Laboratory studies of the interaction of carbon monoxide with water ice

The interaction of carbon monoxide (CO) with vapour-deposited water(H₂O) ices has been studied using temperature programmed desorption (TPD) and Fourier transform reflection-absorption infrared spectroscopy (FT-RAIRS) over a range of astrophysically relevant temperatures. Such measurements have shown that CO desorption from amorphous H₂Oices is a much more complex process than current astrochemical models suggest. Re-visiting previously reported laboratory experiments (Collings et al., 2003), a rate model has been constructed to explain, in a phenomenological manner, the desorption of CO over astronomically relevant time scales. The model presented here can be widely applied to a range of astronomical environments where depletion of CO from the gas phase is relevant. The model accounts for the two competing processes of CO desorption and migration, and also enables the entrapment of some of the CO in the ice matrix and its subsequent release as the water ice crystallises and then desorbs. The astronomical implications of this model are discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

In-Orbit Vignetting Calibrations of XMM-Newton Telescopes

We describe measurements of the mirror vignetting in the XMM-Newton Observatory made in-orbit, using observations of SNR G21.5-09 and SNR 3C58 with the EPIC imaging cameras. The instrument features that complicate these measurements are briefly described. We show the spatial and energy dependences of measured vignetting, outlining assumptions made in deriving the eventual agreement between simulation and measurement. Alternate methods to confirm these are described, including an assessment of source elongation with off-axis angle, the surface brightness distribution of the diffuse X-ray background, and the consistency of Coma cluster emission at different position angles. A synthesis of these measurements leads to a change in the XMM calibration data base, for the optical axis of two of the three telescopes, by in excess of 1 arcmin. This has a small but measureable effect on the assumed spectral responses of the cameras for on-axis targets. This revised version was published online in July 2006 with corrections to the Cover Date.     

Dynamical implications of Jupiter's tropospheric ammonia abundance

Groundbased radio observations indicate that Jupiter's ammonia is globally depleted from 0.6 bars to at least 4-6 bars relative to the deep abundance of ∼3 times solar, a fact that has so far defied explanation. The observations also indicate that (i) the depletion is greater in belts than zones, and (ii) the greatest depletion occurs within Jupiter's local 5-μm hot spots, which have recently been detected at radio wavelengths. Here, we first show that both the global depletion and its belt-zone variation can be explained by a simple model for the interaction of moist convection with Jupiter's cloud-layer circulation. If the global depletion is dynamical in origin, then important endmember models for the belt-zone circulation can be ruled out. Next, we show that the radio observations of Jupiter's 5-μm hot spots imply that the equatorial wave inferred to cause hot spots induces vertical parcel oscillation of a factor of ∼2 in pressure near the 2-bar level, which places important constraints on hot-spot dynamics. Finally, using spatially resolved radio maps, we demonstrate that low-latitude features exceeding ∼4000 km diameter, such as the equatorial plumes and large vortices, are also depleted in ammonia from 0.6 bars to at least 2 bars relative to the deep abundance of 3 times solar. If any low-latitude features exist that contain 3-times-solar ammonia up to the 0.6-bar ammonia condensation level, they must have diameters less than ∼4000 km.     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

First results from the Gauribidanur Radio heliograph

Observations of the Sun at two frequencies (51 and 77 MHz) using the East-West arm of the Gauribidanur Radio heliograph are presented.     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

The Dergaon (H5) chondrite: Fall,classification, petrological and chemical characteristics,cosmogenic effects,and noble gas records

Abstract— A multiple fall of a stony meteorite occurred near the town of Dergaon in Assam, India, on March 2, 2001. Several fragments weighing <2 kg and a single large fragment weighing ～10 kg were recovered from the strewn field, which extended over several tens of square kilometers. Chemical, petrographic, and oxygen isotopic studies indicate it to be, in most aspects, a typical H5 chondrite, except the unusually low K content of ～340 ppm. A cosmic ray exposure of 9.7 Ma is inferred from the cosmogenic noble gas records. Activities of eleven cosmogenic radionuclides were measured. ²⁶Al and ²²Na activities as well as the ²²Na/²⁶Al activity ratio are close to the values expected on the basis of solar modulation of galactic cosmic rays. The low ⁶⁰Co activity (<1 dpm/kg) is indicative of a small preatmospheric size of the meteorite. Cosmic ray heavy nuclei track densities in olivine grains range from ～106 cm^?2 in samples from the largest fragment to approximately (4–9) × 105 cm^?2 in one of the smaller fragments. The combined track, radionuclide, and noble gas data suggest a preatmospheric radius of ～20 cm for the Dergaon meteorite.