The linear segment with parabolic blend (LSPB) trajectory deviates from the specified waypoints. It is restricted to that the acceleration must be sufficiently high. In this work, it is proposed to engage modified LSPB trajectory with particle swarm optimization (PSO) so as to create through points on the trajectory. The assumption of normal LSPB method that parabolic part is centered in time around waypoints is replaced by proposed coefficients for calculating the time duration of the linear part. These coefficients are functions of velocities between through points. The velocities are obtained by PSO so as to force the LSPB trajectory passing exactly through the specified path points. Also, relations for velocity correction and exact v

In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

Wastewater discharge containing organic dyes may pose a hazard to the environment, which necessitates that dye removal must occur prior to wastewater release into water bodies. Herein, copper oxide nanoparticles (CuO NPs) were prepared by a green precipitation method to enable decolorization of a cationic dye (methyl violet; MV) from aqueous media. Complementary tools were employed to characterize the CuO NPs adsorbent: spectroscopy (FTIR and UV-VIS), microscopy (FESEM and TEM), XRD, BET surface area analysis, and point of zero charge (pHPZC) via potentiometry. The FTIR bands at 722, 663, 569, and 465 cm−1 correspond to the vibrational modes of CuO NPs, along with the optical absorbance band at 275 nm that supports the formation of Cu

Wastewater discharge containing organic dyes may pose a hazard to the environment, which necessitates that dye removal must occur prior to wastewater release into water bodies. Herein, copper oxide nanoparticles (CuO NPs) were prepared by a green precipitation method to enable decolorization of a cationic dye (methyl violet; MV) from aqueous media. Complementary tools were employed to characterize the CuO NPs adsorbent: spectroscopy (FTIR and UV-VIS), microscopy (FESEM and TEM), XRD, BET surface area analysis, and point of zero charge (pHPZC) via potentiometry. The FTIR bands at 722, 663, 569, and 465 cm1 correspond to the vibrational modes of CuO NPs, along with the optical absorbance band at 275 nm that supports the formation of CuO NPs.

Oil from Brassca campestris (local variety) was extracted with hexane using Soxhlet. The extracted oil was characterized and its antimicrobial activity was determined as well. The content of extracted oil was 40% with 0.5% of volatile oil .Oil was immiscible with polar solvent such as ethanol, acetone and water, while it was easily miscible with chloroform due to its hydrophobicity. The result of organoleptic tests revealed that the oil is clear yellow in color and odorless with acceptable taste. The oil was stable at 4 -25 C? for a month. Refractive index (RI) of oil was 1.4723 with density of 0.914, [both at 4-25 C?]. Boiling point 386 C?. Infra red spectroscopy (IR) indicated the presence of different chemical groups (C=C

Titanium dioxide nanorods have been prepared by sol-gel template
method. The structural and surface morphology of the TiO₂ nanorods was
investigated by X-ray diffraction (XRD) and atomic force microscopy
(AFM), it was found that the nanorods produced were anatase TiO₂ phase.
The photocatalytic activity of the TiO2 nanorods was evaluated by the
photo degradation of methyl orange (MO). The relatively higher
degradation efficiency for MO (D%=78.2) was obtained after 6h of exposed
to UV irradiation.