Abstract. We present an automatic iterative abstraction-refinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symbolic techniques which analyze such counterexamples and refine the abstract model correspondingly. The refinement algorithm keeps the size of the abstract state space small due to the use of abstraction functions which distinguish many degrees of abstraction for each program variable. We describe an implementation of our methodology in NuSMV. Practical experiments including a large Fujitsu IP core design with about 500 latches and 10000 lines of SMV code confirm the effectiveness of our approach.

Abstract. We present an automatic iterative abstraction-refinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symbolic techniques which analyze such counterexamples and refine the abstract model correspondingly. The refinement algorithm keeps the size of the abstract state space small due to the use of abstraction functions which distinguish many degrees of abstraction for each program variable. We describe an implementation of our methodology in NuSMV. Practical experiments including a large Fujitsu IP core design with about 500 latches and 10000 lines of SMV code confirm the effectiveness of our approach.

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Abstract. We provide semantics for the powerful scenario-based language of live sequence charts (LSCs). We show how the semantics of live sequence charts can be captured using temporal logic. This is done by studying various subsets of the LSC language and providing an explicit translation into temporal logic. We show how a kernel subset of the LSC language (which omits variables, for example) can be embedded within the temporal logic CTL * . For this kernel subset the embedding is a strict inclusion. We show that existential charts can be expressed using the branching temporal logic CTL while universal charts are in the intersection of linear temporal logic and branching temporal logic LTL ∩ CTL. Since our translations are efficient, the work described here may be used in the development of tools for analyzing and executing scenario-based requirements and for verifying systems against such requirements.

Abstract.Model checking is an automatic verification technique for finite state concurrent systems. In this approach to verification, temporal logic specifications are checked by an exhaustive search of the state space of the concurrent system. Since the size of the state space grows exponentially with the number of processes, model checking techniques based on explicit state enumeration can only handle relatively small examples. This phenomenon is commonly called the "State Explosion Problem". Over the past ten years considerable progress has been made on this problem by (1) representing the state space symbolically using BDDs and by (2) using abstraction to reduce the size of the state space that must be searched. As a result model checking has been used successfully to find extremely subtle errors in hardware controllers and communication protocols. In spite of these successes, however, additional research is needed to handle large designs of industrial complexity. This aim of this paper is to give a succinct survey of symbolic model checking and to introduce the reader to recent advances in abstraction.

The objective of this study was to determine whether L-glutamate (L-Glu) may serve as a neurotransmitter candidate in the guinea pig myenteric plexus. We observed that [3H]Glu and gamma-[3H]aminobutyric acid were synthesized from [3H]glutamine and released from neurons of the myenteric plexus during K+ and 1,1-dimethyl-4-phenylpiperazinium-evoked depolarization in a concentration-dependent manner. Muscle tension studies performed on ileal longitudinal muscle-myenteric plexus (LM-MP) preparations revealed that L-Glu [mean effective dose (ED50) 2.5 x 10(-5) M] produced concentration-dependent contractions, which were unaffected by hexamethonium but abolished by tetrodotoxin, atropine, and magnesium, suggesting that L-Glu acts via N-methyl-D-aspartate (NMDA)-type receptors that stimulate a cholinergic neural pathway unaffected by ganglionic blockade. In addition, L-Glu (ED50 4 x 10(-5) M) and NMDA (ED50 2 x 10(-4) M) stimulated concentration-dependent release of [3H]acetylcholine (ACh) from LM-MP sections, which was inhibited by tetrodotoxin, magnesium, and the NMDA receptor antagonist D-2-amino-5-phosphonovaleric acid (AP-5). L-Glu-mediated release of [3H]ACh was enhanced by theophylline (10-6 M) and 3-isobutyl-1-methylxanthine (1 mM) and was significantly reduced by the adenylate cyclase inhibitor, 2',5'-dideoxyadenosine (10(-4) M) and somatostatin-14 (10(-6) M), which inhibits adenosine 3',5'-cyclic monophosphate (cAMP)-dependent cholinergic transmission in the myenteric plexus. These studies suggest that L-Glu may serve as an excitatory neurotransmitter in the myenteric plexus via its action on NMDA-type receptors, which are coupled to cAMP-dependent release of ACh.

The successful launch of the Landsat 8 satellite provides important data for the monitoring of urban heat island effects. Since the Landsat 8 TIRS data has two thermal infrared bands, it is suitable for many algorithms to retrieve the land surface temperature (LST). However, the selection of algorithms for retrieving the LST, the acquisition of algorithm input parameters, and the verification of the results are problems without obvious solutions. Taking Changchun City as an example, this paper used the mono-window algorithm (MWA), the split window algorithm (SWA), and the single-channel (SC) method to extract the LST from the Landsat 8 image and compared the three algorithms in terms of input parameters, accuracy, and sensitivity. The results show that all three algorithms can achieve good results in retrieving the LST. The SWA is the least sensitive to the error of the input parameters. The MWA and the SC method are sensitive to the error of the input parameters, and compared with the error of the LSE, these two algorithms are more sensitive to the error of atmospheric water vapor content. In addition, the MWA is also very sensitive to the error of the effective mean atmospheric temperature.