In this research, a mathematical model of tumor treatment by radiotherapy is studied and a new modification for the model is proposed as well as introducing the check for the suggested modification. Also the stability of the modified model is analyzed in the last section.

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

One of the most important problems in the oil production process and when its continuous flow, is emulsified oil (w/o emulsion), which in turn causes many problems, from the production line to the extended pipelines that are then transported to the oil refining process. It was observed that the nanomaterial (SiO₂) supported the separation process by adding it to the emulsion sample and showed a high separation rate with the demulsifiers (RB6000) and (sebamax) where the percentage of separation was greater than (90 and 80 )%  respectively, and less than that when dealing with (Sodium dodecyl sulfate and Diethylene glycol), the percentage of separation was (60% and 50%) respectively.

   The high proportion

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

Zinc, Copper, Selenium, Magnesium, Manganese, Chromium, Iron, Nickel, Cobalt, Vanadium and Germanium were determined by atomic absorption spectrophotometer (AAS) in blood serum of patients with rheumatoid arthritis, (30) patients (14male and 16female) with age range (37-60) years compared with normal tensive control. The analysis of results showed that the mean value of concentration (Magnesium,  Manganese and Nickel) were significantly higher in patients with rheumatoid arthritis compared to that of healthy, while the mean levels of serum (Zinc, Copper, Selenium, Chromium, Iron, Cobalt and Germanium) were significantly lower than controls. There were no significant changes in overall mean concentration of serum Vanadium in patients

S Khalifa E, N Adil A, AS Mazin M…, 2008

In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr₂O₃) with Titanium dioxide (TiO₂) nanofibers (Cr₂O₃-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO₂ exhibits nanofibers (TNFs) shape struct