Singularity-free Next-to-leading Order ΔS=1\Delta S= 1 Renormalization Group Evolution and ϵK′/ϵK\epsilon_{K}^{\prime}/\epsilon_{K} in the Standard Model and Beyond

The standard analytic solution of the renormalization group (RG) evolution for the $\Delta S = 1$ Wilson coefficients involves several singularities, which complicate analytic solutions. In this paper we derive a singularity-free solution of the next-to-leading order (NLO) RG equations, which greatly facilitates the calculation of $\epsilon_K^{\prime}$, the measure of direct $CP$ violation in $K\to \pi\pi$ decays. Using our new RG evolution and the latest lattice results for the hadronic matrix elements, we calculate the ratio $\epsilon_{K}^{\prime}/\epsilon_{K}$ (with $\epsilon_{K}$ quantifying indirect $CP$ violation) in the Standard Model (SM) at NLO to $\epsilon_{K}^{\prime}/\epsilon_{K} = (1.06 \pm 5.07) \times 10^{-4}$, which is $2.8\,\sigma$ below the experimental value. We also present the evolution matrix in the high-energy regime for calculations of new physics contributions and derive easy-to-use approximate formulae. We find that the RG amplification of new-physics contributions to Wilson coefficients of the electroweak penguin operators is further enhanced by the NLO corrections: If the new contribution is generated at the scale of 1-10 TeV, the RG evolution between the new-physics scale and the electroweak scale enhances these coefficients by 50-100 %. Our solution contains a term of order $\alpha_{EM}^2/\alpha_s^2$, which is numerically unimportant for the SM case but should be included in studies of high-scale new-physics.Comment: 42 pages, 2 figures, 6 tables; formulae corrected, numerical results almost unchanged, to be published in JHE

Spatial Interpolation of Air Quality Data with Multidimensional Gaussian Processes

The central question of this paper is whether interpolation techniques applied to a distributed sensor network can indeed provide more information than using the constant background of an urban reference station to measure air pollution. We compare different interpolation techniques based on temporal-spatial machine learning in terms of their applicability for correctly predicting personal exposure. Using a dataset of stationary low-cost sensors, we estimate exposure on a route through the city and compare it to mobile measurements. The results show that while different machine learning-based interpolation methods yield quite different results, validation of machine learning-based approaches is still challenging

Recent progress on CP violation in K→ππ decays in the SM and a supersymmetric solution

Using the recent first lattice results of the RBC-UKQCD collaboration for K→ππ decays, we perform a phenomenological analysis of ϵ′K/ϵK and find a discrepancy between SM prediction and experiments by ∼3σ. We discuss an explanation by new physics. The well-understood value of ϵK, which quantifies indirect CP violation, however, typically prevents large new physics contributions to ϵ′K/ϵK. In this talk, we show a solution of the ϵ′K/ϵK discrepancy in the Minimal Supersymmetric Standard Model with squark masses above 3 TeV without fine-tuning of CP phases. In this solution, the Trojan penguin diagram gives large isospin-breaking contributions which enhance ϵ′K, while the contribution to ϵK is suppressed thanks to the Majorana nature of gluinos

Adaptives luftqualitätsgewichtetes Fahrradrouting mittels Land-use Regression auf Basis offener Daten

Luftschadstoffen ausgesetzt zu sein hat langfristige negative gesundheitliche Folgen, denen besonders Fahrradfahrer im urbanen Raum ausgesetzt sind. Dabei gibt es wahrscheinlich keine unschädliche Dosis: weniger ist immer besser. Diese Arbeit zeigt, dass luftqualitätsgewichtete Fahrradrouten die persönliche Exposition gemäß dem Regressionsmodell deutlich reduzieren können, wobei die errechneten Umwege zumeist nur minimal sind. Auf Basis offener Daten wird ein neuronales Netzwerk zur Schätzung der Luftqualität trainiert. Dabei werden PM10-Daten aus mobilen Messungen als Indikator der Luftqualität verwendet. Das entstehende Land-Use-Regression-Modell bezieht dabei sowohl zeitliche als auch räumliche Features mit ein. Anschließend wird dieses Modell verwendet, um luftqualitätsgewichtete Routen zu berechnen. Dabei wird gezeigt, wie ein solches feingranulare Modell im Routing verwendet werden kann. Anhand von zufällig gewählten Start/Ziel Paaren werden die luftqualitätsgewichteten Routen mit der jeweils kürzesten Strecke verglichen

A grand-unified Nelson–Barr model

We argue that the Nelson–Barr solution to the Strong CP Problem can be naturally realized in an E₆ grand-unified theory. The chiral SM fermions reside in three generations of E₆ fundamentals together with heavy vectorlike down quarks, leptons doublets and right-handed neutrinos. CP is imposed on the Lagrangian and broken only spontaneously at high scales, leading to a mixing between chiral and vectorlike fields that allows to solve the Strong CP Problem through the Nelson–Barr mechanism. The main benefit of the E₆ GUT structure is the predictivity in the SM fermion sector, and a perfect fit to all SM observables can be obtained despite being over-constrained. Definite predictions are made for the neutrino sector, with a Dirac CP phase that is correlated to the CKM phase, allowing to test this model in the near future

How do pediatric anesthesiologists define intraoperative hypotension?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75736/1/j.1460-9592.2009.03140.x.pd