Understanding the Global Energy Crisis

Central issues in global energy are discussed through interdisciplinary dialogue between experts from both North America and Europe with overview from historical, political, and socio-cultural perspectives, outlining the technology and policy issues facing the development of major conventional and renewable energy sources. We are facing a global energy crisis caused by world population growth, an escalating increase in demand, and continued dependence on fossil-based fuels for generation. It is widely accepted that increases in greenhouse gas concentration levels, if not reversed, will result in major changes to world climate with consequential effects on our society and economy. This is just the kind of intractable problem that Purdue University’s Global Policy Research Institute seeks to address in the Purdue Studies in Public Policy series by promoting the engagement between policy makers and experts in fields such as engineering and technology

EQUIPT: protocol of a comparative effectiveness research study evaluating cross-context transferability of economic evidence on tobacco control

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.This article has been made available through the Brunel Open Access Publishing Fund.Tobacco smoking claims 700 000 lives every year in Europe and the cost of tobacco smoking in the EU is estimated between €98 and €130 billion annually; direct medical care costs and indirect costs such as workday losses each represent half of this amount. Policymakers all across Europe are in need of bespoke information on the economic and wider returns of investing in evidence-based tobacco control, including smoking cessation agendas. EQUIPT is designed to test the transferability of one such economic evidence base-the English Tobacco Return on Investment (ROI) tool-to other EU member states

Calculating partial expected value of perfect information via Monte Carlo sampling algorithms

Partial expected value of perfect information (EVPI) calculations can quantify the value of learning about particular subsets of uncertain parameters in decision models. Published case studies have used different computational approaches. This article examines the computation of partial EVPI estimates via Monte Carlo sampling algorithms. The mathematical definition shows 2 nested expectations, which must be evaluated separately because of the need to compute a maximum between them. A generalized Monte Carlo sampling algorithm uses nested simulation with an outer loop to sample parameters of interest and, conditional upon these, an inner loop to sample remaining uncertain parameters. Alternative computation methods and shortcut algorithms are discussed and mathematical conditions for their use considered. Maxima of Monte Carlo estimates of expectations are biased upward, and the authors show that the use of small samples results in biased EVPI estimates. Three case studies illustrate 1) the bias due to maximization and also the inaccuracy of shortcut algorithms 2) when correlated variables are present and 3) when there is nonlinearity in net benefit functions. If relatively small correlation or nonlinearity is present, then the shortcut algorithm can be substantially inaccurate. Empirical investigation of the numbers of Monte Carlo samples suggests that fewer samples on the outer level and more on the inner level could be efficient and that relatively small numbers of samples can sometimes be used. Several remaining areas for methodological development are set out. A wider application of partial EVPI is recommended both for greater understanding of decision uncertainty and for analyzing research priorities

An investigation into CLIL-related sections of EFL coursebooks : issues of CLIL inclusion in the publishing market

The current ELT global coursebook market has embraced CLIL as a weak form of bilingual education and an innovative component to include in General English coursebooks for EFL contexts. In this paper I investigate how CLIL is included in ELT coursebooks aimed at teenaged learners, available to teachers in Argentina. My study is based on the content analysis of four series which include a section advertised as CLIL-oriented. Results suggest that such sections are characterised by (1) little correlation between featured subject specific content and school curricula in L1, (2) oversimplification of contents, and (3) dominance of reading skills development and lower-order thinking tasks. Through this study, I argue that CLIL components become superficial supplements rather than a meaningful attempt to promote weak forms of bilingual education

Primitive Shape Imagery Classification from Electroencephalography

Introduction: Brain-computer interfaces (BCIs) augment traditional interfaces for human-computer interaction and provide alternative communication devices to enable the physically impaired to work. Imagined object/shape classification from electroencephalography (EEG) may lead, for example, to enhanced tools for fields such as engineering, design, and the visual arts. Evidence to support such a proposition from non-invasive neuroimaging techniques to date has mainly involved functional magnetic resonance tomography (fMRI) [1] indicating that visual perception and mental imagery show similar brain activity patterns [2] and, although the primary visual cortex has an important role in mental imagery and perception, the occipitotemporal cortex also encodes sensory, semantic and emotional properties during shape imagery [3]. Here we investigate if five imagined primitive shapes (sphere, cone, pyramid, cylinder, cube) can be classified from EEG using filter bank common spatial patterns (FBCSP) [4]. Material, Methods, and Results: Ten healthy volunteers (8 males and 2 females, aged 26-44) participated in a single session study (three runs, four blocks/run, 30 trials/block (i.e., six repetitions of five primitive shapes in random order)). Trials lasted 7s as shown in Fig. 1 and ended with an auditory tone. Thirty EEG channels were recorded with a g.BSamp EEG system using active electrodes (g.tec, Austria). EEG channels with high-level noise were removed. Signals were band-pass filtered in six non-overlapped, 4Hz width bands covering the 4-40Hz frequency range. Filter bank common spatial pattern (FBCSP) based feature extraction and mutual information (MI) based feature selection methods provided input features for 2-class classification using linear discriminant analysis (LDA) for target shape versus the rest, separately. The final 5-class classification was decided by assessing the signed distance in the 2-class discriminant hyperplane for each of the five binary classifiers as shown in Fig. 1. Classifiers were trained on two runs and tested on the one unseen run (i.e., 3 fold cross-validation). A Wilcoxon non-parametric test was used to validate the difference of DA at end of the resting period (-1s) and at the maximal peak accuracy occurring during the shape imagery task (0-3s) is significant (p<0.001). Fig. 1 shows the between-subject average time-varying classification accuracies with standard deviation (shaded area). Discussion: The results indicate that there is separability provided by the shape imagery and there is significantly higher accuracy compared to the ~20% chance level prior the display period with maximum accuracy reaching 34%. In [5] classification of five imagined primitive and complex shapes with 44% accuracy is reported using a 14 channel Emotiv headset. Differences in performance reported may be influenced by EEG recording (EEG in [5] appears to have different dynamics (significant mean shifts)), the study had more sessions/trials, applied ICA for noise removal and the participants had designer experience whilst our study did not. Improvement of our methods is required to achieve higher accuracy rate. It is unclear if an online feedback to shape imagery training and learning will an impact performance – a multisession online study with feedback is the next step in this research. Significance: To best of our knowledge this is only the second study of shape imagery classification from EEG

Application of a policy framework for the public funding of drugs for rare diseases

BACKGROUND: In many countries, decisions about the public funding of drugs are preferentially based on the results of randomized trials. For truly rare diseases, such trials are not typically available, and approaches by public payers are highly variable. In view of this, a policy framework intended to fairly evaluate these drugs was developed by the Drugs for Rare Diseases Working Group (DRDWG) at the request of the Ontario Public Drug Programs. OBJECTIVE: To report the initial experience of applying a novel evaluation framework to funding applications for drugs for rare diseases. METHODS: Retrospective observational cohort study. MEASURES: Clinical effectiveness, costs, funding recommendations, funding approval. KEY RESULTS: Between March 2008 and February 2013, eight drugs were evaluated using the DRDWG framework. The estimated average annual drug cost per patient ranged from 28,000 to 1,200,000 Canadian dollars (CAD). For five drugs, full evaluations were completed, specific funding recommendations were made by the DRDWG, and funding was approved after risk-sharing agreements with the manufacturers were negotiated. For two drugs, the disease indications were determined to be ineligible for consideration. For one drug, there was insufficient natural history data for the disease to provide a basis for recommendation. For the five drugs fully evaluated, 32 patients met the predefined eligibility criteria for funding, and five were denied based on predefined exclusion criteria. CONCLUSIONS: The framework improved transparency and consistency for evaluation and public funding of drugs for rare diseases in Ontario. The evaluation process will continue to be iteratively refined as feedback on actual versus expected clinical and economic outcomes is incorporated. © 2014 Society of General Internal Medicine

What guidance are researchers given on how to present network meta-analyses to end-users such as policymakers and clinicians? A systematic review

© 2014 Sullivan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Introduction: Network meta-analyses (NMAs) are complex methodological approaches that may be challenging for non-technical end-users, such as policymakers and clinicians, to understand. Consideration should be given to identifying optimal approaches to presenting NMAs that help clarify analyses. It is unclear what guidance researchers currently have on how to present and tailor NMAs to different end-users. Methods: A systematic review of NMA guidelines was conducted to identify guidance on how to present NMAs. Electronic databases and supplementary sources were searched for NMA guidelines. Presentation format details related to sample formats, target audiences, data sources, analysis methods and results were extracted and frequencies tabulated. Guideline quality was assessed following criteria developed for clinical practice guidelines. Results: Seven guidelines were included. Current guidelines focus on how to conduct NMAs but provide limited guidance to researchers on how to best present analyses to different end-users. None of the guidelines provided reporting templates. Few guidelines provided advice on tailoring presentations to different end-users, such as policymakers. Available guidance on presentation formats focused on evidence networks, characteristics of individual trials, comparisons between direct and indirect estimates and assumptions of heterogeneity and/or inconsistency. Some guidelines also provided examples of figures and tables that could be used to present information. Conclusions: Limited guidance exists for researchers on how best to present NMAs in an accessible format, especially for non-technical end-users such as policymakers and clinicians. NMA guidelines may require further integration with end-users' needs, when NMAs are used to support healthcare policy and practice decisions. Developing presentation formats that enhance understanding and accessibility of NMAs could also enhance the transparency and legitimacy of decisions informed by NMAs.The Canadian Institute of Health Research (CIHR) Drug Safety and Effectiveness Network (Funding reference number – 116573)