The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.

The rapid spread of the COVID-19 coronavirus in 2019 infected many people, primarily affecting the respiratory system. Both COVID-19 and type 2 diabetes have been associated with numerous risks that have become life-threatening. The study studied the link between galectin levels and some clinical characteristics in Iraqis with type 2 diabetes and COVID-19 against those without diabetes. The study included 120 patients and healthy men. Three groups were formed for this study depending on the initial mutant cell line: 80 samples of individuals with type 2 diabetes, aged 40–60 years, with and without COVID-19, were included in each of the first and second groups. The control group consisted of 40 research participants who were matched for ag

The effluent quality improvement being discharged from wastewater treatment plants is essential to maintain an environment and healthy water resources. This study was carried out to evaluate the possibility of intermittent slow sand filtration as a promising tertiary treatment method for the sequencing batch reactor (SBR) effluent. Laboratory scale slow sand filter (SSF) of 1.5 UC and 0.1 m/h filtration rate, was used to study the process performance. It was found that SSF IS very efficient in oxidizing organic matter with COD removal efficiency up to 95%, also it is capable of removing considerable amounts of phosphate with 76% and turbidity with 87% removal efficiencies. Slow sand filter efficiently reduced the mass of suspended

Anastatica Hierochuntica L. Used As an Alternative of Conjugated Estrogen (Premarin) in Rabbit Females

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf