GaAs monolithic frequency doublers with series connected varactor diodes

GaAs monolithic frequency doublers using series connected varactor diodes have been fabricated for the first time. Output powers of 150 mW at 36.9 GHz with 24% efficiency and 300 mW at 24.8 GHz with 18% efficiency have been obtained. Peak efficiencies of 35% at output power levels near 100 mW have been achieved at both frequencies. Both K-band and Ka-band frequency doublers are derived from a lower power, single-diode design by series connection of two diodes and scaling to achieve different power and frequency specifications. Their fabrication was accomplished using the same process sequence

HEAO 3 upper limits to the expected 1634 KeV line from SS 483

A model based on 24 Mg(1369) was developed as the source of the lines in which refractory grains in the jets, containing Mg and 0, are bombarded, by ambient protons in the local ISM. The narrowness of the features results because the recoil Mg nucleus is stopped in the grain before the 1369 keV excited state decays. A consequence of the 24 Mg interpretation is the expected appearance of other emission lines, due to 20 Ne and 20 Na, which are produced by proton bombardment of 24 Mg at the 33 MeV/nucleon energy corresponding to the velocity of the jets. These lines appear at rest energies of 1634 keV and 1636 keV, respectively, and should have essentially the same total flux as that emited at 1369 keV. The HEAO 3 data are examined to search for the 1634 keV (rest) emission. The observation and analysis, the results, and the implications for the understanding of SS 433 are discussed

High-resolution spectrum of Cygnus X-1

A high resolution spectrum of Cygnus X-1 in the 45 to 600 keV range is presented. The measurement was made by the HEAO 3 gamma ray spectrometer during 82 days in the fall of 1979 and spring of 1980, when the source was in its normal low state. Results of a search for narrow emission lines from the source are reported. The spectrum shows no significant narrow features. The 3 delta upper limit to a narrow 511 keV annihilation line is 3 x 0.0001 photons/sq cm/s. There is also no evidence in HEAO 3 broadband data above 500 keV for the broad annihilation feature observed by HEAO 1

Galactic distribution of interstellar Al-26

A narrow cosmic gamma ray line at 1809 keV was discovered which was interpreted as resulting from the decay of approximately 3 M sub theta of Al-26 residing in the galactic disk. While its intrinsic width was unresolved by the HEAO 3 spectrometer, a (1 sigma) limit of 3 keV FWHM was obtained; this corresponds to bulk motions of v 250 km/s, which is consistent with material at rest in the ISM. Sites which have been suggested include type II supernovae and massive stars which are members of the extreme population I, as well as novae and red giants which are associated with an older disk population. The HEAO 3 data was used to distinguish between these two stellar populations

Beluga, Delphinapterus leucas, Distribution and Survey Effort in the Gulf of Alaska

Beluga, Delphinapterus leucas, distribution in the Gulf of Alaska and adjacent inside waters was examined through a review of surveys conducted as far back as 1936. Although beluga sightings have occurred on almost every marine mammal survey in northern Cook Inlet (over 20 surveys reported here), beluga sightings have been rare outside the inlet in the Gulf of Alaska. More than 150,000 km of dedicated survey effort in the Gulf of Alaska resulted in sightings of over 23,000 individual cetaceans, of which only 4 beluga sightings (5 individuals) occurred. In addition, nearly 100,000 individual cetaceans were reported in the Platforms of Opportunity database; yet, of these, only 5 sightings (39 individuals) were belugas. Furthermore, approximately 19 beluga sightings (>260 individuals), possibly including resightings, have been reported without information on effort or other cetacean sightings. Of the 28 sightings of belugas outside of Cook Inlet, 9 were near Kodiak Island, 10 were in or near Prince William Sound, 8 were in Yakutat Bay, and 1 anomalous sighting was well south of the Gulf. These sightings support archaeological and commercial harvest evidence indicating the only persistent group of belugas in the Gulf of Alaska occurs in Cook Inlet

Report of the x ray and gamma ray sensors panel

Overall five major areas of technology are recommended for development in order to meet the science requirements of the Astrotech 21 mission set. These are: detectors for high resolution gamma ray spectroscopy, cryogenic detectors for improved x ray spectral and spatial resolution, advanced x ray charge coupled devices (CCDs) for higher energy resolution and larger format, extension to higher energies, liquid and solid position sensitive detectors for improving stopping power in the energy range 5 to 500 keV and 0.2 to 2 MeV. Development plans designed to achieve the desired capabilities on the time scales required by the technology freeze dates have been recommended in each of these areas

Semi-supervised Eigenvectors for Large-scale Locally-biased Learning

In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks "nearby" that prespecified target region. For example, one might be interested in the clustering structure of a data graph near a prespecified "seed set" of nodes, or one might be interested in finding partitions in an image that are near a prespecified "ground truth" set of pixels. Locally-biased problems of this sort are particularly challenging for popular eigenvector-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing a methodology to construct semi-supervised eigenvectors of a graph Laplacian, and we illustrate how these locally-biased eigenvectors can be used to perform locally-biased machine learning. These semi-supervised eigenvectors capture successively-orthogonalized directions of maximum variance, conditioned on being well-correlated with an input seed set of nodes that is assumed to be provided in a semi-supervised manner. We show that these semi-supervised eigenvectors can be computed quickly as the solution to a system of linear equations; and we also describe several variants of our basic method that have improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph Laplacian