The Direct Synthesis of β-hydroxy-acids by Lithium Naphthalene and Acetic Acid

Lithium naphthalene reacts with acetic acid to give α-anion of lithium acetate. The reaction of this anion with various ketones gives the corresponding β-hydroxy-acids in good yield.     

Stereochemistry and mechanism of the hydrogenation of dialkyl cyclohexenes

In order to investigate the steric effect of the substituents to determine the product distribution, disubstituted cyclohexenes were hydrogenated over several transition metal catalysts. Some cyclohexenes which have two large substituents at the vicinal carbon atoms, at least one of which is trigonal, were not hydrogenated over Raney Ni at all but were hydrogenated over Pt catalyst under our experimental conditions. Presumably, the stereoselectivity depends on the competitive operation of the torsional angle strain and the catalyst hindrance with substituents. In the hydrogenation over Pd catalyst, thermodynamically more stable products were dominant at the standard condition but at high substrate to catalyst ratio the less stable products were slightly preferred. No appreciable stereoselectivity was observed in the hydrogenation of 1,4-disubstituted cyclohexenes.     

Hydrothermal Formation of Hydroxyapatite Layers on the Surface of Type-A Zeolite

Type-A zeolite evenly covered with hydroxyapatite thin layers was prepared using hydrothermal treatment at 120°C for 8 h under autogenous pressure. The hydroxyapatite needlelike nanocrystals, 100–200 nm in diameter and 30 nm in thickness, were grown under the reaction between discharged Ca²⁺ ions from type-A zeolite and PO₄³⁻ ions in (NH₄)₃PO₄ solution. The preferential orientations of the c -axis of hydroxyapatite crystals perpendicular to a zeolite surface were observed using transmission electron microscopy. The crystal structure of type-A zeolite was not destroyed under the reaction, but the surface morphology was changed only with complete covering of scaly hydroxyapatite particles.     

Determination of fatty acid composition by gas chromatography: II. Analysis with use of flame ionization detector

In this study known mixtures of four or five fatty acid methyl esters were analyzed collaboratively by gas chromatography with flame ionization detectors. The experimental data was treated statistically to examine inter- and intralaboratory scattering. More-over the effect of the use of correction factors was investigated. Even if only the specific analytical values that scattered a little were chosen, the averages of such values did not always approach the actual values. In some laboratories a sort of regularity was observed in the deviation of analytical values from real values throughout the analyses of four samples. The application of correction factors to the analytical values obtained by these laboratories resulted in a considerable decrease of interlaboratory scattering and deviation from the real values. When a constant amount of sample was injected, intralaboratory scattering was decreased, whereas interlaboratory scattering was not. Injection of large sample sizes caused deviation. From this collaborative study it was recommended that 0.5–1.0 μl of 20% solution be injected. Presented at the JOCS-AOCS Joint Meeting, Los Angeles, April 1972.     

High-temperature oxidation of pure titanium in CO2 and Ar-10%CO2 atmospheres

The oxidation behavior of pure titanium has been investigated in the temperature range of 1000 K to 1300 K in CO₂ or Ar-10%CO₂. Optical microscopy, electron probe microanalyses, and X-ray measurements on the oxide scales formed during oxidation indicate that their structures are nearly independent of temperature and the corrosion atmosphere. The scales consisted of two layers, an external one and an internal one, having a rutile (TiO₂) structure. The parabolic rate law was confirmed for growth of the external scale and the permeation depth of oxygen in titanium with apparent activation energies of 266 and 226 kJ/mol, respectively. The rate-determining diffusion species in the oxidation processes are discussed.     

Probabilistic calibration of discrete element simulations using the sequential quasi-Monte Carlo filter

The calibration of discrete element method (DEM) simulations is typically accomplished in a trial-and-error manner. It generally lacks objectivity and is filled with uncertainties. To deal with these issues, the sequential quasi-Monte Carlo (SQMC) filter is employed as a novel approach to calibrating the DEM models of granular materials. Within the sequential Bayesian framework, the posterior probability density functions (PDFs) of micromechanical parameters, conditioned to the experimentally obtained stress–strain behavior of granular soils, are approximated by independent model trajectories. In this work, two different contact laws are employed in DEM simulations and a granular soil specimen is modeled as polydisperse packing using various numbers of spherical grains. Knowing the evolution of physical states of the material, the proposed probabilistic calibration method can recursively update the posterior PDFs in a five-dimensional parameter space based on the Bayes’ rule. Both the identified parameters and posterior PDFs are analyzed to understand the effect of grain configuration and loading conditions. Numerical predictions using parameter sets with the highest posterior probabilities agree well with the experimental results. The advantage of the SQMC filter lies in the estimation of posterior PDFs, from which the robustness of the selected contact laws, the uncertainties of the micromechanical parameters and their interactions are all analyzed. The micro–macro correlations, which are byproducts of the probabilistic calibration, are extracted to provide insights into the multiscale mechanics of dense granular materials.     

Reorganizing knowledge in neural networks: an explanatory mechanismfor neural networks in data classification problems

We propose an explanatory mechanism for multilayered neural networks (NN). In spite of the effective learning capability as a uniform function approximator, the multilayered NN suffers from unreadability, i.e., it is difficult for the user to interpret or understand the "knowledge" that the NN has by looking at the connection weights and thresholds obtained by backpropagation (BP). This unreadability comes from the distributed nature of the knowledge representation in the NN. In this paper, we propose a method that reorganizes the distributed knowledge in the NN to extract approximate classification rules. Our rule extraction method is based on the analysis of the function that the NN has learned, rather than on the direct interpretation of connection weights as correlation information. More specifically, our method divides the input space into "monotonic regions" where a monotonic region is a set of input patterns that belongs to the same class with the same sensitivity pattern. Approximate classification rules are generated by projecting these monotonic regions.     

iOS application for quadrotor remote control

With the progress of electronics technology, the development of civilian UAV (unmanned aerial vehicle) applications becomes possible. In addition, smartphones have rapidly gained popularity and become very important due to the simple operability and mobility. Hence, there is a need to have an easy and flexible way to control a UAV using such technology. In this study, a remote controller using an iOS device is developed for a quadrotor to enable remote control with easy operations. Four basic programs for obtaining compass information, controlling a gimbal, autopilot function for return, and video preview function are developed and implemented for an iOS device. The basic functionalities of the programs are evaluated and confirmed through experiments using a quadrotor and an iOS device.