Ignition delay time, τ_ign, is a key quantity of interest that is used to assess the predictability of a chemical kinetic model. This dissertation explores the sensitivity of τ_ign to uncertainties in: 1. rate-rule kinetic rates parameters and 2. enthalpies and entropies of fuel and fuel radicals using global and local sensitivity approaches. We begin by considering variability in τ_ign to uncertainty in rate parameters. We consider a 30-dimensional stochastic germ in which each random variable is associated with one reaction class, and build a surrogate model for τ_ign using polynomial chaos expansions. The adaptive pseudo-spectral projection technique is used for this purpose. First-order and total-order sensitivity indices characterizing the dependence of τ_ign on uncertain inputs are estimated. Results indicate that τ_ign is mostly sensitive to variations in four dominant reaction classes. Next, we develop a thermodynamic class approach to study variability in τ_ign of n-butanol due to uncertainty in thermodynamic properties of species of interest, and to define associated uncertainty ranges. A global sensitivity analysis is performed, again using surrogates constructed using an adaptive pseudo-spectral method. Results indicate that the variability of τ_ign is dominated by uncertainties in the classes associated with peroxy and hydroperoxide radicals. We also perform a combined sensitivity analysis of uncertainty in kinetic rates and thermodynamic properties which revealed that uncertainties in thermodynamic properties can induce variabilities in ignition delay time that are as large as those associated with kinetic rate uncertainties. In the last part, we develop a tangent linear approximation (TLA) to estimate the sensitivity of τ_ign with respect to individual rate parameters and thermodynamic properties in detailed chemical mechanisms. Attention is focused on a gas mixture reacting under adiabatic, constant-volume conditions. The proposed approach is based on integrating the linearized system of equations governing the evolution of the partial derivatives of the state vector with respect to individual random variables, and a linearized approximation is developed to relate ignition delay sensitivity to scaled partial derivatives of temperature. The computations indicate that TLA leads to robust local sensitivity predictions at a computational cost that is order-of-magnitude smaller than that incurred by finite-difference approaches.

Although prior research has examined how individual difference factors are related to relationship initiation and formation over the Internet (e.g., online dating sites, social networking sites), little research has examined how dispositional factors are related to other aspects of online dating. The present research therefore sought to examine the relationship between several dispositional factors, such as Big-Five personality traits, self-esteem, rejection sensitivity, and attachment styles, and the use of online dating sites and online dating behaviors. Rejection sensitivity was the only dispositional variable predictive of use of online dating sites whereby those higher in rejection sensitivity are more likely to use online dating sites than those lower in rejection sensitivity. We also found that those higher in rejection sensitivity, those lower in conscientiousness, and men indicated being more likely to engage in potentially risky behaviors related to meeting an online dating partner face-to-face. Further research is needed to further explore the relationships between these dispositional factors and online dating behaviors.

Background-Ventricular hypertrophy is a physiological response to pressure overload that, if left untreated, can ultimately result in ventricular dysfunction, including diastolic dysfunction. The aim of this study was to test the hypothesis that frequency-dependent myofilament desensitization, a physiological response of healthy myocardium, is altered in hypertrophied myocardium. Methods and Results-New Zealand white rabbits underwent a pulmonary artery banding procedure to induce pressure overload. After 10 weeks, the animals were euthanized, hearts removed, and suitable trabeculae harvested from the free wall of the right ventricle. Twitch contractions, calibrated bis-fura-2 calcium transients, and myofilament calcium sensitivity (potassium contractures) were measured at frequencies of 1, 2, 3, and 4 Hz. The force frequency response, relaxation frequency response, and calcium frequency relationships were significantly blunted, and diastolic tension significantly increased with frequency in the pulmonary artery banding rabbits compared with sham-operated animals. Myofilament calcium sensitivity was virtually identical at 1 Hz in the treatment versus sham group (pCa 6.11 ± 0.03 versus 6.11 ± 0.06), but the frequency-dependent desensitization that takes place in the sham group (ΔpCa 0.14±0.06, P<0.05) was not observed in the pulmonary artery banding animals (ΔpCa 0.02±0.05). Analysis of myofilament protein phosphorylation revealed that the normally observed frequency-dependent phosphorylation of troponin-I is lost in pulmonary artery banding rabbits. Conclusions-The frequency-dependent myofilament desensitization is significantly impaired in right ventricular hypertrophy and contributes to the frequency-dependent elevation of diastolic tension in hypertrophy.

Prior research suggests that rejection sensitive individuals may find it easier to express their true selves in an online environment. The purpose of the present study was to examine the extent to which rejection sensitivity (RS) and true self influence self-disclosure within the context of online dating. We collected data from a total of 1,295 individuals who completed an online survey. For those who engaged in online dating, RS was not directly related to self-disclosure in online dating profiles or in communicating with individuals met through online dating sites/apps, but true self was. In addition, there was an indirect relationship between RS and self-disclosure in the context of online dating through true self. These findings suggest that rejection sensitive individuals who feel more comfortable revealing aspects of their "true"selves online may be more likely to engage in self-disclosure within the context of online dating, which could potentially offer some clue as to why rejection sensitive individuals may be somewhat more likely to engage in online dating than less rejection sensitive individuals. That is, rejection sensitive individuals are perhaps more likely to engage in online dating because it may facilitate representation of their "true"selves and may thus increase dating success.

Prior research (Blackhart et al., 2014) found that rejection-sensitive individuals are more likely to use online dating sites. The purpose of the current research was to explain the relationship between rejection sensitivity and online dating site usage. Study 1 examined whether true self mediated the relation between rejection sensitivity and online dating. Study 2 sought to replicate the findings of Study 1 and to examine whether self-disclosure moderated the relationship between true self and online dating in the mediation model. Results replicated those found by Blackhart et al. and also found that true self mediated the relationship between rejection sensitivity and online dating site usage. These findings suggest that rejection-sensitive individuals feel they can more easily represent their “true” selves in online environments, such as online dating sites, which partially explains why they are more likely to engage in online dating.

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Rejection sensitivity (RS) is defined as the tendency to anxiously anticipate, perceive, and overreact to real or perceived rejection and can have significant effects on interpersonal relationships. Previous research has shown the negative social effects of RS, particularly in the context of romantic relationships, but less is known about the cognitive implications of having high levels of RS. Specifically, it is unclear whether a heightened sensitivity to rejection is associated with enhanced error processing or feedback evaluation. The current study used EEG to examine the effect of RS on two event-related potential (ERP) components associated with error monitoring and feedback evaluation, error-related negativity (ERN) and feedback-related negativity (FRN), respectively. Participants completed a Flanker task during which they received either social (faces) or nonsocial (symbols) feedback about their performance. Results showed an increased ERN on error trials for individuals with higher RS. Although the FRN was not influenced by RS, there was an expectancy-valence interaction. FRN amplitude was also sensitive to condition, with correct feedback eliciting significantly more negative FRN in the social condition compared to the nonsocial condition; FRN for unexpected feedback was also greater in the social condition. Overall, the results suggest a relationship between error monitoring and RS, as well as a relationship between social information and feedback processing. Future research should further explore the relationship between rejection sensitivity, attention, and social feedback processing.

Sleep and cortisol function are two physiological self-regulatory processes that codevelop during infancy. Dysregulation of each system is linked to enduring health problems, so it is critical to understand factors contributing to the development of physiological self-regulation. However, it is not clear how infant sleep and cortisol interact with each other or with the parenting context. This project examined (1) the interplay of infant sleep and cortisol; (2) how cortisol interacts with parent characteristics in relation to infant sleep; and (3) whether consistent parenting buffers infant cortisol dysregulation. Study 1 (86 parent-infant dyads) investigated whether average nighttime sleep onset and duration predicted cumulative cortisol exposure, indexed by hair cortisol concentration (HCC). As hypothesized, infants who fell asleep earlier at night had lower HCC regardless of their family income and household chaos. Additionally, I expected that sleep characteristics on one night would predict total salivary cortisol exposure (AUCg) the next day, and that salivary cortisol at bedtime would predict sleep the same night. Partially supporting expectations, time-based analyses revealed that infants with lower cortisol on a particular evening fell asleep earlier the same night. In Study 2 (84 parent-infant dyads), I hypothesized that the link between parent characteristics (i.e., bedtime parental involvement and parental sensitivity) and infant sleep would differ by AUCg. Falling asleep independently predicted earlier sleep onset only for infants with dysregulated cortisol, whereas bedtime parental involvement did not predict sleep for infants with well-regulated cortisol. Infants with emotionally warm and appropriately responsive parents fell asleep earlier at night only if their cortisol was well-regulated. Utilizing archival data of 82 mother-infant dyads, Study 3 assessed consistency in parenting behaviors (i.e., smiles and laughter, and positive vocalizations), cortisol, and socioeconomic status (SES). As hypothesized, higher-SES infants experienced consistency, whereas lower-SES infants experienced inconsistency, in maternal smiles and laughter across 6 to 12 months of infancy. Contrary to expectations, inconsistent parenting did not predict cortisol. Findings highlight the intricate relation between two vital physiological processes codeveloping in the first year of life – sleep and cortisol regulation – and the role cortisol plays in moderating how parenting characteristics contribute to infant sleep.

As a result of the global climate change, extreme precipitation is occurring more frequently which increases the risk of flooding, especially in urban areas. Urbanisation is widely discussed regarding urban flooding where an increase of impervious surfaces limits the infiltration and increases the surface runoff. Flooding events in urban areas are increasing around the world and can cause large damages on infrastructure and buildings, which makes the cities vulnerable. Urban flood models are an important tool for analysing the capacity of the drainage systems, to predict the extent of the events and to find optimal locations to implement measures to prevent damages from flooding. In this project, a sensitivity analysis in MIKE FLOOD, a coupled 1D-2D flood model developed by DHI is presented, where sewer- and surface systems are integrated. The aim with this project is to investigate how the result of a coupled flood model vary in relation to changes in input parameters. The sensitivity analysis is performed to evaluate how different parameters impact the model output in terms of water depth and variations in cost of flooded buildings, roads, rail- and tramways. The analysis is applied in a case study in Lundby-Lindholmen, Gothenburg city, Sweden. The results show that modelling without infiltration influenced the model output the most, with the largest increase both in terms of cost and water depth over the investigated area. Here the correlation between the initial water saturation and location of the applied pre-rain was highlighted. The model outputs were less sensitive to changes in surface roughness (expressed as Manning value) than without infiltration but did lead to measurable changes in surface water depth and distribution while the flood damage cost didn’t show any major changes. Additionally, the coupled flood model was evaluated in terms of handling changes in magnitudes of rain-events. Data indicates the shorter the return period, the smaller the flood propagation, as well as the flood damage cost decreases with shorter return periods. The data evaluated supports the use of this coupled model approach for shorter return periods in terms of flood propagation.

Uncertainty in model predictions is associated with data, parameters, and model structure. The estimation of these contributions to uncertainty is a critical issue in hydrology. Using a variety of single and multiple criterion methods for sensitivity analysis and inverse modeling, the behaviors of two state-of-the-art land surface models, the Simple Biosphere Model 3 and Noah model, are analyzed. The different algorithms used for sensitivity and inverse modeling are analyzed and compared along with the performance of the land surface models. Generalized sensitivity and variance methods are used for the sensitivity analysis, including the Multi-Objective Generalized Sensitivity Analysis, the Extended Fourier Amplitude Sensitivity Test, and the method of Sobol. The methods used for the parameter uncertainty estimation are based on Markov Chain Monte Carlo simulations with Metropolis type algorithms and include A Multi-algorithm Genetically Adaptive Multi-objective algorithm, Differential Evolution Adaptive Metropolis, the Shuffled Complex Evolution Metropolis, and the Multi-objective Shuffled Complex Evolution Metropolis algorithms. The analysis focuses on the behavior of land surface model predictions for sensible heat, latent heat, and carbon fluxes at the surface. This is done using data from hydrometeorological towers collected at several locations within the Large-Scale Biosphere Atmosphere Experiment in Amazonia domain (Amazon tropical forest) and at locations in Arizona (semiarid grass and shrub-land). The influence that the specific location exerts upon the model simulation is also analyzed. In addition, the Santarém kilometer 67 site located in the Large-Scale Biosphere Atmosphere Experiment in Amazonia domain is further analyzed by using datasets with different levels of quality control for evaluating the resulting effects on the performance of the individual models. The method of Sobol was shown to give the best estimates of sensitivity for the variance-based algorithms and tended to be conservative in terms of assigning parameter sensitivity, while the multi-objective generalized sensitivity algorithm gave a more liberal number of sensitive parameters. For the optimization, the Multi-algorithm Genetically Adaptive Multi-objective algorithm consistently resulted in the smallest overall error; however all other algorithms gave similar results. Furthermore the Simple Biosphere Model 3 provided better estimates of the latent heat and the Noah model gave better estimates of the sensible heat.