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BACKGROUND AND AIMS Joint hypermobility when associated with symptoms in the absence of systemic rheumatologic disease is termed as benign joint hypermobility syndrome (BJHS). BJHS is often an under-recognised and a poorly managed entity. Indian studies on BJHS are very few and none have been carried out in any of the service rheumatology centres. Hence(More)
Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging methods to the big data setting of the next-generation telescopes. This article sheds new light on(More)
Extremely high data rates expected in next-generation radio interferometers necessitate a fast and robust way to process measurements in a big data context. Dimensionality reduction can alleviate computational load needed to process these data, in terms of both computing speed and memory usage. In this article, we present image reconstruction results from(More)
Jet photoproduction, where the two highest transverse energy (E T ) jets have E jet T above 6 GeV and a jet-jet invariant mass above 23 GeV, has been studied with the ZEUS detector at the HERA ep collider. Resolved and direct photoproduction samples have been separated. The cross section as a function of the angle between the jet-jet axis and the beam(More)
Next-generation radio-interferometers face a computing challenge with respect to the imaging techniques that can be applied in the big data setting in which they are designed. Dimensionality reduction can thus provide essential savings of computing resources, allowing imaging methods to scale with data. The work presented here approaches dimensionality(More)
In deep inelastic neutral current scattering of positrons and protons at the center of mass energy of 300 GeV, we observe, with the ZEUS detector, events with a high energy neutron produced at very small scattering angles with respect to the proton direction. The events constitute a fixed fraction of the deep inelastic, neutral current event sample(More)
In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this paper, we propose a scalable algorithm for RI imaging that offers a highly parallelizable structure paving the way for nextgeneration(More)