In-vitro biological activities of the free new H4L ( indole-7-thiocarbohydrazone) ligand and its Ni(II), Pd(II) , Pt(II), Cu(II), Ag(I), Zn(II) and Cd(II) complexes are screened against two cancerous cell lines, that revealed significant activity only for [Cu2Cl2(H4L)2(PPh3)2] after 72 h treatment by the highest tested concentrations. The Copper(I) complex was characterized by X-ray Crystallography and the NMR spectra, whereas it has been confirmed to have momentous cytotoxicity against ovarian, breast cancerous cell lines (Caov-3, MCF-7). The apoptosis-inducing properties of the Cu(I) complex have been investigated through fluorescence microscopy visualization, DNA fragmentation analysis and propidium iodide flow cytometry.
The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
KE Sharquie, AA Al-Nuaimy, FA Al-Shimary, Saudi medical journal, 2005 - Cited by 20
A new four series of 2,2′-([1,1′- phenyl or biphenyl]-4,4′-diylbis(azanediyl)) bis(N′-((E)-1-(4-alkoxyphenyl) ethylidene) acetohydrazide) [V-XI]a,b and 1,1′-(2,2′-([1,1′- phenyl or biphenyl]-4,4′-diyl bis(azanediyl)) bis- (acetyl)) bis(3-(4-ethoxyphenyl)-1H-pyrazole-4-carbalde hyde) [XII-XVIII]a,b have been synthesized by varying terminal lateral alkoxy chain length (n = 1–3, 5–8), central linkage group (phenyl or biphenyl) and induced pyrazole heterocyclic ring in the main chain. The last two series were synthesized by the cyclization of substituted acetophenone hydrazones with Vilsmeier–Haack reagent (DMF/POCl3) to produce 4-formylpyrazole derivatives. The chemical structures of the synthesized compounds were examine
... Show MoreMany authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai
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