SONTRAC—a scintillating plastic fiber tracking detector for neutron and proton imaging spectroscopy

SONTRAC (SOlar Neutron TRACking imager and spectrometer) is a conceptual instrument intended to measure the energy and incident direction of 20–150 MeV neutrons produced in solar flares. The intense neutron background in a low-Earth orbit requires that imaging techniques be employed to maximize an instrument’s signal-to-noise ratio. The instrument is comprised of mutually perpendicular, alternating layers of parallel, scintillating, plastic fibers that are viewed by optoelectronic devices. Two stereoscopic views of recoil proton tracks are necessary to determine the incident neutron’s direction and energy. The instrument can also be used as a powerful energetic proton imager. Data from a fully functional 3-d prototype are presented. Early results indicate that the instrument’s neutron energy resolution is approximately 10% with the neutron incident direction determined to within a few degrees

Telecommunications and data acquisition support for the Pioneer Venus Project: Pioneers 12 and 13, prelaunch through March 1984

The support provided by the Telecommunications and Data Acquisition organization of the Jet Propulsion Laboratory (JPL) to the Pioneer Venus missions is described. The missions were the responsibility of the Ames Research Center (ARC). The Pioneer 13 mission and its spacecraft design presented one of the greatest challenges to the Deep Space Network (DSN) in the implementation and operation of new capabilities. The four probes that were to enter the atmosphere of Venus were turned on shortly before arrival at Venus, and the DSN had to acquire each of these probes in order to recover the telemetry being transmitted. Furthermore, a science experiment involving these probes descending through the atmosphere required a completed new data type to be generated at the ground stations. This new data type is known as the differential very long baseline interferometry. Discussions between ARC and JPL of the implementation requirements involved trade-offs in spacecraft design and led to a very successful return of science data. Specific implementation and operational techniques are discussed, not only for the prime mission, but also for the extended support to the Pioneer 12 spacecraft (in orbit around Venus) with its science instruments including that for radar observations of the planet

BOARD INVITED REVIEW: Prospects for improving management of animal disease introductions using disease-dynamic models

Management and policy decisions are continually made to mitigate disease introductions in animal populations despite often limited surveillance data or knowledge of disease transmission processes. Science-based management is broadly recognized as leading to more effective decisions yet application of models to actively guide disease surveillance and mitigate risks remains limited. Disease-dynamic models are an efficient method of providing information for management decisions because of their ability to integrate and evaluate multiple, complex processes simultaneously while accounting for uncertainty common in animal diseases. Here we review disease introduction pathways and transmission processes crucial for informing disease management and models at the interface of domestic animals and wildlife. We describe how disease transmission models can improve disease management and present a conceptual framework for integrating disease models into the decision process using adaptive management principles. We apply our framework to a case study of African swine fever virus in wild and domestic swine to demonstrate how disease-dynamic models can improve mitigation of introduction risk. We also identify opportunities to improve the application of disease models to support decision-making to manage disease at the interface of domestic and wild animals. First, scientists must focus on objective-driven models providing practical predictions that are useful to those managing disease. In order for practical model predictions to be incorporated into disease management a recognition that modeling is a means to improve management and outcomes is important. This will be most successful when done in a cross-disciplinary environment that includes scientists and decisionmakers representing wildlife and domestic animal health. Lastly, including economic principles of value-of-information and cost-benefit analysis in disease-dynamic models can facilitate more efficient management decisions and improve communication of model forecasts. Integration of disease-dynamic models into management and decision-making processes is expected to improve surveillance systems, risk mitigations, outbreak preparedness, and outbreak response activities

The sum number of the cocktail party graph

A graph G is called a sum graph if there exists a labelling of the vertices of G by distinct positive integers such that the vertices labelled u and v are adjacent if and only if there exists a vertex labelled u + v. If G is not a sum graph, adding a finite number of isolated vertices to it will always yield a sum graph, and the sum number oe(G) of G is the smallest number of isolated vertices that will achieve this result. A labelling that realizes G + K oe(G) as a sum graph is said to be optimal. In this paper we consider G = H m;n , the complete n-partite graph on n 2 sets of m 2 nonadjacent vertices. We give an optimal labelling to show that oe(H 2;n ) = 4n \Gamma 5, and in the general case we give constructive proofs that oe(H m;n ) 2 \Omega\Gamma mn) and oe(H m;n ) 2 O(mn 2 ). We conjecture that oe(H m;n ) is asymptotically greater than mn, the cardinality of the vertex set; if so, then H m;n is the first known graph with this property. We also provide for the first time an optimal labelling of the complete bipatite graph Kmn whose smallest label is 1

Modifying the radiative quantum efficiency of erbium-doped glass in silicon slot waveguides

We have modulated the radiative emission rate of Er In SI slot waveguides with Er-doped glass slots by varying the waveguide layer dimensions. The corresponding quantum efficiency of 1537-nm emission varies between 0.37 and 0.51

SONTRAC: an imaging spectrometer for solar neutrons

An instrument capable of unambiguously determining the energy and direction of incident neutrons has important applications in solar physics-as well as environmental monitoring and medical/radiological sciences. The SONTRAC (SOlar Neutron TRACking) instrument is designed to operate in the neutron energy range of 20-250 MeV. The measurement principle is based on non-relativistic double scatter of neutrons off ambient protons (n-p scattering) within a block of densely packed scintillating fibers. Using this double-scatter mode it is possible to uniquely determine neutron energy and direction on an event-by-event basis. A fully operational science model of such an instrument has been built using 300 μm (250 μm active) scintillating fibers. The science model consists of a 5×5×5 cm cube of orthogonal plastic scintillating fiber layers. Two orthogonal imaging chains, employing image intensifiers and CCD cameras, allow full 3-dimensional reconstruction of scattered proton particle tracks. We report the results of the science model instrument calibration using 35-65 MeV protons. The proton calibration is the first step toward understanding the instrument response to n-p scatter events. Preliminary results give proton energy resolution of 2% (6%) at 67.5 (35) MeV, and angular resolution of 2° (4.5°) at 67.5 (35) MeV. These measurements are being used to validate detailed instrument simulations that will be used to optimize the instrument design and develop quantitative estimates of science return. Based on the proton calibration, neutron energy and angular resolution for a 10×10×10 cm version of SONTRAC is expected to be ~5% an