Academic performance & student engagement in level 1 physics undergraduates

At the beginning of academic year 2007-08, staff in the Department of Physics & Astronomy at the University of Glasgow started to implement a number of substantial changes to the administration of the level 1 physics undergraduate class. The main aims were to improve the academic performance and progression statistics. With this in mind, a comprehensive system of learning support was introduced, the main remit being the provision of an improved personal contact and academic monitoring and support strategy for all students at level 1. The effects of low engagement with compulsory continuous assessment components had already been observed to have a significant effect for students sitting in the middle of the grade curve. Analysis of data from the 2007-08 class showed that even some nominally high-achieving students achieved lowered grades due to the effects of low engagement. Nonetheless, academic and other support measures put in place during 2007-08 played a part in raising the passrate for the level 1 physics class by approximately 8% as well as raising the progression rate by approximately 10%.Comment: 12 pages, 3 figure

Evaluation of gene importance in microarray data based upon probability of selection

BACKGROUND: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. RESULTS: Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes) with optimal classification performance, compared with results reported in the literature. CONCLUSION: In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities

Correlating the Energetics and Atomic Motions of the Metal-Insulator Transition of M1 Vanadium Dioxide

Materials that undergo reversible metal-insulator transitions are obvious candidates for new generations of devices. For such potential to be realised, the underlying microscopic mechanisms of such transitions must be fully determined. In this work we probe the correlation between the energy landscape and electronic structure of the metal-insulator transition of vanadium dioxide and the atomic motions occurring using first principles calculations and high resolution X-ray diffraction. Calculations find an energy barrier between the high and low temperature phases corresponding to contraction followed by expansion of the distances between vanadium atoms on neighbouring sub-lattices. X-ray diffraction reveals anisotropic strain broadening in the low temperature structure's crystal planes, however only for those with spacings affected by this compression/expansion. GW calculations reveal that traversing this barrier destabilises the bonding/anti-bonding splitting of the low temperature phase. This precise atomic description of the origin of the energy barrier separating the two structures will facilitate more precise control over the transition characteristics for new applications and devices.Comment: 11 Pages, 8 Figure

Principles of genome evolution in the Drosophila melanogaster species group.

That closely related species often differ by chromosomal inversions was discovered by Sturtevant and Plunkett in 1926. Our knowledge of how these inversions originate is still very limited, although a prevailing view is that they are facilitated by ectopic recombination events between inverted repetitive sequences. The availability of genome sequences of related species now allows us to study in detail the mechanisms that generate interspecific inversions. We have analyzed the breakpoint regions of the 29 inversions that differentiate the chromosomes of Drosophila melanogaster and two closely related species, D. simulans and D. yakuba, and reconstructed the molecular events that underlie their origin. Experimental and computational analysis revealed that the breakpoint regions of 59% of the inversions (17/29) are associated with inverted duplications of genes or other nonrepetitive sequences. In only two cases do we find evidence for inverted repetitive sequences in inversion breakpoints. We propose that the presence of inverted duplications associated with inversion breakpoint regions is the result of staggered breaks, either isochromatid or chromatid, and that this, rather than ectopic exchange between inverted repetitive sequences, is the prevalent mechanism for the generation of inversions in the melanogaster species group. Outgroup analysis also revealed evidence for widespread breakpoint recycling. Lastly, we have found that expression domains in D. melanogaster may be disrupted in D. yakuba, bringing into question their potential adaptive significance