To investigate the post-fire seismic behaviour of reinforced concrete (RC) frames with different columnto-beam bending capacity ratios, four specimens were fabricated, which included a strong-beam-weakcolumn frame and a strong-column-weak-beam frame either under room temperature or after being exposed to fire. The fire test was conducted in a furnace chamber, followed by quasi-static tests under a low-frequency cyclic load. The crack patterns, hysteretic loops, plastic hinges, and failure modes were investigated in the loading process. The influence of two factors, i.e., the fire exposure and the columnto-beam bending capacity ratio, on the mechanical performance, ductility, stiffness degradation, and energy dissipation was compared and analysed. The experimental results indicated that the ultimate bearing capacity, the stiffness, the ductility factor, and the energy dissipation capacity of the RC frames decreased after fire exposure. The bearing capacity of the strong-beam-weak-column frame decreased even more seriously. Although the yielding displacements of the post-fire frames increased, their ultimate displacements decreased. In addition, the strong-column-weak-beam frame under room temperature failed in the form of beam-end plastic hinging, while after being exposed to fire, the failure mode changed to shear-bond failure in column.
The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) is Europe's primary resource for nucleotide sequence information. With the growing volume and diversity of public sequencing data comes the need for increased sophistication in data organisation, presentation and search services so as to maximise its discoverability and usability. In response to this, ENA has been introducing and improving checklists for use during submission and expanding its search facilities to provide targeted search results. Here, we give a brief update on ENA content and some major developments undertaken in data submission services during 2014. We then describe in more detail the services we offer for data discovery and retrieval.
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