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bsj-8476
Visible-Light-driven Photocatalytic Properties of Copper(I) Oxide (Cu2O) and Its Graphene-based Nanocomposites
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In this study, an improved process was proposed for the synthesis of structure-controlled Cu2O nanoparticles, using a simplified wet chemical method at room temperature. A chemical solution route was established to synthesize Cu2O crystals with various sizes and morphologies. The structure, morphology, and optical properties of Cu2O nanoparticles were analyzed by X-ray diffraction, SEM (scanning electron microscope), and UV-Vis spectroscopy. By adjusting the aqueous mixture solutions of NaOH and NH2OH•HCl, the synthesis of Cu2O crystals with different morphology and size could be realized. Strangely, it was found that the change in the ratio of de-ionized water and NaOH aqueous solution led to the synthesis of Cu2O crystals of different sizes, while the morphology of Cu2O crystals was not affected. The synthesized Cu2O crystal samples were used as photocatalysts for methyl orange (MO) dye decomposition, as a model molecule, to evaluate the photocatalytic activities. However, under 200 watts of a visible light source, there are four samples with and without graphene-based nanocomposite of Cu2O NPs. The results showed that, compared with roughly spherical, irregular but thick plates, brick and small granule spheres shaped Cu2O nanoparticles provided better activity. The Cu2O sample with irregular but thick platelet-like shapes, having an average particle size of 0.53 µm, exhibited excellent photocatalytic activity (99.08% degradation). In addition, by reducing the size of Cu2O particles and preparing their graphene composition, one can fabricate a sample (Cu2-Cu2Gr) with the highest efficiency which has significantly better photocatalytic activity in comparison to the others. This work represents an innovative strategy for pre-the-case production of nanomaterials with shapes and sizes, that is, Cu2O crystals, with excellent photocatalytic activity through compositing with graphene

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Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
Heuristic Initialization And Similarity Integration Based Model for Improving Extractive Multi-Document Summarization
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Publication Date
Sun Dec 21 2025
Journal Name
International Journal On Humanities And Social Sciences
Motivation-based Human Needs and their Disclosure Prompts in Chris Cleave’s Little Bee
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The present work folds two qualitative objectives; the first focuses on investigating the multiplicity of motivation-based human needs in Little Bee. The second objective involves examining the linguistic forms adopted to disclose such needs. Consequently, the researchers are to adapt eclectically Alderfer's Existence, Relatedness, and Growth Theory (1969) and Langacker’s theory of Domains (1987) together with his Active Zone Operation (1991). Such a study helps to embody the connectivity between the social and psychological aspects, and the way these two aspects are disclosed using particular linguistic The study has concluded that Bee needed Alderfer’s basic human needs: existence, relatedness, and growth. Besides, satisfying

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Publication Date
Fri May 04 2018
Journal Name
Wireless Personal Communications
IFRS: An Indexed Face Recognition System Based on Face Recognition and RFID Technologies
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Composites Science
Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Fri May 20 2005
Journal Name
Thesis
Extraction and Description of Urease Enzyme Produced from Staphylococcus saprophyticus and study of its effect on kidney and bladder of white mice
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Extraction and Description of Urease Enzyme Produced from Staphylococcus saprophyticus and study of its effect on kidney and bladder of white mice

Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Stomatology
Preferences of treatments and materials used in the management of exposed pulps: a web-based questionnaire study
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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Optimization of Inventory Inflation Budget Based on Spare-parts and Miscellaneous Costs of a Typical Automobile Industry
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Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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