This contribution focuses on the modeling and performance analysis of the manufacturing process for transport platforms at the Alimak Group facility in La Muela, Spain. The objective is to leverage formal tools to gain insights into this complex manufacturing process and explore potential applications such as control and optimization. This work presents a preliminary study, where a Generalized Stochastic Petri net model of the manufacturing process is proposed to be used for simulation, performance analysis, and optimization of the system.

This paper presents a novel approach to analyze and optimize healthcare systems based on clinical pathways, using timed continuous Petri nets (TCPNs) under infinite server semantics. TCPNs allow for an efficient continuous-time analysis of the patient flow and resource utilization dynamics of these types of systems. We demonstrate the feasibility and effectiveness of our method through a case study of a hip fracture pathway at the "Lozano Blesa" University Clinical Hospital, in Zaragoza Spain. Additionally, we propose a method to optimize the behavior of the modeled system by taking a control theory approach, which enables the system to achieve maximum throughput more efficiently. Finally, we provide simulation results to demonstrate the effectiveness of the proposed controller in practical settings.

MOTIVATION: Despite the fact that antimicrobial resistance is an increasing health concern, the pace of production of new drugs is slow due to the high cost and uncertain success of the process. The development of high-throughput technologies has allowed the integration of biological data into detailed genome-scale models of multiple organisms. Such models can be exploited by means of computational methods to identify system vulnerabilities such as chokepoint reactions and essential reactions. These vulnerabilities are appealing drug targets that can lead to novel drug developments. However, the current approach to compute these vulnerabilities is only based on topological data and ignores the dynamic information of the model. This can lead to misidentified drug targets. RESULTS: This work computes flux constraints that are consistent with a certain growth rate of the modelled organism, and integrates the computed flux constraints into the model to improve the detection of vulnerabilities. By exploiting these flux constraints, we are able to obtain a directionality of the reactions of metabolism consistent with a given growth rate of the model, and consequently, a more realistic detection of vulnerabilities can be performed. Several sets of reactions that are system vulnerabilities are defined and the relationships among them are studied. The approach for the detection of these vulnerabilities has been implemented in the Python tool CONTRABASS. Such tool, for which an online web server has also been implemented, computes flux constraints and generates a report with the detected vulnerabilities. AVAILABILITY AND IMPLEMENTATION: CONTRABASS is available as an open source Python package at https://github.com/openCONTRABASS/CONTRABASS under GPL-3.0 License. An online web server is available at http://contrabass.unizar.es. SUPPLEMENTARY INFORMATION: A glossary of terms are available at Bioinformatics online.

BACKGROUND: Many biological systems exhibit sustained stochastic oscillations in their steady state. Assessing these oscillations is usually a challenging task due to the potential variability of the amplitude and frequency of the oscillations over time. As a result of this variability, when several stochastic replications are averaged, the oscillations are flattened and can be overlooked. This can easily lead to the erroneous conclusion that the system reaches a constant steady state. RESULTS: This paper proposes a straightforward method to detect and asses stochastic oscillations. The basis of the method is in the use of polar coordinates for systems with two species, and cylindrical coordinates for systems with more than two species. By slightly modifying these coordinate systems, it is possible to compute the total angular distance run by the system and the average Euclidean distance to a reference point. This allows us to compute confidence intervals, both for the average angular speed and for the distance to a reference point, from a set of replications. CONCLUSIONS: The use of polar (or cylindrical) coordinates provides a new perspective of the system dynamics. The mean trajectory that can be obtained by averaging the usual cartesian coordinates of the samples informs about the trajectory of the center of mass of the replications. In contrast to such a mean cartesian trajectory, the mean polar trajectory can be used to compute the average circular motion of those replications, and therefore, can yield evidence about sustained steady state oscillations. Both, the coordinate transformation and the computation of confidence intervals, can be carried out efficiently. This results in an efficient method to evaluate stochastic oscillations.

The paradigm of Petri nets offers a rich modeling power that has been successfully exploited in many different application domains as manufacturing, logistic, traffic, computer and biological domains. In order to develop and analyze Petri models in an efficient and systematic way, appropriate software tools are required. Among the existing software platforms for scientific software development, MATLAB places at the user's disposal a large set of toolboxes with an inutitive graphical interface. This paper describes some of the existing Petri net toolboxes that have been developed on MATLAB, and that cover the needs for the modeling and analysis of discrete, continuous and hybrid systems.

Many artificial systems can be modeled as discrete dynamic systems in which resources are shared among different tasks. The performance of such systems, which is usually a system requirement, heavily relies on the number and distribution of such resources. The goal of this paper is twofold: first, to design a technique to estimate the steady-state performance of a given system with shared resources, and second, to propose a heuristic strategy to distribute shared resources so that the system performance is enhanced as much as possible. The systems under consideration are assumed to be large systems, such as service-oriented architecture (SOA) systems, and modeled by a particular class of Petri nets (PNs) called process PNs. In order to avoid the state explosion problem inherent to discrete models, the proposed techniques make intensive use of linear programming (LP) problems.

With the scaling of process technologies, communication delays represent a bottleneck for the performance of circuits. One of the main issues that has to be handled is the variability of such delays. Latency-insensitive circuits offer a form of elast

Traffic systems are often highly populated discrete event systems that exhibit several modes of behavior such as free flow traffic, traffic jams, stop-and-go waves, etc. An appropriate closed loop control of the congested system is crucial in order to avoid undesirable behavior. This paper proposes a macroscopic model based on continuous Petri nets as a tool for designing control laws that improve the behavior of traffic systems. The main reason to use a continuous model is to avoid the state explosion problem inherent to large discrete event systems. The obtained model captures the different operation modes of a traffic system and is highly compositional. In order to handle the variability of the traffic conditions, a model predictive control strategy is proposed and validated.

Retiming and recycling are two transformations used to optimize the performance of latency-insensitive (a.k.a. synchronous elastic) systems. This paper presents an approach that combines these two transformations for performance optimization of elastic systems with early evaluation. The method is based on Mixed Integer Linear Programming.

Buffer resizing and buffer insertion are two transformation techniques for the performance optimization of elastic systems. Different approaches for each technique have already been proposed in the literature. Both techniques increase the storage capacity and can potentially contribute to improve the throughput of the system. Each technique offers a different trade-off between area cost and latency. This paper presents a method that combines both techniques to achieve the maximum possible throughput while minimizing the cost of the implementation. The provided method is based on mixed integer linear programming. A set of experiments is designed to show the feasibility of the approach.

This paper is devoted both to the study of observability criteria and the design of observers in the continuous Petri net setting. The concept of structural observability, regarding the possibility of estimating the marking of places, i.e., the system state, for any speed of the transitions is introduced and studied for the subclass of join-free Petri nets (JF). For non-join-free Petri nets, conditions to compute suitable state estimates are established. The proposed observers are piecewise linear systems that assure the continuity of the estimate even when a switch occurs. The system simulation may allow us to estimate even the unobservable space of the net system during a given time period.

Early evaluation allows to execute operations when enough information at the inputs has been received to determine the value at the outputs. Systems that can tolerate variable-latency units, such as latency-insensitive or asynchronous systems, can enhance their performance by using early evaluation. The most relevant example of a unit with early evaluation is the multiplexor: the output can be determined as soon as the information of the selected channel arrives, without waiting for the other channels.

In this paper we deal with the problem of estimating the marking of a labeled Petri net with nondeterministic transitions. In particular, we consider the case in which nondeterminism is due to the presence of transitions that share the same label and that can be simultaneously enabled. Under the assumption that: the structure of the net is known, the initial marking is known, the transition labels can be observed, the nondeterministic transitions are contact-free, we present a technique for characterizing the set of markings that are consistent with the actual observation. More precisely, we show that the set of markings consistent with an observed word can be represented by a linear system with a fixed structure that does not depend on the length of the observed word.