Three atmospheric dispersion experiments involving oil fog plumes measured by lidar

The Wave Propagation Lab. participated with the U.S. Environmental Protection Agency in a series of experiments with the goal of developing and validating dispersion models that perform substantially better that models currently available. The lidar systems deployed and the data processing procedures used in these experiments are briefly described. Highlights are presented of conclusions drawn thus far from the lidar data

Random-phase-approximation-based correlation energy functionals: Benchmark results for atoms

The random phase approximation (RPA) for the correlation energy functional of density functional theory has recently attracted renewed interest. Formulated in terms of the Kohn-Sham (KS) orbitals and eigenvalues, it promises to resolve some of the fundamental limitations of the local density and generalized gradient approximations, as for instance their inability to account for dispersion forces. First results for atoms, however, indicate that the RPA overestimates correlation effects as much as the orbital-dependent functional obtained by a second order perturbation expansion on the basis of the KS Hamiltonian. In this contribution, three simple extensions of the RPA are examined, (a) its augmentation by an LDA for short-range correlation, (b) its combination with the second order exchange term, and (c) its combination with a partial resummation of the perturbation series including the second order exchange. It is found that the ground state and correlation energies as well as the ionization potentials resulting from the extensions (a) and (c) for closed sub-shell atoms are clearly superior to those obtained with the unmodified RPA. Quite some effort is made to ensure highly converged RPA data, so that the results may serve as benchmark data. The numerical techniques developed in this context, in particular for the inherent frequency integration, should also be useful for applications of RPA-type functionals to more complex systems.Comment: 11 pages, 7 figure

On the use of IR lidar and K(sub a)-band radar for observing cirrus clouds

Advances in lidar and radar technology have potential for providing new and better information on climate significant parameters of cirrus. Consequently, the NOAA Wave Propagation Lab. is commencing CLARET (Cloud Lidar And Radar Exploratory Test) to evaluate the promise of these new capabilities. Parameters under study include cloud particle size distribution, height of cloud bases, tops, and multiple layers, and cloud dynamics revealed through measurement of vertical motions. The first phase of CLARET is planned for Sept. 1989. The CO2 coherent Doppler lidar and the sensitive K sub a band radar hold promise for providing valuable information on cirrus that is beyond the grasp of current visible lidars

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). What are the neuronal mechanisms responsible for these changes and how does targeted stimulation by a BBCI shape population-level synaptic connectivity? The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites are strengthened for spike-stimulus delays consistent with experimentally derived spike time dependent plasticity (STDP) rules. However, the relationship between STDP mechanisms at the level of networks, and their modification with neural implants remains poorly understood. Using our model, we successfully reproduces key experimental results and use analytical derivations, along with novel experimental data. We then derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered stimulation in different regimes of cortical activity.Comment: 35 pages, 9 figure

Progress in interpreting CO2 lidar signatures to obtain cirrus microphysical and optical properties

One cloud/radiation issue at FIRE 2 that has been addressed by the CO2 lidar team is the zenith-enhanced backscatter (ZEB) signature from oriented crystals. A second topic is narrow-beam optical depth measurements using CO2 lidar. This paper describes the theoretical models we have developed for these phenomena and the data-processing algorithms derived from them

Cirrus properties deduced from CO2 lidar observations of zenith-enhanced backscatter from oriented crystals

Many lidar researchers have occasionally observed zenith-enhanced backscatter (ZEB) from middle and high clouds. The ZEB signature consists of strong backscatter when the lidar is pointed directly at zenith and a dramatic decline in backscatter as the zenith angle dips slightly off zenith. Mirror-like reflection from horizontal facets of oriented crystals (especially plates) is generally accepted as the cause. It was found during a 3-year observation program that approximately 50 percent of ice clouds had ZEB, regardless of cloud height. The orientation of crystals and the ZEB they cause are important to study and understand for several reasons. First, radiative transfer in clouds with oriented crystals is different than if the same particles were randomly oriented. Second, crystal growth depends partly on the orientation of the particles. Third, ZEB measurements may provide useful information about cirrus microphysical and radiative properties. Finally, the remarkable effect of ZEB on lidar signals should be understood in order to properly interpret lidar data

A Model-Based Reconstruction Method for Incomplete Projection Industrial Computed Tomography Imaging

In computerized tomography, the cross-sectioned image of an object can be reconstructed from a set of projection data. It provides the ability to image internal structure which can not be inspected effectively with alternate techniques. Based on the Fourier slice theorem[l], projections in a full angular range and with sufficiently fine angular spacing are required to reconstruct a unique image. In some situations, however, complete projections are not available due to physical limitations in the data acquisition process. Image quality is degraded by the absence of complete data. Because most manufactured parts were built from a designer’s blueprint or solid modeling electronic database, a great deal is known about the physical structure of the part. Incorporating a priori information extracted from the CAD model has the potential to enhance incomplete projection CT image quality. In this paper, a model-based CT reconstruction method is presented. The a priori information used to enhance incomplete projection CT image quality is extracted from a 3-D solid modeling electronic database. Engineering database matching is conducted to extract the proper 2D cross-sectioned model image corresponding to the CT projection plane. A moment-based registration method is applied to ensure proper use of a priori information for model-based CT reconstruction. Furthermore, a projection substitution scheme, including projection alignment and automatic scaling method, is developed so that the projection data in the missing angular range calculated from a model image can be automatically rescaled to match the projection data in the available angular range. Experimental results of applying the model-based CT reconstruction method to an industrial part in both the limited-angle and the penetration-limited incomplete projection situations are presented and described. It is shown that the use of a priori information from solid models is a powerful technique for enhancing the quality of incomplete data CT images