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Sökning: LAR1:lu > Konferensbidrag

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1.
  • A., Johnsson, et al. (författare)
  • Physical inactivity increases the risk of endometrial cancer and premenopausal breast cancer
  • 2015
  • Ingår i: Cancer Research. - 0008-5472. ; 75:15 Suppl
  • Konferensbidrag (refereegranskat)abstract
    • Background. Epidemiological studies indicate that physical activity reduces the risk of cancer. Physical inactivity or sedentary behavior, has recently been suggested as a risk factor independent of physical activity level. Breast and endometrial cancer incidence have both been associated with physical activity, and endometrial cancer incidence with physical inactivity/sedentary behavior. The purpose of the present study was to investigate physical inactivity as a risk factor for breast cancer, divided into pre- and postmenopausal subtypes, and for endometrial cancer, and to explore possible dose-response relations regarding the level of physical inactivity. Methods. In a population-based prospective cohort study, 29 520 women in the southern part of Sweden, in ages between 25 and 64 years, participated. A questionnaire-based survey was performed 1990-92. Their reported professions were classified as sedentary or not which together with reported participation in competitive sports constituted the basis for classification into three activity-levels; (1) physical inactivity, defined as having sedentary occupation and no participation in competitive sports, (2) partly inactive, defined as either having a sedentary occupation or non- participation in competitive sports, (3) Physical active, defined as not having a sedentary occupation and participation in competitive sports. The association between physical inactivity and pre and postmenopausal breast and endometrial cancer incidence were analyzed by Cox regression, adjusted for hormonal factors, family history of cancer, body mass index (BMI) and age. Results. Physical inactive women had a significantly increased risk of endometrial cancer (HR = 2.41, 95% CI 1.14-5.11) and premenopausal breast cancer (HR = 2.40, 95% CI 1.14-5.02), compared with women who were less physical inactive. No such association was found for postmenopausal breast cancer. Analysis of linear trend showed a significant dose-response relationship with increased risk of both premenopausal breast cancer (ptrend 0.02) and endometrial cancer (ptrend
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2.
  • Aaboud, M, et al. (författare)
  • ATLAS Collaboration
  • 2019
  • Ingår i: XXVIIth International Conference on Ultrarelativistic Nucleus–Nucleus Collisions (Quark Matter 2018). - 0375-9474. ; 982, s. 985-1009
  • Konferensbidrag (refereegranskat)
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  • Aamodt, K., et al. (författare)
  • Alignment of the ALICE Inner Tracking System with cosmic-ray tracks
  • 2010
  • Ingår i: Journal of Instrumentation. - 1748-0221. ; 5
  • Konferensbidrag (refereegranskat)abstract
    • ALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 mu m in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10(5) charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.
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  • Aanæs, Henrik, et al. (författare)
  • Camera Resectioning from a Box
  • 2009
  • Ingår i: Lecture Notes in Computer Science. - 0302-9743 .- 1611-3349.
  • Konferensbidrag (refereegranskat)abstract
    • In this paper we describe how we can do camera resectioning from a box with unknown dimensions, i.e. determine the camera model, assuming that image pixels are square. This assumption is equivalent to assuming that the camera as an aspect ratio of one and zero skew, and holds for most - if not all - digital cameras. Our proposed method works by first deriving 9 linear constraints on the projective camera matrix from the box, leaving a 3 dimensional subspace in which the projective camera matrix can lye. A single solution in this 3D subspace is then found via a method by Triggs in 1999, which uses the squared pixel assumption to set up a 4th degree polynomial to which the solution is the desired model. This approach is, however, numerically challenging, and we use several means to combat this issue. Lastly the solution is refined in an iterative manner, i.e. using bundle adjustment.
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  • Aanæs, Henrik, et al. (författare)
  • Factorization with erroneous data
  • 2002
  • Konferensbidrag (refereegranskat)abstract
    • Factorization algorithms for recovering structure and motion from an image stream have many advantages, but traditionally requires a set of well tracked feature points. This limits the usability since, correctly tracked feature points are not available in general. There is thus a need to make factorization algorithms deal successfully with incorrectly tracked feature points. We propose a new computationally efficient algorithm for applying an arbitrary error function in the factorization scheme, and thereby enable the use of robust statistical techniques and arbitrary noise models for individual feature points. These techniques and models effectively deal with feature point noise as well as feature mismatch and missing features. Furthermore, the algorithm includes a new method for Euclidean reconstruction that experimentally shows a significant improvement in convergence of the factorization algorithms. The proposed algorithm has been implemented in the Christy–Horaud factorization scheme and the results clearly illustrate a considerable increase in error tolerance.
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