An increasing number of transplant centers are performing adult living donor liver transplantation (LDLT). We evaluated peoples' perspectives on possible outcomes of living donation, thresholds for donating, and views regarding the donation process. One hundred fifty people were surveyed; half were from a medical care group serving an indigent population and half were from a private clinic. Preferences about outcomes of adult living donation were ranked and quantified on a visual analogue scale. Thresholds for donation to a loved one were quantified. Sixty percent of the respondents suggested they would prefer to donate and die and have the transplant recipient live rather than forgo donation and have the potential transplant recipient die of liver failure. Participants' stated threshold for living donation was a median survival for themselves of only 79%. They would require that their loved one have a median survival of 55% with transplantation before they would agree to donate. Respondents from the medical care group reported higher survival thresholds for themselves and the transplant recipient, and race was the most statistically significant predictor of those thresholds. Sex was more predictive of threshold probabilities from the private clinic. Eighty-one percent of the respondents believed that the potential donor, not a physician, should have the final say regarding candidacy for living donation. In conclusion, the findings of this survey support the use of adult LDLT. Most respondents were willing to accept mortality rates that far exceed the estimated risk of donation and favored outcomes in which a loved one was saved. (Liver Transpl 2001;7:335-340.)

There was little agreement between patients' preference values about hepatitis C and their physicians' estimates of those values. Utility analysis could facilitate shared decision making about hepatitis C.

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With an ever growing emphasis on security systems, automated personal identification based on biometrics has been getting extensive focus in both research and practical over the last decade. The methods for iris recognition mainly focus on feature representation and matching. As we known traditional iris recognition method is using Gabor Wavelet features, the iris recognition is performed by a 256 byte iris code, which is computed by applying Gabor wavelets to a given portion of iris. Log Gabor wavelet based features are invariant to changes in brightness and illumination whereas techniques like principal component analysis can produce spatially global features. The goal of this paper is to compare feature extraction algorithm based on PCA, Log Gabor Wavelet and Gabor Wavelet. We use these methods to generate feature vectors that could represent iris efficiently. Conclusions based on comparisons can provide useful information for further research. Performance of these algorithms is analyzed using CASIA database.