Three new synonymies in \u3ci\u3ePhyllophaga\u3c/i\u3e Harris, 1827 (Coleoptera: Scarabaeidae), with lectotype and neotype designations

In the course of working on new species of North American Phyllophaga Harris, 1827 (Coleoptera: Scarabaeidae: Melolonthinae) some synonyms have been found and are proposed here. New synonymies: Phyllophaga knausii (Schaeffer, 1907) is synonymized with Phyllophaga sociata (Horn, 1878); Phyllophaga chippewa Saylor, 1939 is synonymized with Phyllophaga rugosa (Melsheimer, 1845); and Phyllophaga falta Sanderson, 1950 is synonymized with Phyllophaga bipartita (Horn, 1887). Lectotypes are here designated for the following species: Listrochelus knausii Schaeffer, Listrochelus sociatus Horn, and Lachnosterna bipartita Horn. A neotype for Ancylonycha rugosa Melsheimer is here designated from the Horn Collection

Incremental Recompilation of Knowledge

Approximating a general formula from above and below by Horn formulas (its Horn envelope and Horn core, respectively) was proposed by Selman and Kautz (1991, 1996) as a form of ``knowledge compilation,'' supporting rapid approximate reasoning; on the negative side, this scheme is static in that it supports no updates, and has certain complexity drawbacks pointed out by Kavvadias, Papadimitriou and Sideri (1993). On the other hand, the many frameworks and schemes proposed in the literature for theory update and revision are plagued by serious complexity-theoretic impediments, even in the Horn case, as was pointed out by Eiter and Gottlob (1992), and is further demonstrated in the present paper. More fundamentally, these schemes are not inductive, in that they may lose in a single update any positive properties of the represented sets of formulas (small size, Horn structure, etc.). In this paper we propose a new scheme, incremental recompilation, which combines Horn approximation and model-based updates; this scheme is inductive and very efficient, free of the problems facing its constituents. A set of formulas is represented by an upper and lower Horn approximation. To update, we replace the upper Horn formula by the Horn envelope of its minimum-change update, and similarly the lower one by the Horn core of its update; the key fact which enables this scheme is that Horn envelopes and cores are easy to compute when the underlying formula is the result of a minimum-change update of a Horn formula by a clause. We conjecture that efficient algorithms are possible for more complex updates.Comment: See http://www.jair.org/ for any accompanying file

Acoustic transducer apparatus with reduced thermal conduction

A horn is described for transmitting sound from a transducer to a heated chamber containing an object which is levitated by acoustic energy while it is heated to a molten state, which minimizes heat transfer to thereby minimize heating of the transducer, minimize temperature variation in the chamber, and minimize loss of heat from the chamber. The forward portion of the horn, which is the portion closest to the chamber, has holes that reduce its cross-sectional area to minimize the conduction of heat along the length of the horn, with the entire front portion of the horn being rigid and having an even front face to efficiently transfer high frequency acoustic energy to fluid in the chamber. In one arrangement, the horn has numerous rows of holes extending perpendicular to the length of horn, with alternate rows extending perpendicular to one another to form a sinuous path for the conduction of heat along the length of the horn

More on Descriptive Complexity of Second-Order HORN Logics

This paper concerns Gradel's question asked in 1992: whether all problems which are in PTIME and closed under substructures are definable in second-order HORN logic SO-HORN. We introduce revisions of SO-HORN and DATALOG by adding first-order universal quantifiers over the second-order atoms in the bodies of HORN clauses and DATALOG rules. We show that both logics are as expressive as FO(LFP), the least fixed point logic. We also prove that FO(LFP) can not define all of the problems that are in PTIME and closed under substructures. As a corollary, we answer Gradel's question negatively

Learning definite Horn formulas from closure queries

A definite Horn theory is a set of n-dimensional Boolean vectors whose characteristic function is expressible as a definite Horn formula, that is, as conjunction of definite Horn clauses. The class of definite Horn theories is known to be learnable under different query learning settings, such as learning from membership and equivalence queries or learning from entailment. We propose yet a different type of query: the closure query. Closure queries are a natural extension of membership queries and also a variant, appropriate in the context of definite Horn formulas, of the so-called correction queries. We present an algorithm that learns conjunctions of definite Horn clauses in polynomial time, using closure and equivalence queries, and show how it relates to the canonical Guigues–Duquenne basis for implicational systems. We also show how the different query models mentioned relate to each other by either showing full-fledged reductions by means of query simulation (where possible), or by showing their connections in the context of particular algorithms that use them for learning definite Horn formulas.Peer ReviewedPostprint (author's final draft

Rhinoceros Horn Libation Cup

On display in the “Wonders of Nature and Artifice” exhibit at Gettysburg College is an exquisitely carved Chinese rhinoceros horn cup decorated with many images of animals, from dragons to tortoises.The rhinoceros horn has been noted by the Chinese as early as the T’ang dynasty (618-907) to have magical properties, and it was believed that when a poisonous liquid was poured into a rhino horn, the horn would change colors to alert to the presence of poison.Due to these magical properties, rhinoceros horns have been regarded as especially valuable. [excerpt

The Limits of Horn Logic Programs

Given a sequence $\{\Pi_n\}$ of Horn logic programs, the limit $\Pi$ of $\{\Pi_n\}$ is the set of the clauses such that every clause in $\Pi$ belongs to almost every $\Pi_n$ and every clause in infinitely many $\Pi_n$'s belongs to $\Pi$ also. The limit program $\Pi$ is still Horn but may be infinite. In this paper, we consider if the least Herbrand model of the limit of a given Horn logic program sequence $\{\Pi_n\}$ equals the limit of the least Herbrand models of each logic program $\Pi_n$. It is proved that this property is not true in general but holds if Horn logic programs satisfy an assumption which can be syntactically checked and be satisfied by a class of Horn logic programs. Thus, under this assumption we can approach the least Herbrand model of the limit $\Pi$ by the sequence of the least Herbrand models of each finite program $\Pi_n$. We also prove that if a finite Horn logic program satisfies this assumption, then the least Herbrand model of this program is recursive. Finally, by use of the concept of stability from dynamical systems, we prove that this assumption is exactly a sufficient condition to guarantee the stability of fixed points for Horn logic programs.Comment: 11 pages, added new results. Welcome any comments to [email protected]