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Accurate electricity price forecasting (EPF) can provide a necessary basis for market decision making by power market participants to reduce the operating cost of the power system and ensure the system's stable operation. To address the characteristics of high frequency, strong nonlinearity, and high volatility of electricity prices, this paper proposes a short-term electricity price forecasting model based on a two-layer variational modal decomposition (VMD) technique, using the sparrow search algorithm (SSA) to optimize the long and short-term memory network (LSTM). The original electricity price sequence is decomposed into multiple modal components using VMD. Then, each piece is predicted separately using an SSA-optimized LSTM. For the element with the worst prediction accuracy, IMF-worst is decomposed for a second time using VMD to explore the price characteristics further. Finally, the prediction results of each modal component are reconstructed to obtain the final prediction results. To verify the validity and accuracy of the proposed model, this paper uses data from three electricity markets, Australia, Spain, and France, for validation analysis. The experimental results show that the proposed model has MAPE of 0.39%, 1.58%, and 0.95%, RMSE of 0.25, 0.9, and 0.3, and MAE of 0.19, 0.68, and 0.31 in three different cases, indicating that the proposed model can well handle the nonlinear and non-stationarity characteristics of the electricity price series and has superior forecasting performance. [ABSTRACT FROM AUTHOR]

The increased penetration of renewable energy sources (RESs) as an effective mechanism to reduce carbon emissions leads to an increased weather dependency for power and energy systems. This has created dynamic operation and degradation phenomena, which affect the lifetime estimation of the assets operated with RESs. For the reliable and efficient operation of RES it is crucial to monitor the health of its constituent components and feature selection is a crucial step for building robust and accurate health monitoring approaches. In this context, this paper presents a probabilistic feature selection approach, which probabilistically weights and selects features through a heuristic and iterative process for an improved asset lifetime estimation. Power transformers are key power grid assets and they are used to demonstrate the validity and impact of the proposed approach. The approach is tested on two different photovoltaic power plants operated in Spain and Australia. Results consistently show that the proposed feature-selection approach reduces the prediction error and consistently selects relevant features. The approach has been applied to transformer lifetime estimation, but it can be generally applied to assist in the lifetime estimation of other components operated in RESs. Part of the studies presented here as well as source codes are all open-source under the GitHub repository https://github.com/iramirezg/FeatureSelection. • Probabilistic feature selection approach for improved asset lifetime estimation. • Integration of environmental features for improved renewable-operated asset lifetime. • Systematic and robust feature weighting methodology. • Improved transformer lifetime estimation including sensor and environmental data. • Validated on two real photovoltaic power plant case studies. [ABSTRACT FROM AUTHOR]

This paper provides three case studies of initiatives developed to improve educational opportunities in vulnerable urban communities. The cities in the three countries involved, Australia, the United States, and Spain, are different in many ways; however, each has persistent and entrenched inequalities between the educational opportunities and outcomes of historically marginalised students and their mainstream counterparts. Here, we focus on conceptualising and describing urban examples of poverty from three different countries, and reporting on programs and strategies aimed at enhancing the quality of teaching in schools in high-poverty areas. By providing and comparing the three cases, we aim to contribute to broader understandings of poverty in three locations and how teachers and schools in high-poverty urban settings can re-think their practices. [ABSTRACT FROM AUTHOR]

Daily mobility varies by gender and is likely related to contextual factors including the gender division of employment and family work, options for modes of transport, and support for work-family reconciliation. This paper compares travel time patterns of men and women using nationally representative time-diary data from Australia, the UK, Spain and Finland (n = 14,176). Despite similarities in men and women's total travel time within countries, results show substantial gender variation in the purpose of daily travel, the transport mode used, who is present, and the way parents in couple-headed households share travel with and for children in relative terms. The extent of the gender gaps vary cross-nationally in ways consistent with prevalent patterns in the gendered division of labour and social parenting norms, but relative gaps in child-serving travel were universal, attesting to the ubiquity of gendered mobility constraints in households with children. • Daily mobility varies cross-nationally by gender in purpose, mode and company. • Gendered mobility reflects national patterns of gendered division of labour. • Gendered mobility reflects national patterns of parenting norms and social trust. • Relative gender gaps in parents' travel with and for children are universal. [ABSTRACT FROM AUTHOR]

Aims To report a systematic review of the psychometric properties of self-report instruments to identify the symptoms of anxiety in pregnancy to help clinicians and researchers select the most suitable instrument. Background Excessive anxiety in pregnancy is associated with adverse birth outcomes, developmental and behavioural problems in infants and postnatal depression. Despite recommendations for routine psychological assessment in pregnancy, the optimal methods to identify anxiety in pregnancy have not been confirmed. Design Psychometric systematic review. Data sources A systematic literature search of the multiple databases (1990-September 2014). Review methods Identification of self-report instruments to measure anxiety in pregnancy using COSMIN guidelines to assess studies reporting a psychometric evaluation of validity and reliability. Results Thirty-two studies were included. Studies took place in the UK, Australia, Belgium, Canada, Germany, Italy, Scandinavia, Spain and the Netherlands. Seventeen different instruments were identified. Measures of validity were reported in 19 papers and reliability in 16. The overall quality of the papers was rated as fair to excellent using the COSMIN checklist. Only one paper scored excellent in more than one category. Conclusion Many instruments have been adapted for use in different populations to those for which they were designed. The State Trait Anxiety Inventory, Edinburgh Postnatal Depression Scale and the Hospital Anxiety and Depression Scale have been tested more frequently than other instruments, yet require further assessment to confirm their value for use in pregnancy. [ABSTRACT FROM AUTHOR]

Some previous studies have shown that the availability of orthographic information leads to positive effects for second language (L2) phonology, while others document negative effects. In this paper, we examine the role of orthography on novel spoken-word learning by comparing word pairs that differed in most or all of their segments (nonminimal pairs) and those that only differed in one phoneme (minimal pairs) that was considered easy or difficult to discriminate. We tested the performance of learners whose native languages have transparent orthographies as well as learners with opaque orthographies. Our findings show that regardless of linguistic background and native orthographic system, availability of orthographic information during word learning did not have an effect on nonminimal pairs or perceptually easy minimal pairs. However, it had a positive effect on two minimal pairs that had the highest accuracy among the seven perceptually difficult ones, indicating that orthography only helped contrasts that were relatively easy to discriminate. The implications of these findings for L2 teaching and for future directions within L2 phonology are discussed. [ABSTRACT FROM AUTHOR]

The transfer of successful water market governance between international settings is increasingly attractive to policy makers under globalization. This paper tests lesson-drawing approaches to water market governance transfers using data from Spain and the Murray-Darling Basin, Australia. Spain is the blueprint country for water market adoption in Europe, while Australia is often presented as a world leader in innovative water market arrangements. A preliminary comparative analysis framework linking water market governance principles to observed institutional arrangements and outcomes is provided. Finally, some key lessons, problems and policy transfer potential to stimulate and enhance Spanish water markets from lesson-drawing approaches are drawn, with an emphasis on adaptive capacity as an institutional performance metric. We find that Spain's current water governance institutions and arrangements offer a solid platform for marketing reform, where some key adaptive capacity constraints are able to be addressed. The lessons drawn from this study highlight those areas of change which, while challenging, can be achieved in our view. • Lesson drawing methods offer a novel way to assess adaptive capacity in policy settings. • Australia's water markets provide a case study for comparing Spain's readiness for water market adoption. • Current institutional strengths and weaknesses are identified via the analysis. • Future adaptive capacity evaluation offers useful insights for water governors and policy-makers. [ABSTRACT FROM AUTHOR]