**Volume 1 Issue 1**

Pan, L., Păun, Gh., Zhang, G. (2019). **Foreword: Starting JMC**. *Journal of Membrane Computing*, *1*(1), 1–2. https://doi.org/10.1007/s41965-019-00010-5

Bottoni, P.,
Labella, A., & Rozenberg, G. (2019). **Reaction systems with influence on
environment**. *Journal of Membrane Computing*, *1*(1), 3–19. https://doi.org/10.1007/s41965-018-00005-8

Reaction systems, motivated by the functioning of the living cell, became a novel
model of interactive computation. In
this paper, we pursue this line of research. More specifically, we present a
systematic investigation of possible interactions of a reaction system with its
environment (context). While in the
original definition this interaction is one-way,
i.e., the behavior of a reaction system is influenced by its environment, we
investigate now also the influence of the
system on its environment, where a possible time delay of this influence is also considered. To understand the
behavior of reaction systems when such a two-way
interaction takes place, we establish its relationship to their context-independent behavior (i.e., the
behavior which is not influenced by the environment).

Mayne, R.,
Phillips, N., & Adamatzky, A. (2019). **Towards experimental P-systems
using multivesicular liposomes**. *Journal of Membrane Computing*, *1*(1),
20–28. https://doi.org/10.1007/s41965-018-00006-7

P-systems
are abstract computational models inspired by the phospholipid
bilayer membranes generated by biological cells. Illustrated here is a
mechanism by which recursive liposome
structures (multivesicular liposomes) may be experimentally
produced through electroformation
of dipalmitoylphosphatidylcholine films for use in ‘real’ P-systems. We first present the electroformation protocol
and microscopic characterisation of incident liposomes towards estimating the size of computing elements, level of internal
compartment recursion, fault tolerance
and stability. Following, we demonstrate
multiple routes towards embedding symbols,
namely modification of swelling solutions,
passive diffusion, and microinjection. Finally, we discuss how
computing devices based on P-systems can be produced
and their current limitations.

Orellana-Martín,
D., Valencia-Cabrera, L., Riscos-Núñez, A., & Pérez-Jiménez,
M. J. (2019). **P systems with proteins: a new frontier when membrane division
disappears**. *Journal of Membrane Computing*, *1*(1), 29–39. https://doi.org/10.1007/s41965-018-00003-w

P
systems with active membranes are usually defined as devices hierarchically
structured that evolve through rewriting rules. These rules take the
inspiration on the chemical reactions that happen within a cell and the role of
both the inner and the plasma membranes
as a “filter”, letting components pass
or not. Classically, these systems are non-cooperative,
that is, the left-hand side of the rules has at most one object. Using polarizations, dissolution or cooperation,
these systems have been proved to have enough power to efficiently solve
computationally hard problems, obtaining new complexity frontiers with respect
to their non-cooperative counterparts. In this paper, division rules are
interchanged by separation rules. While
the first ones produce two new membranes and two new objects, duplicating the
objects within the original one, separation rules distribute
the objects of the original membrane into the two new created membranes, so no new objects are created in this way. To
obtain new objects, a rule of the type [ a→a^{2} ] would be
needed to accomplish that feature that seems to be necessary to obtain efficient solutions to NP-complete problems.
Here, we present the limits when using
separation rules instead of division rules.

Sánchez-Karhunen,
E., & Valencia-Cabrera, L. (2019). **Modelling complex market interactions
using PDP systems**. *Journal of Membrane Computing*, *1*(1),
40–51. https://doi.org/10.1007/s41965-019-00008-z

Last
decade has witnessed an increasing effort on modelling
and simulation of phenomena within a wide range of areas such as
Biochemistry, Ecology, Robotics or Engineering by using membrane computing,
providing solutions for relevant problems (signalling pathways, population
dynamics, robot control or fault diagnosis, among others). However, for no
apparent reasons, other areas have not
been investigated to such extent. This is the case of computational economics, where Gh. and R. Păun explored the
so-called producer–retailer problem and,
in a foundational paper, proposed an initial model
making use of membrane computing modelling
tools. In the present paper, we design a solution based on population dynamics P systems for an enriched version of that problem. This
enhanced model, closer to reality, takes into account several economic issues
not considered in the initial model, including: depreciation
of production capacity, decision mechanism to
increase manufacturing capability, dividends
payment and costs associated to production
factors. Additionally, the model has been simulated making use of the framework
provided by P-Lingua and MeCoSim, and
delivering a custom application based on
them to reproduce the virtual experiments. Finally, several scenarios have been
analysed focusing on different elements
included in the model.

Román, G.
(2019). **Inference of bounded L systems with polymorphic P systems**. *Journal
of Membrane Computing*, *1*(1), 52–57. https://doi.org/10.1007/s41965-019-00007-0

In
this paper, we are going to solve the inference
problem of bounded L systems, namely
such L systems which work on filaments having
length up to a fixed size. We will show that these bounded L systems
have considerable computational power as they can simulate
linear-bounded automata. To carry out the inference, we are going to
construct a specific polymorphic P
system with target indication, which can
reproduce the transitions of the
examined bounded L system, and which is of size O(n|G|^{4}),
where G is the alphabet of the bounded L system with n as the maximal size of
the filaments.

Díaz-Pernil,
D., Gutiérrez-Naranjo, M. A., & Peng, H. (2019). **Membrane
computing and image processing: a short survey**. *Journal of Membrane
Computing*, *1*(1), 58–73. https://doi.org/10.1007/s41965-018-00002-x

Membrane
computing is a well-known research area in computer science inspired by the
organization and behavior of live cells and tissues. Their computational
devices, called P systems, work in parallel and distributed mode and the
information is encoded by multisets in a localized manner. All these features
make P systems appropriate for dealing with digital
images. In this paper, some of the open
research lines in the area are presented, focusing on segmentation problems, skeletonization and algebraic-topological
aspects of the images. An extensive bibliography
about the application of membrane computing to the study of digital
images is also provided.

**Volume 1 Issue 2**

Leporati, A., Manzoni,
L., Mauri, G., Porreca, A. E., & Zandron, C. (2019). **Characterizing
PSPACE with shallow non-confluent P systems**. *Journal of Membrane
Computing*, *1*(2), 75–84. https://doi.org/10.1007/s41965-019-00011-4

In
P systems with active membranes, the question of understanding the power of non-confluence within a polynomial time bound is still an open problem. It is known that, for shallow P systems, that is, with only one
level of nesting, non-confluence allows them to solve conjecturally harder problems than confluent P systems, thus
reaching **PSPACE**. Here we show that **PSPACE**
is not only a bound, but actually an exact
characterization. Therefore, the power endowed by non-confluence to shallow P
systems is equal to the power gained by confluent P systems when non-elementary membrane division and polynomial depth
are allowed, thus suggesting a connection between the roles of non-confluence and nesting depth.

Orellana-Martín,
D., Valencia-Cabrera, L., Riscos-Núñez, A., & Pérez-Jiménez,
M. J. (2019). **Minimal cooperation as a way to achieve the efficiency in
cell-like membrane systems**. *Journal of Membrane Computing*, *1*(2),
85–92. https://doi.org/10.1007/s41965-018-00004-9

Cooperation is doubtless a relevant ingredient on rewriting rules based computing models. This
paper provides an overview on both classical
and newest results studying how cooperation among objects influences the
ability of cell-like membrane systems to solve computationally hard problems in
an efficient way. In this paper, two types of such membrane systems will be
considered: (a) polarizationless
P systems with active membranes without
dissolution rules when minimal
cooperation is permitted in object evolution rules; and (b) cell-like
P systems with symport/antiport
rules of minimal length. Specifically,
assuming that **P** is not equal to **NP**, several frontiers of the efficiency are obtained in
these two computing frameworks, in such manner that each borderline provides a
tool to tackle the **P** versus **NP** problem.

Pérez-Hurtado,
I., Orellana-Martín, D.,
Zhang, G., & Pérez-Jiménez, M. J. (2019). **P-Lingua in two
steps: flexibility and efficiency**. *Journal of Membrane Computing*, *1*(2),
93–102. https://doi.org/10.1007/s41965-019-00014-1

Membrane
computing is a bio-inspired computing paradigm that lacks in vivo
implementation. That is why software or
hardware implementations have to be used to validate models. Several tools
have been created for this purpose; some of them are created for specific purposes, such as solving a
computationally hard problem; and others are more generic,
to cover a broad spectrum of possible models. The former have the advantage of
being very efficient, crucial for solving large
instances of certain problems; however, this efficiency leads to a loss of generality, since algorithms are
usually hard-coded and they do not allow other models. On the contrary, the
latter are perfect tools for researchers,
given that new models can be checked
without much effort by defining them in the
framework; since these algorithms have to simulate as many models as possible, they lack specificities to improve the performance. P-Lingua has been widely used to simulate membrane systems, having integrated
both a language and a simulator. To
obtain better results in terms of time used to
simulate models defined in this language, a new perspective is studied. The model defined in P-Lingua will
be compiled into C++ source code that
will implement an ad hoc simulator. This
code will consider specifications about how
rules have to be executed, that is, some simple
specifications of the semantics. To show how it works, some examples of specifications of models will be
presented, which can be simulated using the new-developed GNU GPLv3 command-line tool *pcc*.

Nash, A., & Kalvala,
S. (2019). **A P system model of swarming and aggregation in a Myxobacterial
colony**. *Journal of Membrane Computing*, *1*(2), 103–111. https://doi.org/10.1007/s41965-019-00015-0

Bacterial communities provide an interesting
subject for the study of emergence and
complexity as the consequence of many local
interactions. In particular, the soil-dwelling
social bacterium Myxobacteria
demonstrates two distinct types of motility, social
motility via the sensing of bacterial
slime deposits and adventurous motility.
Both modes of motility are governed by local interactions. Using P systems, a
membrane computing methodology based on compartmental rewrite rules for modelling
computational processes; this work demonstrates how minimal set of rules can model swarming
and aggregating behaviour in Myxobacteria bacterial populations. Our model
uses a multi-environment P system
similar a 2D cellular automaton to
represent the substrate environment
whilst stochastic rule selection
dictates Myxobacterial motion according to behaviour observed in vitro. The rules account for both
mechanisms of motility, the deposit and
detection of slime, a change in
direction due to C-signal induction
and the mixing of population numbers.
Simulations demonstrate an extensible computational framework for the modelling
of bacterial behaviour, with the potential for extension into additional emergent behaviours.

Cooper, J.,
& Nicolescu, R. (2019). **Alternative representations of P systems
solutions to the graph colouring problem**. *Journal of Membrane Computing*,
*1*(2), 112–126. https://doi.org/10.1007/s41965-019-00013-2

This
paper first presents a simulation of the simple
kernel P systems solution to the graph
3-colouring problem presented in a previous paper by Gheorghe et al.,
implemented in a programming style named Concurrent ML,
which is based on the concept of synchronous
communication between logical processing
elements. This paper then presents and informally analyses an alternative compact single-cell solution to
the same problem using P systems with compound
objects (cP systems), which has the benefit of naturally adapting to the use of any number of colours
greater than zero—only the specified colour symbols need to be changed. Successful and failing examples of the latter
solution are also presented.

Mitrana, V.
(2019). **Polarization: a new communication protocol in networks of
bio-inspired processors**. *Journal of Membrane Computing*, *1*(2),
127–143. https://doi.org/10.1007/s41965-018-0001-9

This
work is a survey of the most recent results regarding the computational power of the networks of bio-inspired processors
whose communication is based on a new protocol called polarization. In the former models, the communication amongst
processors is based on filters defined
by some random-context conditions,
namely the presence of some symbols and
the absence of other symbols. In the new
protocol discussed here, a polarization (negative, neutral, and positive) is
associated with each node, while the polarization of data navigating through the
network is computed in a dynamical way
by means of a valuation function.
Consequently, the protocol of communication
amongst processors is naturally based on
the compatibility between their polarization
and the polarization of the data. We consider here three types of bio-inspired processors: evolutionary
processors, splicing processors, and multiset processors. A quantitative generalization of polarization (evaluation sets) is also presented. We recall
results regarding the computational power of these networks considered as accepting devices. Furthermore, a solution to
an intractable problem, namely the 0 / 1 Knapsack problem, based on the
networks of splicing processors with
evaluation sets considered as problem solving
devices, is also recalled. Finally, we discuss some open problems and possible directions for
further research in this area.

**Volume 1 Issue 3**

Jimenez, Z. B., Cabarle,
F. G. C., de la Cruz, R. T. A., Buño, K. C., Adorna, H. N., Hernandez,
N. H. S., & Zeng, X. (2019). **Matrix representation and simulation algorithm
of spiking neural P systems with structural plasticity**. *Journal of
Membrane Computing*, 1(3), 145–160. https://doi.org/10.1007/s41965-019-00020-3

In
this paper, we create a matrix representation
for spiking neural P systems with structural
plasticity (SNPSP, for short), taking inspiration from existing
algorithms and representations for related variants. Using our matrix
representation, we provide a simulation
algorithm for SNPSP systems. We prove that the algorithm correctly simulates an SNPSP system: our
representation and algorithm are able to capture the syntax and semantics of SNPSP systems, e.g. plasticity rules, dynamism in the synapse set.
Analyses of the time and space complexity
of our algorithm show that its implementation can benefit
using parallel computers. Our representation and simulation algorithm
can be useful when implementing SNPSP systems and related variants with a dynamic topology, in software or hardware.

Cruz, R. T. A.
D. L., Cabarle, F. G., & Adorna, H. N. (2019). **Generating
context-free languages using spiking neural P systems with structural
plasticity**. *Journal of Membrane Computing*, 1(3), 161–177. https://doi.org/10.1007/s41965-019-00021-2

Spiking
neural P system (SNP system) is a model of computation inspired by networks of
spiking neurons. An SNP system is a network of neurons that can send an object,
known as a spike, to each other. Spiking neural P system with structural plasticity (SNPSP system) is a
variant of the classical SNP system. SNPSP system that incorporates the ideas
of synaptogenesis (creating new
synapses) and synaptic pruning (deletion
of existing synapses), collectively known as structural plasticity, as features
of the model. This gives SNPSP systems the ability to change their own structure/topology. In this work, we use SNPSP
systems to generate context-free
languages. We create a procedure for constructing an SNPSP system given a
context-free grammar in Greibach normal form
(GNF). The resulting SNPSP system essentially simulates
the way in which a context-free grammar in GNF is used to generate languages. We use modules known as arithmetic-memory modules, also created using
SNPSP systems, to perform arithmetic operations
which are needed for the simulation.

Ciencialová,
L., Csuhaj-Varjú, E., Cienciala, L., & Sosík, P. (2019). **P colonies**.
*Journal of Membrane Computing*, 1(3), 178–197. https://doi.org/10.1007/s41965-019-00019-w

P colonies
are abstract computing devices modelling
communities of very simple reactive
agents living and acting in a joint
shared environment. The concept was motivated by so-called colonies, grammar systems based on interplay of very
simple agents, on one hand, and by
membrane systems, massively parallel computational models inspired by cell
biology, on the other hand. Some variants of P colonies also allow the environment to participate actively
in the system’s evolution. In this paper we summarize
the most important results on P colonies, present open
problems concerning these constructs, and suggest
new research directions in their study.

Sosík, P.
(2019). **P systems attacking hard
problems beyond NP****: a survey**. *Journal of Membrane Computing*,
1(3), 198–208. https://doi.org/10.1007/s41965-019-00017-y

In
the field of membrane computing, a great attention is traditionally paid
to the results demonstrating a theoretical possibility to solve NP-complete problems in polynomial time
by means of various models of P systems. A bit less
common is the fact that almost all models of P systems with this
capability are actually stronger: some
of them are able to solve PSPACE-complete
problems in polynomial time, while others have been recently shown to
characterize the class **P ^{#P}**
(which is conjectured to be strictly included in

Valencia-Cabrera,
L., Orellana-Martín, D., Martínez-del-Amor, M. Á., & Pérez-Jiménez,
M. J. (2019). **An interactive timeline of simulators in membrane computing**.
*Journal of Membrane Computing*, 1(3), 209–222. https://doi.org/10.1007/s41965-019-00016-z

As
with any fast-emerging research front in computer science, the proliferation of
theoretical and practical results within Membrane computing since its
appearance in 1998 was astonishing. As a consequence, it became necessary
during the subsequent years to produce several surveys collecting the main
achievements from a theoretical point of view, along with some specific surveys about simulation tools for this
paradigm. As the discipline has reached a certain degree of maturity, more practical applications have arisen, and new
collective works are summarising the new software
products appeared. However, while these recapitulation efforts remain
useful for details about new simulators, they cannot act as exhaustive updated listings, as they become
obsolete as soon as new tools are developed. Thus, we considered that it was
necessary to provide an interactive tool
showing an updated timeline (https://www.gcn.us.es/SimulationMC)
about the simulation of the computational devices of membrane computing (a.k.a
P systems), aiming to stay updated whenever any new practical work comes out in
the discipline. This paper recalls the main stages and milestones within the evolution of simulation tools for different types and variants of P systems, along with
their main related applications. In addition, it describes the interactive web tool with the timeline mentioned, where
all the references related here have been incorporated. Unlike other survey
papers, it is the intent of this work to reinforce this initial collective
effort with the web endpoint kept alive and updated.

Manca, V.
(2019). **Metabolic computing**. *Journal of Membrane Computing*, 1(3),
223–232. https://doi.org/10.1007/s41965-019-00012-3

The
paper reviews some aspects of MP grammars,
a particular type of P systems (M stands for Metabolic) consisting of multiset
rewriting rules, which were introduced in the context of Membrane Computing,
for modeling biological dynamics. The
main features of MP theory are recalled,
such as the control mechanisms based on regulation functions, MP graphs, representation of oscillatory
dynamics, regression algorithms,
and MP modeling. Finally, the computational universality
of MP grammars is proved by means of Minsky’s register machines.

**Volume 1 Issue 4**

Aman, B., & Ciobanu,
G. (2019). **Synchronization of rules in membrane computing**. *Journal of
Membrane Computing*, *1*(4), 233–240. https://doi.org/10.1007/s41965-019-00022-1

We
modify the most used evolution strategy in membrane systems (namely that of
maximal parallelism) by imposing a synchronization
between rules. A synchronization over a set of rules can be applied only if each rule of the set can be applied at
least once. For membrane systems working in the accepting
mode, this synchronization is powerful enough to provide the computational completeness without any other
ingredient (no catalysts, promoters, inhibitors, etc). The modeling power of synchronization is described
by simulating the basic arithmetic operations
(addition, subtraction, multiplication and division).

Ţurlea, A., Gheorghe, M., Ipate, F.,
& Konur, S. (2019). **Search ‑ based testing in membrane computing**.
*Journal of Membrane Computing*, *1*(4), 241–250. https://doi.org/10.1007/s41965-019-00027-w

Search-based testing is widely used for generating test sets.
It is also applied in the case of model-based
testing, especially for (extended)
finite state machines. In this paper, we define such an approach for kernel P system models. We consider a specific
kernel P system model and a define a search-based testing method. The test set generated consists of input sequences producing a given computation
defined by the model. An example illustrates
the use of the introduced method.

Gazdag, Z.,
& Kolonits, G. (2019). **A new method to simulate restricted variants of polarizationless
P systems with active membranes**. *Journal of Membrane Computing*, *1*(4),
251–261. https://doi.org/10.1007/s41965-019-00024-z

According
to the P conjecture by Gh. Păun, polarizationless
P systems with active membranes cannot solve NP-complete problems in polynomial
time. The conjecture is proved only in special
cases yet. In this paper we consider the case where only elementary membrane division and dissolution
rules are used and the initial membrane structure consists of one elementary membrane besides the skin
membrane. We give a new approach based
on the concept of object division polynomials
introduced in this paper to simulate certain
computations of these P systems. Moreover, we show how to compute efficiently the result of these
computations using these polynomials.

Buiu, C., &
George, A. (2019). **Membrane computing models and robot controller design ,
current results and challenges**. *Journal of Membrane Computing*, *1*(4),
262–269. https://doi.org/10.1007/s41965-019-00029-8

Designing membrane controllers for single- and multi-robot systems is an
application area initiated in 2011 at the Laboratory of Natural Computing and
Robotics (natuRO) of the Politehnica University of Bucharest. In this paper, an
overview of natuRO’s research on the design of robot controllers based on various
models of membrane systems is given. After an introduction to robotics and
natural computing, this paper follows multiple directions. Firstly, a
description of three membrane system simulators
is given, taking into account their evolution,
comparative capabilities, and application areas for each of them.
Secondly, the main part of this paper is a synopsis
of the applications of membrane systems in robot
control, while an emphasis is paid to the new
membrane computing models introduced at natuRO, Enzymatic Numerical P Systems and XP
colonies, and their specific use in
single- and multiple-robot applications. Thirdly, the paper continues
with a critical overview of the performances
of membrane controllers as compared to traditional ways to control
single- and multiple-robot systems, current challenges
and possible ways to overcome these.
Example avenues for future related works
are given in the conclusion.

Jiang, Y., Su,
Y., & Luo, F. (2019). **An improved universal spiking neural P system with
generalized use of rules**. *Journal of Membrane Computing*, *1*(4),
270–278. https://doi.org/10.1007/s41965-019-00025-y

Taken
inspiration from biological phenomenon that neurons communicate via spikes, spiking neural P systems (SN P systems, for
short) are a class of distributed and parallel computing devices. So far firing rules in most of the SN P systems
usually work in a sequential way or in
an exhaustive way. Recently, a combination of the two ways mentioned above is
considered in SN P systems. This new strategy of using rules, which is called a
generalized way of using rules, is
applicable for both firing rules and forgetting
rules. In SN P systems with generalized use of rules (SNGR P systems, for short), if a rule is used at some step, it
can be applied any possible number of times, nondeterministically
chosen. In this work, the computational
completeness of SNGR P systems is investigated. Specifically, a universal SNGR P system is constructed, where
each neuron contains at most 5 rules,
and for each time each firing rule consumes at
most 6 spikes and each forgetting rule
removes at most 4 spikes. This result makes an improvement regarding to these related parameters, thus provides
an answer to the open problem mentioned in original work. Moreover, with this
improvement we can use less resources
(neurons and spikes involved in the evolution of system) to construct universal
SNGR P systems.

Andonie, R. (2019). **Hyperparameter
optimization in learning systems**. *Journal of
Membrane Computing*, 1(4), 279-291. https://doi.org/10.1007/s41965-019-00023-0

While
the training parameters of machine learning models are adapted during the training phase, the values of the hyperparameters (or
meta-parameters) have to be specified before
the learning phase. The goal is to find
a set of hyperparameter values which gives us the best model for our data in a reasonable amount of time. We present an integrated view of methods used in hyperparameter
optimization of learning systems, with an emphasis on computational complexity aspects. Our thesis is that we should solve a hyperparameter optimization problem
using a combination of techniques for: optimization,
search space and training time reduction. Case
studies from real-world applications illustrate
the practical aspects. We create the framework
for a future separation between parameters and hyperparameters in adaptive P systems.

Manca, V.
(2019). **From biopolymer duplication to membrane duplication and beyond**. *Journal
of Membrane Computing*, *1*(4), 292–303.
https://doi.org/10.1007/s41965-019-00018-x

The
relationship between biopolymer duplication
and membranes compartmentation is
analyzed, by stressing their intertwinement and the different monomers that determine
their forms of aggregation (linear and circular) with their functions. Both polymers and membranes are prebiotic forms of molecular assemblies, but in their integration the seed of life emerges. From membranes hosting a
replicative metabolism cells stem as
living unities, where an almost perfect synthesis is realized between
metabolism and duplication. What is missing to perfection becomes the basis of
evolution. The whole logic of the processes at the origin of life is
reconstructed in general terms, in the line of Manca (Infobiotics: information
in biotic systems. Springer, New York, 2013),
Manca (J Proteom Bioinform 11(7), 135–137, 2018)
and Manca and Santagata (Un meraviglioso accidente. La nascita della vita. Mondadori, Italy, 2018),
with no biochemistry detail, but only on the basis of the needs for representing, conserving, developing, and
transmitting biological information.

**Online First **(as of 15.02.2020, check https://link.springer.com/journal/41965/onlineFirst
for updates)

Andreu-Guzmán,
J. A., Valencia-Cabrera, L. **A novel solution for GCP based on an OLMS
membrane algorithm with dynamic operators**. *Journal of Membrane Computing*,
https://doi.org/10.1007/s41965-019-00026-x

Graph coloring problem (GCP) is an NP-complete combinatorial
optimization problem. Its computational complexity motivated many
efforts to get approximate solutions
through different meta-heuristics, such
as several variants of evolutionary algorithms.
On the other hand, membrane algorithms have appeared as alternative hybrid
techniques merging together the structure and operators of membrane systems,
along with the capabilities of optimization
algorithms inside each membrane. This paper explores the ability of a
new variants of one-level membrane systems
using a recent variant of evolutionary algorithm dynamically
using different genetic operators
depending on the best fitness found. The
experimental results presented show that
this new algorithm, called DOGAPS,
outperforms the dynamic evolutionary
algorithm, with the extra value provided by the membrane system. Additionally,
the role of some parameters involved in
our algorithm are analyzed, including
the number of membranes, iterations per membrane or mutation rate.

Freund, R. **How
derivation modes and halting conditions may influence the computational power
of P systems**. *Journal of Membrane Computing*, https://doi.org/10.1007/s41965-019-00030-1

In
the area of P systems, besides the standard maximally parallel derivation mode,
many other derivation modes have been
investigated, too. In this overview paper, many variants of hierarchical P systems using different
derivation modes are considered and the effects
of using different derivation modes, especially the maximally parallel
derivation modes and the maximally parallel set
derivation modes, on the generative and
accepting power are illustrated. Moreover, an overview on some control mechanisms used for P systems is
given. Furthermore, besides the standard total halting, we also consider different halting conditions such as unconditional halting and partial halting and explain how the use of
different halting conditions may considerably
change the computing power of P systems.

Calude, C. S., Dinneen,
M. J., Hua, R. **Quantum solutions for densest k-subgraph problems**.

In this paper, we present, for the first time, quantum annealing solutions for densest k-subgraph problems which have many applications in computational biology. Our solutions are formulated as solutions for quadratic unconstrained binary optimization (QUBO) and integer programming problems, proved to be equivalent with the densest k-subgraph problems and then tested on an D-Wave 2X machine. The QUBO formulations are optimal in terms of the number of logical qubits, but require the highest number of physical qubits after embedding. Experimental work reported here suggests that the D-Wave 2X model cannot handle problems of this difficulty. The next generation of D-wave hardware architecture—the Pegasus architecture—is much denser than the current one, so dense QUBOs will be easier to embed. The experimental work also suggests that the current built-in post-processing optimization method does not work very well for some problems and the default setting (post-processing optimization on) should be avoided (or at least tested before being turned on).