A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu

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

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu

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.

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 current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-