Local Environment of Ferromagnetically Ordered Mn in Epitaxial InMnAs

The magnetic properties of the ferromagnetic semiconductor In0.98Mn0.02As were characterized by x-ray absorption spectroscopy and x-ray magnetic circular dichroism. The Mn exhibits an atomic-like L2,3 absorption spectrum that indicates that the 3d states are highly localized. In addition, a large dichroism at the Mn L2,3 edge was observed from 5-300 K at an applied field of 2T. A calculated spectrum assuming atomic Mn2+ yields the best agreement with the experimental InMnAs spectrum. A comparison of the dichroism spectra of MnAs and InMnAs show clear differences suggesting that the ferromagnetism observed in InMnAs is not due to hexagonal MnAs clusters. The temperature dependence of the dichroism indicates the presence of two ferromagnetic species, one with a transition temperature of 30 K and another with a transition temperature in excess of 300 K. The dichroism spectra are consistent with the assignment of the low temperature species to random substitutional Mn and the high temperature species to Mn near-neighbor pairs.Comment: 10 pages, 4 figures, accepted by Applied Physics Letter

The Cross-Validated Adaptive Epsilon-Net Estimator

Suppose that we observe a sample of independent and identically distributed realizations of a random variable. Assume that the parameter of interest can be defined as the minimizer, over a suitably defined parameter space, of the expectation (with respect to the distribution of the random variable) of a particular (loss) function of a candidate parameter value and the random variable. Examples of commonly used loss functions are the squared error loss function in regression and the negative log-density loss function in density estimation. Minimizing the empirical risk (i.e., the empirical mean of the loss function) over the entire parameter space typically results in ill-defined or too variable estimators of the parameter of interest (i.e., the risk minimizer for the true data generating distribution). In this article, we propose a cross-validated epsilon-net estimation methodology that covers a broad class of estimation problems, including multivariate outcome prediction and multivariate density estimation. An epsilon-net sieve of a subspace of the parameter space is defined as a collection of finite sets of points, the epsilon-nets indexed by epsilon, which approximate the subspace up till a resolution of epsilon. Given a collection of subspaces of the parameter space, one constructs an epsilon-net sieve for each of the subspaces. For each choice of subspace and each value of the resolution epsilon, one defines a candidate estimator as the minimizer of the empirical risk over the corresponding epsilon-net. The cross-validated epsilon-net estimator is then defined as the candidate estimator corresponding to the choice of subspace and epsilon-value minimizing the cross-validated empirical risk. We derive a finite sample inequality which proves that the proposed estimator achieves the adaptive optimal minimax rate of convergence, where the adaptivity is achieved by considering epsilon-net sieves for various subspaces. We also address the implementation of the cross-validated epsilon-net estimation procedure. In the context of a linear regression model, we present results of a preliminary simulation study comparing the cross-validated epsilon-net estimator to the cross-validated L^1-penalized least squares estimator (LASSO) and the least angle regression estimator (LARS). Finally, we discuss generalizations of the proposed estimation methodology to censored data structures

Effect of breastfeeding on gastrointestinal infection in infants: A targeted maximum likelihood approach for clustered longitudinal data

The PROmotion of Breastfeeding Intervention Trial (PROBIT) cluster-randomized a program encouraging breastfeeding to new mothers in hospital centers. The original studies indicated that this intervention successfully increased duration of breastfeeding and lowered rates of gastrointestinal tract infections in newborns. Additional scientific and popular interest lies in determining the causal effect of longer breastfeeding on gastrointestinal infection. In this study, we estimate the expected infection count under various lengths of breastfeeding in order to estimate the effect of breastfeeding duration on infection. Due to the presence of baseline and time-dependent confounding, specialized "causal" estimation methods are required. We demonstrate the double-robust method of Targeted Maximum Likelihood Estimation (TMLE) in the context of this application and review some related methods and the adjustments required to account for clustering. We compare TMLE (implemented both parametrically and using a data-adaptive algorithm) to other causal methods for this example. In addition, we conduct a simulation study to determine (1) the effectiveness of controlling for clustering indicators when cluster-specific confounders are unmeasured and (2) the importance of using data-adaptive TMLE.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS727 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Semiparametric theory and empirical processes in causal inference

In this paper we review important aspects of semiparametric theory and empirical processes that arise in causal inference problems. We begin with a brief introduction to the general problem of causal inference, and go on to discuss estimation and inference for causal effects under semiparametric models, which allow parts of the data-generating process to be unrestricted if they are not of particular interest (i.e., nuisance functions). These models are very useful in causal problems because the outcome process is often complex and difficult to model, and there may only be information available about the treatment process (at best). Semiparametric theory gives a framework for benchmarking efficiency and constructing estimators in such settings. In the second part of the paper we discuss empirical process theory, which provides powerful tools for understanding the asymptotic behavior of semiparametric estimators that depend on flexible nonparametric estimators of nuisance functions. These tools are crucial for incorporating machine learning and other modern methods into causal inference analyses. We conclude by examining related extensions and future directions for work in semiparametric causal inference

Boninite and Harzburgite from Leg 125 (Bonin-Mariana Forearc): A Case Study of Magma Genesis during the Initial Stages of Subduction

Holes drilled into the volcanic and ultrabasic basement of the Izu-Ogasawara and Mariana forearc terranes during Leg 125 provide data on some of the earliest lithosphere created after the start of Eocene subduction in the Western Pacific. The volcanic basement contains three boninite series and one tholeiite series. (1) Eocene low-Ca boninite and low-Ca bronzite andesite pillow lavas and dikes dominate the lowermost part of the deep crustal section through the outer-arc high at Site 786. (2) Eocene intermediate-Ca boninite and its fractionation products (bronzite andesite, andesite, dacite, and rhyolite) make up the main part of the boninitic edifice at Site 786. (3) Early Oligocene intermediate-Ca to high-Ca boninite sills or dikes intrude the edifice and perhaps feed an uppermost breccia unit at Site 786. (4) Eocene or Early Oligocene tholeiitic andesite, dacite, and rhyolite form the uppermost part of the outer-arc high at Site 782. All four groups can be explained by remelting above a subduction zone of oceanic mantle lithosphere that has been depleted by its previous episode of partial melting at an ocean ridge. We estimate that the average boninite source had lost 10-15 wt% of melt at the ridge before undergoing further melting (5-10%) shortly after subduction started. The composition of the harzburgite (<2% clinopyroxene, Fo content of about 92%) indicates that it underwent a total of about 25% melting with respect to a fertile MORB mantle. The low concentration of Nb in the boninite indicates that the oceanic lithosphere prior to subduction was not enriched by any asthenospheric (OIB) component. The subduction component is characterized by (1) high Zr and Hf contents relative to Sm, Ti, Y, and middle-heavy REE, (2) light REE-enrichment, (3) low contents of Nb and Ta relative to Th, Rb, or La, (4) high contents of Na and Al, and (5) Pb isotopes on the Northern Hemisphere Reference Line. This component is unlike any subduction component from active arc volcanoes in the Izu-Mariana region or elsewhere. Modeling suggests that these characteristics fit a trondhjemitic melt from slab fusion in amphibolite facies. The resulting metasomatized mantle may have contained about 0.15 wt% water. The overall melting regime is constrained by experimental data to shallow depths and high temperatures (1250°C and 1.5 kb for an average boninite) of boninite segregation. We thus envisage that boninites were generated by decompression melting of a diapir of metasomatized residual MORB mantle leaving the harzburgites as the uppermost, most depleted residue from this second stage of melting. Thermal constraints require that both subducted lithosphere and overlying oceanic lithosphere of the mantle wedge be very young at the time of boninite genesis. This conclusion is consistent with models in which an active transform fault offsetting two ridge axes is placed under compression or transpression following the Eocene plate reorganization in the Pacific. Comparison between Leg 125 boninites and boninites and related rocks elsewhere in the Western Pacific highlights large regional differences in petrogenesis in terms of mantle mineralogy, degree of partial melting, composition of subduction components, and the nature of pre-subduction lithosphere. It is likely that, on a regional scale, the initiation of subduction involved subducted crust and lithospheric mantle wedge of a range of ages and compositions, as might be expected in this type of tectonic setting

Spin and orbital moments of ultra-thin Fe films on various semiconductor surfaces

The magnetic moments of ultrathin Fe films on three different III-V semiconductor substrates, namely GaAs, InAs and In0.2Ga0.8As have been measured with X-ray magnetic circular dichroism at room temperature to assess their relative merits as combinations suitable for next-generation spintronic devices. The results revealed rather similar spin moments and orbital moments for the three systems, suggesting the relationship between film and semiconductor lattice parameters to be less critical to magnetic moments than magnetic anisotropy

Estimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models

In this paper we review an approach to estimating the causal effect of a time-varying treatment on time to some event of interest. This approach is designed for the situation where the treatment may have been repeatedly adapted to patient characteristics, which themselves may also be time-dependent. In this situation the effect of the treatment cannot simply be estimated by conditioning on the patient characteristics, as these may themselves be indicators of the treatment effect. This so-called time-dependent confounding is typical in observational studies. We discuss a new class of failure time models, structural nested failure time models, which can be used to estimate the causal effect of a time-varying treatment, and present methods for estimating and testing the parameters of these models

In Vitro Susceptibility of Mycobacterium tuberculosis to Amikacin, Kanamycin, and Capreomycin

Amikacin, kanamycin and capreomycin are listed among the most important 2nd line drugs for multidrug resistant tuberculosis. Although amikacin and kanamycin are administered in the same dose and show the same pharmacokinetics, they have different WHO breakpoints suggesting that the two drugs have a different minimal inhibitory concentrations (MIC). The aim of this paper was to investigate possible differences in MIC between the aminoglycosides and capreomycin.Using the direct concentration method, a concentration range of amikacin, kanamycin and capreomycin (0.25, 0.50, 1.0, 2.0, 4.0, 8.0, 16.0, 32.0 and 64.0 mg/L) was tested against 57 clinical Mycobacterium tuberculosis strains. The 7H10 agar plates were examined for mycobacterial growth after 14 days.At 2 mg/L, 48 strains (84%) were inhibited by amikacin and only five strains (9%) were inhibited by kanamycin (p < 0.05, Wilcoxon Signed Rank Test). The median MICs of amikacin, kanamycin and capreomycin were 2, 4 and 8 mg/L, respectively. No difference was observed between multidrug resistant and fully susceptible strains in the MIC-distribution of amikacin, kanamycin and capreomycin.The results indicate that amikacin is more active against M. tuberculosis than kanamycin and capreomycin in the absolute concentration method. The impact of this difference on clinical outcome in daily practice requires a prospective study including pharmacokinetic and pharmacodynamics evaluations