Modeling Menstrual Cycle Length and Variability at the Approach of Menopause Using Bayesian Changepoint Models

As women approach menopause, the patterns of their menstruation cycle lengths change. To study these changes, we need to jointly model both the mean and variability of the cycle length. The model incorporates separate mean and variance change points for each woman and a hierarchical model to link them together, along with regression components to include predictors of menopausal onset such as age at menarche and parity. Data are from TREMIN, an ongoing 70-year old longitudinal study that has obtained menstrual calendar data of women throughout their reproductive life course. An additional complexity arises from the fact that these calendars have substantial missingness due to hormone use, surgery, failure to report, and loss of contact. We integrate multiple imputation and time-to event modeling in our Bayesian estimation procedure to deal with different forms of the missingness. Posterior predictive model checks are applied to evaluate the model fit. Our method successfully modeled patterns of women’s menstrual cycle trajectories throughout their late reproductive life and identified the change points for mean and variability of segment length, which provides insight into the menopausal process. More generally, our model points the way toward increasing use of joint mean-variance models to predict health outcomes and better understand disease processes

Unraveling the Contribution of Image Captioning and Neural Machine Translation for Multimodal Machine Translation

Recent work on multimodal machine translation has attempted to address the problem of producing target language image descriptions based on both the source language description and the corresponding image. However, existing work has not been conclusive on the contribution of visual information. This paper presents an in-depth study of the problem by examining the differences and complementarities of two related but distinct approaches to this task: textonly neural machine translation and image captioning. We analyse the scope for improvement and the effect of different data and settings to build models for these tasks. We also propose ways of combining these two approaches for improved translation quality

Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty

The long-term health effects of air pollution are often estimated using a spatio-temporal ecological areal unit study, but this design leads to the following statistical challenges: (1) how to estimate spatially representative pollution concentrations for each areal unit; (2) how to allow for the uncertainty in these estimated concentrations when estimating their health effects; and (3) how to simultaneously estimate the joint effects of multiple correlated pollutants. This article proposes a novel 2-stage Bayesian hierarchical model for addressing these 3 challenges, with inference based on Markov chain Monte Carlo simulation. The first stage is a multivariate spatio-temporal fusion model for predicting areal level average concentrations of multiple pollutants from both monitored and modelled pollution data. The second stage is a spatio-temporal model for estimating the health impact of multiple correlated pollutants simultaneously, which accounts for the uncertainty in the estimated pollution concentrations. The novel methodology is motivated by a new study of the impact of both particulate matter and nitrogen dioxide concentrations on respiratory hospital admissions in Scotland between 2007 and 2011, and the results suggest that both pollutants exhibit substantial and independent health effects

Endonuclease controlled aggregation of gold nanoparticles for the ultrasensitive detection of pathogenic bacterial DNA

The development of an ultrasensitive biosensor for the low-cost and on-site detection of pathogenic DNA could transform detection capabilities within food safety, environmental monitoring and clinical diagnosis. Herein, we present an innovative approach exploiting endonuclease-controlled aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. The method utilizes RNA-functionalized AuNPs which form DNA-RNA heteroduplex structures through specific hybridization with target DNA. Once formed, the DNA-RNA heteroduplex is susceptible to RNAse H enzymatic cleavage of the RNA probe, allowing the target DNA to liberate and hybridize with another RNA probe. This continuously happens until all of the RNA probes are cleaved, leaving the nanoparticles unprotected and thus aggregated upon exposure to a high electrolytic medium. The assay is ultrasensitive, allowing the detection of target DNA at femtomolar level by simple spectroscopic analysis (40.7 fM and 2.45 fM as measured by UV-vis and dynamic light scattering (DLS), respectively). The target DNA spiked food matrix (chicken meat) is also successfully detected at a concentration of 1.2 pM (by UV-vis) or 18.0 fM (by DLS). In addition to the ultra-high sensitivity, the total analysis time of the assay is less than 3 hours, thus demonstrating its practicality for food analysis

China and the Spanish Empire

Editada en la Fundación Empresa PúblicaEn este artículo argumentamos que Ming China desempeñó un papel fundamental en el auge y decadencia del Imperio español. La demanda china de plata permitió elevados beneficios hasta 1640. El descenso de estos beneficios llevó a la reducción de la producción y la Monarquía se enfrentó a una grave crisis financiera. La consecuencia fue una presión fiscal creciente con objeto de compensar la pérdida de los ingresos externos procedentes de América.In this article we argue that Ming China had a fundamental impact on the rise and decline of the Spanish Empire. China's demand for silver was of such magnitude that private mining profits in the Spanish Empire remained high until about 1640. The decline of these profits led to abandon production. Spain faced a deepening financial crisis due to the fall of silver's value. The loss of purchasing power from the Crown's American enterprise was inevitable and the state's relentless pressure for increased taxation within Castile and elsewhere was mandatory in order to compensate for lost external purchasing power.Publicad

Tailoring transient-amorphous states: towards fast and power-efficient phase-change memory and neuromorphic computing.

A new methodology for manipulating transient-amorphous states of phase-change memory (PCM) materials is reported as a viable means to boost the speed, yet reduce the power consumption of PC memories, and is applicable to new forms of PCM-based neuromorphic devices. Controlling multiple-pulse interactions with PC materials may provide an opportunity toward developing a new paradigm for ultra-fast neuromorphic computing.We acknowledge financial support from the Engineering and Physical Sciences Research Council (UK).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/adma.20140269

Dynamical entropy in Banach spaces

We introduce a version of Voiculescu-Brown approximation entropy for isometric automorphisms of Banach spaces and develop within this framework the connection between dynamics and the local theory of Banach spaces discovered by Glasner and Weiss. Our fundamental result concerning this contractive approximation entropy, or CA entropy, characterizes the occurrence of positive values both geometrically and topologically. This leads to various applications; for example, we obtain a geometric description of the topological Pinsker factor and show that a C*-algebra is type I if and only if every multiplier inner *-automorphism has zero CA entropy. We also examine the behaviour of CA entropy under various product constructions and determine its value in many examples, including isometric automorphisms of l_p spaces and noncommutative tensor product shifts.Comment: 33 pages; unified approach to last three sections give

Efficient generation of tunable photon pairs at 0.8 and 1.6 micrometer

We demonstrate efficient generation of collinearly propagating, highly nondegenerate photon pairs in a periodically-poled lithium niobate cw parametric downconverter with an inferred pair generation rate of 1.4*10^7/s/mW of pump power. Detection of an 800-nm signal photon triggers a thermoelectrically-cooled 20%-efficient InGaAs avalanche photodiode for the detection of the 1600-nm conjugate idler photon. Using single-mode fibers as spatial mode filters, we obtain a signal-conditioned idler-detection probability of about 3.1%.Comment: 8 pages, 3 figure

The cutoff method for the numerical computation of nonnegative solutions of parabolic PDEs with application to anisotropic diffusion and lubrication-type equations

The cutoff method, which cuts off the values of a function less than a given number, is studied for the numerical computation of nonnegative solutions of parabolic partial differential equations. A convergence analysis is given for a broad class of finite difference methods combined with cutoff for linear parabolic equations. Two applications are investigated, linear anisotropic diffusion problems satisfying the setting of the convergence analysis and nonlinear lubrication-type equations for which it is unclear if the convergence analysis applies. The numerical results are shown to be consistent with the theory and in good agreement with existing results in the literature. The convergence analysis and applications demonstrate that the cutoff method is an effective tool for use in the computation of nonnegative solutions. Cutoff can also be used with other discretization methods such as collocation, finite volume, finite element, and spectral methods and for the computation of positive solutions.Comment: 19 pages, 41 figure

Interannual variability of the tropical Atlantic independent of and associated with ENSO: Part I. The North Tropical Atlantic

The interannual variability of the tropical Atlantic ocean-atmosphere system is examined using 50 years of sea-surface temperature (SST) and re-analysis data, and satellite data when available. A singular value decomposition analysis of 12- to 72-month bandpass filtered SST and zonal wind stress reveals two dominant modes of interannual variability. The SST anomalies are confined to the North Tropical Atlantic (NTA) in the first mode and extend over the equatorial and South Tropical Atlantic in the second mode. No evidence is found for an Atlantic SST dipole. The structure of the first (NTA) mode is examined in detail here, while the second mode has been described in a companion paper. In particular, the relationship of the NTA mode with El Nino-Southern Oscillation (ENSO) is investigated. There are 12 NTA events (seven warm and five cold) that are associated with ENSO, and 18 NTA events (seven warm and 11 cold) that are independent of ENSO. The ENSO-associated NTA events appear to be a passive response to remote ENSO forcing, mainly via a Pacific-North America (PNA)-like wave train that induces SST anomalies over the NTA through changes in the surface wind and latent heat flux. The NTA anomalies peak four months after ENSO. There does not appear to be an atmospheric response to the NTA SST anomalies as convection over the Atlantic is suppressed by the anomalous Walker circulation due to ENSO. The ENSO-independent NTA events also appear to be induced by an extratropical wave train from the Pacific sector (but one that is independent of Pacific SST), and forcing by the North Atlantic Oscillation (NAO) also contributes. As the event matures, the atmosphere does respond to the NTA SST anomalies, with enhanced convection over the Caribbean and a wave train that propagates northeastward to Europe