61 research outputs found

    A sensor enabled robotic strategy for automated defect-free multi-pass high-integrity welding

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    High-integrity welds found in safety–critical industries require flaw-free joints, but automation is challenging due to low-volume, often-unique nature of the work, alongside high-uncertainty part-localisation. As such, robotic welding still requires tedious manually taught paths or offline approaches based on nominal Computer-Aided-Design (CAD). Optical and laser sensors are commonly deployed to provide online adjustment of pre-defined paths within controlled environments. This paper presents a sensor-driven approach for defect-free welding, based on the as-built joint geometry alongside the requirement for no-accurate part localisation or CAD knowledge. The approach a) autonomously localises the specimen in the scene without CAD requirement, b) adapts and generates accurate welding paths unique to the as-built workpiece and c) generates robot kinematics based on an external-control strategy. The proposed approach is validated through experiments of unconstrained placed joints, where the increased accuracy of the generated welding paths, with no common seam tracking, is validated with an average error of 0.12 mm, 0.4°. Coupling with a multi-pass welding framework, the deployment of fully automated robotic arc welding takes place for different configurations. Non-Destructive-Testing (NDT) in the form of Ultrasound-Testing (UT) inspection validates the repeatable and flaw-free nature of the sensory-driven approach, exploiting direct benefits in quality alongside reduced re-work

    A cell topography-based mechanism for ligand discrimination by the T cell receptor.

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    The T cell receptor (TCR) initiates the elimination of pathogens and tumors by T cells. To avoid damage to the host, the receptor must be capable of discriminating between wild-type and mutated self and nonself peptide ligands presented by host cells. Exactly how the TCR does this is unknown. In resting T cells, the TCR is largely unphosphorylated due to the dominance of phosphatases over the kinases expressed at the cell surface. However, when agonist peptides are presented to the TCR by major histocompatibility complex proteins expressed by antigen-presenting cells (APCs), very fast receptor triggering, i.e., TCR phosphorylation, occurs. Recent work suggests that this depends on the local exclusion of the phosphatases from regions of contact of the T cells with the APCs. Here, we developed and tested a quantitative treatment of receptor triggering reliant only on TCR dwell time in phosphatase-depleted cell contacts constrained in area by cell topography. Using the model and experimentally derived parameters, we found that ligand discrimination likely depends crucially on individual contacts being ∼200 nm in radius, matching the dimensions of the surface protrusions used by T cells to interrogate their targets. The model not only correctly predicted the relative signaling potencies of known agonists and nonagonists but also achieved this in the absence of kinetic proofreading. Our work provides a simple, quantitative, and predictive molecular framework for understanding why TCR triggering is so selective and fast and reveals that, for some receptors, cell topography likely influences signaling outcomes.This work was funded by The Wellcome Trust, the UK Medical Research Council, the UK Biotechnology and Biological Sciences Research Council and Cancer Research UK. We thank the Wolfson Imaging Centre, University of Oxford, for access to their microscope facility. We would like to thank the Wellcome Trust for the Sir Henry Dale Fellowship of R.A.F. (WT101609MA), the Royal Society for the University Research Fellowship of S.F.L. (UF120277) and acknowledge a GSK Professorship (D.K.). We are also grateful to Doug Tischer (UCSF, US) and Muaz Rushdi (Georgia Tech, US) for their critical comments on the manuscript

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Hybrid Gene Origination Creates Human-Virus Chimeric Proteins during Infection

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    RNA viruses are a major human health threat. The life cycles of many highly pathogenic RNA viruses like influ-enza A virus (IAV) and Lassa virus depends on host mRNA, because viral polymerases cleave 50-m7G-cappedhost transcripts to prime viral mRNA synthesis (‘‘cap-snatching’’). We hypothesized that start codons withincap-snatched host transcripts could generate chimeric human-viral mRNAs with coding potential. We reportthe existence of this mechanism of gene origination, which we named ‘‘start-snatching.’’ Depending on thereading frame, start-snatching allows the translation of host and viral ‘‘untranslated regions’’ (UTRs) to createN-terminally extended viral proteins or entirely novel polypeptides by genetic overprinting. We show thatboth types of chimeric proteins are made in IAV-infected cells, generate T cell responses, and contributeto virulence. Our results indicate that during infection with IAV, and likely a multitude of other human, animaland plant viruses, a host-dependent mechanism allows the genesis of hybrid genes

    Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

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    Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo

    A cost-function driven adaptive welding framework for multi-pass robotic welding

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    Manual teaching of robot paths and welding parameters for multi-pass robotic welding is a cumbersome and time-consuming task, which decreases the flexibility, adaptability, and potential of such systems. This paper introduces and presents a new automated weld parameter and pass deposition sequencing framework, which builds on the current state of the art developments and enables automatic planning of multi-pass welding for single-sided V-groove geometries. By integrating a novel cost-function concept that permutates and identifies the welding parameters for each layer through a user-driven weighting, the framework delivers the minimum number of passes, filler material and welding arc time based on application requirements. A mathematical model relating the cross-section area of beads with the pose of the torch and weaving width was built upon to allow full-process automated welding parameter generation and adaption for different geometric characteristics of the groove. The concept methodology and framework were then developed and verified experimentally, through robotically deployed Metal Active Gas (MAG) welding. For a given representative joint, the arc welding time and amount of filler wire were found to be 32.9 % and 26.18 % lower respectively, than the worst-case available welding parameter combination, delivering a corresponding decrease in direct automated welding manufacturing costs. Lastly, an ultrasonic inspection was undertaken to verify the consistent quality of the weldments validating the framework outcome and enabling welding pass automation through robotic systems
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