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Optimal Campaign Strategies in Fractional-Order Smoking Dynamics
Zeb, Anwar,Zaman, Gul,Jung, Il Hyo,Khan, Madad Verlag der Zeitschrift für Naturforschung 2014 Zeitschrift für Naturforschung. A, A journal Vol.69 No.5
<P>This paper deals with the optimal control problem in the giving up smoking model of fractional order. For the eradication of smoking in a community, we introduce three control variables in the form of education campaign, anti-smoking gum, and anti-nicotive drugs/medicine in the proposed fractional order model. We discuss the necessary conditions for the optimality of a general fractional optimal control problem whose fractional derivative is described in the Caputo sense. In order to do this, we minimize the number of potential and occasional smokers and maximize the number of ex-smokers. We use Pontryagin’s maximum principle to characterize the optimal levels of the three controls. The resulting optimality system is solved numerically by MATLAB.</P>
Ali, Sajid,Ahmad, Bashir,Ali, Ijaz,Mahmood, Nourin,Anwar, Naveed,Saeedi, Ilyas,Afridi, Jehan Zeb Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.5
Background: Response to antiviral therapy has been linked to different genotypes and this impacts on clinical management. Data on general responses to standard interferon (IFN) against HCV infection exists but little is known regarding HCV genotype specific responses. Purpose: Therefore, we attempted to determine genotype specific responses of chronic HCV patients, having different HCV genotypes, to standard IFN and ribavirin combination therapy administered for a period of six months in Kybher Pakhtunkhwa province of Pakistan. Materials and Methods: HCV genotype was determined for all serum samples. Each patient received standard IFN combination therapy with ribavirin administered at dose of 3 MIU three times a week and 800-1200 mg/day, respectively, for a period of six months. After completion of this therapy, PCR was performed for all course completed subjects. Results: Out of total 51 selected patients the most abundant genotypes were 3a (49.0%) and 1a (21.6%) followed by 3b (9.8%), 1b (7.84%), 2a (7.84%) and untypable (3.94%). Moast responsive genotypes were 2a followed by 3a, with end of treatment responses of 77.7%, and 72.2%. Responses for 3b, 1b and untypable were 66.7%, 33.3% and 0%, respectively. Conclusions: IFN response is efficient in case of 2a and 3a genotypes while in case of untypable genotypes, further categorization is required to know about genomic sequences and to adopt some new regimes against these genotypes.