The influence of nonmetallic inclusions on the mechanical properties of steel: A review

The literature regarding the influence of nonmetallic inclusions on the mechanical properties of steel is reviewed, with critical comments on various studies. A brief discussion of inclusion rating methods and a synopsis of the effects of applied stress on inclusions in an isotropic, elastic matrix are presented. The parameters considered are tensile strength, impact strength, reduction of area, fatigue properties and fracture toughness. It is concluded that in many applications, the type of inclusions are more important than the total content and as matrix strength increases, the notch effect of inclusions becomes more significant. Also, mechanical properties can be influenced by any one or a combination of the following inclusion parameters; shape, size, quantity, interspacing, distribution, orientation, interfacial strength, and physical properties relative to the matrix.     

Sticky-free and overhang-free DNA languages

An essential step of any DNA computation is encoding the input data on single or double DNA strands. Due to the biochemical properties of DNA, complementary single strands can bind to one another forming double-stranded DNA. Consequently, data-encoding DNA strands can sometimes interact in undesirable ways when used in computations. It is crucial thus to analyze properties that guard against such phenomena and study sets of sequences that ensure that no unwanted bindings occur during any computation. This paper formalizes and investigates properties of DNA languages that guarantee their robusteness during computations. After defining and investigating several types of DNA languages possessing good encoding properties, such as sticky-free and overhang-free languages, we give algorithms for deciding whether regular DNA languages are invariant under bio-operations. We also give a method for constructing DNA languages that, in addition to being invariant and sticky-free, possess error-detecting properties. Finally, we present the results of running tests that check whether several known gene languages (the set of genes of a given organism) as well as the input DNA languages used in Adlemans DNA computing experiment, have the defined properties.Received: 6 February 2003, Published online: 2 September 2003Research partially supported by Grants R2824A01 and R220259 of the Natural Sciences and Engineering Research Council of Canada.     

Assessment of conformational parameters as predictors of limited proteolytic sites in native protein structures

Despite the importance of limited proteolysis in biological systems it isoften difficult to rationalize why a proteinase hydrolyses a particularbond, given a simple sequence specificity alone. Understanding of thestructural properties limiting the proteolysis represents a first step onthe pathway to control and manipulation of this phenomena. An expanded setof nick-sites in proteins of known tertiary structure, cut by both narrowand broad specificity proteinases, has been generated yielding a robustdata set of strictly limited sites. A critical evaluation of an expandedset of conformational parameters revealed a strong correlation with limitedproteolytic sites, although they are only modest predictors in isolation.The overall predictive power is significantly improved when theconformational parameters are combined in a weighted predictive scheme thatpermits their relative importance to be compared via a Metropolis searchprotocol. A subset of the parameters performs equally well demonstratingthe key determinants of susceptibility. The derived predictive algorithmhas been made available via the internet. Its utility for predicting othersurface-correlated features is also discussed.     

The ({beta}{alpha})8 glycosidases: sequence and structure analyses suggest distant evolutionary relationships

There are currently at least nine distinct glycosidase sequencefamilies which are all known to adopt a TIM barrel fold [Henrissat,B.and Davies,G. (1997) Curr. Opin. Struct. Biol., 7, 637–644].To explore the relationships between these enzymes and theirevolution, comprehensive sequence and structure comparisonswere performed, generating four distinct clusters. The firstcluster, S1, comprises the