Date palm silver nanoparticles are a green synthesis method used as antibacterial agents. Today,
there is a considerable interest in it because it is safe, nontoxic, low costly and ecofriendly. Biofilm bacteria
existing in marketed local milk is at highly risk on population health and may be life-threatening as most
biofilm-forming bacteria are multidrug resistance. The goal of current study is to eradicate biofilm-forming
bacteria by alternative treatment green synthesis silver nanoparticles. The biofilm formation by bacterial
isolates was detected by Congo red method. The silver nanoparticles were prepared from date palm
(khestawy) fruit extract. The formed nanoparticles were characterized with UV-Vis

The δ-mixing of γ-transitions in 70As populated in the 32 70 70 33 Ge p n As (, ) γ reaction is calculated in the present work by using the a2-ratio methods. In one work we applied this method for two cases, the first one is for pure transition and the sacend one is for non pure transition, We take into account the experimental a2-coefficient for previous works and δ -values for one transition only.The results obtained are, in general, in a good agreement within associated errors, with those reported previously , the discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works.

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas

In this research, the theme for employing a simple and sensitive method is to employ a new Schiff base ligand (N’-(4- (dimethyl amino) benzylidene)-3, 5-dinitrobenzohydrazide) to estimate Ni (II) to form orange complex (N-(4-(dimethyl amino) benzylidene)-3, 5-dinitrobenzohydrazide nickel (II) chloride) in acid medium (hydrochloric acid), it gives an absorption peak at the wavelength 485 nm. The preferred conditions were studied to form the complex and obtain the highest absorbance including concentration of Schiff base ligand, the best medium for complex formation, effects of addition sequence on complex formation, the effect of temperature on the absorbance of the complex formed, and the setting time of the formed complex. The obtained r

Activated carbon derived from Ficus Binjamina agro-waste synthesized by pyro carbonic acid microwave method and treated with silicon oxide (SiO2) was used to enhance the adsorption capability of the malachite green (MG) dye. Three factors of concentration of dye, time of mixing, and the amount of activated carbon with four levels were used to investigate their effect on the MG removal efficiency. The results show that 0.4 g/L dosage, 80 mg/L dye concentration, and 40 min adsorption duration were found as an optimum conditions for 99.13% removal efficiency. The results also reveal that Freundlich isotherm and the pseudo-second-order kinetic models were the best models to describe the equilibrium adsorption data.

Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak