The current study deals with the performance of constructed wetland (CW) incorporating a microbial fuel cell (MFC) for wastewater treatment and electricity generation. The whole unit is referred to as CW-MFC. This technique involves two treatments; the first is an aerobic treatment which occurs in the upper layer of the system (cathode section) and the second is anaerobic biological treatment in the lower layer of the system (anode section). Two types of electrode material were tested; stainless steel and graphite. Three configurations for electrodes arrangement CW-MFC were used. In the first unit of CW-MFC, the anode was graphite plate (GPa) and cathode was also graphite plate (GPc), in the second CW-MFC unit, the anode was stainless steel

In this research, we sought to identify the nature of the relationship between the exchange rate of the Chinese yuan and the value of Chinese exports, through the formulation of a standard model based on the model of common integration, and based on the data of the study and using the test "Angel-Granger" It reflects the relationship between the two research variables, through which the relationship between the RMB exchange rate and the value of Chinese exports was estimated during the period 1978-2017.

Six house-hold Abyssinian pumps distributed in different villages of Mansoura (Mans-I, Mans-II and Mans-III) and Talkha (Talk-I, Talk-II and Talk-III) cities, Egypt, have been selected for regular seasonal water quality assessment during 2017. Water samples have been collected within the mid-periods of four seasons Standard assessment tools were employed for the integrated water quality assessment including Water Quality Index (WQI) and ISO standard algal toxicity test. WQI displayed remarkable local and seasonal variations with excellent (≥ 90) and good (70 - 89) only recorded for water samples collected from Mans-I pump located in sparsely populated area and far 50 meters only from the eastern (Damietta) branch of Nile River. WQI of

The present research deals with the spatial variance analysis in Jwartadistrict and conducting a comparison on the spatial and seasonal changes of the vegetation cover between (2007-2013) in order to deduce the relationship between the vegetation density and the areas which are exposed to the risk of water erosion by using Plant Variation Index  NDVI) C (coefficient and by using Satellite images of Landsat satellite which are taken in 2/7/2007 and Satellite images of Landsat satellite taken in 11/1/ 2013, the programs of remote sensitivity and the Geographic Information Systems.

    The study reveals that there is a variance in the density of vegetation cover of the area under study betwee 2007 and 2013. Howev

The exchange rate is of great importance at the global and local levels alike, as this importance increases with the increasing rates of development of economic relations between countries of the world due to openness and integration into the global economy, expressed by the expansion of the volume of trade and financial relations between countries. The Central Bank of Iraq has set the need to stabilize this price as a goal to reduce inflation rates and reduce them to the internationally accepted rates by using the foreign currency sale window to achieve a balance between the forces of supply and demand for foreign currency and to preserve the value of the Iraqi dinar. The research concluded that the central bank was It has a maj

This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.