Resonant Acoustic Determination of Complex Elastic Moduli

A simple, inexpensive, yet accurate method for measuring the dynamic complex modulus of elasticity is described. Using a 'free-free' bar selectively excited in three independent vibrational modes, the shear modulus is obtained by measuring the frequency of the torsional resonant mode and the Young's modulus is determined from measurement of either the longitudinal or flexural mode. The damping properties are obtained by measuring the quality factor (Q) for each mode. The Q is inversely proportional to the loss tangent. The viscoelastic behavior of the sample can be obtained by tracking a particular resonant mode (and thus a particular modulus) using a phase locked loop (PLL) and by changing the temperature of the sample. The change in the damping properties is obtained by measuring the in-phase amplitude of the PLL which is proportional to the Q of the material. The real and imaginary parts or the complex modulus can be obtained continuously as a function of parameters such as temperature, pressure, or humidity. For homogeneous and isotropic samples only two independent moduli are needed in order to characterize the complete set of elastic constants, thus, values can be obtained for the dynamic Poisson's ratio, bulk modulus, Lame constants, etc

Fiber-optic push-pull sensor systems

Fiber-optic push-pull sensors are those which exploit the intrinsically differential nature of an interferometer with concommitant benefits in common-mode rejection of undesired effects. Several fiber-optic accelerometer and hydrophone designs are described. Additionally, the recent development at the Naval Postgraduate School of a passive low-cost interferometric signal demodulator permits the development of economical fiber-optic sensor systems

Why did income growth vary across states during the Great Depression?

State per capita incomes became more disperse during the contraction phase of the Great Depression, and less disperse during the recovery phase. We investigate the effects of spatial dependence, industrial composition, bank failures and fiscal policies on state income growth during each phase. We find that industrial composition and spatial interdependencies contributed to negative state income growth during the contraction, whereas New Deal spending contributed to positive state income growth during the recovery phase. We find no evidence that differences in bank failure rates or state government expenditures contributed to variation in state income growth rates.Depressions

A spatial analysis of state banking regulation

We use a spatial model to investigate a state’s choice of branch banking and interstate banking regimes as a function of the regime choices made by other states and other variables suggested in the literature. We extend the basic spatial econometric model by allowing spatial dependence to vary by geographic region. Our findings reveal that spatial effects have a large, statistically significant impact on state regulatory regime decisions. The importance of spatial correlation in the setting of state banking policies suggests the need to consider spatial effects in empirical models of state policies in general.Banks and banking ; Bank supervision

Regional disparities in the spatial correlation of state income growth

This paper presents new evidence of spatial correlation in U.S. state income growth. We extend the basic spatial econometric model used in the growth literature by allowing spatial correlation in state income growth to vary across geographic regions. We find positive spatial correlation in income growth rates across neighboring states, but that the strength of this spatial correlation varies considerably by region. Spatial correlation in income growth is highest for states located in the Northeast and the South. Our findings have policy implications both at the state and national level, and also suggest that growth models may benefit from incorporating more complex forms of spatial correlation.Regional economics ; Income distribution

Insights into centriole geometry revealed by cryotomography of doublet and triplet centrioles.

Centrioles are cylindrical assemblies comprised of 9 singlet, doublet, or triplet microtubules, essential for the formation of motile and sensory cilia. While the structure of the cilium is being defined at increasing resolution, centriolar structure remains poorly understood. Here, we used electron cryo-tomography to determine the structure of mammalian (triplet) and Drosophila (doublet) centrioles. Mammalian centrioles have two distinct domains: a 200 nm proximal core region connected by A-C linkers, and a distal domain where the C-tubule is incomplete and a pair of novel linkages stabilize the assembly producing a geometry more closely resembling the ciliary axoneme. Drosophila centrioles resemble the mammalian core, but with their doublet microtubules linked through the A tubules. The commonality of core-region length, and the abrupt transition in mammalian centrioles, suggests a conserved length-setting mechanism. The unexpected linker diversity suggests how unique centriolar architectures arise in different tissues and organisms

Kerstetter et al. Supplemental Materials

This document provides additional photographs to the Kerstetter et al. main text from baited game camera placements in West Lake Park, Broward County, Florida (USA) from January 2019 through January 2020

Update on the Fishes of Texas Project

Poster presentation presented at the 2017 Texas Academy of Sciences annual meeting in Belton, Texas on March 4, 2017.The Fishes of Texas project (www.fishesoftexas.org), originating in 2006, remains the most reliable (quality controlled) and data rich site for acquiring occurrence data for Texas fishes, holding over 124,000 records from 42 institutions. Among many discoveries, the project is responsible for detecting at least 3 freshwater species not previously known from the state. We continue making improvements, but substantial updates so far have been onerous for our developers for various reasons. A recent major update reduces coding redundancies, points the website to a new massively restructured and more fully normalized PostgreSQL database (was MySQL), and places the code in a versioning environment. These changes have little immediate effect on user experience, but will greatly accelerate development. PostgreSQL allows for complex spatial queries which will allow users to quickly map occurrence data alongside many more political/environmental layers than currently possible. While our database/web designers have been implementing these changes and fixing bugs etc., we’ve been preparing resources for them to integrate into the website. Some highlights to expect: 1 new updates to the state Species of Greatest Concern list; 2 expert opinion-determined nativity spatial layers for all freshwater fishes displaying in our new mapping system; 3 dynamic statistical summaries; 4 new data types from the literature (>14,900 records), citizen science (>4,300), anglers (>37,000), and agency databases (>1,000,000); 5 new museum records, many derived from our gap sampling (~19,000, 4 museums); 6 more specimen examinations (>400) and photographs (1000); 7 document archive with “smart” text search tools (currently in beta testing using TPWD fisheries reports). So be patient and keep your eyes open for updates.University of Texas at Austin, Texas Parks and Wildlife Department, Texas Commission on Environmental Quality, U.S. Department of the Interior,Integrative Biolog

Statistical methods for automated drug susceptibility testing: Bayesian minimum inhibitory concentration prediction from growth curves

Determination of the minimum inhibitory concentration (MIC) of a drug that prevents microbial growth is an important step for managing patients with infections. In this paper we present a novel probabilistic approach that accurately estimates MICs based on a panel of multiple curves reflecting features of bacterial growth. We develop a probabilistic model for determining whether a given dilution of an antimicrobial agent is the MIC given features of the growth curves over time. Because of the potentially large collection of features, we utilize Bayesian model selection to narrow the collection of predictors to the most important variables. In addition to point estimates of MICs, we are able to provide posterior probabilities that each dilution is the MIC based on the observed growth curves. The methods are easily automated and have been incorporated into the Becton--Dickinson PHOENIX automated susceptibility system that rapidly and accurately classifies the resistance of a large number of microorganisms in clinical samples. Over seventy-five studies to date have shown this new method provides improved estimation of MICs over existing approaches.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS217 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Fiber Optic Accelerometer With Centrally Supported Flexural Disk

PatentAn accelerometer or seismometer has an elastic disk bearing a mass distributed peripherally around the disk. The disk is supported for flexure and for isolation from mounting strain by a stob centrally through the disk. The accelerometer or seismometer has a pair of flat spirals of optical fiber, each spiral being fixedly attached to a corresponding disk side so that disk flexure lengthens a spiral on one disk side and shortens a spiral on an oppositely facing disk side and so that temperature differences between the spirals are minimized. The pair of spirals are connected as legs of a fiber optic interferometer so that the interferometer provides an output corresponding to the flexure. Several of the disks and asociated pairs of spirals may be coaxially mounted to provide increased sensitivity