The first view of δ Scuti and γ Doradus stars with the TESS mission

We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilize the 2-min cadence TESS data for a sample of 117 stars to classify their behaviour regarding variability and place them in the Hertzsprung-Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74 per cent for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler.Fil: Antoci, Victoria. Stellar Astrophysics Centre; DinamarcaFil: Cunha, M. S.. Universidad de Porto; PortugalFil: Bowman, D. M.. Institute of Astronomy; BélgicaFil: Murphy, S. J.. Stellar Astrophysics Centre; Dinamarca. University of Sydney; AustraliaFil: Kurtz, D. W.. University of Central Lancashire; Reino UnidoFil: Bedding, T. R.. Stellar Astrophysics Centre; Dinamarca. University of Sydney; AustraliaFil: Borre, C. C.. Stellar Astrophysics Centre; DinamarcaFil: Christophe, S.. Universite de Paris I Pantheon - Sorbonne; Francia. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Daszynska Daszkiewicz, J.. Instytut Astronomiczny; PoloniaFil: Fox Machado, L.. Universidad Nacional Autónoma de México; MéxicoFil: García Hernández, A.. Universidad de Granada; EspañaFil: Ghasemi, Hamed. Institute For Advanced Studies In Basic Sciences; IránFil: Handberg, R.. Stellar Astrophysics Centre; DinamarcaFil: Hansen, Ted H.. Stellar Astrophysics Centre; DinamarcaFil: Hasanzadeh, A.. University Of Zanjan; IránFil: Houdek, G.. Stellar Astrophysics Centre; DinamarcaFil: Johnston, C.. Katholikie Universiteit Leuven; BélgicaFil: Justesen, A. B.. Stellar Astrophysics Centre; DinamarcaFil: Kahraman Alicavus, F.. Nicolaus Copernicus Astronomical Center Of The Polish Academy Of Sciences; PoloniaFil: Kotysz, K.. Instytut Astronomiczny, Uniwersytet Wrocławski; PoloniaFil: Latham, D.. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Matthews, J. M.. University of British Columbia; CanadáFil: Mønster, J.. Stellar Astrophysics Centre; DinamarcaFil: Niemczura, E.. Uniwersytet Wrocławski; PoloniaFil: Paunzen, E.. Masaryk University; República ChecaFil: Sánchez Arias, Julieta Paz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Pigulski, A.. Uniwersytet Wrocławski; PoloniaFil: Pepper, J.. Lehigh University; Estados UnidosFil: Richey Yowell, T.. Lehigh University; Estados UnidosFil: Safari, H.. University of Zanjan; Irá

Biosignals reflect pair-dynamics in collaborative work : EDA and ECG study of pair-programming in a classroom environment

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.Peer reviewe

The first view of δ Scuti and γ Doradus stars with the TESS mission

Abstract We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilise the 2-min cadence TESS data for a sample of 117 stars to classify their behaviour regarding variability and place them in the Hertzsprung-Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74% for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler

Summary data for tracer gas dispersion tests for landfill methane emission monitoring at a UK landfill

This dataset supports the publications: 1) Rees-White, T. C., M&oslash;nster, J., Beaven R. P., Scheutz, C. (2018) Measuring methane emissions from a UK landfill sing the tracer dispersion method and the influence of operational and environmental factors https://doi.org/10.1016/j.wasman.2018.03.023 2) Matacchiera F, Manes C, Beaven RP, Rees-White TC, Boano F, M&oslash;nster J and Scheutz C (2018). AERMOD as a Gaussian dispersion model for planning tracer gas dispersion tests for landfill methane emission quantification https://doi.org/10.1016/j.wasman.2018.02.007 Contents +++++++++ This dataset contains the data discussed within the papers listed above and in certain Figures from the Rees-White paper. The figures are as follows: Fig. 3. Atmospheric pressure and wind speed during the period of August 5th to August 14th, 2014. Start and end times of each TDM experiment are given as vertical lines Fig. 4. Incoming solar radiation and air temperature during the period of August 3th to August 14th, 2014. Start and end times of each TDM experiment are given as vertical lines Fig. 6 (a to f). Methane emission data for each transect in a TDM with average overall emission and the 95% confidence interval. The name of the monitoring route used for a given transect is also shown Fig. 7. Measured methane emissions vs. average wind speed for the six TDM trials. Linear regression is given (R2 = -0.82). Fig. 8. Individual transect data from TDM2 shown against estimated wind speed, interpolated between measurement points. Data are colour coded to reflect the monitoring route used. a) shows data between 18:07 and 20:09, and b) 20:59 to 22:14. Fig. 9. a) Average methane emission data from each monitoring route shown against measuring distance, b) Average methane emission rate from each monitoring route for a given TDM measured at different monitoring distances. Geographic location of this data collection: University of Southampton, U.K. Dataset available under a CC BY 4.0 licence Publisher: University of Southampton, U.K. Date: April 2018</span

AERMOD as a Gaussian dispersion model for planning tracer gas dispersion tests for landfill methane emission quantification

The measurement of methane emissions from landfills is important to the understanding of landfills' contribution to greenhouse gas emissions. The Tracer Dispersion Method (TDM) is becoming widely accepted as a technique, which allows landfill emissions to be quantified accurately provided that measurements are taken where the plumes of a released tracer-gas and landfill-gas are well-mixed. However, the distance at which full mixing of the gases occurs is generally unknown prior to any experimental campaign.To overcome this problem the present paper demonstrates that, for any specific TDM application, a simple Gaussian dispersion model (AERMOD) can be run beforehand to help determine the distance from the source at which full mixing conditions occur, and the likely associated measurement errors. An AERMOD model was created to simulate a series of TDM trials carried out at a UK landfill, and was benchmarked against the experimental data obtained. The model was used to investigate the impact of different factors (e.g. tracer cylinder placements, wind directions, atmospheric stability parameters) on TDM results to identify appropriate experimental set ups for different conditions.The contribution of incomplete vertical mixing of tracer and landfill gas on TDM measurement error was explored using the model. It was observed that full mixing conditions at ground level do not imply full mixing over the entire plume height. However, when full mixing conditions were satisfied at ground level, then the error introduced by variations in mixing higher up were always less than 10%.</p