The process for preparing activated carbon (AC) made from tea residue was described in this paper. Investigated were the physicochemical characteristics and adsorption efficiency of the produced AC. Activation with potassium hydroxide (KOH) and carbonization at 350 °C are the two key steps in the manufacturing of AC. The activated carbon was used to adsorb Tetracycline (TC). Different parameters were studied at room temperature to show their effects on the adsorption efficiency of TC. These parameters are the initial concentration of adsorbate TC, solution acidity pH, time of adsorption, and adsorbent dosage. The prepared active carbon was characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (
... Show MoreIn this work, the photocatalytic degradation of indigo carmine (IC) using zinc oxide suspension was studied. The effect of influential parameters such as initial indigo carmine concentration and catalyst loading were studied with the effect of Vis irradiation in the presence of reused ZnO was also investigated. The increased in initial dye concentration decreased the photodegradation and the increased catalyst loading increased the degradation percentage and the reused-ZnO exhibits lower photocatalytic activity than the ZnO catalyst. It has been found that the photocatalytic degradation of indigo carmine obeyed the pseudo-first-order kinetic reaction in presence of zinc oxide. This was found from plotting the relationship between ln
... Show MoreIntroduction: COVID-19 vaccine have been indicated to successfully decrease the hazard for symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection furthermore associated hospitalisations. Objective: To study the immune response among different types of SARS-CoV-2 vaccines. Methods: This study includes 100 vaccinated individuals (43 Sinopharm, 30 AstraZeneca and 27 Pfizer) with one or two doses from different health centres in Baghdad. During the period from April 2021 to the end of May 2021, SARS-CoV-2 IgG and SARS-CoV-2 IgM levels were detected using AFIAS-6 device depending on FIA (Fluorescence Immunoassay) technique. Results: 93% of the cases were positive for IgG levels, and negative in 7% case
... Show MoreTo enhance interfacial bonding between carbon fibers and epoxy matrix, the carbon fibers have been modified with multiwall carbon nanotubes (MWCNTs) using the dip- coating technique. FT-IR spectrum of the MWCNTs shows a peak at 1640 cm−1 corresponding to the stretching mode of the C=C double bond which forms the framework of the carbon nanotube sidewall. The broad peak at 3430 cm−1 is due to O–H stretching vibration of hydroxyl groups and the peak at 1712 cm−1 corresponds to the carboxylic (C=O) group attached to the carbon fiber. The peaks at 2927 cm−1 and 2862 cm−1 ar
Listeria monocytogenes represents a critical foodborne pathogen causing listeriosis, a severe infection with mortality rates of 20- 30%. This comprehensive review integrates cutting-edge research from 2015-2024 with Iraqi epidemiological data to address significant knowledge gaps in regional surveillance and global comparative analysis. Recent discoveries include five novel Listeria species in 2021, revolutionary whole genome sequencing (WGS) surveillance systems, and advanced understanding of RNA-mediated regulation. Iraqi prevalence data reveals concerning patterns with rates ranging from 3.5% to 93.8% across different sample types, substantially higher than global averages. Critically, Iraqi isolates demonstrate alarming antibiotic resis
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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