2,511 research outputs found

    QED-Induced Rapidity-Gap Events at the Z Peak

    Full text link
    We study rapidity-gap events in e+e−e^+e^- annihilation at the Z boson peak initiated by the emission of a virtual photon. This mechanism is suppressed by the QED coupling constant, but it is enhanced due to a large propagator term from the virtual photon. For typical kinematics, we find a smaller event rate than analogous QCD type gap events. In the small jet-pair invariant mass limit, the QED type events follow a 1+cos⁡2ξ1+\cos^2\theta distribution in the jet-pair scattering angle, instead of the sin⁡2ξ\sin^2\theta distribution of the QCD case.Comment: 13 pages, plain TeX (needs the PHYZZX macros), 4 figures in PostScript. SLAC-PUB-6116, DOE/ER/40762-009, U of Md. PP \#93-19

    Unusual linewidth dependence of coherent THz emission measured from intrinsic Josephson junction stacks in the hot-spot regime

    Full text link
    We report on measurements of the linewidth {\Delta}f of THz radiation emitted from intrinsic Josephson junction stacks, using a Nb/AlN/NbN integrated receiver for detection. Previous resolution limited measurements indicated that {\Delta}f may be below 1 GHz - much smaller than expected from a purely cavity-induced synchronization. While at low bias we found {\Delta}f to be not smaller than ? 500 MHz, at high bias, where a hotspot coexists with regions which are still superconducting, {\Delta}f turned out to be as narrow as 23 MHz. We attribute this to the hotspot acting as a synchronizing element. {\Delta}f decreases with increasing bath temperature, a behavior reminiscent of motional narrowing in NMR or ESR, but hard to explain in standard electrodynamic models of Josephson junctions.Comment: 4 figures, 5 page

    Two-Loop Polarization Contributions to Radiative-Recoil Corrections to Hyperfine Splitting in Muonium

    Full text link
    We calculate radiative-recoil corrections of order α2(Zα)(m/M)EF\alpha^2(Z\alpha)(m/M)E_F to hyperfine splitting in muonium generated by the diagrams with electron and muon polarization loops. These corrections are enhanced by the large logarithm of the electron-muon mass ratio. The leading logarithm cubed and logarithm squared contributions were obtained a long time ago. The single-logarithmic and nonlogarithmic contributions calculated here improve the theory of hyperfine splitting, and affect the value of the electron-muon mass ratio extracted from the experimental data on the muonium hyperfine splitting.Comment: 15 pages, 11 figure

    UV stable, Lorentz-violating dark energy with transient phantom era

    Full text link
    Phantom fields with negative kinetic energy are often plagued by the vacuum quantum instability in the ultraviolet region. We present a Lorentz-violating dark energy model free from this problem and show that the crossing of the cosmological constant boundary w=-1 to the phantom equation of state is realized before reaching a de Sitter attractor. Another interesting feature is a peculiar time-dependence of the effective Newton's constant; the magnitude of this effect is naturally small but may be close to experimental limits. We also derive momentum scales of instabilities at which tachyons or ghosts appear in the infrared region around the present Hubble scale and clarify the conditions under which tachyonic instabilities do not spoil homogeneity of the present/future Universe.Comment: 22 pages, 7 figures; Presentation modified substantially, results and conclusions unchanged. Journal versio

    A hybrid method for accurate iris segmentation on at-a-distance visible-wavelength images

    Full text link
    [EN] This work describes a new hybrid method for accurate iris segmentation from full-face images independently of the ethnicity of the subject. It is based on a combination of three methods: facial key-point detection, integro-differential operator (IDO) and mathematical morphology. First, facial landmarks are extracted by means of the Chehra algorithm in order to obtain the eye location. Then, the IDO is applied to the extracted sub-image containing only the eye in order to locate the iris. Once the iris is located, a series of mathematical morphological operations is performed in order to accurately segment it. Results are obtained and compared among four different ethnicities (Asian, Black, Latino and White) as well as with two other iris segmentation algorithms. In addition, robustness against rotation, blurring and noise is also assessed. Our method obtains state-of-the-art performance and shows itself robust with small amounts of blur, noise and/or rotation. Furthermore, it is fast, accurate, and its code is publicly available.Fuentes-Hurtado, FJ.; Naranjo Ornedo, V.; Diego-Mas, JA.; Alcañiz Raya, ML. (2019). A hybrid method for accurate iris segmentation on at-a-distance visible-wavelength images. EURASIP Journal on Image and Video Processing (Online). 2019(1):1-14. https://doi.org/10.1186/s13640-019-0473-0S11420191A. Radman, K. Jumari, N. Zainal, Fast and reliable iris segmentation algorithm. IET Image Process.7(1), 42–49 (2013).M. Erbilek, M. Fairhurst, M. C. D. C Abreu, in 5th International Conference on Imaging for Crime Detection and Prevention (ICDP 2013). Age prediction from iris biometrics (London, 2013), pp. 1–5. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6913712&isnumber=6867223 .A. Abbasi, M. Khan, Iris-pupil thickness based method for determining age group of a person. Int. Arab J. Inf. Technol. (IAJIT). 13(6) (2016).G. Mabuza-Hocquet, F. Nelwamondo, T. Marwala, in Intelligent Information and Database Systems. ed. by N. Nguyen, S. Tojo, L. Nguyen, B. TrawiƄski. Ethnicity Distinctiveness Through Iris Texture Features Using Gabor Filters. ACIIDS 2017. Lecture Notes in Computer Science, vol. 10192 (Springer, Cham, 2017).S. Lagree, K. W. Bowyer, in 2011 IEEE International Conference on Technologies for Homeland Security (HST). Predicting ethnicity and gender from iris texture (IEEEWaltham, 2011). p. 440–445. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6107909&isnumber=6107829 .J. G. Daugman, High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell.15(11), 1148–1161 (1993).N. Kourkoumelis, M. Tzaphlidou. Medical Safety Issues Concerning the Use of Incoherent Infrared Light in Biometrics, eds. A. Kumar, D. Zhang. Ethics and Policy of Biometrics. ICEB 2010. Lecture Notes in Computer Science, vol 6005 (Springer, Berlin, Heidelberg, 2010).R. P. Wildes, Iris recognition: an emerging biometric technology. Proc. IEEE. 85(9), 1348–1363 (1997).M. Kass, A. Witkin, D. Terzopoulos, Snakes: Active contour models. Int. J. Comput. Vision. 1(4), 321–331 (1988).S. J. Pundlik, D. L. Woodard, S. T. Birchfield, in 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. Non-ideal iris segmentation using graph cuts (IEEEAnchorage, 2008). p. 1–6. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4563108&isnumber=4562948 .H. Proença, Iris recognition: On the segmentation of degraded images acquired in the visible wavelength. IEEE Trans. Pattern Anal. Mach. Intell.32(8), 1502–1516 (2010). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5156505&isnumber=5487331 .T. Tan, Z. He, Z. Sun, Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition. Image Vision Comput.28(2), 223–230 (2010).C. -W. Tan, A. Kumar, in CVPR 2011 WORKSHOPS. Automated segmentation of iris images using visible wavelength face images (Colorado Springs, 2011). p. 9–14. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5981682&isnumber=5981671 .Y. -H. Li, M. Savvides, An automatic iris occlusion estimation method based on high-dimensional density estimation. IEEE Trans. Pattern Anal. Mach. Intell.35(4), 784–796 (2013).M. Yahiaoui, E. Monfrini, B. Dorizzi, Markov chains for unsupervised segmentation of degraded nir iris images for person recognition. Pattern Recogn. Lett.82:, 116–123 (2016).A. Radman, N. Zainal, S. A. Suandi, Automated segmentation of iris images acquired in an unconstrained environment using hog-svm and growcut. Digit. Signal Proc.64:, 60–70 (2017).N. Liu, H. Li, M. Zhang, J. Liu, Z. Sun, T. Tan, in 2016 International Conference on Biometrics (ICB). Accurate iris segmentation in non-cooperative environments using fully convolutional networks (Halmstad, 2016). p. 1–8. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7550055&isnumber=7550036 .Z. Zhao, A. Kumar, in 2017 IEEE International Conference on Computer Vision (ICCV). Towards more accurate iris recognition using deeply learned spatially corresponding features (Venice, 2017). p. 3829–3838. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8237673&isnumber=8237262 .P. Li, X. Liu, L. Xiao, Q. Song, Robust and accurate iris segmentation in very noisy iris images. Image Vision Comput.28(2), 246–253 (2010).D. S. Jeong, J. W. Hwang, B. J. Kang, K. R. Park, C. S. Won, D. -K. Park, J. Kim, A new iris segmentation method for non-ideal iris images. Image Vision Comput.28(2), 254–260 (2010).Y. Chen, M. Adjouadi, C. Han, J. Wang, A. Barreto, N. Rishe, J. Andrian, A highly accurate and computationally efficient approach for unconstrained iris segmentation. Image Vision Comput. 28(2), 261–269 (2010).Z. Zhao, A. Kumar, in 2015 IEEE International Conference on Computer Vision (ICCV). An accurate iris segmentation framework under relaxed imaging constraints using total variation model (Santiago, 2015). p. 3828–3836. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7410793&isnumber=7410356 .Y. Hu, K. Sirlantzis, G. Howells, Improving colour iris segmentation using a model selection technique. Pattern Recogn. Lett.57:, 24–32 (2015).E. Ouabida, A. Essadique, A. Bouzid, Vander lugt correlator based active contours for iris segmentation and tracking. Expert Systems Appl.71:, 383–395 (2017).C. -W. Tan, A. Kumar, Unified framework for automated iris segmentation using distantly acquired face images. IEEE Trans. Image Proc.21(9), 4068–4079 (2012).C. -W. Tan, A. Kumar, in Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012). Human identification from at-a-distance images by simultaneously exploiting iris and periocular features (Tsukuba, 2012). p. 553–556. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6460194&isnumber=6460043 .C. -W. Tan, A. Kumar, Towards online iris and periocular recognition under relaxed imaging constraints. IEEE Trans. Image Proc.22(10), 3751–3765 (2013).K. Y. Shin, Y. G. Kim, K. R. Park, Enhanced iris recognition method based on multi-unit iris images. Opt. Eng.52(4), 047201–047201 (2013).CASIA iris databases. http://biometrics.idealtest.org/ . Accessed 06 Sept 2017.WVU iris databases. hhttp://biic.wvu.edu/data-sets/synthetic-iris-dataset . Accessed 06 Sept 2017.UBIRIS iris database. http://iris.di.ubi.pt . Accessed 06 Sept 2017.MICHE iris database. http://biplab.unisa.it/MICHE/ . Accessed 06 Sept 2017.P. J. Phillips, et al, in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), 1. Overview of the face recognition grand challenge (San Diego, 2005). p. 947–954. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1467368&isnumber=31472 .D. S. Ma, J. Correll, B. Wittenbrink, The chicago face database: A free stimulus set of faces and norming data. Behav. Res. Methods. 47(4), 1122–1135 (2015).P. Soille, Morphological Image Analysis: Principles and Applications (Springer, 2013).A. K. Jain, Fundamentals of Digital Image Processing (Prentice-Hall, Inc., Englewood Cliffs, 1989).J. Daugman, How iris recognition works. IEEE Trans. Circ. Syst. Video Technol.14(1), 21–30 (2004).A. Asthana, S. Zafeiriou, S. Cheng, M. Pantic, in 2014 IEEE Conference on Computer Vision and Pattern Recognition. Incremental face alignment in the wild (Columbus, 2014). p. 1859–1866. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6909636&isnumber=6909393 .T. Baltrusaitis, P. Robinson, L. -P. Morency, in 2013 IEEE International Conference on Computer Vision Workshops. Constrained local neural fields for robust facial landmark detection in the wild (Sydney, 2013). p. 354–361. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6755919&isnumber=6755862 .X. Zhu, D. Ramanan, in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference On. Face detection, pose estimation, and landmark localization in the wild (IEEEBerlin Heidelberg, 2012), pp. 2879–2886.G. Tzimiropoulos, in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Project-out cascaded regression with an application to face alignment (Boston, 2015). p. 3659–3667. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7298989&isnumber=7298593 .H. Hofbauer, F. Alonso-Fernandez, P. Wild, J. Bigun, A. Uhl, in 2014 22nd International Conference on Pattern Recognition. A ground truth for iris segmentation (Stockholm, 2014). p. 527–532. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6976811&isnumber=6976709 .H. Proença, L. A. Alexandre, in 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems. The NICE.I: Noisy Iris Challenge Evaluation - Part I (Crystal City, 2007). p. 1–4. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4401910&isnumber=4401902 .J. Daugman, in European Convention on Security and Detection. High confidence recognition of persons by rapid video analysis of iris texture, (1995). p. 244–251. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=491729&isnumber=10615 .Code of Matlab implementation of Daugman’s integro-differential operator (IDO). https://es.mathworks.com/matlabcentral/fileexchange/15652-iris-segmentation-using-daugman-s-integrodifferential-operator/ . Accessed 06 Sept 2017.Code of Matlab implementation of Zhao and Kumar’s iris segmentation framework under relaxed imaging constraints using total variation model. http://www4.comp.polyu.edu.hk/~csajaykr/tvmiris.htm/ . Accessed 06 Sept 2017.Code of Matlab implementation of presented work. https://gitlab.com/ffuentes/hybrid_iris_segmentation/ . Accessed 06 Sept 2017.Face and eye detection with OpenCV. https://docs.opencv.org/trunk/d7/d8b/tutorial_py_face_detection.html . Accessed 07 Sept 2018.A. K. Boyat, B. K. Joshi, 6. A review paper:noise models in digital image processing signal & image processing. An International Journal (SIPIJ), (2015), pp. 63–75. https://doi.org/10.5121/sipij.2015.6206 .A. Buades, Y. Lou, J. M. Morel, Z. Tang, Multi image noise estimation and denoising (2010). Available: https://hal.archives-ouvertes.fr/hal-00510866/

    Exploration of the beliefs and experiences of Aboriginal people with cancer in Western Australia: a methodology to acknowledge cultural difference and build understanding

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Aboriginal Australians experience poorer outcomes, and are 2.5 times more likely to die from cancer than non-Aboriginal people, even after adjustment for stage of diagnosis, cancer treatment and comorbidities. They are also less likely to present early as a result of symptoms and to access treatment. Psycho-social factors affect Aboriginal people's willingness and ability to participate in cancer-related screening and treatment services, but little exploration of this has occurred within Australia to date. The current research adopted a phenomenological qualitative approach to understand and explore the lived experiences of Aboriginal Australians with cancer and their beliefs and understanding around this disease in Western Australia (WA). This paper details considerations in the design and process of conducting the research.</p> <p>Methods/Design</p> <p>The National Health and Medical Research Council (NHMRC) guidelines for ethical conduct of Aboriginal research were followed. Researchers acknowledged the past negative experiences of Aboriginal people with research and were keen to build trust and relationships prior to conducting research with them. Thirty in-depth interviews with Aboriginal people affected by cancer and twenty with health service providers were carried out in urban, rural and remote areas of WA. Interviews were audio-recorded, transcribed verbatim and coded independently by two researchers. NVivo7 software was used to assist data management and analysis. Participants' narratives were divided into broad categories to allow identification of key themes and discussed by the research team.</p> <p>Discussion and conclusion</p> <p>Key issues specific to Aboriginal research include the need for the research process to be relationship-based, respectful, culturally appropriate and inclusive of Aboriginal people. Researchers are accountable to both participants and the wider community for reporting their findings and for research translation so that the research outcomes benefit the Aboriginal community. There are a number of factors that influence whether the desired level of engagement can be achieved in practice. These include the level of resourcing for the project and the researchers' efforts to ensure dissemination and research translation; and the capacity of the Aboriginal community to engage with research given other demands upon their time.</p

    Search for Branons at LEP

    Get PDF
    We search, in the context of extra-dimension scenarios, for the possible existence of brane fluctuations, called branons. Events with a single photon or a single Z-boson and missing energy and momentum collected with the L3 detector in e^+ e^- collisions at centre-of-mass energies sqrt{s}=189-209$ GeV are analysed. No excess over the Standard Model expectations is found and a lower limit at 95% confidence level of 103 GeV is derived for the mass of branons, for a scenario with small brane tensions. Alternatively, under the assumption of a light branon, brane tensions below 180 GeV are excluded

    Massive migration from the steppe is a source for Indo-European languages in Europe

    Full text link
    We generated genome-wide data from 69 Europeans who lived between 8,000-3,000 years ago by enriching ancient DNA libraries for a target set of almost four hundred thousand polymorphisms. Enrichment of these positions decreases the sequencing required for genome-wide ancient DNA analysis by a median of around 250-fold, allowing us to study an order of magnitude more individuals than previous studies and to obtain new insights about the past. We show that the populations of western and far eastern Europe followed opposite trajectories between 8,000-5,000 years ago. At the beginning of the Neolithic period in Europe, ~8,000-7,000 years ago, closely related groups of early farmers appeared in Germany, Hungary, and Spain, different from indigenous hunter-gatherers, whereas Russia was inhabited by a distinctive population of hunter-gatherers with high affinity to a ~24,000 year old Siberian6 . By ~6,000-5,000 years ago, a resurgence of hunter-gatherer ancestry had occurred throughout much of Europe, but in Russia, the Yamnaya steppe herders of this time were descended not only from the preceding eastern European hunter-gatherers, but from a population of Near Eastern ancestry. Western and Eastern Europe came into contact ~4,500 years ago, as the Late Neolithic Corded Ware people from Germany traced ~3/4 of their ancestry to the Yamnaya, documenting a massive migration into the heartland of Europe from its eastern periphery. This steppe ancestry persisted in all sampled central Europeans until at least ~3,000 years ago, and is ubiquitous in present-day Europeans. These results provide support for the theory of a steppe origin of at least some of the Indo-European languages of Europe
    • 

    corecore