Using Wearable Sensors to Measure Interpersonal Synchrony in Actors and Audience Members During a Live Theatre Performance

Studying social interaction in real-world settings is of increasing importance to social cognitive researchers. Theatre provides an ideal opportunity to study rich face-to-face interactions in a controlled, yet natural setting. Here we collaborated with Flute Theatre to investigate interpersonal synchrony between actors-actors, actors-audience and audience-audience within a live theatrical setting. Our 28 participants consisted of 6 actors and 22 audience members, with 5 of these audience members being audience participants in the show. The performance was a compilation of acting, popular science talks and demonstrations, and an audience participation period. Interpersonal synchrony was measured using inertial measurement unit (IMU) wearable accelerometers worn on the heads of participants, whilst audio-visual data recorded everything that occurred on the stage. Participants also completed post-show self-report questionnaires on their engagement with the overall scientists and actors performance. Cross Wavelet Transform (XWT) and Wavelet Coherence Transform (WCT) analysis were conducted to extract synchrony at different frequencies, pairing with audio-visual data. Findings revealed that XWT and WCT analysis are useful methods in extracting the multiple types of synchronous activity that occurs when people perform or watch a live performance together. We also found that audience members with higher ratings on questionnaire items such as the strength of their emotional response to the performance, or how empowered they felt by the performance, showed a high degree of interpersonal synchrony with actors during the acting segments of performance. We further found that audience members rated the scientists performance higher than the actors performance on questions related to their emotional response to the performance as well as, how uplifted, empowered, and connected to social issues they felt. This shows the types of potent connections audience members can have with live performances. Additionally, our findings highlight the importance of the performance context for audience engagement, in our case a theatre performance as part of public engagement with science rather than a stand-alone theatre performance. In sum we conclude that interdisciplinary real-world paradigms are an important and understudied route to understanding in-person social interactions

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

On the Adaptability and Effect of High Damping Rubber Bearings in the Seismic Resistance of Large Aqueducts

Being the critical hydraulic structure in the construction of national water diversion projects, the large-scale aqueduct is one of the indispensable buildings in the rational allocation of water resources. Moreover, its safe operation during an earthquake is related to the success of the national water network’s construction. In this paper, HDRBs (high damping rubber bearings) have been used as the seismic isolation device for the large aqueduct, considering the FSI (fluid solid interaction) between the water and the walls of the aqueduct, and the mechanical model of HDRBs has been constructed by the bilinear model. The dynamic responses of the large aqueduct under different ground motion excitations, including different peak ground accelerations (PGAs) and operating conditions, have been calculated using the precise integration method. At the same time, the influence of RB (rubber bearings) and HDRBs, two kinds of bearings, on the seismic response of the large aqueduct is compared and analyzed. The maximum reduction in natural frequency with HRDB is about 72%, compared with the use of RB under different working conditions. When there is substitution of HDRB for RB, the stresses in the concrete at the corresponding positions decrease from 1.87 MPa to about 0.71 MPa. The analysis shows that HDRBs are equipped with well seismic isolation and energy dissipation performance, which can effectively reduce the seismic responses and improve the seismic performance of the large aqueduct. In addition, it shows that HDRBs have well adaptability to different operating conditions, ground motion excitation, and PGA, which can be extended to the constructions of aqueduct projects with high seismic intensity and complex geological conditions

Development and Application of Intelligent Temperature Control System for Large Aqueduct

When the temperature rise and fall rates of a large-scale aqueduct with traditional water-cooling technology exceeds the standard, it is difficult to avoid the temperature change of aqueduct concrete deviating from its control curve in the process of temperature rise and fall by adjusting the water flow rate or cooling the water temperature of a water pipe only by manual experience. Aiming at such problems, an intelligent temperature control system for a large aqueduct body is developed and applied, which is composed of an information processing and decision-making module, simulation calculation module and information collection and control module, with real-time interactive information and real-time update of the temperature change control curve. The system is applied to the 1:30 Dongjia Village Aqueduct model experiment. The model experiment results show that the system can automatically adjust the water flow velocity of concrete according to the temperature variation control curve, and update the temperature variation control curve according to the changes of environmental parameters and cooling water parameters

Intelligent Recognition System Based on Contour Accentuation for Navigation Marks

Sensing navigational environment represented by navigation marks is an important task for unmanned ships and intelligent navigation systems, and the sensing can be performed by recognizing the images from a camera. In order to improve the image recognition accuracy, this paper combined a contour accentuation algorithm into a multiple scale attention mechanism-based classification model for navigation marks. Experimental results show that the method increases the accuracy of navigation mark classification from 95.98% to 96.53%. Based on the classification model, an intelligent navigation mark recognition system was developed for the Changjiang Nanjing Waterway Bureau, in which the model is deployed and updated by the TensorFlow Serving