Combined use of the GGSFT data base and on Board Marine Collected Data to Model the Moho Beneath the Powell Basin, Antarctica

The Powell Basin is a small oceanic basin located at the NE end of the Antarctic Peninsula developed during the Early Miocene and mostly surrounded by the continental crusts of the South Orkney Microcontinent, South Scotia Ridge and Antarctic Peninsula margins. Gravity data from the SCAN 97 cruise obtained with the R/V Hespérides and data from the Global Gravity Grid and Sea Floor Topography (GGSFT) database (Sandwell and Smith, 1997) are used to determine the 3D geometry of the crustal-mantle interface (CMI) by numerical inversion methods. Water layer contribution and sedimentary effects were eliminated from the Free Air anomaly to obtain the total anomaly. Sedimentary effects were obtained from the analysis of existing and new SCAN 97 multichannel seismic profiles (MCS). The regional anomaly was obtained after spectral and filtering processes. The smooth 3D geometry of the crustal mantle interface obtained after inversion of the regional anomaly shows an increase in the thickness of the crust towards the continental margins and a NW-SE oriented axis of symmetry coinciding with the position of an older oceanic spreading axis. This interface shows a moderate uplift towards the western part and depicts two main uplifts to the northern and eastern sectors.

Dynamics of flow: a nonlinear perspective

The aims of this study are to consider the experience of flow from a nonlinear dynamics perspective. The processes and temporal nature of intrinsic motivation and flow, would suggest that flow experiences fluctuate over time in a dynamical fashion. Thus it can be argued that the potential for chaos is strong. The sample was composed of 20 employees (both full and part time) recruited from a number of different organizations and work backgrounds. The Experience Sampling Method (ESM) was used for data collection. Once obtained the temporal series, they were subjected to various analyses proper to the com- plexity theory (Visual Recurrence Analysis and Surrogate Data Analysis). Results showed that in 80% of the cases, flow presented a chaotic dynamic, in that, flow experiences delineated a complex dynamic whose patterns of change were not easy to predict. Implications of the study, its limitations and future research are discussed.