Radio spectra of the low-luminosity active galactic nucleus NGC 266 at centimetre-to-submillimetre wavelengths

We report multi-frequency and multi-epoch radio continuum observations with multi-spatial resolution for the low-luminosity active galactic nucleus (LLAGN) NGC 266. In the centimetre regime, we find diffuse components with Very Large Array (VLA) observations, and a variable compact core with a rising spectrum with Very Long Baseline Array (VLBA) observations. Although the spectral index of the rising spectrum is consistent with the prediction of the simple advection-dominated accretion flow (ADAF) model, the observed radio power is slightly high compared with that of the model prediction. A spectral break at centimetre-to-millimetre wavelengths is inferred from the upper limits of flux densities from Nobeyama Millimetre Array (NMA) and James Clerk Maxwell Telescope (JCMT) data at millimetre and submillimetre wavelengths, respectively. More complicated considerations are required for the theoretical model to interpret such observed radio properties.     

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 lower limit to the field strength in magnetic reconnection sites in solar flares inferred from hard X-ray bursts

It is shown how the hard X-ray burst count rate and itse-folding ime can be used to estimate the minimum magnetic fieldB _min required in a flare magnetic reconnection site for the burst to be interpreted in terms of a thick target model. Application of the method to data from the Solar Maximum Mission (HXRBS) indicates absolute minimum fields well in excess of 100 G, and impossibly high values for some reconnection geometries.     

Robertson-Walker type model with conformally invariant scalar field with trace-free energy momentum tensor

A non-static exact solution of the Einstein equations corresponding to a conformally invariant scalar field with trace-free energy momentum tensor is obtained for the Robertson-Walker type metric. Some physical properties of the solution are discussed.     

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.     

What Drives Star Formation?

Current theoretical models for what drives star formation (especially low-mass star formation) are: (1) magnetic support of self-gravitating clouds with ambipolar diffusion removing support in cores and triggering collapse and (2) compressible turbulence forming self-gravitating clumps that collapse as soon as the turbulent cascade produces insufficient turbulent support. Observations of magnetic fields can distinguish between these two models because of different predictions in three areas: (1) magnetic field morphology, (2) the scaling of field strength with density and non-thermal velocities, and (3) the mass to magnetic flux ratio, M/Φ. We first discuss the techniques and limitations of methods for observing magnetic fields in star formation regions, then describe results for the L1544 prestellar core as an exemplar of the observational results. Application of the three tests leads to the following conclusions. The observational data show that both magnetic fields and turbulence are important in molecular cloud physics. Field lines are generally regular rather than chaotic, implying strong field strengths. But fields are not aligned with the minor axes of oblate spheroidal clouds, suggesting that turbulence is important. Field strengths appear to scale with non-thermal velocity widths, suggesting a significant turbulent support of clouds. Giant Molecular Clouds (GMCs) require mass accumulation over sufficiently large volumes that they would likely have an approximately critical M/Φ. Yet H I clouds are observed to be highly subcritical. If self-gravitating (molecular) clouds form with the subcritical M/Φ of H I clouds, the molecular clouds will be subcritical. However, the observations of molecular cloud cores suggest that they are approximately critical, with no direct evidence for subcritical molecular clouds or cloud envelopes. Hence, the observations remain inconclusive in deciding between the two extreme-case models of what drives star formation. What is needed to further advance our understanding of the role of magnetic fields in the star formation process are additional high sensitivity surveys of magnetic field strengths and other cloud properties in order to further refine the assessment of the importance of magnetic fields in molecular cores and envelopes.