Graft copolymers of starch. I. Copolymerization of gelatinized wheat starch with acrylonitrile. Fractionation of copolymer and effect of solvent on copolymer composition

The starch–polyacrylonitrile graft copolymer prepared from gelatinized wheat starch with ceric ammoninm nitrate as the initiator has been freed of ungrafted polyacrylonitrile and separated into fractions by extraction with dimethylformamide, γ-butyrolactone, and dimethyl sulfoxide. The copolymer fractions obtained differed appreciably in level of add-on, molecular weights of grafted chains, and grafting frequency. To determiue the molecular weights of grafted chains, the starch part of the copolymer was effectively removed by hydrolysis with α-amylase. It was necessary to dissolve or swell the polymer in dimethyl sulfoxide and freshly precipitate it by addition to water before enzymatic hydrolysis. In studying the effect of reaction medium on copolymer composition, there was less ungrafted homopolymer formed and a higher yield of graft copolymer possessing more frequent grafts with water than with aqueous dimethylformamide or aqueous ethylene glycol. Polymer solubility, the results of control polymerizations of acrylonitrile in the absence of starch, and the detection of glucose endgroups on the polyacrylonitrile liberated from the fractionated polymer by hydrolysis are presented as evidence that the copolymers obtained are true grafts rather thau intimate mixtures.     

Selecting a Military Computer Architecture

Selecting or even designing a computer architecture is at best as much a black art as a science. The problem is particularly difficult when one tries to choose an architecture meant to serve a very broad range of users whose present and future requirements are poorly understood. This article describes the activities of a joint Army/Navy Selection Committee, which was charged with the task of selecting a single computer architecture to be used as the basis for a new military computer family. The range of applications for military computers is broad and ill defined; how the committee tried to cope with this problem should be of interest to others who are interested in measuring, designing, or selecting computer architectures.     

Cryptographic hash standards: where do we go from here?

Successful attacks against the two most commonly used cryptographic hash functions, MD5 and SHA-1, have triggered a kind of feeding frenzy in the cryptographic community. Many researchers are now working on hash function attacks, and we can expect new results in this area for the next several years. This article discusses the SHA-1 attack and the US National Institute of Standards and Technology's (NIST's) plans for SHA-1 and hash functions in general.     

Measuring trunk motions in industry: variability due to task factors, individual differences, and the amount of data collected

The focus of this study was to determine the amount of data needed to ensure sufficient accuracy in estimating mean trunk motions of employees performing industrial manual materials handling tasks. Over 450 tasks were selected, in which the load weight and the vertical start and destination heights of the activity remained constant throughout the task. Data were collected as employees did their work at the job site, using the Lumbar Motion Monitor. Variance components were estimated in a hierarchical design and used to compute standard errors of mean trunk kinematic measures. These analyses found task-to-task variation to be much larger than the variability due to either multiple employees performing the same task or to repetitive movements within a task. Also, it was found that no significant reduction in the standard errors occurred when data were gathered for more than three employees and three repetitions of each task by an employee. This study indicates that the vast majority of variability in mean trunk motions is accounted for by the design of work tasks, and variations due to repeated cycles of a task or to employees are rather minor. It is also important as a basis for future work on modelling low-back disorder risk based on a job's trunk kinematic measures.     

Plastic Extrusion Process Optimization by Inversion of Stacked Autoencoder Classification Machines

In the face of climate change and rising energy prices, lowering energy usage of industrial machines is gaining widespread attention. Αpropriate machine settings could lead to reduced production costs and lower environmental impact, while simultaneously maintaining products' quality. However, defining the complex, nonlinear dependencies between these settings and energy usage or quality in manufacturing is often a challenging task. In the presented work, a method for optimized machine settings recommendation is proposed using inverse classification via autoencoders. The algorithm can suggest operation parameters, based on predefined intervals of energy consumption and product properties. The performance is evaluated on data generated by a digital twin of an extrusion process.