Using attribute importance rankings within discrete choice experiments: an application to valuing bread attributes

We present a new Bayesian econometric specification for a hypothetical Discrete Choice Experiment (DCE) incorporating respondent ranking information about attribute importance. Our results indicate that a DCE debriefing question that asks respondents to rank the importance of attributes helps to explain the resulting choices. We also examine how mode of survey delivery (online and mail) impacts model performance, finding that results are not substantively a§ected by the mode of survey delivery. We conclude that the ranking data is a complementary source of information about respondent utility functions within hypothetical DCEs

The origins and impact of proportional representation

This article in the peer-reviewed Oxford Bibliographies series, gives an introduction to the literatures on the varieties, origins, and effects of proportional electoral systems.

Representation of model error in a convective-scale ensemble prediction system

In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.

Nationalised large-scale mining, trade unions and community representation: perspectives from Northern Madagascar

This article critically explores the nature and purpose of relationships and inter-dependencies between stakeholders in the context of a parastatal chromite mining company in the Betsiboka Region of Northern Madagascar. An examination of the institutional arrangements at the interface between the mining company and local communities identified power hierarchies and dependencies in the context of a dominant paternalistic environment. The interactions, inter alia, limited social cohesion and intensified the fragility and weakness of community representation, which was further influenced by ethnic hierarchies between the varied community groups; namely, indigenous communities and migrants to the area from different ethnic groups. Moreover, dependencies and nepotism, which may exist at all institutional levels, can create civil society stakeholder representatives who are unrepresentative of the society they are intended to represent. Similarly, a lack of horizontal and vertical trust and reciprocity inherent in Malagasy society engenders a culture of low expectations regarding transparency and accountability, which further catalyses a cycle of nepotism and elite rent-seeking behaviour. On the other hand, leaders retain power with minimal vertical delegation or decentralisation of authority among levels of government and limit opportunities to benefit the elite, perpetuating rent-seeking behaviour within the privileged minority. Within the union movement, pluralism and the associated politicisation of individual unions restricts solidarity, which impacts on the movement’s capacity to act as a cohesive body of opinion and opposition. Nevertheless, the unions’ drive to improve their social capital has increased expectations of transparency and accountability, resulting in demands for greater engagement in decision-making processes.

A semiotic framework for information representation of energy consumption in office buildings

Taking a perspective from a whole building lifecycle, occupier's actions could account for about 50% of energy. However occupants' activities influence building energy performance is still a blind area. Building energy performance is thought to be the result of a combination of building fabrics, building services and occupants' activities, along with their interactions. In this sense, energy consumption in built environment is regarded as a socio-technical system. In order to understand how such a system works, a range of physical, technical and social information is involved that needs to be integrated and aligned. This paper has proposed a semiotic framework to add value for Building Information Modelling, incorporating energy-related occupancy factors in a context of office buildings. Further, building information has been addressed semantically to describe a building space from the facility management perspective. Finally, the framework guides to set up building information representation system, which can help facility managers to manage buildings efficiently by improving their understanding on how office buildings are operated and used.

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr - Part 3: improved representation of solar cycle 11

Svalgaard (2014) has recently pointed out that the calibration of the Helsinki magnetic observatory’s H component variometer was probably in error in published data for the years 1866–1874.5 and that this makes the interdiurnal variation index based on daily means, IDV(1d), (Lockwood et al., 2013a), and the interplanetary magnetic field strength derived from it (Lockwood et al., 2013b), too low around the peak of solar cycle 11. We use data from the modern Nurmijarvi station, relatively close to the site of the original Helsinki Observatory, to confirm a 30% underestimation in this interval and hence our results are fully consistent with the correction derived by Svalgaard. We show that the best method for recalibration uses the Helsinki Ak(H) and aa indices and is accurate to ±10 %. This makes it preferable to recalibration using either the sunspot number or the diurnal range of geomagnetic activity which we find to be accurate to ±20 %. In the case of Helsinki data during cycle 11, the two recalibration methods produce very similar corrections which are here confirmed using newly digitised data from the nearby St Petersburg observatory and also using declination data from Helsinki. However, we show that the IDV index is, compared to later years, too similar to sunspot number before 1872, revealing independence of the two data series has been lost; either because the geomagnetic data used to compile IDV has been corrected using sunspot numbers, or vice versa, or both. We present corrected data sequences for both the IDV(1d) index and the reconstructed IMF (interplanetary magnetic field).We also analyse the relationship between the derived near-Earth IMF and the sunspot number and point out the relevance of the prior history of solar activity, in addition to the contemporaneous value, to estimating any “floor” value of the near-Earth interplanetary field.

Conceptual representation in bilinguals: the role of language specificity and conceptual change

Most prominent models of bilingual representation assume a degree of interconnection or shared representation at the conceptual level. However, in the context of linguistic and cultural specificity of human concepts, and given recent findings that reveal a considerable amount of bidirectional conceptual transfer and conceptual change in bilinguals, a particular challenge that bilingual models face is to account for non-equivalence or partial equivalence of L1 and L2 specific concepts in bilingual conceptual store. The aim of the current paper is to provide a state-of-the-art review of the available empirical evidence from the fields of psycholinguistics, cognitive, experimental, and cross-cultural psychology, and discuss how these may inform and develop further traditional and more recent accounts of bilingual conceptual representation. Based on a synthesis of the available evidence against theoretical postulates of existing models, I argue that the most coherent account of bilingual conceptual representation combines three fundamental assumptions. The first one is the distributed, multi-modal nature of representation. The second one concerns cross-linguistic and cross-cultural variation of concepts. The third one makes assumptions about the development of concepts, and the emergent links between those concepts and their linguistic instantiations.

Neural representation of reward in recovered depressed patients

These findings support the view that abnormal neural responses to reward may be an endophenotype for depression and a potential target for intervention and prevention strategies.

Cognitive influences on the affective representation of touch and the sight of touch in the human brain

We show that the affective experience of touch and the sight of touch can be modulated by cognition, and investigate in an fMRI study where top-down cognitive modulations of bottom-up somatosensory and visual processing of touch and its affective value occur in the human brain. The cognitive modulation was produced by word labels, 'Rich moisturizing cream' or 'Basic cream', while cream was being applied to the forearm, or was seen being applied to a forearm. The subjective pleasantness and richness were modulated by the word labels, as were the fMRI activations to touch in parietal cortex area 7, the insula and ventral striatum. The cognitive labels influenced the activations to the sight of touch and also the correlations with pleasantness in the pregenual cingulate/orbitofrontal cortex and ventral striatum. Further evidence of how the orbitofrontal cortex is involved in affective aspects of touch was that touch to the forearm [which has C fiber Touch (CT) afferents sensitive to light touch] compared with touch to the glabrous skin of the hand (which does not) revealed activation in the mid-orbitofrontal cortex. This is of interest as previous studies have suggested that the CT system is important in affiliative caress-like touch between individuals.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

Earthworm distribution and abundance predicted by a process-based model

Earthworms are significant ecosystem engineers and are an important component of the diet of many vertebrates and invertebrates, so the ability to predict their distribution and abundance would have wide application in ecology, conservation and land management. Earthworm viability is known to be affected by the availability and quality of food resources, soil water conditions and temperature, but has not yet been modelled mechanistically to link effects on individuals to field population responses. Here we present a novel model capable of predicting the effects of land management and environmental conditions on the distribution and abundance of Aporrectodea caliginosa, the dominant earthworm species in agroecosystems. Our process-based approach uses individual based modelling (IBM), in which each individual has its own energy budget. Individual earthworm energy budgets follow established principles of physiological ecology and are parameterised for A. caliginosa from experimental measurements under optimal conditions. Under suboptimal conditions (e.g. food limitation, low soil temperatures and water contents) reproduction is prioritised over growth. Good model agreement to independent laboratory data on individual cocoon production and growth of body mass, under variable feeding and temperature conditions support our representation of A. caliginosa physiology through energy budgets. Our mechanistic model is able to accurately predict A. caliginosa distribution and abundance in spatially heterogeneous soil profiles representative of field study conditions. Essential here is the explicit modelling of earthworm behaviour in the soil profile. Local earthworm movement responds to a trade-off between food availability and soil water conditions, and this determines the spatiotemporal distribution of the population in the soil profile. Importantly, multiple environmental variables can be manipulated simultaneously in the model to explore earthworm population exposure and effects to combinations of stressors. Potential applications include prediction of the population-level effects of pesticides and changes in soil management e.g. conservation tillage and climate change.

Smart-phone based electrocardiogram wavelet decomposition and neural network classification

This paper discusses ECG classification after parametrizing the ECG waveforms in the wavelet domain. The aim of the work is to develop an accurate classification algorithm that can be used to diagnose cardiac beat abnormalities detected using a mobile platform such as smart-phones. Continuous time recurrent neural network classifiers are considered for this task. Records from the European ST-T Database are decomposed in the wavelet domain using discrete wavelet transform (DWT) filter banks and the resulting DWT coefficients are filtered and used as inputs for training the neural network classifier. Advantages of the proposed methodology are the reduced memory requirement for the signals which is of relevance to mobile applications as well as an improvement in the ability of the neural network in its generalization ability due to the more parsimonious representation of the signal to its inputs.