Various industrial applications include the dyeing of textiles, paper, leather, and food products, as well as the cosmetics industry. Physic-chemical methods are required to breakdown dyes because they are known to be harmful and persistent in the environment. Many companies' treated effluents contain small amounts of dyes. When it comes to removing dye from wastewater, adsorption has verified to be aneconomical alternative to more traditional treatment procedures. It's important to degrade color impurities in industrial effluents since they constitute a serious health and environmental concern. One way that's been tried is using clay minerals as an adsorbent. Using adsorption for removing

Thin films of cadmium sulphoselenide (CdSSe) have been prepared by a thermal evaporation method on glass substrate, and with pressure of 4x10-5 mbar. The optical constants such as (refractive index n, dielectric constant ?i,r and Extinction coefficient ?) of the deposition films were obtained from the analysis of the experimental recorded transmittance spectral data. The optical band gap of (CdSSe) films is calculate from (?h?)2 vs. photon energy curve. CdSSe films have a direct energy gap, and the values of the energy gap were found to increase when increasing annealing temperature. The band gap of the films varies from 1.68 – 2.39 eV.

The adsorption isotherms and kinetic uptakes of CO₂ were measured. Adsorption isotherms were measured at two temperatures 309 K and 333 K and over a pressure range of 1 to 7 bar. Experimental data of CO₂ adsorption isotherms were modeled using Langmuir, Freundlich and Temkin. Based on coefficient of correlation it was found that Langmuir isotherm model was well suited with the experimental data of CO₂ adsorption isotherms.  In addition, Adsorption kinetic of CO₂ mixture with N₂ containing 10 % by volume CO₂ and 90 % by volume N₂ were determined in a temperature 36 °C and under the atmospheric pressure .When the flow rate was increased from

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

The development of technology used in computerized programs is considered on of the most important topics that is responsible for creating tools that can be used in the business environment, the audit profession is one of those professions that received this development. In order for this profession to be more effective, there must be a tool based on sound (correct) scientific basis that can be based upon to enhance the quality of auditing. The research also aims to propose a computerized program to plan the auditing process according to the methods appropriate to the working environment in the audit offices and companies in Iraq. The computerized program was applied to the research sample and the hypothesis of the research has been prov

This study focused on extracting the outer membrane nanovesicles (OMVs) from Escherichia coli BE2 (EC- OMVs) by ultracentrifugation, and the yield was 2.3mg/ml. This was followed by purification with gel filtration chromatography using Sephadex G-150, which was 2mg/ml. The morphology and size of purified EC-OMVs were confirmed by transmission electron microscopy (TEM) at 40-200 nm. The nature of functional groups in the vesicle vesicle was determined by Fourier transforms infrared spectroscopy (FT-IR) analysis. The antitumor activity of EC-OMVs was conducted in vitro by MTT assay in human ovarian (OV33) cancer cell line at 24,48 and 96hrs. The cytotoxicity test showed high susceptibility to the vesicles in ovarian compared to normal

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm