79 research outputs found

    Comparing sexual risks and patterns of alcohol and drug use between injection drug users (IDUs) and non-IDUs who report sexual partnerships with IDUs in St. Petersburg, Russia

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    <p>Abstract</p> <p>Background</p> <p>To date, the great majority of Russian HIV infections have been diagnosed among IDUs and concerns about the potential for a sexual transmission of HIV beyond the IDU population have increased. This study investigated differences in the prevalence of sexual risk behaviors between IDUs and non-IDUs in St. Petersburg, Russia and assessed associations between substance use patterns and sexual risks within and between those two groups.</p> <p>Methods</p> <p>Cross-sectional survey data and biological test results from 331 IDUs and 65 non-IDUs who have IDU sex partners were analyzed. Multivariate regression was employed to calculate measures of associations.</p> <p>Results</p> <p>IDUs were less likely than non-IDUs to report multiple sexual partners and unprotected sex with casual partners. The quantity, frequency and intensity of alcohol use did not differ between IDUs and non-IDUs, but non-IDUs were more likely to engage in alcohol use categorized as risky per the alcohol use disorders identification test (AUDIT-C). Risky sexual practices were independently associated with monthly methamphetamine injection among IDUs and with risky alcohol use among non-IDUs. Having sex when high on alcohol or drugs was associated with unprotected sex only among IDUs.</p> <p>Conclusions</p> <p>Greater prevalence of sexual risk among non-IDUs who have IDU sex partners compared to IDUs suggests the potential for sexual transmission of HIV from the high-prevalence IDU population into the general population. HIV prevention programs among IDUs in St. Petersburg owe special attention to risky alcohol use among non-IDUs who have IDU sex partners and the propensity of IDUs to have sex when high on alcohol or drugs and forgo condoms.</p

    Real-time optimization for large scale processes: Nonlinear model predictive control of a high purity distillation column

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    The purpose of this paper is an experimental proof-of-concept of the application of NMPC for large scale systems using specialized dynamic optimization strategies. For this aim we investigate the application of modern, computationally effcient NMPC schemes and real-time optimization techniques to a nontrivial process control example, namely the control of a high purity binary distillation column. All necessary steps are discussed, from formulation of a DAE model with 164 states up to the final application to the experimental apparatus. Especially an effcient real-time optimization scheme based on the direct multiple shooting method is introduced. It is characterized by an initial value embedding strategy, that allows to immediately respond to disturbances, and real-time iterations, that dovetail the optimization iterations with the real process development. Using this scheme, sampling times of 10 seconds are feasible on a standard PC. This shows that an efficient NMPC scheme based on large scale DAE models is feasible for the real-time control of a pilot scale distillation column
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