8,170 research outputs found
On the Hybrid Extension of CTL and CTL+
The paper studies the expressivity, relative succinctness and complexity of
satisfiability for hybrid extensions of the branching-time logics CTL and CTL+
by variables. Previous complexity results show that only fragments with one
variable do have elementary complexity. It is shown that H1CTL+ and H1CTL, the
hybrid extensions with one variable of CTL+ and CTL, respectively, are
expressively equivalent but H1CTL+ is exponentially more succinct than H1CTL.
On the other hand, HCTL+, the hybrid extension of CTL with arbitrarily many
variables does not capture CTL*, as it even cannot express the simple CTL*
property EGFp. The satisfiability problem for H1CTL+ is complete for triply
exponential time, this remains true for quite weak fragments and quite strong
extensions of the logic
On the Expressive Power of Hybrid Branching-Time Logics
Hybrid branching-time logics are a powerful extension of branching-time logics like CTL, CTL^* or even the modal mu-calculus through the addition of binders, jumps and variable tests. Their expressiveness is not restricted by bisimulation-invariance anymore. Hence, they do not retain the tree model property, and the finite model property is equally lost. Their satisfiability problems are typically undecidable, their model checking problems (on finite models) are decidable with complexities ranging from polynomial to non-elementary time. In this paper we study the expressive power of such hybrid branching-time logics beyond some earlier results about their invariance under hybrid bisimulations. In particular, we aim to extend the hierarchy of non-hybrid branching-time logics CTL, CTL^+, CTL^* and the modal mu-calculus to their hybrid extensions. We show that most separation results can be transferred to the hybrid world, even though the required techniques become a bit more involved. We also present some collapse results for restricted classes of models that are especially worth investigating, namely linear, tree-shaped and finite models
Enriched MU-Calculi Module Checking
The model checking problem for open systems has been intensively studied in
the literature, for both finite-state (module checking) and infinite-state
(pushdown module checking) systems, with respect to Ctl and Ctl*. In this
paper, we further investigate this problem with respect to the \mu-calculus
enriched with nominals and graded modalities (hybrid graded Mu-calculus), in
both the finite-state and infinite-state settings. Using an automata-theoretic
approach, we show that hybrid graded \mu-calculus module checking is solvable
in exponential time, while hybrid graded \mu-calculus pushdown module checking
is solvable in double-exponential time. These results are also tight since they
match the known lower bounds for Ctl. We also investigate the module checking
problem with respect to the hybrid graded \mu-calculus enriched with inverse
programs (Fully enriched \mu-calculus): by showing a reduction from the domino
problem, we show its undecidability. We conclude with a short overview of the
model checking problem for the Fully enriched Mu-calculus and the fragments
obtained by dropping at least one of the additional constructs
Towards Cancer Hybrid Automata
This paper introduces Cancer Hybrid Automata (CHAs), a formalism to model the
progression of cancers through discrete phenotypes. The classification of
cancer progression using discrete states like stages and hallmarks has become
common in the biology literature, but primarily as an organizing principle, and
not as an executable formalism. The precise computational model developed here
aims to exploit this untapped potential, namely, through automatic verification
of progression models (e.g., consistency, causal connections, etc.),
classification of unreachable or unstable states and computer-generated
(individualized or universal) therapy plans. The paper builds on a
phenomenological approach, and as such does not need to assume a model for the
biochemistry of the underlying natural progression. Rather, it abstractly
models transition timings between states as well as the effects of drugs and
clinical tests, and thus allows formalization of temporal statements about the
progression as well as notions of timed therapies. The model proposed here is
ultimately based on hybrid automata, and we show how existing controller
synthesis algorithms can be generalized to CHA models, so that therapies can be
generated automatically. Throughout this paper we use cancer hallmarks to
represent the discrete states through which cancer progresses, but other
notions of discretely or continuously varying state formalisms could also be
used to derive similar therapies.Comment: In Proceedings HSB 2012, arXiv:1208.315
Basins of Attraction, Commitment Sets and Phenotypes of Boolean Networks
The attractors of Boolean networks and their basins have been shown to be
highly relevant for model validation and predictive modelling, e.g., in systems
biology. Yet there are currently very few tools available that are able to
compute and visualise not only attractors but also their basins. In the realm
of asynchronous, non-deterministic modeling not only is the repertoire of
software even more limited, but also the formal notions for basins of
attraction are often lacking. In this setting, the difficulty both for theory
and computation arises from the fact that states may be ele- ments of several
distinct basins. In this paper we address this topic by partitioning the state
space into sets that are committed to the same attractors. These commitment
sets can easily be generalised to sets that are equivalent w.r.t. the long-term
behaviours of pre-selected nodes which leads us to the notions of markers and
phenotypes which we illustrate in a case study on bladder tumorigenesis. For
every concept we propose equivalent CTL model checking queries and an extension
of the state of the art model checking software NuSMV is made available that is
capa- ble of computing the respective sets. All notions are fully integrated as
three new modules in our Python package PyBoolNet, including functions for
visualising the basins, commitment sets and phenotypes as quotient graphs and
pie charts
HBsAg-vectored DNA vaccines elicit concomitant protective responses to multiple CTL epitopes relevant in human disease.
Vaccines capable of controlling neoplastic and infectious diseases which depend on the cellular immune response for their resolution, have proven difficult to develop. We, and others, have previously demonstrated that the potent immunogenicity of hepatitis B surface antigen (HBsAg), the already- licensed human vaccine for hepatitis B infection, may be exploited to deliver foreign antigens for cytotoxic T-lymphocyte (CTL) induction. In this study we demonstrate that recombinant (r) HBsAg DNA delivering a CTL polyepitope appended at the C' terminus elicits concomitant responses to multiple epitopes restricted through a diversity of MHC class I haplotypes, which are relevant in a number of human diseases. We show that the rHBsAg DNA vaccine elicits concomitant protection against neoplastic and infectious disease. These studies vindicate the use of HBsAg as a powerful vector to deliver CTL responses to foreign antigens, and have implications for a multi-disease vaccine applicable to the HLA-polymorphic human population
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