In this research, aflatoxins were produced, extracted, isolated, and purified in order to optimize the storage conditions of feed. Using a preparative thin layer chromatography (TLC) method, with commercially available plates of 1.5 to 2.0 mm, B1 aflatoxin was isolated from the feed samples of whole wheat, maize, and crushed rice, and the procedure was repeated four times. A purity value of 99 % for B1 aflatoxin was achieved and tested using spectrophotometric and chromatographic methods. As solvents, acetone:water (85:15l) was used for aflatoxin extraction from the feed sample, whereas methanol: water (50: 50) was used for trichothecenes extraction. The primary findings of this research indicate that B1 aflatoxin reac

Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost

In this study, zinc ferrite magnetic nanoparticles (ZnFe₂O₄, ZFO MNPs) were employed as a sorbent for the removal of oil spill from water surfaces. ZFO MNPs were synthesized via a sol-gel process and characterized by Fourier transform infrared spectroscopy (FTIR) and X-ray powder diffraction (XRD). Both the apparent density and magnetic force were determined. ZFO MNPs presented a considerable magnetic force (40.22 mN) and an adequate density (0.5287 g/cm³), which are important for the magnetic separation and flotation. Four oil samples (gasoline engine oil, crude oil, used motor oil and diesel engine oil) were used to investigate the gravimetric oil removal capability of ZFO MNPs. The oil sorption capacit

Recently, increasing material prices coupled with more acute environmental awareness and the implementation of regulation has driven a strong movement toward the adoption of sustainable construction technology. In the pavement industry, using low temperature asphalt mixes and recycled concrete aggregate are viewed as effective engineering solutions to address the challenges posed by climate change and sustainable development. However, to date, no research has investigated these two factors simultaneously for pavement material. This paper reports on initial work which attempts to address this shortcoming. At first, a novel treatment method is used to improve the quality of recycled concrete coarse aggregates. Thereafter, the treated recycled

       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

In this paper, we investigate some methods to solve one of the multi-criteria machine scheduling problems. The discussed problem is the total completion time and the total earliness jobs  To solve this problem, some heuristic methods are proposed which provided good results. The Branch and Bound (BAB) method is applied with new suggested upper and lower bounds to solve the discussed problem, which produced exact results for  in a reasonable time.