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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Human Frontal Lobes and AI Planning Systems

Human frontal lobes are essential for maintaining a self-regulating balance between predictive and reactive behavior. This paper describes a system that integrates prediction and reaction based on neuropsychological theories of frontal lobe function. In addition to enhancing our understanding of deliberate action in humans' the model is being used to develop and evaluate the same properties in machines. First, the paper presents some background neuropsychology in order to set a general context. The role of frontal lobes is then presented by summarizing three theories which formed the basis for this work. The components of an artificial frontal lobe are then discussed from both neuropsychological and AI perspectives. The paper concludes by discussing issues and methods for evaluating systems that integrate planning and reaction.

Levinson, Richard↗

Signatures of Chemical Evolution in Protostellar Nebulae

A decade ago observers began to take serious notice of the presence of crystalline silicate grains in the dust flowing away from some comets. While crystallinity had been seen in such objects previously, starting with the recognitions by Campins and Ryan (1990) that the 10 micron feature of Comet Halley resembled that of the mineral forsterite, most such observations were either ignored or dismissed as no path to explain such crystalline grains was available in the literature. When it was first suggested that an outward flow must be present to carry annealed silicate grains from the innermost regions of the Solar Nebula out to the regions where comets could form (Nuth, 1999; 2001) this suggestion was also dismissed because no such transport mechanism was known at the time. Since then not only have new models of nebular dynamics demonstrated the reality of long distance outward transport (Ciesla, 2007; 2008; 2009) but examination of older models (Boss, 2004) showed that such transport had been present but had gone unrecognized for many years. The most unassailable evidence for outward nebular transport came with the return of the Stardust samples from Comet Wild2, a Kuiper-belt comet that contained micron-scale grains of high temperature minerals resembling the Calcium-Aluminum Inclusions found in primitive meteorites (Zolensky et aI., 2006) that formed at T > 1400K. Now that outward transport in protostellar nebulae has been firmly established, a re-examination of its consequences for nebular gas is in order that takes into account both the factors that regulate both the outward flow as well as those that likely control the chemical composition of the gas. Laboratory studies of surface catalyzed reactions suggest that a trend toward more highly reduced carbon and nitrogen compounds in the gas phase should be correlated with a general increase in the crystallinity of the dust (Nuth et aI., 2000), but is such a trend actually observable? Unlike the Fischer-Tropsch or the Haber-Bosch reactions used in industry, the surface catalyzed reactions seen in our laboratory do not produce a simple product stream of methane or ammonia, respectively. Instead, such reactions produce a wide range of both aliphatic and aromatic hydrocarbons, as well as reduced nitrogen compounds such as ammonia, amines, amides and imides, as gas phase products together with a heavy, macromolecular, kerogen-like surface coating that remains on the grains. While CO and N2 will certainly be depleted by conversion into more complex and less volatile species via reaction on grain surfaces, it may be very difficult to monitor such changes from outside the system.

Nuth, Joseph A., III↗

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗