In this study, SnO2 nanoparticles were prepared from cost-low tin chloride (SnCl2.2H2O) and ethanol by adding ammonia solution by the sol-gel method, which is one of the lowest-cost and simplest techniques. The SnO2 nanoparticles were dried in a drying oven at a temperature of 70°C for 7 hours. After that, it burned in an oven at a temperature of 200°C for 24 hours. The structure, material, morphological, and optical properties of the synthesized SnO2 in nanoparticle sizes are studied utilizing X-ray diffraction. The Scherrer expression was used to compute nanoparticle sizes according to X-ray diffraction, and the results needed to be scrutinized more closely. The micro-strain indicates the broadening of diffraction peaks for nanoparticles that are not ideal crystals. The extra broadening of the diffraction peak may lead to a miscalculation of the nanoparticle size. We use the Williamson-Hall method to directly compute and discuss the particle size and micro-strain of SnO2 nanoparticles and compare them with results obtained using the Scherrer method. In conclusion, the straight line has been derived due to Williamson–Hall methods demonstrating the nanoparticles' uniformity.
One hundred and eighty five urine samples were collected eight isolates (4.3%) were obtained and diagnosed as Staphylococcus aureus. Among 8 isolates, 5 (62.5%) S. aureus isolates were found to be enterotoxigenic, most of isolates produced at least two types of Staphylococcal enterotoxins (SEs). The production of enterotoxins in the presence or absence of Thymol extracts (aqueous and alcoholic) were estimated using a reversed passive latex agglutination (SET-RPLA) kit. The extracts reduced enterotoxin production compared with the control. Enterotoxin inhibition was observed for enterotoxin C production at minimal inhibitory concentrations (MIC) at 400 µg/ml, whereas production of enterotoxins A, B, and
... Show MoreBackground: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, an
... Show MoreThe study involved the removal of acidity from free fatty acid via the esterification reaction of oleic acid with ethanol. The reaction was done in a batch reactor using commercial 13X zeolite as a catalyst. The effects of temperatures (40 to 70 °C) and reaction time (up to 120 minutes) were studied using 6:1 mole ratio of pure ethanol to oleic acid and 5 wt. % of the catalyst. The results showed that acid removed increased with increasing temperature and reaction time. Also, the acidity removal rises sharply during the first reaction period and then changes slightly afterward. The highest acidity removal value was 67 % recorded at 110 minutes and 70 °C. An apparent homogeneous reversible reaction kinetic model has been proposed a
... Show MoreBackground: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, and seven
... Show MoreSmear zone is usually formed around the prefabricated vertical drains (PVD’s) due to mandrel driving. The geotechnical properties of the soil in this zone exhibit significant changes that affect the performance of the PVD’s. The most relevant property in this respect is the coefficient of permeability. So far, no serious attention is paid to investigate the effects of shearing under large shear strains on the geotechnical properties of the soft soil in Fao region. In this study, an extensive laboratory testing program was conducted to assess the characteristics of the smear zone with an emphasis on the permeability coefficient of Fao soft soil. The results show that the permeability of the smear zone is about 70% of
... Show MoreThis paper describes a research effort that aims of developing solar models for housing suitable for the Arabian region since the Arabian Peninsula is excelled with very high levels of solar radiation.
The current paper is focused on achieving energy efficiency through utilizing solar energy and conserving energy. This task can be accomplished by implementation the major elements related to energy efficiency in housing design , such as embark on an optimum photovoltaic system orientation to maximize seize solar energy and produce solar electricity. All the precautions were taken to minimizing the consumption of solar energy for providing the suitable air-condition to the inhibitor of the solar house in addition to use of energy effici
The research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.
Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo
Abstract:
The phenomenon of financial failure is one of the phenomena that requires special attention and in-depth study due to its significant impact on various parties, whether they are internal or external and those who benefit from financial performance reports. With the increase in cases of bankruptcy and default facing companies and banks, interest has increased in understanding the reasons that led to this financial failure. This growing interest should be a reason to develop models and analytical methods that help in the early detection of this increasing phenomenon in recent year . The research examines the use of
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