the scroll expander.However,the increase in temperature and meshing clearance leads to a decline in the overall output performance of the scroll expander,leading to a decrease in volumetric efficiency by 8.43%and 12.79%,respectively.The experiments demonstrate that under equal inlet pressure conditions,increasing the inlet temperature elevates both the rotational speed and torque output of the scroll expander.Specifically,compared to operating at normal temperatures,the output torque increases by 21.8%under high-temperature conditions.However,the rate of speed and torque variation decreases as a consequence of enlarged meshing clearance,resulting in increased internal leakage and reduction in isentropic efficiency.展开更多
An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of t...An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.展开更多
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponen...We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.展开更多
Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design o...Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
With the application of 2.5D Woven Variable Thickness Composites(2.5DWVTC)in aviation and other fields,the issue of strength failure in this composite type has become a focal point.First,a three-step modeling approach...With the application of 2.5D Woven Variable Thickness Composites(2.5DWVTC)in aviation and other fields,the issue of strength failure in this composite type has become a focal point.First,a three-step modeling approach is proposed to rapidly construct full-scale meso-finite element models for Outer Reduction Yarn Woven Composites(ORYWC)and Inner Reduction Yarn Woven Composites(IRYWC).Then,six independent damage variables are identified:yarn fiber tension/compression,yarn matrix tension/compression,and resin matrix tension/compression.These variables are utilized to establish the constitutive equation of woven composites,considering the coupling effects of microscopic damage.Finally,combined with the Hashin failure criterion and von Mises failure criterion,the strength prediction model is implemented in ANSYS using APDL language to simulate the strength failure process of 2.5DWVTC.The results show that the predicted stiffness and strength values of various parts of ORYWC and IRYWC are in good agreement with the relevant test results.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
Cold seeps are oases for biological communities on the sea floor around hydrocarbon emission pathways.Microbial utilization of methane and other hydrocarbons yield products that fuel rich chemosynthetic communities at...Cold seeps are oases for biological communities on the sea floor around hydrocarbon emission pathways.Microbial utilization of methane and other hydrocarbons yield products that fuel rich chemosynthetic communities at these sites.One such site in the cold seep ecosystem of Krishna-Godavari basin(K-G basin)along the east coast of India,discovered in Feb 2018 at a depth of 1800 m was assessed for its bacterial diversity.The seep bacterial communities were dominated by phylum Proteobacteria(57%),Firmicutes(16%)and unclassified species belonging to the family Helicobacteriaceae.The surface sediments of the seep had maximum OTUs(operational taxonomic units)(2.27×10^(3))with a Shannon alpha diversity index of 8.06.In general,environmental parameters like total organic carbon(p<0.01),sulfate(p<0.001),sulfide(p<0.05)and methane(p<0.01)were responsible for shaping the bacterial community of the cold seep ecosystem in the K-G Basin.Environmental parameters play a significant role in changing the bacterial diversity richness between different cold seep environments in the oceans.展开更多
This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant trunk.Specifically,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its stre...This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant trunk.Specifically,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its strength.The design features two concentric parts:inner pneumatically actuated bellows and an outer tendon-driven helical spring.The tendons control the omnidirectional bending of the manipulator,while the fusion of the pneumatic bellows with the tendon-driven spring results in an antagonistic actuation mechanism that provides the manipulator with variable stiffness and extensibility.This paper presents a new design for extensible manipulator and analyzes its stiffness and motion characteristics.Experimental results are consistent with theoretical analysis,thereby demonstrating the validity of the theoretical approach and the versatile practical mechanical properties of the continuum manipulator.The impressive extensibility and variable stiffness of the manipulator were further demonstrated by performing a pin-hole assembly task.展开更多
Predictive control(PC)is an advanced control algorithm,which is widely used in industrial process control.Among them,model-based predictive control(MPC)is an important branch of predictive control.Its basic principle ...Predictive control(PC)is an advanced control algorithm,which is widely used in industrial process control.Among them,model-based predictive control(MPC)is an important branch of predictive control.Its basic principle is to use the system model to predict future behavior and determine the current control action by optimizing the objective function.Based on the algorithm combined with three different sections using deep learning technology to identify vehicles and output the optimal speed limit,to achieve the effect of traffic flow optimization.展开更多
Application of variable speed limits(VSL)is gradually increasingly implemented especially on highways.As a result of conducted studies and implementations,it is observed that the variable speed limits have reduced the...Application of variable speed limits(VSL)is gradually increasingly implemented especially on highways.As a result of conducted studies and implementations,it is observed that the variable speed limits have reduced the number of car accidents as well as proved positive results in terms of delays and environmental factors.Purpose of this study is to develop an algorithm for VSL application that is considered to be applied on Istanbul D100 highway and to assess the effects of application.Algorithm that is developed for VSL is a different VSL algorithm and compared with the constant speed system.According to obtained results,when the proposed system is compared to current system,it is observed that the number of delays and average stops are reduced%30 and%40 respectively and also emissions reduced at the rate of%12.展开更多
In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This...In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.展开更多
We prove the boundedness of the parametric Lusin's S functionμ_(S)^(?)(f)and Littlewood-Paley's g_(λ)^(*)-funtionμ_(λ),^(*,?)(f)on grand Herz-Morrey spaces with variable exponents.Additionally,we establish...We prove the boundedness of the parametric Lusin's S functionμ_(S)^(?)(f)and Littlewood-Paley's g_(λ)^(*)-funtionμ_(λ),^(*,?)(f)on grand Herz-Morrey spaces with variable exponents.Additionally,we establish the boundedness of higher-order commutators ofμ_(S)^(?)andμ_(λ),^(*,?)with BMO functions applying some properties of variable exponents and generalized BMO norms.展开更多
This work develops a protein imprinted nanosphere with varied recognition specificity for bovine serum albumin(BSA)and lysozyme(Lyz)under different UV light through a gradient dual crosslinked imprinting strategy(i.e....This work develops a protein imprinted nanosphere with varied recognition specificity for bovine serum albumin(BSA)and lysozyme(Lyz)under different UV light through a gradient dual crosslinked imprinting strategy(i.e.,covalent crosslinking and dynamic reversible crosslinking).The imprinting cavities are initially constructed using irreversible covalent crosslinking to specifically recognize BSA,and then the coumarin residues in the imprinting cavities are crosslinked under 365 nm UV light to further imprint Lyz,because Lyz has smaller size than BSA.Since the photo-crosslinking of coumarin is a reversible reaction,the imprinting cavities of Lyz can be de-crosslinked under 254 nm UV light and restore the imprinting cavities of BSA.Moreover,the N-isopropyl acrylamide(NIPAM)and pyrrolidine residues copolymerized in the polymeric surface of the nanospheres are temperature-and p H-responsive respectively.Therefore,the protein rebinding and release behaviors of the nanospheres are controlled by external temperature and p H.As a result,the materials can selectively separate BSA from real bovine whole blood and Lyz from egg white under different UV light.This study may provide a new strategy for construction of protein imprinted materials with tunable specificity for different proteins.展开更多
In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image blurring.Conventional deblurring m...In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image blurring.Conventional deblurring methods applied to PSP images often suffer from limited accuracy and require extensive computational resources.To address these issues,this study proposes a deep learning-based approach tailored for PSP image deblurring.Considering that PSP applications primarily involve the accurate pressure measurements of complex geometries,the images captured under such conditions exhibit distinctive non-uniform motion blur,presenting challenges for standard deep learning models utilizing convolutional or attention-based techniques.In this paper,we introduce a novel deblurring architecture featuring multiple DAAM(Deformable Ack Attention Module).These modules provide enhanced flexibility for end-to-end deblurring,leveraging irregular convolution operations for efficient feature extraction while employing attention mechanisms interpreted as multiple 1×1 convolutions,subsequently reassembled to enhance performance.Furthermore,we incorporate a RSC(Residual Shortcut Convolution)module for initial feature processing,aimed at reducing redundant computations and improving the learning capacity for representative shallow features.To preserve critical spatial information during upsampling and downsampling,we replace conventional convolutions with wt(Haar wavelet downsampling)and dysample(Upsampling by Dynamic Sampling).This modification significantly enhances high-precision image reconstruction.By integrating these advanced modules within an encoder-decoder framework,we present the DFDNet(Deformable Fusion Deblurring Network)for image blur removal,providing robust technical support for subsequent PSP data analysis.Experimental evaluations on the FY dataset demonstrate the superior performance of our model,achieving competitive results on the GOPRO and HIDE datasets.展开更多
This paper deals with a semilinear parabolic problem involving variable coefficients and nonlinear memory boundary conditions.We give the blow-up criteria for all nonnegative nontrivial solutions,which rely on the beh...This paper deals with a semilinear parabolic problem involving variable coefficients and nonlinear memory boundary conditions.We give the blow-up criteria for all nonnegative nontrivial solutions,which rely on the behavior of the coefficients when time variable tends to positive infinity.Moreover,the global existence of solutions are discussed for non-positive exponents.展开更多
Casting experiments and macro-micro numerical simulations were conducted to examine the microstructure characteristics of K439B nickel-based superalloy casting with varying cross-sections during the gravity investment...Casting experiments and macro-micro numerical simulations were conducted to examine the microstructure characteristics of K439B nickel-based superalloy casting with varying cross-sections during the gravity investment casting process.Firstly,microstructure analysis was conducted on the casting using scanning electron microscopy(SEM)and electron backscatter diffraction(EBSD).Subsequently,calculation of the phase diagram and differential scanning calorimetry(DSC)tests were conducted to determine the macro-micro simulation parameters of the K439B alloy,and the cellular automaton finite element(CAFE)method was employed to develop macro-micro modeling of K439B nickel-based superalloy casting with varying cross-sections.The experimental results revealed that the ratio of the average grain area increased from the edge to the center of the sections as the ratio of the cross-sectional area increased.The simulation results indicated that the average grain area increased from 0.885 to 0.956 mm^(2)as the ratio of the cross-sections increased from 6꞉1 to 12꞉1.The experiment and simulation results showed that the grain size became more heterogeneous and the grain shape became more irregular with an increase in the ratio of the cross-sectional area of the casting.CAFE modeling was an effective method to simulate the microstructure evolution of the K439B alloy and ensure the accuracy of the simulation.展开更多
This study explores the bioconvective behavior of a Reiner-Rivlin nanofluid,accounting for spatially varying thermal properties.The flow is considered over a porous,stretching surface with mass suction effects incorpo...This study explores the bioconvective behavior of a Reiner-Rivlin nanofluid,accounting for spatially varying thermal properties.The flow is considered over a porous,stretching surface with mass suction effects incorporated into the transport analysis.The Reiner-Rivlin nanofluid model includes variable thermal conductivity,mass diffusivity,and motile microorganism density to accurately reflect realistic biological conditions.Radiative heat transfer and internal heat generation are considered in the thermal energy equation,while the Cattaneo-Christov theory is employed to model non-Fourier heat and mass fluxes.The governing equations are non-dimensionalized to reduce complexity,and a numerical solution is obtained using a shooting method.Parametric studies are conducted to examine the influence of key dimensionless parameters on velocity,temperature,concentration,and motile microorganism profiles.The results are presented through a series of graphs,offering insight into the dynamic interplay between physical mechanisms affecting heat and mass transfer in non-Newtonian bioconvective nanofluid systems.展开更多
文摘A bimorph piezoelectric beam with periodically variable cross-sections is used for the vibration energy harvesting. The effects of two geometrical parameters on the first band gap of this periodic beam are investigated by the generalized differential quadrature rule （GDQR） method. The GDQR method is also used to calculate the forced vibration response of the beam and voltage of each piezoelectric layer when the beam is subject to a sinusoidal base excitation. Results obtained from the analytical method are compared with those obtained from the finite element simulation with ANSYS, and good agreement is found. The voltage output of this periodic beam over its first band gap is calculated and compared with the voltage output of the uniform piezoelectric beam. It is concluded that this periodic beam has three advantages over the uniform piezoelectric beam, i.e., generating more voltage outputs over a wide frequency range, absorbing vibration, and being less weight.
基金funded by the National Key Research and Development Program of China(No.2024YFE0208100).
文摘The scroll expander,as the core component of the micro-compressed air energy storage and power generation system,directly affects the output efficiency of the system.Meanwhile,the scroll profile plays a central role in determining the output performance of the scroll expander.In this study,in order to investigate the output characteristics of a variable cross-section scroll expander,numerical simulation and experimental studies were con-ducted by using Computational Fluid Dynamics(CFD)methods and dynamic mesh techniques.The impact of critical parameters on the output performance of the scroll expander was analyzed through the utilization of the control variable method.It is found that increasing the inlet pressure and temperature within a certain range can improve the output power of the scroll expander.However,the increase in temperature and meshing clearance leads to a decline in the overall output performance of the scroll expander,leading to a decrease in volumetric efficiency by 8.43%and 12.79%,respectively.The experiments demonstrate that under equal inlet pressure conditions,increasing the inlet temperature elevates both the rotational speed and torque output of the scroll expander.Specifically,compared to operating at normal temperatures,the output torque increases by 21.8%under high-temperature conditions.However,the rate of speed and torque variation decreases as a consequence of enlarged meshing clearance,resulting in increased internal leakage and reduction in isentropic efficiency.
基金supported by the National Natural Science Foundation of China(No.51905123)Major Scientific and Technological Innovation Program of Shandong Province,China(Nos.2020CXGC010303,2022ZLGX04)Key R&D Programme of Shandong Province,China(No.2022JMRH0308).
文摘An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.
基金supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
基金supported by the National Natural Science Foundation of China(Grant No.11971486)。
文摘We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.
基金supports for this research were provided by the National Natural Science Foundation of China(No.12272301,12002278,U1906233)the Guangdong Basic and Applied Basic Research Foundation,China(Nos.2023A1515011970,2024A1515010256)+1 种基金the Dalian City Supports Innovation and Entrepreneurship Projects for High-Level Talents,China(2021RD16)the Key R&D Project of CSCEC,China(No.CSCEC-2020-Z-4).
文摘Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by National Science and Technology Major Project,China(No.2017-IV-0007-0044)National Natural Science Foundation of China(No.52175142),National Natural Science Foundation of China(No.52305170)Natural Science Foundation of Sichuan Province,China(No.2022NSFSC1885)。
文摘With the application of 2.5D Woven Variable Thickness Composites(2.5DWVTC)in aviation and other fields,the issue of strength failure in this composite type has become a focal point.First,a three-step modeling approach is proposed to rapidly construct full-scale meso-finite element models for Outer Reduction Yarn Woven Composites(ORYWC)and Inner Reduction Yarn Woven Composites(IRYWC).Then,six independent damage variables are identified:yarn fiber tension/compression,yarn matrix tension/compression,and resin matrix tension/compression.These variables are utilized to establish the constitutive equation of woven composites,considering the coupling effects of microscopic damage.Finally,combined with the Hashin failure criterion and von Mises failure criterion,the strength prediction model is implemented in ANSYS using APDL language to simulate the strength failure process of 2.5DWVTC.The results show that the predicted stiffness and strength values of various parts of ORYWC and IRYWC are in good agreement with the relevant test results.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
文摘Cold seeps are oases for biological communities on the sea floor around hydrocarbon emission pathways.Microbial utilization of methane and other hydrocarbons yield products that fuel rich chemosynthetic communities at these sites.One such site in the cold seep ecosystem of Krishna-Godavari basin(K-G basin)along the east coast of India,discovered in Feb 2018 at a depth of 1800 m was assessed for its bacterial diversity.The seep bacterial communities were dominated by phylum Proteobacteria(57%),Firmicutes(16%)and unclassified species belonging to the family Helicobacteriaceae.The surface sediments of the seep had maximum OTUs(operational taxonomic units)(2.27×10^(3))with a Shannon alpha diversity index of 8.06.In general,environmental parameters like total organic carbon(p<0.01),sulfate(p<0.001),sulfide(p<0.05)and methane(p<0.01)were responsible for shaping the bacterial community of the cold seep ecosystem in the K-G Basin.Environmental parameters play a significant role in changing the bacterial diversity richness between different cold seep environments in the oceans.
基金supported by the National Key R&D Program of China(No.2018YFB1305400)the Major Research Plan of the National Natural Science Foundation of China(No.92048301)+1 种基金the National Natural Science Foundation of China(No.52025054)the Joint Research Fund between the National Natural Science Foundation of China(NSFC)and Shen Zhen(No.U1713201).
文摘This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant trunk.Specifically,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its strength.The design features two concentric parts:inner pneumatically actuated bellows and an outer tendon-driven helical spring.The tendons control the omnidirectional bending of the manipulator,while the fusion of the pneumatic bellows with the tendon-driven spring results in an antagonistic actuation mechanism that provides the manipulator with variable stiffness and extensibility.This paper presents a new design for extensible manipulator and analyzes its stiffness and motion characteristics.Experimental results are consistent with theoretical analysis,thereby demonstrating the validity of the theoretical approach and the versatile practical mechanical properties of the continuum manipulator.The impressive extensibility and variable stiffness of the manipulator were further demonstrated by performing a pin-hole assembly task.
文摘Predictive control(PC)is an advanced control algorithm,which is widely used in industrial process control.Among them,model-based predictive control(MPC)is an important branch of predictive control.Its basic principle is to use the system model to predict future behavior and determine the current control action by optimizing the objective function.Based on the algorithm combined with three different sections using deep learning technology to identify vehicles and output the optimal speed limit,to achieve the effect of traffic flow optimization.
文摘Application of variable speed limits(VSL)is gradually increasingly implemented especially on highways.As a result of conducted studies and implementations,it is observed that the variable speed limits have reduced the number of car accidents as well as proved positive results in terms of delays and environmental factors.Purpose of this study is to develop an algorithm for VSL application that is considered to be applied on Istanbul D100 highway and to assess the effects of application.Algorithm that is developed for VSL is a different VSL algorithm and compared with the constant speed system.According to obtained results,when the proposed system is compared to current system,it is observed that the number of delays and average stops are reduced%30 and%40 respectively and also emissions reduced at the rate of%12.
基金Supported by the Natural Science Foundation of Fujian Province(2022J011177,2024J01903)the Key Project of Fujian Provincial Education Department(JZ230054)。
文摘In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.
基金Supported by the Natural Science Research Project of Anhui Educational Committee(Grant No.2024AH050129)。
文摘We prove the boundedness of the parametric Lusin's S functionμ_(S)^(?)(f)and Littlewood-Paley's g_(λ)^(*)-funtionμ_(λ),^(*,?)(f)on grand Herz-Morrey spaces with variable exponents.Additionally,we establish the boundedness of higher-order commutators ofμ_(S)^(?)andμ_(λ),^(*,?)with BMO functions applying some properties of variable exponents and generalized BMO norms.
基金financial support from the National Natural Science Foundation of China(No.22275148)National Key R&D Program of China(No.2018YFB1900201)for Qiuyu Zhang+2 种基金the National Natural Science Foundation of China(No.22271232)Fundamental Research Funds for the Central Universities(No.D5000230114)for Shixin Fathe Fundamental Research Funds for the Central Universities(No.D5000220339)for Qing Liu。
文摘This work develops a protein imprinted nanosphere with varied recognition specificity for bovine serum albumin(BSA)and lysozyme(Lyz)under different UV light through a gradient dual crosslinked imprinting strategy(i.e.,covalent crosslinking and dynamic reversible crosslinking).The imprinting cavities are initially constructed using irreversible covalent crosslinking to specifically recognize BSA,and then the coumarin residues in the imprinting cavities are crosslinked under 365 nm UV light to further imprint Lyz,because Lyz has smaller size than BSA.Since the photo-crosslinking of coumarin is a reversible reaction,the imprinting cavities of Lyz can be de-crosslinked under 254 nm UV light and restore the imprinting cavities of BSA.Moreover,the N-isopropyl acrylamide(NIPAM)and pyrrolidine residues copolymerized in the polymeric surface of the nanospheres are temperature-and p H-responsive respectively.Therefore,the protein rebinding and release behaviors of the nanospheres are controlled by external temperature and p H.As a result,the materials can selectively separate BSA from real bovine whole blood and Lyz from egg white under different UV light.This study may provide a new strategy for construction of protein imprinted materials with tunable specificity for different proteins.
基金supported by the National Natural Science Foundation of China(No.12202476).
文摘In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image blurring.Conventional deblurring methods applied to PSP images often suffer from limited accuracy and require extensive computational resources.To address these issues,this study proposes a deep learning-based approach tailored for PSP image deblurring.Considering that PSP applications primarily involve the accurate pressure measurements of complex geometries,the images captured under such conditions exhibit distinctive non-uniform motion blur,presenting challenges for standard deep learning models utilizing convolutional or attention-based techniques.In this paper,we introduce a novel deblurring architecture featuring multiple DAAM(Deformable Ack Attention Module).These modules provide enhanced flexibility for end-to-end deblurring,leveraging irregular convolution operations for efficient feature extraction while employing attention mechanisms interpreted as multiple 1×1 convolutions,subsequently reassembled to enhance performance.Furthermore,we incorporate a RSC(Residual Shortcut Convolution)module for initial feature processing,aimed at reducing redundant computations and improving the learning capacity for representative shallow features.To preserve critical spatial information during upsampling and downsampling,we replace conventional convolutions with wt(Haar wavelet downsampling)and dysample(Upsampling by Dynamic Sampling).This modification significantly enhances high-precision image reconstruction.By integrating these advanced modules within an encoder-decoder framework,we present the DFDNet(Deformable Fusion Deblurring Network)for image blur removal,providing robust technical support for subsequent PSP data analysis.Experimental evaluations on the FY dataset demonstrate the superior performance of our model,achieving competitive results on the GOPRO and HIDE datasets.
基金Supported by Shandong Provincial Natural Science Foundation(Grant Nos.ZR2021MA003 and ZR2020MA020).
文摘This paper deals with a semilinear parabolic problem involving variable coefficients and nonlinear memory boundary conditions.We give the blow-up criteria for all nonnegative nontrivial solutions,which rely on the behavior of the coefficients when time variable tends to positive infinity.Moreover,the global existence of solutions are discussed for non-positive exponents.
基金supported by the National Science and Technology Major Project of China(No.J2019-VI-0004-0117)。
文摘Casting experiments and macro-micro numerical simulations were conducted to examine the microstructure characteristics of K439B nickel-based superalloy casting with varying cross-sections during the gravity investment casting process.Firstly,microstructure analysis was conducted on the casting using scanning electron microscopy(SEM)and electron backscatter diffraction(EBSD).Subsequently,calculation of the phase diagram and differential scanning calorimetry(DSC)tests were conducted to determine the macro-micro simulation parameters of the K439B alloy,and the cellular automaton finite element(CAFE)method was employed to develop macro-micro modeling of K439B nickel-based superalloy casting with varying cross-sections.The experimental results revealed that the ratio of the average grain area increased from the edge to the center of the sections as the ratio of the cross-sectional area increased.The simulation results indicated that the average grain area increased from 0.885 to 0.956 mm^(2)as the ratio of the cross-sections increased from 6꞉1 to 12꞉1.The experiment and simulation results showed that the grain size became more heterogeneous and the grain shape became more irregular with an increase in the ratio of the cross-sectional area of the casting.CAFE modeling was an effective method to simulate the microstructure evolution of the K439B alloy and ensure the accuracy of the simulation.
文摘This study explores the bioconvective behavior of a Reiner-Rivlin nanofluid,accounting for spatially varying thermal properties.The flow is considered over a porous,stretching surface with mass suction effects incorporated into the transport analysis.The Reiner-Rivlin nanofluid model includes variable thermal conductivity,mass diffusivity,and motile microorganism density to accurately reflect realistic biological conditions.Radiative heat transfer and internal heat generation are considered in the thermal energy equation,while the Cattaneo-Christov theory is employed to model non-Fourier heat and mass fluxes.The governing equations are non-dimensionalized to reduce complexity,and a numerical solution is obtained using a shooting method.Parametric studies are conducted to examine the influence of key dimensionless parameters on velocity,temperature,concentration,and motile microorganism profiles.The results are presented through a series of graphs,offering insight into the dynamic interplay between physical mechanisms affecting heat and mass transfer in non-Newtonian bioconvective nanofluid systems.
