25,091 research outputs found
Physicochemical properties and leaching behavior of eight U.S. long-grain rice cultivars as related to rice texture
There are many long-grain rice cultivars produced commercially in the U.S.; however, little work has been done on correlating the structure and physicochemical properties of starch with their texture. The physicochemical properties, leaching behavior, and texture attributes of eight longgrain rice cultivars were studied. Differences were observed in the approximate composition of kernels, including crude protein (6.6-9.3%), crude lipid (0.18-0.51%), and apparent amylose content (25.5-30.9%). These cultivars also differed slightly in thermal properties, such as onset temperature (73.7° to 77.4°C) and peak temperature (78.8° to 81.9°C). Although they showed a similar pasting temperature, their peak viscosities ranged from 680 to 982 Brabender units. The amount and the molecular size distribution of the leached starch molecules varied greatly among the samples. The leached amylose, instead of the apparent amylose, was suggested to play an important role in cooked rice texture
Stochastic Trust Region Methods with Trust Region Radius Depending on Probabilistic Models
We present a stochastic trust-region model-based framework in which its
radius is related to the probabilistic models. Especially, we propose a
specific algorithm, termed STRME, in which the trust-region radius depends
linearly on the latest model gradient. The complexity of STRME method in
non-convex, convex and strongly convex settings has all been analyzed, which
matches the existing algorithms based on probabilistic properties. In addition,
several numerical experiments are carried out to reveal the benefits of the
proposed methods compared to the existing stochastic trust-region methods and
other relevant stochastic gradient methods
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