Romanus Langerak

Multi-core nested depth-first search

The LTL Model Checking problem is reducible to finding accepting cycles in a graph. The Nested Depth-First Search (Ndfs) algorithm detects accepting cycles efficiently: on-the-fly, with linear-time complexity and negligible memory overhead. The only downside of the algorithm is that it relies on an inherently-sequential, depth-first search. It has not been parallelized beyond running the independent nested search in a separate thread (dual core). n nIn this paper, we introduce, for the first time, a multi-core Ndfs algorithm that can scale beyond two threads, while maintaining exactly the same worst-case time complexity. We prove this algorithm correct, and present experimental results obtained with an implementation in the LTSmin tool set on the entire Beem benchmark database. We measured considerable speedups compared to the current state of the art in parallel cycle detection algorithms.

ECHO: the executable chondrocyte

Publicado em Journal of tissue engineering and regenerative medicine. Vol. 8, suppl. s1 (2014)Introduction: Decellularized engineered extracellular matrices (ECM) are used in a variety of regenerative medicine applications. Existing decellularization strategies rely on cell lysis and generally result in a variable but significant impairment of the ECM structure/composition. As an alternative, we aimed at activating the apoptotic pathway in order to decellularize engineered matrices while preserving their osteo-inductive properties [1]. Materials and methods: We generated a death-inducible, immortalized human Mesenchymal Stromal Cell (hMSC) line [2]. Cells were seeded on ceramic scaffolds and cultured for 4 weeks in osteogenic medium in a 3D perfusion bioreactor system (U-cup, Cellec). The ECM was decellularized by direct supply of the apoptotic inducer in the 3D culture system. Grafts were implanted in a rat cranial defect model to assess their regenerative potential after 12 weeks. Results: Cells were successfully seeded and differentiated, leading to deposition of a dense ECM during 3D culture. The apoptosis induction allowed for efficient decellularization while preserving the secreted matrix. These “apoptized” cell-free ECM coated constructs induced superior bone regeneration than control materials (Fig. 2). Areas of de novo bone formation not connected with surrounding bone suggest osteoinductive properties of the grafts.

Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer

BACKGROUNDnWith the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required.nnnOBJECTIVESnTo illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions.nnnMETHODSnAn early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed.nnnRESULTSnBoth models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure.nnnCONCLUSIONSnBoth techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems.

ANIMO: a tool for modeling biological pathway dynamics

Publicado em Journal of tissue engineering and regenerative medicine. Vol. 8, suppl. s1 (2014)Introduction: Decellularized engineered extracellular matrices (ECM) are used in a variety of regenerative medicine applications. Existing decellularization strategies rely on cell lysis and generally result in a variable but significant impairment of the ECM structure/composition. As an alternative, we aimed at activating the apoptotic pathway in order to decellularize engineered matrices while preserving their osteo-inductive properties [1]. Materials and methods: We generated a death-inducible, immortalized human Mesenchymal Stromal Cell (hMSC) line [2]. Cells were seeded on ceramic scaffolds and cultured for 4 weeks in osteogenic medium in a 3D perfusion bioreactor system (U-cup, Cellec). The ECM was decellularized by direct supply of the apoptotic inducer in the 3D culture system. Grafts were implanted in a rat cranial defect model to assess their regenerative potential after 12 weeks. Results: Cells were successfully seeded and differentiated, leading to deposition of a dense ECM during 3D culture. The apoptosis induction allowed for efficient decellularization while preserving the secreted matrix. These “apoptized” cell-free ECM coated constructs induced superior bone regeneration than control materials (Fig. 2). Areas of de novo bone formation not connected with surrounding bone suggest osteoinductive properties of the grafts.

A composition operator for systems with active and passive actions

We investigate requirements for a composition operator for complex control systems. The operator should be suitable for a context where we have both supervisory control and a system that consists of multiple (two or more) components. We conclude that using both passive (observing) and active (controlling) transitions is advantageous for the specification of supervisory control systems. We introduce a composition operator that meets the requirements. We give both operational and trace semantics for this operator and give necessary and sufficient conditions for commutativity and associativity.

Deriving a Graph Rewriting System from a Complete Finite Prefix of an Unfolding

The starting point of this paper is McMillans complete finite prefix of an unfolding that has been obtained from a Petri net or a process algebra expression. The paper addresses the question of how to obtain the (possibly infinite) system behaviour from the complete finite prefix. An algorithm is presented to derive from the prefix a graph rewriting system that can be used to construct the unfolding. It is shown how to generate event sequences from the graph rewriting system which is important for constructing an interactive simulator. Finally it is indicated how the graph rewriting system yields a transition system that can be used for model checking and test derivation.

Discretization of Continuous Dynamical Systems Using UPPAAL

We want to enable the analysis of continuous dynamical systems (where the evolution of a vector of continuous state variables is described by differential equations) by model checking. We do this by showing how such a dynamical system can be translated into a discrete model of communicating timed automata that can be analyzed by the UPPAAL tool. The basis of the translation is the well-known Euler approach for solving differential equations where we use fixed discrete value steps instead of fixed time steps. Each state variable is represented by a timed automaton in which the delay for taking the next value is calculated on the fly using the differential equations. The state variable automata proceed independently but may notify each other when a value step has been completed; this leads to a recalculation of delays. The approach has been implemented in the tool ANIMO for analyzing biological kinase networks in cells. This tool has been used in actual biological research on osteoarthritis dealing with systems where the dimension of the state vector (the number of nodes in the network) is in the order of one hundred.

ModelEd, TestEd, TrustEd : Essays Dedicated to Ed Brinksma on the Occasion of His 60th Birthday

This Festschrift volume has been published in honor of Ed Brinksma, on the occasion of his 60th birthday. The contributions in this Festschrift are written by a number of Eds former Ph.D. students and collaborators. The papers are a reflection on his research contributions and interests and all fall into the area of formal methods, or in Eds terminology applied mathematics in computer science. The papers address modeling languages and semantics, model-based testing, verification and performance analysis, probabilistic computation, system dynamics, and applications of formal methods.

PRM113 - Timed Automata Modeling of The Personalized Treatment Decisions In Metastatic Castration Resistant Prostate Cancer

Objectives: The Timed Automata modeling paradigm has emerged from Computer Science as a mature tool for the functional analysis and performance evaluation of timed distributed systems. This study is a first exploration of the suitability of Timed Automata for health economic modeling, using a case study on personalized treatment for metastatic Castration Resistant Prostate Cancer (mCRPC). Methods: The treatment process has been modeled by creating several independent timed automata, where an automaton represents a patient, a physician, a test, or a treatment/testing guideline schedule. These automata interact via message passing and are fully parameterized with quantitative information. Messages can be passed, asynchronously, from one automaton to one or more other automata, at any point in time, thereby triggering events and decisions in the treatment process. In the automata time is continuous, and both QALYs and costs can be incorporated using (assignable) local clocks. Uncertainty can be modeled using probabilities and timing intervals that can be uniformly or exponentially distributed. Software for building timed automata is freely available for academic use and includes procedures for statistical model checking (SMC) to validate the (internal) behavior and results of the model. Results: In several days a Timed Automata model has been produced that is compositional, easy to understand and easy to update. The behavior and results of the model have been assessed using the SMC tool. Actual results for the mCRPC case study obtained from the Timed Automata model are compared with results of a Discrete Event Simulation model in a separate study. Conclusions: The Timed Automata paradigm can be successfully applied to evaluate the potential benefits of a personalized treatment process of mCRPC. The compositional nature of the resulting model provides a good separation of all relevant components. This leads to models that are easy to formulate, validate, understand, maintain and update.

Comparison of Timed Automata with Discrete Event Simulation for Modeling Personalized Treatment Decisions: the Case of Metastatic Castration Resistant Prostate Cancer.

Objectives nThe aim of this study is to compare the usefulness of two promising alternative modeling techniques, Timed Automata (TA) originating from informatics, and Discrete Event Simulation (DES) known in operations research, for modeling todays complex and personalized treatment decisions over time, involving multiple interactions and decision gates. n nMethods nThe usefulness of both modeling techniques was assessed in a case study on the treatment of metastatic Castration Resistant Prostate Cancer (mCRPC) in which Circulating Tumor Cells (CTC) may be used as a response marker for switching first to second line treatment. Techniques were compared on user-friendliness, input requirements, input possibilities, model checking facilities, and results. Input parameters were similar for both models, consisting of costs, QoL, treatment effectiveness, diagnostic performance, physicians’ behavior and survival. Primary outcome measures were health outcomes, expressed in QALYs, and costs. n nResults nModelling was considered easier using TA, as this approach allows independent modeling of the actors and elements comprising the treatment process, such as patients, physicians, tests and treatments, and their mutual interaction and communication. Furthermore, the statistical model checking feature in the TA software was found to be a powerful tool for validation. Input requirements and possibilities were similar for both modelling approaches in this case study. Both modelling approaches yield comparable results. Using TA, CTC reduced first and second line treatment by, on average, 108.9 and 107.6 days, respectively. Using DES, treatment was reduced by 83.6 and 85.0 days. CTC therefore reduced healthcare costs by €28,998 and €21,992 according to TA and DES, respectively. n nConclusions nBoth Timed Automata and Discrete Event Simulation seem to be suitable for modeling complex and personalized treatment processes like that of mCRPC. Timed Automata is a new and interesting alternative modeling technique, as it allows explicit separation of model components and supports statistical model checking to validate models.