Parallelisation strategies for agent based simulation of immune systems

Background In recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeling (ABM), has attracted considerable efforts. The ABM approach is a very common technique in the biological domain due to high demand for a large scale analysis tools for the collection and interpretation of information to solve biological problems. Simulating massive multi-agent systems (i.e. simulations containing a large number of agents/entities) requires major computational effort which is only achievable through the use of parallel computing approaches. Results This paper explores different approaches to parallelising the key component of biological and immune system models within an ABM model: pairwise interactions. The focus of this paper is on the performance and algorithmic design choices of cell interactions in continuous and discrete space where agents/entities are competing to interact with one another within a parallel environment. Conclusions Our performance results demonstrate the applicability of these methods to a broader class of biological systems exhibiting typical cell to cell interactions. The advantage and disadvantage of each implementation is discussed showing each can be used as the basis for developing complete immune system models on parallel hardware

Elementary linear logic revisited for polynomial time and an exponential time hierarchy (extended version)

Nombre de pages: 20. Une version courte de ce travail est à paraître dans les actes de: Asian Symposium on Programming Languages and Systems (APLAS 2011).Elementary linear logic is a simple variant of linear logic, introduced by Girard and which characterizes in the proofs-as-programs approach the class of elementary functions (computable in time bounded by a tower of exponentials of fixed height). Our goal here is to show that despite its simplicity, elementary linear logic can nevertheless be used as a common framework to characterize the different levels of a hierarchy of deterministic time complexity classes, within elementary time. We consider a variant of this logic with type fixpoints and weakening. By selecting specific types we then characterize the class P of polynomial time predicates and more generally the hierarchy of classes k-EXP, for k>=0, where k-EXP is the union of DTIME(2_k^{n^i}), for i>=1

Light types for polynomial time computation in lambda-calculus

We propose a new type system for lambda-calculus ensuring that well-typed programs can be executed in polynomial time: Dual light affine logic (DLAL). DLAL has a simple type language with a linear and an intuitionistic type arrow, and one modality. It corresponds to a fragment of Light affine logic (LAL). We show that contrarily to LAL, DLAL ensures good properties on lambda-terms: subject reduction is satisfied and a well-typed term admits a polynomial bound on the reduction by any strategy. We establish that as LAL, DLAL allows to represent all polytime functions. Finally we give a type inference procedure for propositional DLAL.Comment: 20 pages (including 10 pages of appendix). (revised version; in particular section 5 has been modified). A short version is to appear in the proceedings of the conference LICS 2004 (IEEE Computer Society Press

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand

Conceptual uncertainties in modelling the interaction between engineered and natural barriers of nuclear waste repositories in crystalline rocks

Nuclear waste disposal in geological formations relies on a multi-barrier concept that includes engineered components – which, in many cases, include a bentonite buffer surrounding waste packages – and the host rock. Contrasts in materials, together with gradients across the interface between the engineered and natural barriers, lead to complex interactions between these two subsystems. Numerical modelling, combined with monitoring and testing data, can be used to improve our overall understanding of rock–bentonite interactions and to predict the performance of this coupled system. Although established methods exist to examine the prediction uncertainties due to uncertainties in the input parameters, the impact of conceptual model decisions on the quantitative and qualitative modelling results is more difficult to assess. A Swedish Nuclear Fuel and Waste Management Company Task Force project facilitated such an assessment. In this project, 11 teams used different conceptualizations and modelling tools to analyse the Bentonite Rock Interaction Experiment (BRIE) conducted at the Äspö Hard Rock Laboratory in Sweden. The exercise showed that prior system understanding along with the features implemented in the available simulators affect the processes included in the conceptual model. For some of these features, sufficient characterization data are available to obtain defensible results and interpretations, whereas others are less supported. The exercise also helped to identify the conceptual uncertainties that led to different assessments of the relative importance of the engineered and natural barrier subsystems. The range of predicted bentonite wetting times encompassed by the ensemble results were considerably larger than the ranges derived from individual models. This is a consequence of conceptual uncertainties, demonstrating the relevance of using a multi-model approach involving alternative conceptualizations.Peer ReviewedPostprint (author's final draft

Vulnerability assessments of pesticide leaching to groundwater

Pesticides may have adverse environmental effects if they are transported to groundwater and surface waters. The vulnerability of water resources to contamination of pesticides must therefore be evaluated. Different stakeholders, with different objectives and requirements, are interested in such vulnerability assessments. Various assessment methods have been developed in the past. For example, the vulnerability of groundwater to pesticide leaching may be evaluated by indices and overlay-based methods, by statistical analyses of monitoring data, or by using process-based models of pesticide fate. No single tool or methodology is likely to be appropriate for all end-users and stakeholders, since their suitability depends on the available data and the specific goals of the assessment. The overall purpose of this thesis was to develop tools, based on different process-based models of pesticide leaching that may be used in groundwater vulnerability assessments. Four different tools have been developed for end-users with varying goals and interests: (i) a tool based on the attenuation factor implemented in a GIS, where vulnerability maps are generated for the islands of Hawaii (U.S.A.), (ii) a simulation tool based on the MACRO model developed to support decision-makers at local authorities to assess potential risks of leaching of pesticides to groundwater following normal usage in drinking water abstraction districts, (iii) linked models of the soil root zone and groundwater to investigate leaching of the pesticide mecoprop to shallow and deep groundwater in fractured till, and (iv) a meta-model of the pesticide fate model MACRO developed for 'worst-case' groundwater vulnerability assessments in southern Sweden. The strengths and weaknesses of the different approaches are discussed

A stochastic multiple players multi-issues bargaining model for the Piave river basin

The objective of this paper is to investigate the usefulness of non-cooperative bargaining theory for the analysis of negotiations on water allocation and management. We explore the impacts of different economic incentives, a stochastic environment and varying individual preferences on players’ strategies and equilibrium outcomes through numerical simulations of a multilateral, multiple issues, non-cooperative bargaining model of water allocation in the Piave River Basin, in the North East of Italy. Players negotiate in an alternating-offer manner over the sharing of water resources (quantity and quality). Exogenous uncertainty over the size of the negotiated amount of water is introduced to capture the fact that water availability is not known with certainty to negotiating players. We construct the players’ objective function with their direct input. We then test the applicability of our multiple players, multi-issues, stochastic framework to a specific water allocation problem and conduct comparative static analyses to assess sources of bargaining power. Finally, we explore the implications of different attitudes and beliefs over water availability.Bargaining, non-cooperative game theory, simulation models, uncertainty

Conceptual uncertainties in modelling the interaction between engineered and natural barriers of nuclear waste repositories in crystalline rocks

Nuclear waste disposal in geological formations relies on a multi-barrier concept that includes engineered components – which, in many cases, include a bentonite buffer surrounding waste packages – and the host rock. Contrasts in materials, together with gradients across the interface between the engineered and natural barriers, lead to complex interactions between these two subsystems. Numerical modelling, combined with monitoring and testing data, can be used to improve our overall understanding of rock–bentonite interactions and to predict the performance of this coupled system. Although established methods exist to examine the prediction uncertainties due to uncertainties in the input parameters, the impact of conceptual model decisions on the quantitative and qualitative modelling results is more difficult to assess. A Swedish Nuclear Fuel and Waste Management Company Task Force project facilitated such an assessment. In this project, 11 teams used different conceptualizations and modelling tools to analyse the Bentonite Rock Interaction Experiment (BRIE) conducted at the Äspö Hard Rock Laboratory in Sweden. The exercise showed that prior system understanding along with the features implemented in the available simulators affect the processes included in the conceptual model. For some of these features, sufficient characterization data are available to obtain defensible results and interpretations, whereas others are less supported. The exercise also helped to identify the conceptual uncertainties that led to different assessments of the relative importance of the engineered and natural barrier subsystems. The range of predicted bentonite wetting times encompassed by the ensemble results were considerably larger than the ranges derived from individual models. This is a consequence of conceptual uncertainties, demonstrating the relevance of using a multi-model approach involving alternative conceptualizations

A Stochastic Multiple Players Multi-Issues Bargaining Model for the Piave River Basin

The objective of this paper is to investigate the usefulness of non-cooperative bargaining theory for the analysis of negotiations on water allocation and management. We explore the impacts of different economic incentives, a stochastic environment and varying individual preferences on players’ strategies and equilibrium outcomes through numerical simulations of a multilateral, multiple issues, non-cooperative bargaining model of water allocation in the Piave River Basin, in the North East of Italy. Players negotiate in an alternating-offer manner over the sharing of water resources (quantity and quality). Exogenous uncertainty over the size of the negotiated amount of water is introduced to capture the fact that water availability is not known with certainty to negotiating players. We construct the players’ objective function with their direct input. We then test the applicability of our multiple players, multi-issues, stochastic framework to a specific water allocation problem and conduct comparative static analyses to assess sources of bargaining power. Finally, we explore the implications of different attitudes and beliefs over water availability.bargaining, non-cooperative game theory, simulation models, uncertainty

A Stochastic Multiple Players Multi-Issues Bargaining Model for the Piave River Basin

The objective of this paper is to investigate the usefulness of non-cooperative bargaining theory for the analysis of negotiations on water allocation and management. We explore the impacts of different economic incentives, a stochastic environment and varying individual preferences on players’ strategies and equilibrium outcomes through numerical simulations of a multilateral, multiple issues, non-cooperative bargaining model of water allocation in the Piave River Basin, in the North East of Italy. Players negotiate in an alternating-offer manner over the sharing of water resources (quantity and quality). Exogenous uncertainty over the size of the negotiated amount of water is introduced to capture the fact that water availability is not known with certainty to negotiating players. We construct the players’ objective function with their direct input. We then test the applicability of our multiple players, multi-issues, stochastic framework to a specific water allocation problem and conduct comparative static analyses to assess sources of bargaining power. Finally, we explore the implications of different attitudes and beliefs over water availability.Bargaining, Non-Cooperative Game Theory, Simulation Models, Uncertainty