Parametric preference functionals under risk in the gain domain: a Bayesian analysis

The performance of rank dependent preference functionals under risk is comprehensively evaluated using Bayesian model averaging. Model comparisons are made at three levels of heterogeneity plus three ways of linking deterministic and stochastic models: the differences in utilities, the differences in certainty equivalents and contextualutility. Overall, the"bestmodel", which is conditional on the form of heterogeneity is a form of Rank Dependent Utility or Prospect Theory that cap tures the majority of behaviour at both the representative agent and individual level. However, the curvature of the probability weighting function for many individuals is S-shaped, or ostensibly concave or convex rather than the inverse S-shape commonly employed. Also contextual utility is broadly supported across all levels of heterogeneity. Finally, the Priority Heuristic model, previously examined within a deterministic setting, is estimated within a stochastic framework, and allowing for endogenous thresholds does improve model performance although it does not compete well with the other specications considered.

Carbon trading for phosphorus gain: the balance between rhizosphere carboxylates and arbuscular mycorrhizal symbiosis in plant phosphorus acquisition

Two key plant adaptations for phosphorus (P) acquisition are carboxylate exudation into the rhizosphere and mycorrhizal symbioses. These target different soil P resources, presumably with different plant carbon costs. We examined the effect of inoculation with arbuscular mycorrhizal fungi (AMF) on amount of rhizosphere carboxylates and plant P uptake for 10 species of low-P adapted Kennedia grown for 23 weeks in low-P sand. Inoculation decreased carboxylates in some species (up to 50%), decreased plant dry weight (21%) and increased plant P content (23%). There was a positive logarithmic relationship between plant P content and the amount of rhizosphere citric acid for inoculated and uninoculated plants. Causality was indicated by experiments using sand where little citric acid was lost from the soil solution over 2 h and citric acid at low concentrations desorbed P into the soil solution. Senesced leaf P concentration was often low and P-resorption efficiencies reached >90%. In conclusion, we propose that mycorrhizally mediated resource partitioning occurred because inoculation reduced rhizosphere carboxylates, but increased plant P uptake. Hence, presumably, the proportion of plant P acquired from strongly sorbed sources decreased with inoculation, while the proportion from labile inorganic P increased. Implications for plant fitness under field conditions now require investigation.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.