The cell surface receptor Tartan is a potential in vivo substrate for the receptor tyrosine phosphatase Ptp52F

Receptor-linked protein-tyrosine phosphatases (RPTPs) are essential regulators of axon guidance and synaptogenesis in Drosophila, but the signaling pathways in which they function are poorly defined. We identified the cell surface receptor Tartan (Trn) as a candidate substrate for the neuronal RPTP Ptp52F by using a modified two-hybrid screen with a substrate-trapping mutant of Ptp52F as "bait." Trn can bind to the Ptp52F substrate-trapping mutant in transfected Drosophila S2 cells if v-Src kinase, which phosphorylates Trn, is also expressed. Coexpression of wild-type Ptp52F causes dephosphorylation of v-Src-phosphorylated Trn. To examine the specificity of the interaction in vitro, we incubated Ptp52F-glutathione S-transferase (GST) fusion proteins with pervanadate-treated S2 cell lysates. Wild-type Ptp52F dephosphorylated Trn, as well as most other bands in the lysate. GST "pulldown" experiments demonstrated that the Ptp52F substrate-trapping mutant binds exclusively to phospho-Trn. Wild-type Ptp52F pulled down dephosphorylated Trn, suggesting that it forms a stable Ptp52F-Trn complex that persists after substrate dephosphorylation. To evaluate whether Trn and Ptp52F are part of the same pathway in vivo, we examined motor axon guidance in mutant embryos. trn and Ptp52F mutations produce identical phenotypes affecting the SNa motor nerve. The genes also display dosage-dependent interactions, suggesting that Ptp52F regulates Trn signaling in SNa motor neurons

Maximum Entropy Models For Natural Language Ambiguity Resolution

This thesis demonstrates that several important kinds of natural language ambiguities can be resolved to state-of-the-art accuracies using a single statistical modeling technique based on the principle of maximum entropy. We discuss the problems of sentence boundary detection, part-of-speech tagging, prepositional phrase attachment, natural language parsing, and text categorization under the maximum entropy framework. In practice, we have found that maximum entropy models offer the following advantages: State-of-the-art Accuracy: The probability models for all of the tasks discussed perform at or near state-of-the-art accuracies, or outperform competing learning algorithms when trained and tested under similar conditions. Methods which outperform those presented here require much more supervision in the form of additional human involvement or additional supporting resources. Knowledge-Poor Features: The facts used to model the data, or features, are linguistically very simple, or knowledge-poor but yet succeed in approximating complex linguistic relationships. Reusable Software Technology: The mathematics of the maximum entropy framework are essentially independent of any particular task, and a single software implementation can be used for all of the probability models in this thesis. The experiments in this thesis suggest that experimenters can obtain state-of-the-art accuracies on a wide range of natural language tasks, with little task-specific effort, by using maximum entropy probability models

Fracture criteria for discontinuously reinforced metal matrix composites

Summarized is the progress achieved during the period September 16, 1987 to August 15, l988 on NASA Grant NAG1-724, Fracture Criteria for Discontinuously Reinforced Metal Matrix Composites. Appended are copies of three manuscripts prepared under NASA funding during the performance period

Altered levels of Gq activity modulate axonal pathfinding in Drosophila

A majority of neurons that form the ventral nerve cord send out long axons that cross the midline through anterior or posterior commissures. A smaller fraction extend longitudinally and never cross the midline. The decision to cross the midline is governed by a balance of attractive and repulsive signals. We have explored the role of a G-protein, Gαq, in altering this balance in Drosophila. A splice variant of Gαq, dgqα3, is expressed in early axonal growth cones, which go to form the commissures in the Drosophila embryonic CNS. Misexpression of a gain-of-function transgene of dgqα3 (AcGq3) leads to ectopic midline crossing. Analysis of the AcGq3 phenotype in roundabout and frazzled mutants shows that AcGq3 function is antagonistic to Robo signaling and requires Frazzled to promote ectopic midline crossing. Our results show for the first time that a heterotrimeric G-protein can affect the balance of attractive versus repulsive cues in the growth cone and that it can function as a component of signaling pathways that regulate axonal pathfinding

Peer-to-Peer Network: Kantian Cooperation Discourage Free Riding

The problem of how to achieve cooperation among rational peers in order to discourage free riding is one that has received a lot of attention in peer-to-peer computing and is still an important one. The field of game theory is applied to the task of finding solutions that will encourage cooperation while discouraging free riding. The cooperative conduct of peers is typically portrayed as a traditional version of the game known as the "Prisoners' Dilemma." It is common knowledge that if two peers engage in a situation known as the Prisoner's Dilemma more than once, collaboration can be achieved through the use of punishment. Nevertheless, this is not the case when there is only one interaction between peers. This short article demonstrates that Kantian peers prefer to cooperate and attain social welfare even when they interacted only once. This, dissuade peers from freeriding.Comment: 1

The Length-Biased Versus Random Sampling for the Binomial and Poisson Events

The equivalence between the length-biased and the random sampling on a non-negative, discrete random variable is established. The length-biased versions of the binomial and Poisson distributions are discussed

A Note on α-Curvature of the Manifolds of the Length-biased Lognormal and Gamma Distributions in View of Related Applications in Data Analysis

The α-curvature tensors of the statistical manifolds of the length-biased versions of the log-normal and gamma distributions are derived and discussed. This study was designed to investigate observations related to the parameter estimation for the length-biased lognormal distribution as a model for the lengthbiased data from oil field exploration