114 resultados para Driver feedback


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We quantify the effect of the snow-albedo feedback on Swiss spring temperature trends using daily temperature and snow depth measurements from six station pairs for the period 1961–2011. We show that the daily mean 2-m temperature of a spring day without snow cover is on average 0.4 °C warmer than one with snow cover at the same location. This estimate is comparable with estimates from climate modelling studies. Caused by the decreases in snow pack, the snow-albedo feedback amplifies observed temperature trends in spring. The influence is small and confined to areas around the upward-moving snow line in spring and early summer. For the 1961–2011 period, the related temperature trend increases are in the order of 3–7 % of the total observed trend.

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Increasing optical depth poleward of 45° is a robust response to warming in global climate models. Much of this cloud optical depth increase has been hypothesized to be due to transitions from ice-dominated to liquid-dominated mixed-phase cloud. In this study, the importance of liquid-ice partitioning for the optical depth feedback is quantified for 19 Coupled Model Intercomparison Project Phase 5 models. All models show a monotonic partitioning of ice and liquid as a function of temperature, but the temperature at which ice and liquid are equally mixed (the glaciation temperature) varies by as much as 40 K across models. Models that have a higher glaciation temperature are found to have a smaller climatological liquid water path (LWP) and condensed water path and experience a larger increase in LWP as the climate warms. The ice-liquid partitioning curve of each model may be used to calculate the response of LWP to warming. It is found that the repartitioning between ice and liquid in a warming climate contributes at least 20% to 80% of the increase in LWP as the climate warms, depending on model. Intermodel differences in the climatological partitioning between ice and liquid are estimated to contribute at least 20% to the intermodel spread in the high-latitude LWP response in the mixed-phase region poleward of 45°S. It is hypothesized that a more thorough evaluation and constraint of global climate model mixed-phase cloud parameterizations and validation of the total condensate and ice-liquid apportionment against observations will yield a substantial reduction in model uncertainty in the high-latitude cloud response to warming.

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Objective: To introduce a new approach to problem based learning (PBL) used in the context of medicinal chemistry practical class teaching pharmacy students. Design: The described chemistry practical is based on independent studies by small groups of undergraduate students (4-5), who design their own practical work taking relevant professional standards into account. Students are carefully guided by feedback and acquire a set of skills important to their future profession as healthcare professionals. This model has been tailored to the application of PBL in a chemistry practical class setting for a large student cohort (150 students). Assessment: The achievement of learning outcomes is based on the submission of relevant documentation including a certificate of analysis, in addition to peer assessment. Some of the learning outcomes are also assessed in the final written examination at the end of the academic year. Conclusion: The described design of a novel PBL chemistry laboratory course for pharmacy students has been found to be successful. Self-reflective learning and engagement with feedback were encouraged, and students enjoyed the challenging learning experience. Skills that are highly essential for the students’ future careers as healthcare professionals are promoted.

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A body of research suggests that the provision of energy feedback information to building users can elicit significant energy reductions through behaviour change. However, most studies have focused on energy use in homes and the assessment of interventions and technologies, to the neglect of the non-domestic context and broader issues arising from the introduction of feedback technologies. To address this gap, a non-domestic case study explores the delivery of personalized energy feedback to office workers through a novel system utilizing wireless technologies. The research demonstrates advantages of monitoring occupancy and quantifying energy use from specific behaviours as a basis for effective energy feedback; this is particularly important where there are highly disaggregated forms of energy use and a range of locations for that activity to take place. Quantitative and qualitative data show that personalized feedback can help individuals identify energy reduction opportunities. However, the analysis also highlights important contextual barriers and issues that need to be addressed when utilizing feedback technologies in the workplace. If neglected, these issues may limit the effective take-up of feedback interventions.

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Exploiting the observed robust relationships between temperature and optical depth in extratropical clouds, we calculate the shortwave cloud feedback from historical data, by regressing observed and modeled cloud property histograms onto local temperature in middle to high southern latitudes. In this region, all CMIP5 models and observational data sets predict a negative cloud feedback, mainly driven by optical thickening. Between 45° and 60°S, the mean observed shortwave feedback (−0.91 ± 0.82 W m−2 K−1, relative to local rather than global mean warming) is very close to the multimodel mean feedback in RCP8.5 (−0.98 W m−2 K−1), despite differences in the meridional structure. In models, historical temperature-cloud property relationships reliably predict the forced RCP8.5 response. Because simple theory predicts this optical thickening with warming, and cloud amount changes are relatively small, we conclude that the shortwave cloud feedback is very likely negative in the real world at middle to high latitudes.

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Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.

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Observations and climate models suggest significant decadal variability within the North Atlantic subpolar gyre (NA SPG), though observations are sparse and models disagree on the details of this variability. Therefore, it is important to understand 1) the mechanisms of simulated decadal variability, 2) which parts of simulated variability are more faithful representations of reality, and 3) the implications for climate predictions. Here, we investigate the decadal variability in the NA SPG in the state-of-the-art, high resolution (0.25◦ ocean resolution), climate model ‘HadGEM3’. We find a decadal mode with a period of 17 years that explains 30% of the annual variance in related indices. The mode arises due to the advection of heat content anomalies, and shows asymmetries in the timescale of phase reversal between positive and negative phases. A negative feedback from temperature-driven density anomalies in the Labrador Sea (LS) allows for the phase reversal. The North Atlantic Oscillation (NAO), which exhibits the same periodicity, amplifies the mode. The atmosphere-ocean coupling is stronger during positive rather than negative NAO states, explaining the asymmetry. Within the NA SPG, there is potential predictability arising partly from this mode for up to 5 years. There are important similarities between observed and simulated variability, such as the apparent role for the propagation of heat content anomalies. However, observations suggest interannual LS density anomalies are salinity-driven. Salinity control of density would change the temperature feedback to the south, possibly limiting real-world predictive skill in the southern NA SPG with this model. Finally, to understand the diversity of behaviours, we analyse 42 present-generation climate models. Temperature and salinity biases are found to systematically influence the driver of density variability in the LS. Resolution is a good predictor of the biases. The dependence of variability on the background state has important implications for decadal predictions.

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Anticipating synchronization has been recently proposed as a mechanism of interaction in dynamical systems which are able to bring about predictions of future states of a driver system. We suggest that an interesting insight into the anticipating synchronization can be obtained by the renormalization of the time scale in the driven system. Our approach directly links the feedback delay of the driven system with the renormalized time scale of the driven system, identifying the main component in the anticipating synchronization paradigm and suggesting an alternative method to generate the anticipating and the lagging synchronization.