Transit Timing and Duration Variations for the Discovery and Characterization of Exoplanets

Transiting exoplanets in multi-planet systems have non-Keplerian orbits which can cause the times and durations of transits to vary. The theory and observations of transit timing variations (TTV) and transit duration variations (TDV) are reviewed. Since the last review, the Kepler spacecraft has detected several hundred perturbed planets. In a few cases, these data have been used to discover additional planets, similar to the historical discovery of Neptune in our own Solar System. However, the more impactful aspect of TTV and TDV studies has been characterization of planetary systems in which multiple planets transit. After addressing the equations of motion and parameter scalings, the main dynamical mechanisms for TTV and TDV are described, with citations to the observational literature for real examples. We describe parameter constraints, particularly the origin of the mass/eccentricity degeneracy and how it is overcome by the high-frequency component of the signal. On the observational side, derivation of timing precision and introduction to the timing diagram are given. Science results are reviewed, with an emphasis on mass measurements of transiting sub-Neptunes and super-Earths, from which bulk compositions may be inferred.Comment: Revised version. Invited review submitted to 'Handbook of Exoplanets,' Exoplanet Discovery Methods section, Springer Reference Works, Juan Antonio Belmonte and Hans Deeg, Eds. TeX and figures may be found at https://github.com/ericagol/TTV_revie

Are mice good models for human neuromuscular disease? Comparing muscle excursions in walking between mice and humans

The mouse is one of the most widely used animal models to study neuromuscular diseases and test new therapeutic strategies. However, findings from successful pre-clinical studies using mouse models frequently fail to translate to humans due to various factors. Differences in muscle function between the two species could be crucial but often have been overlooked. The purpose of this study was to evaluate and compare muscle excursions in walking between mice and humans

Does Uptake of Pharmaceuticals Vary Across Earthworm Species?

This study compared the uptake and depuration of four commonly used pharmaceuticals (carbamazepine, diclofenac, fluoxetine and orlistat) in two earthworm species (Lumbricus terrestris and Eisenia fetida). L. terrestris are a larger species and often found in deep burrows whereas E. fetida prefer to reside near the soil surface. Species burrowing habits and sizes may alter uptake by earthworms. All four pharmaceuticals were taken up into both L. terrestris and E. fetida tissue after 21 days exposure to spiked soil. Bioconcentration factors (BCFs) ranged between 1.72 and 29.83 for L. terrestris and 1.14 and 63.03 for E. fetida. For carbamazepine and diclofenac, BCFs were similar whereas for fluoxetine and orlistat, BCFs in E. fetida were more than double those seen in L. terrestris. Results indicate that uptake into earthworms cannot be generalised between species and that the influence of species traits can vary depending on the nature of the study chemical

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Newsprint coverage of smoking in cars carrying children : a case study of public and scientific opinion driving the policy debate

Acknowledgements Date of Acceptance:17/10/2014 Acknowledgements: This project was funded by Cancer Research UK (MC_U130085862) and the Scottish School of Public Health Research. Cancer Research UK and the Scottish School of Public Health Research was not involved in the collection, analysis, and interpretation of data, writing of the manuscript or the decision to submit the manuscript for publication. Shona Hilton, Karen Wood, Josh Bain and Chris Patterson are funded by the UK Medical Research Council as part of the Understandings and Uses of Public Health Research programme (MC_UU_12017/6) at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. We thank Alan Pollock who provided assistance with coding.Peer reviewedPublisher PD

Brief communication: Impacts of a developing polynya off Commonwealth Bay, East Antarctica, triggered by grounding of iceberg B09B

The dramatic calving of the Mertz Glacier tongue in 2010, precipitated by the movement of iceberg B09B, reshaped the oceanographic regime across the Mertz Polynya and Commonwealth Bay, regions where high-salinity shelf water (HSSW) - the precursor to Antarctic bottom water (AABW) - is formed. Here we present post-calving observations that suggest that this reconfiguration and subsequent grounding of B09B have driven the development of a new polynya and associated HSSW production off Commonwealth Bay. Supported by satellite observations and modelling, our findings demonstrate how local icescape changes may impact the formation of HSSW, with potential implications for large-scale ocean circulation

Family coordination in families who have a child with autism spectrum disorder

Little is known about the interactions of families where there is a child with autism spectrum disorder (ASD). The present study applies the Lausanne Trilogue Play (LTP) to explore both its applicability to this population as well as to assess resources and areas of deficit in these families. The sample consisted of 68 families with a child with ASD, and 43 families with a typically developing (TD) child. With respect to the global score for family coordination there were several negative correlations: the more severe the symptoms (based on the child’s ADOS score), the more family coordination was dysfunctional. This correlation was particularly high when parents had to play together with the child. In the parts in which only one of the parents played actively with the child, while the other was simply present, some families did achieve scores in the functional range, despite the child’s symptom severity. The outcomes are discussed in terms of their clinical implications both for assessment and for interventio

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

To respond or not to respond - a personal perspective of intestinal tolerance

For many years, the intestine was one of the poor relations of the immunology world, being a realm inhabited mostly by specialists and those interested in unusual phenomena. However, this has changed dramatically in recent years with the realization of how important the microbiota is in shaping immune function throughout the body, and almost every major immunology institution now includes the intestine as an area of interest. One of the most important aspects of the intestinal immune system is how it discriminates carefully between harmless and harmful antigens, in particular, its ability to generate active tolerance to materials such as commensal bacteria and food proteins. This phenomenon has been recognized for more than 100 years, and it is essential for preventing inflammatory disease in the intestine, but its basis remains enigmatic. Here, I discuss the progress that has been made in understanding oral tolerance during my 40 years in the field and highlight the topics that will be the focus of future research