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    Overcoming Critical Challenges Hindering Resistance Spot Welding of Dissimilar Advanced High Strength Steel Joints: LME Mitigation and Weld Class Prediction
    (University of Waterloo, 2026-05-04) Nooranfar, Melika
    Reducing carbon dioxide emissions from the transportation sector has driven demand for lighter vehicles. Advanced high-strength steels (AHSS) enable the use of thinner gauges without compromising crashworthiness due to ability to absorb high fracture energy. Because these materials are exposed while in-service AHSS are typically zinc-coated for corrosion protection. However, excellent mechanical strength is insufficient for these materials to be used for automotive application, they must also be capable of being welded into the automotive structure. Resistance spot welding remains the dominant joining method in automotive body-in-white production, yet two challenges affect weld quality in dissimilar stack-ups: liquid metal embrittlement (LME) cracking and the absence of reliable offline quality prediction. Most existing studies have focused on similar stack-ups, leaving dissimilar joints inadequately addressed. This research examines both challenges using dissimilar configurations representative of industrial practice. The first part investigates LME mitigation in two-sheet joints of zinc-coated 3G-980 AHSS and interstitial-free steel. A short high-current pre-pulse (16 kA, 20 ms) reduced the crack index from 0.56 to 0.14, a 75% reduction. Cross-sectional analysis revealed that the pre-pulse shifted the nugget toward the IF sheet, increasing the distance between the susceptible 3G-980 surface and the fusion boundary. This geometric shift reduced the overlap between liquid zinc and tensile stresses, suppressing crack formation. Contrary to welding made in similar material joint configurations where high-current pre-pulses intensified cracking, the same approach effectively mitigates LME in dissimilar configurations. The second part develops a machine learning framework for weld quality classification in three-sheet dissimilar AHSS stack-ups. Each weld was classified as acceptable (Ok), No weld, or Expulsion based on online assessments. Random Forest and XGBoost classifiers were trained on a 137-sample dataset, with XGBoost achieving 89.3% accuracy and superior performance near class boundaries. The trained models enabled identification of no weld regions and provided a basis for adaptive parameter selection. Both LME severity and weld class are critical indicators of joint integrity yet have rarely been addressed together for dissimilar coated AHSS. This thesis provides an experimentally grounded vii framework linking welding parameters to quality outcomes, offering practical pathways for process optimization in automotive resistance spot welding.
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    Patterns of home care assessment and service provision before and during the COVID-19 pandemic in Ontario, Canada
    (Public Library of Science, 2022-03-30) Sinn, Chi-Ling Joanna; Sultan, Heebah; Turcotte, Luke Andrew; McArthur, Caitlin; Hirdes, John P.
    Objective The objective was to compare home care episode, standardised assessment, and service patterns in Ontario's publicly funded home care system during the first wave of the COVID-19 pandemic (i.e., March to September 2020) using the previous year as reference. Study design and setting We plotted monthly time series data from March 2019 to September 2020 for home care recipients in Ontario, Canada. Home care episodes were linked to interRAI Home Care assessments, interRAI Contact Assessments, and home care services. Health status measures from the patient's most recent interRAI assessment were used to stratify the receipt of personal support, nursing, and occupational or physical therapy services. Significant level and slope changes were detected using Poisson, beta, and linear regression models. Results The March to September 2020 period was associated with significantly fewer home care admissions, discharges, and standardised assessments. Among those assessed with the interRAI Home Care assessment, significantly fewer patients received any personal support services. Among those assessed with either interRAI assessment and identified to have rehabilitation needs, significantly fewer patients received any therapy services. Among patients receiving services, patients received significantly fewer hours of personal support and fewer therapy visits per month. By September 2020, the rate of admissions and services had mostly returned to pre-pandemic levels, but completion of standardised assessments lagged behind. Conclusion The first wave of the COVID-19 pandemic was associated with substantial changes in Ontario's publicly funded home care system. Although it may have been necessary to prioritise service delivery during a crisis situation, standardised assessments are needed to support individualised patient care and system-level monitoring. Given the potential disruptions to home care services, future studies should examine the impact of the pandemic on the health and well-being of home care recipients and their caregiving networks.
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    A multi-stage process to develop quality indicators for community-based palliative care using interRAI data
    (Public Library of Science, 2022-04-07) Guthrie, Dawn M.; Williams, Nicole; Beach, Cheryl; Buzath, Emma; Cohen, Joachim; Declercq, Anja; Fisher, Kathryn; Fries, Brant E.; Goodridge, Donna; Hermans, Kirsten; Hirdes, John P.; Seow, Hsien; Silveira, Maria; Sinnarajah, Aynharan; Stevens, Susan; Tanuseputro, Peter; Taylor, Deanne; Vadeboncoeur, Christina; Martin, Tracy Lyn Wityk
    Background Individuals receiving palliative care (PC) are generally thought to prefer to receive care and die in their homes, yet little research has assessed the quality of home- and community-based PC. This project developed a set of valid and reliable quality indicators (QIs) that can be generated using data that are already gathered with interRAI assessments - an internationally validated set of tools commonly used in North America for home care clients. The QIs can serve as decision-support measures to assist providers and decision makers in delivering optimal care to individuals and their families. Methods The development efforts took part in multiple stages, between 2017-2021, including a workshop with clinicians and decision-makers working in PC, qualitative interviews with individuals receiving PC, families and decision makers and a modified Delphi panel, based on the RAND/UCLA appropriateness method. Results Based on the workshop results, and qualitative interviews, a set of 27 candidate QIs were defined. They capture issues such as caregiver burden, pain, breathlessness, falls, constipation, nausea/vomiting and loneliness. These QIs were further evaluated by clinicians/decision makers working in PC, through the modified Delphi panel, and five were removed from further consideration, resulting in 22 QIs. Conclusions Through in-depth and multiple-stakeholder consultations we developed a set of QIs generated with data already collected with interRAI assessments. These indicators provide a feasible basis for quality benchmarking and improvement systems for care providers aiming to optimize PC to individuals and their families.
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    Factors influencing antimicrobial resistance in the European food system and potential leverage points for intervention: A participatory, One Health study
    (Public Library of Science, 2022-02-22) Lambraki, Irene Anna; Cousins, Melanie; Graells, Tiscar; Leger, Anais; Henriksson, Patrik; Harbath, Stephan; Troell, Max; Wernli, Didier; Jorgensen, Peter Sogaard; Desbois, Andrew P.; Carson, Carolee A.; Parmley, Elizabeth Jane; Majowicz, Shannon Elizabeth
    Introduction Antimicrobial resistance (AMR) is a global crisis that evolves from a complex system of factors. Understanding what factors interact is key to finding solutions. Our objective was to identify the factors influencing AMR in the European food system and places to intervene. Materials and methods We conducted two workshops involving participants with diverse perspectives to identify the factors influencing AMR and leverage points (places) to target interventions. Transcripts were open coded for factors and connections, then transcribed into Vensim 8.0.4 to develop a causal loop diagram (CLD) and compute the number of feedback loops. Thematic analysis followed to describe AMR dynamics in Europe's food system and places for intervention. The CLD and themes were confirmed via participant feedback. Results Seventeen participants representing human, animal and agricultural sectors identified 91 CLD factors and 331 connections. Seven themes (e.g., social and economic conditions) describing AMR dynamics in Europe's food system, five 'overarching factors' that impact the entire CLD system (e.g., leadership) and fourteen places for intervention (e.g., consumer demands) emerged from workshop discussions. Most leverage points fell on highly networked feedback loops suggesting that intervening at these places may create unpredictable consequences. Conclusions Our study produced a CLD of factors influencing AMR in Europe's food system that implicates sectors across the One Health spectrum. The high connectivity between the CLD factors described by participants and our finding that factors are connected with many feedback mechanisms underscores the complexity of the AMR problem and the challenge with finding long-term solutions. Identifying factors and feedbacks helped identify relevant leverage points in the system. Some actions, such as government's setting AMU standards may be easier to implement. These actions in turn can support multi-pronged actions that can help redefine the vision, values and goals of the system to sustainability tackle AMR.
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    Multicenter international assessment of a SARS-CoV-2 RT-LAMP test for point of care clinical application
    (Public Library of Science, 2022-05-11) Lu, Suying; Duplat, David; Benitez-Bolivar, Paula; Leon, Cielo; Villota, Stephany D.; Veloz-Villavicencio, Eliana; Arevalo, Valentina; Jaenes, Katariina; Guo, Yuxiu; Cicek, Seray; Robinson, Lucas; Peidis, Philippos; Pearson, Joel D.; Woodgett, Jim; Mazzulli, Tony; Ponce, Patricio; Restrepo, Silvia; Gonzalez, John M.; Bernal, Adriana; Guevara-Suarez, Marcela; Pardee, Keith; Cevallos, Varsovia E.; Gonzalez, Camila; Bremner, Rod
    Continued waves, new variants, and limited vaccine deployment mean that SARS-CoV-2 tests remain vital to constrain the coronavirus disease 2019 (COVID-19) pandemic. Affordable, point-of-care (PoC) tests allow rapid screening in non-medical settings. Reverse-transcription loop-mediated isothermal amplification (RT-LAMP) is an appealing approach. A crucial step is to optimize testing in low/medium resource settings. Here, we optimized RT-LAMP for SARS-CoV-2 and human β-actin, and tested clinical samples in multiple countries. “TTTT” linker primers did not improve performance, and while guanidine hydrochloride, betaine and/or Igepal-CA-630 enhanced detection of synthetic RNA, only the latter two improved direct assays on nasopharygeal samples. With extracted clinical RNA, a 20 min RT-LAMP assay was essentially as sensitive as RT-PCR. With raw Canadian nasopharygeal samples, sensitivity was 100% (95% CI: 67.6% - 100%) for those with RT-qPCR Ct values ≤ 25, and 80% (95% CI: 58.4% - 91.9%) for those with 25 < Ct ≤ 27.2. Highly infectious, high titer cases were also detected in Colombian and Ecuadorian labs. We further demonstrate the utility of replacing thermocyclers with a portable PoC device (FluoroPLUM). These combined PoC molecular and hardware tools may help to limit community transmission of SARS-CoV-2.