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Investigation Desulfurization Method Using Air and Zinc Oxide/Activated Carbon Composite
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In present work examined the oxidation desulfurization in batch system for model fuels with 2250 ppm sulfur content using air as the oxidant and ZnO/AC composite prepared by thermal co-precipitation method. Different factors were studied such as composite loading 1, 1.5 and 2.5 g, temperature 25 oC, 30 oC and 40 oC and reaction time 30, 45 and 60 minutes. The optimum condition is obtained by using Tauguchi experiential design for oxidation desulfurization of model fuel. the highest percent sulfur removal is about 33 at optimum conditions. The kinetic and effect of internal mass transfer were studied for oxidation desulfurization of model fuel, also an empirical kinetic model was calculated for model fuels at optimum condition, the apparent activation energy was found to be 16.724 kJ/mol.

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Publication Date
Tue Sep 01 2020
Journal Name
Heliyon
Extraction, optical properties, and aging studies of natural pigments of various flower plants
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Publication Date
Thu Jun 20 2024
Journal Name
Ingénierie Des Systèmes D Information
Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
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Publication Date
Fri Nov 01 2013
Journal Name
Romanian Biotechnological Letters
Elicitation of pseudomonas aeruginosa with live and dead microbial cells enhances phenazine production
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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
Sun Dec 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison between the effects of Aloe vera and chlorhexidine on clinical periodontal parameters
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Background: Periodontal diseases are one of the major dental pathologies that affect human populations worldwide at high prevalence rates The term periodontal disease usually refers only to plaque related inflammatory disease of the dental supporting tissues. Mouth rinses which act as an anti-plaque agents mostly used as adjuncts to oral hygiene. Aims of the study: To Estimate and compare the effects of Aloe vera relative to chlorhexidine on the clinical periodontal parameters (plaque index, gingival index, bleeding on probing). Material and method: A total of 44 subjects with plaque-induced gingivitis, baseline of data were collected for (PLI, GI, and BOP) and underwent oral hygiene instruction, scaling and polishing, then divided into:

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Magnetism And Magnetic Materials
Structural analysis, magnetic and electrical properties of samarium substituted lithium–nickel mixed ferrites
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Publication Date
Mon Aug 01 2016
Journal Name
The Astrophysical Journal
MATTER IN THE BEAM: WEAK LENSING, SUBSTRUCTURES, AND THE TEMPERATURE OF DARK MATTER
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ABSTRACT<p>Warm dark matter (WDM) models offer an attractive alternative to the current cold dark matter (CDM) cosmological model. We present a novel method to differentiate between WDM and CDM cosmologies, namely, using weak lensing; this provides a unique probe as it is sensitive to all of the “matter in the beam,” not just dark matter haloes and the galaxies that reside in them, but also the diffuse material between haloes. We compare the weak lensing maps of CDM clusters to those in a WDM model corresponding to a thermally produced 0.5 keV dark matter particle. Our analysis clearly shows that the weak lensing magnification, convergence, and shear distributions can be used to distinguish</p> ... Show More
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Publication Date
Tue Feb 04 2025
Journal Name
Journal Of Communicable Diseases
Correlation between MicroRNA-155 Expression and Viral Load in Severe COVID-19 Patients
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Background: The SARS-CoV-2 virus causes COVID-19, a respiratory syndrome. It causes inflammation and damages several organs in the body. miRNAs play a role in regulating the infection resulting from SARS-CoV-2. MicroRNA-155, a kind of microRNA linked to viral defences, can affect the immune responses during COVID-19. Objectives: Examination of the involvement of microRNA-155 in the development and severity of COVID-19, as well as finding the correlation between microRNA-155 and viral load (copies/mL) in severe cases of the disease. Materials and Method: A case-control research study was performed between October 2022 and June 2023. It included a cohort of 120 hospitalised individuals with severe cases of COVID-19, together with 115 individu

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Publication Date
Wed May 27 2020
Journal Name
Acta Biologica Szegediensis
Phytochemical analysis, cytotoxicity and antioxidant activity of cuckoo pint (Arum maculatum) leaf extract
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Arum maculatum is traditionally used for the control of many diseases and illnesses such as kidney pain, liver injury, hemorrhoids. However, the detailed biomedical knowledge about this species is still lacking. This study reports on the bioactive components and the possible mechanisms underlying the antioxidant, anti-inflammatory and cytotoxic activity of A. maculatum leaf extract. Gas chromatography-mass spectrometry (GC-MS) was used for phytochemical analysis. Assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide ) (MTT) was used to determine the cytotoxicity in the murine cell line L20B upon exposure to different extract concentrations for 24 h. Enzyme-linked immunosorbent assay (ELISA) was used to detect pro-in

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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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