Abbreviated Larval Period of Rana Catesbeiana in Iowa

It has long been reported that the larval period of Rana catesbeiana in the North lasts for two years (Pope, \u2747, Wright and Wright, \u2749, Smith, \u2750). Examination of tadpoles from such ponds indicates that two age classes are present. The two groups result from the fact that eggs are deposited every year while tadpoles transform only after their second winter. In the light of this information, we were quite surprised to find bullfrog tadpoles apparently of only one age group in Iowa City. 1 In view of this general information, it seems possible that bullfrog tadpoles in this vicinity undergo an abbreviated larval period. Premature metamorphosis of these tadpoles may occur in even more widely distributcd areas since Klimstra (‘47) reports similar observations on Rana catesbeiana from several farm ponds in southern Iowa. In these ponds which were newly· constructed, transforming tadpoles were seen one year after adult bullfrogs first invaded them. Measurements of the tadpoles seemed to fall in one group, ranging in size from 4.1 - 5.9 inches. Unfortunately the number of tadpoles which were measured was not reported. Since all these observations of abbreviated metamorphosis seem to be of such general nature, we decided to follow closely the life history of bullfrog tadpoles in two large ponds on the Rohner farm about five miles south of Iowa City

Implementing Groundness Analysis with Definite Boolean Functions

The domain of definite Boolean functions, Def, can be used to express the groundness of, and trace grounding dependencies between, program variables in (constraint) logic programs. In this paper, previously unexploited computational properties of Def are utilised to develop an efficient and succinct groundness analyser that can be coded in Prolog. In particular, entailment checking is used to prevent unnecessary least upper bound calculations. It is also demonstrated that join can be defined in terms of other operations, thereby eliminating code and removing the need for preprocessing formulae to a normal form. This saves space and time. Furthermore, the join can be adapted to straightforwardly implement the downward closure operator that arises in set sharing analyses. Experimental results indicate that the new Def implementation gives favourable results in comparison with BDD-based groundness analyses

Pruning Algorithms for Pretropisms of Newton Polytopes

Pretropisms are candidates for the leading exponents of Puiseux series that represent solutions of polynomial systems. To find pretropisms, we propose an exact gift wrapping algorithm to prune the tree of edges of a tuple of Newton polytopes. We prefer exact arithmetic not only because of the exact input and the degrees of the output, but because of the often unpredictable growth of the coordinates in the face normals, even for polytopes in generic position. We provide experimental results with our preliminary implementation in Sage that compare favorably with the pruning method that relies only on cone intersections.Comment: exact, gift wrapping, Newton polytope, pretropism, tree pruning, accepted for presentation at Computer Algebra in Scientific Computing, CASC 201

Generation of Functional CLL-Specific Cord Blood CTL Using CD40-Ligated CLL APC

PMCID: PMC3526610This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Bifurcating spatially heterogeneous solutions in a chemotaxis model for biological pattern formation

We consider a simple cell-chemotaxis model for spatial pattern formation on two-dimensional domains proposed by Oster and Murray (1989,J. exp. Zool. 251, 186–202). We determine finite-amplitude, steady-state, spatially heterogeneous solutions and study the effect of domain growth on the resulting patterns. We also investigate in-depth bifurcating solutions as the chemotactic parameter varies. This numerical study shows that this deceptively simple-chemotaxis model can produce a surprisingly rich spectrum of complex spatial patterns

LNCS

Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools

Symbolic Verification and Strategy Synthesis for Linearly-Priced Probabilistic Timed Automata

Probabilistic timed automata are a formalism for modelling systems whose dynamics includes probabilistic, nondeterministic and timed aspects including real-time systems. A variety of techniques have been proposed for the analysis of this formalism and successfully employed to analyse, for example, wireless communication protocols and computer security systems. Augmenting the model with prices (or, equivalently, costs or rewards) provides a means to verify more complex quantitative properties, such as the expected energy usage of a device or the expected number of messages sent during a protocol’s execution. However, the analysis of these properties on probabilistic timed automata currently relies on a technique based on integer discretisation of real-valued clocks, which can be expensive in some cases. In this paper, we propose symbolic techniques for verification and optimal strategy synthesis for priced probabilistic timed automata which avoid this discretisation. We build upon recent work for the special case of expected time properties, using value iteration over a zone-based abstraction of the model

Evaluating Design Tradeoffs in Numeric Static Analysis for Java

Numeric static analysis for Java has a broad range of potentially useful applications, including array bounds checking and resource usage estimation. However, designing a scalable numeric static analysis for real-world Java programs presents a multitude of design choices, each of which may interact with others. For example, an analysis could handle method calls via either a top-down or bottom-up interprocedural analysis. Moreover, this choice could interact with how we choose to represent aliasing in the heap and/or whether we use a relational numeric domain, e.g., convex polyhedra. In this paper, we present a family of abstract interpretation-based numeric static analyses for Java and systematically evaluate the impact of 162 analysis configurations on the DaCapo benchmark suite. Our experiment considered the precision and performance of the analyses for discharging array bounds checks. We found that top-down analysis is generally a better choice than bottom-up analysis, and that using access paths to describe heap objects is better than using summary objects corresponding to points-to analysis locations. Moreover, these two choices are the most significant, while choices about the numeric domain, representation of abstract objects, and context-sensitivity make much less difference to the precision/performance tradeoff

PRISM-games: verification and strategy synthesis for stochastic multi-player games with multiple objectives

PRISM-games is a tool for modelling, verification and strategy synthesis for stochastic multi-player games. These allow models to incorporate both probability, to represent uncertainty, unreliability or randomisation, and game-theoretic aspects, for systems where different entities have opposing objectives. Applications include autonomous transport, security protocols, energy management systems and many more. We provide a detailed overview of the PRISM-games tool, including its modelling and property specification formalisms, and its underlying architecture and implementation. In particular, we discuss some of its key features, which include multi-objective and compositional approaches to verification and strategy synthesis. We also discuss the scalability and efficiency of the tool and give an overview of some of the case studies to which it has been applied