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1

P Systems with Rule Production and Removal

Pan Linqiang, Song Bosheng

Fundamenta Informaticae

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2020

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Vol. 171, nr 1-4

313--329

EN

P systems are a class of parallel computational models inspired by the structure and functioning of living cells, where all the evolution rules used in a system are initially set up and keep unchanged during a computation. In this work, inspired by the fact that chemical reactions in a cell can be affected by both the contents of the cell and the environmental conditions, we introduce a variant of P systems, called P systems with rule production and removal (abbreviated as RPR P systems), where rules in a system are dynamically changed during a computation, that is, at any computation step new rules can be produced and some existing rules can be removed. The computational power of RPR P systems and catalytic RPR P systems is investigated. Specifically, it is proved that catalytic RPR P systems with one catalyst and one membrane are Turing universal; for purely catalytic RPR P systems, one membrane and two catalysts are enough for reaching Turing universality. Moreover, a uniform solution to the SAT problem is provided by using RPR P systems with membrane division. It is known that standard catalytic P systems with one catalyst and one membrane are not Turing universal. These results imply that rule production and removal is a powerful feature for the computational power of P systems.

2

The Computational Power of Cell-like P Systems with Symport/Antiport Rules and Promoters

Jiang Suxia, Wang Yanfeng, Xu Jinbang, Xu Fei

Fundamenta Informaticae

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2019

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Vol. 164, nr 2-3

207--225

EN

Cell-like P systems with symport/antiport rules (CSA P systems, for short) are a class of computational models in membrane computing, inspired by the way of transmembrane transport of substances through membrane channels between neighboring regions in a cell. In this work, we propose a variant of CSA P systems, called cell-like P systems with symport/antiport rules and promoters (CSAp P systems, for short), where symport/antiport rules are regulated by multisets of promoters. The computational power of CSAp P systems is investigated. Specifically, it is proved that CSAp P systems working in the maximally parallel mode, having arbitrary large number of membranes and promoters and using only symport rules of length 1 or antiport rules of length 2, are able to compute only finite sets of non-negative integers. Furthermore, we show that CSAp P systems with two membranes working in a sequential mode when having at most two promoters and using only symport rules of length 2, or having at most one promoter and using symport rules of length 1 and antiport rules of length 2, are Turing universal.

3

Communication P Systems with Channel States Working in Flat Maximally Parallel Manner

Jiang Suxia, Wang Yanfeng, Xu Fei, Deng Junli

Fundamenta Informaticae

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2019

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Vol. 168, nr 1

1--24

EN

Communication P systems with channel states (CC P systems, for short) are a class of distributed parallel computing models, where communication (symport/antiport) rules associated with channel states are executed in a sequential manner on membrane channels. In this work, communication P systems with channel states working in flat maximally parallel manner are considered and the computational power is investigated. Specifically, it is proved that communication P systems with channel states using symport rules of length two are Turing universal when having one membrane and any number of channel states, or two membranes and three channel states. Furthermore, membrane division is introduced into communication P systems with channel states, communication P systems with channel states and membrane division (CCD P systems, for short) are proposed. We provide a uniform solution to the Hamiltonian path problem (HPP) by CCD P systems working in a flat maximally parallel manner.

4

Spiking Neural P Systems with Rules on Synapses Working in Sum Spikes Consumption Strategy

Su Y., Wu T., Xu F., Păun A.

Fundamenta Informaticae

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2017

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Vol. 156, nr 2

187--208

EN

Spiking neural P systems with rules on synapses (RSSN P systems, for short) are a class of distributed and parallel computation models inspired by the way in which neurons process and communicate information with each other by means of spikes, where neurons only contain spikes and the evolution rules are on synapses. RSSN P systems have been proved to be Turing universal, using the strategy that restricts all the applied rules to consume the same number of spikes from the given neuron, termed as equal spikes consumption strategy. In this work, in order to avoid imposing the equal spikes consumption restriction on the application of rules, a new strategy for rule application, termed as sum spikes consumption strategy, is considered in RSSN P systems, where a maximal set of enabled rules from synapses starting from the same neuron is nondeterministically chosen to be applied, in the sense that no further synapse can use any of its rules, and the sum of these numbers of spikes that all the applied rules consume is removed from the neuron. In this way, the proposed strategy avoids checking whether all the applied rules consume the same number of spikes from the given neuron. The computation power of RSSN P systems working in the proposed strategy is investigated, and it is proved that such systems characterize the semilinear sets of natural numbers, i.e., such systems are not universal. Furthermore, RSSN P systems with weighted synapses working in the proposed strategy are proved to be Turing universal. These results show that the weight on synapses is a powerful ingredient of RSSN P systems in terms of the computation power, which makes RSSN P systems working in sum spikes consumption strategy become universal from non-universality.

5

A Note on Spiking Neural P Systems with Homogenous Neurons and Synapses

Yu Y., Wu T., Xu J., Wang Y., He J.

Fundamenta Informaticae

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2017

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Vol. 150, nr 2

231--240

EN

Spiking neural (SN, for short) P systems are a class of computation models inspired from the way in which neurons communicate by exchanging spikes. SN P systems with homogenous neurons and synapses are a new variant of SN P systems, where the spiking and forgetting rules are placed on synapses instead of in neurons and each synapse has the same set of spiking and forgetting rules. Recent studies illustrated that this variant of SN P systems is Turing universal as both number generating and accepting devices. In this note, we prove that SN P systems with homogenous neurons and synapses without the feature of delay are also Turing universal. This result gives a positive answer to an open problem formulated in [K. Jiang, et al. Neurocomputing 171(2016) 1548-1555] “whether SN P systems with homogenous neurons and synapses are Turing universal when the feature of delay is not used”.

6

Tissue P Systems with Protein on Cells

Song B., Pan L., Pérez-Jiménez M. J.

Fundamenta Informaticae

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2016

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Vol. 144, nr 1

77--107

EN

Tissue P systems are a class of distributed parallel computing devices inspired by biochemical interactions between cells in a tissue-like arrangement, where objects can be exchanged by means of communication channels. In this work, inspired by the biological facts that the movement of most objects through communication channels is controlled by proteins and proteins can move through lipid bilayers between cells (if these cells are fused), we present a new class of variant tissue P systems, called tissue P systems with protein on cells, where multisets of objects (maybe empty), together with proteins between cells are exchanged. The computational power of such P systems is studied. Specifically, an efficient (uniform) solution to the SAT problem by using such P systems with cell division is presented. We also prove that any Turing computable set of numbers can be generated by a tissue P system with protein on cells. Both of these two results are obtained by such P systems with communication rules of length at most 4 (the length of a communication rule is the total number of objects and proteins involved in that rule).

7

Small Universal Spiking Neural P Systems with Homogenous Neurons and Synapses

Wu T., Wang Y., Jiang S., Shi X.

Fundamenta Informaticae

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2016

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Vol. 149, nr 4

451--470

EN

Spiking neural (SN, for short) P systems are a class of distributed parallel computing models inspired by the way in which neurons communicate with each other by means of electrical impulses. Recently, a new variant of SN P systems, called SN P systems with homogenous neurons and synapses (HRSSN P systems for short) was proposed, where the spiking and forgetting rules are placed on synapses instead of in neurons and each synapse has the same set of spiking and forgetting rules. This variant of SN P systems has already been proved to be Turing universal as both number generating and accepting devices. In this work, we consider the problem of looking for small universal HRSSN P systems. Specifically, a universal HRRSN P system with standard rules and weight at most 5 having 70 neurons is constructed as a device of computing functions; as a number generator, we find a universal system with standard rules and weight at most 5 having 71 neurons.

8

On the Universality of Colored One-Catalyst P Systems

Wu T., Zhang Z., Paun G., Pan L.

Fundamenta Informaticae

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2016

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Vol. 144, nr 2

205--212

EN

A control strategy on the computations in a one-catalyst P system is provided: the rules are assumed “colored” and in each step only rules of the same “color” are used. Such control leads to Turing universality for one-catalyst P systems with one membrane. Turing universality is also reached for purely catalytic P systems with two catalysts, and for purely catalytic P systems with only one catalyst and cooperating rules working in the so-called terminal mode.

9

Automatic segmentation of cell nuclei using Krill Herd optimization based multi-thresholding and Localized Active Contour Model

Beevi K. S., Nair M. S., Bindu G. R.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

584--596

EN

Analysis of tissue components in histopathology image stays on as the gold standard in detecting different types of cancers. Active Contour Models (ACM) serve as a widely useful tool in object segmentation in pathology images. Since the ACMs are susceptible to initial contour placement, efficiency of object detection is very much influenced by the selection of primary curve placement technique. In this paper, in order to handle diffused intensities present along object boundaries in histopathology images, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques in the detection stage. Krill Herd Algorithm (KHA) based optimal curve placement provides better initial boundaries compared with other detection techniques. The segmentation performance is investigated based on Housdorff (HD) and Maximum Absolute Distance (MAD) measures. The algorithm also shows comparable performance with other state-of-the-art techniques in terms of quantitative measures such as Precision, Accuracy and Touching Nuclei Resolution when applied to complex images of stained breast biopsy slides.

10

A P–Lingua Based Simulator for P Systems with Symport/Antiport Rules

Macías-Ramos L. F., Valencia-Cabrera L., Song B., Song T., Pan L., Pérez-Jiménez M. J.

Fundamenta Informaticae

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2015

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Vol. 139, nr 2

211--227

EN

Inspired by mitosis process and membrane fission processes, cell-like P systems with symport/antiport rules and membrane division rules or membrane separation rules have been introduced, respectively. These computation systems have two key features: the ability to have infinite copies of some objects (within an active environment) and to generate an exponential workspace in polynomial time. In this work, we extend the P-Lingua framework for simulating that kind of P systems taking into account these two features. Consequently, a new simulator has been developed and included in pLinguaCore library. The functioning of the simulator has been checked by simulating efficient solutions to SAT problem using a family of cell-like P systems with symport/antiport rules and membrane division rules or membrane separation rules. The corresponding MeCoSim based application is also provided.