Sorry Buddy, But Your Name Isn\u27t on the List: Fear and the Ethics of Organ Donation in Film

The fear of death and illness is a powerful motivator. When taking into account the ethical reasoning that drives organ transplantation and procurement practices, it is persuasive enough to sway minds and corrupt pure reason. And so this paper will uncover how fear of illness and death shape answers to the ethical questions that arise in transplant debates and how these debates are in turn raised in the ethical dilemmas portrayed by popular American films. This paper will examine recent films such as The Island, and Never Let Me Go to illustrate how the ethical dilemmas associated with organ transplantation, and the fear engendered by these depictions of it express the ethical debates of the American culture. It will determine that the shortage of available organs lies at the root of this fear, and then analyze how it inspires two general views of transplantation debates. It creates a fear that motivates the organ recipient and a fear which motivates the potential organ donor

Autonomously managed electrical power systems

The electric power systems for future spacecraft such as the Space Station will necessarily be more sophisticated and will exhibit more nearly autonomous operation than earlier spacecraft. These new power systems will be more reliable and flexible than their predecessors offering greater utility to the users. Automation approaches implemented on various power system breadboards are investigated. These breadboards include the Hubble Space Telescope power system test bed, the Common Module Power Management and Distribution system breadboard, the Autonomusly Managed Power System (AMPS) breadboard, and the 20 kilohertz power system breadboard. Particular attention is given to the AMPS breadboard. Future plans for these breadboards including the employment of artificial intelligence techniques are addressed

Program computes equilibrium normal shock and stagnation point solutions for arbitrary gas mixtures

Program computes solutions for flow parameters in arbitrary gas mixtures behind a normal and a reflected normal shock, for in-flight and shock-tube stagnation conditions. Equilibrium flow calculations are made by a free-energy minimization technique coupled with the steady-flow conservation equations and a modified Newton-Raphson iterative scheme

Brazil soybean yield covariance model

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature

Argentina soybean yield model

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years

Argentina wheat yield model

Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963

Argentina corn yield model

A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years

Brazil wheat yield covariance model

A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature

A perfect-gas analysis of the expansion tunnel, a modification to the expansion tube

Perfect gas analysis of expansion shock tunnel with nozzle to stabilize expansio

A study of the use of great paintings in religious education

https://place.asburyseminary.edu/ecommonsatsdissertations/1929/thumbnail.jp