Networks of PhD Students and Academic Performance: A Comparison across Countries

In this article we compare regression models obtained to predict PhD students’ academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student’s research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. Academic performance was measured by the weighted number of publications. Two web questionnaires were designed, one for PhD students and one for their supervisors and other research group members. Most of the variables were easily comparable across universities due to the careful translation procedure and pre-tests. When direct comparison was not possible we created comparable indicators. We used a regression model in which the country was introduced as a dummy coded variable including all possible interaction effects. The optimal transformations of the main and interaction variables are discussed. Some differences between Slovenian and Girona universities emerge. Some variables like supervisor’s performance and motivation for autonomy prior to starting the PhD have the same positive effect on the PhD student’s performance in both countries. On the other hand, variables like too close supervision by the supervisor and having children have a negative influence in both countries. However, we find differences between countries when we observe the motivation for research prior to starting the PhD which increases performance in Slovenia but not in Girona. As regards network variables, frequency of supervisor advice increases performance in Slovenia and decreases it in Girona. The negative effect in Girona could be explained by the fact that additional contacts of the PhD student with his/her supervisor might indicate a higher workload in addition to or instead of a better advice about the dissertation. The number of external student’s advice relationships and social support mean contact intensity are not significant in Girona, but they have a negative effect in Slovenia. We might explain the negative effect of external advice relationships in Slovenia by saying that a lot of external advice may actually result from a lack of the more relevant internal advice

Conformations of poly{G}-poly{C} π stacks with high hole mobility

Charge transfer properties of DNA depend strongly on the π stack conformation. In the present paper, we identify conformations of homogeneous poly-{G}-poly-{C} stacks that should exhibit high charge mobility. Two different computational approaches were applied. First, we calculated the electronic coupling squared, V2, between adjacent base pairs for all 1 ps snapshots extracted from 15 ns molecular dynamics trajectory of the duplex G15. The average value of the coupling squared 〈 V2 〉 is found to be 0.0065 eV2. Then we analyze the base-pair and step parameters of the configurations in which V2 is at least an order of magnitude larger than 〈 V2 〉. To obtain more consistent data, ∼65 000 configurations of the (G:C)2 stack were built using systematic screening of the step parameters shift, slide, and twist. We show that undertwisted structures (twist<20°) are of special interest, because the π stack conformations with strong electronic couplings are found for a wide range of slide and shift. Although effective hole transfer can also occur in configurations with twist=30° and 35°, large mutual displacements of neighboring base pairs are required for that. Overtwisted conformation (twist38°) seems to be of limited interest in the context of effective hole transfer. The results may be helpful in the search for DNA based elements for nanoelectronics