Correcting for Activity Effects on the Temperatures, Radii, and Estimated Masses of Low-Mass Stars and Brown Dwarfs

We present empirical relations for determining the amount by which the effective temperatures and radii---and therefore the estimated masses---of low-mass stars and brown dwarfs are altered due to chromospheric activity. Accurate estimates of stellar radii are especially important in the context of searches for transiting exoplanets, which rely upon the assumed stellar radius/density to infer the planet radius/density. Our relations are based on a large set of well studied low-mass stars in the field and on a set of benchmark low-mass eclipsing binaries. The relations link the amount by which an active object's temperature is suppressed, and its radius inflated, to the strength of its Halpha emission. These relations are found to approximately preserve bolometric luminosity. We apply these relations to the peculiar brown-dwarf eclipsing binary 2M0535-05, in which the active, higher-mass brown dwarf has a cooler temperature than its inactive, lower-mass companion. The relations correctly reproduce the observed temperatures and radii of 2M0535-05 after accounting for the Halpha emission; 2M0535-05 would be in precise agreement with theoretical isochrones were it inactive. The relations that we present are applicable to brown dwarfs and low-mass stars with masses below 0.8 Msun and for which the activity, as measured by Halpha, is in the range -4.6 < log Lha/Lbol < -3.3. We expect these relations to be most useful for correcting radius and mass estimates of low-mass stars and brown dwarfs over their active lifetimes (few Gyr). We also discuss the implications of this work for determinations of young cluster IMFs.Comment: To appear in Cool Stars 17 proceeding

The "new genetics" and clinical practice

The document attached has been archived with permission from the editor of the Medical Journal of Australia. An external link to the publisher’s copy is included.A "new genetics" has emerged driven by knowledge gained at the DNA level. In clinical practice, a practical application of the new genetics is DNA testing, which can be expected to expand with the completion of the Human Genome Project as the functions of new genes are discovered. Genetic DNA testing scenarios include diagnostic DNA testing, prenatal DNA testing, predictive (presymptomatic) DNA testing and screening DNA testing. The challenge for genetic DNA testing and clinical practice will be to define the roles to be played by the general practitioner, the specialist, and other healthcare professionals. From the patients' and families' perspective, the new genetics will best be implemented if a planned approach is adopted in the ordering of DNA tests and the associated counselling and support processes.Ronald J A Trent, Robert Williamson and Grant R Sutherlan

Frame Selection in a Connectionist Model Of High-Level Inferencing

Frame selection is a fundamental problem in high-level reasoning. Connectionist models have been unable to approach this problem because of their inability to represent multiple dynamic variable bindings and use them by applying general knowledge rules. These deficits have barred them from performing the high-level inferencing necessary for planning, reasoning, and natural language understanding. This paper describes a localist spreading-activation model, ROBIN, which solves a significant subset of these problems. ROBIN incorporates the normal semantic network su^ucture of previous localist networks, but has additional stfucture to handle variables and dynamic role-binding. Each concept in the network has a uniquely-identifying activation value, called its signature. A dynamic binding is created when a binding node receives the activation of a concept's signature. Signatures propagates across paths of binding nodes to dynamically instantiate candidate inference paths, which are selected by the evidential activation on the network's semantic structure. R O B I N is thus able to approach many of the high-level inferencing and frame selection tasks not handled by previous connectionist models

Grain legume evaluation

Pea variety evaluation, 89NM20, 89EB22, 89KA68, 89N334, 89EB24, 89SC27, 89A24, 89EB33, 89EB25. Grain legume species evaluation, 89NM21, 89MO41, 89N25, 89MC9, 89NM21, 89A22. Faba bean evaluation, 89MO42, 89A23, 89MC10, 89EB27, 89SG22 Grain legume agronom

Grain legumes evaluation.

Lupin agronomy, 87AL14. Nitrogen fertilizer for legume crops, 87BA2. Pea variety evaluation, 87C59, 87M08, 87ME1, 87N012, 87SG8, 87KA7, 87N2. Interstate pea variety trials, 87N096, 87N099, 87KA6. Disease Resistance Pea Variety Testing, 87JE1. Grain legume species comparisons, 87A2, 87C2, 87KA37, 87M09, 87MA1, 87NA15. Legume species variety trials, 87LG2. Faba bean evaluation, 87MC34 and 87KA8. Faba bean \u27synthetic\u27 variety yield trial, 87MC36. Faba bean screening nursery, 87MC35. Preliminary agronomy of faba bean, chickpea and lentil, 87A21. Seeding date, 87A22. Legume species herbicide tolerance, 87KA82

Rainbow Thresholds

We extend a recent breakthrough result relating expectation thresholds and actual thresholds to include rainbow versions

Validation of a Monte Carlo Based Depletion Methodology Using HFIR Post-Irradiation Measurements

Post-irradiation uranium isotopic atomic densities within the core of the High Flux Isotope Reactor (HFIR) were calculated and compared to uranium mass spectrographic data measured in the late 1960s and early 70s [1]. This study was performed in order to validate a Monte Carlo based depletion methodology for calculating the burn-up dependent nuclide inventory, specifically the post-irradiation uraniu