ABSTRACT

In this paper, genetic algorithm (GA) is used to solve the GENCOs profit based unit commitment problem (PBUCP) in a dayahead competitive electricity markets considering power and reserve generations simultaneously, whereas enhanced lambda iteration (ELI) method is used to solve the economic dispatch (ED) sub-problem. The proposed algorithm helps GENCO to take decision regarding how much power and reserve must be put up for sale in the markets to receive the maximum profit. Moreover, two types of market strategies based on the demand constraint are discussed and implemented. Performance of GA is tested on 3-unit, 12-h and 10-unit, 24-h test systems. Results demonstrate that the proposed method is superior to the other methods reported in the literature.Keywords: Competitive electricity market, Economic dispatch, Genetic algorithm, Unit commitment

BackgroundObesity may alter tissue distribution and clearance of several drugs, especially lipophilic ones. Itraconazole, a lipophilic drug, has been recently introduced in a super-bioavailable formulation (SB-ITZ) for the treatment of dermatophytosis. Evidence regarding optimal dosing of SB-ITZ in obesity is lacking. A current experimental study was planned to analyze tissue concentrations of SB-ITZ at different doses in obese and non-obese rats. Materials and methodsThirty-six Wistar albino rats of either sex were divided into obese and non-obese rats equally. Further, rats in both categories were divided into three dosing groups. Group 1 received SB-ITZ 13 mg once daily in the morning, group 2 received SB-ITZ 13 mg in the morning and 6.5 mg in the evening, while Group 3 rats received SB-ITZ 13 mg twice daily, orally. Concentrations of SB-ITZ in the skin, serum, and fatty tissue were assessed in each group on days 7, 14, 21, and 28. Comparison of SB-ITZ concentrations in various tissues in obese and non-obese rats and inter-group comparison of tissue concentrations across the three dosing regimens was done at day 28 and expressed as Mean ± SD.36 Wistar rats were divided into obese and nonobese rats equally. ResultsAt day 28, skin concentrations of SB-ITZ were 5.36±1.1, 8.9±1.7 and 10.13±1.7 µg/g in Groups 1, 2, and 3, respectively, in non-obese rats, which was statistically significant (p<0.05) than skin concentration of obese rats (2.72±0.6, 4.2±0.7 and 4.66±0.5 µg/g) for the corresponding dosing groups respectively. Skin concentration of SB-ITZ was statistically significant for Groups 2 and 3 as compared to Group 1. Still, no statistically significant difference was noted between Groups 2 and 3 in non-obese and obese rats. Fatty tissue concentration of SB-ITZ was comparable in all 3 dosing regimens in non-obese and obese rats. But on the intergroup comparison, a statistically significant difference was observed for Groups 2 and 3 against Group 1 (p<0.05). Increasing the dose of SB-ITZ increased serum concentration. In non-obese rats, a statistically significant difference was noted between Group 2 (74.33±6.6 ng/ml) and Group 1 (52.5±9.9 ng/ml); p<0.01 and also in Group 3 (81.33±6.8 ng/ml) against Group 1; p<0.01. Group 3 achieved significantly higher concentration than the other two groups in obese rats (Group 3; 72±5.3, Group 2; 60.5±4.3, and Group 1; 45±7 ng/ml; p<0.01). ConclusionOverall, skin, fatty tissue, and serum concentrations of SB-ITZ were higher in non-obese rats compared to obese rats in all three dosing groups. Moreover, skin and fatty tissue concentrations were proportionately higher than serum in all the groups in non-obese and obese rats. Though the skin concentration of nonobese rats was significantly higher than obese rats, skin concentration in obese rats was within the minimum inhibitory concentration (MIC) range, demonstrating the efficacy of all dosing regimens.

Grid computing is a collection of distributed resources interconnected by networks to provide a unified virtual computing resource view to the user. Grid computing has one important responsibility of resource management and techniques to allow the user to make optimal use of the job completion time and achieving good throughput. It is a big deal to design the efficient scheduler and is implementation. In this paper, the constraint based job and resource scheduling algorithm has been proposed. The four constraints are taken into account for grouping the jobs, i.e. Resource memory, Job memory, Job MI and the fourth constraint L2 cache are considered. Our implementation is to reduce the processing time efficiently by adding the fourth constraint L2 cache of the resource and is allocated to the resource for parallel computing. The L2 cache is a part of computer's processor; it increases the performance of computer. It is smaller and extremely fast computer memory. The use of more constraint of the resource and job can increase the efficiency more. The work has been done in MATLAB using the parallel computing toolbox. All the constraints are calculated using different functions in MATLAB and are allocated to the resource based on it. The resource memory, Cache, job memory size and job MI are the key factors to group the jobs according to the available capability of the selected resource. The processing time is taken into account to analyze the feasibility of the algorithms.

The term 'open apex' is used to indicate the presence of an exceptionally wide root canal at the apex. Open apices occurs in immature teeth when root development ceases as a result of pulp necrosis. Trauma and caries are regarded as the main cause of open apices in immature anterior teeth. Successful root canal treatment occurs when overinstrumentation and overfilling are avoided and filling materials confined to the limits of the canal. Hence, accurate working length is essential for optimal healing. Open apices pose many difficulties to contemporary methods of canal length determination. A case report presents a consistent tactile method for working length determination in teeth with open apices.