The subject of this research involves studying adsorption to remove hexavalent chromium Cr(VI) from aqueous solutions. Adsorption process on bentonite clay as adsorbent was used in the Cr(VI) concentration range (10-100) ppm at different temperatures (298, 303, 308 and 313)K, for different periods of time. The adsorption isotherms were obtained by obeying Langmuir and Freundlich adsorption isotherm with R2 (0.9921-0.9060) and (0.994-0.9998), respectively. The thermodynamic parameters were calculated by using the adsorption process at four different temperatures the values of ?H, ?G and ?S was [(+6.582 ? +6.547) kJ.mol-1, (-284.560 ? -343.070) kJ.mol-1 and (+0.977 ? +1.117) kJ.K-1.mol-1] respectively. This data indicates the spontaneous sorp

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

       The present study was performed to spotlight the potential role of soil bacteria in the Al-Rumaila oil field as a bioindicator of heavy metals pollution. For this purpose, nine soil samples were collected from different sites, with 20cm depth, to assess the pollution status depending on the total and available concentrations of heavy metals.  The result indicates pollution of the studied soils with the following metals: Cd, Cu, Fe, Zn, and Pb. The mean of total concentration for all studied metals was higher than the allowed maximum limit based on the international limit:(3.394, 3.994, 39.993, 8844.979,150.372, and 103.347 µg/g), respectively. While measuring the total Metal concentration is important in determining the de

       The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Background: Large amounts of oily wastewater and its derivatives are discharged annually from several industries to the environment. Objective: The present study aims to investigate the ability to remove oil content and turbidity from real oily wastewater discharged from the wet oil's unit (West Qurna 1-Crude Oil Location/ Basra-Iraq) by using an innovated electrocoagulation reactor containing concentric aluminum tubes in a monopolar mode. Methods: The influences of the operational variables (current density (1.77-7.07 mA/cm2) and electrolysis time (10-40 min)) were studied using response surface methodology (RSM) and Minitab-17 statistical program. The agitation speed was taken as 200 rpm. Energy and electrodes consumption had been studi

Water-based drilling fluids (WBDFs) are the industry-preferred medium for drilling reactive shale formations, yet they remain susceptible to shale swelling, fluid invasion, and cuttings dispersion—all of which compromise wellbore stability. Although oil-based fluids (OBFs) provide effective shale inhibition, their high cost and adverse environmental profile limit their use. Nanoparticles (NPs) derived from waste feedstocks offer a low-cost, environmentally responsible alternative for enhancing WBDF performance, but no prior study has simultaneously evaluated both waste-derived SiO2 and Al2O2 NPs within a single WBDF system. This study synthesised SiO2 NPs from Halfaya bentonite clay waste and Al2O2 NPs from recycled aluminium scrap, char

In this paper, various aspects of smart grids are described. These aspects include the components of smart grids, the detailed functions of the smart energy meters within the smart grids and their effects on increasing the awareness, the advantages and disadvantages of smart grids, and the requirements of utilizing smart grids. To put some light on the difference between smart grids and traditional utility grids, some aspects of the traditional utility grids are covered in this paper as well.