Modeling the Subsurface Structure of Sunspots

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local helioseismology is the only means by which we can investigate subphotospheric structure. However, as current linear inversion techniques do not yet allow helioseismology to probe the internal structure with sufficient confidence to distinguish between the monolith and cluster models, the development of physically realistic sunspot models are a priority for helioseismologists. This is because they are not only important indicators of the variety of physical effects that may influence helioseismic inferences in active regions, but they also enable detailed assessments of the validity of helioseismic interpretations through numerical forward modeling. In this paper, we provide a critical review of the existing sunspot models and an overview of numerical methods employed to model wave propagation through model sunspots. We then carry out an helioseismic analysis of the sunspot in Active Region 9787 and address the serious inconsistencies uncovered by \citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find that this sunspot is most probably associated with a shallow, positive wave-speed perturbation (unlike the traditional two-layer model) and that travel-time measurements are consistent with a horizontal outflow in the surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic

Managing information for innovation using knowledge integration capability: The role of boundary spanning objects

Knowledge Integration (KI) or the capability to collate and process distinctive stocks of organizational information is central to innovation. Although an essential capability, KI is also challenging to accomplish in practice due to relational obstacles. The relational obstacles arise because of knowledge boundaries: (a) syntactic boundary where the challenge is to transfer the knowledge; (b) semantic boundary where the challenge is to translate the knowledge; and (c) pragmatic boundary, where the challenge is to transform the knowledge to realize relational rents. In this paper, we propose that these relational obstacles could be resolved through a common lexicon, common meaning, and common interests, or common knowledge of knowledge actors that can serve as potential drivers to realizing relational rents. Analysis of data collected from 139 small firms indicates that common meaning and common interests positively influence KI. Further, KI positively influences organizational innovation. Moreover, the results demonstrate that novelty plays a crucial role in affecting the strength of relational resources’ relationships with KI capability. As novelty increases, the importance of common meaning and common interests on KI capability increases. Our findings contribute to our understanding of the role of relational obstacles and KI and empirically assess the efficacy of boundary-spanning objects in facilitating KI capability and innovation

Measurements, Models, Systems and Design

531 s.