1722 research outputs found
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Commitment Under Pressure: The Paradox of Post-Pandemic Workforce Recovery in Canadian Education
No full textThis study examines how the education sector in one Canadian province has navigated post-pandemic recovery between 2023 and 2025, drawing on cross-sectional survey data from a convenience sample of sector employees in the 2023–2024 (n = 1411) and 2024–2025 (n = 742) school years. The findings revealed selective improvement over time, including increased organizational commitment among teachers and other education workforce members, alongside reduced perceptions of students’ academic, social, and behavioural needs. Teachers indicated no corresponding increases in their perceived frequency of meeting students’ needs, whereas other educator sector employees indicated improvement in this area. In contrast, no year-over-year differences were found in the education workforce members’ and teachers’ stress, coping, well-being or connectedness, and job search behaviours remained high, ranging from 14 to 43%. Guided by the Job Demands–Resources (JD-R) model, these findings suggest that post-pandemic recovery reflects the establishment of a new and complex baseline. The coexistence of improved commitment with persistent job strain signals a paradox of stability amid depletion. Qualitative responses reinforced this interpretation, revealing how educators adapt to ongoing organizational resource constraints and shifting student needs. Together, the findings extend JD-R-informed understandings of post-crisis workforce adaptation and identify implications for leadership and policy aimed at supporting organizational health and workforce sustainability.This study was made possible through the funding and support of the Canadian Mental Health Association, Manitoba and Winnipeg (Grant 20564).https://www.mdpi.com/2227-7102/16/1/
Introductory Chemistry
No full textIntroductory Chemistry serves as a comprehensive guide tailored for a year-long university-level introductory chemistry course, laying the foundation for students entering advanced studies in chemistry, biochemistry, physics, and other related scientific disciplines. This resource introduces and develops foundational concepts in chemistry with clarity and precision. By placing these fundamental principles in the context of real-world applications, the text not only facilitates comprehension but also fosters an appreciation for the pivotal role chemistry plays in our contemporary world. It was edited from the OpenStax book Chemistry 2e.Campus Manitobahttps://pressbooks.openedmb.ca/introductorychemistry
Using Deep Learning to Detect Pea Root Nodules Within a Complex Soil Media Background
No full textSubmitted VersionRoot nodule phenotyping is essential for understanding biological ni-trogen fixation in legumes, an important process for crop growth and productiv-ity; however, traditional manual approaches for analyzing root nodules can be slow and prone to human bias, making them impractical for large-scale studies. More recent studies have utilized deep learning for high-throughput nodule as-sessments but usually focus on images of isolated roots. In this study, we imple-mented and evaluated two state-of-the-art deep learning architectures (YOLOv12 and Mask R-CNN) to automate the detection of root nodules from pea root sys-tems grown within a controlled rhizobox environment. To generate ground truth data, we annotated 62 high-resolution images of root systems, growing within sand-peat media mix. The study also incorporated two complementary Explainable AI (XAI) tech-niques: Gradient-weighted Class Activation Mapping++ (Grad-CAM++) for class-discriminative explanation and Feature Activation Maps for low-level at-tention visualization. A comparative evaluation of YOLOv12 and Mask R-CNN architecture shows increased nodule detection performance with YOLOv12 (precision: 59%, recall: 71%) as compared to Mask R-CNN (precision: 46%, recall: 60%), with compa-rable Intersection over Union (IoU) values (0.61 vs. 0.67). Our implementation of explainable AI techniques through Grad-CAM++ and feature activation visu-alizations help explain the performance differences observed between the two architectures.https://link.springer.com/chapter/10.1007/978-3-032-15375-3_
A Comparative Study of Forensic File Type Identification Methods for Tool Type Identification
No full textThe increase in digital communications has led to changes in the nature of documents that are often encountered in document examinations. Whereas document examiners use physical and chemical characteristics to authenticate documents and examine hypotheses about the age, origin, alterations, and signatures, digital documents cannot be subjected to such methods. This has led to calls for alternative approaches to digital document examination. In this paper, we present a comparative study that explores the determination of document origin, particularly, the identification of the creator tool type and the applicability of structural-based and machine-learning file type identification methods to this problem. To generate a baseline for the comparison of our methods, we implemented several machine learning algorithms that have most commonly and successfully been used for file type identification. These methods are then applied for tool type identification for digital documents to evaluate their relevance and effectiveness in this case. The paper focuses on the identification of creator tool types for Portable Document Format (PDF) documents due to their prevalence. We present our approach for identifying the tool used to create a document and evaluate our results against baseline results from file type identification. Our result shows that many of the structure-based analysis methods and machine learning algorithms used in file type identification can be extended to tool type identification in forensic digital document examination. The paper provides recommendations for adopting this extension and is the first work to explore the comparison of file type identification methods for creator tool type identification.This work was supported by the University of Winnipeg (Grants numbers: RSH 16792, RSH 20545, and RSH 28617) and by the Mitacs Globalink Research Internship Program.https://ieeexplore.ieee.org/document/1135755
Mobile Privacy and Security for Older Adults: A Systematic Review of Concerns, Risks, Usability, and Pathways for Support
No full textDespite the benefits of the widespread adoption of mobile technologies, older adults continue to face significant security and privacy challenges in their use of mobile devices, due to several factors. This often results in the avoidance of certain security and privacy mechanisms, leaving many older adults vulnerable to digital security challenges and privacy risks. This paper examines 41 peer-reviewed studies to investigate how older adults view and control mobile security and privacy mechanisms, risks, andchallenges. We examine the perceptions around mobile security and privacy mechanisms and educational and support strategies. Our findings highlight how closely security and privacy concerns relate to system design and support, and user knowledge. It also emphasizes promising methods such as embedded social learning, tailored training, and policy recommendations to address highlighted issues, allowing developers and policymakers to more effectively instill confidence and facilitate better digital inclusion and mobile security and privacy of older adults.This work is supported by the University of Winnipeg, Discretionary Grant, Work Study and USRA-I awards. Award numbers: RSH 25929 and RSH 27719.https://journals.sagepub.com/doi/10.1177/0733464826141618
Advanced Dutch Elm Disease Management in Winnipeg through RPAS-Based Monitoring and Elm Bark Beetle Activity Tracking
No full textThis study consisted of two projects designed to provide information to improve Dutch elm disease (DED), (Ophiostoma novo-ulmi), management methods in Winnipeg, Manitoba. The objective of the first project was to test whether a remote piloted aircraft system (RPAS) equipped with a multispectral camera can detect DED symptoms in American elm (Ulmus americana) trees. Three neighbourhoods in Winnipeg were surveyed using this technology in 2022 and 2023, and categorical maps of diseased versus healthy trees were generated for each neighbourhood using a variety of vegetation indices and methods of delineating tree canopies in the imagery. Ground disease detection surveys were conducted in conjunction with the aerial surveys to guide and validate these maps. Results for each survey showed that healthy tree canopies had significantly higher mean normalized difference vegetation index (NDVI) values than DED/hazard trees. Other vegetation indices were also tested, but mean NDVI values generated the most accurate classifications. Manually digitized polygons outlining the shape of each tree canopy also generated more accurate classifications than generic circles or rectangles centred on tree coordinates, but overall success of DED detection was still moderately low with manual polygons at 67.3%. The results from this research indicate that the use of RPAS solely to detect DED will require more refinement to increase accuracy levels to be as reliable as ground survey crews. However, the technology is effective at detecting dead elm trees or trees with advanced DED symptoms with 79.5% overall correct classification, and would therefore be a useful tool to assist with current DED management strategies, particularly in less accessible locations. The native elm bark beetle (Hylurgopinus rufipes) is the primary known insect vector of DED spread in Manitoba, while several other elm bark beetle species can also spread the disease elsewhere in North America. One of these species, the banded elm bark beetle (Scolytus schevyrewi) has been reported in rural Manitoba feeding on Siberian elm (Ulmus pumila). The objectives of the second project were to determine the beginning of emergence of summer brood of elm bark beetles in Winnipeg, and to determine if the banded elm bark beetle is present and attracted to American elm trees in Winnipeg. A pilot experiment was carried out from July 13 to September 18, 2023. American elm and Siberian elm logs were collected and left exposed in a Winnipeg neighbourhood. Logs were partially debarked throughout the study period. Beetles found on the surface of logs, boring into them, or inside the logs, along with larvae in galleries, were collected and preserved. Nearly all adult bark beetles collected were identified as banded elm bark beetles, which was unexpected given that banded elm bark beetles were not found to be attracted to American elm in previous studies in rural Manitoba. DNA bar coding technology was used to confirm that larvae and adults collected in elm logs were banded elm bark beetles. These findings suggest that banded elm bark beetles could potentially be a second significant vector of DED in Winnipeg’s urban forest.Volatus Aerospace; Mitacs; SERG InternationalMaster of Science in Environmental and Social Chang
Haptic Reading: Verse and Prose Inscriptions on Jumping Weights and Discuses
No full textThis article examines inscriptions in prose and verse on dedications of athletic equipment from pentathlon competitions, specifically jumping weights and discuses from the Archaic and Early Classical periods. By paying close attention to the layout of inscriptions and contextualizing these sorts of dedications in light of literary evocations of athletic objects, this article argues that handling and moving an athletic dedication added significantly to the meaning and potency of the inscription.https://muse.jhu.edu/article/95469
Exploring the potential of synthetic and natural chelators to enhance phytoextraction by Indian mustard in metal(loid) (As, Cd, Cu, Ni, Pb, Zn and V)-contaminated soils
No full textSoil contamination with metal(loid)s poses significant environmental and human health risks due to their non-biodegradable and highly persistent nature. Phytoextraction is an eco-friendly phytoremediation method that uses plants to extract and accumulate metal(loid)s in harvestable tissues. Chelators can enhance this process by increasing metal(loid) bioavailability through the formation of metal-chelate complexes. Despite the proven effectiveness of synthetic chelators like EDTA, its associated drawbacks, such as excessive metal solubilization, slow degradation rate, phytotoxicity, and the metal leaching risk, have limited its field application. As an alternative, natural chelators such as citric acid (CA) and oxalic acid (OA) offer lower phytotoxicity and greater biodegradability. However, the effectiveness of CA and OA compared to EDTA is poorly investigated under different soil conditions, and a knowledge gap exists in the combined application of these chelators for phytoextraction of acidic multi-metal (loid) contaminated and alkaline V-contaminated soils. Therefore, this thesis examined the effectiveness of chelators alone and in combination for phytoextraction of (i) mining-impacted acidic (pH 5.6) multi-metal (loid) contaminated (As, Cd, Cu, Ni, Pb, Zn) boreal forest soil (first study) and (ii) alkaline soil (pH 7.6) contaminated with V at two different levels (200 and 400 mg/kg V) (second study), using Indian mustard. Separate greenhouse experiments were conducted for 10 weeks (first study) and 13 weeks (second study). Six treatments were applied with triplicates in the first study (control, EDTA, CA, OA at 3 mmol/kg each; EDTA + CA, EDTA + OA at 1.5:3 mmol/kg each) and five (all treatments in study 1 except EDTA) in the second study for each contamination level. Chelators were applied twice at monthly intervals, and soil pore water was collected thrice; before chelator application, after the first application, and after the second application. At the end of the experiment, aboveground biomass (dry weight) and metal(loid) concentrations in pore water, soil, and plant tissues were analyzed using ICP-AES. Results of the first study demonstrated that while EDTA alone or combined with CA and OA was the most effective chelator in increasing the metal(loid) bioavailability in multi-metal(loid)-contaminated soil, it induced severe phytotoxicity in Indian mustard, leading to plant death. Conversely, CA and OA alone had minimal impact on metal(loid) bioavailability and plant uptake but did not induce phytotoxicity. These results suggest that Indian mustard, when used with optimized concentrations of natural chelators alone or in combination with EDTA, could be effective for remediating multi-metal(loid)-contaminated boreal forest soils. In the second study also, EDTA combined applications with CA and OA significantly enhanced the V in pore water, soil, and plant tissues at the 200 mg/kg V-contaminated soils, without inducing phytotoxicity. However, at the 400 mg/kg V-contaminated soils, these treatments were ineffective in increasing V bioavailability and plant uptake. At both V concentrations, natural chelators alone had no significant effect on V phytoextraction. These findings suggest that Indian mustard is suitable for phytoremediation of both acidic multi-metal(loid) (As, Cd, Cu, Ni, Pb, Zn) and alkaline V-contaminated soils. Additionally, the findings highlighted that chelate-assisted phytoextraction is an effective approach to remediate multi-metal(loid) and moderate V-contaminated soils (~ 200 mg/kg). Further investigations are beneficial on optimizing natural chelator concentrations to enhance the phytoextraction efficiency.Master of Science in Bioscience, Technology, and Public Polic
Energy Efficiency Programming and Indigenous Rights in Manitoba, Canada
No full textImproving energy efficiency is increasingly recognized as key to the energy transition and offers numerous benefits at the household level. There has been little scholarship to date addressing how energy efficiency is governed, and even less study of how Indigenous Nations and settler governments might co-develop energy efficiency policy. This gap is notable because energy efficiency policy can exacerbate equity issues when done without proper consideration of the diverse needs of different energy users. Through a document analysis and key informant interviews, this case study of energy efficiency governance in Manitoba, Canada investigates how Efficiency Manitoba works with Indigenous Nations and how well its programs meet the needs of Indigenous communities. Efficiency Manitoba’s approach to building relationships with Indigenous Peoples has several strengths that other settler governments and institutions would do well to emulate. Evaluating the overall success of Efficiency Manitoba’s programs for Indigenous participants is inhibited by limited data availability, so there is a need for better measurement and transparency. This research also found that the overlap between housing policy and residential energy efficiency policy is much greater than is commonly acknowledged in energy efficiency literature. Efficiency Manitoba is already collaborating with Indigenous-led housing initiatives, but more explicit integration of energy efficiency and housing supports could be beneficial, especially on First Nations reserves."I would like to acknowledge funding from the University of Winnipeg President’s Distinguished Graduate Student Scholarship, the Government of Canada’s New Frontiers in Research Fund (NFRF) CANSTOREnergy project NFRFT-2022-00197, and other funding from the University of Winnipeg Master of Environment and Social Change program."Master in Environmental and Social Chang