Bayesian evidence for two companions orbiting HIP 5158

We present results of a Bayesian analysis of radial velocity (RV) data for the star HIP 5158, confirming the presence of two companions and also constraining their orbital parameters. Assuming Keplerian orbits, the two-companion model is found to be e^{48} times more probable than the one-planet model, although the orbital parameters of the second companion are only weakly constrained. The derived orbital periods are 345.6 +/- 2.0 d and 9017.8 +/- 3180.7 d respectively, and the corresponding eccentricities are 0.54 +/- 0.04 and 0.14 +/- 0.10. The limits on planetary mass (m \sin i) and semimajor axis are (1.44 +/- 0.14 M_{J}, 0.89 +/- 0.01 AU) and (15.04 +/- 10.55 M_{J}, 7.70 +/- 1.88 AU) respectively. Owing to large uncertainty on the mass of the second companion, we are unable to determine whether it is a planet or a brown dwarf. The remaining `noise' (stellar jitter) unaccounted for by the model is 2.28 +/- 0.31 m/s. We also analysed a three-companion model, but found it to be e^{8} times less probable than the two-companion model.Comment: 5 pages, 4 figures, 3 tables. Added a couple of figures showing the residuals after one and two companion fits. Accepted for publication in MNRAS Letter

Multiple plasmon resonances in naturally-occurring multiwall nanotubes: infrared spectra of chrysotile asbestos

Chrysotile asbestos is formed by densely packed bundles of multiwall hollow nanotubes. Each wall in the nanotubes is a cylindrically wrapped layer of $Mg_3 Si_2 O_5 (OH)_4$. We show by experiment and theory that the infrared spectrum of chrysotile presents multiple plasmon resonances in the Si-O stretching bands. These collective charge excitations are universal features of the nanotubes that are obtained by cylindrically wrapping an anisotropic material. The multiple plasmons can be observed if the width of the resonances is sufficiently small as in chrysotile.Comment: 4 pages, 5 figures. Revtex4 compuscript. Misprint in Eq.(6) correcte

Gaining insight into exclusive and common transcriptomic features linked with biotic stress responses in Malus

Identifying key information in transcriptomic data is very important, especially when the “omic” study deals with plant responses to stresses in field conditions where a high number of variables and disturbing factors may affect the analysis. In this meta-analysis we collected 12 transcriptomic works in Malus in order to identify which key genes, proteins, gene categories are involved in general plant pathological conditions and those features linked with exclusive biotic stress responses. Those genes that are only related with molecular responses to pathogen attacks and those linked with other plant physiological processes were identified. A pipeline composed by pathway and gene set enrichment analysis, protein-protein interaction networks and gene visualization tools was employed. A total of 13,230 genes of the 12 studies were analyzed with functional data mining tools: 5,215 were upregulated, 8,015 were downregulated. Gene set enrichment analysis pointed out that photosynthesis was inhibited by Erwinia amylovora and fungal pathogens. Different hormonal crosstalk was linked with responses to different pathogens. Gibberellin-related pathways, ABA-related were mostly repressed by fungal pathogens. Relating to transcription factors, genes encoding MYBs and WRKY2 were downregulated by fungal pathogens and 12 WRKYs were commonly regulated by different biotic stresses The protein-protein interaction analysis discovered the presence of several proteins affected by more than one biotic stress including a WRKY40 and some highly interactive proteins such as heat shock proteins. This study represents a first preliminary curated meta-analysis of apple transcriptomic responses to biotic stresses

A practical application of text mining to literature on cognitive rehabilitation and enhancement through neurostimulation

The exponential growth in publications represents a major challenge for researchers. Many scientific domains, including neuroscience, are not yet fully engaged in exploiting large bodies of publications. In this paper, we promote the idea to partially automate the processing of scientific documents, specifically using text mining (TM), to efficiently review big corpora of publications. The “cognitive advantage” given by TM is mainly related to the automatic extraction of relevant trends from corpora of literature, otherwise impossible to analyze in short periods of time. Specifically, the benefits of TM are increased speed, quality and reproducibility of text processing, boosted by rapid updates of the results. First, we selected a set of TM-tools that allow user-friendly approaches of the scientific literature, and which could serve as a guide for researchers willing to incorporate TM in their work. Second, we used these TM-tools to obtain basic insights into the relevant literature on cognitive rehabilitation (CR) and cognitive enhancement (CE) using transcranial magnetic stimulation (TMS). TM readily extracted the diversity of TMS applications in CR and CE from vast corpora of publications, automatically retrieving trends already described in published reviews. TMS emerged as one of the important non-invasive tools that can both improve cognitive and motor functions in numerous neurological diseases and induce modulations/enhancements of many fundamental brain functions. TM also revealed trends in big corpora of publications by extracting occurrence frequency and relationships of particular subtopics. Moreover, we showed that CR and CE share research topics, both aiming to increase the brain's capacity to process information, thus supporting their integration in a larger perspective. Methodologically, despite limitations of a simple user-friendly approach, TM served well the reviewing process

Detecting extrasolar planets from stellar radial velocities using Bayesian evidence

Stellar radial velocity (RV) measurements have proven to be a very successful method for detecting extrasolar planets. Analysing RV data to determine the parameters of the extrasolar planets is a significant statistical challenge owing to the presence of multiple planets and various degeneracies between orbital parameters. Determining the number of planets favoured by the observed data is an even more difficult task. Bayesian model selection provides a mathematically rigorous solution to this problem by calculating marginal posterior probabilities of models with different number of planets, but the use of this method in extrasolar planetary searches has been hampered by the computational cost of the evaluating Bayesian evidence. Nonetheless, Bayesian model selection has the potential to improve the interpretation of existing observational data and possibly detect yet undiscovered planets. We present a new and efficient Bayesian method for determining the number of extrasolar planets, as well as for inferring their orbital parameters, without having to calculate directly the Bayesian evidence for models containing a large number of planets. Instead, we work iteratively and at each iteration obtain a conservative lower limit on the odds ratio for the inclusion of an additional planet into the model. We apply this method to simulated data-sets containing one and two planets and successfully recover the correct number of planets and reliable constraints on the orbital parameters. We also apply our method to RV measurements of HD 37124, 47 Ursae Majoris and HD 10180. For HD 37124, we confirm that the current data strongly favour a three-planet system. We find strong evidence for the presence of a fourth planet in 47 Ursae Majoris, but its orbital period is suspiciously close to one year, casting doubt on its validity. For HD 10180 we find strong evidence for a six-planet system.Comment: 12 pages, 6 figures, 12 tables. Added results obtained by applying the method to 47 Ursae Majoris and HD 10180. Accepted for publication in MNRA

Large scale distribution of total mass versus luminous matter from Baryon Acoustic Oscillations: First search in the SDSS-III BOSS Data Release 10

Baryon Acoustic Oscillations (BAOs) in the early Universe are predicted to leave an as yet undetected signature on the relative clustering of total mass versus luminous matter. A detection of this effect would provide an important confirmation of the standard cosmological paradigm and constrain alternatives to dark matter as well as non-standard fluctuations such as Compensated Isocurvature Perturbations (CIPs). We conduct the first observational search for this effect, by comparing the number-weighted and luminosity-weighted correlation functions, using the SDSS-III BOSS Data Release 10 CMASS sample. When including CIPs in our model, we formally obtain evidence at $3.2\sigma$ of the relative clustering signature and a limit that matches the existing upper limits on the amplitude of CIPs. However, various tests suggest that these results are not yet robust, perhaps due to systematic biases in the data. The method developed in this Letter, used with more accurate future data such as that from DESI, is likely to confirm or disprove our preliminary evidence.Comment: 6 pages, 2 figures, accepted for publication in PR

Elastic-plastic analyses using the solid-shell finite element SHB8PS and evaluation on sheet forming applications - COMPLAS XI

In this contribution, the formulation of the SHB8PS continuum shell finite element is extended to anisotropic elastic–plastic behavior models with combined isotropic-kinematic hardening at large deformations. The resulting element is then implemented into the commercial implicit finite element code Abaqus/Standard via the UEL subroutine. The SHB8PS element is an eight-node, three-dimensional brick with displacements as the only degrees of freedom and a preferential direction called the thickness. A reduced integration scheme is adopted using an arbitrary number of integration points along the thickness direction and only one integration point in the other directions. The hourglass modes due to this reduced integration are controlled using a physical stabilization technique together with an assumed strain method for the elimination of locking. Therefore, the element can be used to model thin structures while providing an accurate description of the various throughthickness phenomena. Its performance is assessed through several applications involving different types of non-linearities: geometric, material and that induced by contact. Particular attention is given to springback prediction for a Numisheet benchmark problem

Prediction of strain localization during sheet metal forming using bifurcation analysis and Gurson- type damage - Complas XI

The strain localization phenomenon that may occur during sheet metal forming represents a major cause of defective parts produced in the industry. Several instability criteria have been developed in the literature to predict the occurrence of these instabilities. The proposed work aims to couple a Gurson-type model to the Rice’s localization criterion. The implementation of the modeling is achieved via a user subroutine (Umat) in Abaqus/std using a Runge-Kutta explicit integration scheme. Finally, we show the effectiveness of the proposed coupling for the prediction of the formability of stretched metal sheets