Variations of the solar granulation motions with height using the GOLF/SoHO experiment

Below 1 mHz, the power spectrum of helioseismic velocity measurements is dominated by the spectrum of convective motions (granulation and supergranulation) making it difficult to detect the low-order acoustic modes and the gravity modes. We want to better understand the behavior of solar granulation as a function of the observing height in the solar atmosphere and with magnetic activity during solar cycle 23. We analyze the Power Spectral Density (PSD) of eleven years of GOLF/SOHO velocity-time series using a Harvey-type model to characterize the properties of the convective motions in the solar oscillation power spectrum. We study then the evolution of the granulation with the altitude in the solar atmosphere and with the solar activity. First, we show that the traditional use of a lorentzian profile to fit the envelope of the p modes is not well suitable for GOLF data. Indeed, to properly model the solar spectrum, we need a second lorentzian profile. Second, we show that the granulation clearly evolves with the height in the photosphere but does not present any significant variation with the activity cycle.Comment: Paper accepted in A&A. 7 pages, 4 figures, 2 table

The effects of forcing and dissipation on phase transitions in thin granular layers

Recent experimental and computational studies of vibrated thin layers of identical spheres have shown transitions to ordered phases similar to those seen in equilibrium systems. Motivated by these results, we carry out simulations of hard inelastic spheres forced by homogenous white noise. We find a transition to an ordered state of the same symmetry as that seen in the experiments, but the clear phase separation observed in the vibrated system is absent. Simulations of purely elastic spheres also show no evidence for phase separation. We show that the energy injection in the vibrated system is dramatically different in the different phases, and suggest that this creates an effective surface tension not present in the equilibrium or randomly forced systems. We do find, however, that inelasticity suppresses the onset of the ordered phase with random forcing, as is observed in the vibrating system, and that the amount of the suppression is proportional to the degree of inelasticity. The suppression depends on the details of the energy injection mechanism, but is completely eliminated when inelastic collisions are replaced by uniform system-wide energy dissipation.Comment: 10 pages, 5 figure

The onset of solar cycle 24: What global acoustic modes are telling us

We study the response of the low-degree, solar p-mode frequencies to the unusually extended minimum of solar surface activity since 2007. A total of 4768 days of observations collected by the space-based, Sun-as-a-star helioseismic GOLF instrument are analyzed. A multi-step iterative maximum-likelihood fitting method is applied to subseries of 365 days and 91.25 days to extract the p-mode parameters. Temporal variations of the l=0, 1, and 2 p-mode frequencies are then obtained from April 1996 to May 2009. While the p-mode frequency shifts are closely correlated with solar surface activity proxies during the past solar cycles, the frequency shifts of the l=0 and l=2 modes show an increase from the second half of 2007, when no significant surface activity is observable. On the other hand, the l=1 modes follow the general decreasing trend of the solar surface activity. The different behaviours between the l=0 and l=2 modes and the l=1 modes can be interpreted as different geometrical responses to the spatial distribution of the solar magnetic field beneath the surface of the Sun. The analysis of the low-degree, solar p-mode frequency shifts indicates that the solar activity cycle 24 started late 2007, despite the absence of activity on the solar surface.Comment: To be accepted by A&A (with minor revisions), 4 pages, 3 figures, 1 tabl

Sensitivity analysis of the solar rotation to helioseismic data from GONG, GOLF and MDI observations

Accurate determination of the rotation rate in the radiative zone of the sun from helioseismic observations requires rotational frequency splittings of exceptional quality as well as reliable inversion techniques. We present here inferences based on mode parameters calculated from 2088-days long MDI, GONG and GOLF time series that were fitted to estimate very low frequency rotational splittings (nu < 1.7 mHz). These low frequency modes provide data of exceptional quality, since the width of the mode peaks is much smaller than the rotational splitting and hence it is much easier to separate the rotational splittings from the effects caused by the finite lifetime and the stochastic excitation of the modes. We also have implemented a new inversion methodology that allows us to infer the rotation rate of the radiative interior from mode sets that span l=1 to 25. Our results are compatible with the sun rotating like a rigid solid in most of the radiative zone and slowing down in the core (R_sun < 0.2). A resolution analysis of the inversion was carried out for the solar rotation inverse problem. This analysis effectively establishes a direct relationship between the mode set included in the inversion and the sensitivity and information content of the resulting inferences. We show that such an approach allows us to determine the effect of adding low frequency and low degree p-modes, high frequency and low degree p-modes, as well as some g-modes on the derived rotation rate in the solar radiative zone, and in particular the solar core. We conclude that the level of uncertainties that is needed to infer the dynamical conditions in the core when only p-modes are included is unlikely to be reached in the near future, and hence sustained efforts are needed towards the detection and characterization of g-modes.Comment: Accepted for publication in Astrophysical journal. 15 pages, 19 figure

Prediction of protein-protein interaction types using association rule based classification

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Park et alBackground: Protein-protein interactions (PPI) can be classified according to their characteristics into, for example obligate or transient interactions. The identification and characterization of these PPI types may help in the functional annotation of new protein complexes and in the prediction of protein interaction partners by knowledge driven approaches. Results: This work addresses pattern discovery of the interaction sites for four different interaction types to characterize and uses them for the prediction of PPI types employing Association Rule Based Classification (ARBC) which includes association rule generation and posterior classification. We incorporated domain information from protein complexes in SCOP proteins and identified 354 domain-interaction sites. 14 interface properties were calculated from amino acid and secondary structure composition and then used to generate a set of association rules characterizing these domain-interaction sites employing the APRIORI algorithm. Our results regarding the classification of PPI types based on a set of discovered association rules shows that the discriminative ability of association rules can significantly impact on the prediction power of classification models. We also showed that the accuracy of the classification can be improved through the use of structural domain information and also the use of secondary structure content. Conclusion: The advantage of our approach is that we can extract biologically significant information from the interpretation of the discovered association rules in terms of understandability and interpretability of rules. A web application based on our method can be found at http://bioinfo.ssu.ac.kr/~shpark/picasso/SHP was supported by the Korea Research Foundation Grant funded by the Korean Government(KRF-2005-214-E00050). JAR has been supported by the Programme Alβan, the European Union Programme of High level Scholarships for Latin America, scholarship E04D034854CL. SK was supported by Soongsil University Research Fund