Microstructural and High-Temperature Electrical Characterization of La<Subscript>1 − <Emphasis Type="Italic">x</Emphasis></Subscript>Sr<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>FeO<Subscript>3 − δ</Subscript>

Strontium-doped lanthanum ferrites (LSF) were studied using scanning electron microscopy (SEM), X-ray diffraction (XRD), 4-point D.C. electrical conductivity and bulk property measurements. The results were compared to those of previous studies as well as selected processing conditions. The investigation focused on effects of sintering temperature, time, atmosphere (air, O₂ and N₂) and composition of La_1–xSr_xFeO_3– (x = 0.2–0.9), on the sintering behavior, microstructural development and electrical conductivity. An oxalate precipitation method was used to prepare lanthanum ferrite powders. Simultaneous thermogravimetric and differential thermal analysis (TGA/DTA) studies found calcination temperatures of 800 and 850^C were necessary to form single-phase crystalline powders, as determined by XRD. Specimens were sintered from 1300 to 1400^C with dwell times from to 2 hrs. Results from SEM/EDS analysis showed the presence of a second phase in the samples fired in air or oxygen. The second phase was not detected by x-ray diffraction due to the small amount of material present. Samples fired in nitrogen had the lowest conductivity while those fired in oxygen had the highest. A composition of x = 0.5 resulted in the highest conductivity, 352 S/cm, at an operating temperature of 550C in air. High strontium additions (x = 0.9) lowered the linear shrinkage of LSF.     

Gene Discovery in Gelsemium Highlights Conserved Gene Clusters in Monoterpene Indole Alkaloid Biosynthesis

Genome mining is a routine technique in microbes for discovering biosynthetic pathways. In plants, however, genomic information is not commonly used to identify novel biosynthesis genes. Here, we present the genome of the medicinal plant and oxindole monoterpene indole alkaloid (MIA) producer Gelsemium sempervirens (Gelsemiaceae). A gene cluster from Catharanthus roseus, which is utilized at least six enzymatic steps downstream from the last common intermediate shared between the two plant alkaloid types, is found in G. sempervirens, although the corresponding enzymes act on entirely different substrates. This study provides insights into the common genomic context of MIA pathways and is an important milestone in the further elucidation of the Gelsemium oxindole alkaloid pathway.     

Development of forming limits for superplastic formed fine grain 7475 AI

Forming limits in conventional sheet metal forming are given by strain levels obtainable prior to the onset of a localized neck or tear in the sheet. While the external appearance of such a neck is not observed in superplastic metals until strains become quite large, the formation of internal cavities could dictate the tolerable levels of strain in formed components. In this paper, these useful strain limits for a superplastic 7475 Al alloy have been explored. The approach used was to establish the influence of strain state (uniaxial, plane strain, and balanced biaxial) on the inception and growth characteristics of cavities and to correlate the extent of cavitation with material properties. Based on these data, it was then possible to establish strain states for which little or no loss in properties was observed, and thereby to define forming limits for superplastic forming this material. These results, coupled with comparisons against strains developed in actual parts as well as analytically predicted strains, show that a wide range of structural parts can be superplastically formed within the constraints of the recommended forming limits.     

Data Mining in Large Databases Using Domain Generalization Graphs

Attribute-oriented generalization summarizes the information in a relational database by repeatedly replacing specific attribute values with more general concepts according to user-defined concept hierarchies. We introduce domain generalization graphs for controlling the generalization of a set of attributes and show how they are constructed. We then present serial and parallel versions of the Multi-Attribute Generalization algorithm for traversing the generalization state space described by joining the domain generalization graphs for multiple attributes. Based upon a generate-and-test approach, the algorithm generates all possible summaries consistent with the domain generalization graphs. Our experimental results show that significant speedups are possible by partitioning path combinations from the DGGs across multiple processors. We also rank the interestingness of the resulting summaries using measures based upon variance and relative entropy. Our experimental results also show that these measures provide an effective basis for analyzing summary data generated from relational databases. Variance appears more useful because it tends to rank the less complex summaries (i.e., those with few attributes and/or tuples) as more interesting.     

A note on regeneration with virtual copies

Regeneration with virtual copies (RVC) is a voting-based consistency control algorithm for replicated data objects in a distributed computing system. Proposed by Adam and Tewari (ibid., vol. 19, no. 6, pp. 594-602, 1993), it utilizes selective regeneration and recovery mechanisms for maintaining the availability and consistency of copies. This paper describes some problems with the original paper and proposes solutions     

ROBUST CONTROLLER DESIGN AND EXPERIMENTAL VERIFICATION OF I.C. ENGINE SPEED CONTROL

Presented in this paper is the robust idle speed control of a Ford 4⋅6 L V-8 fuel injected engine. The goal of this investigation is to design a robust feedback controller that maintains the idle speed within a 150 rpm tolerance about 600 rpm despite a 20 Nm step torque disturbance delivered by the power steering pump. The controlled input is the by-pass air valve which is subjected to an output saturation constraint. Issues complicating the controller design include the nonlinear nature of the engine dynamics, the induction-to-power delay of the manifold filling dynamics, and the saturation constraint of the by-pass air valve. An experimental verification of the proposed controller is included. © 1997 by John Wiley & Sons, Ltd.     

Adaptive autonomous underwater vehicles for littoral surveillance

Autonomous underwater vehicles (AUVs) have gained more interest in recent years for military as well as civilian applications. One potential application of AUVs is for the purpose of undersea surveillance. As research into undersea surveillance using AUVs progresses, issues arise as to how an AUV acquires, acts on, and shares information about the undersea battle space. These issues naturally touch on aspects of vehicle autonomy and underwater communications, and need to be resolved through a spiral development process that includes at sea experimentation. This paper presents a recent AUV implementation for active anti-submarine warfare tested at sea in the summer of 2010. On-board signal processing capabilities and an adaptive behavior are discussed in both a simulation and experimental context. The implications for underwater surveillance using AUVs are discussed.     

Poitín: Distilling Theorems From Conjectures

In this paper, we describe a new fully automatic theorem prover called Poitín which makes use of a novel transformation algorithm called distillation to prove input conjectures. The input conjectures are defined in a functional language and are transformed using the distillation algorithm. The result of this transformation can be easily inspected to see whether the original conjecture is true. Possible divergence of the transformation algorithm is detected, and this information is used to perform generalizations to ensure termination. We give several examples of the application of the theorem prover, and compare it to related work.