Substrate-mediated interactions and intermolecular forces between molecules adsorbed on surfaces

Adsorbate interactions and reactions on metal surfaces have been investigated using scanning tunneling microscopy. The manners in which adsorbates perturb the surface electronic structure in their vicinity are discussed. The effects these perturbations have on other molecules are shown to be important in overlayer growth. Interactions of molecules with surface steps are addressed, and each molecule's electron affinity is shown to dictate its adsorption sites at step edges. Standing waves emanating from steps are demonstrated to effect transient molecular adsorption up to 40 A away from the step edge. Halobenzene derivatives are used to demonstrate how the surface is important in aligning reactive intermediates.     

Relationship of peroxide value and thiobarbituric acid value to development of undesirable flavor characteristics in fats

The peroxide value and thiobarbituric acid value were compared with the flavor score for a series of different types of fats, with and without added monoglyceride and with and without different stabilizers. The data indicated that the flavor score cannot be estimated for any given fat from either the peroxide value or the thiobarbituric acid value. Either can be used to follow the development of off flavors in a given product or formulation but the relative level may vary from product to product. Presented at the AOCS Meeting in Minneapolis, 1963.     

Quantum correlations at negative absolute temperatures

We study behavior of quantum discord, a kind of quantum correlation, in systems of dipole–dipole interacting spins in an external magnetic field in the whole temperature range ( \(-\infty ). It was shown that negative temperatures, which are introduced to describe inversions in the population in a finite level system, provide more favorable conditions for emergence of quantum correlations including entanglement. We show that at negative temperature, the correlations become more intense and discord exists between remote spins being in separated states.     

Biodesulfurization of dibenzothiophene sulfone by Arthrobacter sp. and studies with oxidized Illinois No. 6 coal

A bacterium identified as Arthrobacter sp. was grown on dibenzothiophene (DBT) sulfone as a sole source of sulfur, producing sulfite and sulfate. Sulfur in DBT sulfone (1.0 mM) was nearly quantitatively converted to sulfate by the organism. The organism could also use DBT sulfone as a sole source of carbon and energy. There was evidence for transient accumulation of benzoic acid in the culture medium after growth of the cells slowed. The DBT sulfoxide analogue 9-fluorenone was converted by resting cells to a product identified as 1,10-dihydroxy-1,10-dihydrofluoren-9-one, suggesting that DBT sulfone may be metabolized via an angular hydroxylation resulting in carbon- sulfur bond cleavage. This strain of Arthrobacter showed no ability to desulfurize oxidized Illinois No. 6 coal.     

Creep of 6H α-Silicon Carbide Single Crystals

The compressive creep behavior of single-crystal 6H α-SiC was measured for orientations parallel to and at 45° to [0001]. Deformation of the 45° orientation was dominated by basal slip. Steady-state creep rates above 10^-7/s were measured at temperatures as low as 800°C. An activation energy of 277 kJ/mol and a stress exponent of 3.32 were determined. Creep testing with applied stresses parallel to [0001] was performed at 1650°C to 1850°C, yielding a stress exponent and activation energy of 4.93 and 180 kJ/mol, respectively. The occurrence of basal slip in the [0001] specimens suggested that significant off-axis stresses were present during testing.     

Rheological properties of molten poly(ethylene terephthalate)

The complete steady-state flow properties of molten poly(ethylene terephthalate) for shear stresses ≦4.14 × 10⁶ dynes/cm² were determined. A single, complete master curve had been constructed in earlier work by Gregory and Watson; the curve interrelates the shear stress, shear rate, temperature, and molecular weight (inherent viscosity) by using a temperature superposition scheme from the literature and a similar molecular weight superposition scheme. Equations in agreement with theory and with other published experimental data were derived from the master curve. Results presented here make possible the direct calculation of the melt viscosity of poly(ethylene terephthalate) at shear stresses ≦4.14 × 10⁶ dynes/cm². The effects of a unit temperature change and/or a unit change in inherent viscosity (I. V.) on the melt viscosity were determined. For poly(ethylene terephthalate) with a 0.6 I. V., a 0.0025 change in I. V. accounts for about the same change in melt viscosity as a 1°C change in temperature.     

An ontology-driven framework towards building enterprise semantic information layer

Enterprises Information Systems (EIS) have been applied for decades in Computer-Aided Engineering (CAE) and Computer-Aided Design (CAD), where huge amount of increasing data is stored in the heterogeneous and distributed systems. As systems evaluating, system redesign and reengineering are demanded. A facing challenge is how to interoperate among different systems by overcoming the gap of conceptual heterogeneity. In this article, an enlarged data representation called semantic information layer (SIL) is described for facilitating heterogeneous systems interoperable. SIL plays a role as mediation media and knowledge representation among heterogeneous systems. The SIL building process is based on ontology engineering, including ontology extraction from relational database (RDB), ontology enrichment and ontology alignment. Mapping path will maintain the links between SIL and data source, and query implementation and user interface are for retrieving data and interacting with end users. We described fully a practical ontology-driven framework for building SIL and introduced extensively relevant standards and techniques for implementing the framework. In the core part of ontology development, a dynamic multi-strategies ontology alignment with automatic matcher selection and dynamic similarity aggregation is proposed. A demonstration case study in the scenario of mobile phone industry is used to illustrate the proposed framework.     

Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR

Remote sensing of invasive species is a critical component of conservation and management efforts, but reliable methods for the detection of invaders have not been widely established. In Hawaiian forests, we recently found that invasive trees often have hyperspectral signatures unique from that of native trees, but mapping based on spectral reflectance properties alone is confounded by issues of canopy senescence and mortality, intra- and inter-canopy gaps and shadowing, and terrain variability. We deployed a new hybrid airborne system combining the Carnegie Airborne Observatory (CAO) small-footprint light detection and ranging (LiDAR) system with the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) to map the three-dimensional spectral and structural properties of Hawaiian forests. The CAO-AVIRIS systems and data were fully integrated using in-flight and post-flight fusion techniques, facilitating an analysis of forest canopy properties to determine the presence and abundance of three highly invasive tree species in Hawaiian rainforests.

The LiDAR sub-system was used to model forest canopy height and top-of-canopy surfaces; these structural data allowed for automated masking of forest gaps, intra- and inter-canopy shadows, and minimum vegetation height in the AVIRIS images. The remaining sunlit canopy spectra were analyzed using spatially-constrained spectral mixture analysis. The results of the combined LiDAR-spectroscopic analysis highlighted the location and fractional abundance of each invasive tree species throughout the rainforest sites. Field validation studies demonstrated < 6.8% and < 18.6% error rates in the detection of invasive tree species at  7 m² and  2 m² minimum canopy cover thresholds. Our results show that full integration of imaging spectroscopy and LiDAR measurements provides enormous flexibility and analytical potential for studies of terrestrial ecosystems and the species contained within them.     

Wetland change mapping for the U.S. mid-Atlantic region using an outlier detection technique

Although the impacts of wetland loss are often felt at regional scales, effective planning and management require a comparative assessment of local needs, costs, and benefits. Satellite remote sensing can provide spatially explicit, synoptic land cover change information to support such an assessment. However, a common challenge in conventional remote sensing change detection is the difficulty of obtaining phenologically and radiometrically comparable data from the start and end of the time period of interest. An alternative approach is to use a prior land cover classification as a surrogate for historic satellite data and to examine the self-consistency of class spectral reflectances in recent imagery. We produced a 30-meter resolution wetland change probability map for the U.S. mid-Atlantic region by applying an outlier detection technique to a base classification provided by the National Wetlands Inventory (NWI). Outlier-resistant measures – the median and median absolute deviation – were used to represent spectral reflectance characteristics of wetland class populations, and formed the basis for the calculation of a pixel change likelihood index. The individual scene index values were merged into a consistent region-wide map and converted to pixel change probability using a logistic regression calibrated through interpretation of historic and recent aerial photography. The accuracy of a regional change/no-change map produced from the change probabilities was estimated at 89.6%, with a Kappa of 0.779. The change probabilities identify areas for closer inspection of change cause, impact, and mitigation potential. With additional work to resolve confusion resulting from natural spatial heterogeneity and variations in land use, automated updating of NWI maps and estimates of areal rates of wetland change may be possible. We also discuss extensions of the technique to address specific applications such as monitoring marsh degradation due to sea level rise and mapping of invasive species.     

Maximum-likelihood registration of range images with missing data

Missing data are common in range images, due to geometric occlusions, limitations in the sensor field of view, poor reflectivity, depth discontinuities, and cast shadows. Using registration to align these data often fails, because points without valid correspondences can be incorrectly matched. This paper presents a maximum likelihood method for registration of scenes with unmatched or missing data. Using ray casting, correspondences are formed between valid and missing points in each view. These correspondences are used to classify points by their visibility properties, including occlusions, field of view, and shadow regions. The likelihood of each point match is then determined using statistical properties of the sensor, such as noise and outlier distributions. Experiments demonstrate a high rates of convergence on complex scenes with varying degrees of overlap.