Open Theses & Dissertations

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    Stand dynamics models of tropical eucalyptus hybrid clone plantations in Sumatera, Indonesia
    (University of New Brunswick, 2021-03) Waldy, Joni; Kershaw Jr., John A.
    Eucalyptus is one of the most widely cultivated species and provides raw materials for pulp and paper production in many tropical countries. Growth and yield is essential for forest management decision-making processes such as prediction of future forest yields and exploration of silvicultural options. However, limited publications related to growth and yield of this species exist in Indonesia compared to other regions. In this study, time-based and state-space modeling approaches were evaluated for estimating stand-level attributes of tropical hybrid Eucalyptus clonal plantation in Sumatera over normal rotation periods. Moment-based, percentile-based and hybrid methods for parameter recovery of Weibull distribution parameters for characterizing diameter distributions were also studied. The time-based approach was observed to provide simple and more accurate estimates of stand attributes across relatively short rotation ages. Moment-based parameter recovery methods also was found to give better performance. The combined system of models enables forest managers to evaluate total yield and its distribution across size classes.
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    A story of being and becoming an artist
    (University of New Brunswick, 2021-03) Rooney, Jean; Blatherwick, Mary
    The purpose of this autoethnographic story study is to adventure through the process of self-reflection and writing to explore and interrogate my narratives of lived experience as an artist. This study is both my story of being and becoming an artist educator and what is drawn out of the stories by connecting them to the broader cultural, political and social meanings and understandings. My reflections consider the context of being an immigrant Irish artist and educator on Indigenous Land in New Brunswick. Storytelling is key throughout this thesis and used as part of the methodology. While I will relate my stories as an artist educator, I will critically interrogate the discourses that have formed those experiences. Within this study I story my narratives of becoming and being an artist and explore through reflexivity how they impact my andragogical practice. This study is useful for artist educators in modelling and encouraging reflection upon their own creative practices, art educational discourses, artists’ relationality and community. Keywords: artist, artist educator, autoethnography, reflexivity, personal narrative.
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    Average speed enforcement and its potential application on New Brunswick roads
    (University of New Brunswick, 2021-03) Van Wiechen, Trevor Andrew; Hildebrand, Eric
    Average Speed Enforcement (ASE) is a is a relatively new approach that can be used to enforce speed limits. ASE determines a vehicle’s mean speed over an extended length of road by recording the time a motorist took to drive between two set points. Reducing the speed of motorists over a longer section of roadway yields benefits such as fewer collisions and a reduction in fuel consumption. This study investigated the findings of the effectiveness of average speed enforcement among those jurisdictions that have adopted it. It was found that ASE reduces collisions by 30-40% and that it lowers carbon emissions by roughly 15% on a 100 km/h road. These findings were then applied to a local road to determine if an economic case could be made for its use in New Brunswick. Route 7 between Oromocto and Saint John was chosen as a test site. A field study found that the average space mean speed on this facility was 107 km/h and the 85th percentile speed was 114 km/h despite the posted speed limit being only 100 km/h. The potential benefits of ASE were estimated and an economic evaluation found that its deployment would yield a benefit-cost ratio of approximately 15.6.
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    Design of efficient and privacy-preserving similarity query over encrypted data in Cloud
    (University of New Brunswick, 2022-02) Zheng, Yandong; Lu, Rongxing
    Similarity query, retrieving objects similar to a sample of interest, has enabled plentiful customized services in a variety of applications, such as disease diagnosis, locationbased services, recommendation system, signal processing, etc.; and attracted considerable attention from industry and academia. Meanwhile, big data era has stimulated the continuing explosive growth of data volumes in these applications and has been leading data owners to outsource data and the corresponding similarity query services to a powerful cloud for releasing the burden of local data storage and computation. Due to privacy concerns, data are usually outsourced in an encrypted form, and as a result, similarity queries have to be performed over encrypted data, which is more challenging to implement than similarity queries over plaintext data. Targeting at similarity queries over encrypted data, many solutions have been proposed by designing some customized protocols based on selected encryption techniques, e.g., homomorphic encryption. Based on the type of data, three categories of extensively studied privacy-preserving similarity queries include similarity query for eHealthcare data, similarity query for set data, and similarity query for time series, which are also the focus of our dissertation. Although these three categories have been widely studied, existing solutions still have some limitations in query efficiency, security, and practicality. To address these issues, in the dissertation, we design several efficient and privacy-preserving similarity query schemes for encrypted eHealthcare data with the distance measure of Euclidean distance; for encrypted set data with the distance measure of Jaccard similarity; and for encrypted time series with the distance measure of time warp edit distance (TWED), in the cloud outsourced environment. Specifically, our main contributions of the dissertation can be summarized as i) Design an efficient and privacy-preserving kNN query scheme for outsourced eHealthcare data by employing the k-d tree data structure as index and designing two privacy-preserving protocols for the encrypted data comparison and Euclidean distance computation in the cloud based on a homomorphic encryption technique. The proposed scheme can not only support efficient and privacy-preserving kNN queries over encrypted eHealthcare data but also dynamically update encrypted eHealthcare data in the cloud. ii) Propose a new efficient, privacy-preserving, and practical Euclidean distance based similarity range query scheme over encrypted eHealthcare data in the cloud by integrating the modified asymmetric scalar-product-preserving encryption (ASPE) scheme and Quadsector tree structure, where the modified ASPE scheme enables the cloud server to determine whether a data point satisfies the current similarity range query request through the encrypted data under a single-server setting; and the Quadsector tree used to index the dataset reduces the average computational complexity of query processing sublinear to the size of the dataset. iii) Formalize and design a similarity query based healthcare monitoring scheme over the digital twin cloud platform. In this scheme, we deploy a partition-based tree (PB-tree) to represent the healthcare center’s data and introducing the modified ASPE scheme to design a privacy-preserving PB-tree based similarity range query (PSRQ) algorithm. iv) Propose an efficient and privacy-preserving set similarity query scheme under a single-server setting, which achieves high efficiency in the set similarity query while preserving the data privacy. In the proposed scheme, we design a symmetric-key predicate encryption scheme to achieve privacy-preserving similarity queries over binary vectors and employ B+ tree as the index structure to improve the query efficiency. v) Propose an efficient and privacy-preserving similarity range query scheme for time series data by organizing time series data into a k-d tree and applying the modified ASPE scheme and a symmetric homomorphic encryption to preserve the privacy of k-d tree based similarity queries. vi) Analyze the security of all proposed similarity query schemes in the dissertation and conduct extensive experiments to validate their efficiency. The results demonstrate that all proposed schemes are privacy-preserving, protecting the privacy of datasets and query requests against the honest-but-curious cloud server; and are computationally efficient.
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    Binary logistic models with partially crossed random effects
    (University of New Brunswick, 2021-11) Zhang, Zizhe; Yan, Guohua; Ma, Renjun
    Educational studies and behavioural scientists frequently encounter data with binary outcomes that have cross-classified data structures. For example, in a student admission study (success or failure), schools and areas could be treated as crossed random effects since not all students from the same school live in the same area and vice versa. It is crucial to incorporate crossed random effects into the model for data with cross-classified structures; otherwise, data analysis results might be misleading. This thesis proposes a binary logistic model with partially crossed random effects, which is further extended to a baseline-category logit model with partially crossed random effects for multinomial analysis. The random effects in our proposed models are predicted by the orthodox best linear unbiased predictor (BLUP) approach. Our models are robust because they only need to specify the first and second moments of the random effects. The simulation study shows that the estimation algorithm generally performs well. In addition, we apply these models to insurance data about motor vehicle accidents and interpret the estimates for practical references.
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    High-resolution laser and far-infrared Fourier transform synchrotron-based spectroscopy of selected molecules
    (University of New Brunswick, 2022-02) Zarringhalam, Hanif; Tokaryk, D. W.; Adam, A. G.
    In the first part of this thesis, three ruthenium-bearing diatomic molecules have been studied in the visible region of the electromagnetic spectrum. Ruthenium monofluoride, ruthenium monochloride and ruthenium monoxide molecules were created in a molecular beam apparatus. The high-and low-resolution spectra of these small molecules were taken with the laser-induced fluorescence technique. The dispersed fluorescence technique was used to determine the vibrational frequencies of the RuF, RuCl and RuO molecules. The results of the high-resolution analysis of the spectra revealed extensive isotopic structures of the three molecules. Spin-orbit and hyperfine interactions in the ruthenium monofluoride molecule were observed and analyzed. Hyperfine structure in the ruthenium monoxide molecule was also detected and studied. In the second part of the thesis, three medium-sized ring molecules, catechol, furan and pyrrole, belonging to the C2v point group, have been studied in the infrared region. Vibrational bands of pyrrole and furan were collected between 800-900 cm-1 at the Canadian Light Source with an FTIR technique. Observed vibrational bands of pyrrole and furan in that region were studied. A nearby level that had A2 symmetry which could not be accessed from the ground states had perturbed the fully overlapped bands of these molecules. Also, progress has been made in obtaining the first high-resolution rotationally resolved vibrational band of catechol at the Canadian Light Source.
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    A query-efficient black-box adversarial attack on text classification Deep Neural Networks
    (University of New Brunswick, 2022) Yadollahi, Mohammad Mehdi; Ghorbani, Ali A.; Lashkari, Arash Habibi
    Recent work has demonstrated that modern text classifiers trained on Deep Neural Networks are vulnerable to adversarial attacks. There are insufficient studies on text data compared to the image domain, and the lack of investigation originates from the special challenges of the NLP domain. Despite being extremely effective, most adversarial attacks in the text domain ignore the overhead they induced on the victim model. In this research, we propose a Query-Efficient black-box adversarial attack named EQFooler on text data that tries to attack a textual deep neural network while considering the amount of overhead that it may produce. The evaluation of our method shows that the results are promising. We demonstrate the impact of keyword extraction methods in generating query-efficient adversarial attacks. Four variants of the EQFooler mode are developed based on different keyword extractors and importance score strategies. We compare the performance of these variants in terms of four evaluation metrics, namely original accuracy, adversarial accuracy, change rate, and number of queries. All the variants of the proposed attack significantly reduce the accuracy of the targeted models. Among those variants, EQFooler-Rake-MS has the best functionality in terms of adversarial accuracy, change rate and the number of queries needed. Also, multiple experiments are designed to compare the outcomes of the proposed method with the state-of-the-art adversarial attacks as a baseline. The results show that the EQFooler is as powerful as the state-of-the-art adversarial attacks while requiring fewer queries to the victim model. In addition, we study the transferability of the generated adversarial examples. Compared to the baseline in any transfer setting, at least one of the variants has better outcomes than the baseline.
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    Desires and disclosures: Understanding the desire to post on social media
    (University of New Brunswick, 2021-10) Vogels, Emily A.; O’Sullivan, Lucia F.
    While the uptake and integration of social media into our daily lives has been well-documented, little is known about the desire to post on social media even though that it presumably a critical first step preceding use, as indicated by the model of goaldirected behavior. This dissertation sought to develop and validate a measure of the desire to post on social media among Canadian and American social media users. Exploratory and confirmatory factor analyses revealed four key dimensions of the desire to post on social media: desire to post due to negative events in one’s life, desire to post due to positive events, frequent desire to post, and desire to publicly post in ways that depict oneself in a favorable light. No gender or age differences were observed. During the COVID-19 outbreak, people have relied more heavily on social media than ever before to maintain social connections while remaining physically distant. Consequently, people may desire to use these sites more than they did before the pandemic based on uses and gratification theory and the instrumentality principle. Changes in desiring to post on social media before (Fall 2019) and during the pandemic (June 2020) were assessed using a large cross-sectional sample of Canadian and American social media users. Overall scores on the desire to post tool did not differ between these two time periods; however, the desire to post when experiencing positive events and the frequency with which people desired to post decreased during COVID-19. Correlation comparisons revealed the correlation between the desire to post when experiencing negative events and the desire to publicly and positively self-present had become stronger during COVID-19, as did the correlation between this negative events scale and the frequency with which people desired to post. These findings highlight how desiring to post on social media changes in response to extraneous circumstances (e.g., not being able to socialize in person). These findings have implications for researchers studying online posting behaviors, including self-disclosure of private information and uptake of new technologies, as well as for clinicians working with clients experiencing distress, social isolation, or problematic social media use.
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    Crop field monitoring and damage assessment with unmanned aircraft systems and machine learning
    (University of New Brunswick, 2021-11) Vlachopoulos, Odysseas; Leblon, Brigitte; Wang, Jinfei
    The purpose of this dissertation is to examine and develop novel Machine Learning (ML) pipelines for crop field monitoring and damage assessment using Unmanned Aircraft Systems (UAS) equipped with a multispectral MicaSense RedEdge optical sensor for precision agriculture and insurance purposes. The crop fields were prepared for or planted with barley, corn, potato, oat, and soybean crops. The multispectral imagery from the UAS was radiometrically corrected and mosaicked. The multispectral reflectance orthomosaics from each surveyed field were used as input features in various algorithms along with associated vegetation index rasters. Firstly, field areas and boundaries were delineated over multiple bare soil fields with the two following ML pipelines: A supervised pixel-based Random Forests (RF) classifier and an unsupervised clustering process using the Mean Shift algorithm. The vectorization process of the resulting maps resulted in mean Area Goodness of Fit (AGoF) greater than 99% and mean Boundary Mean Positional Error (BMPE) lower than 0.6 m, indicating that both ML pipelines are excellent. Secondly, fully planted fields with barley, corn, and oat were surveyed in order to delineate crop areas and boundaries using Pixel-Based Image Analysis (PBIA) and Geographic Object-Based Image Analysis (GEOBIA) with the RF classifier. Both methodologies were highly successful, with a mean AGoF greater than 98% and a mean BMPE lower than 0.8 m. Thirdly, lodging damage on barley crop fields was mapped from two UAS surveys. An RF model was utilized in order to classify lodged and standing barley with an overall validation accuracy of 99.7%. The average AGoF was 97.95%, and the average BMPE was 0.235 m. Finally, the crop health status was assessed through the Green Area Index (GAI) for barley and oat fields. Multiple Linear Models, Support Vector Machines, RF, and Artificial Neural Networks regression algorithms were used in order to produce Green Area Index (GAI) maps of the fields, with RF performing best for GAI prediction. The GAI maps and the regression feature space were used with an RF classifier to generate health status maps of the crop fields with a mean overall accuracy of 94%.
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    Automation of the Timed Up and Go test using an instrumented walking cane
    (University of New Brunswick, 2021-10) Valsangkar, Ameya; Scheme, Erik
    The Timed Up and Go (TUG) test is used to test a person’s mobility and static and dynamic balance. It measures the time a person takes to stand up from a chair, walk three meters, turn around, walk back to the chair, and sit down. Typically, the TUG test is assessed by a physiotherapist with a stopwatch, limiting its effectiveness and making it prone to user error. This has motivated research into automated approaches capable of assessing the various segments of the TUG test using a range of sensing modalities. This study extends upon this body of work by evaluating the feasibility of segmenting the TUG test using an instrumented walking cane. More general contributions are made by introducing the use of error in transition time, as opposed to accuracy, as the cost function during the design of the machine learning framework, and a time-series inspired binary segmentation approach that facilitates the comparison of only two segments at a time. Data was collected using an instrumented cane that measures loading and movement information from 16 participants with musculoskeletal injuries. As a group, the participants yielded TUG times ranging from 11.12s to 28.57s, and a mean of 17.8s. Results of segmenting the TUG test into six segments - Sitting to standing, Walking, Turning, Walking back, Turning back, Standing to sitting - were validated using a leave-one-trial-out and a leave-one-person-out approach, to test both within- and across-participant performance. Various approaches were explored, including conventional classifiers Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM), and extended time series and deep learning methods such as Hidden Markov Models (HMM), CNN LSTM (CLSTM) and Encoder-Decoder Temporal Convolutional Networks (EDTCN). A binary segmentation approach leveraging the temporal nature of the TUG test was adopted with a Dynamic Time Warping (DTW)-based postprocessing alignment. The calculated segmentation error for every case was recorded as both the performance measurement and the optimization parameter as opposed to the traditional use of accuracy of prediction. The results promisingly suggest that the segments or subtasks of a TUG test can be extracted using data collected from a smart cane, laying the groundwork for its automation.
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    Stoicism as a coping mechanism for stigmatizing experiences among low-income, higher-weight individuals
    (University of New Brunswick, 2021-10) Turner, Alison; Bombak, Andrea
    Weight and income stigma in healthcare experiences disproportionately affect higher-weight, low-income individuals. This thesis focuses on if and how stoicism is used to manage stigmatizing experiences among 11 higher-weight, low-income adults in New Brunswick. Participants took part in two semi-structured interviews that focused on healthcare experiences and both positive and negative places/spaces in New Brunswick. While stoicism is often seen as an ideology that is deployed by individuals to avoid negative emotions, the results from this thesis were that stoicism is more nuanced and complex. The participants each deployed some combination of stoic behaviours in response to stigmatizing experiences and places; however, no participants showed evidence of a stoic ideology as a coping mechanism. I argue that a stoic ideology is not developed ubiquitously among the participants, instead they showed evidence of stoic behaviours that can be understood through the uptake of fatphobic and neoliberal health messaging. These findings have major implications to understanding how stoicism can be deployed as separate and overlapping behaviours that still impact healthcare experiences.
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    Hydrogen bond rich supramolecular systems towards theranostics
    (University of New Brunswick, 2021-10) True, Allison; Blight, Barry A.
    Iridium complexes have many applications: bioimaging, functional materials (e.g. photovoltaic cells), synthetic catalysts, and, due to their high photoluminescence, organic light emitting diodes (OLEDs). Hydrogen-bonding (H-bonding) is integral to the design of sophisticated functional organic materials because different assembly patterns of Hbond acceptor and donor atoms lead to varying association strengths. Cyclometalated iridium (III) complexes that contain self-assembling H-bonding motifs provide a colourtuning solution to inner-sphere synthetic modifications. In the current work, a DNA-like H-bonding array is used to influence the emissive properties of eight cyclometalated iridium (III) complexes via host-guest chemistry. DNA/RNA nucleobases have naturally occurring H-bonds that mimic an organic guest molecule (pyrimido[4,5-c]isoquinolin-3- amine), making them suitable binding partners for the iridium (III) host complexes. The association strengths of these nucleobase interactions will help to predict how the colourful iridium complexes will perform as potential theranostic (i.e. therapeutic and diagnostic) tools.
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    The ability of road infrastructure in New Brunswick to support Lane Keep Assist technology
    (University of New Brunswick, 2021-11) Stewart, Michael; Hildebrand, Eric
    This study expands our understanding of how well lane keep assist (LKA) technologies perform under varying conditions of pavement markings and lane edge treatments. Freeways, Arterials and Collectors that typically benefit from higher maintenance standards for pavement markings were able to support the LKA system throughout 95% to 100% of their length. These findings do not include weather events where snow/ice accumulation resulted in partial to complete covering of both the centre line marking, and edge of roadway. The compliance percentages include wet & dry surface conditions, varied rain/snow intensities and visibility hinderances caused by fog. These road segments possessed contrast ratios of 2.23 or greater along with retroreflectivity values of 60.7 mcd/lx/m2 or greater. The impact of traversing shadows or the provision of streetlight illumination had little to no effect on the machine vision system (MVS) and consequently the LKA performance. Road segments with edge characteristics other than a painted edge line (i.e., crushed rock, gravel, grass) had mean LKA engagement ranging from only 5.7% to 61.0% and were greatly impacted by lighting conditions, environmental conditions, and deteriorated edge (raveling) of asphalt commonly found on Local highways. These road segments typically possessed contrast ratios and retroreflectivity values less than the recommended guidelines of 1.6, and 34 mcd/lx/m2 for daytime and nighttime dry operations. Road segments in New Brunswick should possess contrast ratios greater than 1.9, and retroreflectivity values of 65 mcd/ls/m2 or greater to ensure LKA engagement of 90% or higher.
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    Characteristics of minor attracted persons in the community: Developing a biopsychosocial-sexual typology of men with sexual interests in children
    (University of New Brunswick, 2022-02) Stewart, Hannah Shirley; Campbell, Mary Ann
    Research investigating causes and factors that affect sexual recidivism among heterogenous forensic populations of child sexual offenders has shown that not all child sexual offenders express pedophilic interests, and not all individuals with pedophilia sexually offend against children. Extending findings from existing studies to community populations of minor attracted persons (MAPs) who have not been involved in the criminal justice system may clarify what distinctions are related to potential risk of child sexual abuse. This dissertation employed online recruitment strategies to identify latent clusters of self-reported developmental, biopsychosocial, sexual, and behavioural characteristics of self-identified MAPs in the community. The final sample consisted of men with self-endorsed sexual interests in minors (n = 609; Mage = 29.7 years) and a comparison group of men with other paraphilic interests (n = 224; Mage = 35.3 years). Data were used to develop a psychometric typology of community members with pedohebephilic interests with no detected justice-involvement. The Vulnerability Typology emerged from latent cluster analysis, with three groups differentiated by relative of endorsement of biopsychosocial-sexual factors, labeled as low vulnerability (n = 165), moderate vulnerability (n = 270), and high vulnerability (n = 149). Multiple analysis of variance was utilized to investigate discriminating factors across groups, identifying prominent biopsychosocial-sexual characteristics within and across clusters. Overall, low vulnerability MAP profiles appeared largely healthy and unimpaired, moderate vulnerability MAPs displayed modest characteristic deficits, and MAPs in the high vulnerability group showed significant impairment across most measured vulnerability constructs. High vulnerability MAPs perceived themselves to pose highest risk for acting on pedohebephilic arousal, whereas lowest self-reported risk was observed among low vulnerability MAPs. Use of maladaptive or adaptive coping strategies did not moderate the relationship between MAP clusters and self-perceived risk of acting on sexual interest in minors. Results of this study provide guidance to inform secondary prevention and risk assessment approaches among community MAPs with no historical justice system contact related to their sexual interests in minors. Specifically, criminogenic needs and destabilizing factors in domains of antisocial cognitions, deviant sexual interests, and psychosocial functioning may be relevant targets for prevention and wellness approaches among minor attracted persons.
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    The impact of executive function: Extending the theory of planned behaviour to understand concussion reporting among university athletes
    (University of New Brunswick, 2022-04) Sorochan, Jennifer B.; LaChapelle, Diane
    Research addressing athlete concussion symptom reporting has primarily emphasized symptom recognition and knowledge of return to play (RTP) protocol as outcome variables. However, there is evidence knowledgeable athletes conceal symptoms to continue playing, especially in important games (Kroshus et al., 2020). A health behaviour model, the Theory of Planned Behaviour (TPB), has recently been used to explain concussion reporting based on associated beliefs and attitudes. Only one study (Register-Mihalik, Linnan, et al., 2013), however, has followed the original methodology designed to elicit a comprehensive account of concussion reporting using the TPB and found the TPB accounted for 58% of the variability in reporting behaviour. In the present study, the addition of executive function (EF; the ability to plan, organize, and execute goal-directed behaviour; Lezak et al., 2012) to the model was examined to determine the extent to which EF improved the model’s predictive validity for intentions to report concussion symptoms. Methodological limitations of previous research were addressed by developing and validating a TPB questionnaire (Theory of Planned Behaviour Concussion Reporting Questionnaire [TPB-CRQ]) with university-level athletes (N = 55) prior to testing the extended model. Subsequently, university-level athletes (N = 264) completed an online questionnaire package including measures of concussion reporting (the TPB-CRQ), executive functioning, athletic identity, and symptoms of Attention-Deficit/Hyperactivity Disorder. Hierarchical multiple regression was used to evaluate the extended TPB model and found TPB variables accounted for 35.1% variance in intention to report. While EF did not improve the model, the findings highlighted the importance of context, inaccurate perceived social norms, and a lack of perceived control over reporting as key determinants of intention to report. Based on the findings, suggested modifications to current educational and intervention approaches include integrating the role of context, emphasizing positive consequences for reporting, building reporting self-efficacy, incorporating facilitated team conversations into preseason education, and re-establishing commitment to safety procedures throughout the season to increase attitudes and belief transparency among athletes, coaches, and staff.
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    Patterns and processes of recently settled and juvenile American lobster (Homarus americanus) in the lower Bay of Fundy
    (University of New Brunswick, 2022-03) Sigurdsson, Gudjon Mar; Rochette, Rémy
    In this thesis I quantified, over 4 years, spatial patterns of early life phases of American lobsters (Homarus americanus) at multiple spatial scales in the lower Bay of Fundy, ranging from 0.55 m2 cobble-filled collectors to large regions 127-674 km2 , and I conducted a field experiment and a modeling exercise to investigate which environmental (biological and physical) factors are responsible for the dominant patterns I observed. Benthic recruits and the following two juvenile phases (emergent and vagile lobsters) showed similar spatial patterns at the scales investigated (most patchiness at the “area” scale), but these differed markedly from the pattern (no patchiness at any of the scales investigated) displayed by the fourth life-history phase (adolescents). The number of stage IV larvae (i.e., postlarvae) caught in the plankton by light traps was significantly related to spatial variability in benthic recruitment at the area scale, but the number of stage I larvae was not. The modelling exercise identified four variables that were related to benthic recruitment patterns: North Atlantic Oscillation Index (NAO) over the larval period, fetch of the study area, juvenile abundance, and sea surface temperature over the larval period. Whereas some of these associations appear to be spurious, others suggest, as did the light trap study, that factors affecting postlarval supply are determinants of the spatial patterns observed. Also, the NAO index showed promise in predicting inter-annual variation in benthic recruitment patterns. This work highlights the importance of sparsely distributed nursery grounds to benthic recruitment of this species. As rapid climate change is affecting the distribution of the species and conditions for larval development, continuing monitoring of recruitment is of high and increasing importance. Such monitoring will also allow testing of the predictive ability of the model developed in chapter three, which is an important next step for this work.
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    Genetic engineering of the biosynthesis of the anticancer monoterpenoid indole alkaloid vinblastine precursors in microorganism
    (University of New Brunswick, 2021-12) Shahsavarani, Mohammadamin; Qu, Yang
    Monoterpenoid indole alkaloids (MIAs) are among the most complex specialized metabolites with a broad range of pharmacological activities. These natural products have been used as anticancer (vinblastine and vincristine) and antiarrhythmic (ajmaline) agents since the 1970s. Despite the low yield, the plant Catharanthus roseus (Madagascar periwinkle) remains the sole commercial source for MIA vinblastine and vincristine production because of the complex structure and stereochemistry makes the total synthesis difficult and costly. The complete elucidation of the 28-genes vinblastine biosynthetic pathway in 2018 allows the assembly of this remarkable pathway in microorganisms for the industrial production of vinblastine, which also unlocks the door to producing a broad range of medicinal MIAs using the core pathway. In this thesis, the biosynthesis of early vinblastine intermediate geissoschizine from tryptamine and secologanin precursors was engineered in E. coli by inhibiting the leaky expression of genes during the biomass accumulating stage. The expression issue of the O-acetylstemmadenine oxidase in yeast was solved by replacing its signal peptide with that of the yeast carboxypeptidase Y, which allowed the biosynthesis of two late vinblastine intermediate catharanthine and tabersonine in yeast from geissoschizine intermediate. This research is the first example of microbial production of these MIAs, which lays the foundation for the complete biosynthesis of vinblastine in microbes.
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    Compact, low-cost pulse generator and embedded computing platform for distributed sensing
    (University of New Brunswick, 2021-12) Selby, Quinn; Colpitts, Bruce
    This thesis presents a number of improvements to the Brillouin optical time-domain analysis temperature and strain sensing system. A compact, low-cost ultrawideband pulse generator with variable pulse width was designed, simulated, built and tested in a series of BOTDA measurements, demonstrating sufficient specifications to drive any electro-optic modulator typically used in this application. Additionally, hardware and software was developed for a compact embedded computing platform capable of acquiring and processing BOTDA measurements. The complete design was then evaluated according to a number of performance metrics, including spatial resolution, frequency resolution, measurement time, and more.
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    How municipal asset management practices contribute to achieving the United Nations sustainable development goals
    (University of New Brunswick, 2022-01) Searle, Brandon M.E.; Rankin, Jeff; Sanchez, Xiomara
    Municipal asset management and infrastructure sustainability are closely aligned. The importance of sustainably managing infrastructure to deliver services has been shown through the creation of the United Nations Sustainable Development Goals in 2015. Two barriers to delivering sustainable services through municipal infrastructure include, i) inconsistencies in services delivered by local governments across the country, wherein services may be delivered at the municipal, provincial, or federal levels, with no common practice across a single region, and ii) absent measures to quantify levels of service, resulting in infrastructure owners over- or under-delivering services, in turn impacting the costs and risks associated with delivering services to the community. This research focused on a review of current legislation and services delivered at the local government level and performed an analysis to demonstrate alignment between the United Nations Sustainable Development Goals and the level of service performance measures used in municipal asset management. The relationship between the two were demonstrated through a case study, where three of the United Nations Sustainable Development Goals were mapped to the level of service objectives being used by a large sized Canadian population centre. The findings of the case study showed that using the 191 United Nations Indicators to measure the Sustainable Development Goals could become a standard method to measure the 509 level of service performance measures at the municipal level. This, in turn, would allow jurisdictions to compare service levels to peers, creating an opportunity for knowledge transfer and improvements by benchmarking their asset management program to other local governments.
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    Developing seabird bioindicators for the Gulf of Maine: a demographic study of an Arctic Tern (Sterna paradisaea) metapopulation
    (University of New Brunswick, 2022-04) Scopel, Lauren C.; Diamond, Antony W.; Forbes, Graham J.
    As climate change proceeds, ecosystems are changing rapidly. Marine ecosystems are complex and difficult to monitor, making the prediction of future changes a daunting task. Seabirds are often suggested as potential bioindicators, yet the development of their data for general predictive use is rare. I, using the data of many collaborators, examined the potential use of Arctic Tern (Sterna paradisaea) diet and demographic data as bioindicators in the rapidly warming Gulf of Maine (GOM) ecosystem. The collapse of the breeding colony at Machias Seal Island, formerly the largest in North America, was primarily driven by unmitigated egg predation by large Larus gulls, not a decline in Atlantic herring (Clupea harengus). At the metapopulation scale, reproductive success of Arctic Terns was subject to multiple environmental interactions. The proximity of a colony to shore was associated with higher diet quality, but also greater predator pressures. Interactions between diet quality, weather, and predator behaviour strongly influenced the reproductive success of terns. At the ecosystem scale, the diets of Arctic and Common Terns (S. hirundo) could be combined with environmental data to describe and track ecosystem states. Arctic Terns were more likely to consume white hake (Urophycis tenuis) and small marine invertebrates, but their dietary trends also tracked measures of the herring stock and fishery. Common Terns were more likely to target high-lipid fish, but they showed stronger spatial trends that limited regional inferences. Finally, I estimated rates of survival, dispersal, and return rates. Arctic Terns have strong dispersal behaviour and regularly leave the major colonies of the GOM, but adult survival has not changed, despite major warming. Multiple types of tern data indicated that the weakest period of the past 30 years was between 2004-2012, when salinity was reduced and small copepods like Centropages typicus were less abundant. Arctic Terns were able to react to major declines in habitat quality, and have adjusted well to recent warming. Although Arctic Terns are affected by both top-down and bottom-up forcing, their diet and demographic data are useful as indicators. Terns could function well as ecosystem, guild-, or site-specific indicators, depending on the desired use.