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No description available.

<p>Preeclampsia and other hypertensive disorders of pregnancy impact 2-8% of pregnancies with often devastating results. Current treatment methods resort to birth, which forces the fetus into the world before they are fully developed but can save the mother’s life. Preeclampsia is broadly considered to be of placental origin and current etiologic understanding focuses on systemic endothelial dysfunction triggered by an imbalance of vasoregulatory factors released by this maternal/fetal organ. This imbalance explains many early-term cases but fails to adequately address later cases where this imbalance is not always seen. Conversely, ischemia-reperfusion of the kidney is known to correlate with endothelial dysfunction, and preeclamptic women are known to have a stenosis in their left renal vein (LRV) in the supine position (on their back). Herein, we suggest that extrinsic compression of the LRV by the gravid uterus, without collaterals, produces a renal injury which can induce systemic endothelial cell dysfunction. We theorize this compression is position dependent and produces renal ischemia through an unchecked cycle of increased intrarenal pressure, subsequent afferent arteriole constriction and decreased glomerular perfusion, and activation of the renin-angiotensin-aldosterone system. We aim to elucidate this through murine studies of a surgically induced LRV stenosis and a retrospective clinical study where the maternal renal veins are measured from magnetic resonance images. Findings from this work suggest partial renal venous outflow obstruction leads to renal injury but could be moderated through alternative maternal resting positions. This potential alternative pathologic mechanism has significant clinical implications for future therapies targeting this condition.</p>

<p>Emerging technologies such as real-time travel information systems and automated vehicles (AVs) have profound impacts on driver decision-making behavior. While they generally have positive impacts by enabling drivers to make more informed decisions or by reducing their driving effort, there are several concerns related to inadequate consideration of cognitive and psychological aspects in their design. In this context, this dissertation analyzes different aspects of driver cognition and psychology that arise from drivers’ interactions with these technologies using physiological data collected in two sets of driving simulator experiments.</p> <p>This research analyzes the latent cognitive and psychological effects of real-time travel information using electroencephalogram (EEG) data measured in the first set of driving simulator experiments. Using insights from the previous analysis, a hybrid route choice modeling framework is proposed that incorporates the impacts of the latent information-induced cognitive and psychological effects along with other explanatory variables that can be measured directly (i.e., route characteristics, information characteristics, driver attributes, and situational factors) on drivers’ route choice decisions. EEG data is analyzed to extract two latent cognitive variables that capture the driver’s cognitive effort during and immediately after the information provision, and cognitive inattention before implementing the route choice decision. </p> <p>Several safety concerns emerge for the transition of control from the automated driving system to a human driver after the vehicle issues a takeover warning under conditional vehicle automation (SAE Level 3). In this context, this study investigates the impacts of driver’s pre-warning cognitive state on takeover performance (i.e., driving performance while resuming manual control) using EEG data measured in the second set of driving simulator experiments. However, there is no comprehensive metric available in the literature that could be used to benchmark the role of driver’s pre-warning cognitive state on takeover performance, as most existing studies ignore the interdependencies between the associated driving performance indicators by analyzing them independently. This study proposes a novel comprehensive takeover performance metric, Takeover Performance Index (TOPI), that combines multiple driving performance indicators representing different aspects of takeover performance. </p> <p>Acknowledging the practical limitations of EEG data to have real-world applications, this dissertation evaluates the driver’s situational awareness (SA) and mental stress using eye-tracking and heart rate measures, respectively, that can be obtained from in-vehicle driver monitoring systems in real-time. The differences in SA and mental stress over time, their correlations, and their impacts on the TOPI are analyzed to evaluate the efficacy of using eye-tracking and heart rate measures for estimating the overall takeover performance in conditionally AVs.</p> The study findings can assist information service providers and auto manufacturers to incorporate driver cognition and psychology in designing safer real-time information and their delivery systems. They can also aid traffic operators to incorporate cognitive aspects while devising strategies for designing and disseminating real-time travel information to influence drivers’ route choices. Further, the study findings provide valuable insights to design operating and licensing strategies, and regulations for conditionally automated vehicles. They can also assist auto manufacturers in designing integrated in-vehicle driver monitoring and warning systems that enhance road safety and user experience.