Lithium Depletion in the Sun: A Study of Mixing Based on Hydrodynamical Simulations

Based on radiation hydrodynamics modeling of stellar convection zones, a diffusion scheme has been devised describing the downward penetration of convective motions beyond the Schwarzschild boundary (overshoot) into the radiative interior. This scheme of exponential diffusive overshoot has already been successfully applied to AGB stars. Here we present an application to the Sun in order to determine the time scale and depth extent of this additional mixing, i.e. diffusive overshoot at the base of the convective envelope. We calculated the associated destruction of lithium during the evolution towards and on the main-sequence. We found that the slow-mixing processes induced by the diffusive overshoot may lead to a substantial depletion of lithium during the Sun's main-sequence evolution. This revised version was published online in June 2006 with corrections to the Cover Date.     

Considerations for the Short-Term Stability of Frequency Multipliers

The effects of frequency multiplication circuits on the short-term stability of an oscillator system are analyzed. The short-term stability of real components such as varactor multipliers are compared to the short-term stability of an ?ideal? frequency multiplier which maintains the stability of the basic oscillator. In addition, it is shown that positive feedback like that used in a synchronized oscillator, while useful for tracking, degrades short-term stability.     

High temperature alters the growth reaction of Pottia protonemata.

Under gravistimulation, dark-grown protonemata of Pottia intermedia revealed negative gravitropism with a growth rate of approximately 28 μm·h⁻¹ at room temperature (20 °C). In 7 days, the protonema formed a bundle of vertically oriented filaments. At an elevated temperature (30 °C), bundles of vertically growing filaments were also formed. However, both filament growth rate and amplitude of the gravicurvature were reduced. Red light (RL) irradiation induced a positive phototropism of most apical protonemal cells at 20 °C. In a following period of darkness, approximately two-thirds of such cells began to grow upward again, recovering their negative gravitropism. RL irradiation at the elevated temperature caused a partial increase in the number of protonemal cells with negative phototropism, but the protonemata did not exhibit negative gravitropism after transfer to darkness. The negative gravitropic reaction was renewed only when protonemata were placed at 20 °C. A dramatic decrease in starch amount in protonemal apical cells, which are sensitive to both gravity and light, occurred at the higher temperature. Such a decrease may be one of the reasons for the inhibition of the protonemal gravireaction at the higher temperature. The observation has a bearing on the starch-statolith theory.     

Analysis of an adaptive CFAR detector in non-Gaussian interference

Coherent signal detection in non-Gaussian interference is presently of interest in adaptive array applications. Conventional array detection algorithms inherently model the interference with a multivariate Gaussian random vector. However, non-Gaussian interference models are also under investigation for applications where the Gaussian assumption may not be appropriate. We analyze the performance of an adaptive array receiver for signal detection in interference modeled with a non-Gaussian distribution referred to as a spherically invariant random vector (SIRV). We first motivate this interference model with results from radar clutter measurements collected in the Mountain Top Program. Then we develop analytical expressions for the probability of false alarm and the probability of detection for the adaptive array receiver. Our analysis shows that the receiver has constant false alarm rate (CFAR) performance with respect to all the interference parameters. Some illustrative examples are included that compare the detection performance of this CFAR receiver with a receiver that has prior knowledge of the interference parameters     

Large-scale Coronal Heating, Clustering of Coronal Bright Points, and Concentration of Magnetic Flux

By combining quiet-region Fe XII coronal images from SOHO/EIT with magnetograms from NSO/Kitt Peak and from SOHO/MDI, we show that the population of network coronal bright points and the magnetic flux content of the network are both markedly greater under the bright half of the large-scale quiet corona than under the dim half. These results (1) support the view that the heating of the entire corona in quiet regions and coronal holes is driven by fine-scale magnetic activity (microflares, explosive events, spicules) seated low in the magnetic network, and (2) suggest that this large-scale modulation of the magnetic flux and coronal heating is a signature of giant convection cells. This revised version was published online in June 2006 with corrections to the Cover Date.     

Evaluation of multiple radar target trackers in stressfulenvironments

This paper evaluates the performance of multiple target tracking (MTT) algorithms in real-life stressful radar tracking environments. Real closely spaced maneuver radar data, generated by six F-18 fighters and other targets, were collected jointly by the defence departments of Canada and United States to support this practical MTT algorithm evaluation study. A set of performance metrics was defined here to compare the suboptimal nearest neighbor (SNN), global nearest neighbor (GNN), and various variants of the joint probabilistic data association (JPDA) MTT trackers. Results reveal an interesting result that all these MTT algorithms exhibited very close performance. In addition, the weighted sum approach of the PDA/JPDA trackers which are theoretically effective were observed to perform poorly in tracking closely spaced targets. Overall speaking, the GNN filter based on the Munkres algorithm had the best performance in terms of both tracking performance and robustness