Towards cost-sensitive adaptation: when is it worth updating your predictive model?

Our digital universe is rapidly expanding,more and more daily activities are digitally recorded, data arrives in streams, it needs to be analyzed in real time and may evolve over time. In the last decade many adaptive learning algorithms and prediction systems, which can automatically update themselves with the new incoming data, have been developed. The majority of those algorithms focus on improving the predictive performance and assume that model update is always desired as soon as possible and as frequently as possible. In this study we consider potential model update as an investment decision, which, as in the financial markets, should be taken only if a certain return on investment is expected. We introduce and motivate a new research problem for data streams ? cost-sensitive adaptation. We propose a reference framework for analyzing adaptation strategies in terms of costs and benefits. Our framework allows to characterize and decompose the costs of model updates, and to asses and interpret the gains in performance due to model adaptation for a given learning algorithm on a given prediction task. Our proof-of-concept experiment demonstrates how the framework can aid in analyzing and managing adaptation decisions in the chemical industry.

Striking a balance: cultural conflicts or cultural adaptation

This paper explores the cultural representations embedded in the EFL textbooks for Primary English language education in China. In particular, it examines how cultural globalisation and localisation are competing with each other as the educational policy in English attempts to strike a balance between the local culture and ‘western’ culture. Using discourse analysis as an analytical framework, this paper argues that culture as a social construct is constantly evolving and traditions are fused with new cultural values and worldviews brought about by globalisation. As such, the analysis of the textbooks illustrates that culture as a social phenomenon has changed over the decades and glocalisation is gaining new perspectives in English language education in China. Importantly, the analysis shows that new cultural elements have been established and cultural globalisation has taken place when local culture adapt ‘foreign’ cultures to suit local needs. Acknowledging that there are cultural conflicts and competing ideologies in the texts, the paper argues that these conflicts and contradictories can be used to develop students’ critical language awareness and foster their critical analytical abilities. Importantly, the analysis can facilitate the students’ English language learning by providing them with opportunities to read beyond texts per se to cultural politics and practices. Juxtaposing different cultural and ideological perspectives can help students understand that cultural values are socially and politically constructed when they are confronted with complex linguistic and cultural environments in reality.

Similarities in butterfly emergence dates among populations suggest local adaptation to climate

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate-driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among-population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space-temperature and time-temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature-mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest.