21090 research outputs found
Sort by
Multi-dimensional Analysis of Molecular Clusters in the Gas-phase
No full textIn this thesis, interactions and properties of novel gas-phase clusters are studied. These gas-phase clusters often possess unique geometries and unexpected properties, which are influenced by the forces and interactions between the moieties within the cluster. Spectroscopic methods and ion mobility methods are coupled with tandem mass spectrometry to elucidate the cluster properties and geometry. IRMPD provides insight toward the nature of the cluster by their IR fingerprints, which can be used in parallel with tandem mass spectrometry method such as CID to provide further information. In addition, ion mobility methods are used to differentiate conformational differences between isomeric clusters.
In chapter 3, IRMPD and CID of deprotonated fluorinated propionic acids are studied. In analytical studies of short chain per- and polyfluoroalkyl substances (PFAS), the quantification and the identification of these carboxylic acids are done by monitoring the carbanion signal after the loss of CO2. The degree of fluorination influences fragmentation under IRMPD and CID, leading to fragmentation pathways such as formation of FCO2– and HF elimination. Fluorinated propionic acids with at least one fluorine atom bound to the terminal carbon yield FCO2–, whereas loss of HF is observed in polyfluorinated species with at least one fluorine bound to the α-carbon. The formation of FCO2– and HF elimination products occur through a four-membered ring transition state.
Chapter 4 describes the study of aromatic organometallic compounds such as cyclopentadienyl that are known to form sandwich complexes with counter cations, because the dominant interactions between the cation and the anion are Coulombic interactions and ion-induced dipole interactions. This work focuses on studying the influence on the geometry of the cluster by reducing the symmetry of the aromatic compound through clustering 1,2,3–triazolide and 1,2,4–triazolide with various alkali metal cations (with an excess of one cation to preserve cationic states). Through a combination of IRMPD and DFT calculations, the primary interaction between the alkali metal cations and the triazolide is found to be dominantly ion-dipole interactions and lone-pair donation interactions. This results in the geometry of the 1,2,3–triazolide clusters to be a 3D compact structure, whereas the 1,2,4–triazolide analogues are found to be more open with longer distances between the cations. Potential overtone bands or combination bands associated with the C-H wagging motion and ring torsion motion are found between the 1500 – 1800 cm–1 region.
Chapter 5 is a study on the clusters of perfluorinated dodecaborate cages, B12F122–, with protonated diaminoalkanes H2N(CH2)nH2N (n = 2 – 12) through a combination of IMRPD action spectroscopy and ion mobility spectrometry. I focus on characterizing the different singly-charged clusters of the form [B12F12 + H2N(CH2)nNH2 + H]– and doubly-charged clusters of the form [2(B12F12) + H2N(CH2)nH2N + 2H]2– (n = 2 – 12). Three unique geometries are found for the singly-charged clusters, a low energy proton-bound ring geometry where intramolecular hydrogen bonding occurs between the two amine functional groups, a bidentate geometry (where both amine groups bind to the B12F122– moiety), and a monodentate geometry. For the doubly-charged clusters, the doubly protonated diaminoalkane act as a tether between the B12F122– cages. The major fragmentation channels of the singly-charged and doubly-charged clusters are found to be: (i) proton-transfer leading to production of HB12F12– and (ii) the loss of B12F122–. Formation of HB12F12– likely leads to further gas-phase reactions that can yield compounds such as [B12F11 + N2]–. Travelling wave ion mobility spectrometry (TWIMS) analysis of HB12F12– finds CCSTWIMS = 142 ± 6.7 Å2. IRMPD spectroscopy, aided by computational modelling, indicates that the bidentate conformation is the major sub-population in the gas-phase ensemble
Model Predictive Control for Systems with Partially Unknown Dynamics Under Signal Temporal Logic Specifications
No full textAutonomous systems are seeing increased deployment in real-world applications such as self-driving vehicles, package delivery drones, and warehouse robots. In these applications, such systems are often required to perform complex tasks that involve multiple, possibly inter-dependent steps that must be completed in a specific order or at specific times. One way of mathematically representing such tasks is using temporal logics. Specifically, Signal Temporal Logic (STL), which evaluates real-valued, continuous-time signals, has been used to formally specify behavioral requirements for autonomous systems.
This thesis proposes a design for a Model Predictive Controller (MPC) for systems to satisfy STL specifications when the system dynamics are partially unknown, and only a nominal model and past runtime data are available. The proposed approach uses Gaussian Process (GP) regression to learn a stochastic, data-driven model of the unknown dynamics, and manages uncertainty in the STL specification resulting from the stochastic model using Probabilistic Signal Temporal Logic (PrSTL). The learned model and PrSTL specification are then used to formulate a chance-constrained MPC. For systems with high control rates, a modification is discussed for improving the solution speed of the control optimization. In simulation case studies, the proposed controller increases the frequency of satisfying the STL specification compared to controllers that use only the nominal dynamics model. An initial design is also proposed that extends the controller to distributed multi-agent systems, which must make individual decisions to complete a cooperative task
Testing the application of novel technology for monitoring grape vine health and berry maturity using transmitted visible and near infrared light
No full textClimate change is impacting wine-growing regions globally, with varying effects on vineyards. While some regions may benefit from warmer temperatures, others may face detrimental consequences, especially with the predicted increase in extreme weather events or less than optimal conditions. Precision viticulture uses remote and proximal sensing technologies to monitor these changes and adapt vineyards by providing insights into vine health and grape maturity. This information can be used to determine when intervention is needed in vineyards to maintain grape quality. However, existing precision viticulture methods are limited, such as the inability to provide continuous, real-time data and the utilization of reflected light, which can lead to inaccurate measurements. Current research has not yet investigated the potential of using transmitted light for monitoring vine health and grape maturity, a method that could provide more accurate insights. This thesis seeks to fill this gap by evaluating the feasibility of applying a novel system, TreeTalker-Wine© (TTW), to continuously monitor grapevine health and maturity through transmitted light in commercial vineyards.
To test the application of TTWs for monitoring vine health, the sensors were deployed under the canopy of Cabernet Franc in two commercial vineyards in Niagara, Ontario, Canada. Spectral data collected by the TTWs was used to calculate the daily Normalized Difference Vegetation Index (NDVIT) based on transmitted light. The resulting NDVIT values were consistent with expected ranges and aligned with viticultural management practices and weather events. To assess the potential of TTWs for monitoring grape maturity, partial least squares (PLS) models were developed for Cabernet Franc, Chardonnay, and Riesling varieties using spectral data from the grape clusters, along with air temperature and Total Soluble Solids (TSS) content. Grape clusters were collected bi-weekly from a third vineyard in Niagara, Ontario, Canada, starting at the pea-size stage and continuing through veraison. After veraison, sampling frequency increased to weekly until harvest. After each collection day, the fruit was transported to a laboratory with a plant growth chamber designed to replicate the vineyard’s environmental conditions. Grape clusters were suspended over the TTWs in the plant growth chamber to collect spectral signatures of the fruit before the entire cluster was juiced to determine TSS content. The results of the PLS models suggest that TTWs are able to determine TSS content from the spectral signatures of the grape clusters, however unique models are required for each grape variety. These findings indicate that TTWs offer a promising approach to precision viticulture. Future research is needed to assess a broader range of grape varieties to better understand the relationship between NDVIT and vine health, as well as to refine the TSS prediction models. This will enable further exploration of the potential of transmitted light in monitoring grapevine health and maturity, supporting more accurate and timely viticulture practices in changing climate
A Modular Framework for the Plausible Depiction of Starburst Patterns
No full textWhen human viewers look at an intense light source, they can observe a set of dense spikes radiating from its center. The observed spike patterns result from a complex optical process known as the starburst phenomenon. These patterns have been frequently depicted in virtual applications (e.g., films and video games) to enhance the perception of brightness. From a broader scientific perspective, they also have relevant real life implications such as the impairing of driving safety. This may occur when an observed starburst pattern saturates a driver’s field of view. Previous computer graphics works on the simulation of the starburst phenomenon have primarily relied on the assumption that the resulting patterns are formed by light being obscured and diffracted by particles in the observer’s eyeball during the focusing process. However, the key role played by background luminance on the perception of starburst patterns has been consistently overlooked. By also taking into account this pivotal factor as well as the different physiological characteristics of the human photoreceptor cells, we propose a modular framework capable of producing plausible visual depictions of starburst patterns for daytime and nighttime scenes. To enhance the physical correctness and resolution of the simulated patterns, its formulation was guided by the Rayleigh-Sommerfeld diffraction theory and implemented using the Chirp Z Transform, respectively. We also introduce a biophysically-inspired algorithm to enable the seamless incorporation of the resulting patterns onto computer-rendered scenes. Besides examining theoretical and practical aspects associated with the use of the proposed framework in realistic image synthesis, we also derive biophysical insights that may contribute to the current knowledge about the inner workings of the starburst phenomenon
Echoes of contamination: Investigating heavy metal exposure at Wadi Faynan 100, Jordan
No full textLocated in southern Jordan, Wadi Faynan was once a center for copper mining, smelting, and trade during the Early Bronze Age (EBA). The legacy of pollution in Wadi Faynan is visible in the contemporary landscape in the form of spoil tips and over 250 copper mines. The largest and possibly most significant EBA site in Wadi Faynan is Wadi Faynan 100 (WF100), which dates to EBA Ib (3300-3000 BCE) and has clear evidence of copper production including copper ores, slag, and copper casting molds. This research employed laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to measure trace element concentrations of lead (Pb), cadmium (Cd), and arsenic (As) in human enamel from WF100 to determine if copper production during EBA Ib introduced heavy metal toxicity into the population. The sample consisted of 29 human teeth divided into three groups representative of different early life stages: first molars, premolars, and third molars. Although seven samples were excluded from the main analysis, the others all had trace amounts of Pb, Cd, and As. The samples were categorized into four different groupings for Pb based on their pattern of exposure across the growth layers of enamel: stable exposure, variable exposure, increasing exposure, and decreasing exposure. For Cd and As, each sample was identified as having concentrations above or below their limit of detections. Examination of the distribution of these heavy metals revealed inter- and intra-individual variation in exposure providing insight into participation in copper production activities and possible mobility patterns practiced at WF100
CADC++: Extending CADC with a Paired Weather Domain Adaptation Dataset for 3D Object Detection in Autonomous Driving
No full textLidar sensors enable precise 3D object detection for autonomous driving under clear weather but face significant challenges in snowy conditions due to signal attenuation and backscattering. While prior studies have explored the effects of snowfall on lidar returns, its impact on 3D object detection performance remains underexplored. Conducting such an evaluation objectively requires a dataset with abundant labelled data from both weather conditions and ideally captured in the same driving environment. Current driving datasets with lidar data either do not provide enough labelled data in both snowy and clear weather conditions, or rely on simulation methods to generate data for the weather domain with insufficient data. Simulations, nevertheless, often lack realism, introducing an additional domain shift that impedes accurate evaluations. This thesis presents our work in creating CADC++, a paired weather domain adaptation dataset that extends the existing snowy dataset, CADC, with clear weather data. Our CADC++ clear weather data have been recorded on the same roads and around the same days as CADC. We pair each CADC sequence with a clear weather one as closely as possible, both spatially and temporally. Our curated CADC++ achieves similar object distributions as CADC, enabling minimal domain shift in environmental factors beyond the presence of snow. Additionally, we propose track-based auto-labelling methods to overcome a limited labelling budget. Our approach, evaluated on the Waymo Open Dataset, achieves a balanced performance across stationary and dynamic objects and still surpasses a standard 3D object detector when using as low as 0.5% of human-annotated ground-truth labels
Toward a Taxonomy of Typestate Systems: Soundness Without Alias Information
No full textExternal third-party APIs are commonly used in real-world programming. Specifications or protocols are given by the designer to direct the usage of those APIs combined. The violation of specifications may crash the program, or weaken or break the guarantees of the framework, which would be vital to some safety-critical systems such as encryption.
Typestate system is one of the approaches to check the valid use of APIs based on a given protocol. However, the soundness of the general typestate system relies on the soundness of external alias information. Obtaining whole-program alias information is often expensive and inefficient. One way to remove this dependency is to restrict the protocols. This work tries to examine the class of protocols that can be soundly checked without alias information. We formalize the notion of the protocol and the typestate system, from where we further construct some special classes of protocols. We identify the group of typestate systems called the accumulative typestate system, which is a superset of typestate systems that can be checked soundly without alias information. We also pin down two groups of accumulative typestate systems that are actually sound without alias information
Melt-blowing of polymers for porous and functional air filters
No full textThis thesis develops innovative, high-performance, melt-blown nonwoven materials for air filtration. The first chapter presents a two-step process to create nano-porous, compostable PLA nonwovens with high porosity for particulate capture. First, PLA is melt-blended with polyethylene glycol (PEG) of varying molecular weights to enhance melt flow index (MFI), producing blends with MFI values ranging from 56 g/10 min to 238 g/10 min. These blends are processed into microfibers, with diameters from 1.05 to 2.64 µm, using a twin-screw extruder. The second step involves boiling water etching to remove PEG and form nanopores (50–200 nm), achieving approximately 85% particulate capture efficiency for 0.3 µm NaCl particles. This eco-friendly method shows potential for air and water filtration and battery
separators.
The second chapter addresses the limitations of conventional face masks, which lack antibacterial or antiviral properties. To improve mask functionality, advanced melt-blown filters are created using polypropylene (PP) and Rose bengal (RB), a photosensitizer. The study investigates the impact of processing temperature on fiber morphology, filtration efficiency, and antibacterial properties. The optimized filters show superior antibacterial performance, particulate filtration efficiency, and breathability, offering significant improvements for personal protective equipment (PPE), with enhanced antimicrobial protection and durability
Development of Novel Human Aggrecanse-2 Dual-Binding Bis-Squaramide Inhibitors
No full textOsteoarthritis (OA) is a degenerative joint disease that affects millions of individuals worldwide. OA is characterized by the breakdown of articular cartilage, including the proteoglycan aggrecan, which plays a crucial role in enabling cartilage to withstand compressive loads. A Disintegrin and Metalloproteinase with Thrombospondin Motifs-5 (ADAMTS-5; aggrecanase-2), has been reported to be the predominant aggrecanase in mice, and in vitro studies revealed ADAMTS-5 exhibits high efficiency at cleaving aggrecan. Although no disease modifying OA drugs have been developed, it is hypothesized that inhibitors against ADAMTS-5 could slow the progression of OA. Typical inhibitors of ADAMTS-5 include zinc-binding groups (ZBGs) that interact with the catalytic zinc. Recently, an exosite that inhibitors can target has been identified at a nearby domain, not within the catalytic site. Here we present the development of novel potential dual-binding inhibitors which aim to target both the catalytic site and exosite of ADAMTS-5.
The inhibitors investigated in this thesis incorporate a squaramide nucleus, which is an excellent molecular scaffold due to its ease of derivatization, known synthetic pathways, and commercial availability. To identify potential dual-binding bis-squaramide inhibitors, a large in silico library was constructed, consisting of the squaramide nucleus linking potential exosite binding groups and ZBGs. Numerous computational techniques were utilized to identify inhibitors, including molecular docking to evaluate potential interactions with both the binding pocket and exosite of ADAMTS-5, as well as molecular dynamics simulations to assess inhibitor stability and predict binding affinities. The four bis-squaramide molecules identified from the computational screening were successfully synthesized using a one-pot, microwave-assisted synthetic approach, which facilitated a high-throughput process through reaction automation. A range of bis-squaramide compounds were enzymatically screened with micromolar IC50’s for ADAMTS-5
"Superior by nature"?-Diagnosing dementia in northwestern Ontario
No full textIn 2025, Canada is home to approximately 771,939 people living with dementia and Ontario is projected to have the most new cases by province in the country by 2050. Northern Ontario makes up over 90% of the province’s landmass and has 6% of its population. In Northwestern Ontario specifically, there is a higher proportion of people over the age of 65 compared to the rest of the province. This is important because prevalence of dementia nearly doubles every five years after the age of 65, meaning a population more at risk of developing dementia. Rural and remote communities in the northwest region are struggling to meet the basic healthcare needs of their residents. The Ontario Medical Association has labeled the state of the healthcare in this region a ‘crisis’ (n.d.(b)). This research explored the experiences of giving and receiving a diagnosis of dementia from the perspectives of physicians and caregivers of people living with dementia in northwestern Ontario. Existentialist phenomenology was utilized to uncover shared meanings and understandings about the diagnosis process, particularly how these experiences are situated in a remote and rural context. There were significant system gaps that impacted the experience of caregivers of people living with dementia and physicians in northwestern Ontario. Not being heard by physicians damaged relationships between caregivers and the healthcare system and created feelings of mistrust, frustration, and isolation. Physicians managed the emotional work of dementia diagnoses in private while working to overcome system shortages that impacted their ability to care for people living with dementia. However, despite the tension in relationships between physicians and caregivers, they often cited similar healthcare challenges that greatly impacted good dementia care. The struggles plaguing the healthcare system in northwestern Ontario appeared to impact everyone involved in dementia diagnoses, and both caregivers and physicians were committed to overcoming challenges and providing the best care possible for people living with dementia