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Greenspace density and Rohingya refugee depression symptoms in Cox’s Bazar, Bangladesh
Get PDFIn this project, I analyze the relationship between surrounding vegetation (greenspace) levels and depression symptoms for Rohingya refugees living in the Kutupalong refugee camp in Cox’s Bazar, Bangladesh. To do this, I use survey data from the Cox’s Bazar Panel Survey (CBPS), which includes socioeconomic, demographic, housing, health, trauma, and mental health data from a representative sample of over 2000 Rohingya refugee households, which includes the Patient Health Questionnaire-9 (PHQ-9) – a popular depression questionnaire. Additionally, I use survey location data to create spatial statistics unique to each respondent’s local characteristics, such as Normalized Difference Vegetation Index (NDVI) scores, surrounding settlement density, and distance to amenities. I categorize PHQ-9 by risk category and analyze my results using ordered logistic regression. For privacy reasons, I was not given direct access to the true survey points; instead, I wrote a script for the study team to run that generated the statistics associated with the true survey points. I have not yet received the true spatial statistics, so my current analysis uses statistics associated with random points within Kutupalong. However, my preliminary analysis of the CBPS data indicates similar relationships between determinants of depression and depression risk levels as seen in previous research.Jamie Cassels Undergraduate Research Awards (JCURA)UndergraduateReviewe
Mapping vegetation height and identifying the northern forest limit across Canada using ICESat-2, Landsat time series and topographic data
No full textThe northern forest-tundra ecotone is one of the fastest warming regions of the globe. Models of vegetation change generally predict a northward advance of boreal forests and corresponding retreat of the tundra. Previous satellite remote sensing analyses in this region have focused on mapping vegetation greenness and tree cover derived from optical multi-spectral sensors. Changes in vegetation structure relating to height and biomass are less frequently investigated due to limited availability of lidar data over space and time in comparison with optical platforms. As such, there is an opportunity to combine lidar and optical remote sensing products for continuous mapping of vegetation structure at high-latitudes, with an emphasis on the forest-tundra transition. In this study, we used lidar data from the Ice, Cloud and land Elevation Satellite (ICESat-2) to classify canopy presence/absence, and predict canopy height across 120 million hectares of the Canadian forest-tundra ecotone at 30 m spatial resolution. Spatially continuous predictors derived from the Landsat satellite archive (2012−2021) and the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Digital Elevation Model were used to extrapolate 98th percentile canopy height from the ICESat-2 Land and Vegetation Height (ATL08) product using Random Forests models developed in R (version 4.2.2). Model accuracy was assessed using data from the Land, Vegetation and Ice Sensor (LVIS), a large-footprint airborne lidar system. The overall accuracy of the canopy presence classification was 89%, and canopy presence was detected with 88% accuracy. Models of vegetation height showed an overall R2 of 0.54 and RMSE of 2.09 m. Finally, we used these methods to map the limit of continuous 3 m forest across Canada and compared our model outputs with forest cover from the MODIS and Landsat Vegetation Continuous Fields datasets. This work demonstrates the challenges and potential for mapping horizontal and vertical vegetation structure within sparse, high latitude forests using both lidar and optical remote sensing data.This research was funded in part through the Canadian Space Agency (Grant number: 21SUESECDL) and by NSERC support of Nicholas Coops (RGPIN-2018-03851). We also acknowledge funding support to Hana Travers-Smith from the NSERC Canada Graduate Scholarship-Doctoral and the University of British Columbia.FacultyReviewe
Ergodicity in software systems
Get PDFThis dissertation applies dynamical systems theory (DST) to formally investigate the statistical run-time performance predictability of arbitrary scale software-centric systems, ranging from small-scale embedded systems to modern large-scale cloud-deployed container and virtual machine based distributed systems. The research focuses on verifying Birkhoff’s Ergodic Theorem (BET) compliance for queuing network (QN) models of deployed software systems against BET-compliant Poisson and bursty incoming workloads. The approach applies a previously developed extension of Maurer’s Turing-reducible computer model, termed the Extended Maurer Model (EMM), as the requisite bridge between classical QN software system models and the DST-based BET tenets underlying classical Markovian QN analysis approaches. Moreover, it is shown that as the EMM describes a -finite measure space, a known ergodicity equivalency theorem can be used to develop a formal DST analysis approach to prove when BET left-hand and right-hand side conditions can be met for run-time software systems performance measures. More specifically, formally proving recurrence holds within large-scale systems, as required by classical Markovian analyses, has remained an open problem. By comparison, this research shows that this issue can be addressed by instead assessing when and why: i) wandering sets of non-zero measure arise and ii) event space variations and non-invariant DST measures arise, given (i) and (ii) are mathematically known to be equivalent to assessing recurrence within -finite measure spaces.
This theoretical DST analysis of QNs defined over the EMM representation of run-time software system behaviors then leads to the development of four pragmatically easily measurable and implementable software engineering design rules that can be used to assess when and why a given deployed software system will (or will not) exhibit statistically predictable run-time behaviors. These design rules are then applied to develop a sufficiently rich cloud-deployed software system simulation framework, which includes incoming statistical workloads, cloud networking fabric, physical server, virtual machine, and container deployment regimes, fair and real-time OS scheduling, and background physical server workloads. This simulation framework is then used to validate the DST theory BET-compliance analysis insights through a detailed set of software system run-time deployment scenarios, both for an industry-held exemplar system and for emerging industry deployment trends.
To our knowledge, this is the first set of research to formally assess run-time software system BET-compliance for systems of arbitrary scale and complexities. Moreover, it is the first work to show, through theory and simulation-based validation, that modern software systems exist as highly complex dynamical systems that can concurrently admit BET-compliant and BET non-compliant performance measures, while also admitting measures that can dynamically transition back and forth between BET-compliance and non-compliance as the system runs. As engineering can be summarily defined in terms of the need to build systems and solutions that behave predictably in their real-world operation under all likely deployment scenarios and environments, the developed novel insight into the core DST complexity of software systems helps to partially explain why the software engineering of modern industry-scale software systems has remained a challenging and largely open problem, outside of specific quite tailored regimes, i.e., the regimes that can be seen to follow this dissertation's developed software engineering design rules.
The issue of BET-compliance has wide applicability across many areas, spanning statistical run-time performance predictability, control theory, machine learning (ML) and artificial intelligence (AI), quantum computing, etc. The insights and theoretical framework developed in this research have wide potential applicability beyond just the core software engineering need to develop and deploy software systems that behave predictably, in the sense of remaining within a defined set of statistical behavioral bounds. More particularly, emerging areas of potentially applicable research include: the use of formal control theory approaches within cloud elastic services; the safety and operationally critical aspects of Smart Cities, Smart Grids, autonomous vehicles and vehicle networks; when, why, and how AI/ML approaches can be applied to accurately predict software system run-time behaviors; BET-compliance within cyber-security focused regimes and solutions; etc. As such, we hope this work will be seen as a useful and insightful contribution to advancing the formal engineering of software-centric systems and solutions.Graduat
Neighbourhood Food Democracy: Participatory Food Asset Mapping in Vancouver’s Westside
Get PDFFood insecurity represents a pervasive systemic issue that has a devastating population impact. Ordinary people, especially those most impacted by the failings of the food system, have little say in its governance. Food democracy aims to support regaining of the democratic control of the food system and enable its transformation by promoting active citizen participation in the decision-making processes. This research study presents a vignette to begin to consider potential pathways for supporting participation of equity-denied groups in addressing the issue that directly impacts them. Set in Vancouver’s Westside, this thesis explores the potential of participatory food asset mapping and a focus group discussion as tools for engagement of equity-denied groups in a democratic process. Based on the proposed conceptual framework of neighbourhood food democracy, these Community Based Participatory Action Research methods serve to support research objectives of community empowerment, knowledge co-creation and setting an agenda for social change. The research study engaged 15 community members with lived experience of food insecurity in the Westside in participatory mapping and focus group discussion. Participants identified neighbourhood food priorities, including values and barriers to local food access, as well as considered contributing systemic factors (knowledge co-creation). Participants suggested recommendations for the community, non-profit and public sectors to support community food security by maximizing value, reducing barriers to food access, and addressing systemic factors (agenda for social change). The research study validated the promise of CBPAR methods in supporting participation of equity-denied groups in a democratic process (community empowerment). To fully realize the promise of neighbourhood food democracy, the report recommends ongoing local opportunities for meaningful participation of marginalized groups in democratic processes on the issue that affects them.Graduat
On the multidisciplinary design of a hybrid rocket launcher with a composite overwrapped pressure vessel
Get PDFA multidisciplinary design optimisation (MDO) study of a hybrid rocket launcher is presented, with a focus on quantifying the impact of using composite overwrapped pressure vessels (COPVs) as the oxidiser tank. The rocket hybrid propulsion system (RHPS) consists of a combination of solid fuel (paraffin) and liquid oxidiser (NOx). The oxidiser is conventionally stored in metallic vessels. Alternative design concepts involving composite-based pressure vessels are explored that could lead to significant improvements in the overall performance of the rocket. This design choice may potentially affect parameters such as total weight, thrust curve, and maximum altitude achieved. With this eventual impact in mind, structural considerations such as wall thickness for the COPV are integrated into an in-house MDO framework to conceptually optimise a hybrid rocket launcher.This research was funded by Fundação para a Ciência e a Tecnologia (FCT), through IDMEC and INEGI, under LAETA, projects UIDB/50022/2020 and UIDP/50022/2020.FacultyReviewe
An application of multiple Erdélyi–Kober fractional integral operators to establish new inequalities involving a general class of functions
Get PDFThis research aims to develop generalized fractional integral inequalities by utilizing multiple Erdélyi–Kober (E–K) fractional integral operators. Using a set of j, with (j?N) positively continuous and decaying functions in the finite interval a?t?x, the Fox-H function is involved in establishing new and novel fractional integral inequalities. Since the Fox-H function is the most general special function, the obtained inequalities are therefore sufficiently widespread and significant in comparison to the current literature to yield novel and unique results.FacultyReviewe
In vitro glioblastoma model on a plate for localized drug release study from a 3D-printed drug-eluted hydrogel mesh
Get PDFGlioblastoma multiforme (GBM) is an aggressive type of brain tumor that has limited treatment options. Current standard therapies, including surgery followed by radiotherapy and chemotherapy, are not very effective due to the rapid progression and recurrence of the tumor. Therefore, there is an urgent need for more effective treatments, such as combination therapy and localized drug delivery systems that can reduce systemic side effects. Recently, a handheld printer was developed that can deliver drugs directly to the tumor site. In this study, the feasibility of using this technology for localized co-delivery of temozolomide (TMZ) and deferiprone (DFP) to treat glioblastoma is showcased. A flexible drug-loaded mesh (GlioMesh) loaded with poly (lactic-co-glycolic acid) (PLGA) microparticles is printed, which shows the sustained release of both drugs for up to a month. The effectiveness of the printed drug-eluting mesh in terms of tumor toxicity and invasion inhibition is evaluated using a 3D micro-physiological system on a plate and the formation of GBM tumoroids within the microenvironment. The proposed in vitro model can identify the effective combination doses of TMZ and DFP in a sustained drug delivery platform. Additionally, our approach shows promise in GB therapy by enabling localized delivery of multiple drugs, preventing off-target cytotoxic effects.This research was funded Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Foundation for Innovation (CFI) and BC Knowledge Development Found.FacultyReviewe
Edge computing for effective and efficient traffic characterization
Get PDFTraffic flow analysis is essential to develop smart urban mobility solutions. Many advanced traffic flow monitoring solutions have been proposed but they employ only a small number of parameters. To overcome this limitation, an edge computing solution is proposed based on nine traffic parameters, namely vehicle count, direction, speed, and type, flow, peak hour factor, density, time headway, and distance headway. This solution is low cost, low power, low data bandwidth, and easy to install, deploy, and maintain. It is a sensor node comprised of an RPi 4, Pi Camera, Intel Movidius NCS2, Xiaomi MI Power Bank, and Zong 4G Bolt+. Pre-trained models from the OpenVINO Toolkit are employed for vehicle detection and classification, and a Centroid Tracking Algorithm (CRA) is used to estimate vehicle speed. The measured traffic parameters are transmitted to the ThingSpeak cloud platform via 4G. The proposed solution was field-tested for one week (7 h/day), with approximately 10,000 vehicles per day. The count, classification, and speed accuracies obtained were 79.8%, 93.2%, and 82.9%, respectively. The sensor node can operate for approximately 8 h with a 10,000 mAh power bank and the required data bandwidth is 1.5 MB/h. The proposed edge computing solution overcomes the limitations of existing traffic monitoring systems and can work in complex and heterogeneous environments.Graduat
Generation and reactivity of transient aminoboranes and phosphinoboranes: Intermediates in the formation of inorganic polymers
Get PDFPolymers are ubiquitous. From the infamous plastic water bottle, typically made of polyethylene terephthalate, to chitin, a polysaccharide, polymeric materials are produced on massive scales in both industry and the biosphere. Most known polymers consist of long chains containing C–C, C–O, or C–N bonds. However, inclusion of elements other than carbon, oxygen, or nitrogen, can introduce valuable properties into the resulting bulk material. For example, the first boot to make contact with the moon had a sole comprised of silicone rubber, a material that can remain rubbery at even lunar temperatures. The ability of this material to remain pliable at such low temperatures is largely due to the inorganic Si–O bonds in its main-chain, which allow for greater conformational flexibility compared to polymers comprised primarily of C–C bonds.
The work described in this thesis focuses on a different class of inorganic polymers, polyaminoboranes and polyphosphinoboranes. These polymers feature main-chains of alternating nitrogen and boron or phosphorus and boron atoms.
• Chapter 1 provides a general introduction to inorganic polymers as well as a more detailed survey of polyaminoboranes and polyphosphinoboranes.
• Chapter 2 explores the synthesis of polyphosphinoboranes via the generation of transient phosphinoboranes (PhRP–BH2; R = H, Ph, Et) through the deprotonation of PhRPH•BH2(NTf2). These transient phosphinoboranes then undergo an addition polymerization.
• Chapter 3 describes the solution generation, observation, and subsequent reactivity of primary aminoboranes (RNH=BH2; R = tBu, Me, CPh3), a class of species that has only otherwise been isolated on solid argon matrices or observed as a complex mixture of products by 11B NMR spectroscopy. These aminoboranes were generated via the deprotonation of RNH2•BH2(NTf2) and observed at –78 °C as the sole 11B containing species, allowing for subsequent reactivity studies.
• Chapter 4 explores the role of catalysts in the catalytic dehydropolymerization of phosphine-borane adducts, where it is discovered that high molar mass, low dispersity polymers can be accessed using commercially available salts such as LiOTf or by adding catalytic amounts of BH3•SMe2. Further, a new potential mechanism for phosphine-borane dehydropolymerization is discussed.
• Chapter 5 ties together the themes of phosphinoboranes and aminoboranes, revealing that sterically unencumbered aminoboranes can accept hydrogen from phosphine-borane adducts, producing amine-borane adducts and phosphinoboranes. These transient phosphinoboranes then undergo subsequent reactivity to form dehydrocoupled products.
• Chapter 6 summarizes the findings of the research, discusses future research directions, and provides an overall outlook.Graduat
The New Carthaginians
Get PDF'This project explores how Augustan literature uses the Carthaginians as a symbol for the 'dangerous other' to allude to their contemporary enemies. This form of inadvertent political commentary functioned as a way for Augustus to justify his sole rule over the Roman people. Later, these literary paradigms surrounding the Carthaginians impacted cinema created in the modern era. Films such as Cabiria (Dir. Pastrone, 1914), Scipio Africanus; The Defeat of Hannibal (Dir. Gallone, 1937), and Hannibal (Dir. Ulmer, 1959) all demonstrate how Augustan literature's depictions of Carthage are used to create a commentary on the social anxieties of their time. Furthermore, later iterations of films depicting Carthage often respond to what was made previously, creating a scaffolded reception of the fallen North African nation, which began with the Augustan literature's Carthaginian LegendJamie Cassels Undergraduate Research Awards (JCURA)UndergraduateReviewe