Apparatus for Distilling Alcohol from Biological Fluids and a Calculator for Harger Titrations

For the determination of alcohol in body fluids the Harger (1935) titration is extensively used with distillates obtained in various ways; e.g., by steam distillation, desiccation, distillation from picric acid, picrate-tartrate or tungstic acid. Gibson (1939) has combined it with the simple distillation from picric acid solution (Nicloux, et al. 1934) to produce an essentially satisfactory and rapid determination. Clinical simplicity with research accuracy has been achieved by the use of a specially designed distillation apparatus with the method (Johnston and Gibson, 1940). After using this method for a long period the authors have been able to revise it for still more convenience in use, and to design a calculator for obtaining the alcohol concentration in a body fluid directly from the burette readings of Harger titrations. This paper presents the revised design of the apparatus, with some modifications in use, and the calculator

Fabrication techniques for very fast diffractive lenses

Aspheric lenses with arbitrary phase functions can be fabricated on thin light weight substrates via the binary optics fabrication technique. However, it is difficult and costly to fabricate a fast lens (f/number less than 1) for use as the shorter wavelengths. The pitch of the masks and the alignment accuracy must be very fine. For a large lens, the space-bandwidth product of the element can also become impractically large. In this paper, two alternate approaches for the fabrication of fast aspheric diffractive lenses are described. The first approach fabricates the diffractive lens interferometrically, utilizing a spherical wavefront to provide the optical power of the lens and a computer generated hologram to create the aspheric components. The second approach fabricates the aspheric diffractive lens in the form if a higher order kinoform which trades groove profile fidelity for coarser feature size. The design and implementation issues for these two fabrication techniques are discussed

Letter from Dr. Marron C. Fort

Typed letter from Dr. Marron C. Fort, Coordinator of the Conference on the French Language Community in North America, to Charlotte Michaud.https://digitalcommons.usm.maine.edu/michaud-1970-1973/1017/thumbnail.jp

Sticky central limit theorems on open books

Given a probability distribution on an open book (a metric space obtained by gluing a disjoint union of copies of a half-space along their boundary hyperplanes), we define a precise concept of when the Fr\'{e}chet mean (barycenter) is sticky. This nonclassical phenomenon is quantified by a law of large numbers (LLN) stating that the empirical mean eventually almost surely lies on the (codimension $1$ and hence measure $0$) spine that is the glued hyperplane, and a central limit theorem (CLT) stating that the limiting distribution is Gaussian and supported on the spine. We also state versions of the LLN and CLT for the cases where the mean is nonsticky (i.e., not lying on the spine) and partly sticky (i.e., is, on the spine but not sticky).Comment: Published in at http://dx.doi.org/10.1214/12-AAP899 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

Automated inspection of turbine blades: Challenges and opportunities

Current inspection methods for complex shapes and contours exemplified by aircraft engine turbine blades are expensive, time-consuming and labor intensive. The logistics support of new manufacturing paradigms such as integrated product-process development (IPPD) for current and future engine technology development necessitates high speed, automated inspection of forged and cast jet engine blades, combined with a capability of retaining and retrieving metrology data for process improvements upstream (designer-level) and downstream (end-user facilities) at commercial and military installations. The paper presents the opportunities emerging from a feasibility study conducted using 3-D holographic laser radar in blade inspection. Requisite developments in computing technologies for systems integration of blade inspection in production are also discussed

A Fast and Compact Quantum Random Number Generator

We present the realization of a physical quantum random number generator based on the process of splitting a beam of photons on a beam splitter, a quantum mechanical source of true randomness. By utilizing either a beam splitter or a polarizing beam splitter, single photon detectors and high speed electronics the presented devices are capable of generating a binary random signal with an autocorrelation time of 11.8 ns and a continuous stream of random numbers at a rate of 1 Mbit/s. The randomness of the generated signals and numbers is shown by running a series of tests upon data samples. The devices described in this paper are built into compact housings and are simple to operate.Comment: 23 pages, 6 Figs. To appear in Rev. Sci. Inst