The survey and checklist of invasive species of the insects in some different localities of Iraq are revised; 24 invasive species were documented until December 2018 during the current investigations. The species distributions, common names and synonyms are given.

The current investigation included all of exotic species in Iraq, which are not collected during this study.

Background: Insulin resistance is present in 50% or more of patients with primary hypothyroidism. Metformin can decrease TSH levels in these patients by a complex matter, this can be of great help in clinical practice.

Objective: This study was designed to evaluate the effect of metformin in reducing TSH levels in patients with primary hypothyroidism.

Methods: Hundred patients with primary hypothyroidism, 82 females, 18 males were included in this study, everyone was followed up for two months after adding metformin 850 mg twice daily in addition to thyroxin.

Results: 36 patients (36%) have a normal baseline TSH and no change after 2 months, 64 pa

There is substantial data supporting the importance of both endogenous and exogenous estrogen in maintaining reproductive health and preventing chronic disease, androgens in women's health are rarely discussed. This is one of the first researches to investigate correlates of blood testosterone concentrations in women with osteopenia, in anticipation of the growing interest in the role of androgens in women's health. A 65 volunteer women were enrolled in the current study, they were divided into two groups, 35 postmenopausal women with osteopenia were in the first group, and the second group contained 30 postmenopausal women without osteopenia as a control. Blood samples were collected from all participants and analyzed for testosterone l

The main objective of this study is to describe the preparation of topographic maps using the Surfer software. A total of 159 regularly distributed Ground Control Points (GCPs) were collected with the use of the Differential Global Positioning System (DGPS). Seven methods (Contour Map, Post Map, 3D Surface Map, 3D Wireframe Maps, Grid Vector-1 Map, Color Relief Map, and Shaded Relief Maps) at the Surfer environment were used to prepare the topographic maps at the Mukhtar Village near the Al-Fallujah City. Contour lines with other features were superimposed on the DEM layer, which refers to the topography of the terrain inside this study area. The accuracy of the database's results was estimated, essential maps were given, and the re

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Activated carbon (AC) is a highly important adsorbent material, as it is a solid form of pure carbon that boasts a porous structure and a large surface area, making it effective for capturing pollutants. Thanks to its exceptional features, AC is widely used for purifying water that is contaminated with odors and removing dyes in a cost-effective manner. A variety of carbonic materials have been employed to prepare AC, and this study aimed to evaluate the suitability of utilizing waste mango and avocado seeds for this purpose, followed by testing their efficacy in removing dye from aqueous solutions. The results indicate that using waste mango and avocado as AC is technically feasible, achieving dye removal percentages of 98% and 93%,

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen