Impact of Friction Stir Welding on the microstructure of ODS steel

We have assessed the impact of the welding parameters on the nano-sized oxide dispersion and the grain size in the matrix of an ODS steel after friction stir welding. Our results, based on combined small angle neutron scattering and electron microscopy, reveal a decrease in the volume fraction of the particles smaller than 80 nm in the welds, mainly due to particle agglomeration. The increase in tool rotation speed or decrease in transverse speed leads to a higher reduction in nano-sized particle fraction, and additionally to the occurrence of particle melting. The dependence of the average grain size in the matrix on the particle volume fraction follows a Zener pinning-type relationship. This result points to the principal role that the particles have in pinning grain boundary movement, and consequently in controlling the grain size during welding.</p

Heritable patterns of tooth decay in the permanent dentition: principal components and factor analyses

<p>Abstract</p> <p>Background</p> <p>Dental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies. Therefore, global measures of decay, such as the DMFS index, may not be optimal for identifying risk factors that manifest as specific decay patterns, especially if the risk factors such as genetic susceptibility loci have small individual effects. We used two methods to extract patterns of decay from surface-level caries data in order to generate novel phenotypes with which to explore the genetic regulation of caries.</p> <p>Methods</p> <p>The 128 tooth surfaces of the permanent dentition were scored as carious or not by intra-oral examination for 1,068 participants aged 18 to 75 years from 664 biological families. Principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without <it>a priori </it>surface classifications, were applied to our data.</p> <p>Results</p> <p>The three strongest caries patterns identified by PCA recaptured variation represented by DMFS index (correlation, r = 0.97), pit and fissure surface caries (r = 0.95), and smooth surface caries (r = 0.89). However, together, these three patterns explained only 37% of the variability in the data, indicating that <it>a priori </it>caries measures are insufficient for fully quantifying caries variation. In comparison, the first pattern identified by FA was strongly correlated with pit and fissure surface caries (r = 0.81), but other identified patterns, including a second pattern representing caries of the maxillary incisors, were not representative of any previously defined caries indices. Some patterns identified by PCA and FA were heritable (h²= 30-65%, p = 0.043-0.006), whereas other patterns were not, indicating both genetic and non-genetic etiologies of individual decay patterns.</p> <p>Conclusions</p> <p>This study demonstrates the use of decay patterns as novel phenotypes to assist in understanding the multifactorial nature of dental caries.</p