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Aliaga, R. J., & Guirao, A. J. (2019). On the preserved extremal structure of Lipschitz-free spaces. Studia Math., 245(1), 1–14.
Abstract: We characterize preserved extreme points of the unit ball of Lipschitz-free spaces F (X) in terms of simple geometric conditions on the underlying metric space (X, d). Namely, the preserved extreme points are the elementary molecules corresponding to pairs of points p, q in X such that the triangle inequality d (p, q) <= d (p, r) + d (q, r) is uniformly strict for r away from p, q. For compact X, this condition reduces to the triangle inequality being strict. As a consequence, we give an affirmative answer to a conjecture of N. Weaver that compact spaces are concave if and only if they have no triple of metrically aligned points, and we show that all extreme points are preserved for several classes of compact metric spaces X, including Holder and countable compacta.
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Moles-Valls, R. (2011). Alignment of the ATLAS Inner Detector with proton-proton collision data. Nucl. Instrum. Methods Phys. Res. A, 650(1), 235–239.
Abstract: ATLAS is a multipurpose experiment that records the products of the LHC collisions. In order to reconstruct the trajectories of the charged particles produced in these collisions. ATLAS has an internal tracking system made of silicon planar sensors (pixels and micro-strips) and drift-tube based detectors; both together, they constitute the ATLAS Inner Detector. The alignment of the ATLAS tracking system requires the determination of their almost 36,000 degrees-of-freedom (DOF) with high accuracy. Thus, the demanded precision for the alignment of the pixel and micro-strip sensors is below 10 μm. As alignment algorithms are based on the minimization of the track-hit residuals, a linear system with a large number of DOF has to be solved. The alignment results of the ATLAS tracker using data recorded during cosmic commissioning phases in 2008 and 2009 and the LHC start up run in 2009 will be presented. Moreover recent 7 TeV data collected during 2010 run have been used to study the detector performance. These studies reveal that the detector is aligned with a precision high enough to cope with the requirements.
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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2015). LHCb detector performance. Int. J. Mod. Phys. A, 30(7), 1530022–73pp.
Abstract: The LHCb detector is a forward spectrometer at the Large Hadron Collider (LHC) at CERN. The experiment is designed for precision measurements of CP violation and rare decays of beauty and charm hadrons. In this paper the performance of the various LHCb sub-detectors and the trigger system are described, using data taken from 2010 to 2012. It is shown that the design criteria of the experiment have been met. The excellent performance of the detector has allowed the LHCb collaboration to publish a wide range of physics results, demonstrating LHCb's unique role, both as a heavy flavour experiment and as a general purpose detector in the forward region.
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Carrasco-Ribelles, L. A., Pardo-Mas, J. R., Tortajada, S., Saez, C., Valdivieso, B., & Garcia-Gomez, J. M. (2021). Predicting morbidity by local similarities in multi-scale patient trajectories. J. Biomed. Inform., 120, 103837–9pp.
Abstract: Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease. On the other hand, healthcare predictive models generally rely on static snapshots of patient information. Only a few works about prediction in healthcare have been found that use PTs, and therefore benefit from their temporal dimension. All of them, however, have used PTs created from single-source information. Therefore, the use of longitudinal multi-scale data to build PTs and use them to obtain predictions about health conditions is yet to be explored. Our hypothesis is that local similarities on small chunks of PTs can identify similar patients concerning their future morbidities. The objectives of this work are (1) to develop a methodology to identify local similarities between PTs before the occurrence of morbidities to predict these on new query individuals; and (2) to validate this methodology on risk prediction of cardiovascular diseases (CVD) occurrence in patients with diabetes. We have proposed a novel formal definition of PTs based on sequences of longitudinal multi-scale data. Moreover, a dynamic programming methodology to identify local alignments on PTs for predicting future morbidities is proposed. Both the proposed methodology for PT definition and the alignment algorithm are generic to be applied on any clinical domain. We validated this solution for predicting CVD in patients with diabetes and we achieved a precision of 0.33, a recall of 0.72 and a specificity of 0.38. Therefore, the proposed solution in the diabetes use case can result of utmost utility to secondary screening.
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Yepes, H. (2012). The ANTARES neutrino detector instrumentation. J. Instrum., 7, C01022–9pp.
Abstract: ANTARES is actually the fully operational and the largest neutrino telescope in the Northern hemisphere. Located in the Mediterranean Sea, it consists of a 3D array of 885 photomultiplier tubes (PMTs) arranged in 12 detection lines (25 storeys each), able to detect the Cherenkov light induced by upgoing relativistic muons produced in the interaction of high energy cosmic neutrinos with the detector surroundings. Among its physics goals, the search for neutrino astrophysical sources and the indirect detection of dark matter particles coming from the sun are of particular interest. To reach these goals, good accuracy in track reconstruction is mandatory, so several calibration systems for timing and positioning have been developed. In this contribution we will present the design of the detector, calibration systems, associated equipment and its performance on track reconstruction.
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