Residual stress redistribution during elastic shake down in welded plates

Residual stresses are a consequence of welding in various structures such as ships and offshore structures. Residual stresses can be relaxed or redistributed according to the load levels during operation. The elastic shakedown phenomenon can be considered as one of the reasons for this change. This paper studies the relaxation/redistribution of weld residual stress during different levels of shakedown in a butt-welded plate chosen according to ship design and welding procedures. Welding was performed on DH36, a ship structural steel. Neutron diffraction was used to measure residual stresses in these plates in the as-welded state and after different levels of shakedown. A mixed hardening model in line with the Chaboche model is determined for both weld and base material. A numerical model is developed to estimate the shakedown limit on butt-welded plate. Further, the redistribution of residual stress in a numerical weld model according to the different levels of shakedown limit is studied. Based on the shakedown limit of the butt-welded plate, a shakedown region is determined, where the structure will undergo elastic shakedown in the presence of an existing residual stress field if the maximum stress on the load section after a few initial cycles is in the shakedown region

Genomic integration of transgenes using UV irradiation in Pristionchus pacificus

Transgenes are widely used throughout molecular biology for numerous applications. In Caenorhabditis elegans, stable transgenes are usually generated by microinjection into the germline establishing extrachromosomal arrays. Furthermore, numerous technologies exist to integrate transgenes into the C. elegans genome. In the nematode Pristionchus pacificus, transgenes are possible, however, their establishment is less efficient and dependent on the formation of complex arrays containing the transgene of interest and host carrier DNA. Additionally, genomic integration has only been reported via biolistic methods. Here we describe a simple technique using UV irradiation to facilitate the integration of transgenes into the P. pacificus genome

DRISEE overestimates errors in metagenomic sequencing data

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Briefings in Bioinformatics 15 (2014): 783-787, doi:10.1093/bib/bbt010.The extremely high error rates reported by Keegan et al. in ‘A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE’ (PLoS Comput Biol 2012;8:e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that the presence of conserved artificial sequences, e.g. Illumina adapters, and other naturally occurring sequence motifs accounts for most of the reported errors. We conclude that DRISEE reports inflated levels of sequencing error, particularly for Illumina data. Tools offered for evaluating large datasets need scrupulous review before they are implemented.National Institutes of Health [1UH2DK083993 to M.L.S.]; National Science Foundation [BDI- 096026 to S.M.H.]

Fragmentation of Fractal Random Structures

We analyze the fragmentation behavior of random clusters on the lattice under a process where bonds between neighboring sites are successively broken. Modeling such structures by configurations of a generalized Potts or random-cluster model allows us to discuss a wide range of systems with fractal properties including trees as well as dense clusters. We present exact results for the densities of fragmenting edges and the distribution of fragment sizes for critical clusters in two dimensions. Dynamical fragmentation with a size cutoff leads to broad distributions of fragment sizes. The resulting power laws are shown to encode characteristic fingerprints of the fragmented objects.Comment: Thoroughly revised version. Final version published in Physical Review Letter

Oligotyping : differentiating between closely related microbial taxa using 16S rRNA gene data

© The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society.. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Methods in Ecology and Evolution 4 (2013): 1111–1119, doi:10.1111/2041-210X.12114.Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference data bases or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In this paper, we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental data sets through 16S ribosomal RNA gene data by the canonical approaches. Our analysis of two data sets from two different environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.This work was supported by the National Institutes of Health [1UH2DK083993 to M.L.S.] and the Alfred P. Sloan Foundation

Manipulation monitoring and robot intervention in complex manipulation sequences

Trabajo presentado al IX Robotics Science and Systems: "Workshop on Robotic Monitoring" (RSS-WRM), celebrado en Berkeley (US) del 12 al 16 de julio de 2014.-- et al.Compared to machines, humans are intelligent and dexterous; they are indispensable for many complex tasks in areas such as flexible manufacturing or scientific experimentation. However, they are also subject to fatigue and inattention, which may cause errors. This motivates automated monitoring systems that verify the correct execution of manipulation sequences. To be practical, such a monitoring system should not require laborious programming.The research leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2013 (Specific Programme Cooperation, Theme 3, Information and Communication Technologies) under grant agreement no. 269959, IntellAct.Peer Reviewe