What do patients want to know? An empirical approach to explanation generation and validation

This article describes an empirical, user-centred approach to explanation design. It reports three studies that investigate what patients want to know when they have been prescribed medication. The question is asked in the context of the development of a drug prescription system called OPADE. The system is aimed primarily at improving the prescribing behaviour of physicians, but will also produce written explanations for indirect users such as patients. In the first study, a large number of people were presented with a scenario about a visit to the doctor, and were asked to list the questions that they would like to ask the doctor about the prescription. On the basis of the results of the study, a categorization of question types was developed in terms of how frequently particular questions were asked. In the second and third studies a number of different explanations were generated in accordance with this categorization, and a new sample of people were presented with another scenario and were asked to rate the explanations on a number of dimensions. The results showed significant differences between the different explanations. People preferred explanations that included items corresponding to frequently asked questions in study 1. For an explanation to be considered useful, it had to include information about side effects, what the medication does, and any lifestyle changes involved. The implications of the results of the three studies are discussed in terms of the development of OPADE's explanation facility.

Dominance in the Tetra Pak case: an empirical approach

The 1991 decision of the European Commission on the Tetra Pak case was based on information which seemed to prove the firm's anti-competitive behavior. The Tetra Pak case is investigated here focusing on the meaning of multimarket dominance, using empirical techniques. We find that a more rigorous analysis of the data available would not confirm the Commission's assertions. That is, it cannot be concluded with certainty that the Commission was right to relate Tetra Pak's dominance in the aseptic sector to its market power in the non-aseptic sector. Our results suggest a general framework for the analysis of abusive transfer of market power across vertically or/and horizontally related markets.

Updated empirical model of genetically-modified maize grain production practices to achieve European Union labeling thresholds

An updated empirical approach is proposed for specifying coexistence requirements for genetically modified (GM) maize (Zea mays L.) production to ensure compliance with the 0.9% labeling threshold for food and feed in the European Union. The model improves on a previously published (Gustafson et al., 2006) empirical model by adding recent data sources to supplement the original database and including the following additional cases: (i) more than one GM maize source field adjacent to the conventional or organic field, (ii) the possibility of so-called “stacked” varieties with more than one GM trait, and (iii) lower pollen shed in the non-GM receptor field. These additional factors lead to the possibility for somewhat wider combinations of isolation distance and border rows than required in the original version of the empirical model. For instance, in the very conservative case of a 1-ha square non-GM maize field surrounded on all four sides by homozygous GM maize with 12 m isolation (the effective isolation distance for a single GM field), non-GM border rows of 12 m are required to be 95% confident of gene flow less than 0.9% in the non-GM field (with adventitious presence of 0.3%). Stacked traits of higher GM mass fraction and receptor fields of lower pollen shed would require a greater number of border rows to comply with the 0.9% threshold, and an updated extension to the model is provided to quantify these effects.

Toward an integrated seasonal forecasting system for South America

This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: ( i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and ( ii) a multimodel system composed of three European coupled ocean - atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated ( i. e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Nino or La Nina years rather than in neutral years.

The role of food standards in international trade: evidence from Brazilian beef exports to the EU market

The study reviews the literature on global chain governance and food standards to allow for an assessment of Brazilian beef exports to the European Union. The empirical approach employed is based on company case studies. The results suggest that the Brazilian beef chain has little choice but to adapt to market changes as standards evolve. Costs of compliance for meeting international food standards reduce Brazil's comparative advantage. At the same time, changes in the nature of demand have created the need for a more integrated supply chain in order to enhance confidence in Brazil's beef production and processing abroad.

A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition

Transient neural assemblies mediated by synchrony in particular frequency ranges are thought to underlie cognition. We propose a new approach to their detection, using empirical mode decomposition (EMD), a data-driven approach removing the need for arbitrary bandpass filter cut-offs. Phase locking is sought between modes. We explore the features of EMD, including making a quantitative assessment of its ability to preserve phase content of signals, and proceed to develop a statistical framework with which to assess synchrony episodes. Furthermore, we propose a new approach to ensure signal decomposition using EMD. We adapt the Hilbert spectrum to a time-frequency representation of phase locking and are able to locate synchrony successfully in time and frequency between synthetic signals reminiscent of EEG. We compare our approach, which we call EMD phase locking analysis (EMDPL) with existing methods and show it to offer improved time-frequency localisation of synchrony.

Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements - I. A universal approach to calculate thermal inertia

In this paper we pledge that physically based equations should be combined with remote sensing techniques to enable a more theoretically rigorous estimation of area-average soil heat flux, G. A standard physical equation (i.e. the analytical or exact method) for the estimation of G, in combination with a simple, but theoretically derived, equation for soil thermal inertia (F), provides the basis for a more transparent and readily interpretable method for the estimation of G; without the requirement for in situ instrumentation. Moreover, such an approach ensures a more universally applicable method than those derived from purely empirical studies (employing vegetation indices and albedo, for example). Hence, a new equation for the estimation of Gamma(for homogeneous soils) is discussed in this paper which only requires knowledge of soil type, which is readily obtainable from extant soil databases and surveys, in combination with a coarse estimate of moisture status. This approach can be used to obtain area-averaged estimates of Gamma(and thus G, as explained in paper II) which is important for large-scale energy balance studies that employ aircraft or satellite data. Furthermore, this method also relaxes the instrumental demand for studies at the plot and field scale (no requirement for in situ soil temperature sensors, soil heat flux plates and/or thermal conductivity sensors). In addition, this equation can be incorporated in soil-vegetation-atmosphere-transfer models that use the force restore method to update surface temperatures (such as the well-known ISBA model), to replace the thermal inertia coefficient.

Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements - II. Diurnal shape of soil heat flux

For vegetated surfaces, calculation of soil heat flux, G, with the Exact or Analytical method requires a harmonic analysis of below-canopy soil surface temperature, to obtain the shape of the diurnal course of G. When determining G with remote sensing methods, only composite (vegetation plus soil) radiometric brightness temperature is available. This paper presents a simple equation that relates the sum of the harmonic terms derived for the composite radiometric surface temperature to that of belowcanopy soil surface temperature. The thermal inertia, Gamma(,) for which a simple equation has been presented in a companion paper, paper I, is used to set the magnitude of G. To assess the success of the method proposed in this paper for the estimation of the diurnal shape of G, a comparison was made between 'remote' and in situ calculated values from described field sites. This indicated that the proposed method was suitable for the estimation of the shape of G for a variety of vegetation types and densities. The approach outlined in paper I, to obtain Gamma, was then combined with the estimated harmonic terms to predict estimates of G, which were compared to values predicted by empirical remote methods found in the literature. This indicated that the method proposed in the combination of papers I and II gave reliable estimates of G, which, in comparison to the other methods, resulted in more realistic predictions for vegetated surfaces. This set of equations can also be used for bare and sparsely vegetated soils, making it a universally applicable method. (C) 2007 Elsevier B.V. All rights reserved.

An event-based approach to validating solar wind speed predictions: high-speed enhancements in the Wang-Sheeley-Arge model

One of the primary goals of the Center for Integrated Space Weather Modeling (CISM) effort is to assess and improve prediction of the solar wind conditions in near‐Earth space, arising from both quasi‐steady and transient structures. We compare 8 years of L1 in situ observations to predictions of the solar wind speed made by the Wang‐Sheeley‐Arge (WSA) empirical model. The mean‐square error (MSE) between the observed and model predictions is used to reach a number of useful conclusions: there is no systematic lag in the WSA predictions, the MSE is found to be highest at solar minimum and lowest during the rise to solar maximum, and the optimal lead time for 1 AU solar wind speed predictions is found to be 3 days. However, MSE is shown to frequently be an inadequate “figure of merit” for assessing solar wind speed predictions. A complementary, event‐based analysis technique is developed in which high‐speed enhancements (HSEs) are systematically selected and associated from observed and model time series. WSA model is validated using comparisons of the number of hit, missed, and false HSEs, along with the timing and speed magnitude errors between the forecasted and observed events. Morphological differences between the different HSE populations are investigated to aid interpretation of the results and improvements to the model. Finally, by defining discrete events in the time series, model predictions from above and below the ecliptic plane can be used to estimate an uncertainty in the predicted HSE arrival times.

Blended learning approach to include the innovative use of vodcasts (video-podcasts) to enrich students learning experience in structures laboratory

Students may have difficulty in understanding some of the complex concepts which they have been taught in the general areas of science and engineering. Whilst practical work such as a laboratory based examination of the performance of structures has an important role in knowledge construction this does have some limitations. Blended learning supports different learning styles, hence further benefits knowledge building. This research involves the empirical studies of how an innovative use of vodcasts (video-podcasts) can enrich learning experience in the structural properties of materials laboratory of an undergraduate course. Students were given the opportunity of downloading and viewing the vodcasts on the theory before and after the experimental work. It is the choice of the students when (before or after, before and after) and how many times they would like to view the vodcasts. In blended learning, the combination of face-to-face teaching, vodcasts, printed materials, practical experiments, writing reports and instructors’ feedbacks benefits different learning styles of the learners. For the preparation of the practical laboratory work, the students were informed about the availability of the vodcasts prior to the practical session. After the practical work, students submit an individual laboratory report for the assessment of the structures laboratory. The data collection consists of a questionnaire completed by the students, and the practical reports submitted by them for assessment. The results from the questionnaire were analysed quantitatively, whilst the data from the assessment reports were analysed qualitatively. The analysis shows that students who have not fully grasped the theory after the practical were successful in gaining the required knowledge by viewing the vodcasts. Some students who have understood the theory may choose to view it once or not at all. Their understanding was demonstrated by the quality of their explanations in their reports. This is illustrated by the approach they took to explicate the results of their experimental work, for example, they can explain how to calculate the Young’s Modulus properly and provided the correct value for it. The research findings are valuable to instructors who design, develop and deliver different types of blended learning, and beneficial to learners who try different blended approaches. Recommendations were made on the role of the innovative application of vodcasts in the knowledge construction for structures laboratory and to guide future work in this area of research.

Forecast calibration and combination: a simple Bayesian approach for ENSO

This study presents a new simple approach for combining empirical with raw (i.e., not bias corrected) coupled model ensemble forecasts in order to make more skillful interval forecasts of ENSO. A Bayesian normal model has been used to combine empirical and raw coupled model December SST Niño-3.4 index forecasts started at the end of the preceding July (5-month lead time). The empirical forecasts were obtained by linear regression between December and the preceding July Niño-3.4 index values over the period 1950–2001. Coupled model ensemble forecasts for the period 1987–99 were provided by ECMWF, as part of the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction (DEMETER) project. Empirical and raw coupled model ensemble forecasts alone have similar mean absolute error forecast skill score, compared to climatological forecasts, of around 50% over the period 1987–99. The combined forecast gives an increased skill score of 74% and provides a well-calibrated and reliable estimate of forecast uncertainty.

Contextualist research: Iterating between methods while following an empirically grounded approach

An alternative approach to research is described that has been developed through a succession of significant construction management research projects. The approach follows the principles of iterative grounded theory, whereby researchers iterate between alternative theoretical frameworks and emergent empirical data. Of particular importance is an orientation toward mixing methods, thereby overcoming the existing tendency to dichotomize quantitative and qualitative approaches. The approach is positioned against the existing contested literature on grounded theory, and the possibility of engaging with empirical data in a “theory free” manner is discounted. Emphasis instead is given to the way in which researchers must be theoretically sensitive as a result of being steeped in relevant literatures. Knowledge of existing literatures therefore shapes the initial research design; but emergent empirical findings cause fresh theoretical perspectives to be mobilized. The advocated approach is further aligned with notions of knowledge coproduction and the underlying principles of contextualist research. It is this unique combination of ideas which characterizes the paper's contribution to the research methodology literature within the field of construction management. Examples are provided and consideration is given to the extent to which the emergent findings are generalizable beyond the specific context from which they are derived.

EMG signal filtering based on Empirical Mode Decomposition

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.

Detection of neural correlates of self-paced motor activity using empirical mode decomposition phase locking analysis

Transient episodes of synchronisation of neuronal activity in particular frequency ranges are thought to underlie cognition. Empirical mode decomposition phase locking (EMDPL) analysis is a method for determining the frequency and timing of phase synchrony that is adaptive to intrinsic oscillations within data, alleviating the need for arbitrary bandpass filter cut-off selection. It is extended here to address the choice of reference electrode and removal of spurious synchrony resulting from volume conduction. Spline Laplacian transformation and independent component analysis (ICA) are performed as pre-processing steps, and preservation of phase synchrony between synthetic signals. combined using a simple forward model, is demonstrated. The method is contrasted with use of bandpass filtering following the same preprocessing steps, and filter cut-offs are shown to influence synchrony detection markedly. Furthermore, an approach to the assessment of multiple EEG trials using the method is introduced, and the assessment of statistical significance of phase locking episodes is extended to render it adaptive to local phase synchrony levels. EMDPL is validated in the analysis of real EEG data, during finger tapping. The time course of event-related (de)synchronisation (ERD/ERS) is shown to differ from that of longer range phase locking episodes, implying different roles for these different types of synchronisation. It is suggested that the increase in phase locking which occurs just prior to movement, coinciding with a reduction in power (or ERD) may result from selection of the neural assembly relevant to the particular movement. (C) 2009 Elsevier B.V. All rights reserved.

What does a transdiagnostic approach have to offer the treatment of anxiety disorders?

Purpose: The purpose of this paper is to review the rationale for 'transdiagnostic' approaches to the understanding and treatment of anxiety disorders. Methods: Databases searches and examination of the reference lists of relevant studies were used to identify papers of relevance. Results: There is increasing recognition that diagnosis-specific interventions for single anxiety-disorders are of less value than might appear since a large proportion of patients have more than one co-existing anxiety disorder and the treatment of one anxiety disorder does not necessarily lead to the resolution of others. As transdiagnostic approaches have the potential to address multiple co-existing anxiety disorders they are potentially more clinically relevant than single anxiety disorder interventions. They may also have advantages in ease of dissemination and in treating anxiety disorder not otherwise specified. Conclusions: The merits of the various transdiagnostic cognitive-behavioral approaches that have been proposed are reviewed. Such approaches have potential benefits, particularly in striking the balance between completely idiosyncratic formulations and diagnosis-driven treatments of anxiety disorders. However, caution is needed to ensure that transdiagnostic theories and treatments benefit from progress made by research on diagnosis-specific treatments, and further empirical work is needed to identify the shared maintaining processes that need to be targeted in the treatment of anxiety disorders.