Graft polymerization of vinyl acetate onto silica

The free‐radical graft polymerization of vinyl acetate onto nonporous silica particles was studied experimentally. The grafting procedure consisted of surface activation with vinyltrimethoxysilane, followed by free‐radical graft polymerization of vinyl acetate in ethyl acetate with 2,2′‐azobis(2,4‐dimethylpentanenitrile) initiator. Initial monomer concentration was varied from 10 to 40% by volume and the reaction was spanned from 50 to 70°C. The resulting grafted polymer, which was stable over a wide range of pH levels, consisted of polymer chains that are terminally and covalently bonded to the silica substrate. The experimental polymerization rate order, with respect to monomer concentration, ranged from 1.61 to 2.00, consistent with the kinetic order for the high polymerization regime. The corresponding rate order for polymer grafting varied from 1.24 to 1.43. The polymer graft yield increased with both initial monomer concentration and reaction temperature, and the polymer‐grafted surface became more hydrophobic with increasing polymer graft yield. The present study suggests that a denser grafted polymer phase of shorter chains was created upon increasing temperature. On the other hand, both polymer chain length and polymer graft density increased with initial monomer concentration. Atomic force microscopy–determined topology of the polymer‐grafted surface revealed a distribution of surface clusters and surface elevations consistent with the expected broad molecular‐weight distribution for free‐radical polymerization. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 300–310, 2003     

Efficacy of iron fortification compared to iron supplementation among Vietnamese schoolchildren

Background  

Parents of six children are facing a trial on charges of aggravated manslaughter in the care a 5 1/2 month old infant who died suddenly and neglect of their four older children for causing them to be malnourished by feeding them all an exclusively raw foods vegan diet. Both parents declined plea bargains and plan to defend themselves in court.     

Application of Fuzzy Moving Sliding Surface Approach for Container Cranes

International Journal of Control, Automation and Systems - In this paper, we consider the fuzzy moving sliding surface anti-sway control problem for container cranes. We first introduce the dynamic...     

Satellite-Based Water Quality Mapping from Sequential Simulation with Parameter Outlier Removal

The satellite-based regression model provides the data model that identifies water quality for inland and coastal waters. However, the satellite regression usually depends on the selection of observation, satellite data, and model type. A resampling simulation technique, such as sequential simulation using geographically weighted regression (GWR simulation), can be applied in generating multiple realizations for water quality estimation to reduce the sampling effect and consider spatial heterogeneity. Traditional models often result in considerable underestimation in extreme observations. The GWR simulation provides the best goodness of fit and spatial varying relationship between observed water quality and remote sensing considering parameter outlier and noise removal for parameter stability. This simulation model can increase the sampling diversity from various observations and reduce the neighboring effects of observations using outlier and noise removal. The model that handles spatial uncertainty and heterogeneity is a novel tool for inferring the characteristics of water quality from a series of sample subsets.

     

Micro cam system driven by electrostatic comb-drive actuators based on SOI-MEMS technology

Microsystem Technologies - This paper reports a design and fabrication process of a micro cam system (MCS) with a flat-faced translating follower. The cam rim with cover diameter of 2.4 mm...     

High quality voice conversion using prosodic and high-resolution spectral features

Voice conversion methods have advanced rapidly over the last decade. Studies have shown that speaker characteristics are captured by spectral feature as well as various prosodic features. Most existing conversion methods focus on the spectral feature as it directly represents the timbre characteristics, while some conversion methods have focused only on the prosodic feature represented by the fundamental frequency. In this paper, a comprehensive framework using deep neural networks to convert both timbre and prosodic features is proposed. The timbre feature is represented by a high-resolution spectral feature. The prosodic features include F0, intensity and duration. It is well known that DNN is useful as a tool to model high-dimensional features. In this work, we show that DNN initialized by our proposed autoencoder pretraining yields good quality DNN conversion models. This pretraining is tailor-made for voice conversion and leverages on autoencoder to capture the generic spectral shape of source speech. Additionally, our framework uses segmental DNN models to capture the evolution of the prosodic features over time. To reconstruct the converted speech, the spectral feature produced by the DNN model is combined with the three prosodic features produced by the DNN segmental models. Our experimental results show that the application of both prosodic and high-resolution spectral features leads to quality converted speech as measured by objective evaluation and subjective listening tests.