Discovery and genotyping of structural variation from long-read haploid genome sequence data

In an effort to more fully understand the full spectrum of human genetic variation, we generated deep single-molecule, real-time (SMRT) sequencing data from two haploid human genomes. By using an assembly-based approach (SMRT-SV), we systematically assessed each genome independently for structural variants (SVs) and indels resolving the sequence structure of 461,553 genetic variants from 2 bp to 28 kbp in length. We find that &gt;89% of these variants have been missed as part of analysis of the 1000 Genomes Project even after adjusting for more common variants (MAF &gt; 1%). We estimate that this theoretical human diploid differs by as much as ∼16 Mbp with respect to the human reference, with long-read sequencing data providing a fivefold increase in sensitivity for genetic variants ranging in size from 7 bp to 1 kbp compared with short-read sequence data. Although a large fraction of genetic variants were not detected by short-read approaches, once the alternate allele is sequence-resolved, we show that 61% of SVs can be genotyped in short-read sequence data sets with high accuracy. Uncoupling discovery from genotyping thus allows for the majority of this missed common variation to be genotyped in the human population. Interestingly, when we repeat SV detection on a pseudodiploid genome constructed in silico by merging the two haploids, we find that ∼59% of the heterozygous SVs are no longer detected by SMRT-SV. These results indicate that haploid resolution of long-read sequencing data will significantly increase sensitivity of SV detection.</jats:p

Predicting Student Failure in an Introductory Programming Course with Multiple Back-Propagation

One of the most challenging tasks in computer science and similar courses consists of both teaching and learning computer programming. Usually this requires a great deal of work, dedication, and motivation from both teachers and students. Accordingly, ever since the first programming languages emerged, the problems inherent to programming teaching and learning have been studied and investigated. The theme is very serious, not only for the important concepts underlying computer science courses but also for reducing the lack of motivation, failure, and abandonment that result from students frustration. Therefore, early identification of potential problems and immediate response is a fundamental aspect to avoid student’s failure and reduce dropout rates. In this paper, we propose a machine-learning (neural network) predictive model of student failure based on the student profile, which is built throughout programming classes by continuously monitoring and evaluating student activities. The resulting model allows teachers to early identify students that are more likely to fail, allowing them to devote more time to those students and try novel strategies to improve their programming skills

An Equation of State of a Carbon-Fibre Epoxy Composite under Shock Loading

An anisotropic equation of state (EOS) is proposed for the accurate extrapolation of high-pressure shock Hugoniot (anisotropic and isotropic) states to other thermodynamic (anisotropic and isotropic) states for a shocked carbon-fibre epoxy composite (CFC) of any symmetry. The proposed EOS, using a generalised decomposition of a stress tensor [Int. J. Plasticity \textbf{24}, 140 (2008)], represents a mathematical and physical generalisation of the Mie-Gr\"{u}neisen EOS for isotropic material and reduces to this equation in the limit of isotropy. Although a linear relation between the generalised anisotropic bulk shock velocity $U^{A}_{s}$ and particle velocity $u_{p}$ was adequate in the through-thickness orientation, damage softening process produces discontinuities both in value and slope in the $U^{A}_{s}$-$u_{p}$ relation. Therefore, the two-wave structure (non-linear anisotropic and isotropic elastic waves) that accompanies damage softening process was proposed for describing CFC behaviour under shock loading. The linear relationship $U^{A}_{s}$-$u_{p}$ over the range of measurements corresponding to non-linear anisotropic elastic wave shows a value of $c^{A}_{0}$ (the intercept of the $U^{A}_{s}$-$u_{p}$ curve) that is in the range between first and second generalised anisotropic bulk speed of sound [Eur. Phys. J. B \textbf{64}, 159 (2008)]. An analytical calculation showed that Hugoniot Stress Levels (HELs) in different directions for a CFC composite subject to the two-wave structure (non-linear anisotropic elastic and isotropic elastic waves) agree with experimental measurements at low and at high shock intensities. The results are presented, discussed and future studies are outlined.Comment: 12 pages, 9 figure

Trading More Food in the Context of High-end Climate Change: Implications for Land Displacement through Agricultural Trade

The study analyzes the impacts of agricultural trade liberalization on cropland use dynamics, focusing not only on the total amount of cropland area, but also on the spatial allocation among regions. With an agro-economic dynamic optimization model, the study is able to analyze the leakage effects resulted from trade liberalization as well as climate impacts on crop yields, by using crop yields simulation output from a vegetation model based on different climate models. In the scenario of high-end climate impacts on crop yields, although trade liberalization mitigates the negative impacts of climate impacts on agricultural supply and spares the land resource on the global scale, it further deteriorates the virtual trade of cropland among regions. The absolute amount of total cropland imbalance will increase by 272.2 million hectares at the end of the twenty-fist century. Latin America and China are the main exporters of cropland relate to food production, while Sub-Saharan Africa and South Asia are the regions of exporting cropland. By considering climate projection uncertainty, the study finds that the general trend of cropland displacement remains, although there exists a wide range for the amount of traded cropland in Sub-Saharan Africa, South Asia and Latin America. Acknowledgement

Integrating Synchronous and Asynchronous Interactions in Groupware Applications

Abstract. It is common that, in a long-term asynchronous collaborative activity, groups of users engage in occasional synchronous sessions. In this paper, we analyze the requirements for supporting this common work practice in typical collaborative activities and applications. This analysis shows that, for some applications, it is necessary to rely on different data sharing techniques in synchronous and asynchronous settings. We present a data management system that allows to integrate a synchronous session in the context of a long-term asynchronous interaction, using the suitable data sharing techniques in each setting. We exemplify the use of our system with two multi-synchronous applications.