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Gimenez-Alventosa, V., Gimenez, V., Ballester, F., Vijande, J., & Andreo, P. (2020). Monte Carlo calculation of beam quality correction factors for PTW cylindrical ionization chambers in photon beams. Phys. Med. Biol., 65(20), 205005–11pp.
Abstract: The beam quality correction factork(Q)for megavoltage photon beams has been calculated for eight PTW (Freiburg, Germany) ionization chambers (Farmer chambers PTW30010, PTW30011, PTW30012, and PTW30013, Semiflex 3D chambers PTW31021, PTW31010, and PTW31013, and the PinPoint 3D chamber PTW31016). Simulations performed on the widely used NE-2571 ionization chamber have been used to benchmark the results. The Monte Carlo code PENELOPE/penEasy was used to calculate the absorbed dose to a point in water and the absorbed dose to the active air volume of the chambers for photon beams in the range 4 to 24 MV. Of the nine ionization chambers analysed, only five are included in the current version of the International Code of Practice for dosimetry based on standards of absorbed dose to water (IAEA TRS 398). The values reported in this work agree with those in the literature within the uncertainty estimates and are to be included in the average values of the data obtained by different working groups for the forthcoming update of TRS 398.
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Schaffter, T. et al, Albiol, F., & Caballero, L. (2020). Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms. JAMA Netw. Open, 3(3), e200265–15pp.
Abstract: Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results Overall, 144231 screening mammograms from 85580 US women (952 cancer positive <= 12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166578 examinations from 68008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation. Question How do deep learning algorithms perform compared with radiologists in screening mammography interpretation? Findings In this diagnostic accuracy study using 144231 screening mammograms from 85580 women from the United States and 166578 screening mammograms from 68008 women from Sweden, no single artificial intelligence algorithm outperformed US community radiologist benchmarks; including clinical data and prior mammograms did not improve artificial intelligence performance. However, combining best-performing artificial intelligence algorithms with single-radiologist assessment demonstrated increased specificity. Meaning Integrating artificial intelligence to mammography interpretation in single-radiologist settings could yield significant performance improvements, with the potential to reduce health care system expenditures and address resource scarcity experienced in population-based screening programs. This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms.
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Maso-Ferrando, A., Sanchis-Gual, N., Font, J. A., & Olmo, G. J. (2021). Boson stars in Palatini f(R) gravity. Class. Quantum Gravity, 38(19), 194003–25pp.
Abstract: We explore equilibrium solutions of spherically symmetric boson stars in the Palatini formulation of f (R) gravity. We account for the modifications introduced in the gravitational sector by using a recently established correspondence between modified gravity with scalar matter and general relativity with modified scalar matter. We focus on the quadratic theory f (R) = R + xi R-2 and compare its solutions with those found in general relativity, exploring both positive and negative values of the coupling parameter xi. As matter source, a complex, massive scalar field with and without self-interaction terms is considered. Our results show that the existence curves of boson stars in Palatini f (R) gravity are fairly similar to those found in general relativity. Major differences are observed for negative values of the coupling parameter which results in a repulsive gravitational component for high enough scalar field density distributions. Adding self-interactions makes the degeneracy between f (R) and general relativity even more pronounced, leaving very little room for observational discrimination between the two theories.
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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2019). Observation of B-(s)(0) -> J/psi p(p)over-bar Decays and Precision Measurements of the B-(s)(0) Masses. Phys. Rev. Lett., 122(19), 191804–10pp.
Abstract: The first observation of the decays B-(s)(0) -> J/psi p (p) over bar is reported, using proton-proton collision data corresponding to an integrated luminosity of 5.2 fb(-1), collected with the LHCb detector. These decays are suppressed due to limited available phase space, as well as due to Okubo-Zweig-Iizuka or Cabibbo suppression. The measured branching fractions are beta(B-(s)(0) -> J/psi p (p) over bar). [4.51 +/- 0.40(stat)+/- 0.44(syst)] x 10(-7), BB(s)0 -> J/psi p (p) over bar) = 3.58 +/- 0.19(stat) 0.39(syst)] x 10(-6). For the B-s(0) meson, the result is much higher than the expected value of O(10(-9)). The small available phase space in these decays also allows for the most precise single measurement of both the B-0 mass as 5279.74 +/- 0.30(stat) 0.10(syst) MeV and the B-s(0) mass as 5366.85 +/- 0.19(stat) +/- 0.13(syst) MeV.
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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2019). Search for CP Violation in D-s(+) -> K-S(0)pi(+), D+ -> (KSK+)-K-0, and D+ -> phi pi(+) Decays. Phys. Rev. Lett., 122(19), 191803–11pp.
Abstract: A search for charge-parity (CP) violation in Cabibbo-suppressed D-s(+) -> K-S(0)pi(+), D+ -> (KSK+)-K-0, and D+ -> phi pi(+) decays is reported using proton-proton collision data, corresponding to an integrated luminosity of 3.8 fb(-1), collected at a center-of-mass energy of 13 TeV with the LHCb detector. High-yield samples of kinematically and topologically similar Cabibbo-favored D-(s())+ decays are analyzed to subtract nuisance asymmetries due to production and detection effects, including those induced by CP violation in the neutral kaon system. The results are A(CP)(D-s(+) -> K-S(0)pi(+)) = (1.3 +/- 1.9 +/- 0.5) x 10(-3), A(CP)(D+ -> (KSK+)-K-0) = (-0.09 +/- 0.65 +/- 0.48) x 10(-3), A(CP)(D+ -> phi pi(+)) = (0.05 +/- 0.42 +/- 0.29) x 10(-3), where the first uncertainties are statistical and the second systematic. They are the most precise measurements of these quantities to date, and are consistent with CP symmetry. A combination with previous LHCb measurements, based on data collected at 7 and 8 TeV, is also reported.
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Observation of the Decay Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu)over-bar(tau). Phys. Rev. Lett., 128(19), 191803–11pp.
Abstract: The first observation of the semileptonic b-baryon decay Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau) with a significance of 6.1 sigma, is reported using a data sample corresponding to 3 fb(-1) of integrated luminosity, collected by the LHCb experiment at center-of-mass energies of 7 and 8 TeV at the LHC. The tau(-) lepton is reconstructed in the hadronic decay to three charged pions. The ratio K = B(Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau))/B(Lambda(0)(b) -> Lambda(+)(c)pi(-)pi(+)pi(-)) is measured to be 2.46 +/- 0.27 +/- 0.40, where the first uncertainty is statistical and the second systematic. The branching fraction B(Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau)) (1.50 +/- 0.16 +/- 0.25 +/- 0.23)% is obtained, where the third uncertainty is from the external branching fraction of the normalization channel Lambda(0)(b) -> Lambda(+)(c)pi(-)pi(+)pi(-). The ratio of semileptonic branching fractions R(Lambda(+)(c)) B(Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau))/B(Lambda(0)(b) -> Lambda(+)(c)mu(-)(nu) over bar (tau)) is derived to be 0.242 +/- 0.026 +/- 0.040 +/- 0.059, where the external branching fraction uncertainty from the channel Lambda(0)(b) -> Lambda(+)(c)mu(-)(nu) over bar (tau) contributes to the last term. This result is in agreement with the standard model prediction.
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Tests of Lepton Universality Using B-0 -> K(S)(0)l(+) l(-) and B+ -> K*(+)l(+)l(-) Decays. Phys. Rev. Lett., 128(19), 191802–15pp.
Abstract: Tests of lepton universality in B-0 -> K(S)(0)l(+)l(-) and B+ -> K*(+)l(+)l(-) decays where l is either an electron or a muon are presented. The differential branching fractions of B-0 -> K(S)(0)e(+)e(-) and B+ -> K*(+)e(+)e(-) decays are measured in intervals of the dilepton invariant mass squared. The measurements are performed using proton-proton collision data recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb(-1). The results are consistent with the standard model and previous tests of lepton universality in related decay modes. The first observation of B-0 -> K(S)(0)e(+)e(-) and B+ -> K*(+)e(+)e(-) decays is reported.
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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2019). Search for Lepton-Universality Violation in B+ -> K(+)l(+)l(-) Decays. Phys. Rev. Lett., 122(19), 191801–13pp.
Abstract: A measurement of the ratio of branching fractions of the decays B+ -> K+mu(+)mu(-) and B+ -> K(+)e(+)e(-) is presented. The proton-proton collision data used correspond to an integrated luminosity of 5.0 fb(-1) recorded with the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV. For the dilepton mass-squared range 1.1 < q(2) < 6.0 GeV2/c(4) the ratio of branching fractions is measured to be R-K = 0.846(-0.054-0.014)(+0.060+0.016), where the first uncertainty is statistical and the second systematic. This is the most precise measurement of R-K to date and is compatible with the standard model at the level of 2.5 standard deviations.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cantero, J., et al. (2023). Observation of Single-Top-Quark Production in Association with a Photon Using the ATLAS Detector. Phys. Rev. Lett., 131(18), 181901–22pp.
Abstract: This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139 fb(-1) of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688 +/- 23(stat)(-71)(+75) (syst) fb, to be compared with the standard model prediction of 515(-42)(+36) fb at next-to-leading order in QCD.
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Belle II Collaboration(Abudinen, F. et al), & Marinas, C. (2021). Search for B+ -> K+nu(nu)over-bar Decays Using an Inclusive Tagging Method at Belle H. Phys. Rev. Lett., 127(18), 181802–10pp.
Abstract: A search for the flavor-changing neutral-current decay B+ -> K+nu(nu) over bar is performed at the Belle II experiment at the SuperKEKB asymmetric energy electron-positron collider. The data sample corresponds to an integrated luminosity of 63 fb(-1) collected at the Upsilon(4S) resonance and a sample of 9 fb(-1) collected at an energy 60 MeV below the resonance. Because the measurable decay signature involves only a single charged kaon, a novel measurement approach is used that exploits not only the properties of the B+ -> K+nu(nu) over bar decay, but also the inclusive properties of the other B meson in the Upsilon(4S) -> B (B) over bar event, to suppress the background from other B meson decays and light-quark pair production. This inclusive tagging approach offers a higher signal efficiency compared to previous searches. No significant signal is observed. An upper limit on the branching fraction of B+ -> K+nu(nu) over bar of 4.1 x 10(-5) is set at the 90% confidence level.
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