A model-based system, specifically designed for the automated modeling of the mechanical behavior... more A model-based system, specifically designed for the automated modeling of the mechanical behavior of viscoelastic materials, has been used to investigate the mucoadhesive performance of a class of polymers candidate for use as drug carriers within new-concept controlled-release delivery systems. Such an approach is cheaper than the traditional purely experimental one as well as more informative about the polymer-mucus interaction . The system integrates qualitative and quantitative techniques to make the most of the available heterogeneous and interdisciplinary knowledge with a consequent gain in computational efficiency and robustness.
This paper presents a qualitative model of iron metabolism. The model, based on QSIM formalism, i... more This paper presents a qualitative model of iron metabolism. The model, based on QSIM formalism, is able to provide qualitative predictions of the time course of iron content in the different body pools under a variety of pathogenetic mechanisms and therapeutical treatments, such as reduced iron absorption, reduced erythropoietic activity, increased red cells haemolysis, and single blood donation or loss. Moreover, we discuss how this model can be used to improve the performances of a knowledge base system, called NEOANEMIA, able to diagnose disorders causing anaemia.
This paper presents a computational approach to the generation of rheological models. A rheologic... more This paper presents a computational approach to the generation of rheological models. A rheological structure can be analogically described as a set of basic components connected in series or in parallel. The models are automatically created in two different forms: a symbolic qualitative relation and a mathematical equation. In both cases, the designed algorithm uses the same knowledge representation scheme which is based on rooted binary tree-like graphs. The mathematical model of a rheological structure, made up of n basic components, is built from the basic models of each component by exploiting connection laws. This work is part of a more ambitious project aiming at carrying out a system for automated reasoning about rheological systems. Beside a model-building task, such a system should perform a simulation and diagnostic task. Therefore it should provide methods for the simulation, both qualitative and quantitative, of the behavior of a rheological structure and methods for the identification of a model of an actual material, given its behavior.
ABSTRACT Describes part of an implemented system for the automated modeling of the mechanical beh... more ABSTRACT Describes part of an implemented system for the automated modeling of the mechanical behavior of materials. The paper focuses on the qualitative aspects. More precisely, it describes an algorithm for the qualitative simulation of the response of a visco-elastic material to both creep and relaxation experiments, and discusses some problems related to the qualitative interpretation of the experimental data. The authors' qualitative simulation algorithm is restricted to creep and relaxation experiments which are the most commonly performed because of the simplicity of their implementation with respect to the richness of the captured information
Mathematics and Computers in Simulation, Jul 1, 2016
Advanced experimental technologies have made the disclosure of networks of intricate regulatory i... more Advanced experimental technologies have made the disclosure of networks of intricate regulatory interactions between genes and gene products feasible and revealed their extreme complexity. Thus, understanding which particular dynamical behaviors derive from specific gene regulatory structures poses a challenging question, at both scientific and application level, that necessarily requires computational tools to be answered. Herein, we discuss the algorithmic aspects and the implementation of a mathematical method, grounded on singular perturbation analysis, for the study of the dynamics of regulated gene networks. This results in a gene regulatory network simulator of the full range of possible dynamics of a specific class of ordinary differential equations adequate to model gene regulatory networks. The considered class of equations represent phenomenological models of the long interaction chains in a network: genes are the main players and the interactions between them are modeled by steep threshold-dependent response functions. The simulator we propose operates in the presence of incomplete knowledge of parameter values. It assumes that threshold-dependent regulation is modeled by continuous steep sigmoid functions, and each transcription factor only regulates one gene at each of its thresholds. Under these assumptions, the simulator derives sound predictions of the nonlinear and temporal multiscale dynamics of a gene regulatory network from an initial state and parameter space, symbolically described by inequalities between parameters. Beside its predictive soundness, it outperforms other qualitative simulators as for characterization of trajectories and possible calculation of the probability of occurrence of each behavior when parameters are assigned stochastic values. Simulation tool of the nonlinear dynamics of gene network models.Generation of all the possible trajectories in a single run.Characterization of the qualitative properties of predicted trajectories.Calculation of the probability of occurrence of each simulated trajectory.
IEEE transactions on systems, man and cybernetics, 1998
ABSTRACT Automated model formulation is a crucial issue in the construction of computational envi... more ABSTRACT Automated model formulation is a crucial issue in the construction of computational environments that can reason about the behavior of a physical system. The procedure of mathematically modeling a physical system is complex and involves three fundamental entities: the experimental data, a set of candidate models, and rules for determining in such a set the “best” model that reproduces the measured data. The construction of the candidate models is domain dependent and based on specific knowledge and techniques of the application domain. The choice of the best model is guided by the data themselves; a first rough guess is refined through system identification techniques so that the quantitative properties of the observed behavior are assessed. Automating such a procedure requires handling and integrating different formalisms and methods, both qualitative and quantitative. The paper describes a comprehensive environment that aims at the automated formulation of an accurate quantitative model of the mechanical behavior of an actual viscoelastic material in accordance with the observed response of the material to standard experiments. Algorithms and methods for both the generation of an exhaustive library of models of ideal materials and the selection of the most “accurate” model of a real material have been designed and implemented. The model selection phase occurs in two main stages: first the subset of most plausible candidate models for the material is drawn from the library; then, the most accurate model of the material is identified by using both statistical and numerical methods
ABSTRACT To build model-based systems capable of emulating the scientist's or engineer&am... more ABSTRACT To build model-based systems capable of emulating the scientist's or engineer's way of reasoning about a given physical domain requires methods for automating the formulation or selection of a model which adequately captures the knowledge needed for solving a specific problem. To find and exploit such models requires the use and integration of different kinds of knowledge, formalisms and methods. This paper describes a system which aims at reasoning automatically about visco-elastic materials from a mechanical point of view. It integrates both domain-specific and domain-independent knowledge in order to classify and analyse the mechanical behaviour of materials. The classification task is based on qualitative knowledge, whereas the analysis of a material is performed at a quantitative level and is based on numerical simulation. The key ideas of the work are to automatically generate a library of models of ideal materials and their corresponding qualitative responses to standard experiments; to classify an actual material by selecting from within the library a class of models whose simulated qualitative behaviours towards standard loads match the observed behaviours; to identify a quantitative model of the material, and then to analyse the material by simulating its behaviour on any load. Each model in the library is automatically generated in two different forms; at the lowest level, as a symbolic description and, at a mathematical level, as an ordinary differential equation. This paper mainly concentrates on the methods and algorithms of model generation and qualitative simulation
Computer Methods and Programs in Biomedicine, Apr 1, 1994
This paper describes a framework, called QCMF (Qualitative Compartmental Modeling Framework), whi... more This paper describes a framework, called QCMF (Qualitative Compartmental Modeling Framework), which assists the user in formulating models of a pathophysiological system and in analyzing their behaviors through the simulation of the effects of a variety of pathogenetic mechanisms and therapeutical treatments. QCMF has adopted the compartmental theory as modeling ontology: a system is represented as a finite set of interacting compartments. The user enters, through an iconic language and menus, the compartmental structure of a pathophysiological system and the definition of the kinds of functional relationships describing the interactions between compartments. Then, QCMF automatically generates a behavior model of the system. Such a model consists of a set of ordinary differential equations, which are qualitatively expressed, and is directly coded into the language which is interpreted by the simulation algorithm. The system behavior can be obtained by simulating the model starting from an initial state which describes the perturbations acting on the system. The code defining the initial state is automatically built by QCMF as well. Finally, explanations of the predicted behavior are also automatically generated.
The last decade has witnessed major advancements in the direct application of functional imaging ... more The last decade has witnessed major advancements in the direct application of functional imaging techniques to several clinical contexts. Unfortunately, this is not the case of Electrocardiology. As a matter of fact, epicardial maps, which can hit electrical conduction pathologies that routine surface ECG's analysis may miss, can be obtained non invasively from body surface data through mathematical model-based reconstruction methods. But, their interpretation still requires highly specialized skills that belong to few experts. The automated detection of salient patterns in the map, grounded on the existing interpretation rationale, would therefore represent a major contribution towards the clinical use of such valuable tools, whose diagnostic potential is still largely unexploited. We focus on epicardial activation isochronal maps, which convey information about the heart electric function in terms of the depolarization wavefront kinematics. An approach grounded on the integration of a Spatial Aggregation (SA) method with concepts borrowed from Computational Geometry provides a computational framework to extract, from the given activation data, a few basic features that characterize the wavefront propagation, as well as a more specific set of features that identify an important class of heart rhythm pathologies, namely reentry arrhythmias due to block of conduction.
A model-based system, specifically designed for the automated modeling of the mechanical behavior... more A model-based system, specifically designed for the automated modeling of the mechanical behavior of viscoelastic materials, has been used to investigate the mucoadhesive performance of a class of polymers candidate for use as drug carriers within new-concept controlled-release delivery systems. Such an approach is cheaper than the traditional purely experimental one as well as more informative about the polymer-mucus interaction . The system integrates qualitative and quantitative techniques to make the most of the available heterogeneous and interdisciplinary knowledge with a consequent gain in computational efficiency and robustness.
This paper presents a qualitative model of iron metabolism. The model, based on QSIM formalism, i... more This paper presents a qualitative model of iron metabolism. The model, based on QSIM formalism, is able to provide qualitative predictions of the time course of iron content in the different body pools under a variety of pathogenetic mechanisms and therapeutical treatments, such as reduced iron absorption, reduced erythropoietic activity, increased red cells haemolysis, and single blood donation or loss. Moreover, we discuss how this model can be used to improve the performances of a knowledge base system, called NEOANEMIA, able to diagnose disorders causing anaemia.
This paper presents a computational approach to the generation of rheological models. A rheologic... more This paper presents a computational approach to the generation of rheological models. A rheological structure can be analogically described as a set of basic components connected in series or in parallel. The models are automatically created in two different forms: a symbolic qualitative relation and a mathematical equation. In both cases, the designed algorithm uses the same knowledge representation scheme which is based on rooted binary tree-like graphs. The mathematical model of a rheological structure, made up of n basic components, is built from the basic models of each component by exploiting connection laws. This work is part of a more ambitious project aiming at carrying out a system for automated reasoning about rheological systems. Beside a model-building task, such a system should perform a simulation and diagnostic task. Therefore it should provide methods for the simulation, both qualitative and quantitative, of the behavior of a rheological structure and methods for the identification of a model of an actual material, given its behavior.
ABSTRACT Describes part of an implemented system for the automated modeling of the mechanical beh... more ABSTRACT Describes part of an implemented system for the automated modeling of the mechanical behavior of materials. The paper focuses on the qualitative aspects. More precisely, it describes an algorithm for the qualitative simulation of the response of a visco-elastic material to both creep and relaxation experiments, and discusses some problems related to the qualitative interpretation of the experimental data. The authors' qualitative simulation algorithm is restricted to creep and relaxation experiments which are the most commonly performed because of the simplicity of their implementation with respect to the richness of the captured information
Mathematics and Computers in Simulation, Jul 1, 2016
Advanced experimental technologies have made the disclosure of networks of intricate regulatory i... more Advanced experimental technologies have made the disclosure of networks of intricate regulatory interactions between genes and gene products feasible and revealed their extreme complexity. Thus, understanding which particular dynamical behaviors derive from specific gene regulatory structures poses a challenging question, at both scientific and application level, that necessarily requires computational tools to be answered. Herein, we discuss the algorithmic aspects and the implementation of a mathematical method, grounded on singular perturbation analysis, for the study of the dynamics of regulated gene networks. This results in a gene regulatory network simulator of the full range of possible dynamics of a specific class of ordinary differential equations adequate to model gene regulatory networks. The considered class of equations represent phenomenological models of the long interaction chains in a network: genes are the main players and the interactions between them are modeled by steep threshold-dependent response functions. The simulator we propose operates in the presence of incomplete knowledge of parameter values. It assumes that threshold-dependent regulation is modeled by continuous steep sigmoid functions, and each transcription factor only regulates one gene at each of its thresholds. Under these assumptions, the simulator derives sound predictions of the nonlinear and temporal multiscale dynamics of a gene regulatory network from an initial state and parameter space, symbolically described by inequalities between parameters. Beside its predictive soundness, it outperforms other qualitative simulators as for characterization of trajectories and possible calculation of the probability of occurrence of each behavior when parameters are assigned stochastic values. Simulation tool of the nonlinear dynamics of gene network models.Generation of all the possible trajectories in a single run.Characterization of the qualitative properties of predicted trajectories.Calculation of the probability of occurrence of each simulated trajectory.
IEEE transactions on systems, man and cybernetics, 1998
ABSTRACT Automated model formulation is a crucial issue in the construction of computational envi... more ABSTRACT Automated model formulation is a crucial issue in the construction of computational environments that can reason about the behavior of a physical system. The procedure of mathematically modeling a physical system is complex and involves three fundamental entities: the experimental data, a set of candidate models, and rules for determining in such a set the “best” model that reproduces the measured data. The construction of the candidate models is domain dependent and based on specific knowledge and techniques of the application domain. The choice of the best model is guided by the data themselves; a first rough guess is refined through system identification techniques so that the quantitative properties of the observed behavior are assessed. Automating such a procedure requires handling and integrating different formalisms and methods, both qualitative and quantitative. The paper describes a comprehensive environment that aims at the automated formulation of an accurate quantitative model of the mechanical behavior of an actual viscoelastic material in accordance with the observed response of the material to standard experiments. Algorithms and methods for both the generation of an exhaustive library of models of ideal materials and the selection of the most “accurate” model of a real material have been designed and implemented. The model selection phase occurs in two main stages: first the subset of most plausible candidate models for the material is drawn from the library; then, the most accurate model of the material is identified by using both statistical and numerical methods
ABSTRACT To build model-based systems capable of emulating the scientist's or engineer&am... more ABSTRACT To build model-based systems capable of emulating the scientist's or engineer's way of reasoning about a given physical domain requires methods for automating the formulation or selection of a model which adequately captures the knowledge needed for solving a specific problem. To find and exploit such models requires the use and integration of different kinds of knowledge, formalisms and methods. This paper describes a system which aims at reasoning automatically about visco-elastic materials from a mechanical point of view. It integrates both domain-specific and domain-independent knowledge in order to classify and analyse the mechanical behaviour of materials. The classification task is based on qualitative knowledge, whereas the analysis of a material is performed at a quantitative level and is based on numerical simulation. The key ideas of the work are to automatically generate a library of models of ideal materials and their corresponding qualitative responses to standard experiments; to classify an actual material by selecting from within the library a class of models whose simulated qualitative behaviours towards standard loads match the observed behaviours; to identify a quantitative model of the material, and then to analyse the material by simulating its behaviour on any load. Each model in the library is automatically generated in two different forms; at the lowest level, as a symbolic description and, at a mathematical level, as an ordinary differential equation. This paper mainly concentrates on the methods and algorithms of model generation and qualitative simulation
Computer Methods and Programs in Biomedicine, Apr 1, 1994
This paper describes a framework, called QCMF (Qualitative Compartmental Modeling Framework), whi... more This paper describes a framework, called QCMF (Qualitative Compartmental Modeling Framework), which assists the user in formulating models of a pathophysiological system and in analyzing their behaviors through the simulation of the effects of a variety of pathogenetic mechanisms and therapeutical treatments. QCMF has adopted the compartmental theory as modeling ontology: a system is represented as a finite set of interacting compartments. The user enters, through an iconic language and menus, the compartmental structure of a pathophysiological system and the definition of the kinds of functional relationships describing the interactions between compartments. Then, QCMF automatically generates a behavior model of the system. Such a model consists of a set of ordinary differential equations, which are qualitatively expressed, and is directly coded into the language which is interpreted by the simulation algorithm. The system behavior can be obtained by simulating the model starting from an initial state which describes the perturbations acting on the system. The code defining the initial state is automatically built by QCMF as well. Finally, explanations of the predicted behavior are also automatically generated.
The last decade has witnessed major advancements in the direct application of functional imaging ... more The last decade has witnessed major advancements in the direct application of functional imaging techniques to several clinical contexts. Unfortunately, this is not the case of Electrocardiology. As a matter of fact, epicardial maps, which can hit electrical conduction pathologies that routine surface ECG's analysis may miss, can be obtained non invasively from body surface data through mathematical model-based reconstruction methods. But, their interpretation still requires highly specialized skills that belong to few experts. The automated detection of salient patterns in the map, grounded on the existing interpretation rationale, would therefore represent a major contribution towards the clinical use of such valuable tools, whose diagnostic potential is still largely unexploited. We focus on epicardial activation isochronal maps, which convey information about the heart electric function in terms of the depolarization wavefront kinematics. An approach grounded on the integration of a Spatial Aggregation (SA) method with concepts borrowed from Computational Geometry provides a computational framework to extract, from the given activation data, a few basic features that characterize the wavefront propagation, as well as a more specific set of features that identify an important class of heart rhythm pathologies, namely reentry arrhythmias due to block of conduction.
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Papers by Liliana Ironi