XMapTools: a MATLAB©-based program for electron microprobe X-ray image processing and geothermobarometry

XMapTools is a MATLAB©-based graphical user interface program for electron microprobe X-ray image processing, which can be used to estimate the pressure–temperature conditions of crystallization of minerals in metamorphic rocks. This program (available online at http://www.xmaptools.com) provides a method to standardize raw electron microprobe data and includes functions to calculate the oxide weight percent compositions for various minerals. A set of external functions is provided to calculate structural formulae from the standardized analyses as well as to estimate pressure–temperature conditions of crystallization, using empirical and semi-empirical thermobarometers from the literature. Two graphical user interface modules, Chem2D and Triplot3D, are used to plot mineral compositions into binary and ternary diagrams. As an example, the software is used to study a high-pressure Himalayan eclogite sample from the Stak massif in Pakistan. The high-pressure paragenesis consisting of omphacite and garnet has been retrogressed to a symplectitic assemblage of amphibole, plagioclase and clinopyroxene. Mineral compositions corresponding to ~165,000 analyses yield estimates for the eclogitic pressure–temperature retrograde path from 25 kbar to 9 kbar. Corresponding pressure–temperature maps were plotted and used to interpret the link between the equilibrium conditions of crystallization and the symplectitic microstructures. This example illustrates the usefulness of XMapTools for studying variations of the chemical composition of minerals and for retrieving information on metamorphic conditions on a microscale, towards computation of continuous pressure–temperature-and relative time path in zoned metamorphic minerals not affected by post-crystallization diffusion.

Arterial blood pressure during early sepsis and outcome

OBJECTIVE: To evaluate the association between arterial blood pressure (ABP) during the first 24 h and mortality in sepsis. DESIGN: Retrospective cohort study. SETTING: Multidisciplinary intensive care unit (ICU). PATIENTS AND PARTICIPANTS: A total of 274 septic patients. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: Hemodynamic, and laboratory parameters were extracted from a PDMS database. The hourly time integral of ABP drops below clinically relevant systolic arterial pressure (SAP), mean arterial pressure (MAP), and mean perfusion pressure (MPP = MAP - central venous pressure) levels was calculated for the first 24 h after ICU admission and compared with 28-day-mortality. Binary and linear regression models (adjusted for SAPS II as a measure of disease severity), and a receiver operating characteristic (ROC) analysis were applied. The areas under the ROC curve were largest for the hourly time integrals of ABP drops below MAP 60 mmHg (0.779 vs. 0.764 for ABP drops below MAP 55 mmHg; P < or = 0.01) and MPP 45 mmHg. No association between the hourly time integrals of ABP drops below certain SAP levels and mortality was detected. One or more episodes of MAP < 60 mmHg increased the risk of death by 2.96 (CI 95%, 1.06-10.36, P = 0.04). The area under the ROC curve to predict the need for renal replacement therapy was highest for the hourly time integral of ABP drops below MAP 75 mmHg. CONCLUSIONS: A MAP level > or = 60 mmHg may be as safe as higher MAP levels during the first 24 h of ICU therapy in septic patients. A higher MAP may be required to maintain kidney function.

The PLATO 2.0 mission

PLATO 2.0 has recently been selected for ESA’s M3 launch opportunity (2022/24). Providing accurate key planet parameters (radius, mass, density and age) in statistical numbers, it addresses fundamental questions such as: How do planetary systems form and evolve? Are there other systems with planets like ours, including potentially habitable planets? The PLATO 2.0 instrument consists of 34 small aperture telescopes (32 with 25 s readout cadence and 2 with 2.5 s candence) providing a wide field-of-view (2232 deg 2) and a large photometric magnitude range (4–16 mag). It focusses on bright (4–11 mag) stars in wide fields to detect and characterize planets down to Earth-size by photometric transits, whose masses can then be determined by ground-based radial-velocity follow-up measurements. Asteroseismology will be performed for these bright stars to obtain highly accurate stellar parameters, including masses and ages. The combination of bright targets and asteroseismology results in high accuracy for the bulk planet parameters: 2 %, 4–10 % and 10 % for planet radii, masses and ages, respectively. The planned baseline observing strategy includes two long pointings (2–3 years) to detect and bulk characterize planets reaching into the habitable zone (HZ) of solar-like stars and an additional step-and-stare phase to cover in total about 50 % of the sky. PLATO 2.0 will observe up to 1,000,000 stars and detect and characterize hundreds of small planets, and thousands of planets in the Neptune to gas giant regime out to the HZ. It will therefore provide the first large-scale catalogue of bulk characterized planets with accurate radii, masses, mean densities and ages. This catalogue will include terrestrial planets at intermediate orbital distances, where surface temperatures are moderate. Coverage of this parameter range with statistical numbers of bulk characterized planets is unique to PLATO 2.0. The PLATO 2.0 catalogue allows us to e.g.: - complete our knowledge of planet diversity for low-mass objects, - correlate the planet mean density-orbital distance distribution with predictions from planet formation theories,- constrain the influence of planet migration and scattering on the architecture of multiple systems, and - specify how planet and system parameters change with host star characteristics, such as type, metallicity and age. The catalogue will allow us to study planets and planetary systems at different evolutionary phases. It will further provide a census for small, low-mass planets. This will serve to identify objects which retained their primordial hydrogen atmosphere and in general the typical characteristics of planets in such low-mass, low-density range. Planets detected by PLATO 2.0 will orbit bright stars and many of them will be targets for future atmosphere spectroscopy exploring their atmosphere. Furthermore, the mission has the potential to detect exomoons, planetary rings, binary and Trojan planets. The planetary science possible with PLATO 2.0 is complemented by its impact on stellar and galactic science via asteroseismology as well as light curves of all kinds of variable stars, together with observations of stellar clusters of different ages. This will allow us to improve stellar models and study stellar activity. A large number of well-known ages from red giant stars will probe the structure and evolution of our Galaxy. Asteroseismic ages of bright stars for different phases of stellar evolution allow calibrating stellar age-rotation relationships. Together with the results of ESA’s Gaia mission, the results of PLATO 2.0 will provide a huge legacy to planetary, stellar and galactic science.

K(L) --> pi0 e+ e- and K(L) --> pi0 mu+ mu-: A binary star on the stage of flavor physics

A systematic analysis of New Physics impacts on the rare decays KL→π0ell+ell- is performed. Thanks to their different sensitivities to flavor-changing local effective interactions, these two modes could provide valuable information on the nature of the possible New Physics at play. In particular, a combined measurement of both modes could disentangle scalar/pseudoscalar from vector or axial-vector contributions. For the latter, model-independent bounds are derived. Finally, the KL→π0μ+μ- forward-backward CP-asymmetry is considered, and shown to give interesting complementary information.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.