No abstract

Surrogate-assisted evolutionary algorithms have been developed mainly for solving expensive optimization problems where only a small number of real fitness evaluations are allowed. Most existing surrogate-assisted evolutionary algorithms are designed for solving low-dimensional single or multiobjective optimization problems, which are not well suited for many-objective optimization. This paper proposes a surrogateassisted many-objective evolutionary algorithm that uses an artificial neural network to predict the dominance relationship between candidate solutions and reference solutions instead of approximating the objective values separately. The uncertainty information in prediction is taken into account together with the dominance relationship to select promising solutions to be evaluated using the real objective functions. Our simulation results demonstrate that the proposed algorithm outperforms the state-of-the-art evolutionary algorithms on a set of manyobjective optimization test problems.

Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

Besides usual spikes employed in spiking neural P systems, we consider "anti-spikes", which participate in spiking and forgetting rules, but also annihilate spikes when meeting in the same neuron. This simple extension of spiking neural P systems is shown to considerably simplify the universality proofs in this area: all rules become of the form b c → b ′ or b c → λ , where b, b ′ are spikes or anti-spikes. Therefore, the regular expressions which control the spiking are the simplest possible, identifying only a singleton. A possible variation is not to produce anti-spikes in neurons, but to consider some "inhibitory synapses", which transform the spikes which pass along them into anti-spikes. Also in this case, universality is rather easy to obtain, with rules of the above simple forms.

No abstract

In this study, an aptamer-substrate strategy is introduced to control programmable DNA origami pattern. Combined with DNA aptamer-substrate binding and DNAzyme-cutting, small DNA tiles were specifically controlled to fill into the predesigned DNA origami frame. Here, a set of DNA logic gates (OR, YES, and AND) are performed in response to the stimuli of adenosine triphosphate (ATP) and cocaine. The experimental results are confirmed by AFM imaging and time-dependent fluorescence changes, demonstrating that the geometric patterns are regulated in a controllable and programmable manner. Our approach provides a new platform for engineering programmable origami nanopatterns and constructing complex DNA nanodevices.

Synthetic catalytic DNA circuits are important signal amplification tools for molecular programming due to their robust and modular properties. In catalytic circuits, the reactant recycling operation is essential to facilitate continuous processes. Therefore, it is desirable to develop new methods for the recycling of reactants and to improve the recyclability in entropy-driven DNA circuit reactions. Here, we describe the implementation of a nicking-assisted recycling strategy for reactants in entropy-driven DNA circuits, in which duplex DNA waste products are able to revert into active components that could participate in the next reaction cycle. Both a single-layered circuit and multiple two-layered circuits of different designs were constructed and analyzed. During the reaction, the single-layered catalytic circuit can consume excess fuel DNA strands without depleting the gate components. The recycling of the two-layered circuits occurs during the fuel DNA digestion but not during the release of the downstream trigger. This strategy provides a simple yet versatile method for creating more efficient entropy-driven DNA circuits for molecular programming and synthetic biology.

The catalytic DNA circuits play a critical role in engineered biological systems and molecular information processing. Actually, some of the natural or synthetic DNA circuits were triggered by covalent modifications, where conformational changes were induced to facilitate complex DNA engineering functions and signal transmissions. However, most of the reported artificial catalytic DNA circuits were regulated by the toehold-mediated reaction. Therefore, it is significant to propose a strategy to regulate the catalytic DNA circuit not only by the toehold-mediated mechanism, but also by involving the conformational changes induced by the covalent modification. In this study, we developed the catalytic DNA logic circuits regulated by DNAzyme. Here, a regulation strategy based on the covalent modification was proposed to control the DNA circuit, combing two reaction mechanisms: DNAzyme digestion and entropy-driven strand displacement. The DNAzyme and DNA catalyst can participate into the reactions alternatively, thus realizing the cascading catalytic circuits. Using the DNAzyme regulation, a series of logic gates (YES, OR and AND) were constructed. In addition, a two-layer cascading circuit and a feedback self-catalysis circuit were also established. The proposed DNAzyme-regulated strategy shows great potentials as a reliable and feasible method for constructing more complex catalytic DNA circuits.