P Systems with Active Cells

P systems with active membranes is a widely studied framework within the field of Membrane Computing since the creation of the discipline. The abstraction of the structure and behavior of living cells is reflected in the tree-like hierarchy and the kinds of rules that can be used in these kinds of systems. Resembling the organization and communication between cells within tissues that form organs, tissue-like P systems were defined as their abstractions, using symport/antiport rules, that is, moving and exchanging elements from one cell to another one. All the cells are located in an environment where there exist an arbitrary number of some elements. Lately, symport/antiport rules have been used in the framework of cell-like membrane systems in order to study their computational power. Interesting results have been reached, since they act similarly to their counterparts in the framework of tissue P systems. Here, the use of the former defined rules (that is, evolution, communication, dissolution and division/separation rules) is considered, but not working with a tree-like structure. Some remarks about choosing good semantics are given

Limits on P Systems with Proteins and Without Division

In the field of Membrane Computing, computational complexity theory has been widely studied trying to nd frontiers of efficiency by means of syntactic or semantical ingredients. The objective of this is to nd two kinds of systems, one non-efficient and another one, at least, presumably efficient, that is, that can solve NP-complete prob- lems in polynomial time, and adapt a solution of such a problem in the former. If it is possible, then P = NP. Several borderlines have been defi ned, and new characterizations of different types of membrane systems have been published. In this work, a certain type of P system, where proteins act as a supporting element for a rule to be red, is studied. In particular, while division rules, the abstraction of cellular mitosis is forbidden, only problems from class P can be solved, in contrast to the result obtained allowing them.Ministerio de Economía y Competitividad TIN2017-89842-PNational Natural Science Foundation of China No 6132010600

Simulation of Rapidly-Exploring Random Trees in Membrane Computing with P-Lingua and Automatic Programming

Methods based on Rapidly-exploring Random Trees (RRTs) have been widely used in robotics to solve motion planning problems. On the other hand, in the membrane computing framework, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers, but today there is a lack of planning algorithms based on membrane computing for robotics. With this motivation, we provide a variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) addressed to implement RRT algorithms and we illustrate it by simulating the bidirectional RRT algorithm. This paper is an extension of [21]a. The software presented in [21] was an ad-hoc simulator, i.e, a tool for simulating computations of one and only one model that has been hard-coded. The main contribution of this paper with respect to [21] is the introduction of a novel solution for membrane computing simulators based on automatic programming. First, we have extended the P-Lingua syntax –a language to define membrane computing models– to write RENPSM models. Second, we have implemented a new parser based on Flex and Bison to read RENPSM models and produce source code in C language for multicore processors with OpenMP. Finally, additional experiments are presented.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

Narrowing Frontiers of Efficiency with Evolutional Communication Rules and Cell Separation

In the framework of Membrane Computing, several efficient solutions to computationally hard problems have been given. To find new borderlines between families of P systems that can solve them and the ones that cannot is an important way to tackle the P versus NP problem. Adding syntactic and/or semantic ingredients can mean passing from non-efficiency to presumably efficiency. Here, we try to get narrow frontiers, setting the stage to adapt efficient solutions from a family of P systems to another one. In order to do that, a solution to the SAT problem is given by means of a family of tissue P systems with evolutional symport/antiport rules and cell separation with the restriction that both the left-hand side and the right-hand side of the rules have at most two objects.Ministerio de Economía y Competitividad TIN2017-89842-PNational Natural Science Foundation of China No 6132010600

Contour Approximation with P Systems

We model the problem of contour approximation using Hilbert's space lling curve, with a novel type of parallel array rewriting rules. We further use their pattern to introduce a special type of tissue P system, with novel features, among which is controlling their behavior with input. We propose some further developments.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

Bilayered Calcium Sulfate/Calcium Phosphate Space-Making Composites with Multiple Drug Delivery Capabilities

The present invention provides for bilayered composites that provide for sustained drug delivery and support to recovering tissue(s) and areas surrounding, such as with bone tissue. The two layers degrade at separate rates, thereby providing sustained mechanical support and tailored drug delivery

Fuzzy reasoning spiking neural P systems revisited: A formalization

Research interest within membrane computing is becoming increasingly interdisciplinary.In particular, one of the latest applications is fault diagnosis. The underlying mechanismwas conceived by bridging spiking neural P systems with fuzzy rule-based reasoning systems. Despite having a number of publications associated with it, this research line stilllacks a proper formalization of the foundations.National Natural Science Foundation of China No 61320106005National Natural Science Foundation of China No 6147232

An apparently innocent problem in Membrane Computing

The search for effcient solutions of computationally hard problems by means of families of membrane systems has lead to a wide and prosperous eld of research. The study of computational complexity theory in Membrane Computing is mainly based on the look for frontiers of effciency between different classes of membrane systems. Every frontier provides a powerful tool for tackling the P versus NP problem in the following way. Given two classes of recognizer membrane systems R1 and R2, being systems from R1 non-effcient (that is, capable of solving only problems from the class P) and systems from R2 presumably e cient (that is, capable of solving NP-complete problems), and R2 the same class that R1 with some ingredients added, passing from R1 to R2 is comparable to passing from the non effciency to the presumed effciency. In order to prove that P = NP, it would be enough to, given a solution of an NP-complete problem by means of a family of recognizer membrane systems from R2, try to remove the added ingredients to R2 from R1. In this paper, we study if it is possible to solve SAT by means of a family of recognizer P systems from AM0(�����d;+n), whose non-effciency was demonstrated already

A new perspective on computational complexity theory in Membrane Computing

A single Turing machine can solve decision problems with an in nite number of instances. On the other hand, in the framework of membrane computing, a \solution" to an abstract decision problem consists of a family of membrane systems (where each system of the family is associated with a nite set of instances of the problem to be solved). An interesting question is to analyze the possibility to nd a single membrane system able to deal with the in nitely many instances of a decision problem. In this context, it is fundamental to de ne precisely how the instances of the problem are introduced into the system. In this paper, two different methods are considered: pre-computed (in polynomial time) resources and non-treated resources. An extended version of this work will be presented in the 20th International Conference on Membrane Computing.Ministerio de Economía, Industria y Competitividad TIN2017-89842-