The presence of antibiotic residues such as ciprofloxacin (CIPR) in an aqueous environment is dangerous when their concentrations exceed the allowable. Therefore, eliminating these residues from the wastewater becomes an essential issue to prevent their harm. In this work, the potential of efficient adsorption of ciprofloxacin antibiotics was studied using eco-friendly ZSM-5 nanocrystals‑carbon composite (NZC). An inexpensive effective natural binder made of the sucrose-citric acid mixture was used for preparing NZC. The characterization methods revealed the successful preparation of NZC with a favorable surface area of 103.739 m2/g, and unique morphology and functional groups. Investigating the ability of NZC for adsorbing CIPR antibioti

The effluent quality improvement being discharged from wastewater treatment plants is essential to maintain an environment and healthy water resources. This study was carried out to evaluate the possibility of intermittent slow sand filtration as a promising tertiary treatment method for the sequencing batch reactor (SBR) effluent. Laboratory scale slow sand filter (SSF) of 1.5 UC and 0.1 m/h filtration rate, was used to study the process performance. It was found that SSF IS very efficient in oxidizing organic matter with COD removal efficiency up to 95%, also it is capable of removing considerable amounts of phosphate with 76% and turbidity with 87% removal efficiencies. Slow sand filter efficiently reduced the mass of suspended

Zinc oxide thin films were deposited by chemical spray pyrolysis onto glass substrates which are held at a temperature of 673 K. Some structural, electrical, optical and gas sensing properties of films were studied. The resistance of ZnO thin film exhibits a change of magnitude as the ambient gas is cycled from air to oxygen and nitrogen dioxide

Trip generation is the first phase in the travel forecasting process. It involves the estimation of the
total number of trips entering or leaving a parcel of land per time period (usually on a daily basis);
as a function of the socioeconomic, locational, and land-use characteristics of the parcel.
The objective of this study is to develop statistical models to predict trips production volumes for a
proper target year. Non-motorized trips are considered in the modeling process. Traditional method
to forecast the trip generation volume according to trip rate, based on family type is proposed in
this study. Families are classified by three characteristics of population social class, income, and
number of vehicle ownersh

In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.

In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.

The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat