Influence of strain and polycrystalline ordering on magnetic properties of high moment rare earth metals and alloys

Despite being the most suitable candidates for solenoid pole pieces in state-of-the-art superconductor- based electromagnets, the intrinsic magnetic properties of heavy rare earth metals and their alloys have gained comparatively little attention. With the potential of integration in micro- and nanoscale devices, thin films of Gd, Dy, Tb, DyGd and DyTb were plasma-sputtered and investigated for their in-plane magnetic properties, with an emphasis on magnetisation vs. temperature profiles. Based on crystal structure analysis of the polycrystalline rare earth films, which consist of a low magnetic moment FCC layer at the seed interface topped with a higher moment HCP layer, an experimental protocol is introduced which allows the direct magnetic analysis of the individual layers. In line with the general trend of heavy lanthanides, the saturation magnetisation was found to drop with increasing unit cell size. In-situ annealed rare earth films exceeded the saturation magnetisation of a high-moment Fe65Co35 reference film in the cryogenic temperature regime, proving their potential for pole piece applications; however as-deposited rare earth films were found completely unsuitable. In agreement with theoretical predictions, sufficiently strained crystal phases of Tb and Dy did not exhibit an incommensurate magnetic order, unlike their single-crystal counterparts which have a helical phase. DyGd and DyTb alloys followed the trends of the elemental rare earth metals in terms of crystal structure and magnetic properties. Inter-rare-earth alloys hence present a desirable blend of saturation magnetisation and operating temperature.

A constructive approach for examination timetabling based on adaptive decomposition and ordering

In this study, we investigate an adaptive decomposition and ordering strategy that automatically divides examinations into difficult and easy sets for constructing an examination timetable. The examinations in the difficult set are considered to be hard to place and hence are listed before the ones in the easy set in the construction process. Moreover, the examinations within each set are ordered using different strategies based on graph colouring heuristics. Initially, the examinations are placed into the easy set. During the construction process, examinations that cannot be scheduled are identified as the ones causing infeasibility and are moved forward in the difficult set to ensure earlier assignment in subsequent attempts. On the other hand, the examinations that can be scheduled remain in the easy set.

Within the easy set, a new subset called the boundary set is introduced to accommodate shuffling strategies to change the given ordering of examinations. The proposed approach, which incorporates different ordering and shuffling strategies, is explored on the Carter benchmark problems. The empirical results show that the performance of our algorithm is broadly comparable to existing constructive approaches.

Ordering Quantiles through Confidence Statements

Ranking variables according to their relevance to predict an outcome is an important task in biomedicine. For instance, such ranking can be used for selecting a smaller number of genes to then apply other sophisticated experiments only on genes identified as important. A nonparametric method called Quor is designed to provide a confidence value for the order of arbitrary quantiles of different populations using independent samples. This confidence may provide insights about possible differences among groups and yields a ranking of importance for the variables. Computations are efficient and use exact distributions with no need for asymptotic considerations. Experiments with simulated data and with multiple real -omics data sets are performed and they show advantages and disadvantages of the method. Quor has no assumptions but independence of samples, thus it might be a better option when assumptions of other methods cannot be asserted. The software is publicly available on CRAN.

Number comparison and number ordering as predictors of arithmetic performance in adults: Exploring the link between the two skills, and investigating the question of domain-specificity.

Recent evidence has highlighted the important role that number ordering skills play in arithmetic abilities (e.g., Lyons & Beilock, 2011). In fact, Lyons et al. (2014) demonstrated that although at the start of formal mathematics education number comparison skills are the best predictors of arithmetic performance, from around the age of 10, number ordering skills become the strongest numerical predictors of arithmetic abilities. In the current study we demonstrated that number comparison and ordering skills were both significantly related to arithmetic performance in adults, and the effect size was greater in the case of ordering skills. Additionally, we found that the effect of number comparison skills on arithmetic performance was partially mediated by number ordering skills. Moreover, performance on comparison and ordering tasks involving the months of the year was also strongly correlated with arithmetic skills, and participants displayed similar (canonical or reverse) distance effects on the comparison and ordering tasks involving months as when the tasks included numbers. This suggests that the processes responsible for the link between comparison and ordering skills and arithmetic performance are not specific to the domain of numbers. Finally, a factor analysis indicated that performance on comparison and ordering tasks loaded on a factor which included performance on a number line task and self-reported spatial thinking styles. These results substantially extend previous research on the role of order processing abilities in mental arithmetic.