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

A new compound  2-(4-methoxyphcnyl)-5-(4-aminophenyl)-1,3,4-

oxadiazole (VI) was prepared by intramol ecular condensation reaction followed  by elimination  of some simple  moieties such  as IhO  and HCI by using  POCI3 with acid hydrazide. A series of new Shiffs­

bases 2-(4-methoxyphenyl)-5-[4(4:alkoxybenzoyloxy) benzylidene amino phenyl] I,3,4-oxadia:t.ole (VII].was synthesized from treatment

of oxadiazole derivative [VI] with an appropriate  aromatic aldehyde

(IU). Struct\lfe of the resulting products have been ascertaim:d by their melting pointS, elemental analysis ( some of them) and spectral data.

This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed

      In this paper, we introduce and study the notation of approximaitly quasi-primary submodules of a unitary left -module  over a commutative ring  with identity. This concept is a generalization of prime and primary submodules, where a proper submodule  of an -module  is called an approximaitly quasi-primary (for short App-qp) submodule of , if , for , , implies that either  or , for some . Many basic properties, examples and characterizations of this concept are introduced.

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