Concordia University

Thermo-reversible kerosene gel fuels are formulated using 1,3:2,4-di-O-benzylidene sorbitol (DBS) as a low-molecular-weight organogellant, dimethyl sulfoxide (DMSO) as a stock-solution solvent, and 1-hexanol as a co-solvent. Gelation behavior is interpreted using a Hansen solubility parameter framework, where stable gelation occurs when R<13, while mixtures with R≥13 remain as suspensions. The results show that gel formation and gelation kinetics are strongly governed by formulation composition. Increasing gellant concentration enhances network formation, resulting in significantly faster gelation. Rheological measurements confirm a transition from a weaker, more deformable network at lower gellant concentrations to a stiffer and more brittle network at higher concentrations. In contrast, increasing hexanol concentration enhances network flexibility. Thermal analysis reveals that increasing hexanol concentration lowers the glass transition temperature, indicating increased molecular mobility within the gel network. Single-droplet combustion experiments demonstrate that formulation composition also influences combustion behavior. At a gellant concentration of 12 wt%, the droplet undergoes complete thermo-reversible melting and burns like liquid fuel. In contrast, at a gellant concentration of 10 wt%, combustion occurs with an outer DBS-rich shell surrounding the droplet, restricting the evaporation of unreacted fuel vapor. All tested gel fuels burn without leaving solid residue. These results establish direct links between solvent compatibility, supramolecular network strength, and droplet combustion behavior in kerosene-rich thermo-reversible gel fuels.

In many second/foreign-language classrooms, students are expected to learn much or even most of their vocabulary without explicit instruction, simply through exposure to a rich variety of words in meaningful contexts. In fact, however, there are few studies which would allow us to estimate the number of words learners are typically exposed to in second/foreign-language classrooms. In this study, the vocabulary available in the speech of ten teachers in intensive communicative ESL classes for children in Quebec was analysed using specially designed computer programs. The words which occurred in classroom transcripts were classified according to their status as high-frequency or 'unusual' words, according to lists developed by Nation (1986). The working assumption was that a large number of unusual words would be indicative of a rich lexical environment, whereas the absence or extreme rarity of such words would indicate that the classroom vocabulary was poor. The number of unusual words was found to be quite low in short periods of classroom interaction. However, an interpretation of the findings suggest that the actual richness of the vocabulary available may be greater than it appears in terms of this measure.

Abstract Nature‐based Solutions (NbS) encompass a spectrum of conservation and restoration actions aimed at improving biodiversity, climate, and water outcomes. Considerable research exists that focuses on prioritizing either conservation or restoration, or specific environmental outcomes. Yet, there is a need to develop integrated frameworks that align multiple outcomes and enable comprehensive environmental and economic assessments. Here, we present an integrated framework leveraging an AI agent that interprets species' habitat and connectivity changes along with climate and water co‐benefits to select optimal conservation and restoration priority areas. We implement this framework through scenarios maximizing biodiversity protection with ecological integrity, carbon storage, and water co‐benefits to achieve Canada's 30 × 30 conservation and restoration targets. Our results suggest that prioritizing the protection of threatened biodiversity and irrecoverable carbon storage would optimally enhance existing Protected Areas outcomes and conserve 30% of lands by 2030. However, effectively restoring 30% of degraded land will require targeted actions in existing natural and transformed ecosystems. The assessment of current anthropogenic pressures suggests that conservation and restoration actions may enhance climate resilience for forestry in natural lands and potentially benefit agricultural production and public health in transformed lands. Moreover, the mining sector represents the largest growing pressure on both conservation and restoration priorities in the upcoming decade. Overall, this integrated framework reveals strategic conservation and restoration priorities to align environmental targets, while identifying opportunities to coordinate NbS interventions across sectors.

This study explores the use of nonlinear electroencephalography (EEG) features-including correlation dimension, sample entropy, fractal dimension, permutation entropy, and the Lyapunov exponent-to capture the brain's complex dynamics during four cognitive states: idea generation, evolution, evaluation, and rest, observed in modified figural tasks from the Torrance Test of Creative Thinking. Grounded in a nonlinear design-dynamics model that conceptualizes design creativity as a chaotic process highly sensitive to initial conditions, this research offers a preliminary investigation into how distinct EEG patterns characterize different phases of creative cognition. The results reveal that brain activity exhibits varying nonlinear and chaotic dynamics across cognitive states, with key features and regions-particularly in the frontal, parietal, and central lobes-contributing significantly to state differentiation. The Lyapunov exponent emerges as the most influential feature, aligning with theoretical models of creativity as an initial-condition-sensitive process, while correlation and fractal dimensions reflect shifts in the brain's fractal organization, especially in frontal and central regions. These nonlinear measures, particularly in the parietal, central, and temporal areas, effectively distinguish cognitive phases, and the observed dominance of left hemisphere activity suggests asymmetrical neural processing during creative design tasks. As a novel application of these features in this context, the study offers a comprehensive portrait of brain activity across creative states and establishes a foundation for further exploration of the neurocognitive mechanisms underpinning design creativity.

Leadership research has paid limited attention to how distinct leadership behaviours operate jointly under conditions of high complexity in high-reliability settings. This study examines how transformational and directive leadership behaviours combine to influence team psychological safety and patient outcomes during complex surgical procedures. Drawing on situational strength theory and integrative leadership perspectives, we argue that the complementarity of people-focused (transformational) and task-focused (directive) leadership becomes especially functional when surgical complexity is high, enhancing team psychological safety and indirectly improving patient outcomes. We test these arguments using multi-source, time-sequenced data from 150 surgeries, including third-party observations of intraoperative leadership behaviours, team reports of psychological safety, objective indicators of surgical errors and blood loss, and patient-reported postoperative complications. Results show that under high surgical complexity, transformational and directive leadership interact to predict higher team psychological safety. In turn, psychological safety is associated with more observed surgical errors per hour but fewer and less severe post-discharge complications. Transformational leadership shows no unconditional main effects; rather, its benefits emerge only when paired with directive leadership under high complexity. These findings highlight the importance of contextual boundary conditions and demonstrate how leadership combinations shape performance processes and outcomes in high-reliability surgical environments.