Tornado outbreaks have significant human impact, so it is imperative forecasts of these phenomena are accurate. As a synoptic setup lays the foundation for a forecast, synoptic-scale aspects of Storm Prediction Center (SPC) outbreak forecasts of varying accuracy were assessed. The percentages of the number of tornado outbreaks within SPC 10% tornado probability polygons were calculated. False alarm events were separately considered. The outbreaks were separated into quartiles using a point-in-polygon algorithm. Statistical composite fields were created to represent the synoptic conditions of these groups and facilitate comparison. Overall, temperature advection had the greatest differences between the groups. Additionally, there were significant differences in the jet streak strengths and amounts of vertical wind shear. The events forecasted with low accuracy consisted of the weakest synoptic-scale setups. These results suggest it is possible that events with weak synoptic setups should be regarded as areas of concern by tornado outbreak forecasters.

The purpose of this research is to simulate warm-season mesoscale convective systems (MCSs) using the Weather Research and Forecasting Model (WRF) to determine whether modeled atmospheric variables are capable of discriminating between derecho formation and intensity. Fifty total events are selected with half being derecho-producing MCSs and half being non-derecho producing MCSs. WRF is used to model each event with a high-resolution domain centered over the Midwest using the North American Regional Reanalysis (NARR) dataset as initial and boundary conditions. Atmospheric conditions downstream of the MCS damage path are compared to thresholds established by previous research to determine if the model accurately simulates the expected environment. The goal of the research is to gain insight into how well a high-resolution model can simulate the environment that is expected. It is anticipated that the model will be able to distinguish between environments associated with a derecho-producing MCS and a non-derecho MCS.

Sepsis is an uncontrolled response to infection. Severe sepsis is associated with organ dysfunction, and has mortality rate of 30-50%. Identification of severity of sepsis and prediction on mortality is crucial in making clinical decisions. Recently, cell-free DNA (cfDNA) in blood was found to have high discriminative power in predicting ICU mortality in patients with severe sepsis. In an analysis of 80 severely septic patients, the mean cfDNA level in survivors (1.16±0.13μg/ml) was similar to that of healthy volunteers (0.93±0.76μg/ml), while that of non-survivors (4.65±0.48μg/ml) was notably higher. Therefore, rapid quantification of cfDNA concentration in blood will enable physicians to quickly predict mortality of sepsis and decide on treatment. Current methods for quantification of cfDNA involve multiple steps including centrifugation, DNA-extraction from plasma, and its quantification either through spectroscopic methods or quantitative PCR. The whole process is time consuming, thus is not suitable for immediate bedside assessment. To solve the problems, a microfluidic device is designed and fabricated in this thesis, which is potential for cfDNA quantification directly using blood in 5 minutes. The goal is to use this device for distinguishing survivors or healthy donors from non-survivors in patients with severe sepsis. The two-layer device consists of a sample channel (top) and an accumulation channel (bottom) that intersect each other. The accumulation channel is preloaded with 1% agarose gel, and the blood containing cfDNA and intercalating fluorescent dye is loaded in the sample channel. Fluorescently labeled DNA is able to be trapped and concentrated at the intersection using a DC electric field, and fluorescent intensity of the accumulated DNA is representative of its concentration in the blood. The simulated electric field in the sample channel reveals that both the magnitude and the gradient of electric field reach their maximum values at the intersection. Force analysis shows that DNA was driven into the gel by the dominate electrophoretic force, while red blood cells moved away from the gel due to a strong dielectrophoretic force. In this thesis, 4 types of samples have been used to characterize the performance of the device. It showed that DNA was efficiently accumulated at the intersection, and the fluorescent intensity could be measured using a fluorescent microscope. Samples from healthy donors were able to be distinguished from that of severely septic patients in 5 minutes. However, better resolution was needed for differentiating various cfDNA concentrations in patient samples. The discussion on the effect of applied voltage showed that 9V is an optimized setting compared with 3V and 15V. In addition, it has been proved that the fluorescent reagent could be immobilized in the device and the sample preparation could be absolutely eliminated. In summary, the device proposed in this thesis is capable of distinguishing severely septic patients from healthy donors using clinical plasma in 5 minutes, and is potential to be applied in clinical blood samples. It has low cost, and is ready to be developed into a fully functioned system. This tool can be a valuable addition to the ICU to rapidly assess the severity of sepsis for informed decision making. / Thesis / Master of Applied Science (MASc)

Traditional animal models of severe asthma do not recapitulate defining asthma characteristics, including persistent airway hyper-responsiveness, and chronic neutrophilic inflammation. This is problematic because moderating airway hyper-responsiveness decreases asthma frequency and severity, making it a paramount pharmacological goal in asthma research. Employing a spontaneous equine asthma model (equine pasture asthma, EPA), we first confirmed reversible airway obstruction in eight diseased horses during asthma exacerbations in response to ß2renergic agonist stimulation. Next, non-specific airway hyper-responsiveness was confirmed using methacholine bronchoprovocation to identify the provocative concentration causing a 40% increase in baseline lung resistance (PC40RL)- a threshold similarly employed in evaluating human asthmatics unable to mount forced expiration. The PC40RL of ten EPA horses was consistently <1mg/ml of methacholine, which is a cutoff that has been used to diagnose severe human asthma. Like non-asthmatic humans, ten control horses did not respond to methacholine doses up to 16 mg/ml. Finally, persistence of AHR was documented during absence of seasonal aeroallergen triggers in five horses that were evaluated between 3 and 31 months following the initial methacholine bronchoprovocation. This unique ability of EPA horses to model AHR attributes that are not addressed by other animal models points to the suitability of EPA horses to decipher the mechanistic basis of airway hyper-responsiveness. Building on knowledge that 2renergic receptor (AR) signaling is required to develop the asthma phenotype in a murine model, differentially expressed genes from serial lung biopsies of two EPA affected and two controls were filtered to identify genes that interact with the 2-AR. Hyperpolarization Activated Cyclic Nucleotide-Gated Potassium Channel 4 (HCN4) was prioritized because of its interactions with the 2-AR. Relative to control horses, HCN4 was constitutively expressed in airway smooth muscle of EPA horses during remission and increased during seasonal disease exacerbation. Agonism of airway contraction by HCN4 was proven using the specific HCN4 antagonist, ivabradine, which caused dose dependent decreases in carbachol induced contractile responses in both EPA and control bronchi in vitro. These findings highlight utility of EPA as a model of severe asthma and HCN4 as a mediator of airway contraction that warrants further investigation in severe human asthma.

No description available.

No description available.

No description available.

Since the Fukushima Daiichi nuclear accident, there have been ongoing efforts to enhance the modelling capabilities for severe accidents in nuclear power plants. The primary severe accident analysis code used in Canada for its CANDU reactors is MAAP-CANDU (adapted from MAAP-LWR). In order to meet the new requirements that have evolved since Fukushima, upgrades to MAAP-CANDU have been made most recently by the Canadian nuclear industry. While the newest version (i.e. MAAP5-CANDU) offers several important improvements primarily in core nodalization and core collapse modelling, it still lacks mechanistic models for many key thermo-mechanical deformation phenomena that may significantly impact accident progression and event timings. It is also a general consensus that having alternative analysis tools is beneficial in improving our confidence in the simulation results, especially given the complex nature of severe accident phenomena in CANDU and the limited experimental support. This thesis seeks a novel approach to CANDU severe accident modelling by combining the best-estimate thermal-hydraulic code RELAP5, the severe accident models in SCDAP, and several CANDU-specific mechanistic deformation models developed by the author. This work mainly consists of two parts. The first part is focused on the assessment of natural circulation heat sinks following crash-cooldown in the early-phase of a Station Blackout (SBO) accident where fuel channel deformation can be precluded. The effectiveness of steam generator heat removal after crash-cooldown and that of the several water make-up options were demonstrated through the simulation of several SBO scenarios with/without crash-cooldown, sensitivity studies, as well as benchmarking against station and experimental measurements. In the second part, several mechanistic severe accident models were developed to enhance the simulation fidelity beyond the initial steam generator heat sink phase to the moderator boil-off and core disassembly phases. This includes models for predicting the pressure tube ballooning and sagging phenomena during the fuel channel heat-up phase and models for the sagging and disassembly of fuel channel assemblies during the core disassembly phase. After benchmarking against relevant channel deformation experiments, the models were successfully integrated into the RELAP/SCDAPSIM/MOD3.6 code as part of the SCDAP subroutines. The advantage of utilizing a code such as SCDAP is that generic models for fission product release and hydrogen generations, which are well benchmarked, can be directly applied to CANDU simulations. With the modified MOD3.6 code the early-phase SBO simulations were extended to include the later stages of SBO until the calandria vessel dryout. The current modelling approach replaced the simple threshold-type models commonly seen in the integrated severe accident codes such as MAAP-CANDU with more mechanistic models thereby providing a more robust treatment of the core degradation process during severe accident in CANDU. / Thesis / Doctor of Philosophy (PhD)

Current biologics often fail to effectively manage symptoms in severe allergic asthmatic patients, necessitating the exploration of novel therapeutic approaches. Our laboratory has recently identified Lectin Mannose Binding 1 (LMAN1) as a regulatory cell surface receptor for house dust mite (HDM). Binding of LMAN1 to HDM allergens was found to depend on mannosylation, suggesting a potential broader role of this receptor in the recognition of other highly mannosylated allergens such as molds. Alternaria alternata (A. alternata) is a ubiquitous mold often associated with severe asthma. Whether LMAN1 can also act to regulate responses to A. alternata, remains to be explored. To this end, we subjected both WT and LMAN1 knockout mice to an A. alternata-induced asthma model. The absence of LMAN1 resulted in a substantial increase in airway hyperresponsiveness (AHR). Interestingly, changes in AHR did not correlate with either eosinophil or neutrophil infiltration into the lung but instead, went hand in hand with a reduction in alveolar macrophages and an increase in type-2 innate lymphoid cells. Work is currently ongoing to further investigate the cellular and molecular mechanisms underlying these findings. This discovery highlights LMAN1 as a promising target for innovative therapeutic interventions.

Past research has primarily focused on tornado outbreak intensity; however, this study presents an updated ranking index scheme that provides intensity ranks for both hail and tornado-dominant outbreaks. All outbreaks spanning 1960 - 2022 were obtained using a 24-hour kernel-density-based approach to map the severe weather report density. Notably, secular trends in the annual means of many of these variables (such as the number of hail and wind reports) showed a significant upward trend until 2010, after which that trend flattened. Thus, these fields were detrended using support vector regression that better fit these parameters' underlying annual time series. The resulting indices delineate between tornado and hail-dominant outbreaks, allowing further investigation into mixed-mode outbreaks and synoptic-scale precursors of these unique outbreak modes. It also provides an objective measure of outbreak intensity which can be useful when assessing potential future impacts from events with similar meteorological characteristics.