Creating and validating self-efficacy scales for students

Purpose: student radiographers must possess certain abilities to progress in their training; these can be assessed in various ways. Bandura’s social cognitive theory identifies self-efficacy as a key psychological construct with regard to how people adapt to environments where new skills are developed. Use of this construct is common in health care literature but little has been noted within radiographic literature. The authors sought to develop a self-efficacy scale for student radiographers. Method: the scale was developed following a standard format. An initial pool of 80 items was generated and psychometric analysis was used to reduce this to 68 items. Radiography students drawn from 7 universities were participants (N=198) in validating the scale. Results: the psychometric properties of the scale were examined using analysis of variance (ANOVA), factor analysis and item analysis. ANOVA demonstrated an acceptable level of known group validity: first-year, second-year, and third-year students all scored significantly differently (P=.035) from one another. Factor analysis identified the most significant factor as confidence in image appraisal. The scale was refined using item and factor analysis to produce the final 25-item scale. Conclusion This is the first published domain-specific self-efficacy scale validated specifically for student radiographers. In its current format it may have pedagogical utility. The authors currently are extending the work to add to the scale’s validity and embedding it into student training to assess its predictive value

Survival and dispersal of a defined cohort of Irish cattle

An understanding of livestock movement is critical to effective disease prevention, control and prediction. However, livestock movement in Ireland has not yet been quantified. This study has sought to define the survival and dispersal of a defined cohort of cattle born in Co. Kerry during 2000. The cohort was observed for a maximum of four years, from January 1, 2000 to December 31, 2004. Beef and dairy animals moved an average 1.31 and 0.83 times, respectively. At study end, 18.8% of the beef animals remained alive on Irish farms, including 6.7% at the farm-of-birth, compared with 48.6% and 27.7% for dairy animals respectively. Beef animals werae dispersed to all Irish counties, but mainly to Cork, Limerick, Tipperary and Galway. Dairy animals mainly moved to Cork, Limerick, and Tipperary, with less animals going to Galway, Meath and Kilkenny. The four-year survival probability was 0.07 (male beef animals), 0.25 (male dairy), 0.38 (female beef), and 0.72 (female dairy). Although there was considerable dispersal, the number of moves per animal was less than expected

Exclusive Leptoproduction of rho^0 Mesons from Hydrogen at Intermediate Virtual Photon Energies

Measurements of the cross section for exclusive virtual-photoproduction of rho^0 mesons from hydrogen are reported. The data were collected by the HERMES experiment using 27.5 GeV positrons incident on a hydrogen gas target in the HERA storage ring. The invariant mass W of the photon-nucleon system ranges from 4.0 to 6.0 GeV, while the negative squared four-momentum Q^2 of the virtual photon varies from 0.7 to 5.0 GeV^2. The present data together with most of the previous data at W > 4 GeV are well described by a model that infers the W-dependence of the cross section from the dependence on the Bjorken scaling variable x of the unpolarized structure function for deep-inelastic scattering. In addition, a model calculation based on Off-Forward Parton Distributions gives a fairly good account of the longitudinal component of the rho^0 production cross section for Q^2 > 2 GeV^2.Comment: 10 pages, 6 embedded figures, LaTeX for SVJour(epj) document class. Revisions: curves added to Fig. 1, several clarifications added to tex

Effects of chemokines on proliferation and apoptosis of human mesangial cells

BACKGROUND: Proliferation and apoptosis of mesangial cells (MC) are important mechanisms during nephrogenesis, for the maintenance of glomerular homeostasis as well as in renal disease and glomerular regeneration. Expression of chemokines and chemokine receptors by intrinsic renal cells, e.g. SLC/CCL21 on podocytes and CCR7 on MC is suggested to play a pivotal role during these processes. Therefore the effect of selected chemokines on MC proliferation and apoptosis was studied. METHODS: Proliferation assays, cell death assays including cell cycle analysis, hoechst stain and measurement of caspase-3 activity were performed. RESULTS: A dose-dependent, mesangioproliferative effect of the chemokine SLC/CCL21, which is constitutively expressed on human podocytes was seen via activation of the chemokine receptor CCR7, which is constitutively expressed on MC. In addition, in cultured MC SLC/CCL21 had a protective effect on cell survival in Fas-mediated apoptosis. The CXCR3 ligands IP-10/CXCL10 and Mig/CXCL9 revealed a proproliferative effect but did not influence apoptosis of MC. Both the CCR1 ligand RANTES/CCL5 and the amino-terminally modified RANTES analogue Met-RANTES which blocks CCR1 signalling had no effect on proliferation and apoptosis. CONCLUSIONS: The different effects of chemokines and their respective receptors on proliferation and apoptosis of MC suggest highly regulated, novel biological functions of chemokine/chemokine receptor pairs in processes involved in renal inflammation, regeneration and glomerular homeostasis

Are Algae Relevant to the Detritus-Based Food Web in Tank-Bromeliads?

We assessed the occurrence of algae in five species of tank-bromeliads found in contrasting environmental sites in a Neotropical, primary rainforest around the Nouragues Research Station, French Guiana. The distributions of both algal abundance and biomass were examined based on physical parameters, the morphological characteristics of bromeliad species and with regard to the structure of other aquatic microbial communities held in the tanks. Algae were retrieved in all of the bromeliad species with mean densities ranging from ∼102 to 104 cells/mL. Their biomass was positively correlated to light exposure and bacterial biomass. Algae represented a tiny component of the detrital food web in shaded bromeliads but accounted for up to 30 percent of the living microbial carbon in the tanks of Catopsis berteroniana, located in a highly exposed area. Thus, while nutrient supplies are believed to originate from wind-borne particles and trapped insects (i.e., allochtonous organic matter), our results indicate that primary producers (i.e., autochtonous organic matter) are present in this insectivorous bromeliad. Using a 24-h incubation of size-fractionated and manipulated samples from this plant, we evaluated the impact of mosquito foraging on algae, other microorganisms and rotifers. The prey assemblages were greatly altered by the predation of mosquito larvae. Grazing losses indicated that the dominant algal taxon, Bumilleriopsis sp., like protozoa and rotifers, is a significant part of the diet of mosquito larvae. We conclude that algae are a relevant functional community of the aquatic food web in C. berteroniana and might form the basis of a complementary non-detrital food web

Euclid preparation: V. Predicted yield of redshift 7<z<9 quasars from the wide survey

We provide predictions of the yield of 7 < z < 9 quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisions to the Euclid near-infrared filter wavelengths; we adopt steeper rates of decline of the quasar luminosity function (QLF; Φ) with redshift, Φ ∝ 10k(z−6) , k = −0.72, and a further steeper rate of decline, k = −0.92; we use better models of the contaminating populations (MLT dwarfs and compact early-type galaxies); and we make use of an improved Bayesian selection method, compared to the colour cuts used for the Red Book calculation, allowing the identification of fainter quasars, down to JAB ∼ 23. Quasars at z > 8 may be selected from Euclid OY JH photometry alone, but selection over the redshift interval 7 < z < 8 is greatly improved by the addition of z-band data from, e.g., Pan-STARRS and LSST. We calculate predicted quasar yields for the assumed values of the rate of decline of the QLF beyond z = 6. If the decline of the QLF accelerates beyond z = 6, with k = −0.92, Euclid should nevertheless find over 100 quasars with 7.0 < z < 7.5, and ∼ 25 quasars beyond the current record of z = 7.5, including ∼ 8 beyond z = 8.0. The first Euclid quasars at z > 7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 < z < 8, M1450 < −25, using 8 m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at JAB ∼ 23. The precision with which k can be determined over 7 < z < 8 depends on the value of k, but assuming k = −0.72 it can be measured to a 1σ uncertainty of 0.07

Euclid preparation: V. Predicted yield of redshift 7 < z < 9 quasars from the wide survey

We provide predictions of the yield of 7 8 may be selected from Euclid OY JH photometry alone, but selection over the redshift interval 7 7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 < z < 8, M1450 < −25, using 8 m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at JAB ∼ 23. The precision with which k can be determined over 7 < z < 8 depends on the value of k, but assuming k = −0.72 it can be measured to a 1σ uncertainty of 0.07

Euclid preparation: X. The Euclid photometric-redshift challenge

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-zs at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2−2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highlyaccurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo-z deviates by more than 0.15(1 + z) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example z > 1. However they generally perform better than template-fitting methods at low redshift (z < 0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo-z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority

Measurement of the intrinsic electron neutrino component in the T2K neutrino beam with the ND280 detector

The T2K experiment has reported the first observation of the appearance of electron neutrinos in a muon neutrino beam. The main and irreducible background to the appearance signal comes from the presence in the neutrino beam of a small intrinsic component of electron neutrinos originating from muon and kaon decays. In T2K, this component is expected to represent 1.2% of the total neutrino flux. A measurement of this component using the near detector (ND280), located 280 m from the target, is presented. The charged current interactions of electron neutrinos are selected by combining the particle identification capabilities of both the time projection chambers and electromagnetic calorimeters of ND280. The measured ratio between the observed electron neutrino beam component and the prediction is 1.01 +/- 0.10 providing a direct confirmation of the neutrino fluxes and neutrino cross section modeling used for T2K neutrino oscillation analyses. Electron neutrinos coming from muons and kaons decay are also separately measured, resulting in a ratio with respect to the prediction of 0.68 +/- 0.30 and 1.10 +/- 0.14, respectively

T2K neutrino flux prediction

cited By 15 art_number: 012001 affiliation: Centre for Particle Physics, Department of Physics, University of Alberta, Edmonton, AB, Canada; Albert Einstein Center for Fundamental Physics, Laboratory for High Energy Physics (LHEP), University of Bern, Bern, Switzerland; Department of Physics, Boston University, Boston, MA, United States; Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; Department of Physics and Astronomy, University of California Irvine, Irvine, CA, United States; IRFU, CEA Saclay, Gif-sur-Yvette, France; Institute for Universe and Elementary Particles, Chonnam National University, Gwangju, South Korea; Department of Physics, University of Colorado at Boulder, Boulder, CO, United States; Department of Physics, Colorado State University, Fort Collins, CO, United States; Department of Physics, Dongshin University, Naju, South Korea; Department of Physics, Duke University, Durham, NC, United States; IN2P3-CNRS, Laboratoire Leprince-Ringuet, Ecole Polytechnique, Palaiseau, France; Institute for Particle Physics, ETH Zurich, Zurich, Switzerland; Section de Physique, DPNC, University of Geneva, Geneva, Switzerland; H. Niewodniczanski Institute of Nuclear Physics PAN, Cracow, Poland; High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki, Japan; Institut de Fisica d’Altes Energies (IFAE), Bellaterra (Barcelona), Spain; IFIC (CSIC and University of Valencia), Valencia, Spain; Department of Physics, Imperial College London, London, United Kingdom; INFN Sezione di Bari, Dipartimento Interuniversitario di Fisica, Università e Politecnico di Bari, Bari, Italy; INFN Sezione di Napoli and Dipartimento di Fisica, Università di Napoli, Napoli, Italy; INFN Sezione di Padova, Dipartimento di Fisica, Università di Padova, Padova, Italy; INFN Sezione di Roma, Università di Roma la Sapienza, Roma, Italy; Institute for Nuclear Research, Russian Academy of Sciences, Moscow, Russian Federation; Kobe University, Kobe, Japan; Department of Physics, Kyoto University, Kyoto, Japan; Physics Department, Lancaster University, Lancaster, United Kingdom; Department of Physics, University of Liverpool, Liverpool, United Kingdom; Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA, United States; Université de Lyon, Université Claude Bernard Lyon 1, IPN Lyon (IN2P3), Villeurbanne, France; Department of Physics, Miyagi University of Education, Sendai, Japan; National Centre for Nuclear Research, Warsaw, Poland; State University of New York at Stony Brook, Stony Brook, NY, United States; Department of Physics and Astronomy, Osaka City University, Department of Physics, Osaka, Japan; Department of Physics, Oxford University, Oxford, United Kingdom; UPMC, Université Paris Diderot, Laboratoire de Physique Nucléaire et de Hautes Energies (LPNHE), Paris, France; Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, United States; School of Physics, Queen Mary University of London, London, United Kingdom; Department of Physics, University of Regina, Regina, SK, Canada; Department of Physics and Astronomy, University of Rochester, Rochester, NY, United States; III. Physikalisches Institut, RWTH Aachen University, Aachen, Germany; Department of Physics and Astronomy, Seoul National University, Seoul, South Korea; Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom; University of Silesia, Institute of Physics, Katowice, Poland; STFC, Rutherford Appleton Laboratory, Harwell Oxford, Warrington, United Kingdom; Department of Physics, University of Tokyo, Tokyo, Japan; Institute for Cosmic Ray Research, Kamioka Observatory, University of Tokyo, Kamioka, Japan; Institute for Cosmic Ray Research, Research Center for Cosmic Neutrinos, University of Tokyo, Kashiwa, Japan; Department of Physics, University of Toronto, Toronto, ON, Canada; TRIUMF, Vancouver, BC, Canada; Department of Physics and Astronomy, University of Victoria, Victoria, BC, Canada; Faculty of Physics, University of Warsaw, Warsaw, Poland; Institute of Radioelectronics, Warsaw University of Technology, Warsaw, Poland; Department of Physics, University of Warwick, Coventry, United Kingdom; Department of Physics, University of Washington, Seattle, WA, United States; Department of Physics, University of Winnipeg, Winnipeg, MB, Canada; Faculty of Physics and Astronomy, Wroclaw University, Wroclaw, Poland; Department of Physics and Astronomy, York University, Toronto, ON, Canada references: Astier, P., (2003) Nucl. Instrum. Methods Phys. Res., Sect. A, 515, p. 800. , (NOMAD Collaboration), NIMAER 0168-9002 10.1016/j.nima.2003.07.054; Ahn, M., (2006) Phys. Rev. D, 74, p. 072003. , (K2K Collaboration), PRVDAQ 1550-7998 10.1103/PhysRevD.74.072003; Adamson, P., (2008) Phys. Rev. D, 77, p. 072002. , (MINOS Collaboration), PRVDAQ 1550-7998 10.1103/PhysRevD.77.072002; Aguilar-Arevalo, A., (2009) Phys. Rev. D, 79, p. 072002. , (MiniBooNE Collaboration), PRVDAQ 1550-7998 10.1103/PhysRevD.79.072002; (2003) Letter of Intent: Neutrino Oscillation Experiment at JHF, , http://neutrino.kek.jp/jhfnu/loi/loi_JHFcor.pdf, T2K Collaboration; Abe, K., (2011) Nucl. Instrum. Methods Phys. Res., Sect. A, 659, p. 106. , (T2K Collaboration), NIMAER 0168-9002 10.1016/j.nima.2011.06.067; Abe, K., (2011) Phys. Rev. Lett., 107, p. 041801. , (T2K Collaboration), PRLTAO 0031-9007 10.1103/PhysRevLett.107.041801; Abe, K., (2012) Phys. Rev. D, 85, p. 031103. , (T2K Collaboration), PRVDAQ 1550-7998 10.1103/PhysRevD.85.031103; Fukuda, Y., (2003) Nucl. Instrum. Methods Phys. Res., Sect. A, 501, p. 418. , NIMAER 0168-9002 10.1016/S0168-9002(03)00425-X; Beavis, D., Carroll, A., Chiang, I., (1995), Physics Design Report, BNL 52459Abgrall, N., (2011) Phys. Rev. C, 84, p. 034604. , (NA61/SHINE Collaboration), PRVCAN 0556-2813 10.1103/PhysRevC.84.034604; Abgrall, N., (2012) Phys. Rev. C, 85, p. 035210. , (NA61/SHINE Collaboration), PRVCAN 0556-2813 10.1103/PhysRevC.85.035210; Bhadra, S., (2013) Nucl. Instrum. Methods Phys. Res., Sect. A, 703, p. 45. , NIMAER 0168-9002 10.1016/j.nima.2012.11.044; Van Der Meer, S., Report No. CERN-61-07Palmer, R., Report No. CERN-65-32, 141Ichikawa, A., (2012) Nucl. Instrum. Methods Phys. Res., Sect. A, 690, p. 27. , NIMAER 0168-9002 10.1016/j.nima.2012.06.045; Matsuoka, K., (2010) Nucl. Instrum. Methods Phys. Res., Sect. A, 624, p. 591. , NIMAER 0168-9002 10.1016/j.nima.2010.09.074; Abe, K., (2012) Nucl. Instrum. Methods Phys. Res., Sect. A, 694, p. 211. , (T2K Collaboration), NIMAER 0168-9002 10.1016/j.nima.2012.03.023; Abgrall, N., (2011) Nucl. Instrum. Methods Phys. Res., Sect. A, 637, p. 25. , (T2K ND280 TPC Collaboration), NIMAER 0168-9002 10.1016/j.nima.2011.02. 036; Amaudruz, P.-A., (2012) Nucl. Instrum. Methods Phys. Res., Sect. A, 696, p. 1. , (T2K ND280 FGD Collaboration), NIMAER 0168-9002 10.1016/j.nima.2012.08. 020; Battistoni, G., Cerutti, F., Fasso, A., Ferrari, A., Muraro, S., Ranft, J., Roesler, S., Sala, P.R., (2007) AIP Conf. Proc., 896, p. 31. , APCPCS 0094-243X 10.1063/1.2720455; A. Ferrari, P. R. Sala, A. Fasso, and J. Ranft, Report No. CERN-2005-010A. Ferrari P. R. Sala A. Fasso J. Ranft Report No. SLAC-R-773A. Ferrari P. R. Sala A. Fasso J. Ranft Report No. INFN-TC-05-11R. Brun, F. Carminati, and S. Giani, Report No. CERN-W5013Zeitnitz, C., Gabriel, T.A., (1993) Proceedings of International Conference on Calorimetry in High Energy Physics, , in Elsevier Science B.V., Tallahassee, FL; Fasso, A., Ferrari, A., Ranft, J., Sala, P.R., Proceedings of the International Conference on Calorimetry in High Energy Physics, 1994, , in; Beringer, J., (2012) Phys. Rev. D, 86, p. 010001. , (Particle Data Group), PRVDAQ 1550-7998 10.1103/PhysRevD.86.010001; Eichten, T., (1972) Nucl. Phys. B, 44, p. 333. , NUPBBO 0550-3213 10.1016/0550-3213(72)90120-4; Allaby, J.V., Tech. Rep. 70-12 (CERN, 1970)Chemakin, I., (2008) Phys. Rev. C, 77, p. 015209. , PRVCAN 0556-2813 10.1103/PhysRevC.77.015209; Abrams, R.J., Cool, R., Giacomelli, G., Kycia, T., Leontic, B., Li, K., Michael, D., (1970) Phys. Rev. D, 1, p. 1917. , PRVDAQ 0556-2821 10.1103/PhysRevD.1.1917; Allaby, J.V., (1970) Yad. Fiz., 12, p. 538. , IDFZA7 0044-0027; Allaby, J.V., (1969) Phys. Lett. B, 30, p. 500. , PYLBAJ 0370-2693 10.1016/0370-2693(69)90184-1; Allardyce, B.W., (1973) Nucl. Phys. A, 209, p. 1. , NUPABL 0375-9474 10.1016/0375-9474(73)90049-3; Bellettini, G., Cocconi, G., Diddens, A.N., Lillethun, E., Matthiae, G., Scanlon, J.P., Wetherell, A.M., (1966) Nucl. Phys., 79, p. 609. , NUPHA7 0029-5582 10.1016/0029-5582(66)90267-7; Bobchenko, B.M., (1979) Sov. J. Nucl. Phys., 30, p. 805. , SJNCAS 0038-5506; Carroll, A.S., (1979) Phys. Lett. B, 80, p. 319. , PYLBAJ 0370-2693 10.1016/0370-2693(79)90226-0; Cronin, J.W., Cool, R., Abashian, A., (1957) Phys. Rev., 107, p. 1121. , PHRVAO 0031-899X 10.1103/PhysRev.107.1121; Chen, F.F., Leavitt, C., Shapiro, A., (1955) Phys. Rev., 99, p. 857. , PHRVAO 0031-899X 10.1103/PhysRev.99.857; Denisov, S.P., Donskov, S.V., Gorin, Yu.P., Krasnokutsky, R.N., Petrukhin, A.I., Prokoshkin, Yu.D., Stoyanova, D.A., (1973) Nucl. Phys. B, 61, p. 62. , NUPBBO 0550-3213 10.1016/0550-3213(73)90351-9; Longo, M.J., Moyer, B.J., (1962) Phys. Rev., 125, p. 701. , PHRVAO 0031-899X 10.1103/PhysRev.125.701; Vlasov, A.V., (1978) Sov. J. Nucl. Phys., 27, p. 222. , SJNCAS 0038-5506; Feynman, R., (1969) Phys. Rev. Lett., 23, p. 1415. , PRLTAO 0031-9007 10.1103/PhysRevLett.23.1415; Bonesini, M., Marchionni, A., Pietropaolo, F., Tabarelli De Fatis, T., (2001) Eur. Phys. J. C, 20, p. 13. , EPCFFB 1434-6044 10.1007/s100520100656; Barton, D.S., (1983) Phys. Rev. D, 27, p. 2580. , PRVDAQ 0556-2821 10.1103/PhysRevD.27.2580; Skubic, P., (1978) Phys. Rev. D, 18, p. 3115. , PRVDAQ 0556-2821 10.1103/PhysRevD.18.3115; Feynman, R.P., (1972) Photon-Hadron Interactions, , Benjamin, New York; Bjorken, J.D., Paschos, E.A., (1969) Phys. Rev., 185, p. 1975. , PHRVAO 0031-899X 10.1103/PhysRev.185.1975; Taylor, F.E., Carey, D., Johnson, J., Kammerud, R., Ritchie, D., Roberts, A., Sauer, J., Walker, J., (1976) Phys. Rev. D, 14, p. 1217. , PRVDAQ 0556-2821 10.1103/PhysRevD.14.1217; Abgrall, N., (2013) Nucl. Instrum. Methods Phys. Res., Sect. A, 701, p. 99. , NIMAER 0168-9002 10.1016/j.nima.2012.10.079; Hayato, Y., (2002) Nucl. Phys. B, Proc. Suppl., 112, p. 171. , NPBSE7 0920-5632 10.1016/S0920-5632(02)01759-0 correspondence_address1: Abe, K.; Institute for Cosmic Ray Research, Kamioka Observatory, University of Tokyo, Kamioka, Japan coden: PRVDA abbrev_source_title: Phys Rev D Part Fields Gravit Cosmol document_type: Article source: Scopu