Bayesian analysis of the radial velocities of HD 11506 reveals another planetary companion

We aim to demonstrate the efficiency of a Bayesian approach in analysing radial velocity data by reanalysing a set of radial velocity measurements. We present Bayesian analysis of a recently published set of radial velocity measurements known to contain the signal of one extrasolar planetary candidate, namely, HD 11506. The analysis is conducted using the Markov chain Monte Carlo method and the resulting distributions of orbital parameters are tested by performing direct integration of randomly selected samples with the Bulirsch-Stoer method. The magnitude of the stellar radial velocity variability, known as jitter, is treated as a free parameter with no assumptions about its magnitude. We show that the orbital parameters of the planet known to be present in the data correspond to a different solution when the jitter is allowed to be a free parameter. We also show evidence of an additional candidate, a 0.8 MJup planet with period of about 0.5 yr in orbit around HD 11506. This second planet is inferred to be present with a high level of confidence.Comment: 4 pages, 5 figures, to appear in A&

The synthesis of data from instrumented structures and physics-based models via Gaussian processes

At the heart of structural engineering research is the use of data obtained from physical structures such as bridges, viaducts and buildings. These data can represent how the structure responds to various stimuli over time when in operation. Many models have been proposed in literature to represent such data, such as linear statistical models. Based upon these models, the health of the structure is reasoned about, e.g. through damage indices, changes in likelihood and statistical parameter estimates. On the other hand, physics-based models are typically used when designing structures to predict how the structure will respond to operational stimuli. These models represent how the structure responds to stimuli under idealised conditions. What remains unclear in the literature is how to combine the observed data with information from the idealised physics-based model into a model that describes the responses of the operational structure. This paper introduces a new approach which fuses together observed data from a physical structure during operation and information from a mathematical model. The observed data are combined with data simulated from the physics-based model using a multi-output Gaussian process formulation. The novelty of this method is how the information from observed data and the physics-based model is balanced to obtain a representative model of the structures response to stimuli. We present our method using data obtained from a fibre-optic sensor network installed on experimental railway sleepers. The curvature of the sleeper at sensor and also non-sensor locations is modelled, guided by the mathematical representation. We discuss how this approach can be used to reason about changes in the structures behaviour over time using simulations and experimental data. The results show that the methodology can accurately detect such changes. They also indicate that the methodology can infer information about changes in the parameters within the physics-based model, including those governing components of the structure not measured directly by sensors such as the ballast foundation.This work was supported by The Alan Turing Institute under the EPSRC grant EP/N510129/1 and the Turing-Lloyd's Register Foundation Programme for Data-Centric Engineering. The authors would also like to acknowledge EPSRC (grant nos. EP/P020720/1, EP/R018413/1, EP/R034710/1, EP/R004889/1) and Innovate UK (grant no. 920035) for funding this research through the Centre for Smart Infrastructure and Construction (CSIC) Innovation and Knowledge Centre. Research related to installation of the sensor system was carried out under EPSRC grant no. EP/N021614. Mark Girolami is supported by a Royal Academy of Engineering Research Chair in Data Centric Engineering

The complementarity of astrometric and radial velocity exoplanet observations - Determining exoplanet mass with astrometric snapshots

We obtain full information on the orbital parameters by combining radial velocity and astrometric measurements by means of Bayesian inference. We sample the parameter probability densities of orbital model parameters with a Markov chain Monte Carlo (McMC) method in simulated observational scenarios to test the detectability of planets with orbital periods longer than the observational timelines. We show that, when fitting model parameters simultaneously to measurements from both sources, it is possible to extract much more information from the measurements than when using either source alone. We demonstrate this by studying the orbit of recently found extra-solar planet HD 154345 b.Comment: 6 pages, 9 figures. Accepted to A&

A digital twin of bridges for structural health monitoring

© International Workshop on Structural Health Monitoring. All rights reserved. Bridges are critical infrastructure systems connecting different regions and providing widespread social and economic benefits. It is therefore essential that they are designed, constructed and maintained properly to adapt to changing conditions of use and climate-driven events. With the rapid development in capability of collecting bridge monitoring data, a data challenge emerges due to insufficient capability in managing, processing and interpreting large monitoring datasets to extract useful information which is of practical value to the industry. One emerging area of research which focuses on addressing this challenge is the creation of 'digital twins' for bridges. A digital twin serves as a virtual representation of the physical infrastructure (i.e. the physical twin), which can be updated in near real time as new data is collected, provide feedback into the physical twin and perform 'what-if scenarios for assessing asset risks and predicting asset performance. This paper presents and broadly discusses two years of exploratory study towards creating a digital twin of bridges for structural health monitoring purposes. In particular, it has involved an interdisciplinary collaboration between civil engineers at the Cambridge Centre for Smart Infrastructure and Construction (CSIC) and statisticians at the Alan Turing Institute (ATI), using two monitored railway bridges in Staffordshire, UK as a case study. Four areas of research were investigated: (i) real-time data management using BIM, (ii) physics-based approaches, (iii) data-driven approaches, and (iv) data-centric engineering approaches (i.e. synthesis of physics-based and data-driven approaches). A framework for creating a digital twin of bridges, particularly for structural health monitoring purposes, is proposed and briefly discussed

Quantifying the Detrimental Impacts of Land-Use and Management Change on European Forest Bird Populations

The ecological impacts of changing forest management practices in Europe are poorly understood despite European forests being highly managed. Furthermore, the effects of potential drivers of forest biodiversity decline are rarely considered in concert, thus limiting effective conservation or sustainable forest management. We present a trait-based framework that we use to assess the detrimental impact of multiple land-use and management changes in forests on bird populations across Europe. Major changes to forest habitats occurring in recent decades, and their impact on resource availability for birds were identified. Risk associated with these changes for 52 species of forest birds, defined as the proportion of each species' key resources detrimentally affected through changes in abundance and/or availability, was quantified and compared to their pan-European population growth rates between 1980 and 2009. Relationships between risk and population growth were found to be significantly negative, indicating that resource loss in European forests is an important driver of decline for both resident and migrant birds. Our results demonstrate that coarse quantification of resource use and ecological change can be valuable in understanding causes of biodiversity decline, and thus in informing conservation strategy and policy. Such an approach has good potential to be extended for predictive use in assessing the impact of possible future changes to forest management and to develop more precise indicators of forest health

A Niche-Based Framework to Assess Current Monitoring of European Forest Birds and Guide Indicator Species' Selection

Concern that European forest biodiversity is depleted and declining has provoked widespread efforts to improve management practices. To gauge the success of these actions, appropriate monitoring of forest ecosystems is paramount. Multi-species indicators are frequently used to assess the state of biodiversity and its response to implemented management, but generally applicable and objective methodologies for species' selection are lacking. Here we use a niche-based approach, underpinned by coarse quantification of species' resource use, to objectively select species for inclusion in a pan-European forest bird indicator. We identify both the minimum number of species required to deliver full resource coverage and the most sensitive species' combination, and explore the trade-off between two key characteristics, sensitivity and redundancy, associated with indicators comprising different numbers of species. We compare our indicator to an existing forest bird indicator selected on the basis of expert opinion and show it is more representative of the wider community. We also present alternative indicators for regional and forest type specific monitoring and show that species' choice can have a significant impact on the indicator and consequent projections about the state of the biodiversity it represents. Furthermore, by comparing indicator sets drawn from currently monitored species and the full forest bird community, we identify gaps in the coverage of the current monitoring scheme. We believe that adopting this niche-based framework for species' selection supports the objective development of multi-species indicators and that it has good potential to be extended to a range of habitats and taxa

Role of adiponectin and inflammation in insulin resistance of Mc3r and Mc4r knockout mice

Objective: To investigate the involvement of hypoadiponectinemia and inflammation in coupling obesity to insulin resistance in melanocortin-3 receptor and melanocortin-4 receptor knockout (KO) mice (Mc3/4rKO). Research Methods and Procedures: Sera and tissue were collected from 6-month-old Mc3rKO, Mc4rKO, and wild-type C57BL6J litter mates maintained on low-fat diet or exposed to high-fat diet (HFD) for 1 or 3 months. Inflammation was assessed by both real-time polymerase chain reaction analysis of macrophage-specific gene expression and immunohistochemistry. Results: Mc4rKO exhibited hypoadiponectinemia, exacerbated by HFD and obesity, previously reported in murine models of obesity. Mc4r deficiency was also associated with high levels of macrophage infiltration of adipose tissue, again exacerbated by HFD. In contrast, Mc3rKO exhibited normal serum adiponectin levels, irrespective of diet or obesity, and a delayed inflammatory response to HFD relative to Mc4rKO. Discussion: Our findings suggest that severe insulin resistance of Mc4rKO fed a HFD, as reported in other models of obesity such as leptin-deficient (Lep ob/Lepob) and KK-Ay mice, is linked to reduced serum adiponectin and high levels of inflammation in adipose tissue. Conversely, maintenance of normal serum adiponectin may be a factor in the relatively mild insulin-resistant phenotype of severely obese Mc3rKO. Mc3rKO are, thus, a unique mouse model where obesity is not associated with reduced serum adiponectin levels. A delay in macrophage infiltration of adipose tissue of Mc3rKO during exposure to HFD may also be a factor contributing to the mild insulin resistance in this model. Copyright © 2007 NAASO

Five Planets Orbiting 55 Cancri

We report 18 years of Doppler shift measurements of a nearby star, 55 Cancri, that exhibit strong evidence for five orbiting planets. The four previously reported planets are strongly confirmed here. A fifth planet is presented, with an apparent orbital period of 260 days, placing it 0.78 AU from the star in the large empty zone between two other planets. The velocity wobble amplitude of 4.9 \ms implies a minimum planet mass \msini = 45.7 \mearthe. The orbital eccentricity is consistent with a circular orbit, but modest eccentricity solutions give similar \chisq fits. All five planets reside in low eccentricity orbits, four having eccentricities under 0.1. The outermost planet orbits 5.8 AU from the star and has a minimum mass, \msini = 3.8 \mjupe, making it more massive than the inner four planets combined. Its orbital distance is the largest for an exoplanet with a well defined orbit. The innermost planet has a semi-major axis of only 0.038 AU and has a minimum mass, \msinie, of only 10.8 \mearthe, one of the lowest mass exoplanets known. The five known planets within 6 AU define a {\em minimum mass protoplanetary nebula} to compare with the classical minimum mass solar nebula. Numerical N-body simulations show this system of five planets to be dynamically stable and show that the planets with periods of 14.65 and 44.3 d are not in a mean-motion resonance. Millimagnitude photometry during 11 years reveals no brightness variations at any of the radial velocity periods, providing support for their interpretation as planetary.Comment: accepted to Ap

Ten Low Mass Companions from the Keck Precision Velocity Survey

Ten new low mass companions have emerged from the Keck precision Doppler velocity survey, with minimum (msini) masses ranging from 0.8 mjup to 0.34 msun. Five of these are planet candidates with msini < 12 mjup, two are brown dwarf candidates with msini ~30 mjup, and three are low mass stellar companions. Hipparcos astrometry reveals the orbital inclinations and masses for three of the (more massive) companions, and it provides upper limits to the masses for the rest. A new class of extrasolar planet is emerging, characterized by nearly circular orbits and orbital radii greater than 1 AU. The planet HD 4208b appears to be a member of this new class. The mass distribution of extrasolar planets continues to exhibit a rapid rise from 10 mjup toward the lowest detectable masses near 1 msat.Comment: 26 pages, TeX, plus 13 postscript figure

Effect of Oral Iron Repletion on Exercise Capacity in Patients With Heart Failure With Reduced Ejection Fraction and Iron Deficiency: The IRONOUT HF Randomized Clinical Trial.

Importance: Iron deficiency is present in approximately 50% of patients with heart failure with reduced left ventricular ejection fraction (HFrEF) and is an independent predictor of reduced functional capacity and mortality. However, the efficacy of inexpensive readily available oral iron supplementation in heart failure is unknown. Objective: To test whether therapy with oral iron improves peak exercise capacity in patients with HFrEF and iron deficiency. Design, Setting, and Participants: Phase 2, double-blind, placebo-controlled randomized clinical trial of patients with HFrEF ( Interventions: Oral iron polysaccharide (n = 111) or placebo (n = 114), 150 mg twice daily for 16 weeks. Main Outcomes and Measures: The primary end point was a change in peak oxygen uptake (V̇o2) from baseline to 16 weeks. Secondary end points were change in 6-minute walk distance, plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, and health status as assessed by Kansas City Cardiomyopathy Questionnaire (KCCQ, range 0-100, higher scores reflect better quality of life). Results: Among 225 randomized participants (median age, 63 years; 36% women) 203 completed the study. The median baseline peak V̇o2 was 1196 mL/min (interquartile range [IQR], 887-1448 mL/min) in the oral iron group and 1167 mL/min (IQR, 887-1449 mL/min) in the placebo group. The primary end point, change in peak V̇o2 at 16 weeks, did not significantly differ between the oral iron and placebo groups (+23 mL/min vs -2 mL/min; difference, 21 mL/min [95% CI, -34 to +76 mL/min]; P = .46). Similarly, at 16 weeks, there were no significant differences between treatment groups in changes in 6-minute walk distance (-13 m; 95% CI, -32 to 6 m), NT-proBNP levels (159; 95% CI, -280 to 599 pg/mL), or KCCQ score (1; 95% CI, -2.4 to 4.4), all P \u3e .05. Conclusions and Relevance: Among participants with HFrEF with iron deficiency, high-dose oral iron did not improve exercise capacity over 16 weeks. These results do not support use of oral iron supplementation in patients with HFrEF. Trial Registration: clinicaltrials.gov Identifier: NCT02188784