Subsonic Swept Fan Blade

A gas turbine engine includes a spool, a turbine coupled to drive the spool, a propulsor coupled to be driven at a at a design speed by the turbine through the spool, and a gear assembly coupled between the propulsor and the spool. Rotation of the turbine drives the propulsor at a different speed than the spool. The propulsor includes a hub and a row of propulsor blades that extend from the hub. Each of the propulsor blades includes an airfoil body. The leading edge of the airfoil body has a swept profile such that, at the design speed, a component of a relative velocity vector of a working gas that is normal to the leading edge is subsonic along the entire radial span

Book Reviews

Reviews of the following books: Kennebunkport: The Evolution of An American Town, Volume One, 1603-1923 by Joyce Butler; Patriot on the Kennebec: Major Reuben Colburn, Benedict Arnold and the March ot Quebec, 1775 by Mark A. York; Canoe Indians of Down East Maine by William A. Havilan

Far-field Unlabelled Super-Resolution Imaging with Superoscillatory Illumination

Unlabelled super-resolution is the next grand challenge in imaging. Stimulated emission depletion and single-molecule microscopies have revolutionised the life sciences but are still limited by the need for reporters (labels) embedded within the sample. While the Veselago-Pendry “super-lens” using a negative-index metamaterial is a promising idea for imaging beyond the diffraction limit, there are substantial technological challenges to its realisation. Another route to far-field subwavelength focusing is using optical superoscillations: engineered interference of multiple coherent waves creating an, in principle, arbitrarily small hotspot. Here we demonstrate microscopy with superoscillatory illumination of the object and describe its underlying principles. We show that far-field images taken with superoscillatory illumination are themselves superoscillatory and hence can reveal fine structural details of the object that are lost in conventional far-field imaging. We show that the resolution of a superoscillatory microscope is determined by the size of the hotspot, rather than the bandwidth of the optical instrument. We demonstrate high-frame-rate polarisation-contrast imaging of unmodified living cells with resolution significantly exceeding that achievable with conventional instruments. This non-algorithmic, low-phototoxicity imaging technology is a powerful tool both for biological research and for super-resolution imaging of samples that do not allow labelling, such as the interior of silicon chips

Note and Comment

The Doctrine of Unfair Trade; Valuing Property and Franchises of Public Service Corporations for Fixing Rates; Right of the Interstate Commerce Commission to Adduce Testimony; Rule in Shelley\u27s Case controls Estate Created by Deed to Trustee; The Right of the Garnishee to Dispose of Goods in His Possession While the Litigation is Pending; The Police Power, Billboards and Sky Signs; How Far the Record of Voting Machines is Conclusive

Valuing Rigor in the Risk Management Process

NASA, as an organization, takes risk management (RM) seriously, and for most projects, the risk management process is exemplar. There can be challenges, though, with defining RM processes. For example, many different risk analysis methodologies are available, they can be applied with varying degrees of rigor, and they can have different value depending on how projects use them. In particular, risk analysis methodologies vary considerably in the level of quantitative detail, with more probabilistic techniques encouraged in some situations. We discussed these processes and methodologies with ten project managers (PM) at the NASA Goddard Space Flight Center (GSFC). Our intent was not to prove with some level of statistical significance that some are more helpful than others, but rather to obtain a general understanding of how projects are identifying, and thinking, about risks. This paper describes some of the available risk processes and methodologies, and provides some insights about the benefits that can gained from their use. We provide an in-depth discussion of one quantitative methodology, Probabilistic Risk Assessments (PRAs), and conclude with a few insights from observed best practices

Biological and behavioral factors modify urinary arsenic metabolic profiles in a U.S. population

Abstract Background Because some adverse health effects associated with chronic arsenic exposure may be mediated by methylated arsenicals, interindividual variation in capacity to convert inorganic arsenic into mono- and di-methylated metabolites may be an important determinant of risk associated with exposure to this metalloid. Hence, identifying biological and behavioral factors that modify an individual’s capacity to methylate inorganic arsenic could provide insights into critical dose-response relations underlying adverse health effects. Methods A total of 904 older adults (≥45 years old) in Churchill County, Nevada, who chronically used home tap water supplies containing up to 1850 μg of arsenic per liter provided urine and toenail samples for determination of total and speciated arsenic levels. Effects of biological factors (gender, age, body mass index) and behavioral factors (smoking, recent fish or shellfish consumption) on patterns of arsenicals in urine were evaluated with bivariate analyses and multivariate regression models. Results Relative contributions of inorganic, mono-, and di-methylated arsenic to total speciated arsenic in urine were unchanged over the range of concentrations of arsenic in home tap water supplies used by study participants. Gender predicted both absolute and relative amounts of arsenicals in urine. Age predicted levels of inorganic arsenic in urine and body mass index predicted relative levels of mono- and di-methylated arsenic in urine. Smoking predicted both absolute and relative levels of arsenicals in urine. Multivariate regression models were developed for both absolute and relative levels of arsenicals in urine. Concentration of arsenic in home tap water and estimated water consumption were strongly predictive of levels of arsenicals in urine as were smoking, body mass index, and gender. Relative contributions of arsenicals to urinary arsenic were not consistently predicted by concentrations of arsenic in drinking water supplies but were more consistently predicted by gender, body mass index, age, and smoking. Conclusions These findings suggest that analyses of dose-response relations in arsenic-exposed populations should account for biological and behavioral factors that modify levels of inorganic and methylated arsenicals in urine. Evidence of significant effects of these factors on arsenic metabolism may also support mode of action studies in appropriate experimental models