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31. Integrative Mechanisms of Social Attention

Author(s):
Bio, Branden; Graziano, Michael
Abstract:
Monitoring the attention of others is fundamental to social cognition. Most of the literature on the topic assumes that our social cognitive machinery is tuned specifically to the gaze direction of others as a proxy for attention. This standard assumption reduces attention to an externally visible parameter. Here we show that this assumption is wrong and a deeper, more meaningful representation is involved. We presented subjects with two cues about the attentional state of a face: direction of gaze and emotional expression. We tested whether people relied predominantly on one cue, the other, or both. If the traditional view is correct, then the gaze cue should dominate. Instead, people employed a variety of strategies, some relying on gaze, some on expression, and some on an integration of cues. We also assessed people’s social cognitive ability using two, independent, standard tests. If the traditional view is correct, then social cognitive ability, as assessed by the independent tests, should correlate with the degree to which people successfully use the gaze cue to judge the attention state of the face. Instead, social cognitive ability correlated best with the degree to which people successfully integrated the cues together, instead of with the use of any one specific cue. The results suggest a rethink of a fundamental component of social cognition: monitoring the attention of others involves constructing a deep model that is informed by a combination of cues. Attention is a rich process and monitoring the attention of others involves a similarly rich representation.
Type:
Dataset
Issue Date:
22 July 2021

32. Inversion technique to obtain local ion temperature profiles for an axisymmetric plasma with toroidal and radial velocities

Author(s):
Bell, Ronald E.
Abstract:
A matrix inversion technique is derived to calculate local ion temperature from line-integrated measurements of an extended emission source in an axisymmetric plasma which exactly corrects for both toroidal velocity and radial velocity components. Local emissivity and toroidal velocity can be directly recovered from line-integrated spectroscopic measurements, but an independent measurement of the radial velocity is necessary to complete the temperature inversion. The extension of this technique to handle the radial velocity is relevant for magnetic reconnection and merging compression devices where temperature inversion from spectroscopic measurements is desired. A simulation demonstrates the effects of radial velocity on the determination of ion temperature.
Type:
Dataset
Issue Date:
February 2021

33. Multi-Fluid and Kinetic Models of Partially Ionized Magnetic Reconnection

Author(s):
Jara-Almonte, J.; Murphy, N.A.; Ji, H.
Abstract:
Magnetic reconnection in partially ionized plasmas is a ubiquitous and important phenomena in both laboratory and astrophysical systems. Here, simulations of partially ionized magnetic reconnection with well-matched initial conditions are performed using both multi-fluid and fully-kinetic approaches. Despite similar initial conditions, the time-dependent evolution differs between the two models. In multi-fluid models, the reconnection rate locally obeys either a decoupled Sweet-Parker scaling, where neutrals are unimportant, or a fully coupled Sweet-Parker scaling, where neutrals and ions are strongly coupled, depending on the resistivity. In contrast, kinetic models show a faster reconnection rate that is proportional to the fully-coupled, bulk Alfv\'en speed, $v_A^\star$. These differences are interpreted as the result of operating in different collisional regimes. Multi-fluid simulations are found to maintain $\nu_{ni}L/v_A^\star \gtrsim 1$, where $\nu_{ni}$ is the neutral-ion collision frequency and $L$ is the time-dependent current sheet half-length. This strongly couples neutrals to the reconnection outflow, while kinetic simulations evolve to allow $\nu_{ni}L/v_A^\star < 1$, decoupling neutrals from the reconnection outflow. Differences in the way reconnection is triggered may explain these discrepancies.
Type:
Dataset
Issue Date:
2021

37. Prediction of electron density and pressure profile shapes on NSTX-U using neural networks

Author(s):
Boyer, Mark; Chadwick, Jason
Abstract:
A new model for prediction of electron density and pressure profile shapes on NSTX and NSTX-U has been developed using neural networks. The model has been trained and tested on measured profiles from experimental discharges during the first operational campaign of NSTX-U. By projecting profiles onto empirically derived basis functions, the model is able to efficiently and accurately reproduce profile shapes. In order to project the performance of the model to upcoming NSTX-U operations, a large database of profiles from the operation of NSTX is used to test performance as a function of available data. The rapid execution time of the model is well suited to the planned applications, including optimization during scenario development activities, and real-time plasma control. A potential application of the model to real-time profile estimation is demonstrated.
Type:
Dataset
Issue Date:
February 2021

38. Princeton Open Ventilation Monitor

Author(s):
Bourrianne, Philippe; Chidzik, Stanley; Cohen, Daniel; Elmer, Peter; Hallowell, Thomas; Kilbaugh, Todd J.; Lange, David; Leifer, Andrew M.; Marlow, Daniel R.; Meyers, Peter D.; Normand, Edna; Nunes, Janine; Oh, Myungchul; Page, Lyman; Periera, Talmo; Pivarski, Jim; Schreiner, Henry; Stone, Howard A.; Tank, David W.; Thiberge, Stephan; Tully, Christopher
Abstract:
The detailed information on the design and construction of the Princeton Open Ventilation Monitor device and software are contained in this data repository. This information consists of the electrical design files, mechanical design files, bill of materials, human subject recording and analysis code, and a copy of the code repository for operating the patient monitors and central station.
Type:
Dataset, Software, and Image
Issue Date:
22 November 2021