Scattering matrices and expansion coefficients of Martian analogue palagonite particles

We present measurements of ratios of elements of the scattering matrix of Martian analogue palagonite particles for scattering angles ranging from 3 to 174 degrees and a wavelength of 632.8 nm. To facilitate the use of these measurements in radiative transfer calculations we have devised a method that enables us to obtain, from these measurements, a normalized synthetic scattering matrix covering the complete scattering angle range from 0 to 180 degrees. Our method is based on employing the coefficients of the expansions of scattering matrix elements into generalized spherical functions. The synthetic scattering matrix elements and/or the expansion coefficients obtained in this way, can be used to include multiple scattering by these irregularly shaped particles in (polarized) radiative transfer calculations, such as calculations of sunlight that is scattered in the dusty Martian atmosphere.Comment: 34 pages 7 figures 1 tabl

Explaining two circumnuclear star forming rings in NGC5248

The distribution of gas in the central kiloparsec of a galaxy has a dynamically rapid evolution. Nonaxisymmetries in the gravitational potential of the galactic disk, such as a large scale stellar bar or spiral, can lead to significant radial motion of gaseous material from larger radii to the central region. The large influx of gas and the subsequent star formation keep the central region constantly changing. However, the ability of gas to reach the nucleus proper to fuel an AGN phase is not guaranteed. Gas inflow can be halted at a circumnuclear star forming ring several hundred parsec away. The nearby galaxy NGC5248 is especially interesting in this sense since it is said to host 2 circumnuclear star forming rings at 100pc and 370pc from its quiescent nucleus. Here we present new subarcsecond PdBI+30m CO(2-1) emission line observations of the central region. For the first time the molecular gas distribution at the smallest stellar ring is resolved into a gas ring, consistent with the presence of a quiescent nucleus. However, the molecular gas shows no ring structure at the larger ring. We combine analyses of the gaseous and stellar content in the central kiloparsec of this galaxy to understand the gas distribution and dynamics of this star forming central region. We discuss the probability of two scenarios leading to the current observations, given our full understanding of this system, and discuss whether there are really two circumnuclear star forming rings in this galaxy.Comment: Accepted for publication in A&A, 14pages + long tabl

Super Learner

Previous articles (van der Laan and Dudoit (2003); van der Laan et al. (2006); Sinisi et al. (2007)) advertised and theoretically validated the use of cross-validation to select among many candidate estimators to compute a so called super learner which outperforms any of the given candidate estimators. The theoretical basis was provided for this super learner based on oracle results for the cross-validation selector (e.g., van der Laan and Dudoit (2003); van der Laan et al. (2006)) and in Sinisi et al. (2007). In addition, these papers contained a practical demonstration of the adaptivity of this so called super learner in the context of prediction of the fitness of the HIV virus as a function of its mutations. This article proposes a fast algorithm for constructing a super learner in prediction which uses V-fold cross-validation to select a functional form of an initial set of candidate predictors according to a parametric or semi-parametric model, or possibly, data adaptively. The paper contains a proof that the resulting super learner performs asymptotically as well as the oracle selector among the continuum of estimators defined by the (semi-)parametric functional forms of the initial set of candidate estimators. This approach also yields a new class of cross-validation methods to select among a family of candidate estimators by formulating the minimization of the cross-validated risk over the family of candidate estimators as a new least squares regression problem which itself can be carried out with any type of parametric or nonparametric regression methodology (e.g. using cross-validation itself), thereby preventing over-fitting of the cross-validated risk. Simulations and data analysis suggest this new proposed super learner superior to competing methods. This approach for construction of a super learner generalizes to any parameter which can be defined as a minimizer of a loss function

Strain dependence of the Mn anisotropy in ferromagnetic semiconductors observed by x-ray magnetic circular dichroism

We demonstrate sensitivity of the Mn 3d valence states to strain in the ferromagnetic semiconductors (Ga,Mn)As and (Al,Ga,Mn)As, using x-ray magnetic circular dichroism (XMCD). The spectral shape of the Mn $L_{2,3}$ XMCD is dependent on the orientation of the magnetization, and features with cubic and uniaxial dependence are distinguished. Reversing the strain reverses the sign of the uniaxial anisotropy of the Mn $L_3$ pre-peak which is ascribed to transitions from the Mn 2p core level to p-d hybridized valence band hole states. With increasing carrier localization, the $L_3$ pre-peak intensity increases, indicating an increasing 3d character of the hybridized holes.Comment: 4 pages plus 2 figures, accepted for publication in Physical Review

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

Long range antiferromagnetic order of formally nonmagnetic Eu3 Van Vleck ions observed in multiferroic Eu1 xYxMnO3

We report on resonant magnetic x ray scattering and absorption spectroscopy studies of exchange coupled antiferromagnetic ordering of Eu3 magnetic moments in multiferroic Eu1 amp; 8722;xYxMnO3 in the absence of an external magnetic field. The observed resonant spectrum is characteristic of a magnetically ordered 7F1 state that mirrors the Mn magnetic ordering, due to exchange coupling between the Eu 4f and Mn 3d spins. Here, we observe long range magnetic order generated by exchange coupling of magnetic moments of formally nonmagnetic Van Vleck ions, which is a step further towards the realization of exotic phases induced by exchange coupling in systems entirely composed of non magnetic ion

Meta-analysis of 701 published cases of sinonasal neuroendocrine carcinoma:The importance of differentiation grade in determining treatment strategy

AbstractThe aim of this meta-analysis was to provide treatment guidelines for sinonasal neuroendocrine carcinoma (SNC) by combining all available data in the literature.A literature search for all studies concerning SNC was performed against the MEDLINE and EMBASE databases. Available clinical data was normalized, pooled, and statistically analyzed.A total of 701 cases of SNC were available for analysis, comprising 127 well or moderately differentiated sinonasal neuroendocrine carcinomas (SNEC), 459 sinonasal undifferentiated carcinoma (SNUC) and 115 sinonasal small cell carcinoma (SmCC). Tumor type was the most important predictor of survival, with a 5-year disease-specific survival (DSS) of 70.2% for SNEC, 35.9% for SNUC and 46.1% for SmCC. Tumor stage on presentation was of limited value in predicting survival or response to treatment. Overall, the application of surgery yielded significantly better results (5-year DSS 52.2% versus 30.1%, p<0.001). In SNUC, radiotherapy was a beneficial supplement to surgery (5-year DSS 54.7% versus 15.7%, p=0.027), while radiotherapy as monotherapy performed poorly (5-year DSS 17.9%). Chemotherapy did not appear to contribute to survival.Based on these findings, we can conclude that the most important predictors of survival in SNC are differentiation grade and the associated choice of treatment modality. In contrast to other head and neck cancers, tumor staging appears of limited value in predicting survival or deciding on a treatment strategy. Surgery should be the cornerstone of treatment, supplemented by radiotherapy in poorly differentiated subtypes (SNUC, SmCC). Chemotherapy does not appear to contribute to survival

Curie Temperature Enhancement and Cation Ordering in Titanomagnetites: Evidence From Magnetic Properties, XMCD, and Mössbauer Spectroscopy

Previous work has documented time‐ and temperature‐dependent variations in the Curie temperature (Tc) of natural titanomagnetites, independent of any changes in sample composition. To better understand the atomic‐scale processes responsible for these variations, we have generated a set of synthetic titanomagnetites with a range of Ti, Mg, and Al substitution; a subset of samples was additionally oxidized at low temperature (150 °C). Samples were annealed at temperatures between 325 and 400 °C for up to 1,000 hr and characterized in terms of magnetic properties; Fe valence and site occupancy were constrained by X‐ray magnetic circular dichroism (XMCD) and Mössbauer spectroscopy. Annealing results in large (up to ~100 °C) changes in Tc, but Mössbauer, XMCD, and saturation magnetization data all demonstrate that intersite reordering of Fe2+/Fe3+ does not play a role in the observed Tc changes. Rather, the data are consistent with vacancy‐enhanced nanoscale chemical clustering within the octahedral sublattice. This clustering may be a precursor to chemical unmixing at temperatures below the titanomagnetite binary solvus. Additionally, the data strongly support a model where cation vacancies are predominantly situated on octahedral sites, Mg substitution is largely accommodated on octahedral sites, and Al substitution is split between the two sites