Surface heat transfer due to sliding bubble motion

International audienc

Slot Machine Near Wins: Effects on Pause and Sensitivity to Win Ratios

When a near-win outcome occurs on a slot machine, stimuli presented resemble those presented when money is won, but no money is won. Research has shown that gamblers prefer and play for longer on slot machines that present near wins. One explanation for this is that near wins are conditioned reinforcers. If so, near wins would produce longer latencies to the next response than clear losses. Another explanation is that near wins produce frustration; if so, then near wins would produce shorter response latencies. The two current experiments manipulated win ratio across two concurrently available slot machines and also manipulated near win frequency. Latencies were longer following near wins, consistent with near wins functioning as conditioned reinforcers. We also explored the effects of near wins on sensitivity to relative win rate and found that higher rates of near wins were associated with greater sensitivity to relative win frequency, an effect also consistent with near wins as conditioned reinforcers

Thermal performance predictions and tests of a novel type of flat plate solar thermal collectors by integrating with a freeze tolerance solution

A novel design concept of Flat Plate Solar Collectors (FPSCs) is conceived and developed by integrating with a freeze-tolerant (so-called 'ice immune') solution using flexible silicone tubing. It is intended to directly run water in the solar thermal systems with the FPSCs instead of using expensive anti-freeze fluids, and to remove secondary heat transfer facilities (e.g. an extra tank with a buried heat exchanger). Successful development of such kind of solar thermal collectors will enable a reduction of installed cost of conventional solar thermal systems without needing secondary heat transfer facilities. In the prophase design, thermal performances of FPSCs with two configurations, i.e. the serpentine tube type and the header riser type, were predicted based on the collector lumped thermal capacitance model alongside CFD (Computational Fluid Dynamics) calculations. Then two prototypes of FPSCs with the ice-immune silicone tubing (one AES serpentine tube type, one modified Chinese micro-heat-pipe-array panel) were made to determine the collector performance and compared to an original AES solar keymark reference panel via experimental tests. The results show that the Chinese micro-heat-pipe-array panel performs better than the AES header riser solar keymark panel in terms of flow rate per m2 collector aperture area, while the AES serpentine tube panel with silicone tubing performs somewhat lower than the solar keymark with T_m^*≤0.035 and better than the solar keymark when T_m^*>0.035. The serpentine tube panel and the Chinese micro-heat-pipe-array panel both integrated with silicone tubing for freeze tolerance are proven to be effective as the modification doesn’t compromise the collector thermal performance markedly

Altering Pace Control and Pace Regulation: Attentional Focus Effects during Running

Purpose: To date there are no published studies directly comparing self-controlled and externally-controlled pace endurance tasks. However, previous research suggests pace control may impact on cognitive strategy use and effort perceptions. The primary aim of this study was to investigate the effects of manipulating perception of pace control on attentional focus, physiological, and psychological outcomes during running. A secondary aim was to determine the reproducibility of self-paced running performance when regulated by effort perceptions. Methods: Twenty experienced endurance runners completed four 3 km time-trials on a treadmill. Subjects completed two self-controlled pace (SC), one perceived exertion clamped (PE), and one externally-controlled pace (EC) time-trial. PE and EC were completed in a counterbalanced order. Pacing strategy for EC and perceived exertion instructions for PE replicated subjects' fastest SC time-trial. Results: Subjects reported a greater focus on cognitive strategies such as relaxing and optimizing running action during EC than SC. Mean heart rate was 2% lower during EC than SC despite an identical pacing strategy. Perceived exertion did not differ between the three conditions. However, increased internal sensory monitoring coincided with elevated effort perceptions in some subjects during EC, and a 10% slower completion time for PE (13.0 ± 1.6 min) than SC (11.8 ± 1.2 min). Conclusion: Altering pace control and pace regulation impacted on attentional focus. External control over pacing may facilitate performance, particularly when runners engage attentional strategies conducive to improved running efficiency. However, regulating pace based on effort perceptions alone may result in excessive monitoring of bodily sensations and a slower running speed. Accordingly, attentional focus interventions may prove beneficial for some athletes to adopt task-appropriate attentional strategies to optimize performance

Forecasting water temperature in lakes and reservoirs using seasonal climate prediction

ABSTRACT: Seasonal climate forecasts produce probabilistic predictions of meteorological variables for subsequent months. This provides a potential resource to predict the influence of seasonal climate anomalies on surface water balance in catchments and hydro-thermodynamics in related water bodies (e.g., lakes or reservoirs). Obtaining seasonal forecasts for impact variables (e.g., discharge and water temperature) requires a link between seasonal climate forecasts and impact models simulating hydrology and lake hydrodynamics and thermal regimes. However, this link remains challenging for stakeholders and the water scientific community, mainly due to the probabilistic nature of these predictions. In this paper, we introduce a feasible, robust, and open-source workflow integrating seasonal climate forecasts with hydrologic and lake models to generate seasonal forecasts of discharge and water temperature profiles. The workflow has been designed to be applicable to any catchment and associated lake or reservoir, and is optimized in this study for four catchment-lake systems to help in their proactive management. We assessed the performance of the resulting seasonal forecasts of discharge and water temperature by comparing them with hydrologic and lake (pseudo)observations (reanalysis). Precisely, we analysed the historical performance using a data sample of past forecasts and reanalysis to obtain information about the skill (performance or quality) of the seasonal forecast system to predict particular events. We used the current seasonal climate forecast system (SEAS5) and reanalysis (ERA5) of the European Centre for Medium Range Weather Forecasts (ECMWF). We found that due to the limited predictability at seasonal time-scales over the locations of the four case studies (Europe and South of Australia), seasonal forecasts exhibited none to low performance (skill) for the atmospheric variables considered. Nevertheless, seasonal forecasts for discharge present some skill in all but one case study. Moreover, seasonal forecasts for water temperature had higher performance in natural lakes than in reservoirs, which means human water control is a relevant factor affecting predictability, and the performance increases with water depth in all four case studies. Further investigation into the skillful water temperature predictions should aim to identify the extent to which performance is a consequence of thermal inertia (i.e., lead-in conditions).This is a contribution of the WATExR project (watexr.eu/), which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by MINECO-AEI (ES), FORMAS (SE), BMBF (DE), EPA (IE), RCN (NO), and IFD (DK), with co-funding by the European Union (Grant 690462 ). MINECO-AEI funded this research through projects PCIN- 2017-062 and PCIN-2017-092. We thank all water quality and quantity data providers: Ens d’Abastament d’Aigua Ter-Llobregat (ATL, https://www.atl.cat/es ), SA Water ( https://www.sawater.com. au/ ), Ruhrverband ( www.ruhrverband.de ), NIVA ( www.niva.no ) and NVE ( https://www.nve.no/english/ ). We acknowledge the contribution of the Copernicus Climate Change Service (C3S) in the production of SEAS5. C3S provided the computer time for the generation of the re-forecasts for SEAS5 and for the production of the ocean reanalysis (ORAS5), used as initial conditions for the SEAS5 re-forecasts