In this paper, two types of iron oxide nanomaterial (Fe3O4) and nanocomposite (T-Fe3O4) were created from the bio-waste mass of tangerine peel. These two materials were utilized for adsorption tests to remove cefixime (CFX) from an aqueous solution. Before the adsorption application, both adsorbents have been characterized by various characterizations such as XRD, FTIR, VSM, TEM, and FESEM. The mesoporous nano-crystalline structure of Fe3O4 and T-Fe3O4 nanocomposite with less than 100-nm diameter is confirmed. The adsorption of the obtained adsorbents was evaluated for CFX removal by adjusting several operation parameters to optimize the removal. The optimal conditions for CFX removal were found to be an initial concentration of 40 and 50 m

       In 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

The objective of this study was to investigate the release profile of different fat and water soluble bases using diazepam as a model drug , and then to develop  a satisfactory formula with a rapid release of diazepam from suppository bases .The study was conducted using theobroma oil ,glycerol-gelatin and glycerol-PEG1540 bases using conventional mold method for preparation .while the later base was utilized to incorporate diazepam ( buffered solution ) in a hollow type suppositories. The results indicated that all types of bases can be utilized to formulate diazepam as  rectal suppositories with acceptable disintegration time ( 12, 10, 6, and 6min.), respectively . While 100% of the  released drug had been shown differen

Many diseases can produce cardiac overload, of these disease hypertension, valve disease congenital anomaly in addition to many other disease. One of the most common diseases causing left ventricle overload is hypertension. A long term hypertension can cause myocardium hypertrophy leading to changes in the cardiac contractility and reduced efficiency. The investigations were carried out using conventional echocardiography techniques in addition to the tissue Doppler imaging (TDI) from which many noninvasive measurements can be readily obtained. The study has involved the effect of hypertension on the myocardium stiffness index through the measurement of early diastolic filling (E) and the early velocity of lateral mitral annulus (E

Some microorganisms can produce nanocellulose, which is known as bacterial nanocellulose (BNC); the most active bacterial producer is acetic acid bacteria (AAB), which is a gram-negative, motile and obligate aerobic belongs to the family Acetobacteraceae. Bacterial nanocellulose has excellent attention in medical (surgical domain), industrial and pharmaceutical fields because of its flexible properties, characteristics and advantages. So, in this study, the AAB (5AC) isolate was isolated from apple vinegar. The production of BNC was performed by using a natural medium called palm dates liquid medium, the produced bacterial Cellulose was purified by using the sodium hydroxide method; it was observed that the wet weight of the BNC was a

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The genus Larra Fabricius, 1793 (Hymenoptera: Crabronidae) is recorded for the first time from Vietnam. Three species and two subspecies belonging to this genus as follows: L. amplipennis (F. Smith, 1873); L. carbonaria (F. Smith, 1858); L. fenchihuensis Tsuneki, 1967; L. polita polita (F. Smith, 1858) and L. polita luzonensis Rohwer, 1919 are presented. Keys to both sexes of the three species and two subspecies reported here are provided.

This study focuses on how tax administrations in Iraq use Artificial Intelligence (AI) techniques to monitor tax evasion for individuals and companies to achieve Tax Compliance (TC). AI was measured through four dimensions: Advanced Data Analytics Techniques (ADAT), Explainable AI (EAI), Machine learning (ML), and Robotic Process Automation (RPA). At the same time, TC was measured through registration, accounting, and tax payment stages. We relied on the questionnaire form to measure the variables. A sample of employees in the General Tax Authority in Iraq was selected, and a questionnaire was distributed to 132 people. The results indicated that the dimensions of AI affect achieving TC at all stages. This study provides evidence of using A