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 microsc

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 (

Background Type two diabetes (T2DM) is characterized by insufficient insulin production and secretion. Additionally, the body develops insulin resistance which affects 90–95% of diabetics. Complex cytokines, receptors, genetic pathways, and the immune system are involved in T2DM. Interleukin-18 (IL-18) is one of the inflammatory cytokines associated with Type 2 diabetes. Environmental and genetic variables, including genetic polymorphisms, can increase T2DM risk and its consequences. Single nucleotide gene polymorphisms (SNPs) are important risk factors for diabetes that can be used to find the disease early and treat it better. Objective This study aimed to determine the levels of IL-18 in the serum of Iraqi patients with Type 2 diabetes

Objectives: During the COVID-19 pandemic, dentists have had to work under stressful conditions due to the nature of their work. Personal protection equipment (PPE) has become mandatory for work in the dentistry field. This study aimed to examine dentists' practices and attitudes regarding the use of PPE and the associated drawbacks and cost implications during the pandemic.

Methods: A questionnaire-based survey was used and was divided into five sections dedicated to collect demographic variables and to examine the dentists' practices, attitudes toward PPE, drawbacks, and cost of using PPE. Mann-Whitney U and Kruskal-Wallis tests were used to compare different sections of

Iraqi EFL college instructors, who supervise the teaching practice of EFL student teachers, commonly experience the inefficient teaching performance of prospective teachers. This inefficiency is usually due to their inability to make connections between the practical experience and the theoretical knowledge of TEFL. One of the reasons behind this inability may be the employment of traditional ways of training and instructing student teachers. Moreover, it is usually noticed that many Iraqi EFL student teachers have a negative attitude toward the teaching profession. They explicitly state that they would join the teaching force only if they fail to work in any other field.

Abstract

Objective : the aim of the study is to evaluate the effectiveness of nurse’s practices and knowledge program toward care of patient with cardiopulmonary bypass .Methodology: A pre-experimental design (one group pretest- posttest design) was used to carry out this study in three governmental hospitals in Baghdad ( Iraqi Centre for Heart Diseases , Ibn – Albitar Centre for Cardiac Surgery and Ibn – Alnafees Centre for Cardiothoracic and Vascular Surgery ) for the period from 15th of May 2022 into 20th of April 2023.The construction and development of the program and instruments had carry out by the researcher to measured the purposes of the study , twenty two nurses was purposively assigned for the study group . The

Schiff bases are versatile compounds synthesized from the condensation of primary amino compounds with aldehydes or ketones. The high thermal of many Schiff base and their complexes were useful attributes for their application as catalysts in reactions involving at high temperatures. This thermal behavior of Schiff bases and their complexes was evaluated by TGA/DTG and DTA curves with 10 mass losses related to dehydration and decomposition. This review summarizes the developments in the last decade for thermal analysis of Schiff bases. Therefore, synthesis of Schiff bases and their complexes are reviewe

ABSTRACT : This research involves the synthesis of five to seven heterocyclic compounds starting with Schiff’s bases which derived from oxime as a starting material. 1.3-oxazepine derivatives were prepared from adding different anhydrides to the Schiff bases, tetrazole and thiazolidinone derivatives synthesized from add sodium azide and thioglycolic acid to the same Schiff’s bases as a five members ring. Pyrimidine derivatives were prepared after the reaction of the azomethine group with acetyl chloride and then urea and thiourea to synthesis on derivatives contain the six members ring. Another step included identified and confirmed these compounds by FT- IR, 1HNMR, TLC and 13CNMR finally, step included the assay of biological activity

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod