IntroductionEthiopia is the second most populous country in Africa. Ethiopia received most of its COVID-19 vaccines through donations. The Oxford AstraZeneca vaccine is the first to be donated to Ethiopia by the COVAX facility. Healthcare workers were the priority population that received the Oxford AstraZeneca COVID-19 vaccine. However, there was no nationwide study on the safety of the vaccine in Ethiopia. This study aimed to measure the prevalence and predictors of self-reported side effects of the Oxford AstraZeneca vaccine.Materials and methodsThe study employed a cross-sectional design. A sample of healthcare workers who took Oxford AstraZeneca COVID-19 vaccine was drawn from four regions of Ethiopia; namely, Amhara, Oromia, Somali, and Southwest. Data were collected on sociodemographic characteristics, medical anamnesis, COVID-19 related anamnesis, and COVID-19 vaccine anamnesis via telephone interview. Descriptive and inferential analyses were done. The software, IBM SPSS Statistics v21.0, was used for analyses of data.ResultsOut of 384 people, 346 responded (response rate: 90.1%). Female accounted for 34.1% of the respondents. The mean age of the respondents was 31.0 years (Standard Deviation (SD) = 7.4). Nurses accounted for 43.7% of the respondents. The prevalence of at least one local- and systemic-side effect was 50.6 and 44.5%, respectively. The most frequent local- and systemic- side effect were injection site pain and headache, respectively. Both types of side effects mostly subsided in the first 3 days. A third of healthcare workers with side effects took at least one medication. Paracetamol followed by diclofenac sodium were taken by healthcare workers to overcome side effects. There was no independent predictor of local side effect. After controlling for age and chronic diseases, the odds of healthcare workers with COVID-19 like symptoms to experience systemic side effects was 1.38 (Confidence Interval (CI): 1.04–1.82) times more than that of healthcare workers without COVID-19 like symptoms.ConclusionsThe prevalence of local- and systemic-side effects of the Oxford AstraZeneca COVID-19 vaccine was modest. As the symptoms were mostly common in the first 3 days, it is preferable to monitor healthcare workers at least in the first 3 days following the administration of the vaccine.

Nowadays ensure the performance of heat exchanger is one of the toughest roles in industries. In this work focused on improve the performance of shell and tube heat exchangers by reducing the pressure drop as well as raising the overall heat transfer. This work considered as a different nanoparticles such as Aluminium oxide (Al2O3), Silicon dioxide (SiO2), Titanium oxide (TiO2) and Zirconium dioxide (ZrO2) to form a nanofluids. This nanofluids possesses high thermal conductivity by using of this increase the heat transfer rate in shell and tube heat exchanger. The selected nanofluids are compared to base fluid based on the thermophysical properties as well as heat transfer characteristics. All the heat transfer characteristics are improved by applying of nanofluids particularly higher results are obtained with using of TiO2 and Al2O3 compared to SiO2 and ZrO2. Mixing of nanoparticles increased in terms of volume percentage it will be increases the all Heat transfer characteristics as well as performance of the heat exchanger.

Stainless steel is a material which has high corrosive resistance and oxidation resistance at high temperature with the combination of chromium, nickel, and niobium as a primary constituent. This material which is difficult to machine with complex shape is taken by using wire cut electric discharge machining. Wire electrical discharge machining is a nontraditional process widely taken for cutting and machining for complex shapes. This review paper involves wire cut EDM optimization parameters. Pulse interval, pulse duration, wire feed, voltage, and mean current are the operational parameters. The Taguchi orthogonal array method, analysis of variance (ANOVA), and grey relation analysis (GRA) methods are taken for different kinds of machining various kinds of materials, and different kinds of result with best material removal rate (MRR) and surface roughness (SR) are analyzed. This work suggests the most influencing process parameters and best optimization method for various steel materials.

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Aluminium alloy is the most favourable material based on the various properties and economic factors. Always there are so many researches going on based on the enhancement of the material properties with various combinations and the various materials mixing rate depending upon the availability. These researches were focused on the augmentations of the properties, and then the corresponding properties can be used in the various applications depending upon the results. In this study, the AA6066 aluminium alloy composites were created with the magnesium oxide and coal ash with a variety of grouping. The specimens were named as AAMgOCA 1 to AAMgOCA 6 with respect to the volume concentration composition. Then, the composites were tested to identify the impact on various strengths such as yield strength, ultimate tensile strength, shear strength, and flexural strength. These strengths were compared with the two conditions of the composites such as annealed and heat-treated conditions. AAMgOCA 3 has the greatest results in heat-treated condition when compared with the annealed condition.