Compression of Multi-frequency Eddy Current Data using Principal Components Analysis for Pressure Tube to Calandria Tube Gap Measurement

Inspection of components with multi-variable influential parameters may result in a loss of accuracy for the measurement of the target variable. A particular example occurs in the case of a pressure tube (PT) that is contained within a calandria tube (CT) in the fuel channels of CANDU® nuclear reactors. Eddy current (EC) based measurement of gap between PT and CT, as required by nuclear regulators, is affected by variation of PT wall thickness and resistivity, which may confound the accurate gap measurement. In this work principal components analysis (PCA) is examined as a means of simplifying changes in multi-frequency EC data so that the effect on EC signals from multiple parameters may be identified. PCA of analytical model and laboratory results are examined and redundant information in the multi-frequency EC data is removed. An additional benefit of PCA is compressed data acquisition, which permits increased inspection speed and monitoring of multi-parameter variation using a reduced number of variables

Reversible skew laurent polynomial rings and deformations of poisson automorphisms

A skew Laurent polynomial ring S = R[x(+/- 1); alpha] is reversible if it has a reversing automorphism, that is, an automorphism theta of period 2 that transposes x and x(-1) and restricts to an automorphism gamma of R with gamma = gamma(-1). We study invariants for reversing automorphisms and apply our methods to determine the rings of invariants of reversing automorphisms of the two most familiar examples of simple skew Laurent polynomial rings, namely a localization of the enveloping algebra of the two-dimensional non-abelian solvable Lie algebra and the coordinate ring of the quantum torus, both of which are deformations of Poisson algebras over the base field F. Their reversing automorphisms are deformations of Poisson automorphisms of those Poisson algebras. In each case, the ring of invariants of the Poisson automorphism is the coordinate ring B of a surface in F-3 and the ring of invariants S-theta of the reversing automorphism is a deformation of B and is a factor of a deformation of F[x(1), x(2), x(3)] for a Poisson bracket determined by the appropriate surface

RNA interference of gonadotropin-inhibitory hormone gene induces arousal in songbirds.

Gonadotropin-inhibitory hormone (GnIH) was originally identified in quail as a hypothalamic neuropeptide inhibitor of pituitary gonadotropin synthesis and release. However, GnIH neuronal fibers do not only terminate in the median eminence to control anterior pituitary function but also extend widely in the brain, suggesting it has multiple roles in the regulation of behavior. To identify the role of GnIH neurons in the regulation of behavior, we investigated the effect of RNA interference (RNAi) of the GnIH gene on the behavior of white-crowned sparrows, a highly social songbird species. Administration of small interfering RNA against GnIH precursor mRNA into the third ventricle of male and female birds reduced resting time, spontaneous production of complex vocalizations, and stimulated brief agonistic vocalizations. GnIH RNAi further enhanced song production of short duration in male birds when they were challenged by playbacks of novel male songs. These behaviors resembled those of breeding birds during territorial defense. The overall results suggest that GnIH gene silencing induces arousal. In addition, the activities of male and female birds were negatively correlated with GnIH mRNA expression in the paraventricular nucleus. Density of GnIH neuronal fibers in the ventral tegmental area was decreased by GnIH RNAi treatment in female birds, and the number of gonadotropin-releasing hormone neurons that received close appositions of GnIH neuronal fiber terminals was negatively correlated with the activity of male birds. In summary, GnIH may decrease arousal level resulting in the inhibition of specific motivated behavior such as in reproductive contexts

Countercurrent Chromatography Fractions of Plant Extracts with Anti-Tuberculosis Activity

Samples of numerous plant species were received from the southwestern part of the USA, from Richard Spjut, and plant samples were collected here in Illinois. All were extracted with typical solvents, giving crude residues, some of which were subjected to chromatographic methods. Some of the crude residues and some of the fractions were tested for anti-tuberculosis activity and/or antibacterial activity. In a general way, bioactive natural products are dealt with very well by Liang & Fang. More specifically, the southwestern part of the United States has a large variety of indigenous plants many of which have not been investigated for their medicinal potential, and only very few have had their extracts separated into the individual compounds they may contain. But, some information is available for Native American herbal uses (Moerman,2003)

The concentration-discharge slope as a tool for water quality management

Recent technological breakthroughs of optical sensors and analysers have enabled matching the water quality measurement interval to the time scales of stream flow changes and led to an improved understanding of spatially and temporally heterogeneous sources and delivery pathways for many solutes and particulates. This new ability to match the chemograph with the hydrograph has promoted renewed interest in the concentration-discharge (c-q) relationship and its value in characterizing catchment storage, time lags and legacy effects for both weathering products and anthropogenic pollutants. In this paper we evaluated the stream c-q relationships for a number of water quality determinands (phosphorus, suspended sediments, nitrogen) in intensively managed agricultural catchments based on both high-frequency (sub-hourly) and long-term low-frequency (fortnightly-monthly) routine monitoring data. We used resampled high-frequency data to test the uncertainty in water quality parameters (e.g. mean, 95th percentile and load) derived from low-frequency sub-datasets. We showed that the uncertainty in water quality parameters increases with reduced sampling frequency as a function of the c-q slope. We also showed that different sources and delivery pathways control c-q relationship for different solutes and particulates. Secondly, we evaluated the variation in c-q slopes derived from the long-term low-frequency data for different determinands and catchments and showed strong chemostatic behaviour for phosphorus and nitrogen due to saturation and agricultural legacy effects. The c-q slope analysis can provide an effective tool to evaluate the current monitoring networks and the effectiveness of water management interventions. This research highlights how improved understanding of solute and particulate dynamics obtained with optical sensors and analysers can be used to understand patterns in long-term water quality time series, reduce the uncertainty in the monitoring data and to manage eutrophication in agricultural catchments

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Interfacial Stress in the Development of Biologics: Fundamental Understanding, Current Practice, and Future Perspective

Biologic products encounter various types of interfacial stress during development, manufacturing, and clinical administration. When proteins come in contact with vapor–liquid, solid–liquid, and liquid–liquid surfaces, these interfaces can significantly impact the protein drug product quality attributes, including formation of visible particles, subvisible particles, or soluble aggregates, or changes in target protein concentration due to adsorption of the molecule to various interfaces. Protein aggregation at interfaces is often accompanied by changes in conformation, as proteins modify their higher order structure in response to interfacial stresses such as hydrophobicity, charge, and mechanical stress. Formation of aggregates may elicit immunogenicity concerns; therefore, it is important to minimize opportunities for aggregation by performing a systematic evaluation of interfacial stress throughout the product development cycle and to develop appropriate mitigation strategies. The purpose of this white paper is to provide an understanding of protein interfacial stability, explore methods to understand interfacial behavior of proteins, then describe current industry approaches to address interfacial stability concerns. Specifically, we will discuss interfacial stresses to which proteins are exposed from drug substance manufacture through clinical administration, as well as the analytical techniques used to evaluate the resulting impact on the stability of the protein. A high-level mechanistic understanding of the relationship between interfacial stress and aggregation will be introduced, as well as some novel techniques for measuring and better understanding the interfacial behavior of proteins. Finally, some best practices in the evaluation and minimization of interfacial stress will be recommended