This study aimed to obtain an isolate of a mold that has well characteristic for production of citric acid from raw materials available locally by solid-state fermentation and determination of the optimum conditions for production .Fourteen mold isolates producing acid were obtained from different sources, involved decayed fruits and soils. These isolates were subjected to initial qualitative screening followed by secondary quantitative screening In secondary screening a method combined between the submerged fermentation and solid-state fermentation was followed using a piece of sponge saturated by nutrients required for growth and production of acid. It was found that the isolate of A7 was the highest producer for citric acid tha

This paper presents the first data for bremsstrahlung buildup factor (BBUF) produced by the complete absorption of Y-91 beta particles in different materials via the Monte Carlo simulation method. The bremsstrahlung buildup factors were computed for different thicknesses of water, concrete, aluminum, tin and lead. A single relation between the bremsstrahlung buildup factor BBUF with both the atomic number Z and thickness X of the shielding material has been suggested.

By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

A comparative study was done on the adsorption of methyl orange dye (MO) using non-activated and activated corn leaves with hydrochloric acid as an adsorbent material. Scanning electron microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) were utilized to specify the properties of adsorbent material. The effect of several variables (pH, initial dye concentration, temperature, amount of adsorbent and contact time) on the removal efficiency was studied and the results indicated that the adsorption efficiency increases with the increase in the concentration of dye, adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature for both the treated and untreated corn leav

The extract of fig fruit has shown significant medical usefulness in various fields. The entrance of nanotechnology into the field of medicinal and pharmacology has shown remarkable advantages. Plants contain diverse molecules thatcan reduce metals, and provide a safe, eco-friendly approach for synthesizing nanoparticles. Iron oxide nanoparticles (IONPs) have been reported to possess an antimicrobial effect against some strains of bacteria and moulds. We have aimed to synthesize IONPs from fig fruit extract and investigate the influence of fig extract and IONPs in wound healing of mice. UV-Vis spectroscopy, X-ray diffraction (XRD), and field emission scanning electron microscopy were used to characterize the IONPs that were produced

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati