Xiaolong Shi

A Novel Bio-Sensor Based on DNA Strand Displacement

DNA strand displacement technology performs well in sensing and programming DNA segments. In this work, we construct DNA molecular systems based on DNA strand displacement performing computation of logic gates. Specifically, a class of so-called “DNA neurons” are achieved, in which a “smart” way inspired by biological neurons encoding information is developed to encode and deliver information using DNA molecules. The “DNA neuron” is bistable, that is, it can sense DNA molecules as input signals, and release “negative” or “positive” signals DNA molecules. We design intelligent DNA molecular systems that are constructed by cascading some particularly organized “DNA neurons”, which could perform logic computation, including AND, OR, XOR logic gates, automatically. Both simulation results using visual DSD (DNA strand displacement) software and experimental results are obtained, which shows that the proposed systems can detect DNA signals with high sensitivity and accretion; moreover, the systems can process input signals automatically with complex nonlinear logic. The method proposed in this work may provide a new way to construct a sensitive molecular signal detection system with neurons spiking behavior in vitro, and can be used to develop intelligent molecular processing systems in vivo.

Improve capability of DNA automaton: DNA automaton with three internal states and tape head move in two directions

DNA automaton is a simple molecular-scale automaton, in which the converting of information deploys in molecule-scale by DNA and DNA-manipulating enzymes autonomously. Finite automaton with two internal states has been applied to medical diagnosis. This paper analyses the computation ability of DNA automaton with different enzymes and the possibility of DNA finite automaton with three internal states which is more powerful than the two internal states finite automaton. Finally, we describe a DNA finite automaton with three internal states and proposal a scheme of DNA automaton model in which the tape head can move forward and backward, and symbols can be read from and write into the tape, thus extend the computation ability of DNA automaton and its application fields.

A novel thermodynamic model and temperature control method of laser soldering systems

Laser technology is vital in production of precision electronic components and has been widely used in modern industry. In laser soldering systems, accurate temperature control remains a challenging problem, since the temperature is highly sensitive to laser power and thermodynamic parameters of solder joints. In this paper, a good solution is proposed to solve the problem by controlling the temperature based on a novel thermodynamic model. In the model, many of the major factors are taken into account, such as laser energy, flux influence, and solder joints with different parameters. Aimed at the thermodynamic process and the influence of solder fluxes, a mixed mode control method is used to track the designed target temperature curve; this method can produce a solder joint with good quality. As a result, a model-based feed-forward and proportional, integral, and derivative (PID) mixed control method is developed. In practice, the proposed method is verified to have a wider product capability and production size; and a rate of good products of 99.94% is achieved with consuming approximately half of the energy comparing with manual soldering and constant laser power soldering.

A novel computational method to reduce leaky reaction in DNA strand displacement

DNA strand displacement technique is widely used in DNA programming, DNA biosensors, and gene analysis. In DNA strand displacement, leaky reactions can cause DNA signals decay and detecting DNA signals fails. The mostly used method to avoid leakage is cleaning up after upstream leaky reactions, and it remains a challenge to develop reliable DNA strand displacement technique with low leakage. In this work, we address the challenge by experimentally evaluating the basic factors, including reaction time, ratio of reactants, and ion concentration to the leakage in DNA strand displacement. Specifically, fluorescent probes and a hairpin structure reporting DNA strand are designed to detect the output of DNA strand displacement, and thus can evaluate the leakage of DNA strand displacement reactions with different reaction time, ratios of reactants, and ion concentrations. From the obtained data, mathematical models for evaluating leakage are achieved by curve derivation. As a result, it is obtained that long time incubation, high concentration of fuel strand, and inappropriate amount of ion concentration can weaken leaky reactions. This contributes to a method to set proper reaction conditions to reduce leakage in DNA strand displacement.

Solving Vertex Cover Problem Using DNA Tile Assembly Model

DNA tile assembly models are a class of mathematically distributed and parallel biocomputing models in DNA tiles. In previous works, tile assembly models have been proved be Turing-universal; that is, the system can do what Turing machine can do. In this paper, we use tile systems to solve computational hard problem. Mathematically, we construct three tile subsystems, which can be combined together to solve vertex cover problem. As a result, each of the proposed tile subsystems consists of (1) types of tiles, and the assembly process is executed in a parallel way (like DNA’s biological function in cells); thus the systems can generate the solution of the problem in linear time with respect to the size of the graph.

P Systems with Proteins Working in the Minimally Parallel Mode

Membrane systems are distributed and parallel computing devices inspired from the structure and the functioning of living cells, called P systems. Most variant of P systems have been proved to be universal in the model of maximally parallel mode. But this hypothesis does not have biologically realistic support. In order to construct a more “realistic” system, we introduce the minimal parallelism into the protein P systems. Minimal parallelism is a way the rules of a P system used: from each set of applicable rules associated to the same membrane, at least one must be applied. We investigate the computing power of P systems with proteins on membranes working in the minimal parallelism mode. Such systems are shown to be computationally complete even with only three membranes and one protein on each membrane.

Research on the optimization of water-cooling control in high-speed steel rolling system based on Bayesian network

The existing high-speed wire production line of Wuhan Iron and Steel Group Corporation has the shortage that reliability of water-cooling control system is poor, the temperature of rolling line fluctuation range is large. Taking these problems into consideration, we build a water-cooling temperature model based on Bayesian network in order to improve the control accuracy. And the optimized system works well in the industrial site.