One of the goals of adding adjuvants to agricultural spray solutions is to enhance the droplet size characteristics of this spray. Droplet size, in turn, has an influence in the deposited spray quality, in addition to the drift and losses of spray to off-target places. The aim of this research was to evaluate the effect of adding adjuvants to two types of water from different sources on the droplet size characteristics. Two types of adjuvants were employed in the tests: the active substance content of the first adjuvant was a 50% aqueous solution of sodium salt of alkylbenzenesulfonic acid—10% (HY), whereas the second was from rapeseed oil (natural origin)—85% (OL). Both adjuvants were tested in two concentrations: the first was

The consumption of fossil fuels has caused many challenges, including environmental and climate damage, global warming, and rising energy costs, which has prompted seeking to substitute other alternative sources. The current study explored the microwave pyrolysis of Albizia branches to assess its potential to produce all forms of fuel (solid, liquid, gas), time savings, and effective thermal heat transfer. The impact of the critical parameters on the quantity and quality of the biofuel generation, including time, power levels, biomass weight, and particle size, were investigated. The results revealed that the best bio-oil production was 76% at a power level of 450 W and 20 g of biomass. Additionally, low power levels led to enhanced

Infertility is one of the types of diseases that occur in the reproductive system. Obesity is a state that can be occurred due to excessive fats, the progression in obesity stage results in a change in adipose tissue and the development of chronic inflammation, endocrine glands disorders and women’s reproductive system, and also increase the infection with covid-19. The study aimed to investigate the effect of the obesity, lipid-profile, and IL-6 on hormones-dysregulation in infertile-women with COVID-19 complications. The current study included 70 samples: 50 infertility-women-with-covid-19-infected, 20 healthy-women/control, the ages of both patients and healthy subjects were selected within the range 18-34 years. Levels of FBS, LH,

     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

OBJECTIVE: To determine the preferred specialties of graduated medical doctors working in Basra, and determine the factors behind their preferences. METHODS: The study was conducted in 38 primary health care centres and seven hospitals in Basra from January-June 2014. A cross-sectional study was adopted with the use of a self-administered questionnaire form. Two hundred ninety six graduated doctors were agreed to participate. Chisquare test and logistic regression were used to test the association between deciding a future speciality and influencing factors. RESULTS: The most preferred specialties were radiology and ultrasound, gynaecology and obstetrics, surgery, internal medicine, dermatology and paediatrics. Clinical specialties were sta

Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce