Isotactics as a foundation for alignment and abstraction of behavioral models

There are many use cases in business process management that require the comparison of behavioral models. For instance, verifying equivalence is the basis for assessing whether a technical workflow correctly implements a business process, or whether a process realization conforms to a reference process. This paper proposes an equivalence relation for models that describe behaviors based on the concurrency semantics of net theory and for which an alignment relation has been defined. This equivalence, called isotactics, preserves the level of concurrency of aligned operations. Furthermore, we elaborate on the conditions under which an alignment relation can be classified as an abstraction. Finally, we show that alignment relations induced by structural refinements of behavioral models are indeed behavioral abstractions

Petri nets for systems and synthetic biology

We give a description of a Petri net-based framework for modelling and analysing biochemical pathways, which uni¯es the qualita- tive, stochastic and continuous paradigms. Each perspective adds its con- tribution to the understanding of the system, thus the three approaches do not compete, but complement each other. We illustrate our approach by applying it to an extended model of the three stage cascade, which forms the core of the ERK signal transduction pathway. Consequently our focus is on transient behaviour analysis. We demonstrate how quali- tative descriptions are abstractions over stochastic or continuous descrip- tions, and show that the stochastic and continuous models approximate each other. Although our framework is based on Petri nets, it can be applied more widely to other formalisms which are used to model and analyse biochemical networks

Abstracting Asynchronous Multi-Valued Networks: An Initial Investigation

Multi-valued networks provide a simple yet expressive qualitative state based modelling approach for biological systems. In this paper we develop an abstraction theory for asynchronous multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. The abstraction theory therefore provides a mechanism for coping with the state space explosion problem and supports the analysis and comparison of multi-valued networks. We take as our starting point the abstraction theory for synchronous multi-valued networks which is based on the finite set of traces that represent the behaviour of such a model. The problem with extending this approach to the asynchronous case is that we can now have an infinite set of traces associated with a model making a simple trace inclusion test infeasible. To address this we develop a decision procedure for checking asynchronous abstractions based on using the finite state graph of an asynchronous multi-valued network to reason about its trace semantics. We illustrate the abstraction techniques developed by considering a detailed case study based on a multi-valued network model of the regulation of tryptophan biosynthesis in Escherichia coli.Comment: Presented at MeCBIC 201

Pose Induction for Novel Object Categories

We address the task of predicting pose for objects of unannotated object categories from a small seed set of annotated object classes. We present a generalized classifier that can reliably induce pose given a single instance of a novel category. In case of availability of a large collection of novel instances, our approach then jointly reasons over all instances to improve the initial estimates. We empirically validate the various components of our algorithm and quantitatively show that our method produces reliable pose estimates. We also show qualitative results on a diverse set of classes and further demonstrate the applicability of our system for learning shape models of novel object classes

An Abstraction Theory for Qualitative Models of Biological Systems

Multi-valued network models are an important qualitative modelling approach used widely by the biological community. In this paper we consider developing an abstraction theory for multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. This is important as it aids the analysis and comparison of multi-valued networks and in particular, helps address the well-known problem of state space explosion associated with such analysis. We also consider developing techniques for efficiently identifying abstractions and so provide a basis for the automation of this task. We illustrate the theory and techniques developed by investigating the identification of abstractions for two published MVN models of the lysis-lysogeny switch in the bacteriophage lambda.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Mechanism of Selective Ammoxidation of Propene to Acrylonitrile on Bismuth Molybdates from Quantum Mechanical Calculations

In order to understand the mechanism for selective ammoxidation of propene to acrylonitrile by bismuth molybdates, we report quantum mechanical studies (using the B3LYP flavor of density functional theory) for the various steps involved in converting the allyl-activated intermediate to acrylonitrile over molybdenum oxide (using a Mo_3O_9 cluster model) under conditions adjusted to describe both high and low partial pressures of NH_3 in the feed. We find that the rate-determining step in converting of allyl to acrylonitrile at all feed partial pressures is the second hydrogen abstraction from the nitrogen-bound allyl intermediate (Mo−NH−CH_2−CH═CH_2) to form Mo−NH═CH−CH═CH_2). We find that imido groups (Mo═NH) have two roles: (1) a direct effect on H abstraction barriers, H abstraction by an imido moiety is (~8 kcal/mol) more favorable than abstraction by an oxo moiety (Mo═O), and (2) an indirect effect, the presence of spectator imido groups decreases the H abstraction barriers by an additional ~15 kcal/mol. Therefore, at higher NH_3 pressures (which increases the number of Mo═NH groups), the second H abstraction barrier decreases significantly, in agreement with experimental observations that propene conversion is higher at higher partial pressures of NH_3. At high NH_3 pressures we find that the final hydrogen abstraction has a high barrier [ΔH‡_(fourth-ab) = 31.6 kcal/mol compared to ΔH‡_(second-ab) = 16.4 kcal/mol] due to formation of low Mo oxidation states in the final state. However, we find that reoxidizing the surface prior to the last hydrogen abstraction leads to a significant reduction of this barrier to ΔH‡_(fourth-ab) = 15.9 kcal/mol, so that this step is no longer rate determining. Therefore, we conclude that reoxidation during the reaction is necessary for facile conversion of allyl to acrylonitrile

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings