Exclusion of Stellar Companions to Exoplanet Host Stars

Given the frequency of stellar multiplicity in the solar neighborhood, it is important to study the impacts this can have on exoplanet properties and orbital dynamics. There have been numerous imaging survey projects established to detect possible low-mass stellar companions to exoplanet host stars. Here we provide the results from a systematic speckle imaging survey of known exoplanet host stars. In total, 71 stars were observed at 692~nm and 880~nm bands using the Differential Speckle Survey Instrument (DSSI) at the Gemini-North Observatory. Our results show that all but 2 of the stars included in this sample have no evidence of stellar companions with luminosities down to the detection and projected separation limits of our instrumentation. The mass-luminosity relationship is used to estimate the maximum mass a stellar companion can have without being detected. These results are used to discuss the potential for further radial velocity follow-up and interpretation of companion signals.Comment: 11 pages, 4 figures, 3 tables, accepted for publication in A

Gender and ethnic differences in chronic myelogenous leukemia prognosis and treatment response: a single-institution retrospective study

<p>Abstract</p> <p>Background</p> <p>In the last decade the importance of ethnicity, socio-economic and gender differences in relation to disease incidence, diagnosis, and prognosis has been realized. Differences in these areas have become a major health policy focus in the United States. Our study was undertaken to examine the demographic and clinical features of chronic myelogenous leukemia (CML) patients presenting initially at the LAC+USC Medical Center, which serves an ethnically diverse population.</p> <p>Results</p> <p>Patients were evenly split by gender, overwhelmingly Hispanic (60.9%), and quite young (median age 39, range 17–65) compared with previously reported CML patient populations. Previous CML studies identified significant anemia (Hgb <12 g/dl), significant thrombocytosis (platelets >450 × 10⁹/l), and significant leukocytosis (WBC >50 × 10⁹/l) as significant adverse pretreatment prognostic factors. Using these indicators, in addition to the validated Hasford and Sokal scores, patients were stratified and analyzed via gender and ethnicity. A significantly greater proportion of women presented with significant anemia (p = 0.019, Fisher's exact test) and significant thrombocytosis (p = 0.041, Fisher's exact test) compared to men, although no differences were found in risk stratification or treatment response. MCV values for women were significantly (p = 0.02, 2-sample t-test) lower than those for men, suggesting iron deficiency anemia. Focusing on ethnicity, Hispanics as a whole had significantly lower Hasford risk stratification (p = 0.046, Fisher's exact test), and significantly greater likelihood (p = 0.016, Fisher's exact test) of achieving 3-month complete haematological remission (CHR) compared with non-Hispanics at LAC+USC Medical Center, though differences in treatment outcome were no longer significant with analysis limited to patients treated with first-line imatinib.</p> <p>Conclusion</p> <p>Female CML patients at LAC+USC Medical Center present with more significant adverse pre-treatment prognostic factors compared to men, but achieve comparable outcomes. Hispanic patients present with lower risk profile CML and achieve better treatment responses compared to non-Hispanic patients as a whole; these ethnic differences are no longer significant when statistical analysis is limited to patients given imatinib as first-line therapy. Our patients achieve response rates inferior to those of large-scale national studies. This constellation of findings has not been reported in previous studies, and is likely reflective of a unique patient population.</p

A Comparison of Spectroscopic versus Imaging Techniques for Detecting Close Companions to Kepler Objects of Interest

(Abbreviated) Kepler planet candidates require both spectroscopic and imaging follow-up observations to rule out false positives and detect blended stars. [...] In this paper, we examine a sample of 11 Kepler host stars with companions detected by two techniques -- near-infrared adaptive optics and/or optical speckle interferometry imaging, and a new spectroscopic deblending method. We compare the companion Teff and flux ratios (F_B/F_A, where A is the primary and B is the companion) derived from each technique, and find no cases where both companion parameters agree within 1sigma errors. In 3/11 cases the companion Teff values agree within 1sigma errors, and in 2/11 cases the companion F_B/F_A values agree within 1sigma errors. Examining each Kepler system individually considering multiple avenues (isochrone mapping, contrast curves, probability of being bound), we suggest two cases for which the techniques most likely agree in their companion detections (detect the same companion star). Overall, our results support the advantage the spectroscopic deblending technique has for finding very close-in companions ($\theta \lesssim$0.02-0.05") that are not easily detectable with imaging. However, we also specifically show how high-contrast AO and speckle imaging observations detect companions at larger separations ($\theta \geq$0.02-0.05") that are missed by the spectroscopic technique, provide additional information for characterizing the companion and its potential contamination (e.g., PA, separation, $\Delta$m), and cover a wider range of primary star effective temperatures. The investigation presented here illustrates the utility of combining the two techniques to reveal higher-order multiples in known planet-hosting systems.Comment: Accepted to AJ. 40 pages, 12 figure

High-resolution Multi-band Imaging for Validation and Characterization of Small Kepler Planets

High-resolution ground-based optical speckle and near-infrared adaptive optics images are taken to search for stars in close angular proximity to host stars of candidate planets identified by the NASA Kepler Mission. Neighboring stars are a potential source of false positive signals. These stars also blend into Kepler light curves, affecting estimated planet properties, and are important for an understanding of planets in multiple star systems. Deep images with high angular resolution help to validate candidate planets by excluding potential background eclipsing binaries as the source of the transit signals. A study of 18 Kepler Object of Interest stars hosting a total of 28 candidate and validated planets is presented. Validation levels are determined for 18 planets against the likelihood of a false positive from a background eclipsing binary. Most of these are validated at the 99% level or higher, including 5 newly-validated planets in two systems: Kepler-430 and Kepler-431. The stellar properties of the candidate host stars are determined by supplementing existing literature values with new spectroscopic characterizations. Close neighbors of 7 of these stars are examined using multi-wavelength photometry to determine their nature and influence on the candidate planet properties. Most of the close neighbors appear to be gravitationally-bound secondaries, while a few are best explained as closely co-aligned field stars. Revised planet properties are derived for each candidate and validated planet, including cases where the close neighbors are the potential host stars.Comment: in press at AJ, 44 pages, 8 figures; The only changes made relative to version 1 are updates to the list of reference

Lines, Circles, Planes and Spheres

Let $S$ be a set of $n$ points in $\mathbb{R}^3$, no three collinear and not all coplanar. If at most $n-k$ are coplanar and $n$ is sufficiently large, the total number of planes determined is at least $1 + k \binom{n-k}{2}-\binom{k}{2}(\frac{n-k}{2})$. For similar conditions and sufficiently large $n$, (inspired by the work of P. D. T. A. Elliott in \cite{Ell67}) we also show that the number of spheres determined by $n$ points is at least $1+\binom{n-1}{3}-t_3^{orchard}(n-1)$, and this bound is best possible under its hypothesis. (By $t_3^{orchard}(n)$, we are denoting the maximum number of three-point lines attainable by a configuration of $n$ points, no four collinear, in the plane, i.e., the classic Orchard Problem.) New lower bounds are also given for both lines and circles.Comment: 37 page

Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images

Quantifying uncertainty of predictions has been identified as one way to develop more trustworthy artificial intelligence (AI) models beyond conventional reporting of performance metrics. When considering their role in a clinical decision support setting, AI classification models should ideally avoid confident wrong predictions and maximise the confidence of correct predictions. Models that do this are said to be well-calibrated with regard to confidence. However, relatively little attention has been paid to how to improve calibration when training these models, i.e., to make the training strategy uncertainty-aware. In this work we evaluate three novel uncertainty-aware training strategies comparing against two state-of-the-art approaches. We analyse performance on two different clinical applications: cardiac resynchronisation therapy (CRT) response prediction and coronary artery disease (CAD) diagnosis from cardiac magnetic resonance (CMR) images. The best-performing model in terms of both classification accuracy and the most common calibration measure, expected calibration error (ECE) was the Confidence Weight method, a novel approach that weights the loss of samples to explicitly penalise confident incorrect predictions. The method reduced the ECE by 17% for CRT response prediction and by 22% for CAD diagnosis when compared to a baseline classifier in which no uncertainty-aware strategy was included. In both applications, as well as reducing the ECE there was a slight increase in accuracy from 69% to 70% and 70% to 72% for CRT response prediction and CAD diagnosis respectively. However, our analysis showed a lack of consistency in terms of optimal models when using different calibration measures. This indicates the need for careful consideration of performance metrics when training and selecting models for complex high-risk applications in healthcare

Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction

Advances in deep learning (DL) have resulted in impressive accuracy in some medical image classification tasks, but often deep models lack interpretability. The ability of these models to explain their decisions is important for fostering clinical trust and facilitating clinical translation. Furthermore, for many problems in medicine there is a wealth of existing clinical knowledge to draw upon, which may be useful in generating explanations, but it is not obvious how this knowledge can be encoded into DL models - most models are learnt either from scratch or using transfer learning from a different domain. In this paper we address both of these issues. We propose a novel DL framework for image-based classification based on a variational autoencoder (VAE). The framework allows prediction of the output of interest from the latent space of the autoencoder, as well as visualisation (in the image domain) of the effects of crossing the decision boundary, thus enhancing the interpretability of the classifier. Our key contribution is that the VAE disentangles the latent space based on `explanations' drawn from existing clinical knowledge. The framework can predict outputs as well as explanations for these outputs, and also raises the possibility of discovering new biomarkers that are separate (or disentangled) from the existing knowledge. We demonstrate our framework on the problem of predicting response of patients with cardiomyopathy to cardiac resynchronization therapy (CRT) from cine cardiac magnetic resonance images. The sensitivity and specificity of the proposed model on the task of CRT response prediction are 88.43% and 84.39% respectively, and we showcase the potential of our model in enhancing understanding of the factors contributing to CRT response.Comment: MICCAI 2020 conferenc

Validation of Twelve Small Kepler Transiting Planets in the Habitable Zone

We present an investigation of twelve candidate transiting planets from Kepler with orbital periods ranging from 34 to 207 days, selected from initial indications that they are small and potentially in the habitable zone (HZ) of their parent stars. Few of these objects are known. The expected Doppler signals are too small to confirm them by demonstrating that their masses are in the planetary regime. Here we verify their planetary nature by validating them statistically using the BLENDER technique, which simulates large numbers of false positives and compares the resulting light curves with the Kepler photometry. This analysis was supplemented with new follow-up observations (high-resolution optical and near-infrared spectroscopy, adaptive optics imaging, and speckle interferometry), as well as an analysis of the flux centroids. For eleven of them (KOI-0571.05, 1422.04, 1422.05, 2529.02, 3255.01, 3284.01, 4005.01, 4087.01, 4622.01, 4742.01, and 4745.01) we show that the likelihood they are true planets is far greater than that of a false positive, to a confidence level of 99.73% (3 sigma) or higher. For KOI-4427.01 the confidence level is about 99.2% (2.6 sigma). With our accurate characterization of the GKM host stars, the derived planetary radii range from 1.1 to 2.7 R_Earth. All twelve objects are confirmed to be in the HZ, and nine are small enough to be rocky. Excluding three of them that have been previously validated by others, our study doubles the number of known rocky planets in the HZ. KOI-3284.01 (Kepler-438b) and KOI-4742.01 (Kepler-442b) are the planets most similar to the Earth discovered to date when considering their size and incident flux jointly.Comment: 27 pages in emulateapj format, including tables and figures. To appear in The Astrophysical Journa