82837 research outputs found
Sort by
Tailoring Electrical Resistivity of MIL-100 (Fe) Using Carbon Modifiers for Efficient Electrothermal Regeneration
No full textThe growing concern over Volatile Organic Compound (VOC) emissions has led to an increased demand for efficient adsorption and regeneration technologies. Metal-Organic Frameworks (MOFs) have emerged as promising material for VOC capture due to their high surface area, tunable pore structures, and selectivity. However, traditional MOFs, including MIL-100 (Fe), suffer from poor electrical conductivity, limiting their application in advanced regeneration techniques such as electrothermal regeneration. This research aimed to tailor the electrical resistivity of MIL-100 (Fe) by incorporating conductive carbon materials–graphene, carbon nanotubes (CNTs), and porous carbon (PC)– while preserving its adsorption performance.
MIL-100 (Fe) was synthesized with varying concentrations of the carbon additives via sonication-assisted method. Electrical resistivity measurements revealed that graphene-modified samples exhibited the most notable conductivity improvements, achieving values as low as 0.9 Ω·m at 20 mg/ml. CNT-modified samples also showed enhanced conductivity, but required higher concentrations to achieve low resistivity (2.3 Ω·m at 30mg/ml). Porous carbon had the least effective in improving conductivity. X-ray diffraction analysis showed that all samples exhibited similar peak positions, indicating that the crystal structure of MIL-100 (Fe) was largely preserved after modification. However, a decrease in peak sharpness was observed in CNT-modified samples, suggesting a reduction in crystallinity. Scanning Electron Microscopy images further confirmed that the characteristic morphology of MIL-100 (Fe) was retained across all samples, with carbon additives appearing well-dispersed. Minor particle aggregation was noted in CNT-modified samples at higher concentrations, but overall, the integration of additives was uniform and did not result in any notable morphological deformation. Nitrogen adsorption and Thermogravimetric Analysis further demonstrated that carbon incorporation slightly reduced surface area and pore volume but delayed thermal degradation. Additionally, n-heptane isotherms showed that the modified MIL-100 (Fe) samples retained their VOC uptake effectiveness. Building on these conductivity improvements, electrothermal regeneration was compared against conventional thermal conduction regeneration methods to assess energy usage, heating rate, and overall desorption efficiency. The modified MIL-100 (Fe) samples demonstrated reduced energy demands and faster desorption cycles when subjected to electrothermal heating, owing to the immediate and targeted temperature increases facilitated by the enhanced both electrical and thermal conductivity. Specifically, the graphene-modified sample reached 120 °C within 3 minutes, consuming a total of 13.9 kJ, while the CNT-modified sample reached the same temperature in 5 minutes with an energy consumption of 11.0 kJ. In contrast, conventional thermal regeneration required substantially more time to reach 120 °C and consumed approximately 129.0 kJ of energy. These results underscore the efficiency and responsiveness of electrothermal regeneration in comparison to conventional thermal conduction regeneration method. In conclusion, this study successfully developed conductive MIL-100 (Fe) composites by integrating carbon additives, enabling the potential application of electrothermal regeneration. The graphene-modified MIL-100 (Fe) demonstrated the most promising properties, making it particularly well-suited for fast and energy-efficient electrothermal regeneration processes. These findings support the advancement of MOF-based materials for sustainable air pollution control technologies
Testing Motivations to Write Reviews in the Field and Lab
No full textSSHRC IDG awarded 2025: Product reviews strongly influence consumer decisions, but they are often biased and incomplete because only a small share of buyers write reviews, and few update them as their experience with the product evolves. As a result, most reviews reflect first impressions rather than long-term ownership. This project partners with a large review platform to test how psychologically informed, nudge-style messages can encourage consumers to both write new reviews and update existing ones. It investigates three key questions: 1) How different motivational messages affect the likelihood of writing a review, 2) How these motivations influence the likelihood of updating a review, and 3) How messaging impacts the distribution of star ratings. Based on consumer behavior research, the study tests three motivations: helping other consumers, reciprocating or supporting the firm, and enhancing one’s self-image (e.g., feeling like an expert or contributor). The project examines how highlighting these motivations through simple messages influences review creation and updating, and whether effects differ depending on product quality and rating valence. Practically, the findings help platforms increase engagement, provide consumers with more representative and informative reviews, and help firms understand how to encourage more ratings. Theoretically, the study extends prior research by applying established motivations to nudge-based messaging interventions and by exploring the relatively understudied area of review updating, comparing it to initial review writing motivations
2025 Society for Cognitive Studies of the Moving Image Conference
No full textSSHRC CG awarded 2025: The Society for Cognitive Studies of the Moving Image (SCSMI) has been at the international forefront of interdisciplinary research into the production, reception, cultures and analysis of moving images for nearly thirty years. This will be the first conference of SCSMI to be hosted in Canada, featuring over eighty presentations from participants in over twenty countries, alongside keynote talks, QnA sessions with filmmakers, a sound workshop on audio techniques, a mentorship luncheon, and free public events. Event videos will be made available through YouTube. The conference will promote interdisciplinary exchange across the humanities, sciences, social sciences, and fine arts—especially philosophy, psychology, neuroscience, media studies, and creative media. The event aims to strengthen national and international collaboration, showcase Canadian excellence in moving-image scholarship and practice, and foster new research networks
50 Years of CIUS: Ukrainian Studies and Re-Centering Humanities (Symposium and Exhibition)
No full textSSHRC CG awarded 2026: In 2026, the Canadian Institute of Ukrainian Studies (CIUS) at the University of Alberta will celebrate its 50th anniversary with two interconnected initiatives: an international symposium and a traveling exhibition. The international symposium, “Re-Centering Humanities: Ukraine and the World,” will convene leading scholars, policy experts, and thought leaders to examine Ukraine’s evolving global significance—particularly following Russia’s full-scale invasion in 2022. The event positions Ukraine not as a peripheral subject but as a key agent in shaping contemporary debates on democracy, war and peace, historical memory, identity, empire, and cultural resilience. Through keynotes, panels, and roundtables, the symposium will explore how geopolitical upheaval has transformed research agendas and reframed Ukraine’s place in global humanities and social sciences. In parallel, the traveling exhibition “CIUS-50: Shaping Knowledge and Community” will highlight CIUS’s five decades of impact through themes of institutional milestones, scholarship and community engagement, and transnational Ukrainian studies. Featuring archival materials, publications, oral histories, and digital media, the exhibition will launch in Edmonton and Toronto before touring across Canada, with a digital version available internationally. Aligned with SSHRC’s Future Challenge Areas Evolving Narratives of Cultures and Histories and The Arts Transformed, the project translates scholarly research into accessible public storytelling. By integrating academic debate with public outreach and multimedia formats, it mobilizes knowledge about Ukraine within the context of war, migration, and shifting global narratives. Graduate and undergraduate students will gain hands-on experience in research, editing, translation, and design. Overall, the initiative marks both reflection and renewal—strengthening collaboration, mentorship, and the public role of the humanities in connecting communities across borders
A Data-Driven Decision Support System to Enhance Planning and Scheduling in Industrial Construction Projects
Get PDFThe planning and execution of industrial construction projects—such as nuclear plants, and oil and gas production facilities—present significant challenges due to their large scale, fast-tracked timelines, and the complexity of managing extensive resources and a workforce. These projects often suffer from delays and cost overruns exacerbated by the lack of integration and automation in current scheduling practices, as well as fragmented data storage and retrieval systems. Traditional approaches to planning and scheduling in these environments rely on manual processes and the subjective expertise of project managers, leading to frequent delays, cost overruns, and inefficiencies. Accordingly, this research explores innovative methodologies that leverage advanced, data-driven decision support systems, including reinforcement learning (RL), ontology-based knowledge management, natural language processing (NLP), data mining algorithms, and simulation-based planning techniques, to enhance the efficiency and effectiveness of industrial construction project management.
This research focuses first on automating scheduling processes within modularized industrial construction projects, particularly in the context of offsite fabrication shops where components are preassembled before being delivered to construction sites. Current scheduling practices are labor-intensive and often inadequate for managing the high variability and complexity of these environments. To overcome these limitations, this research develops an RL model that simulates the dynamic environment of a fabrication shop and integrates a dueling deep Q-network (DQN) with a prioritized replay buffer to manage the scheduling of pipe spools (critical, customized components in many industrial projects). By formulating the scheduling process as a Markov Decision Process (MDP), the RL model learns from historical data to optimize scheduling decisions, reducing the need for manual intervention and improving overall scheduling efficiency. The model's effectiveness is demonstrated through its application to real-world data from a fabrication shop in Alberta, Canada, where it outperforms traditional scheduling methods and provides a robust foundation for future advancements in automated construction scheduling.
The second key area of this research addresses challenges associated with data management and knowledge retrieval in the early stages of industrial project planning. In current practice, the fragmentation of data across multiple sources, such as drawings, schedules, reports, and personnel experience, hinders efficient project planning and execution. This research proposes the development of an ontology-driven framework, inspired by Advanced Work Packaging (AWP), to organize and ease retrieval of critical project knowledge. The ontology is developed to capture the complexities of industrial construction projects including the relationships between various work packages, resources, and project objectives. By systematically structuring this domain-specific knowledge, the ontology not only facilitates efficient data management but also allows professionals to make more informed decisions during planning and execution phases. The ontology is validated through use cases that demonstrate its ability to reduce the time and resources required for project planning, leading to more consistent and effective project outcomes.
The third aspect of this research focuses on the development of data-driven simulation models to support preliminary planning in industrial projects. These models aim to address the uncertainties and incomplete information that often characterize early stages of fast-tracked industrial projects. By aggregating data from diverse sources and applying NLP and unsupervised learning techniques, the research creates clusters of project components that can be used to develop templates or fragnets (standardized sequences of activities and resource allocations). These fragnets provide a valuable decision support tool that professionals can use to enhance the accuracy and efficiency of early project planning, reducing the reliance on subjective judgment and improving the alignment of engineering, procurement, and construction activities. The effectiveness of this approach is validated through a case study of an industrial project in Canada, which highlights the model's potential to improve scheduling efficiency and project performance by enabling dynamic updates and real-time data integration.
This research offers significant contributions to the field of industrial construction by addressing some of its most pressing challenges through the application of advanced data-driven methodologies. The development of an RL-based scheduling model, an ontology-driven knowledge management framework, and data-driven simulation models provides practical tools for enhancing the planning, scheduling, and execution of complex industrial projects. These innovations not only improve efficiency and reliability of construction processes but also lay the groundwork for future research and development in the field of construction engineering and management, particularly in regard to data-driven decision-making in industrial project management
Religious Reversion
No full textA considerable amount of research supports the longstanding claim that religious belief is an integral part of how people manage existential concerns, especially worries about death and dying via shared rituals, belonging, and belief in afterlives. However, very little research has examined how people who leave religion continue to manage mortal concerns. Building on attachment theory and experimental-existential psychology, the religious reversion hypothesis states that when apostates or people undergoing apostasy are under acute existential threat, they will show attitudinal and behavioral shifts back toward their previously held religious worldview as a way to reinstate existential and psychological equanimity. To test this hypothesis, four studies (N = 875) were conducted to measure the effect mortality salience has on willingness to endorse the existence of supernatural phenomena and entities amongst those who grew up religious but have since become less religious. In Study 1 (n = 270), participants were reminded of death and then responded to a questionnaire assessing their openness to the existence of the supernatural. Study 2 (n = 142) measured certainty in God’s non-existence following mortality salience. Study 3 (n = 257) examined the impact of mortality salience on optimistic teleological thinking. Finally, Study 4 (n = 206) tested whether those with weakened religious convictions would be drawn toward modern-day mythology in the form of superhero fandom after contemplating their own death. Theoretical implications and potential future directions are discussed
PHYTOREMEDIATION POTENTIAL OF SEVEN NATIVE PLANT SPECIES FOR HYDROCARBON CONTAMINATED PEAT SOILS
No full textAlberta’s economy depends on the oil and gas industry, including oil sands mines, well sites, and pipelines, which contribute to the growing risk of contamination in peatlands. Hydrocarbon pollution in these ecosystems threatens their vital soil functions, carbon storage capacity, and biodiversity. Despite their ecological importance, effective remediation strategies for peatlands remain limited. Phytoremediation, a cost effective approach that uses plants to reduce contaminants, offers a sustainable solution for addressing this issue in these environments.
The objective of this research was to evaluate the ability of seven native wetland species to germinate, tolerate, survive, grow, and remove high hydrocarbon concentrations, and to identify best performing species for hydrocarbon remediation. The phytoremediation research was undertaken in the greenhouse with seven plants species exposed to hydrocarbon contaminated peat soil at two soil water contents (saturation, field capacity) for 12 weeks. The seed germination research was conducted in the greenhouse and laboratory with plant seeds exposed to hydrocarbon contaminated peat soil and water in two light treatments (light, dark) for 4 weeks.
All native plant species, tolerated and survived 100 % in hydrocarbon peat soil, although growth and remediation effectiveness varied. Carex aquatilis, Carex utriculata, and Glyceria grandis had significant growth and biomass accumulation under contamination; Typha latifolia had less vigorous growth. These species effectively removed specific contaminants (shoot and root for F2, F3, F4; root for benzo[a]anthracene, benzo[a]pyrene, benzo[e]pyrene, benzo[bj]fluoranthene, benzo[ghi]perylene, chrysene, dibenz[ah]anthracene, fluoranthene, pyrene) indicating complementary roles that enhance overall remediation. Saturated conditions promoted plant biomass and enhanced hydrocarbon uptake, while field capacity conditions promoted more efficient hydrocarbon removal from the soil. Seed germination results showed that Glyceria grandis and Scirpus microcarpus had high resilience with strong germination even in contaminated settings. Carex aquatilis and Typha latifolia showed modest germination. This resilience suggests that these species could be particularly useful for phytoremediation efforts in hydrocarbon contaminated wetlands. Carex utriculata and Schoenoplectus tabernaemontani displayed greater sensitivity, with lower germination success under similar conditions, indicating a need to pair these sensitive species with more resilient ones to optimize restoration efforts. The results highlight the potential suitability of these native wetland species for the phytoremediation of hydrocarbon contaminants in peatlands, offering an effective and environmentally sustainable remediation strategy for hydrocarbon contaminated soil and water
Insight into government, May 16, 2025
No full textAlberta's independent newsletter on government & politics
