Objectives. To characterize the association between potency and comprehensive sexual function. The accurate assessment of sexual function is critical for the evaluation of outcomes after treatment of prostate cancer. The assessments of potency typically used in this context, however, may be oversimplified. Methods. CaPSURE is a large, observational database of men with prostate cancer. Participants complete health-related quality-of-life questionnaires, including the University of California, Los Angeles Prostate Cancer Index, every 6 months after treatment. A total of 5135 men completed at least one questionnaire and did not use medications for erectile function. The men were categorized as potent or impotent based on their ability to have erections and/or intercourse in the prior 4 weeks. Using the remaining questions on the Prostate Cancer Index, sexual function and bother scores were calculated for each group. Results. Of the 5135 men, 27.4% were potent. The mean sexual function scores were 56 and 13 for potent and impotent men, respectively (P Ͻ0.0001). The corresponding mean bother scores were 62 and 36 (P Ͻ0.0001). The function scores ranged from 0 to 100 and 0 to 92 among potent and impotent men, respectively, and bother scores from 0 to 100 in both groups. Function was inversely associated with age in both groups, but bother did not change among potent men and ameliorated among impotent men. Individual Prostate Cancer Index questions correlated with potency to a variable extent. Conclusions. Although potent and impotent men have divergent sexual function and bother scores after treatment, the wide range of these scores in both groups denotes a complex picture of sexual function. The simple documentation of potency after treatment provides an insufficient measure of sexual health-related quality of life and should be supplemented with more comprehensive measures. UROLOGY 61: 190-196, 2003.
In the era of multi-core processors, it is increasingly important to extract parallelism from programs. A key work to find and extract parallelism is data dependence analysis. This paper proposes to analyze the data dependences among code blocks offline, so as to save the computing time and resources with runtime execution.Offline data dependence analysis is feasible because register numbers to access are usually directly encoded in instructions, and register accesses are way more frequent than memory accesses. Therefore we may parse an executable file, divide it into code blocks, and find their register read/write dependences, which can be used at runtime to accelerate future executions.The offline analysis is more than mere static analysis, because many implicit dependences are only revealed at runtime. So we will simulate a runtime environment to analyze the simulated execution, which helps to better understand the dependences, and facilitate runtime parallelization.We built a trace driven simulator and conducted experiments with SPEC2006 benchmarks. The data shows that compared with online analysis, for every 1000 instructions the offline analysis will be able to save at least 1420 ∼ 2332 clocks of time (i.e. 1.42 ∼ 2.33 times of performance improvement), plus other additional 13 ∼ 32 clocks of time (i.e. 1.3% ∼ 3.2% of performance improvement), or equivalent computing resource.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.