The Draftman\u27s View of the Revised Code

In this article, the author seeks to review the Code with the advantage of hindsight afforded by the passage of time since the completion of his activities as Reporter for the Judiciary Committee. Beyond this general review of the Code, the author will offer general observations concerning the process of code revision and the philosophy of the Code. Finally, the author will consider, in the context of the students\u27 Notes appearing in this issue of the Washington Law Review, the effect adoption of the Code will have on criminal law in Washington

Construction of a music attitude scale.

The Junior High program in the Omaha Public Schools has finally developed from dream to reality

An architecture for object-oriented intelligent control of power systems in space

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base

The Mechanical Behavior of a 25Cr Super Duplex Stainless Steel at Elevated Temperature

Peer reviewedPostprin

Transformation of Quartz to Tridymite in the Presence of Binary Silicate Liquids

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66429/1/j.1151-2916.1967.tb15146.x.pd

Linear-Time Algorithms for Computing Maximum-Density Sequence Segments with Bioinformatics Applications

We study an abstract optimization problem arising from biomolecular sequence analysis. For a sequence A of pairs (a_i,w_i) for i = 1,..,n and w_i>0, a segment A(i,j) is a consecutive subsequence of A starting with index i and ending with index j. The width of A(i,j) is w(i,j) = sum_{i <= k <= j} w_k, and the density is (sum_{i<= k <= j} a_k)/ w(i,j). The maximum-density segment problem takes A and two values L and U as input and asks for a segment of A with the largest possible density among those of width at least L and at most U. When U is unbounded, we provide a relatively simple, O(n)-time algorithm, improving upon the O(n \log L)-time algorithm by Lin, Jiang and Chao. When both L and U are specified, there are no previous nontrivial results. We solve the problem in O(n) time if w_i=1 for all i, and more generally in O(n+n\log(U-L+1)) time when w_i>=1 for all i.Comment: 23 pages, 13 figures. A significant portion of these results appeared under the title, "Fast Algorithms for Finding Maximum-Density Segments of a Sequence with Applications to Bioinformatics," in Proceedings of the Second Workshop on Algorithms in Bioinformatics (WABI), volume 2452 of Lecture Notes in Computer Science (Springer-Verlag, Berlin), R. Guigo and D. Gusfield editors, 2002, pp. 157--17

Comparative chromosome painting discloses homologous Segments in distantly related mammals

Comparative chromosome painting, termed ZOO-FISH, using DNA libraries from flow sorted human chromosomes 1,16,17 and X, and mouse chromosome 11 discloses the presence of syntenic groups in distantly related mammalian Orders ranging from primates (Homo sapiens), rodents (Mus musculus), even-toed ungulates (Muntiacus muntjak vaginalis and Muntiacus reevesi) and whales (Balaenoptera physalus). These mammalian Orders have evolved separately for 55-80 million years (Myr). We conclude that ZOO-FISH can be used to generate comparative chromosome maps of a large number of mammalian species