Tracking Data Relay Satellite System (TDRSS) VHF propagation study

A study performed to investigate the use of the Bent Ionospheric Model in computing corrections to the range and range rate measurements of the TDRSS satellites is documented. Several orbital configurations between the two satellites are discussed as to their effects on total electron content along the radio path between the satellites. Problem areas in the accurate computation of total electron content and range rate corrections are also discussed. The Bent Ionospheric Model gives the electron density versus height profile as a function of latitude, longitude, height, time, season, and solar flux

Certainty Closure: Reliable Constraint Reasoning with Incomplete or Erroneous Data

Constraint Programming (CP) has proved an effective paradigm to model and solve difficult combinatorial satisfaction and optimisation problems from disparate domains. Many such problems arising from the commercial world are permeated by data uncertainty. Existing CP approaches that accommodate uncertainty are less suited to uncertainty arising due to incomplete and erroneous data, because they do not build reliable models and solutions guaranteed to address the user's genuine problem as she perceives it. Other fields such as reliable computation offer combinations of models and associated methods to handle these types of uncertain data, but lack an expressive framework characterising the resolution methodology independently of the model. We present a unifying framework that extends the CP formalism in both model and solutions, to tackle ill-defined combinatorial problems with incomplete or erroneous data. The certainty closure framework brings together modelling and solving methodologies from different fields into the CP paradigm to provide reliable and efficient approches for uncertain constraint problems. We demonstrate the applicability of the framework on a case study in network diagnosis. We define resolution forms that give generic templates, and their associated operational semantics, to derive practical solution methods for reliable solutions.Comment: Revised versio

Identification of direct residue contacts in protein-protein interaction by message passing

Understanding the molecular determinants of specificity in protein-protein interaction is an outstanding challenge of postgenome biology. The availability of large protein databases generated from sequences of hundreds of bacterial genomes enables various statistical approaches to this problem. In this context covariance-based methods have been used to identify correlation between amino acid positions in interacting proteins. However, these methods have an important shortcoming, in that they cannot distinguish between directly and indirectly correlated residues. We developed a method that combines covariance analysis with global inference analysis, adopted from use in statistical physics. Applied to a set of >2,500 representatives of the bacterial two-component signal transduction system, the combination of covariance with global inference successfully and robustly identified residue pairs that are proximal in space without resorting to ad hoc tuning parameters, both for heterointeractions between sensor kinase (SK) and response regulator (RR) proteins and for homointeractions between RR proteins. The spectacular success of this approach illustrates the effectiveness of the global inference approach in identifying direct interaction based on sequence information alone. We expect this method to be applicable soon to interaction surfaces between proteins present in only 1 copy per genome as the number of sequenced genomes continues to expand. Use of this method could significantly increase the potential targets for therapeutic intervention, shed light on the mechanism of protein-protein interaction, and establish the foundation for the accurate prediction of interacting protein partners.Comment: Supplementary information available on http://www.pnas.org/content/106/1/67.abstrac

Generation of folk song melodies using Bayes transforms

The paper introduces the `Bayes transform', a mathematical procedure for putting data into a hierarchical representation. Applicable to any type of data, the procedure yields interesting results when applied to sequences. In this case, the representation obtained implicitly models the repetition hierarchy of the source. There are then natural applications to music. Derivation of Bayes transforms can be the means of determining the repetition hierarchy of note sequences (melodies) in an empirical and domain-general way. The paper investigates application of this approach to Folk Song, examining the results that can be obtained by treating such transforms as generative models

Active flow control systems architectures for civil transport aircraft

Copyright @ 2010 American Institute of Aeronautics and AstronauticsThis paper considers the effect of choice of actuator technology and associated power systems architecture on the mass cost and power consumption of implementing active flow control systems on civil transport aircraft. The research method is based on the use of a mass model that includes a mass due to systems hardware and a mass due to the system energy usage. An Airbus A320 aircraft wing is used as a case-study application. The mass model parameters are based on first-principle physical analysis of electric and pneumatic power systems combined with empirical data on system hardware from existing equipment suppliers. Flow control methods include direct fluidic, electromechanical-fluidic, and electrofluidic actuator technologies. The mass cost of electrical power distribution is shown to be considerably less than that for pneumatic systems; however, this advantage is reduced by the requirement for relatively heavy electrical power management and conversion systems. A tradeoff exists between system power efficiency and the system hardware mass required to achieve this efficiency. For short-duration operation the flow control solution is driven toward lighter but less power-efficient systems, whereas for long-duration operation there is benefit in considering heavier but more efficient systems. It is estimated that a practical electromechanical-fluidic system for flow separation control may have a mass up to 40% of the slat mass for a leading-edge application and 5% of flap mass for a trailing-edge application.This work is funded by the Sixth European Union Framework Programme as part of the AVERT project (Contract No. AST5-CT-2006-030914

Sagopilone (ZK-EPO, ZK 219477) for recurrent glioblastoma. A phase II multicenter trial by the European Organisation for Research and Treatment of Cancer (EORTC) Brain Tumor Group

Background: Sagopilone (ZK 219477), a lipophylic and synthetic analog of epothilone B, that crosses the blood-brain barrier has demonstrated preclinical activity in glioma models. Patients and methods: Patients with first recurrence/progression of glioblastoma were eligible for this early phase II and pharmacokinetic study exploring single-agent sagopilone (16 mg/m2 over 3 h every 21 days). Primary end point was a composite of either tumor response or being alive and progression free at 6 months. Overall survival, toxicity and safety and pharmacokinetics were secondary end points. Results: Thirty-eight (evaluable 37) patients were included. Treatment was well tolerated, and neuropathy occurred in 46% patients [mild (grade 1) : 32%]. No objective responses were seen. The progression-free survival (PFS) rate at 6 months was 6.7% [95% confidence interval (CI) 1.3-18.7], the median PFS was just over 6 weeks, and the median overall survival was 7.6 months (95% CI 5.3-12.3), with a 1-year survival rate of 31.6% (95% CI 17.7-46.4). Maximum plasma concentrations were reached at the end of the 3-h infusion, with rapid declines within 30 min after termination. Conclusions: No evidence of relevant clinical antitumor activity against recurrent glioblastoma could be detected. Sagopilone was well tolerated, and moderate-to-severe peripheral neuropathy was observed in despite prolonged administratio