Search

Reaction system (RS) belongs to a type of qualitative computing model inspired by biochemical reactions taking place inside biological cells. It concerns more the interactions and causality among reactions rather than concrete concentrations of chemical entities. Many biochemical processes and models can be represented in the form of reaction systems so that complex relations and ultimate products of a variety of reactions can be revealed qualitatively. The reaction system works in parallel mode. Software simulation of this kind of model may suffer from the penalty of inefficient parallelism for the limited performance of CPU/GPU, especially for the simulation of large-scale models. Considering potential applications of reaction systems in disease diagnoses and in drug developments, hardware implementation of reaction systems provides a better way to accelerate computations involved. In this paper, an FPGA implementation method of a reaction system called RSFIM is proposed. Two small-scale models, i.e., the reaction system of intermediate filaments self-assembly and heat shock response, are implemented on FPGA, achieving a computing speed of 2 × 10 8 steps per second. For large-scale models, the ErbB reaction system is implemented, obtaining a speedup of 7.649 × 10 4 compared with its highest performance GPU simulation so far. The reaction system binary counter, which is a quantitative model, is also implemented by the Boolean explanation of the qualitative character of the reaction system. FPGA implementation of reaction systems opens a novel research line to speed up the simulations of reaction systems and other biological models in the perspective of parallel digital circuits. [ABSTRACT FROM AUTHOR]

Conducting an evaluation of the emergency management capacity of the chemical park and implementing targeted improvements based on the assessment results can significantly enhance the emergency preparedness and response capabilities of both the management departments and enterprises. This article proposes an emergency management capability assessment model for chemical parks based on PFDEMATEL (the Pythagorean fuzzy decision‐making trial and evaluation laboratory)‐G1 (the ordinal relation method) and PFTOPSIS (the Pythagorean fuzzy set TOPSIS). Firstly, based on the four stages of emergency management of chemical parks, emergency prevention, emergency preparedness, emergency response, and emergency recovery, an index system for evaluating the emergency management capacity of chemical parks was established. Secondly, PFDEMATEL is used to modify the G1 method to determine the index weight, so as to realize the objective rationality of the G1 method empowerment. On this basis, an emergency management capability evaluation model of chemical park to improve PFTOPSIS is proposed. Finally, taking three chemical parks as examples, the applicability of the evaluation model is verified. The research results can provide a theoretical reference for the emergency management decision‐making of governments and enterprises, improve the status quo of emergency management, and improve the prevention and handling capabilities of emergencies. [ABSTRACT FROM AUTHOR]

This paper investigates an FPGA architecture whose primary function is to accelerate parallel computations involved in the rapid-exploring random tree (RRT) algorithm. The RRT algorithm is inherently serial, while in each computing step there are many computations that can be executed simultaneously. Nevertheless, how to carry out these parallel computations on an FPGA so that a high degree of acceleration can be realized is the key issue. Membrane computing is a parallel computing paradigm inspired from the structures and functions of eukaryotic cells. As a newly proposed membrane computing model, the generalized numerical P system (GNPS) is intrinsically parallel; so, it is a good candidate for modeling parallel computations in the RRT algorithm. Open problems for the FPGA implementation of the RRT algorithm and GNPS include: (1) whether it possible to model the RRT with GNPS; (2) if yes, how to design such an FPGA architecture to achieve a better speedup; and (3) instead of implementing GNPSs with a fixed-point-number format, how to devise a GNPS FPGA architecture working with a floating-point-number format. In this paper, we modeled the RRT with a GNPS at first, showing that it is feasible to model the RRT with a GNPS. An FPGA architecture was fabricated according to the GNPS-modeled RRT. In this architecture, computations, which can be executed in parallel, are accommodated in different inner membranes of the GNPS. These membranes are designed as Verilog modules in the register transfer level model. All the computations within a membrane are triggered by the same clock impulse to implement parallel computing. The proposed architecture is validated by implementing it on the Xilinx VC707 FPGA evaluation board. Compared with the software simulation of the GNPS-modeled RRT, the FPGA architecture achieves a speedup of a 10 4 order of magnitude. Although this speedup is obtained on a small map, it reveals that this architecture promises to accelerate the RRT algorithm to a higher level compared with the previously reported architectures. [ABSTRACT FROM AUTHOR]