Parameter extraction of solar photovoltaic models using queuing search optimization and differential evolution[Formula presented]

Given the photovoltaic (PV) model's multi-model and nonlinear properties, extracting its parameters is a difficult problem to solve. Furthermore, because of the features of the problem, the algorithms that are used to solve it are subject to becoming stuck in local optima. Nonetheless, proper estimation of the parameters is essential due to the large impact they have on the performance of the PV system in terms of current and energy production. Moreover, the majority of the previously proposed algorithms have satisfactory results for determining PV model parameters. However, for precision and robustness, they generally use a lot of computational resources, such as the quantity of fitness assessments. For alleviating the previous problems, in this paper, an improved queuing search optimization (QSO) algorithm dependent on the differential evolution (DE) technique and bound-constraint amendment procedure, which is called IQSODE, has been presented to efficiently extract the PV parameter values for various PV models. The DE algorithm is applied to each solution generated by the QSO algorithm in order to increase population diversity. IQSODE is tested against other state-of-the-art algorithms. The practical and statistical findings show that IQSODE outperforms other methods in extracting parameters from PV models such as single diode, double diode, and photovoltaic module models. Also, the performance of the proposed algorithm is assessed utilizing two practical manufacturer's datasheets (TFST40 and MCSM55). Statistically, the IQSODE outperforms other state-of-the-art algorithms in terms of convergence speed, reliability, and accuracy. Thus, the presented method is deemed to be a viable solution for PV model parameter extraction

Lipoxygenase inhibitors from the latex of Calotropis Procera

A radical-scavenging, guided phytochemical study of the latex of Calotropis Procera afforded five lignans (1–5), including a new one (4). The structural determination was accomplished using 1D- and 2D-NMR, high-resolution electrospray ionization mass spectrometry (HRESIMS), and correlation with known compounds. Among the isolated compounds, acylated lignans (3–5) showed stronger antioxidant activity than non-acylated derivatives (1,2). Anti-inflammatory activity was evaluated by determining the inhibitory potential against 5- and 15-lipoxygenase enzymes. The highest anti-inflammatory activity was observed in compound 4, with IC50s values of 7.6 µM and 2.7 µM against 5-LOX and 15-LOX, respectively.No Full Tex