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
Hierarchical micro/nanograting structures have attracted increasing attention owing to their significant applications in the fields of structural coloring,anti-counterfeiting,and decoration.Thus,the fabrication of hie...Hierarchical micro/nanograting structures have attracted increasing attention owing to their significant applications in the fields of structural coloring,anti-counterfeiting,and decoration.Thus,the fabrication of hierarchical micro/nanograting structures is important for these applications.In this study,a strategy for machining hierarchical micro/nanograting structures is developed by controlling the tool movement trajectory.A coupling Euler-Lagrange finite element model is established to simulate the machining process.The effect of the machining methods on the nanograting formation is demonstrated,and a suitable machining method for reducing the cutting force is obtained.The height of the nanograting decreases with an increase in the tool edge radius.Furthermore,optical variable devices(OVDs)are machined using an array overlap machining approach.Coding schemes for the parallel column unit crossover and column unit in the groove crossover are designed to achieve high-quality machining of OVDs.The coloring of the logo of the Harbin Institute of Technology and the logo of the centennial anniversary of the Harbin Institute of Technology on the surface of metal samples,such as aluminum alloys,is realized.The findings of this study provide a method for the fabrication of hierarchical micro/nanograting structures that can be used to prepare OVDs.展开更多
Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by la...Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by large elevation gradient and different vegetation zones with complex processes of water and energy exchange.The quality of ET from optical remote sensing is constrained by cloud cover which is common in the NRB in the monsoon seasons.To understand factors controlling the spatial-temporal heterogeneity of ET in NRB,we employed the Variable Infiltration Capacity(VIC)hydrological model by parameter optimization with support of quality controlled remote sensing ET product and observed river runoff series in the river.The modeled ET has increased during 1984-2018,which might be one of the reasons for the runoff decrease but precipitation increase in the same period.ET increase and runoff decrease tended to be quicker within altitudinal band of 2000-4000 m than in other areas in NRB.We observed that ET variation in different climatic zones were controlled by different factors.ET is generally positively correlated with precipitation,temperature,and shortwave radiation but negatively with relative humidity.In the Tundra Climate(Et)zone in the upper reach of NRB,ET is controlled by precipitation,while it is controlled by shortwave radiation in the snow climate with dry winter(Dw)zone.ET increase is influenced by the increase of temperature,wind speed,and shortwave radiation in the middle and downstream of NRB with warm temperate climate,fully humid(Cf)and warm temperate climate with dry winter(Cw).展开更多
Obtaining a reasonable mold flow field for casting slabs with different sections is challenging by solely modifying the nozzle structure and continuous casting process. Research was conducted on small-sectioned (1000 ...Obtaining a reasonable mold flow field for casting slabs with different sections is challenging by solely modifying the nozzle structure and continuous casting process. Research was conducted on small-sectioned (1000 mm × 220 mm) and large-sectioned (3250 mm × 220 mm) slab continuous casting molds with a fixed nozzle form (concave bottom nozzle, side port inclination angle of 0°). A three-dimensional electromagnetic model is established to analyze the current frequency, installation position, and rotation angle under the active deceleration mode and acceleration mode. The results indicate that, regardless of the deceleration mode for small-sectioned slabs or the acceleration mode for large-sectioned slabs, the magnetic flux density in the mold decreases with increasing current frequency. However, the maximum electromagnetic force initially increases and then decreases, suggesting that both electromagnetic modes have the same optimal current frequency (3 Hz). The optimal mechanical design parameters for the deceleration mode of electromagnetic variable flow device (EM-VFD) with the small-sectioned slab are as follows: installation position Z = 115 mm and rotation angle of 15°, ensuring that the maximum electromagnetic force is applied to the nozzle jet area. For the acceleration mode of the large-sectioned slab EM-VFD, the optimal mechanical design parameters are as follows: Z = 115 mm and rotation angle of 10°, ensuring that the maximum electromagnetic force is applied to 1/4 and 3/4 areas of the wide face. These findings indicate that the new electromagnetic variable flow device, which can actively adjust the flow rate and angle of the steel even under given working conditions, provides the possibility for reasonable control of the mold’s flow field.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
Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked dec...Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked decline in runoff,posing challenges to the sustainable development of regional water resources and ecosystem stability.To enhance the understanding of runoff dynamics in the basin,we selected the Dahei River Basin,a representative tributary in the upper reaches of the Yellow River Basin as the study area.A comprehensive analysis of runoff trends and contributing factors was conducted using the data on hydrology,meteorology,and water resource development and utilization.Abrupt change years of runoff series in the Dahei River Basin was identified by the Mann-Kendall and Pettitt tests:1999 at Dianshang,Qixiaying,and Meidai hydrological stations and 1995 at Sanliang hydrological station.Through hydrological simulations based on the Variable Infiltration Capacity(VIC)model,we quantified the factors driving runoff evolution in the Dahei River Basin,with climate change contributing 9.92%–22.91%and human activities contributing 77.09%–90.08%.The Budyko hypothesis method provided similar results,with climate change contributing 13.06%–20.89%and human activities contributing 79.11%–86.94%.Both methods indicated that human activities,particularly water consumption,were dominant factors in the runoff variations of the Dahei River Basin.The integration of hydrological modeling with attribution analysis offers valuable insights into runoff evolution,facilitating adaptive strategies to mitigate water scarcity in arid and semi-arid areas.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
随着全球气候变化的加剧,其对流域水文过程的影响日益显著。湘江流域作为中国南方重要的水资源区域,其径流变化不仅直接影响区域水资源的可持续利用,还对生态安全和社会经济发展具有深远意义。本研究基于VIC (Variable Infiltration Cap...随着全球气候变化的加剧,其对流域水文过程的影响日益显著。湘江流域作为中国南方重要的水资源区域,其径流变化不仅直接影响区域水资源的可持续利用,还对生态安全和社会经济发展具有深远意义。本研究基于VIC (Variable Infiltration Capacity)水文模型,结合第六次国际耦合模式比较计划(CMIP6)气候模式数据,系统预测未来变化情况。研究结果显示,湘江流域未来时期(2020~2099年)的气候及径流变化在时间和空间尺度上均表现出显著特征。年际尺度上,在SSP2-4.5 (中等排放情景)和SSP5-8.5 (高排放情景)下,未来时期降水量和平均温度均呈现增加趋势,且高排放情景下增幅更为显著;径流量在两个情景下均显著增加,中等排放情景下增幅更大。年代尺度上,2020s、2030s和2060s为降水与径流枯水期,2040s、2050s、2070s、2080s和2090s则为丰水期。SSP2-4.5情景下极端降水和径流事件可能集中在2040s、2080s和2090s,而SSP5-8.5情景下则可能出现在2040s和2070s;径流量时间分布与降水变化高度一致,进一步验证了降水是径流变化的主导驱动因子,湘江流域未来径流变化主要是由降水引起。这些研究为未来流域水资源管理和自然灾害预防提供了重要参考。With the intensification of global climate change, its impacts on hydrological processes in river basins are becoming more and more significant. As an important water resource region in southern China, the runoff changes in the Xiangjiang River Basin not only directly affect the sustainable utilization of regional water resources, but also have far-reaching significance on ecological security and socio-economic development. This study is based on the VIC (Variable Infiltration Capacity) hydrological model, combined with the climate model data from the Sixth International Coupled Model Intercomparison Program (CMIP6), to systematically predict future changes. The results show that the climate and runoff changes in the Xiangjiang River Basin in the future period (2020~2099) exhibit significant features at both temporal and spatial scales. At the interannual scale, both precipitation and mean temperature show increasing trends in the future period under SSP2-4.5 (medium emission scenario) and SSP5-8.5 (high emission scenario), and the increase is more significant under the high emission scenario;runoff increases significantly under both scenarios, and the increase is greater under the medium emission scenario. On the chronological scale, the 2020s, 2030s, and 2060s are dry periods for precipitation and runoff, and the 2040s, 2050s, 2070s, 2080s, and 2090s are abundant periods. Extreme precipitation and runoff events are likely to be concentrated in the 2040s, 2080s, and 2090s under the SSP2-4.5 scenario, and the 2040s, 2080s, and 2090s under the SSP5-8.5 scenario 2040s and 2070s. The temporal distribution of runoff is highly consistent with precipitation changes, which further verifies that precipitation is the dominant driving factor of runoff changes, and future runoff changes in the Xiangjiang River Basin are mainly caused by precipitation. These studies provide important references for future water resource management and natural disaster prevention in the basin.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
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Supported by National Natural Science Foundation of China(Grant Nos.52035004,52105434).
文摘Hierarchical micro/nanograting structures have attracted increasing attention owing to their significant applications in the fields of structural coloring,anti-counterfeiting,and decoration.Thus,the fabrication of hierarchical micro/nanograting structures is important for these applications.In this study,a strategy for machining hierarchical micro/nanograting structures is developed by controlling the tool movement trajectory.A coupling Euler-Lagrange finite element model is established to simulate the machining process.The effect of the machining methods on the nanograting formation is demonstrated,and a suitable machining method for reducing the cutting force is obtained.The height of the nanograting decreases with an increase in the tool edge radius.Furthermore,optical variable devices(OVDs)are machined using an array overlap machining approach.Coding schemes for the parallel column unit crossover and column unit in the groove crossover are designed to achieve high-quality machining of OVDs.The coloring of the logo of the Harbin Institute of Technology and the logo of the centennial anniversary of the Harbin Institute of Technology on the surface of metal samples,such as aluminum alloys,is realized.The findings of this study provide a method for the fabrication of hierarchical micro/nanograting structures that can be used to prepare OVDs.
基金supported by the National Natural Science Foundation of China(42171129)the second Tibetan Plateau Scientific Expedition and Research(2019QZKK0208)Yunnan University Talent Introduction Research Project(YJRC3201702)。
文摘Land surface evapotranspiration(ET)is a critical component in the hydrological cycle but has not well been understood in data-scarce areas especially in river basins,like Nujiang River(NRB)which is characterized by large elevation gradient and different vegetation zones with complex processes of water and energy exchange.The quality of ET from optical remote sensing is constrained by cloud cover which is common in the NRB in the monsoon seasons.To understand factors controlling the spatial-temporal heterogeneity of ET in NRB,we employed the Variable Infiltration Capacity(VIC)hydrological model by parameter optimization with support of quality controlled remote sensing ET product and observed river runoff series in the river.The modeled ET has increased during 1984-2018,which might be one of the reasons for the runoff decrease but precipitation increase in the same period.ET increase and runoff decrease tended to be quicker within altitudinal band of 2000-4000 m than in other areas in NRB.We observed that ET variation in different climatic zones were controlled by different factors.ET is generally positively correlated with precipitation,temperature,and shortwave radiation but negatively with relative humidity.In the Tundra Climate(Et)zone in the upper reach of NRB,ET is controlled by precipitation,while it is controlled by shortwave radiation in the snow climate with dry winter(Dw)zone.ET increase is influenced by the increase of temperature,wind speed,and shortwave radiation in the middle and downstream of NRB with warm temperate climate,fully humid(Cf)and warm temperate climate with dry winter(Cw).
基金supported by the Science and Technology Talent Support Project of Hunan province in China(Grant No.2023TJ-Z14).
文摘Obtaining a reasonable mold flow field for casting slabs with different sections is challenging by solely modifying the nozzle structure and continuous casting process. Research was conducted on small-sectioned (1000 mm × 220 mm) and large-sectioned (3250 mm × 220 mm) slab continuous casting molds with a fixed nozzle form (concave bottom nozzle, side port inclination angle of 0°). A three-dimensional electromagnetic model is established to analyze the current frequency, installation position, and rotation angle under the active deceleration mode and acceleration mode. The results indicate that, regardless of the deceleration mode for small-sectioned slabs or the acceleration mode for large-sectioned slabs, the magnetic flux density in the mold decreases with increasing current frequency. However, the maximum electromagnetic force initially increases and then decreases, suggesting that both electromagnetic modes have the same optimal current frequency (3 Hz). The optimal mechanical design parameters for the deceleration mode of electromagnetic variable flow device (EM-VFD) with the small-sectioned slab are as follows: installation position Z = 115 mm and rotation angle of 15°, ensuring that the maximum electromagnetic force is applied to the nozzle jet area. For the acceleration mode of the large-sectioned slab EM-VFD, the optimal mechanical design parameters are as follows: Z = 115 mm and rotation angle of 10°, ensuring that the maximum electromagnetic force is applied to 1/4 and 3/4 areas of the wide face. These findings indicate that the new electromagnetic variable flow device, which can actively adjust the flow rate and angle of the steel even under given working conditions, provides the possibility for reasonable control of the mold’s flow field.
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 Key Research and Development Program of China(2022YFC3204401)the National Natural Science Foundation of China(U23A2001,U2243234)+2 种基金the Major Science and Technology Projects of Inner Mongolia Autonomous Region(KCX2024013-1,2022EEDSKJXM005)the Inner Mongolia Autonomous Region Science and Technology Leading Talent Team(2022LJRC0007)the Inner Mongolia Agricultural University Basic Research Business Expenses Project(BR221012,BR221204).
文摘Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked decline in runoff,posing challenges to the sustainable development of regional water resources and ecosystem stability.To enhance the understanding of runoff dynamics in the basin,we selected the Dahei River Basin,a representative tributary in the upper reaches of the Yellow River Basin as the study area.A comprehensive analysis of runoff trends and contributing factors was conducted using the data on hydrology,meteorology,and water resource development and utilization.Abrupt change years of runoff series in the Dahei River Basin was identified by the Mann-Kendall and Pettitt tests:1999 at Dianshang,Qixiaying,and Meidai hydrological stations and 1995 at Sanliang hydrological station.Through hydrological simulations based on the Variable Infiltration Capacity(VIC)model,we quantified the factors driving runoff evolution in the Dahei River Basin,with climate change contributing 9.92%–22.91%and human activities contributing 77.09%–90.08%.The Budyko hypothesis method provided similar results,with climate change contributing 13.06%–20.89%and human activities contributing 79.11%–86.94%.Both methods indicated that human activities,particularly water consumption,were dominant factors in the runoff variations of the Dahei River Basin.The integration of hydrological modeling with attribution analysis offers valuable insights into runoff evolution,facilitating adaptive strategies to mitigate water scarcity in arid and semi-arid areas.
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.
文摘随着全球气候变化的加剧,其对流域水文过程的影响日益显著。湘江流域作为中国南方重要的水资源区域,其径流变化不仅直接影响区域水资源的可持续利用,还对生态安全和社会经济发展具有深远意义。本研究基于VIC (Variable Infiltration Capacity)水文模型,结合第六次国际耦合模式比较计划(CMIP6)气候模式数据,系统预测未来变化情况。研究结果显示,湘江流域未来时期(2020~2099年)的气候及径流变化在时间和空间尺度上均表现出显著特征。年际尺度上,在SSP2-4.5 (中等排放情景)和SSP5-8.5 (高排放情景)下,未来时期降水量和平均温度均呈现增加趋势,且高排放情景下增幅更为显著;径流量在两个情景下均显著增加,中等排放情景下增幅更大。年代尺度上,2020s、2030s和2060s为降水与径流枯水期,2040s、2050s、2070s、2080s和2090s则为丰水期。SSP2-4.5情景下极端降水和径流事件可能集中在2040s、2080s和2090s,而SSP5-8.5情景下则可能出现在2040s和2070s;径流量时间分布与降水变化高度一致,进一步验证了降水是径流变化的主导驱动因子,湘江流域未来径流变化主要是由降水引起。这些研究为未来流域水资源管理和自然灾害预防提供了重要参考。With the intensification of global climate change, its impacts on hydrological processes in river basins are becoming more and more significant. As an important water resource region in southern China, the runoff changes in the Xiangjiang River Basin not only directly affect the sustainable utilization of regional water resources, but also have far-reaching significance on ecological security and socio-economic development. This study is based on the VIC (Variable Infiltration Capacity) hydrological model, combined with the climate model data from the Sixth International Coupled Model Intercomparison Program (CMIP6), to systematically predict future changes. The results show that the climate and runoff changes in the Xiangjiang River Basin in the future period (2020~2099) exhibit significant features at both temporal and spatial scales. At the interannual scale, both precipitation and mean temperature show increasing trends in the future period under SSP2-4.5 (medium emission scenario) and SSP5-8.5 (high emission scenario), and the increase is more significant under the high emission scenario;runoff increases significantly under both scenarios, and the increase is greater under the medium emission scenario. On the chronological scale, the 2020s, 2030s, and 2060s are dry periods for precipitation and runoff, and the 2040s, 2050s, 2070s, 2080s, and 2090s are abundant periods. Extreme precipitation and runoff events are likely to be concentrated in the 2040s, 2080s, and 2090s under the SSP2-4.5 scenario, and the 2040s, 2080s, and 2090s under the SSP5-8.5 scenario 2040s and 2070s. The temporal distribution of runoff is highly consistent with precipitation changes, which further verifies that precipitation is the dominant driving factor of runoff changes, and future runoff changes in the Xiangjiang River Basin are mainly caused by precipitation. These studies provide important references for future water resource management and natural disaster prevention in the basin.
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.
