A simple and novel membraneless paper-based microfluidic fuel cell was presented in this study. The occurrence of laminar flow was employed to ensure no mixing of the fuel and oxidant fluids along the bath of reaction. The acidic wastewater was used as a fuel. It was an air-breathing cell, so air and tab water were used as oxidants. Both the fuel and tab water flowed continuously under gravity. Whatman filter paper was used for preparation of the fuel cell channel and two carbon fibre electrodes were used and firmed on the edges of the cell. The performance of the cell was examined over three consecutive days. The results indicated that the present cell has the potential to generate electric power, but an extensive study is required to harv

Prison and imprisonment  
And their impact on the strengthening of power
In the Qur'anic perspective

    Ten species of whiteflies (Hemiptera, Aleyrodidae) representing six genera were studied from a collection from different localities in the middle of Iraq. These species are Acaudaleyrodes rachipora (Singh, 1931); Bemisia afer  (Priesner and Hosny,1934); Bemisia tabaci (Gennadius, 1889); Dialeurodes citri (Ashmead,1885); Dialeurodes kirkaldy (Kotinsky, 1907); Neomaskellia andropogonis Corbett, 1926;  Siphoninus phillyreae (Haliday, 1835); Trialeurodes ricini (Misra, 1924); Trialeurodes vapovariorum (Westwood,1856) and Trialeurodes irakeensis (Al-Malo and Abdul-Rassoul, 2000). Notes are given on their localities, date of c

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

 The gas sensing properties of undoped Co₃O₄ and doped with Y₂O₃ nanostructures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for the prepared thin films. XRD analysis showed that all films were polycrystalline, of a cubic structure with crystallite size of (12.6) nm for cobalt oxide and (12.3) nm for the Co₃O₄:6% Y₂O₃. The SEM analysis of thin films indicated that all films undoped Co₃O₄ and doped possessed a nanosphere-like structure.

The sensi

Microbial Desalination Cell (MDC) is capable of desalinating seawater, producing electrical power and treating wastewater. Previously, chemical cathodes were used, which were application restrictions due to operational expenses are quite high, low levels of long-term viability and high toxicity. A pure oxygen cathode was using, external resistance 50 and 150 k Ω were studied with two concentrations of NaCl in the desalination chamber 15-25 g/L which represents the concentration of brackish water and sea water. The highest energy productivity was obtained, which amounted to 44 and 46 mW/m³, and the maximum limit for desalination of saline water was (31% and 26%) for each of 25 g / L and 15 g / L, respectively, when using an ex

In this study, the use of non-thermal plasma theory to remove toxic gases emitted from a vehicle was experimentally investigated. A non-thermal plasma reactor was constructed in the form of a cylindrical tube made of Pyrex glass. Two stainless steel rods were placed inside the tube to generate electric discharge and plasma condition, by connecting with a high voltage power supply (up to 40 kV). The reactor was used to remove the contaminants of a 1.25-liter 4-cylinder engine at ambient conditions. Several tests have been carried out for a ranging speed from 750 to 4,500 rpm of the engine and varying voltages from 0 to 32 kV. The gases entering the reactor were examined by a gas analyzer and the gases concentration ratio

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c