The research aims to apply the activities of the green value chain as one of the modern administrative techniques that economic units resort to develop solutions to the pollution problems that occur due to the activity of economic units and their products that may cause damage to the environment as well as the waste of natural resources and to identify the production of environmentally friendly products and reduce the costs of environmental failure of both types Internal and external that may be borne by economic units such as taxes, fines and compensation due to nonobservance of environmental requirements and the preservation of human health and protection of the environment. To achieve the goal of the research, the researchers rel

This study concerns the removal of a trihydrate antibiotic (Amoxicillin) from synthetically contaminated water by adsorption on modified bentonite. The bentonite was modified using hexadecyl trimethyl ammonium bromide (HTAB), which turned it from a hydrophilic to a hydrophobic material. The effects of different parameters were studied in batch experiments. These parameters were contact time, solution pH, agitation speed, initial concentration (C0) of the contaminant, and adsorbent dosage. Maximum removal of amoxicillin (93 %) was achieved at contact time = 240 min, pH = 10, agitation speed = 200 rpm, initial concentration = 30 ppm, and adsorbent dosage = 3 g bentonite per 1L of pollutant solution. The characterization of the adsorbent, modi

In this study, the aqueous extract of (Typha domingensis Pers.) pollen grain (qurraid) to know its ability to manufacture silver nanoparticles. Qurraid is a semi-solid yellow food substance, sold in Basra markets and eaten by the local population. It is made from the pollen of the T.  domingensis Pers. plant after being pressed and treated with water vapor. The Gas chromatography–mass spectrometry (GC-MS) reaction was done to identify the active compounds of qurraid aqueous extract. The ability of the aqueous extract of qurraid to manufacture silver nanoparticles was tested, and the construction of silver nanoparticles was inferred by the reaction mixture's color, which ranged from yellow to dark brown. The synthesi

The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of