Atmospheric sampling of Supertyphoon Mireille with NASA DC-8 aircraft on September 27,1991, during PEM-West A

The DC-8 mission of September 27, 1991, was designed to sample air flowing into Typhoon Mireille in the boundary layer, air in the upper tropospheric eye region, and air emerging from the typhoon and ahead of the system, also in the upper troposphere. The objective was to find how a typhoon redistributes trace constituents in the West Pacific region and whether any such redistribution is important on the global scale. The boundary layer air (300 m), in a region to the SE of the eye, contained low mixing ratios of the tracer species O3, CO, C2H6, C2H2, C3H8, C6H6and CS2 but high values of dimethylsulfide (DMS). The eye region relative to the boundary layer, showed somewhat elevated levels of CO, substantially increased levels of O3, CS2 and all nonmethane hydrocarbons (NMHCs), and somewhat reduced levels of DMS. Ahead of the eye, CO and the NMHCs remained unchanged, O3 and CS2 showed a modest decrease, and DMS showed a substantial decrease. There was no evidence from lidar cross sections of ozone for the downward entrainment of stratospheric air into the eye region; these sections show that low ozone values were measured in the troposphere. The DMS data suggest substantial entrainment of boundary layer air into the system, particularly into the eye wall region. Estimates of the DMS sulphur flux between the boundary layer and the free troposphere, based on computations of velocity potential and divergent winds, gave values of about 69 μg S m−2 d−1 averaged over a 17.5° grid square encompassing the typhoon. A few hours after sampling with the DC-8, Mireille passed over Oki Island, just to the north of Japan, producing surface values of ozone of 5.5 ppbv. These O3 levels are consistent with the low tropospheric values found by lidar and are more typical of equatorial regions. We suggest that the central eye region may act like a Taylor column which has moved poleward from low latitudes. The high-altitude photochemical environment within Typhoon Mireille was found to be quite active as evidenced by significant levels of measured gas phase H2O2 and CH3OOH and model-computed levels of OH

The DLV System for Knowledge Representation and Reasoning

This paper presents the DLV system, which is widely considered the state-of-the-art implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, function-free disjunctive logic programs (also known as disjunctive datalog), extended by weak constraints, which are a powerful tool to express optimization problems. We then illustrate the usage of DLV as a tool for knowledge representation and reasoning, describing a new declarative programming methodology which allows one to encode complex problems (up to $\Delta^P_3$-complete problems) in a declarative fashion. On the foundational side, we provide a detailed analysis of the computational complexity of the language of DLV, and by deriving new complexity results we chart a complete picture of the complexity of this language and important fragments thereof. Furthermore, we illustrate the general architecture of the DLV system which has been influenced by these results. As for applications, we overview application front-ends which have been developed on top of DLV to solve specific knowledge representation tasks, and we briefly describe the main international projects investigating the potential of the system for industrial exploitation. Finally, we report about thorough experimentation and benchmarking, which has been carried out to assess the efficiency of the system. The experimental results confirm the solidity of DLV and highlight its potential for emerging application areas like knowledge management and information integration.Comment: 56 pages, 9 figures, 6 table

P2Y receptors and pain transmission

It is widely accepted that the most important ATP receptors involved in pain transmission belong to the P2X3 and P2X2/3 subtypes, selectively expressed in small diameter dorsal root ganglion (DRG) neurons. However, several types of the metabotropic ATP (P2Y) receptors have also been found in primary afferent neurons; P2Y1 and P2Y2 receptors are typically expressed in small, nociceptive cells. Here we review the results available on the involvement of P2Y receptors in the modulation of pain transmission

Generality Relations in Answer Set Programming

Abstract. This paper studies generality relations on logic programs. Intuitively, a program P1 is more general than another program P2 if P1 gives us more information than P2. In this paper, we define various kinds of generality relations over nonmonotonic programs in the context of an-swer set programming. The semantic properties of generality relations are investigated based on domain theory, and both a minimal upper bound and a maximal lower bound are constructed for any pair of logic pro-grams. We also introduce the concept of strong generality between logic programs and investigate its relationships to strong equivalence. These results provide a basic theory to compare the degree of incompleteness between nonmonotonic logic programs, and also have important appli-cations to inductive logic programming and multi-agent systems.

Induction of the effects of actions by monotonic methods

Abstract. Induction of the effects of actions considered here consists in learning an action description of a dynamic system from evidence on its behavior. General logic-based induction methods can deal with this problem but, unfortunately, most of the solutions provided have the frame problem. To cope with the frame problem induction under suitable nonmonotonic formalisms has to be used, though this kind of induction is not well understood yet. We propose an alternative method that relies on the identification of a monotonic induction problem whose solutions correspond one-to-one to those of the original problem without the frame problem. From this result induction of the effects of actions can be characterized under current monotonic induction methods.

Dataset Anonyization on Cloud: Open Problems and Perspectives

Data anonymization is the process of making information contained in a group of data such that it is not possible to identify unique references to single elements in the group after the process. This action, when conducted onto datasets used to make statistical inference is bound to have ananlogous behaviours on certain indices before and after the process itself. In this paper we study the pipeline of anonymization process for datasets, when this pipeline is managed on cloud technology, where cryptography is not applicable at all, for datasets being available in an open setting. We examine the open problems, and devise a method to address these problems in a logical framewor

Preferred Answer Sets for Ordered Logic Programs

We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a "best" answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a preference for satisfying certain rules, possibly at the cost of violating less important ones. We show that such a rule order induces a natural order on extended answer sets, the minimal elements of which we call preferred answer sets. We characterize the expressiveness of the resulting semantics and show that it can simulate negation as failure as well as disjunction. We illustrate an application of the approach by considering database repairs, where minimal repairs are shown to correspond to preferred answer sets

Embracing causality in inducing the effects of actions

Abstract. The following problem will be considered: from scattered examples on the behavior of a dynamic system induce a description of the system. For the induced description to be concise and modular, we use a generic action formalism based on causality, that is representable in logic programming. It is relatively simple to induce a description of a dynamic system that suffers from the frame problem. The known solutions to the frame problem require a non-monotonic formalism. Unfortunately induction under non-monotonic formalisms, e.g. normal logic programs, is not well understood yet. We present a method for induction under the non-monotonic behavior needed to solve the frame problem. Technically we introduce a causality predicate for the target fluent and induce a description of the causality of the fluent instead of the fluent itself. The description of causality together with the appropriate inertia axiom models the behavior of the original target fluent. The main advantage of this method is that the induction of the effects of actions can be made with well known induction methods on monotonic formalisms, such as Horn programs.

Extending the Smodels System with Cardinality and Weight Constraints

The Smodels system is one of the state-of-the-art implementations of stable model computation for normal logic programs. In order to enable more realistic applications, the basic modeling language of normal programs has been extended with new constructs including cardinality and weight constraints and corresponding implementation techniques have been developed. This paper summarizes the extensions that have been included in the system, demonstrates their use, provides basic application methodology, illustrates the current level of performance of the system, and compares it to state-of-the-art satis ability checkers