To fulfill the requirements for hybrid real-time system scheduling, a long-release-interval-first （LRIF） real-time scheduling algorithm is proposed. The algorithm adopts both the fixed priority and the dynamic prior...To fulfill the requirements for hybrid real-time system scheduling, a long-release-interval-first （LRIF） real-time scheduling algorithm is proposed. The algorithm adopts both the fixed priority and the dynamic priority to assign priorities for tasks. By assigning higher priorities to the aperiodic soft real-time jobs with longer release intervals, it guarantees the executions for periodic hard real-time tasks and further probabilistically guarantees the executions for aperiodic soft real-time tasks. The schedulability test approach for the LRIF algorithm is presented. The implementation issues of the LRIF algorithm are also discussed. Simulation result shows that LRIF obtains better schedulable performance than the maximum urgency first （MUF） algorithm, the earliest deadline first （EDF） algorithm and EDF for hybrid tasks. LRIF has great capability to schedule both periodic hard real-time and aperiodic soft real-time tasks.展开更多
This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage ti...This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage time, batch splitting, partial equipment connectivity and transfer time. The objective is to make a production plan to satisfy all constraints while meeting demand requirement of packed products from various product families. This problem is NP-hard and the problem size is exponentially large for a realistic-sized problem. Therefore,we propose a genetic algorithm to handle this problem. Solutions to the problems are represented by chromosomes of product family sequences. These sequences are decoded to assign the resource for producing packed products according to forward assignment strategy and resource selection rules. These techniques greatly reduce unnecessary search space and improve search speed. In addition, design of experiment is carefully utilized to determine appropriate parameter settings. Ant colony optimization and Tabu search are also implemented for comparison. At the end of each heuristics, local search is applied for the packed product sequence to improve makespan. In an experimental analysis, all heuristics show the capability to solve large instances within reasonable computational time. In all problem instances, genetic algorithm averagely outperforms ant colony optimization and Tabu search with slightly longer computational time.展开更多
AMP-activated protein kinase （AMPK） is an energy sensor that couples the cellular energy state with basic biological processes. AMPK is thought to be linked with cell division although the underlying mechanisms rema...AMP-activated protein kinase （AMPK） is an energy sensor that couples the cellular energy state with basic biological processes. AMPK is thought to be linked with cell division although the underlying mechanisms remain largely unknown. Here, we show that AMPK functionally participates throughout cell division and that AMPK catalytic subunits, especially α2, are sequentially associated with separate mitotic apparatus. Using quantitative phosphoproteomics analysis, we found that the strong direct sub- strate KIF4A is phosphorylated by AMPK at Set801. Further analysis revealed that AMPK and Aurora B competitively phosphore- gulates KIF4A during mitotic phase due to overlapping recognition motifs, resulting in the elaborate phosphoregutation for KIF4A-dependent central spindle length control. Given the intrinsic energy-sensing function of AMPK, our study links the KIF4A- dependent control of central spindle length with cellular glucose stress.展开更多
基金The Natural Science Foundation of Jiangsu Province(NoBK2005408)
文摘To fulfill the requirements for hybrid real-time system scheduling, a long-release-interval-first （LRIF） real-time scheduling algorithm is proposed. The algorithm adopts both the fixed priority and the dynamic priority to assign priorities for tasks. By assigning higher priorities to the aperiodic soft real-time jobs with longer release intervals, it guarantees the executions for periodic hard real-time tasks and further probabilistically guarantees the executions for aperiodic soft real-time tasks. The schedulability test approach for the LRIF algorithm is presented. The implementation issues of the LRIF algorithm are also discussed. Simulation result shows that LRIF obtains better schedulable performance than the maximum urgency first （MUF） algorithm, the earliest deadline first （EDF） algorithm and EDF for hybrid tasks. LRIF has great capability to schedule both periodic hard real-time and aperiodic soft real-time tasks.
基金Thailand Research Fund (Grant #MRG5480176)National Research University Project of Thailand Office of Higher Education Commission
文摘This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage time, batch splitting, partial equipment connectivity and transfer time. The objective is to make a production plan to satisfy all constraints while meeting demand requirement of packed products from various product families. This problem is NP-hard and the problem size is exponentially large for a realistic-sized problem. Therefore,we propose a genetic algorithm to handle this problem. Solutions to the problems are represented by chromosomes of product family sequences. These sequences are decoded to assign the resource for producing packed products according to forward assignment strategy and resource selection rules. These techniques greatly reduce unnecessary search space and improve search speed. In addition, design of experiment is carefully utilized to determine appropriate parameter settings. Ant colony optimization and Tabu search are also implemented for comparison. At the end of each heuristics, local search is applied for the packed product sequence to improve makespan. In an experimental analysis, all heuristics show the capability to solve large instances within reasonable computational time. In all problem instances, genetic algorithm averagely outperforms ant colony optimization and Tabu search with slightly longer computational time.
基金This work was supported by the National Natural Science Foundation of China （81673489）, the State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences （SIMM1705ZZ-02）, Institutes for Drug Discovery and Development, Chinese Academy of Sciences （CASIMM0120161001）, and the Science and Technology Commission of Shanghai Municipality （16430724100 and 14431902800）.
文摘AMP-activated protein kinase （AMPK） is an energy sensor that couples the cellular energy state with basic biological processes. AMPK is thought to be linked with cell division although the underlying mechanisms remain largely unknown. Here, we show that AMPK functionally participates throughout cell division and that AMPK catalytic subunits, especially α2, are sequentially associated with separate mitotic apparatus. Using quantitative phosphoproteomics analysis, we found that the strong direct sub- strate KIF4A is phosphorylated by AMPK at Set801. Further analysis revealed that AMPK and Aurora B competitively phosphore- gulates KIF4A during mitotic phase due to overlapping recognition motifs, resulting in the elaborate phosphoregutation for KIF4A-dependent central spindle length control. Given the intrinsic energy-sensing function of AMPK, our study links the KIF4A- dependent control of central spindle length with cellular glucose stress.
