Yes / Spiking Neural (SN) P systems is a particular class of P systems that abstracts and applies ideas from neurobiology. Various aspects, representations and features have been studied extensively, but the tool support for modelling and analysing such systems is relatively limited. In this paper, we present a methodology that maps some classes of SN P systems to the equivalent kernel P system representations, which allows analysing SN P system dynamics using the kPWORKBENCH tool. We illustrate the applicability of our approach in some case studies, including an example system from synthetic biology.

Membrane Computing:Traces, Neural Inspired Models, ControlsAutor: Armand-Mihai IonescuDirectores: Dr. Victor Mitrana (URV)Dr. Takashi Yokomori (Universidad Waseda, Japón)Resumen Castellano:El presente trabajo está dedicado a una área muy activa del cálculo natural (que intenta descubrir la odalidad en la cual la naturaleza calcula, especialmente al nivel biológico), es decir el cálculo con membranas, y más preciso, a los modelos de membranas inspirados de la funcionalidad biológica de la neurona.La disertación contribuye al área de cálculo con membranas en tres direcciones principales. Primero, introducimos una nueva manera de definir el resultado de una computación siguiendo los rastros de un objeto especificado dentro de una estructura celular o de una estructura neuronal. A continuación, nos acercamos al ámbito de la biología del cerebro, con el objetivo de obtener varias maneras de controlar la computación por medio de procesos que inhiben/de-inhiben. Tercero, introducimos e investigamos en detallo - aunque en una fase preliminar porque muchos aspectos tienen que ser clarificados - una clase de sistemas inspirados de la manera en la cual las neuronas cooperan por medio de spikes, pulsos eléctricos de formas idénticas.English summary:The present work is dedicated to a very active branch of natural computing (which tries to discover the way nature computes, especially at a biological level), namely membrane computing, more precisely, to those models of membrane systems mainly inspired from the functioning of the neural cell.The present dissertation contributes to membrane computing in three main directions. First, we introduce a new way of defining the result of a computation by means of following the traces of a specified object within a cell structure or a neural structure. Then, we get closer to the biology of the brain, considering various ways to control the computation by means of inhibiting/de-inhibiting processes. Third, we introduce and investigate in a great - though preliminary, as many issues remain to be clarified - detail a class of P systems inspired from the way neurons cooperate by means of spikes, electrical pulses of identical shapes.

Yes / This paper represents a significant advance on the issue of testing for implementations specified by P systems with transformation and communicating rules. Using the X-machine framework and the concept of cover automaton, it devises a testing approach for such systems, that, under well defined conditions, it ensures that the implementation conforms to the specification. It also investigates the issue of identifiability for P systems, that is an essential prerequisite for testing implementations based on such specifications and establishes a fundamental set of properties for identifiable P systems. / Marian Gheorghe and Savas Konur acknowledge the support from EPSRC (EP/I031812/1). Marian Gheorghe’s and Florentin Ipate’s work is partially supported by CNCS-UEFISCDI (PN-II-ID-PCE-2011-3-0688).

No / Recent research in membrane computing examines and confirms the anticipated modelling potential of kernel P systems in several case studies. On the one hand, this computational model is destined to be an abstract archetype which advocates the unity and integrity of P systems onto a single formalism. On the other hand, this envisaged convergence is conceived at the expense of a vast set of primitives and intricate semantics, an exigent context when considering the development of simulation and verification methodologies and tools. Encouraged and guided by the success and steady progress of similar undertakings, in this paper we directly address the issue of formal verification of kernel P systems by means of model checking and unveil a software framework, kpWorkbench, which integrates a set of related tools in support of our approach. A case study that centres around the well known Subset Sum problem progressively demonstrates each stage of the proposed methodology: expressing a kP system model in recently introduced kP-Lingua; the automatic translation of this model into a Promela (Spin) specification; the assisted, interactive construction of a set of LTL properties based on natural language patterns; and finally, the formal verification of these properties against the converted model, using the Spin model checker.

No / In this short paper one overviews the two years development of kernel P systems (kP systems for short), a basic class of P systems combining features of different variants of such systems. The definition of kP systems is given, some examples illustrate various features of the model and the most significant results are presented.

Yes / P colonies, tissue-like P systems with very simple components, have received constant attention from the membrane computing community and in the last years several new variants of the model have been considered. Another P system model, namely kernel P system, integrating the most successfully used features of membrane systems, has recently attracted interest and some important developments have been reported. In this paper we study connections among several classes of P colonies and kernel P systems, by showing how the behaviour of these P colony systems can be represented as kernel P systems. An example illustrates the way it is modelled by using P colonies and kernel P systems and some properties of it are formally proved in the latter approach. / Grant No. K 120558 of the NKFIH—National Research, Development, and Innovation Office, Hungary; Romanian National Authority for Scientific Research, CNCS-UEFISCDI (Project No. PN-III-P4-ID-PCE-2016-0210).

Yes / Structural and behavioural properties of models are very important in development of complex systems and applications. In this paper, we investigate such properties for some classes of SN P systems. First, a class of SN P systems associated to a set of routing problems are investigated through their matrix representation. This allows to make certain connections amongst some of these problems. Secondly, the behavioural properties of these SN P systems are formally verified through a natural and direct mapping of these models into kP systems which are equipped with adequate formal verification methods and tools. Some examples are used to prove the effectiveness of the verification approach. / EPSRC research grant EP/R043787/1; DOST-ERDT research grants; Semirara Mining Corp; UPD-OVCRD;

Yes / A kernel P system integrates in a coherent and elegant manner some of the most successfully used features of the P systems employed in modelling various applications. It also provides a theoretical framework for analysing these applications and a software environment for simulating and verifying them. In this paper, we illustrate the modelling capabilities of kernel P systems by showing how other classes of P systems can be represented with this formalism and providing a number of kernel P system models for a sorting algorithm and a broadcasting problem. We also show how formal verification can be used to validate that the given models work as desired. Finally, a test generation method based on automata is extended to non-deterministic kernel P systems. / The work of MG, FI and RL were supported by a grant of the Romanian National Author- ity for Scientific Research, CNCS-UEFISCDI (project number: PN-II-ID-PCE-2011-3-0688); RCUK

No / Kernel P systems integrate in a coherent and elegant manner many of the features of different P system variants, successfully used for modelling various applications. In this paper, we present our initial attempt to extend the software framework developed to support kernel P systems: a formal verification tool based on the NuSMV model checker and a large scale simulation environment based on FLAME. The use of these two tools for modelling and analysis of biological systems is illustrated with a synthetic biology example.

Yes / Kernel P systems have been introduced as a unifying formalism allowing to specify, simulate and analyse various problems. Several applications of this model have been considered and a powerful tool built in order to support their development and analysis. Testing represents an important aspect of any system analysis and correctness. In this paper we introduce for the first time a bounded test generation approach for kernel P systems by considering bounded input sequences. A learning algorithm for kernel P systems is based on learning X-machine models that are equivalent to these systems for sequences of steps up to a certain limit, ℓ. The Lℓ learning algorithm is used. The testing approach is then devised from the inferred X-machines. The method is applied to a case study illustrating the key parts of the approach. / This research was supported by the European Regional Development Fund, Competitiveness Operational Program 2014-2020 through project IDBC (code SMIS 2014+: 121512). Raluca Lefticaru, Savas Konur and Marian Gheorghe have been partially supported by the Royal Society grant IES╲R3╲213176, 2022-2024. The work of Savas Konur is also supported by EPSRC (EP/R043787/1).