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UNB Scholar is an institutional repository initiative of UNB Libraries intended to collect, preserve, showcase, and promote the open access scholarly output of the UNB community. Use UNB Scholar to explore specific collections, or search all content in the repository. Material submitted to the repository will also be freely discoverable online through Google and other major search engines.
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Recent Submissions
Evaluating asphalt mixture performance in New Brunswick: Defining baselines for volumetric design with performance verification
(University of New Brunswick, 2025-02) Biglari, Moein; Sanchez-Castillo, Xiomara
This study aimed to evaluate the asphalt mixtures used in New Brunswick to establish thresholds as a significant step toward adopting the Balanced Mix Design (BMD) approach. For this purpose, asphalt cores were extracted from six in-service pavement sections in the province. Additionally, two widely used mixtures in New Brunswick were produced and compacted in the laboratory. The Tensile Strength Ratio (TSR) test was conducted to evaluate the moisture susceptibility of the laboratory-prepared specimens. To assess the rutting potential of both cored and laboratory mixes at high temperatures, the Rapid Shear Rutting Test (Ideal RT) test and Hamburg Wheel Track Test (HWTT) test were utilized. The Indirect Tensile Asphalt Cracking Test (Ideal CT) test and Semicircular Bend (SCB) test were employed to investigate the fracture performance of mixes at intermediate and low temperatures, respectively. Finally, using road survey data collected by (Automatic Road Analyzer) ARAN, final thresholds were determined as acceptance criteria for the province of New Brunswick.
A system not their own: Investigating organizational barriers and facilitators to mental health care access among youth
(University of New Brunswick, 2025-02) Miller, David; Ronis, Scott
Onset of mental illness predominantly occurs in adolescence, with epidemiological trends continuing to show that youth represent the greatest comparative year-over-year increase in mental illness onset among age cohorts (Canadian Institute for Health Information, 2022; Raballo & Poletti, 2020). Despite being most likely to experience the onset of psychopathology, 40% of youth with a mental illness are unable to access appropriate supports (Canadian Institute for Health Information, 2015, 2022; Mental Health Commission of Canada, 2016). Barriers stem from constraints in the accessibility and availability of services and are exacerbated by youths’ positions within overarching care systems (de Haan et al., 2013, 2018; Gouliquer & Poulin, 2005). Youth face challenges related to their lack of autonomy, and they disproportionately rely on caregivers and providers for symptom identification and treatment adherence (Birleson & Vance, 2008; Iyer et al., 2015; Wittevrongel et al., 2024). Despite their reliance on adults, 60% of youth endorse receiving little support from others when accessing care (Canadian Institute for Health Information, 2022). As such, it is crucial to obtain youth perspectives to determine ways in which their limited agency affects help seeking in a primarily service-provider-controlled health system. Thirty-four semi-structured interviews were collected as part of the Atlantic Canada Children’s Effective Service Strategies Mental Health (ACCESS-MH) project (ACCESS-MH, 2014), a large-scale multi-site qualitative research project examining barriers and facilitators to mental health treatment among youth in Atlantic Canada. Interviews were analyzed using the Psycho-Social Ethnography of the Commonplaces (P-SEC) methodology to highlight the impact of systemic policies and protocols on youth mental health journeys. Complications to access stemming from provincial mental health policies or protocols were coded as “Organizational Moments” (OMs). Two OMs comprise individual manuscripts in this thesis to allow for in-depth analysis of specific complications, coping strategies, and schematic shifts encapsulating the way youth made sense of the barriers to care. Findings provide a contextual perspective of the unique barriers youth face that stem from stepped-care treatment models, standardized care approaches, and legal nonautonomy.
Beyond moral leadership: Edward H. Levi and the need for structural reform in the Attorney General’s office after Watergate
(University of New Brunswick, 2025-02) Purnell, Elizabeth; Corke, Sarah-Jane
In the aftermath of Watergate, President Gerald R. Ford nominated Dr. Edward H. Levi as Attorney General (AG) of the United States. Ford hoped Levi’s appointment would symbolize a new tradition of an independent AG. As the nation’s chief law officer and member of the Cabinet, the AG had become enormously influential since the position’s creation in 1789. However, politics and ambiguous language concerning the roles and responsibilities of the AG did much to undermine the AGs independence. Ford, hoping the AG’s character alone would restore the office’s integrity, sought an AG who embodied independence, integrity, and professionalism. This thesis argues that although Levi epitomized these three traits, they did not ensure his success in establishing long-lasting structural reforms necessary to insulate the position from politicization and secure a nonpartisan AG in perpetuity.
Leveraging bilingual dictionaries to learn word embeddings for low-resource languages
(University of New Brunswick, 2025-02) Bear, Diego; Cook, Paul
Word embeddings [33, 36] have been used to bolster the performance of natural language processing systems in a wide variety of tasks, including information retrieval [42] and machine translation [37]. However, approaches to learning word embeddings typically require large corpora of running text to learn high quality representations. For many languages, such resources are unavailable. This is the case for Wolastoqey and Mi’kmaq, two endangered low-resource Eastern Algonquian languages. As there exist no large corpora for Wolastoqey and Mi’kmaq, in this thesis, we leverage bilingual dictionaries to learn Wolastoqey and Mi’kmaq word embeddings by encoding their corresponding English definitions into vector representations using English word and sequence representation models. Specifically, we consider representations based on pretrained word2vec [33], RoBERTa [31], and sentence-RoBERTa [40] models, as well as, fine-tuned sentence-RoBERTa models [40]. We evaluate these embeddings in word prediction tasks focused on part-of-speech, animacy, and transitivity; semantic clustering; and reverse dictionary search. We additionally construct word embeddings for higher-resource languages — English, German and Spanish — using our methods and evaluate our embeddings on existing word-similarity datasets. Our findings indicate that our word embedding methods can be used to produce meaningful vector representations for low-resource languages such as Wolastoqey and Mi’kmaq and for higher-resource languages.
Surrogate-based multi-objective optimization of modulated wave laser powder bed fusion using active learning: Balancing time and quality
(University of New Brunswick, 2025-02) McCarthy, Thomas; Aranas Jr., Clodualdo
Additive manufacturing, and more specifically laser powder bed fusion (LPBF), complements conventional manufacturing by producing a low volume of highly complex functional metallic components. The mode of laser emission, either continuous (c-LPBF) or modulated (m-LPBF), has a pronounced impact on the resulting component. Although both have merits, the c-LPBF process dominates commercial machines and academic efforts. To promote further exploration of m-LPBF, which has the potential to reduce defects and enhance microstructural control, the process must strike a balance between component quality and the industry’s demand for increased production. In this work, a multi-objective optimization framework was adopted to balance time and quality of m-LPBF produced Ti-6Al-4V as a function of key processing parameters. Lacking an analytical model, Bayesian inference of Gaussian process regression was utilized to relate laser power, exposure time, point distance, and hatch spacing to the as-built relative density, serving as a proxy for quality, while batch active learning efficiently sampled the design space. In combination, this model accurately captured the relationship in a modest number of experiments and, in conjunction with the application of non-dominated sorting genetic algorithm II, was able to determine a non-dominated set of solutions approximating the Pareto front. Despite the model's accuracy, the current work highlights the need for a sufficiently large data set to accurately reflect the underlying mechanisms occurring in the m-LPBF process.