JPL's Real-Time Weather Processor project (RWP) metrics and observations at system completion

As an integral part of the overall upgraded National Airspace System (NAS), the objective of the Real-Time Weather Processor (RWP) project is to improve the quality of weather information and the timeliness of its dissemination to system users. To accomplish this, an RWP will be installed in each of the Center Weather Service Units (CWSUs), located in 21 of the 23 Air Route Traffic Control Centers (ARTCCs). The RWP System is a prototype system. It is planned that the software will be GFE and that production hardware will be acquired via industry competitive procurement. The ARTCC is a facility established to provide air traffic control service to aircraft operating on Instrument Flight Rules (IFR) flight plans within controlled airspace, principally during the en route phase of the flight. Covered here are requirement metrics, Software Problem Failure Reports (SPFRs), and Ada portability metrics and observations

The Sequential Normal Scores Transformation

The sequential analysis of series often requires nonparametric procedures, where the most powerful ones frequently use rank transformations. Re-ranking the data sequence after each new observation can become too intensive computationally. This led to the idea of sequential ranks, where only the most recent observation is ranked. However, difficulties finding, or approximating, the null distribution of the statistics may have contributed to the lack of popularity of these methods. In this paper, we propose transforming the sequential ranks into sequential normal scores which are independent, and asymptotically standard normal random variables. Thus original methods based on the normality assumption may be used. A novel approach permits the inclusion of a priori information in the form of quantiles. It is developed as a strategy to increase the sensitivity of the scoring statistic. The result is a powerful convenient method to analyze non-normal data sequences. Also, four variations of sequential normal scores are presented using examples from the literature. Researchers and practitioners might find this approach useful to develop nonparametric procedures to address new problems extending the use of parametric procedures when distributional assumptions are not met. These methods are especially useful with large data streams where efficient computational methods are required.Comment: 39 pages, 8 figure

Sharp gene pool transition in a population affected by phenotype-based selective hunting

We use a microscopic model of population dynamics, a modified version of the well known Penna model, to study some aspects of microevolution. This research is motivated by recent reports on the effect of selective hunting on the gene pool of bighorn sheep living in the Ram Mountain region, in Canada. Our model finds a sharp transition in the structure of the gene pool as some threshold for the number of animals hunted is reached.Comment: 5 pages, 4 figure

A Group-Based Yule Model for Bipartite Author-Paper Networks

This paper presents a novel model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random invitations from a group to an outside member. To analyze the model, a number of different metrics that can be obtained in author-paper networks were extracted. A simulation example shows that this model can effectively mimic the behavior of a real-world author-paper network, extracted from a collection of 900 journal papers in the field of complex networks.Comment: 13 pages (preprint format), 7 figure

Portraits of Complex Networks

We propose a method for characterizing large complex networks by introducing a new matrix structure, unique for a given network, which encodes structural information; provides useful visualization, even for very large networks; and allows for rigorous statistical comparison between networks. Dynamic processes such as percolation can be visualized using animations. Applications to graph theory are discussed, as are generalizations to weighted networks, real-world network similarity testing, and applicability to the graph isomorphism problem.Comment: 6 pages, 9 figure

Structure-based discovery of glycomimetic FmlH ligands as inhibitors of bacterial adhesion during urinary tract infection

Significance The emergence of multidrug-resistant bacteria, including uropathogenic Escherichia coli (UPEC), makes the development of targeted antivirulence therapeutics a critical focus of research. During urinary tract infections (UTIs), UPEC uses chaperone–usher pathway pili tipped with an array of adhesins that recognize distinct receptors with sterochemical specificity to facilitate persistence in various tissues and habitats. We used an interdisciplinary approach driven by structural biology and synthetic glycoside chemistry to design and optimize glycomimetic inhibitors of the UPEC adhesin FmlH. These inhibitors competitively blocked FmlH in vitro, in in vivo mouse UTI models, and in ex vivo healthy human kidney tissue. This work demonstrates the utility of structure-driven drug design in the effort to develop antivirulence therapeutic compounds. </jats:p

Statistics of an Unstable Barotropic Jet from a Cumulant Expansion

Low-order equal-time statistics of a barotropic flow on a rotating sphere are investigated. The flow is driven by linear relaxation toward an unstable zonal jet. For relatively short relaxation times, the flow is dominated by critical-layer waves. For sufficiently long relaxation times, the flow is turbulent. Statistics obtained from a second-order cumulant expansion are compared to those accumulated in direct numerical simulations, revealing the strengths and limitations of the expansion for different relaxation times.Comment: 23 pages, 8 figures. Version to appear in J. Atmos. Sc