HyFlex courses are characterised by a mixture of online and face-to-face learning components. In particular, students are allowed to choose themselves to complete any part of the course in online and/or face-to-face mode. Such courses arguably provide the highest flexibility for student learning, but also pose a number of challenges to learning design. These include the ones inherent to online instruction and face-to-face instruction, but also those of creating equitable alignment between the two modes to achieve the same learning outcomes. In this chapter, we report on the insights drawn from designing and delivering a second-year undergraduate information technology course on two campuses, in which students could complete any learning activity and assessment online or face-to-face. We describe our approach to support student engagement, group work, and peer review in HyFlex mode, and some challenges we faced to match learning designs to available technology. We evaluated our teaching components according to student participation and their quantitative and qualitative feedback. We found that most students appreciated the HyFlex mode delivery and while our approach was shown to be effective, it was in some way constrained by the technology available.

Complex event processing received an increasing interest during the last years with the adoption of event-driven architectures in various application domains. Despite a number of solutions that can process events in near real-time, their effectiveness for decision support relies heavily upon human domain knowledge. This poses a problem in areas that require vast amounts of specialized knowledge and background information, such as medical environments. We propose four techniques to enrich complex event processing with domain knowledge from ontologies to overcome this limitation. These techniques focus on preserving the strengths of state-of-the-art systems and enhancing them with existing ontologies to increase accuracy and effectiveness. The viability of our approach is demonstrated in a multifaceted experiment.

The heat-related health burden is expected to persist and worsen in the coming years due to an aging global population and climate change. Defining the breadth and depth of our understanding of age-related changes in thermoregulation can identify underlying causes and strategies to protect vulnerable individuals from heat. We conducted the first systematic quantitative literature review to provide context to the historical experimental research of healthy older adults – compared to younger adults or unhealthy age matched cases – during exogenous heat strain, focusing on factors that influence thermoregulatory function (e.g. co-morbidities). We identified 4,455 articles, with 147 meeting eligibility criteria. Most studies were conducted in the US (39%), Canada (29%), or Japan (12%), with 71% of the 3,411 participants being male. About 71% of the studies compared younger and older adults, while 34% compared two groups of older adults with and without factors influencing thermoregulation. Key factors included age combined with another factor (23%), underlying biological mechanisms (18%), age independently (15%), influencing health conditions (15%), adaptation potential (12%), environmental conditions (9%), and therapeutic/pharmacological interventions (7%). Our results suggest that controlled experimental research should focus on the age-related changes in thermoregulation in the very old, females, those with overlooked chronic heat-sensitive health conditions (e.g. pulmonary, renal, mental disorders), the impact of multimorbidity, prolonged and cumulative effects of extreme heat, evidence-based policy of control measures (e.g. personal cooling strategies), pharmaceutical interactions, and interventions stimulating protective physiological adaptation. These controlled studies will inform the directions and use of limited resources in ecologically valid fieldwork studies.

We extract commodity‐level sentiment from the Twittersphere in 2009–2020. A long–short strategy based on sentiment shifts more than doubles the Sharpe ratio of extant commodity factors. Commodities with lower (higher) sentiment shifts tend to be overvalued (undervalued) when the aggregate market is in backwardation (contango). The sentiment premium is more pronounced during periods of macro contraction and deteriorating funding liquidity. While the premium concentrates in commodities with higher tweet intensity, sentiment extracted from influential tweets (i.e., high number of retweets/likes) does not exhibit stronger predictive ability than low‐attention tweets. Consistent with the overreaction hypothesis, the sentiment premium fully reverses 3 years postformation.

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