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Azetidin-2-one analogues are reported to exhibit various pharmacological activities like cholesterol absorption inhibitory activity, human tryptase, thrombin and chymase inhibitory activity, vasopressin V1a antagonist activity, antidiabetic, anti-inflammatory, antiparkinsonian and anti-HIV activity in addition to antimicrobial. 1-6 In the present study, Isoniazid (INH), the established antitubercular drug was selected as the lead for the design and development of antitubercular agents with minimal toxic effects. A novel series of amino azetidinones were designed from corresponding azetidin-2-ones using various in silico methods. Docking studies were performed at Mtb enoyl acp reductase (4DRE) and the derivatives exhibited best docking scores were prepared from corresponding azetidin-2-ones by treating with various molecules containing amino groups in the presence of TEA. Azetidin-2-ones in turn were obtained from a series of INH Schiff bases by reaction with chloro acetyl chloride. Structures of the newly synthesized compounds were assigned on the basis of elemental analysis, IR, 1 H NMR, 13 CNMR and mass spectral studies. The newly synthesized compounds were screened for their in vitro antitubercular activity using Alamar blue assay method and the hepatotoxicity was determined by MTT assay method using chang liver cells. AAZ1V, the amino azetidinone obtained from N-[3-chloro-2-(4-chlorophenyl)-4-oxoazetidin-1-yl] pyridine-4-carboxamide (AZ1V) by combining with 4-amino 1, 2, 4-triazole produced significant antitubercular activity. The percentage viability produced by AAZ1V against Chang liver cells for hepatotoxicity was better than the percentage viability produced by INH.

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The estimation of the photovoltaic (PV) cell/module model parameters could lead to accomplish a diagnostic tool and to estimate several factors which affect the health state of a PV generator. In this context, it is crucial to look for an extraction technique which performs this evaluation precisely and quickly. Due to the nonlinear and implicit nature of the PV cell/module, significant computational effort is required to obtain all the parameters; therefore, in this context different metaheuristic algorithms are proposed. For the identification of the meaningful parameters of PV cell/module models, illuminated current-voltage (I–V) curves, under real conditions of PV cells temperature and incident irradiance, are employed. Considering several PV cell/module models, the goodness of the proposed algorithms is analyzed by means of statistical errors, convergence speed, and unknown parameters precision. Then these algorithms are tested and validated using a daily set of measured I–V curves, specifically for each one both the whole set of measured data and a reduced set around the maximum power point are used.