After billions of years of evolution,biological intelligence has converged on unrivalled energy efficiency and environmental adaptability.The human brain,for instance,is highly efficient in information transmission,co...After billions of years of evolution,biological intelligence has converged on unrivalled energy efficiency and environmental adaptability.The human brain,for instance,is highly efficient in information transmission,consuming only about 20 W onaverage in a resting state[1,2].A key to this efficiency is that biological signal transduction and processing rely significantly on multi-ions as the signal carriers.Inspired by this paradigm.展开更多
The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and e...The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.展开更多
The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability...Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability of the triazine ring structure within cyanate ester(CE)crosslinked networks after molding posed significant challenges for both recycling,repairing,and degradation of resin.To address these obstacles,dynamic thiocyanate ester(TCE)bonds and photocurable group were incorporated into CE,obtaining the recyclable and 3D printable CE covalent adaptable networks(CANs),denoted as PTCE1.5.This material exhibits a Young's modulus of 810 MPa and a tensile strength of 50.8 MPa.Notably,damaged printed PTCE1.5 objects can be readily repaired through reprinting and interface rejoining by thermal treatment.Leveraging the solid-state plasticity,PTCE1.5 also demonstrated attractive shape memory ability and permanent shape reconfigurability,enabling its reconfigurable 4D printing.The printed PTCE1.5 hinges and a main body were assembled into a deployable and retractable satellite model,validating its potential application as a controllable component in the aerospace field.Moreover,printed PTCE1.5 can be fully degraded into thiol-modified intermediate products.Overall,this material not only enriches the application range of CE resin,but also provides a reliable approach to addressing environmental issue.展开更多
背景:骨代谢紊乱会引起骨相关疾病的发生,而叉头框转录因子O3可以通过调节氧化应激、自噬水平等来影响骨组织细胞增殖、分化与凋亡,调控骨代谢过程。目的:系统性分析叉头框转录因子O3调控骨代谢及其在骨科疾病中作用机制的相关研究文献...背景:骨代谢紊乱会引起骨相关疾病的发生,而叉头框转录因子O3可以通过调节氧化应激、自噬水平等来影响骨组织细胞增殖、分化与凋亡,调控骨代谢过程。目的:系统性分析叉头框转录因子O3调控骨代谢及其在骨科疾病中作用机制的相关研究文献,为后续以叉头框转录因子O3为靶点治疗骨疾病的研究提供参考。方法:以“(SU=FoxO3a OR SU=Foxo3 OR SU=Forkhead box O3 OR SU=叉头框转录因子O3)AND SU=骨”为检索句在中国知网进行检索,以“主题:(“FoxO3a”)OR主题:(“Foxo3”)OR主题:(“Forkhead box O3”)OR主题:(“叉头框转录因子O3”)AND主题:(“骨”)”为检索句在万方医学数据库进行检索;以“((FoxO3a)OR(Foxo3)OR(Forkhead box O3))AND((bone)OR(Skeleton))”为检索句在PubMed数据库进行检索,排除陈旧、重复、质量较差以及不相关的文献,最终纳入56篇文献进行综述分析。结果与结论:①叉头框转录因子O3与骨髓间充质干细胞:叉头框转录因子O3能够促进成骨谱系的形成,还可通过激活自噬促进早期成骨分化。同时,叉头框转录因子O3在骨髓间充质干细胞中体现抗氧化特性,保护细胞免受氧化应激诱导的衰老。②叉头框转录因子O3与成骨细胞:叉头框转录因子O3在成骨细胞中能通过干扰Wnt/β-连环蛋白通路抑制成骨,同时能激活抗氧化酶保护成熟成骨细胞。叉头框转录因子O3能促进成骨祖细胞的增殖,并通过激活自噬促进成骨分化。③叉头框转录因子O3与破骨细胞:叉头框转录因子O3表达可抵抗氧化应激和激活自噬抑制破骨细胞生成。④叉头框转录因子O3与骨细胞:叉头框转录因子O3可通过抗氧化作用保护骨细胞,还可通过抑制p16和p53信号通路和抑制衰老相关分泌表型来减少骨流失。⑤叉头框转录因子O3与软骨细胞:叉头框转录因子O3在骨关节炎中对软骨细胞起到保护作用,抑制软骨细胞分解或凋亡,促进软骨细胞外基质合成,可抑制软骨细胞肥大;然而,叉头框转录因子O3与Runt相关转录因子1在软骨细胞中高度共表达却会促进软骨祖细胞的早期软骨形成和终末肥大。⑥叉头框转录因子O3通过参与氧化应激抵抗与调控自噬等过程影响骨代谢,参与多类骨相关疾病的病理进程。展开更多
随着大语言模型(large language models,LLMs)(以下简称“大模型”)参数规模的持续增长,微调百亿级参数大模型对计算和存储资源提出了极高要求。传统分布式训练方案通常依赖大量高端GPU和高速互联网络,训练成本极为昂贵。现有单GPU训练...随着大语言模型(large language models,LLMs)(以下简称“大模型”)参数规模的持续增长,微调百亿级参数大模型对计算和存储资源提出了极高要求。传统分布式训练方案通常依赖大量高端GPU和高速互联网络,训练成本极为昂贵。现有单GPU训练方案虽通过张量卸载缓解显存压力,但仍然面临I/O传输效率低和设备利用率不足等问题。传统内核态I/O操作在大规模张量迁移中引入频繁的系统调用和上下文切换,成为制约性能的关键瓶颈;同时,优化器计算无法充分发挥多核CPU的并行能力,难以实现与GPU计算的有效重叠,进一步限制了系统性能。针对上述问题,提出了一种面向大模型训练的异构内存卸载与I/O优化方案HiTrain。首先构建了基于存储性能开发工具包(storage performance development kit,SPDK)的高性能张量存储模块,通过在用户态管理张量数据,避免了内核I/O栈开销,从而提高张量卸载的并发性与吞吐率;其次,设计并实现了基于异步优化器的存储-计算流水线调度模块,通过对优化器的执行进行优化重排来减少GPU等待时间,提高整体训练效率。实验结果表明,在配备单张GPU和非易失性存储器快速固态硬盘(non-volatile memory express solid state drive,NVMe SSD)的服务器上,所提出的方案能够充分利用系统中的存算资源,使得模型训练过程中张量卸载与加载效率提升32.7%,整体训练吞吐提升至现有方案的1.49倍,为低成本大模型训练提供了切实可行的技术路径。展开更多
文摘After billions of years of evolution,biological intelligence has converged on unrivalled energy efficiency and environmental adaptability.The human brain,for instance,is highly efficient in information transmission,consuming only about 20 W onaverage in a resting state[1,2].A key to this efficiency is that biological signal transduction and processing rely significantly on multi-ions as the signal carriers.Inspired by this paradigm.
基金Supported by the National Natural Science Foundation of China(Grant Nos.11961059,1210502)the University Innovation Project of Gansu Province(Grant No.2023B-062)the Gansu Province Basic Research Innovation Group Project(Grant No.23JRRA684).
文摘The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
基金supported by the National Natural Science Foundation of China(Nos.52473080,52403167 and 52173079)the Fundamental Research Funds for the Central Universities(Nos.xtr052023001 and xzy012023037)+1 种基金the Postdoctoral Research Project of Shaanxi Province(No.2024BSHSDZZ054)the Shaanxi Laboratory of Advanced Materials(No.2024ZY-JCYJ-04-12).
文摘Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability of the triazine ring structure within cyanate ester(CE)crosslinked networks after molding posed significant challenges for both recycling,repairing,and degradation of resin.To address these obstacles,dynamic thiocyanate ester(TCE)bonds and photocurable group were incorporated into CE,obtaining the recyclable and 3D printable CE covalent adaptable networks(CANs),denoted as PTCE1.5.This material exhibits a Young's modulus of 810 MPa and a tensile strength of 50.8 MPa.Notably,damaged printed PTCE1.5 objects can be readily repaired through reprinting and interface rejoining by thermal treatment.Leveraging the solid-state plasticity,PTCE1.5 also demonstrated attractive shape memory ability and permanent shape reconfigurability,enabling its reconfigurable 4D printing.The printed PTCE1.5 hinges and a main body were assembled into a deployable and retractable satellite model,validating its potential application as a controllable component in the aerospace field.Moreover,printed PTCE1.5 can be fully degraded into thiol-modified intermediate products.Overall,this material not only enriches the application range of CE resin,but also provides a reliable approach to addressing environmental issue.
文摘背景:骨代谢紊乱会引起骨相关疾病的发生,而叉头框转录因子O3可以通过调节氧化应激、自噬水平等来影响骨组织细胞增殖、分化与凋亡,调控骨代谢过程。目的:系统性分析叉头框转录因子O3调控骨代谢及其在骨科疾病中作用机制的相关研究文献,为后续以叉头框转录因子O3为靶点治疗骨疾病的研究提供参考。方法:以“(SU=FoxO3a OR SU=Foxo3 OR SU=Forkhead box O3 OR SU=叉头框转录因子O3)AND SU=骨”为检索句在中国知网进行检索,以“主题:(“FoxO3a”)OR主题:(“Foxo3”)OR主题:(“Forkhead box O3”)OR主题:(“叉头框转录因子O3”)AND主题:(“骨”)”为检索句在万方医学数据库进行检索;以“((FoxO3a)OR(Foxo3)OR(Forkhead box O3))AND((bone)OR(Skeleton))”为检索句在PubMed数据库进行检索,排除陈旧、重复、质量较差以及不相关的文献,最终纳入56篇文献进行综述分析。结果与结论:①叉头框转录因子O3与骨髓间充质干细胞:叉头框转录因子O3能够促进成骨谱系的形成,还可通过激活自噬促进早期成骨分化。同时,叉头框转录因子O3在骨髓间充质干细胞中体现抗氧化特性,保护细胞免受氧化应激诱导的衰老。②叉头框转录因子O3与成骨细胞:叉头框转录因子O3在成骨细胞中能通过干扰Wnt/β-连环蛋白通路抑制成骨,同时能激活抗氧化酶保护成熟成骨细胞。叉头框转录因子O3能促进成骨祖细胞的增殖,并通过激活自噬促进成骨分化。③叉头框转录因子O3与破骨细胞:叉头框转录因子O3表达可抵抗氧化应激和激活自噬抑制破骨细胞生成。④叉头框转录因子O3与骨细胞:叉头框转录因子O3可通过抗氧化作用保护骨细胞,还可通过抑制p16和p53信号通路和抑制衰老相关分泌表型来减少骨流失。⑤叉头框转录因子O3与软骨细胞:叉头框转录因子O3在骨关节炎中对软骨细胞起到保护作用,抑制软骨细胞分解或凋亡,促进软骨细胞外基质合成,可抑制软骨细胞肥大;然而,叉头框转录因子O3与Runt相关转录因子1在软骨细胞中高度共表达却会促进软骨祖细胞的早期软骨形成和终末肥大。⑥叉头框转录因子O3通过参与氧化应激抵抗与调控自噬等过程影响骨代谢,参与多类骨相关疾病的病理进程。
文摘随着大语言模型(large language models,LLMs)(以下简称“大模型”)参数规模的持续增长,微调百亿级参数大模型对计算和存储资源提出了极高要求。传统分布式训练方案通常依赖大量高端GPU和高速互联网络,训练成本极为昂贵。现有单GPU训练方案虽通过张量卸载缓解显存压力,但仍然面临I/O传输效率低和设备利用率不足等问题。传统内核态I/O操作在大规模张量迁移中引入频繁的系统调用和上下文切换,成为制约性能的关键瓶颈;同时,优化器计算无法充分发挥多核CPU的并行能力,难以实现与GPU计算的有效重叠,进一步限制了系统性能。针对上述问题,提出了一种面向大模型训练的异构内存卸载与I/O优化方案HiTrain。首先构建了基于存储性能开发工具包(storage performance development kit,SPDK)的高性能张量存储模块,通过在用户态管理张量数据,避免了内核I/O栈开销,从而提高张量卸载的并发性与吞吐率;其次,设计并实现了基于异步优化器的存储-计算流水线调度模块,通过对优化器的执行进行优化重排来减少GPU等待时间,提高整体训练效率。实验结果表明,在配备单张GPU和非易失性存储器快速固态硬盘(non-volatile memory express solid state drive,NVMe SSD)的服务器上,所提出的方案能够充分利用系统中的存算资源,使得模型训练过程中张量卸载与加载效率提升32.7%,整体训练吞吐提升至现有方案的1.49倍,为低成本大模型训练提供了切实可行的技术路径。
