2,672 research outputs found
Electroshock protection circuit
Circuit was developed to prevent accidental shock through electrodes used to test subjects as part of Skylab program. This circuit is placed between electrical apparatus and electrode that is attached to patient's body. Thus, patient is effectively protected from dangerous electrical shock that might be caused by failure in electrical apparatus
Quarterly literature review of the remote sensing of natural resources
The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports
Literature review of the remote sensing of natural resources
Abstracts of 596 documents related to remote sensors or the remote sensing of natural resources by satellite, aircraft, or ground-based stations are presented. Topics covered include general theory, geology and hydrology, agriculture and forestry, marine sciences, urban land use, and instrumentation. Recent documents not yet cited in any of the seven information sources used for the compilation are summarized. An author/key word index is provided
Displaying 3D images: algorithms for single-image random-dot
A new, simple, and symmetric algorithm can be implemented that results in higher levels of detail in solid objects than previously possible with autostereograms. In a stereoscope, an optical instrument similar to binoculars, each eye views a different picture and thereby receives the specific image that would have arisen naturally. An early suggestion for a color stereo computer display involved a rotating filter wheel held in front of the eyes. In contrast, this article describes a method for viewing on paper or on an ordinary computer screen without special equipment, although it is limited to the display of 3D monochromatic objects. (The image can be colored, say, for artistic reasons, but the method we describe does not allow colors to be allocated in a way that corresponds to an arbitrary coloring of the solid object depicted.) The image can easily be constructed by computer from any 3D scene or solid object description
Earth resources evaluation for New Mexico by LANDSAT-2
The author has identified the following significant results. The Middle Rio Grande project has not yet progressed to the point where mineral exploration sites can be chosen; however, there does appear to be some correlation between the known structure and mineral deposits and the LANDSAT lineament map. A circular feature identified in the southern Magdalena Mountains on LANDSAT-1 imagery agrees well with the location of a newly proposed caldron complex. Several recognized and unrecognized circular features were identified on imagery of the Mogollon-Datil volcanic field. A check of aeromagnetic maps for New Mexico found that the circular features on the LANDSAT imagery showed up as areas of generally high magnetic intensity
Biolistic co-transformation of Metarhizium anisopliae var. acridum strain CG423 with green fluorescent protein and resistance to glufosinate ammonium.
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Automated identification of neurons and their locations
Individual locations of many neuronal cell bodies (>10^4) are needed to
enable statistically significant measurements of spatial organization within
the brain such as nearest-neighbor and microcolumnarity measurements. In this
paper, we introduce an Automated Neuron Recognition Algorithm (ANRA) which
obtains the (x,y) location of individual neurons within digitized images of
Nissl-stained, 30 micron thick, frozen sections of the cerebral cortex of the
Rhesus monkey. Identification of neurons within such Nissl-stained sections is
inherently difficult due to the variability in neuron staining, the overlap of
neurons, the presence of partial or damaged neurons at tissue surfaces, and the
presence of non-neuron objects, such as glial cells, blood vessels, and random
artifacts. To overcome these challenges and identify neurons, ANRA applies a
combination of image segmentation and machine learning. The steps involve
active contour segmentation to find outlines of potential neuron cell bodies
followed by artificial neural network training using the segmentation
properties (size, optical density, gyration, etc.) to distinguish between
neuron and non-neuron segmentations. ANRA positively identifies 86[5]% neurons
with 15[8]% error (mean[st.dev.]) on a wide range of Nissl-stained images,
whereas semi-automatic methods obtain 80[7]%/17[12]%. A further advantage of
ANRA is that it affords an unlimited increase in speed from semi-automatic
methods, and is computationally efficient, with the ability to recognize ~100
neurons per minute using a standard personal computer. ANRA is amenable to
analysis of huge photo-montages of Nissl-stained tissue, thereby opening the
door to fast, efficient and quantitative analysis of vast stores of archival
material that exist in laboratories and research collections around the world.Comment: 38 pages. Formatted for two-sided printing. Supplemental material and
software available at http://physics.bu.edu/~ainglis/ANRA
A mutant of Metarhizium anisopliae var. acridum with enhanced submerged conidiation.
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Previous issue date: 2007-01-16bitstream/item/178116/1/ID-27883-1.pd
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