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At least 235 records · Page 13

Data Mining for Vortices on the Earth's Magnetosphere - Algorithm Application for Detection and Analysis

Unsteady processes in the solar wind– magnetosphere interaction, such as vortices developed at the magnetopause boundary by the Kelvin–Helmholtz instability, may contribute to the process of mass, momentum and energy transfer into the Earth’s magnetosphere. The research described in this paper validates an algorithm to automatically detect and characterize vortices based on velocity data from simulations. The vortex identification algorithm (VIA) systematically searches the 3-D velocity fields to identify critical points where the magnitude of the velocity vector vanishes. The velocity gradient tensor is computed and its invariants are used to assess vortex structure in the flow field. We use the Community Coordinated Modeling Center (CCMC) Runs on Request capability to create a series of model runs initialized from the conditions observed by the Cluster mission in the Hwang et al. (2011) analysis of Kelvin–Helmholtz vortices observed during southward interplanetary magnetic field (IMF) conditions. We analyze further the properties of the vortices found in the runs, including the velocity changes within their motion across the magnetosheath. We also demonstrate the potential of our tool to identify and characterize other transient features (e.g., flux transfer events, FTEs) with vortical internal structures. We find that the vortices are associated with flows on the magnetosheath side of the magnetopause that reach speeds greater than the solar wind speed at the bow shock.

Collado-Vega, Yaireska M.↗

Characterization of physio-chemical properties of polymeric and electrochemical materials for aerospace flight

Sealed nickel cadmium cells having undergone a large number of cycles were discharged using the Hg/HgO reference electrode. The negative electrode exhibited the second plateau. SEM of negative plates of such cells show clusters of large crystals of cadmium hydroxide. These large crystals on the negative plates disappear after continuous overcharging in flooded cells. Atomic Absorption Spectroscopy and standard wet chemical methods are being used to determine the cell materials viz: nickel, cadmium, cobalt, potassum and carbonate. The anodes and cathodes are analyzed after careful examination and the condition of the separator material is evaluated.

Rock, M.↗

Parameters Inference and Model Reduction for the Single-Particle Model of Li Ion Cells

The Single-Particle Model (SPM) of Li ion cell is a computationally efficient model for simulating Li ion cell for weak to moderate currents. The model depends n a number of parameters describing the geometry and material properties of a cell components. In order to apply the model to simulating a cell, the best-fit parametric values have to be inferred from a constant discharge data. We report our efforts to determine the best-fit set for 18650 LP batteries. We found that rather than being best-fit by a particular point in the parametric space the data is fit equally well by an ensemble of points clustering about an effective multidimensional manifold in the parametric space. This property of the SPM is known to be shared by a multitude of the so-called "sloppy models" of complex systems, characterized by a few stiff directions in the parametric space, in which the predicted behavior varies significantly, and a number of sloppy directions in which the behavior doesn't change appreciably. Only the stiff parameters combinations are identifiable. Geometrical features of the BFM give insights to possible reduction of the SPM to a model having fewer sloppy parameters. We have constructed a hierarchy of such models. The fully reduced model depends on only stiff effective parameters which are identifiable and can be used for characterization of the battery's state of health.

Khasin, Michael↗

Physiological Maturation of Regenerating Hair Cells

The bullfrog saccule, a sensor of gravity and substrate-borne vibration, is a model system for hair cell transduction. Saccular hair cells also increase in number throughout adult life and rapidly recover after hair cell damage, making this organ an ideal system for studying hair cell development, repair, and regeneration. We have used of hair cell and supporting cell immunocytochemical markers to identify damaged hair cells and hair cell precursors in organotypic cultures of the bullfrog saccule. We then used an innovative combination of confocal, electron, and time-lapse microscopy to study the fate of damaged hair cells and the origin of new hair cells after gentamicin ototoxicity in normal and mitotically blocked saccular cultures. These studies have shown that gentamicin ototoxicity produces both lethal and sublethal hair cell damage. They have also shown that hair cell recovery in this organ takes place by both the repair of sublethally damaged hair cells and by the replacement of lost hair cells by mitotic regeneration. In parallel studies, we have used biophysical and molecular biological techniques to study the differentiation and innervation of developing, repairing, and regenerating hair cells. More specifically, we have used RT-PCR to obtain the bullfrog homologues of L-type voltage- gated calcium (L-VGCC) and large-conductance Ca(2+)-activated potassium (BK) channel genes. We have then obtained probes for these genes and, using in situ hybridization, begun to examine their expression in the bullfrog saccule and amphibian papilla. We have also used fluorescent-labeled channel toxins and channel toxin derivatives to determine the time of appearance of L-type voltage-gated calcium (L-VGCC) and Ca(2+)-activated potassium (BK) channels and to study dynamic changes in the number, distribution, and co-localization of these proteins in developing, repairing, and regenerating hair cells. Using time-lapse microscopy, we are also studying the dynamic relationship between ion channel clustering and synaptic formation in hair cells and afferent neurons. In future studies, we will determine when hair cell precursors acquire electrical tuning, and, using whole-cell patch-clamp techniques, identify and characterize their L-VGCC and BK currents. We will also use biophysical techniques to determine the number of L-VGCC and BK channels and the size and gating kinetics of their underlying L-VGCC and BK conductances, correlating these variables with the amplitude and frequency of membrane oscillations produced by intracellular current steps. We expect these studies to determine how hair cells regulate ion channel expression to achieve specific physiological responses.

Baird, Richard A.↗

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

Northern dwarf and low surface brightness galaxies. IV - The large-scale space distribution

Results are reported from a statistical analysis of published observational data on a sample of 860 northern dwarf and low-surface-brightness (D/LSB) galaxies with delta = 0 deg or greater and b between -40 and 40 deg, selected from the Uppsala General Catalogue of Galaxies (Nilson et al., 1973). The results are presented in extensive redshift/space maps, histograms, graphs and tables and characterized in detail. It is shown that the distribution of D/LSB galaxies closely resembles that of bright galaxies, apparently ruling out biased-star-formation models predicting a uniform distribution of D/LSBs. Although bright galaxies outside clusters are somewhat more clustered than the H I-rich D/LSBs, the latters' pairwise peculiar velocity (460 + or - 50 km/sec) is similar to that of the former.

Thuan, Trinh X.↗

Global, Multi-Objective Trajectory Optimization With Parametric Spreading

Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

trajectory design↗

On the redistribution of OB star luminosity and the warming of nearby molecular clouds

Infrared Astronomy Satellite (IRAS) observations of the neighborhoods of six outer-Galaxy HII regions were combined with CO observations to show that most of the far infrared (FIR) luminosity from within approximately 25 to 75 pc of the ionizing stars is contributed by dust in molecular clouds, not by dust in the low-density ionized gas. Dust associated with the clouds is warmed by absorption of UV and visible light from the cluster of stars responsible for the ionization. Most of the OB cluster starlight is not absorbed locally. A fraction of the order of 10% of the OB cluster luminosity is absorbed by nearby molecular clouds and reradiated as FIR light. The luminosity per unit mass for the heated clouds is approximately 3 to 13 solar luminosity/solar mass, approximately one order of magnitude greater than the corresponding ratio for clouds found near clusters without O stars, and two orders of magnitude greater than the ratio for dark clouds heated primarily by the interstellar radiation field. If the observations of clouds near outer-Galaxy HII regions are used to characterize the molecular clouds heated by HII regions in the inner-Galaxy, then at most 30% of the Galaxy's molecular cloud mass is actively engaged in the formation of massive stars at the present time.

Leisawitz, D.↗

Characteristic archaebacterial 16S rRNA oligonucleotides

A method of analyzing 16S rRNA catalog data has been developed in which groupings at various taxonomic levels can be characterized in terms of specific "signature" oligonucleotides. This approach provides an alternative means for evaluating higher order branching possibilities and can be used to assess the phylogenetic position of isolates that are poorly placed by the usual clustering procedures. This signature approach has been applied to forty archaebacterial catalogs and every oligonucleotide with significant signature value has been identified. Sets of specific oligonucleotides were identified for every major group on a dendrogram produced by cluster analysis procedures. Signatures that would establish between group relationships were also sought and found. In the case of the Methanobacteriaceae the clustering methods suggest a specific relationship to the Methanococcaceae. This inclusion is in fact supported by six strong signature oligonucleotides. However there are also significant numbers of signature oligonucleotides supporting a specific relationship of the Methanobacteriaceae to either the Halobacteriaceae or the Methanomicrobiaceae. Thus the placement of the Methanobacteriaceae is less certain than the usual dendrograms imply. The signature approach also was used to assess the phylogenetic position of Thermoplasma acidophilum which is found to be more closely related to the methanogen/halophile Division than to the sulfur dependent Division of the archaebacteria. This does not imply however that Thermoplasma acidophilum is properly regarded as being in the methanogen/halophile Division.

NASA Discipline Exobiology↗

X-Ray Fingerprinting Techniques for Recognizing A Hydrological Role in the Formation of Minerals on the Surface of Mars

Previous work has demonstrated the ability of a miniaturized XRD-XRF instrument to perform in-situ analyses without sample preparation or acquisition. Deployment of this instrument on a Martian rover will allow a large number of rapid qualitative analyses, which will maximize the diversity of samples studied and selected for possible return. As a first step in designing a decision tree for recognizing minerals in complex mixtures, d spacings were plotted against intensity for several mineral groups comprising rock and soil types inferred for the surface of Mars (weathered basalt, playa and hydrothermal deposits, clay-rich soils). In all groups, d spacings cluster in a range from about 1-4 angstroms, which can under certain circumstances obscure patterns for individual phases. However, within the silicate family, minerals containing either bound OH- or molecules of H20 (clays, micas, amphiboles, zeolites) are characterized by a shift of peaks to higher d spacings. Large d spacings (greater than about 7 angstroms) thus act as a first-order filter for distinguishing hydrous from anhydrous silicates. The ability to quickly verify the presence of silicates that have interacted with water has important implications for using mineral chemistry and structure to help decipher the hydrologic and atmospheric history of Mars. This represents a beginning for developing more sophisticated methods of pattern recognition. These will combine XRD and XRF analyses with optical data to rapidly7 discern environmentally diagnostic assemblages without the necessity of identifying every peak individual mineral phase.

Metzger, Ellen P.↗

NanoSIMS Sheds Light on the Origin and Significance of Early Archean Organic Microstructures from the Pilbara of Australia

NanoSIMS was used to characterize sub-micron scale morphology and elemental composition (C, N, S, Si, O) of organic microstructures in Early Archean (3 - 3.4 Ga) charts from the Pilbara of Western Australia. Three categories of structures were analyzed: small spheroids in clusters; spindle-shaped remains; and large spheroids. All are relatively poorly preserved and occur within the chert matrix of the samples. Carbonaceous material in a secondary hydrothermal vein also was analyzed, as an example of non-indigenous organic matter. Comparisons were made of NanoSIMS characteristics of the Archean samples and those from well-preserved, biogenic microfossils in the 0.8 Ga Bitter Springs Formation. The comparisons show that the Pilbara microstructures are generally distinct from material in the hydrothermal vein but similar in morphology and elemental composition to the Bitter Springs microfossils. In addition, the Pilbara structures exhibit a spatial relationship to silicon and oxygen that seemingly reflects silica nucleation on organic surfaces; this argues that the organic frameworks of the Archean structures were present in the sediment during crystallization of the silica matrix. The structures are thus interpreted as being indigenous to the enclosing sediment. While these results are suggestive of Early Archean biogenicity and are consistent with a growing body of data suggesting that life on Earth was well established by 3 to 3.4 Ga, work is continuing to determine the N/C and 13C ratios of individual forms, and this should provide additional insight into the derivation and significance of these ancient organic remains.

Oehler, Dorothy Z.↗

Origin, Transport, and Vertical Distribution of Atmospheric Polluntants over the Northern Sourth China Sea During the 7-SEAS-Dongsha Experiment

During the spring of 2010, comprehensive in situ measurements were made for the first time on a small atoll (Dongsha Island) in the northern South China Sea (SCS), a key region of the 7-SEAS (the Seven South East Asian Studies) program. This paper focuses on characterizing the source origins, transport processes, and vertical distributions of the Asian continental outflows over the region, using measurements including mass concentration, optical properties, hygroscopicity, and vertical distribution of the aerosol particles, as well as the trace gas composition. Cluster analysis of backward trajectories classified 52% of the air masses arriving at ground level of Dongsha Island as having a continental origin, mainly from northern China to the northern SCS, passing the coastal area and being confined in the marine boundary layer (0-0.5 km). Compared to aerosols of oceanic origin, the fine mode continental aerosols have a higher concentration, extinction coefficient, and single-scattering albedo at 550 nm (i.e., 19 vs. 14 microg per cubic meter in PM(sub 2.5); 77 vs. 59 M per meter in beta(sub e); and 0.94 vs. 0.90 in omega, respectively). These aerosols have a higher hygroscopicity (f at 85% RH = 2.1) than those in the upwind inland regions, suggesting that the aerosols transported to the northern SCS were modified by the marine environment. In addition to the near-surface aerosol transport, a significant upper-layer (3-4 km) transport of biomass-burning aerosols was observed. Our results suggest that emissions from both China and Southeast Asia could have a significant impact on the aerosol loading and other aerosol properties over the SCS. Furthermore, the complex vertical distribution of aerosols-coinciding-with-clouds has implications for remote-sensing observations and aerosol-cloud-radiation interactions.

pollutants↗

Landslides in West Coast Metropolitan Areas: The Role of Extreme Weather Events

Rainfall-induced landslides represent a pervasive issue in areas where extreme rainfall intersects complex terrain. A farsighted management of landslide risk requires assessing how landslide hazard will change in coming decades and thus requires, inter alia, that we understand what rainfall events are most likely to trigger landslides and how global warming will affect the frequency of such weather events. We take advantage of 9 years of landslide occurrence data compiled by collating Google news reports and of a high-resolution satellite-based daily rainfall data to investigate what weather triggers landslide along the West Coast US. We show that, while this landslide compilation cannot provide consistent and widespread monitoring everywhere, it captures enough of the events in the major urban areas that it can be used to identify the relevant relationships between landslides and rainfall events in Puget Sound, the Bay Area, and greater Los Angeles. In all these regions, days that recorded landslides have rainfall distributions that are skewed away from dry and low-rainfall accumulations and towards heavy intensities. However, large daily accumulation is the main driver of enhanced hazard of landslides only in Puget Sound. There, landslide are often clustered in space and time and major events are primarily driven by synoptic scale variability, namely "atmospheric rivers" of high humidity air hitting anywhere along the West Coast, and the interaction of frontal system with the coastal orography. The relationship between landslide occurrences and daily rainfall is less robust in California, where antecedent precipitation (in the case of the Bay area) and the peak intensity of localized downpours at sub-daily time scales (in the case of Los Angeles) are key factors not captured by the same-day accumulations. Accordingly, we suggest that the assessment of future changes in landslide hazard for the entire the West Coast requires consideration of future changes in the occurrence and intensity of atmospheric rivers, in their duration and clustering, and in the occurrence of short-duration (sub-daily) extreme rainfall as well. Major regional landslide events, in which multiple occurrences are recorded in the catalog for the same day, are too rare to allow a statistical characterization of their triggering events, but a case study analysis indicates that a variety of synoptic-scale events can be involved, including not only atmospheric rivers but also broader cold- and warm-front precipitation. That a news-based catalog of landslides is accurate enough to allow the identification of different landslide/ rainfall relationships in the major urban areas along the US West Coast suggests that this technology can potentially be used for other English-language cities and could become an even more powerful tool if expanded to other languages and non-traditional news sources, such as social media.

landslides↗

Springtime SEA Air Is Consistently Both Smoky and Humid, but This Relationship (and Its Radiative Effects) Varies Spatially and Seasonally

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. A previous study discussed the spatial characteristics of the water vapor-BB plume observations in the September 2016 flight data and their degree of agreement with several atmospheric reanalyses and models. In the present work, we first discuss atmospheric chemistry, structure, and aerosol results from all three ORACLES deployments to place these results in a broader seasonal context. Despite the differing locations and season of each deployment, we show that there continues to be good agreement between the airborne ORACLES dataset and large-scale reanalyses, specifically the ECMWF ERA5 and CAMS reanalyses. Other reanalyses (specifically NASA's MERRA-2) preserved the observed correlation between meteorology and biomass burning conditions, but, as was seen for 2016, was frequently displaced spatially relative to the observations. The CAMS reanalysis performs better with water vapor than with CO. Results comparing CAMS column AOD to the field measurements show slight overestimates, consistent with previous analysis, but the good relationship observed between AOD and inlet-based aerosol extinction demonstrates this metric's utility to broader studies. The good ERA5/CAMS/ORACLES agreement allows us to next examine the multi-year seasonal patterns and trends beyond the three ORACLES deployment periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalysis, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. This classification will allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗

The Seasonal Evolution of Atmospheric Vertical Structure of Smoke and Humidity Over the Southeast Atlantic Biomass Burning Region

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region; this correlation is persistent through the biomass burning season, although varying through the course of the season. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. We use the ORACLES observations to assess this smoke-vapor relationship. First, we discuss the good agreement between the airborne ORACLES dataset and the ECMWF ERA5 and CAMS reanalyses, as well as results from NASA’s MERRA-2, as seen over the three deployment years. We then use the reanalyses to develop a framework in which to understand more broadly the radiative and dynamical interactions between the elevated smoke and water vapor over the SEA through the biomass burning season, beyond the three ORACLES observation periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalyses, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. The radiative heating of both aerosol and water vapor has potential to influence the cloud-top entrainment and atmospheric turbulence, thus modifying the underlying stratocumulus cloud properties. We next discuss how these smoke-humidity variations influence both the low-cloud fraction (as observed by MODIS and VIIRS, and output by ERA5) and the boundary layer height in the region. This classification will ultimately allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗

Energy Landscape, and Structural and Spectroscopic Characterization of Diazirine and Its Cyclic Isomers

Identifying new nitrogenated hydrocarbon molecules in the interstellar medium (ISM) is challenging due to the lack of comprehensive spectroscopic data from experiments. In this computational work, we focus on investigating the structures, relative energies, spectroscopic constants, and energy landscape of the cyclic isomers of diazirine (c-CH2N2) using ab initio quantum chemical methods. Density functional theory (DFT) methods and coupled cluster theory with singles and doubles including perturbative triples [CCSD(T)] and CCSD(T) with the explicitly correlated F12 b correction [CCSD(T)-F12b] were employed for this purpose along with large correlation consistent cc-pVTZ, cc-pVQZ, and cc-pV5Z basis sets. Harmonic vibrational frequencies, infrared vibrational intensities, rotational constants, and dipole moments are reported. An harmonic vibrational fundamentals along with centrifugal distortion constants, and vibration-rotation interaction constants are also reported for all the cyclic isomers. The energies computed with the CCSD(T) and CCSD(T)-F12b methods were extrapolated to the one-particle complete basis set (CBS) limit following a three-point formula. At the CCSD(T)-F12b/CBS level of theory the 3,3H-diazirine (c-CH2N2) is the lowest energy cyclic isomer followed by 1,3H-diazirine, (E)-1,2H-Diazirine, and (Z)-1,2H-diazirine which are 20.1, 47.8, and 51.3kcal mol-1above the 3,3H-Diazirine, respectively. Accurate structures and spectroscopic constants that are reported here could be useful for future identification of these cyclic nitrogenated organic molecules in the interstellar medium or circumstellar disks.

Energy Landscape↗

Is There a Cosmological Constant?

The grant contributed to the publication of 18 refereed papers and 5 conference proceedings. The primary uses of the funding have been for page charges, travel for invited talks related to the grant research, and the support of a graduate student, Charles Keeton. The refereed papers address four of the primary goals of the proposal: (1) the statistics of radio lenses as a probe of the cosmological model (#1), (2) the role of spiral galaxies as lenses (#3), (3) the effects of dust on statistics of lenses (#7, #8), and (4) the role of groups and clusters as lenses (#2, #6, #10, #13, #15, #16). Four papers (#4, #5, #11, #12) address general issues of lens models, calibrations, and the relationship between lens galaxies and nearby galaxies. One considered cosmological effects in lensing X-ray sources (#9), and two addressed issues related to the overall power spectrum and theories of gravity (#17, #18). Our theoretical studies combined with the explosion in the number of lenses and the quality of the data obtained for them is greatly increasing our ability to characterize and understand the lens population. We can now firmly conclude both from our study of the statistics of radio lenses and our survey of extinctions in individual lenses that the statistics of optically selected quasars were significantly affected by extinction. However, the limits on the cosmological constant remain at lambda < 0.65 at a 2-sigma confidence level, which is in mild conflict with the results of the Type la supernova surveys. We continue to find that neither spiral galaxies nor groups and clusters contribute significantly to the production of gravitational lenses. The lack of group and cluster lenses is strong evidence for the role of baryonic cooling in increasing the efficiency of galaxies as lenses compared to groups and clusters of higher mass but lower central density. Unfortunately for the ultimate objective of the proposal, improved constraints on the cosmological constant, the next large survey for gravitational lenses did not release its results during the term of the proposal. The research supported the career development. of six graduate students (polar, Fletcher, Herold, Keeton, Deng and Rusin) and two post-docs (Labor and Munoz).

Kochanek, Christopher↗

Possibilistic clustering for shape recognition

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

Keller, James M.↗