Suchergebnisse

The dynamics of an autonomous underwater vehicle (AUV), which can perform manoeuvres with pitch angles in the range of 90° is investigated in this paper. The purpose of the AUV is to perform station keeping manoeuvre at about 90° pitch angle by varying propeller revolution. The AUV is launched / retrieved in horizontal orientation. Quaternion mathematics, 4 quadrant propeller open water characteristics and PID controller for propeller revolution are incorporated in manoeuvring mathematical model for this purpose. A procedure for optimizing the gain coefficients for the PID controller is developed using the manoeuvring mathematical model. Two design configuration of the AUV are investigated, positively buoyant and negatively buoyant. It is shown that both the optimal gain coefficients for the PID controller for propeller revolution and dynamic response of the AUV are different for each design configuration.

Abstract
Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.