Elliptic Curves over Real Quadratic Fields are Modular

We prove that all elliptic curves defined over real quadratic fields are modular.Comment: 38 pages. Magma scripts available as ancillary files with this arXiv versio

Evolution of Parallel Spindles Like genes in plants and highlight of unique domain architecture#

<p>Abstract</p> <p>Background</p> <p>Polyploidy has long been recognized as playing an important role in plant evolution. In flowering plants, the major route of polyploidization is suggested to be sexual through gametes with somatic chromosome number (2<it>n</it>). <it>Parallel Spindle1 </it>gene in <it>Arabidopsis thaliana </it>(<it>AtPS1</it>) was recently demonstrated to control spindle orientation in the 2nd division of meiosis and, when mutated, to induce 2<it>n </it>pollen. Interestingly, <it>AtPS1 </it>encodes a protein with a FHA domain and PINc domain putatively involved in RNA decay (i.e. Nonsense Mediated mRNA Decay). In potato, 2<it>n </it>pollen depending on parallel spindles was described long time ago but the responsible gene has never been isolated. The knowledge derived from <it>AtPS1 </it>as well as the availability of genome sequences makes it possible to isolate potato <it>PSLike </it>(<it>PSL</it>) and to highlight the evolution of <it>PSL </it>family in plants.</p> <p>Results</p> <p>Our work leading to the first characterization of <it>PSLs </it>in potato showed a greater <it>PSL </it>complexity in this species respect to <it>Arabidopsis thaliana</it>. Indeed, a genomic <it>PSL </it>locus and seven cDNAs affected by alternative splicing have been cloned. In addition, the occurrence of at least two other <it>PSL </it>loci in potato was suggested by the sequence comparison of alternatively spliced transcripts.</p> <p>Phylogenetic analysis on 20 <it>Viridaeplantae </it>showed the wide distribution of <it>PSLs </it>throughout the species and the occurrence of multiple copies only in potato and soybean.</p> <p>The analysis of PSL^FHAand PSL^PINcdomains evidenced that, in terms of secondary structure, a major degree of variability occurred in PINc domain respect to FHA. In terms of specific active sites, both domains showed diversification among plant species that could be related to a functional diversification among <it>PSL </it>genes. In addition, some specific active sites were strongly conserved among plants as supported by sequence alignment and by evidence of negative selection evaluated as difference between non-synonymous and synonymous mutations.</p> <p>Conclusions</p> <p>In this study, we highlight the existence of PSLs throughout <it>Viridaeplantae</it>, from mosses to higher plants. We provide evidence that <it>PSLs </it>occur mostly as singleton in the analyzed genomes except in soybean and potato both characterized by a recent whole genome duplication event. In potato, we suggest the candidate <it>PSL </it>gene having a role in 2<it>n </it>pollen that should be deeply investigated.</p> <p>We provide useful insight into evolutionary conservation of FHA and PINc domains throughout plant PSLs which suggest a fundamental role of these domains for PSL function.</p

Railway bridge structural health monitoring and fault detection: state-of-the-art methods and future challenges

Railway importance in the transportation industry is increasing continuously, due to the growing demand of both passenger travel and transportation of goods. However, more than 35% of the 300,000 railway bridges across Europe are over 100-years old, and their reliability directly impacts the reliability of the railway network. This increased demand may lead to higher risk associated with their unexpected failures, resulting safety hazards to passengers and increased whole life cycle cost of the asset. Consequently, one of the most important aspects of evaluation of the reliability of the overall railway transport system is bridge structural health monitoring, which can monitor the health state of the bridge by allowing an early detection of failures. Therefore, a fast, safe and cost-effective recovery of the optimal health state of the bridge, where the levels of element degradation or failure are maintained efficiently, can be achieved. In this article, after an introduction to the desired features of structural health monitoring, a review of the most commonly adopted bridge fault detection methods is presented. Mainly, the analysis focuses on model-based finite element updating strategies, non-model-based (data-driven) fault detection methods, such as artificial neural network, and Bayesian belief network–based structural health monitoring methods. A comparative study, which aims to discuss and compare the performance of the reviewed types of structural health monitoring methods, is then presented by analysing a short-span steel structure of a railway bridge. Opportunities and future challenges of the fault detection methods of railway bridges are highlighted