4,132 research outputs found
Design of an electron microscope phase plate using a focused continuous-wave laser
We propose a Zernike phase contrast electron microscope that uses an intense
laser focus to convert a phase image into a visible image. We present the
relativistic quantum theory of the phase shift caused by the
laser-electron-interaction, study resonant cavities for enhancing the laser
intensity, and discuss applications in biology, soft materials science, and
atomic and molecular physics.Comment: 5 pages, 3 figure
Physiology and phylogeny of green sulfur bacteria forming a monospecific phototrophic assemblage at a depth of 100 meters in the Black Sea
The biomass, phylogenetic composition, and photoautotrophic metabolism of green sulfur bacteria in the Black Sea was assessed in situ and in laboratory enrichments. In the center of the western basin, bacteriochlorophyll e (BChl e) was detected between depths of 90 and 120 m and reached maxima of 54 and 68 ng liter−1. High-pressure liquid chromatography analysis revealed a dominance of farnesyl esters and the presence of four unusual geranyl ester homologs of BChl e. Only traces of BChl e (8 ng liter−1) were found at the northwestern slope of the Black Sea basin, where the chemocline was positioned at a significantly greater depth of 140 m. Stable carbon isotope fractionation values of farnesol indicated an autotrophic growth mode of the green sulfur bacteria. For the first time, light intensities in the Black Sea chemocline were determined employing an integrating quantum meter, which yielded maximum values between 0.0022 and 0.00075 μmol quanta m−2 s−1 at the top of the green sulfur bacterial layer around solar noon in December. These values represent by far the lowest values reported for any habitat of photosynthetic organisms. Only one 16S rRNA gene sequence type was detected in the chemocline using PCR primers specific for green sulfur bacteria. This previously unknown phylotype groups with the marine cluster of the Chlorobiaceae and was successfully enriched in a mineral medium containing sulfide, dithionite, and freshly prepared yeast extract. Under precisely controlled laboratory conditions, the enriched green sulfur bacterium proved to be capable of exploiting light intensities as low as 0.015 μmol quanta m−2 s−1 for photosynthetic 14CO2 fixation. Calculated in situ doubling times of the green sulfur bacterium range between 3.1 and 26 years depending on the season, and anoxygenic photosynthesis contributes only 0.002 to 0.01% to total sulfide oxidation in the chemocline. The stable population of green sulfur bacteria in the Black Sea chemocline thus represents the most extremely low-light-adapted and slowest-growing type of phototroph known to date
A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models
Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks
A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models
Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks
Co-registration of Laser Altimeter Tracks with Digital Terrain Models and Applications in Planetary Science
We have derived algorithms and techniques to precisely co-register laser altimeter profiles with gridded Digital Terrain Models (DTMs), typically derived from stereo images. The algorithm consists of an initial grid search followed by a least-squares matching and yields the translation parameters at sub-pixel level needed to align the DTM and the laser profiles in 3D space. This software tool was primarily developed and tested for co-registration of laser profiles from the Lunar Orbiter Laser Altimeter (LOLA) with DTMs derived from the Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) stereo images. Data sets can be co-registered with positional accuracy between 0.13 m and several meters depending on the pixel resolution and amount of laser shots, where rough surfaces typically result in more accurate co-registrations. Residual heights of the data sets are as small as 0.18 m. The software can be used to identify instrument misalignment, orbit errors, pointing jitter, or problems associated with reference frames being used. Also, assessments of DTM effective resolutions can be obtained. From the correct position between the two data sets, comparisons of surface morphology and roughness can be made at laser footprint- or DTM pixel-level. The precise co-registration allows us to carry out joint analysis of the data sets and ultimately to derive merged high-quality data products. Examples of matching other planetary data sets, like LOLA with LRO Wide Angle Camera (WAC) DTMs or Mars Orbiter Laser Altimeter (MOLA) with stereo models from the High Resolution Stereo Camera (HRSC) as well as Mercury Laser Altimeter (MLA) with Mercury Dual Imaging System (MDIS) are shown to demonstrate the broad science applications of the software tool
Partisan impacts on the economy: evidence from prediction markets and close elections
Analyses of the effects of election outcomes on the economy have been hampered by the problem that economic outcomes also influence elections. We sidestep these problems by analyzing movements in economic indicators caused by clearly exogenous changes in expectations about the likely winner during election day. Analyzing high frequency financial fluctuations following the release of flawed exit poll data on election day 2004, and then during the vote count we find that markets anticipated higher equity prices, interest rates and oil prices, and a stronger dollar under a George W. Bush presidency than under John Kerry. A similar Republican–Democrat differential was also observed for the 2000 Bush–Gore contest. Prediction market based analyses of all presidential elections since 1880 also reveal a similar pattern of partisan impacts, suggesting that electing a Republican president raises equity valuations by 2–3 percent, and that since Ronald Reagan, Republican presidents have tended to raise bond yields
ROOT CAUSE ANALYSIS OF LABOR SHORTAGES IN THE SKILLED TRADES SUPPORTING NAVY SHIPYARD MAINTENANCE AND MODERNIZATION
The U.S. Navy is experiencing significant delays in ship and submarine maintenance periods. A major factor in these delays is the lack of skilled trades engaged in the shipyard industry, both in the public and private sectors. Often referred to as “blue-collar,” these trades include electrical, welding, piping, mechanical, machining, and others. This thesis is a research-based root cause analysis aimed at understanding and addressing the fundamental reasons for this labor shortage. Utilizing the Ishikawa method adapted for this application, including a fishbone diagram, a multitude of root causes are identified, touching on topics such as economics, public policy, federal government contracting, education, and national security. Recommendations for actions to be taken include recruiting and training initiatives, while topic areas like government contracting are recommended for future research.Civilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited
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