Fourier classification images in cardiac nuclear medicine

At present, the diagnosis of cardiac left ventricular regional wall motion abnormalities (RWMA) in nuclear medicine is aided mainly by phase images and amplitude images, which picture the spatial distribution of the phase and of the amplitude of the first harmonics of pixel time activity curves, respectively. However, they do not utilize other information contained in the original radionuclide images, and they do not offer a direct diagnostic interpretation of the data. The proposed Fourier classification images (FCI) overcome these deficiencies. Their pixel intensities express directly the diagnostic class of RWMA. The FCI pixel intensities are functions of pixel coordinates, Fourier features of pixel time activity curves, and their distribution parameters, and they are not limited by the first harmonics model. The derivation of the pixel classifier includes normalization transformation of coordinates and activities. Fourier analysis of raw image data, and teaching the computer by examples of already diagnosed cases with the help of discriminant analysis. FCI offer direct and robust diagnosis of RWMA, superior to that derived from phase and amplitude images, especially in the detection of mild RWMA.     

Multidisciplinary optimization of gas-quenching process

Distortion as a result of the quenching process is predominantly due to the thermal gradient and phase transformations within the component. Compared with traditional liquid quenching, the thermal boundary conditions during gas quenching are relatively simple to control. By adjusting the gas-quenching furnace pressure, the flow speed, or the spray nozzle configuration, the heat-transfer coefficients can be designed in terms of both the component geometry and the quenching time. The purpose of this research is to apply the optimization methodology to design the gas-quenching process. The design objective is to minimize the distortion caused by quenching. Constraints on the average surface hardness, and its distribution and residual stress are imposed. The heat-transfer coefficients are used as design variables. DEFORM-HT is used to predict material response during quenching. The response surface method is used to obtain the analytical models of the objective function and constraints in terms of the design variables. Once the response surfaces of the objective and constraints are obtained, they are used to search for the optimum heat-transfer coefficients. This process is then used instead of the finite-element analysis. A one-gear blank case study is used to demonstrate the optimization scheme.     

Improved corrosion protection of aluminum alloys by electrodeposited silanes

Organofunctional silanes recently have emerged as outstanding, environmentally friendly corrosion protectors for metal substrates, compared with conventional chromate treatments. A simple immersion technique is typically used to coat the metal surface with silane films. However, the thickness and uniformity of the films are uncontrolled in this process. This paper proposes a new deposition technique for the silane films on the metal surface, i.e., by electrodeposition. Hydrolyzed silanes are water-soluble, ionized molecules, so they can be deposited on metals by electrodeposition. Various combinations of silane mixtures were tested at different voltages, pH values, bath concentrations, and exposure times on panels of alloy aluminum and mirror-polished ferro-plate. The surface structure was characterized by scanning electron microscopy (SEM) and ellipsometry. The resistance of the film to corrosion was investigated by direct current (DC) polarization and electrochemical impedance spectroscopy (EIS) techniques. Electrodeposition results in a more organized and uniform film with fewer pores, compared with immersed or dipped films. This paper was presented at the 2nd International Surface Engineering Congress sponsored by ASM International, on September 15–17, 2003, in Indianapolis, Indiana, and appears on pp. 320–26 of the Proceedings.     

The distribution of grain boundary planes in polycrystals

During the last ten years, techniques have been developed to measure the distribution of grain boundaries in polycrystals as a function of both lattice misorientation and grain boundary plane orientation. This paper presents a brief overview of the techniques used for these measurements and the principle findings of studies implementing these techniques. The most significant findings are that grain boundary plane distributions are anisotropic, that they are scale invariant during normal grain growth, that the most common grain boundary planes are those with low surface energies, that the grain boundary populations are inversely correlated with the grain boundary energy, and that the coincident site lattice number is a poor predictor of the grain boundary energy and population.     

Preparation of Protein-Stabilized β-Carotene Nanodispersions by Emulsification–Evaporation Method

This work was initiated to prepare protein-stabilized β-carotene nanodispersions using emulsification–evaporation. A pre-mix of the aqueous phase composed of a protein and hexane containing β-carotene was subjected to high-pressure homogenization using a microfluidizer. Hexane in the resulting emulsion was evaporated under reduced pressures, causing crystallization and precipitation of β-carotene inside the droplets and formation of β-carotene nanoparticles. Sodium caseinate (SC) was the most effective emulsifier among selected proteins in preparing the nanodispersion, with a monomodal β-carotene particle-size distribution and a 17-nm mean particle size. The results were confirmed by transmission-electron microscopy analysis. SC-stabilized nanodispersion also had considerably high ζ-potential (−27 mV at pH 7), suggesting that the nanodispersion was stable against particle aggregation. Increasing the SC concentration decreased the mean particle size and improved the polydispersity of the nanodispersions. Nanodispersions prepared with higher β-carotene concentrations and higher organic-phase ratios resulted in larger β-carotene particles. Although increased microfluidization pressure did not decrease particle size, it did improve the polydispersity of the nanodispersions. Repeating the microfluidization process at 140 MPa caused the nanodispersions to become polydisperse, indicating the loss of emulsifying capacity of SC due to protein denaturation.     

Informational Entropy: a Failure Tolerance and Reliability Surrogate for Water Distribution Networks

Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies.     

Nature-Inspired Meta-Heuristics on Modern GPUs: State of the Art and Brief Survey of Selected Algorithms

Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly parallel implementation and execution of Nature and Bio-inspired Algorithms with excellent price-to-power ratio. In contrast to common multicore CPUs that contain up to tens of independent cores, the GPUs represent a massively parallel single-instruction multiple-data devices that can nowadays reach peak performance of hundreds and thousands of giga floating-point operations per second. Nature and Bio-inspired Algorithms implement parallel optimization strategies in which a single candidate solution, a group of candidate solutions (population), or multiple populations seek for optimal solution or set of solutions of given problem. Genetic algorithms (GA) constitute a family of traditional and very well-known nature-inspired populational meta-heuristic algorithms that have proved its usefulness on a plethora of tasks through the years. Differential evolution (DE) is another efficient populational meta-heuristic algorithm for real-parameter optimization. Particle swarm optimization (PSO) can be seen as nature-inspired multiagent method in which the interaction of simple independent agents yields intelligent collective behavior. Simulated annealing (SA) is global optimization algorithm which combines statistical mechanics and combinatorial optimization with inspiration in metallurgy. This survey provides a brief overview of the latest state-of-the-art research on the design, implementation, and applications of parallel GA, DE, PSO, and SA-based methods on the GPUs.     

Use of cascade reduction potential for selective precipitation of Au,Cu, and Pb in hydrochloric acid solution

Optimization of reduction potential for electroseparation was studied for the recovery of gold, copper, and lead from acidic solution. A linear sweep voltammetric method enabled us to determine characteristic reduction potentials for each metal and the kinetics of the metal deposition indicated by current-voltage curves. In order to precipitate the metal species sequentially, reduction potentials were examined for the individual and mixed solutions of Au(III), Cu(II), and Pb(II). The three metals were reasonably well isolated from the mixed solutions such as Cu(II)/ Pb(II) and Au(III)/Cu(II)/Pb(II) in the order of the corresponding reduction potentials, in particular, the mass transfer controlled reduction potentials, obtained from linear sweep voltammetry (LSV) measurement.     

Hydrodynamic characteristics of a FCC regenerator

The hydrodynamic and gas mixing characteristics have been determined in a FCC regenerator (0.48 m I.D.x3.4 m high) with FCC particles. Solids holdup in the dense bed decreases with increasing gas velocity, but it increases in the freeboard region. The bubble/void fraction increases with an increase along the bed height at a given gas velocity and increases with increasing gas velocity at a constant bed height. Backmixed tracer gas at the wall region is higher than that at the center region of the bed. The gas backmixing coefficient decreases with increasing gas velocity.