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The aging process affects every anatomical layer of the face. Improved knowledge of how aging occurs in each anatomical layer of the face has helped evolve the facial rejuvenation strategies with HA fillers. Understanding the age-related changes in the anatomical facial layers, including their time of onset and how the changes occur in the different tissue layers, an injector can provide much more targeted and refined HA filler treatments. As fillers’ use has increased, there has been a distinct shift away from procedures lifting the skin and SMAS. We can selectively target the anatomical facial layers with HA fillers for more refined and predictable outcomes. An extensive range of HA filler variants is now available. Each filler type is optimized and designed to be injected into specific tissue planes for the best results. Knowing the predictable aging changes in the different tissue layers of the face is crucial as this guides the optimum filler choice. Working knowledge of the individual characteristics of the numerous HA-based products allows for their effective placement in the correct layer. Familiarity with the correct HA product may also help to minimize the downtime and risk of adverse events.

Human error is a leading cause of collisions on highways. Thus, if the aim is to reduce collision rates and keep drivers safe, it is necessary to investigate the factors that influence human mistakes and develop mitigation strategies to prevent these errors from occurring. One crucial approach to achieving lower collision rates is to design highways that do not overwhelm drivers with high mental workloads since too many tasks that challenge drivers’ workload levels lead to human error. Better design will allow drivers enough mental capacity to make proper decisions. However, there is a lack of research on the quantitative relationship between mental workload and objective safety measures, as well as an absence of information on how to explicitly incorporate workload demand in geometric design guidelines and manage highway speeds in complex road environments. To address this research gap, this thesis investigates the relationship between mental workload and highway traffic safety from a geometric design perspective. The geometric design attributes for horizontal and vertical curvatures were automatically extracted from LiDAR data. This data offered various highway geometric parameters such as degree of curvatures and deflection angles of horizontal curves, detection of the existence of vertical crest curves, changes in cross-section, intersections, and available sight distances. Then, the outputs from the self-report measures were related to collision data and highway geometric design parameters. The objectives were to: (1) examine and model the relationship between workload demand and collisions using safety performance function, (2) calibrate highway design guidelines using reliability analysis, (3) create a system advisory speed limit on horizontal curves that incorporates workload demand, and finally (4) update the current workload ratings by adding new factors to assess the impact of weather and in-car technologies on workload levels. The results from the safety performance function showed a statistically significant relationship between collisions and MWL. The probability of non-compliance from the reliability analysis revealed that the mental workload stopping sight distance satisfied 99% of the driving population. Then, based on the mental workload stopping sight distance, an advisory speed limit, which compensates for any restrictions in mental workload sight distance was proposed. Finally, the last objective resulted in mental workload ratings that were highly correlated to their counterparts in the literature. Additionally, the new ratings incorporated several essential factors such as active transportation, severe weather conditions, and in-car assistance technologies. This thesis significantly contributes to the current body of work by providing a framework to transition from a subjective workload measure to safety, design, and operational transportation applications. These applications would provide engineers with the tools to evaluate their designs in terms of mental workload and identify the countermeasures to address challenging infrastructural designs.

Purpose Effects of hemodialysis on pharmacokinetic properties and QTc were studied in 4 patients taking daily methadone dose of 100 mg (range, 60–120 mg). Methods Methadone in serum, dialysate, and urine were measured by LC-MS/MS. QTc was calculated with Bazett’s formula. Findings The serum C min methadone level was 1124 nmol/L (range, 547–1581 nmol/L). Methadone dialysate clearance was 17.1 mL/min (range, 13.7–20.6 mL/min). Total loss in dialysate was 2.30% (range, 1,25–3,70%) of daily methadone intake. QTc increased from 391 msec (range, 369–406 msec) to 445 msec (range, 407–479 msec), independently of serum methadone level, which may be explained by normalization of serum electrolytes. Implications Methadone dose adjustment is not needed because of hemodialysis.