The 3D electro-Fenton technique is, due to its high efficiency, one of the technologies suggested to eliminate organic pollutants in wastewater. The type of particle electrode used in the 3D electro-Fenton process is one of the most crucial variables because of its effect on the formation of reactive species and the source of iron ions. The electrolytic cell in the current study consisted of graphite as an anode, carbon fiber (CF) modified with graphene as a cathode, and iron foam particles as a third electrode. A response surface methodology (RSM) approach was used to optimize the 3D electro-Fenton process. The RSM results revealed that the quadratic model has a high R2 of 99.05 %. At 4 g L-1 iron foam particles, time of 5 h, and 1 g of graphene, the maximum efficiency of phenol removal of 92.58 % and chemical oxygen demand (COD) of 89.33 % were achieved with 32.976 kWh kg-1 phenol of consumed power. Based on the analysis of variance (ANOVA) results, the time has the highest impact on phenol removal efficiency, followed by iron foam and graphene dosage. In the present study, the 3D electro-Fenton technique with iron foam partials and carbon fiber modified with graphene was detected as a great choice for removing phenol from aqueous solutions due to its high efficiency, formation of highly reactive species, with excellent iron ions source electrode.
The aim of the research is to shed light on identifying the extent of the university professor's competencies and their roles in managing and training participants in e-training workshops as a pedagogical point view. The research sample consisted of a group of (30) university professors (lecturers) in the training workshops, in scientific,humanitarian and social disciplines, including (12) a university professor (holding a trainer certificate), , the research methodology is descriptive, and the community is a group of trained participants. (115) participated in (40) e-training workshops organized by the Center for Continuing Education at the University of Baghdad (and the selection of workshops within the researcher's specialization in the
... Show MoreIn this study a new antiseptic was formulated and tested to match the effectiveness against microorganisms. The formulation consisted of Povidone - Iodine (PVP-I) (10%), H2O2 (3%) and Aloe Vera gel (pure). Different ratios of these materials were prepared within the acceptable range of pH for an antiseptic (3-6). The prepared samples were tested. The In Vitro test was performed by using four bacteria, two were Gram-Positive (Staphylococcus aureus and Bacillus cereus) and two were Gram-Negative (Escherichia coli and Pseudomonas aeruginosa). The new antiseptic showed 100% killing rate for E. coli, Ps. aeruginosa and S. aureus and 96.4667% killing rate for B. cereus. When the new antiseptic was compared with two common
... Show MoreIntroduction: Carrier-based gutta-percha is an effective method of root canal obturation creating a 3-dimensional filling; however, retrieval of the plastic carrier is relatively difficult, particularly with smaller sizes. The purpose of this study was to develop composite carriers consisting of polyethylene (PE), hydroxyapatite (HA), and strontium oxide (SrO) for carrier-based root canal obturation. Methods: Composite fibers of HA, PE, and SrO were fabricated in the shape of a carrier for delivering gutta-percha (GP) using a melt-extrusion process. The fibers were characterized using infrared spectroscopy and the thermal properties determined using differential scanning calorimetry. The elastic modulus and tensile strength tests were dete
... Show Moreتناولنا في هذه الدراسة التأكيد على تطوير المناهج الدراسية بأتجاه تنمية قيم التسامح والتعايش السلمي ، لان ثقافة التسامح باتت من الضرورات الملحة التي يفرضها الواقع الراهن لمواجهة العنف المجتمعي ، مما يوجب الحرص على ترسيخ القيم الانسانية ، لان التسامح من الصفات التي تحبها النفوس وتنجذب اليها القلوب .
والقيم الاخلاقية والسلوكية كالتسامح وغيرها ، من الامور الرئيسية لعمليتي التربية والتعليم في المدارس وال
... Show MorePurpose: The purpose of the study is to compare and evaluate Earnings Management in Tunisia and Iraq. Theoretical framework: Earnings Management is an important topic that has been studied by a significant number of researchers, as well as those who are interested in the accounting profession. Earnings Management has gotten a lot of attention from academics, professionals, and other interested parties in recent years (e.g. Kliestik et al., 2020; Rahman et al., 2021; Gamra &Ellouze, 2021) Design/methodology/approach: The sample includes ten banks listed on the Bourse of Tunisia and Iraq Stock Exchanges for the year 2017. We have used a model of Kothari et al., (2005) as a tool to measure Earnings Management in both mark
... Show MoreThe paper aims to build a model that supports organizational sustainability by analyzing the correlations and revealing the impact between the two main variables (entrepreneurial leadership) with its dimensions of proactive outlook, risk, and creativity (Van Zyl & Mathur-Helm, 2007), and (organizational sustainability) with its economic, environmental, and societal dimensions (Hansmann et al., 2012). As well as identifying the level of awareness and informing managers in the General Company for the Automotive and Equipment Industry, of the theoretical implications and performance, and its vital importance to society and the surrounding ecological environment, and drawing attention to that and improving performance, and indicatin
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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