A theoretical approach for the interpretation of pulsating PMS intermediate-mass stars

The investigation of the pulsation properties of pre-main-sequence intermediate-mass stars is a promising tool to evaluate the intrinsic properties of these stars and to constrain current evolutionary models. Many new candidates of this class have been discovered during the last decade and very accurate data are expected from space observations obtained for example with the CoRoT satellite. In this context we aim at developing a theoretical approach for the interpretation of observed frequencies, both from the already available ground-based observations and from the future more accurate and extensive CoRoT results. To this purpose we have started a project devoted to the computations of fine and extensive grids of asteroseismic models of intermediate mass pre-main-sequence stars. The obtained frequencies are used to derive an analytical relation between the large frequency separation and the stellar luminosity and effective temperature and to develop a tool to compare theory and observations in the echelle diagram. The predictive capabilities of the proposed method are verified through the application to two test stars. As a second step, we apply the procedure to two true observations from multisite campaigns and we are able to constrain their stellar parameters, in particular the mass, in spite of the small number of frequencies. We expect that with a significantly higher number of frequencies both the stellar mass and age could be constrained and, at the same time, the physics of the models could be tested.Comment: Accepted for publication on A&

Towards a network psychometrics approach to assessment: simulations for redundancy, dimensionality, and loadings

Research using network models in psychology has proliferated over the last decade. The popularity of network models has largely been driven by their alternative explanation for the emergence of psychological attributes—observed variables co-occur because they are causally coupled and dynamically reinforce each other, forming cohesive systems. Despite their rise in popularity, the growth of network models as a psychometric tool has remained relatively stagnant, mainly being used as a novel measurement perspective. In this dissertation, the goal is to expand the role of network models in modern psychometrics and to move towards using these models as a tool for the validation of assessment instruments. This paper presents three simulation studies and an empirical example that are designed to evaluate different aspects of the psychometric network approach to assessment: reducing redundancy, detecting dimensions, and estimating loadings. The first simulation evaluated two novel approaches for determining whether items are redundant, which is a key component for the accuracy and interpretation of network measures. The second simulation evaluated several different community detection algorithms, which are designed to detect dimensions in networks. The third simulation evaluated an adapted formulation of the network measure, node strength, and how it compares to factor loadings estimated by exploratory and confirmatory factor analysis. The results of the simulations demonstrate that network models can be used as an effective psychometric tool and one that is on par with more traditional methods. Finally, in the empirical example, the methods from the simulations are applied to a real-world dataset measuring personality. This example demonstrated that these methods are not only effective, but they can validate whether an assessment instrument is consistent with theoretical and empirical expectations. With these methods in hand, network models are poised to take the next step towards becoming a robust psychometric tool

Remotely close associations: openness to experience and semantic memory structure

Openness to experience—the enjoyment of novel experiences, ideas, and unconventional perspectives—has shown several connections to cognition that suggest open people might have different cognitive processes than those low in openness. People high in openness are more creative, have broader general knowledge, and show greater cognitive flexibility. The associative structure of semantic memory might be one such cognitive process that people in openness differ in. In this study, 497 people completed a measure of openness to experience and verbal fluency. Three groups of high (n = 115), moderate (n = 121), and low (n = 118) openness were created to construct semantic networks—graphical models of semantic associations that provide quantifiable representations of how these associations are organized—from their verbal fluency responses. The groups were compared on graph theory measures of their respective semantic networks. The semantic network analysis revealed that as openness increased, the rigidity of the semantic structure decreased and the interconnectivity increased, suggesting greater flexibility of associations. Semantic structure also became more condensed and had better integration, which facilitates open people’s ability to reach more unique associations. These results were supported by open people coming up with more individual and unique responses, starting with less conventional responses, and having a flatter frequency proportion slope than less open people. In summary, the semantic network structure of people high in openness to experience supports the retrieval of remote concepts via short associative pathways, which promotes unique combinations of disparate concepts that are key for creative cognition

The Octave (Birmingham - Sheffield Hallam) automated pipeline for extracting oscillation parameters of solar-like main-sequence stars

The number of main-sequence stars for which we can observe solar-like oscillations is expected to increase considerably with the short-cadence high-precision photometric observations from the NASA Kepler satellite. Because of this increase in number of stars, automated tools are needed to analyse these data in a reasonable amount of time. In the framework of the asteroFLAG consortium, we present an automated pipeline which extracts frequencies and other parameters of solar-like oscillations in main-sequence and subgiant stars. The pipeline uses only the timeseries data as input and does not require any other input information. Tests on 353 artificial stars reveal that we can obtain accurate frequencies and oscillation parameters for about three quarters of the stars. We conclude that our methods are well suited for the analysis of main-sequence stars, which show mainly p-mode oscillations.Comment: accepted by MNRA

ASTEC -- the Aarhus STellar Evolution Code

The Aarhus code is the result of a long development, starting in 1974, and still ongoing. A novel feature is the integration of the computation of adiabatic oscillations for specified models as part of the code. It offers substantial flexibility in terms of microphysics and has been carefully tested for the computation of solar models. However, considerable development is still required in the treatment of nuclear reactions, diffusion and convective mixing.Comment: Astrophys. Space Sci, in the pres

Understanding inner music: A dimensional approach to musical imagery

Musical imagery—hearing music inside your head that isn’t playing in the environment—is a common yet complex experience. To capture the diversity of musical imagery, the present research develops a new conceptual framework consisting of five dimensions, including a distinction between initiation and management as different ways in which musical imagery can be voluntary. A dimensional approach can represent both common and unusual forms of musical imagery, and it can highlight conceptual similarities between seemingly different experiences. In an experience-sampling study, musicians and people from the university community (n = 132) were contacted throughout the day via a smartphone app and asked about their in vivo experiences with musical imagery, with an emphasis on five dimensions: valence, repetitiveness, vividness, length, and mental control. The results indicated substantial variability at both the within-person and between-person levels on each dimension—people have a wide variety of musical imagery experiences, not a few types. A within-person network model illustrated that the dimensions were internally coherent and distinct from each other. Taken together, the findings reveal rich heterogeneity in musical imagery and indicate that mental control over musical imagery is both common and multifaceted

Network structure of the Wisconsin Schizotypy Scales—Short Forms: Examining psychometric filtering approaches

Schizotypy is a multidimensional construct that provides a useful framework for understanding the etiology, development, and risk for schizophrenia-spectrum disorders. Past research has applied traditional methods, such as factor analysis, to uncovering common dimensions of schizotypy. In the present study, we aimed to advance the construct of schizotypy, measured by the Wisconsin Schizotypy Scales–Short Forms (WSS-SF), beyond this general scope by applying two different psychometric network filtering approaches—the state-of-the-art approach (lasso), which has been employed in previous studies, and an alternative approach (information-filtering networks; IFNs). First, we applied both filtering approaches to two large, independent samples of WSS-SF data (ns = 5,831 and 2,171) and assessed each approach’s representation of the WSS-SF’s schizotypy construct. Both filtering approaches produced results similar to those from traditional methods, with the IFN approach producing results more consistent with previous theoretical interpretations of schizotypy. Then we evaluated how well both filtering approaches reproduced the global and local network characteristics of the two samples. We found that the IFN approach produced more consistent results for both global and local network characteristics. Finally, we sought to evaluate the predictability of the network centrality measures for each filtering approach, by determining the core, intermediate, and peripheral items on the WSS-SF and using them to predict interview reports of schizophrenia-spectrum symptoms. We found some similarities and differences in their effectiveness, with the IFN approach’s network structure providing better overall predictive distinctions. We discuss the implications of our findings for schizotypy and for psychometric network analysis more generally

Creative fixation is no laughing matter: The effects of funny and unfunny examples on humor production

How do people come up with humorous ideas? In creative cognition research, exposure to good examples sometimes causes fixation (people get “stuck” on the examples) but other times sparks inspiration (people's responses are more creative). The present research examined the effects of funny and unfunny examples on joke production. A sample of 175 adults read scenarios that they completed with funny responses. All participants were instructed to be funny, but before responding they read (a) funny responses as examples of good responses to emulate, (b) unfunny responses as examples of poor responses to avoid, or (c) no examples. The participants’ own responses were rated for funniness and for similarity to the example responses, and response times were recorded. Reading either funny or unfunny examples, compared to no examples, caused people to come up with funnier jokes. Similarity to the examples was low in all conditions, so fixation was relatively modest, but people who saw unfunny examples spent more time coming up with their responses. Taken together, the findings support the growing literature showing that examples are often inspiring rather than constraining, and they imply that good and bad examples spark creative thought via different paths

On equilibrium tides in fully convective planets and stars

We consider the tidal interaction of a fully convective primary star and a point mass. Using a normal mode decomposition we calculate the evolution of the primary angular velocity and orbit for arbitrary eccentricity e. The dissipation acting on the tidal perturbation is associated with convective turbulence. A novel feature of the Paper is that, to take into account of the fact that there is a relaxation time t_{c}, being the turn-over time of convective eddies, associated with the process, this is allowed to act non locally in time, producing a dependence of the dissipation on tidal forcing frequency. Results are expressed in terms of the Fourier coefficients of the tidal potential. We find analytical approximations for these valid for $e>0.2$. When the tidal response is frequency independent, our results are equivalent to those obtained in the standard constant time lag approximation. When there is the frequency dependence of the dissipative response, the evolution can differ drastically. In that case the system can evolve through a sequence of spin-orbit corotation resonances with Omega_{r}/Omega_{orb}=n/2, where Omega_{r} and Omega_{orb} are the rotation and orbital frequencies and n is an integer. We study this case analytically and numerically.Comment: The size of the shown abstract is reduced. Submitted to MNRA