Antarctic iron meteorites: An unexpectedly high proportion of falls of unusual interest

The inhabited and explored areas of Earth have contributed 725 iron meteorites, accounting for 28% of the 2611 authenticated meteorites known of all types. Observed fall statistics give a much different view of relative abundance. The 42 historic iron meteorite falls spanning 230 years suggests a frequency of one fall per 5.6 years and represents only 4.9% of the total 853 known falls. Antarctic iron meteorite recoveries offer promise of providing a new perspective on the influx problem. At least 42 iron meteorite specimens were found during the last 25 years by various field teams working in Antarctica. Most of these specimens were not described in detail, but the available data indicates that 21 separate falls are represented, 50% of the number of recovered specimens. Twelve of the 21 falls were both structurally classified and placed into chemical groups. They are listed in order of increasing structural complexity and/or Ni content

A Neural Attention Model for Categorizing Patient Safety Events

Medical errors are leading causes of death in the US and as such, prevention of these errors is paramount to promoting health care. Patient Safety Event reports are narratives describing potential adverse events to the patients and are important in identifying and preventing medical errors. We present a neural network architecture for identifying the type of safety events which is the first step in understanding these narratives. Our proposed model is based on a soft neural attention model to improve the effectiveness of encoding long sequences. Empirical results on two large-scale real-world datasets of patient safety reports demonstrate the effectiveness of our method with significant improvements over existing methods.Comment: ECIR 201

Learning a Static Analyzer from Data

To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under analysis. While important, manually addressing these challenges is difficult for at least two reasons: (i) the effects on the overall analysis can be non-trivial, and (ii) as the size and complexity of modern libraries increase, so is the number of cases the analysis must handle. In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs. Our method consists of two ingredients: (i) a synthesis algorithm capable of learning a candidate analyzer from a given dataset, and (ii) a counter-example guided learning procedure which generates new programs beyond those in the initial dataset, critical for discovering corner cases and ensuring the learned analysis generalizes to unseen programs. We implemented and instantiated our approach to the task of learning JavaScript static analysis rules for a subset of points-to analysis and for allocation sites analysis. These are challenging yet important problems that have received significant research attention. We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers

Meningeal carcinomatosis diagnosed during stroke evaluation in the emergency department

A 70-year-old female presented to the emergency department with a 3-day history of intermittent dysphasia and right facial droop. Computed tomography (CT) and magnetic resonance imaging (MRI) were obtained, and the patient was found to have meningeal carcinomatosis, also known as leptomeningeal metastases. Meningeal carcinomatosis is a rare metastatic complication of some solid tumors and hematopoietic neoplasms, and has a median survival rate of 2.4 months. The role of the emergency physician is to appropriately diagnose this condition, treat emergent side effects, provide symptomatic relief, and ensure multi-disciplinary management

Automatic Abstraction for Congruences

One approach to verifying bit-twiddling algorithms is to derive invariants between the bits that constitute the variables of a program. Such invariants can often be described with systems of congruences where in each equation $\vec{c} \cdot \vec{x} = d \mod m$, (unknown variable m)$is a power of two,$\vec{c}$is a vector of integer coefficients, and$\vec{x}$ is a vector of propositional variables (bits). Because of the low-level nature of these invariants and the large number of bits that are involved, it is important that the transfer functions can be derived automatically. We address this problem, showing how an analysis for bit-level congruence relationships can be decoupled into two parts: (1) a SAT-based abstraction (compilation) step which can be automated, and (2) an interpretation step that requires no SAT-solving. We exploit triangular matrix forms to derive transfer functions efficiently, even in the presence of large numbers of bits. Finally we propose program transformations that improve the analysis results

The effect of a home-based, gamified stability skills intervention on 4-5-year-old children's physical and cognitive outcomes: A pilot study

Background: Stability skills (e.g., static/dynamic balance) are a precursor for other movement skill development (e.g., jumping, catching). However, young children consistently demonstrate low stability and movement skill ability. There is therefore a need to develop effective strategies to improve stability skills in early childhood. Aim: To pilot the effect of a home-based gamified stability skills intervention on 4-5-year-old children's physical skills, self-perceptions and cognitions. Methods: One-hundred-and-eleven 4-5-year-old children participated from three schools. Two schools were allocated into the intervention group (n = 66 children, 33 boys) and one to the control group (n = 45 children, 25 boys). Stability, fundamental movement skills, perceived motor competence, and cognition were assessed at baseline and at post-intervention. The intervention group was given a booklet detailing the 12-week gamified stability skill intervention. The control group participated in their usual weekly activities. Results: A series of ANCOVAs controlling for baseline values demonstrated significantly higher stability skills (F(1,93) = 24.79, p < 0.001, partial η2 = 0.212), fundamental movement skills (F(1,94) = 15.5, p = < 0.001, partial η2 = 0.139), perceived motor competence (F(1,96) = 5.48, p = 0.021, partial η2 = 0.054) and cognition (F(1,96) = 15.5, p = < 0.001, partial η2 = 0.139) at post-test for the intervention versus control groups. Discussion: This study demonstrates that a home-based, gamified, stability skills intervention enhances stability skills, fundamental movement skills, perceived motor competence and cognition in children aged 4-5-years old

Spin current in ferromagnet/insulator/superconductor junctions

A theory of spin polarized tunneling spectroscopy based on a scattering theory is given for tunneling junctions between ferromagnets and d-wave superconductors. The spin filtering effect of an exchange field in the insulator is also treated. We clarify that the properties of the Andreev reflection are largely modified due to a presence of an exchange field in the ferromagnets, and consequently the Andreev reflected quasiparticle shows an evanescent-wave behavior depending on the injection angle of the quasiparticle. Conductance formulas for the spin current as well as the charge current are given as a function of the applied voltage and the spin-polarization in the ferromagnet for arbitrary barrier heights. It is shown that the surface bound states do not contribute to the spin current and that the zero-bias conductance peak expected for a d-wave superconductor splits into two peaks under the influence of the exchange interaction in the insulator.Comment: 14 pages, 11 figure

Spin Injection and Detection in Magnetic Nanostructures

We study theoretically the spin transport in a nonmagnetic metal connected to ferromagnetic injector and detector electrodes. We derive a general expression for the spin accumulation signal which covers from the metallic to the tunneling regime. This enables us to discuss recent controversy on spin injection and detection experiments. Extending the result to a superconducting device, we find that the spin accumulation signal is strongly enhanced by opening of the superconducting gap since a gapped superconductor is a low carrier system for spin transport but not for charge. The enhancement is also expected in semiconductor devices.Comment: 4 pages, 3 figure

Observation of anomalous decoherence effect in a quantum bath at room temperature

Decoherence of quantum objects is critical to modern quantum sciences and technologies. It is generally believed that stronger noises cause faster decoherence. Strikingly, recent theoretical research discovers the opposite case for spins in quantum baths. Here we report experimental observation of the anomalous decoherence effect for the electron spin-1 of a nitrogen-vacancy centre in high-purity diamond at room temperature. We demonstrate that under dynamical decoupling, the double-transition can have longer coherence time than the single-transition, even though the former couples to the nuclear spin bath as twice strongly as the latter does. The excellent agreement between the experimental and the theoretical results confirms the controllability of the weakly coupled nuclear spins in the bath, which is useful in quantum information processing and quantum metrology.Comment: 22 pages, related paper at http://arxiv.org/abs/1102.557

The Composition Gradient in M101 Revisited. II. Electron Temperatures and Implications for the Nebular Abundance Scale

(Abridged) We use high S/N spectra of 20 HII regions in the giant spiral galaxy M101 to derive electron temperatures for the HII regions and robust metal abundances over radii R = 0.19-1.25 Ro (6-41 kpc). We compare the consistency of electron temperatures measured from the [O III]4363, [N II]5755, [S III]6312, and [O II]7325 auroral lines. Temperatures from [O III], [S III], and [N II] are correlated with relative offsets that are consistent with expectations from nebular photoionization models. However, the temperatures derived from the [O II]7325 line show a large scatter and are nearly uncorrelated with temperatures derived from other ions. Our derived oxygen abundances O/H are well fitted by an exponential distribution over six disk scale lengths, from approximately 1.3 solar in the center to 1/15 solar in the outermost region studied (for solar 12 + log (O/H)=8.7). We measure significant radial gradients in N/O and He/H abundance ratios, but relatively constant S/O and Ar/O. Our abundances are systematically lower by 0.2-0.5 dex than those derived from the most widely used strong-line "empirical" abundance indicators. We suspect that most of the disagreement with the strong-line abundances arises from uncertainties in the nebular models that are used to calibrate the "empirical" scale, and that strong-line abundances derived for HII regions and emission-line galaxies are as much as a factor of two higher than the actual oxygen abundances. However other explanations, such as the effects of temperature fluctuations on the auroral line based abundances cannot be completely ruled out. These results point to the need for direct abundance determinations of a larger sample of extragalactic HII regions, especially for objects more metal-rich than solar.Comment: 50 pages, 14 figures, 8 tables. Accepted by Ap