The study aimed to evaluate Glucagon-Like Peptide-1 levels in Polycystic ovary syndrome (PCOS) infertile female with Diabetes Mellitus (DM) and compare the results with control group, also, to find the correlation for GLP-1 with Luteinizing hormone (LH), Follicle stimulating hormone (FSH) and LH/FSH ratio that may be used in prediction atherosclerosis in these patients. The study included nineteen women with age ranged (30-40) years and BMI ranged between (30-35) Kg/m 2. Subjects were divided into two groups: group (1) consist of (45) females as a healthy control and group (2) consist of (45) infertile females with PCOS and DM as complication. Fasting serum glucose was determined by using commercial kits (Biolabo SA-France); LH, FSH, prolactin were determined by ELISA, fasting serum insulin was determined by using ELISA kit (DRG-Germany). Insulin-resistance (IR) calculated by (HOMA-IR). FSH, LH, LH/FSH ratio and prolactin levels for all studied groups were measured. A highly significant elevation in prolactin, LH and LH/FSH ratio was found when G1 comparing with G2. While significant reduction seen in FSH levels in G2 comparing to G1. A high significant elevation in Fasting blood glucose,% HbA1C levels in patients group when comparing to healthy control. Results revealed a highly significant elevation in insulin, HOMA-IR and glucagon, while there are a significant reduction in GLP-1levels. There is significant positive correlation was found in GLP-1 levels with (FSH) in G1, while a significant negative correlation was observed in levels of GLP-1 and (FSH) inG2. A significant negative correlation was found in GLP-1 levels
Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.
Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreOne of the costliest problems facing the production of hydrocarbons in unconsolidated sandstone reservoirs is the production of sand once hydrocarbon production starts. The sanding start prediction model is very important to decide on sand control in the future, including whether or when sand control should be used. This research developed an easy-to-use Computer program to determine the beginning of sanding sites in the driven area. The model is based on estimating the critical pressure drop that occurs when sand is onset to produced. The outcomes have been drawn as a function of the free sand production with the critical flow rates for reservoir pressure decline. The results show that the pressure drawdown required to
... Show MoreThe field of structural optimization (optimal design) has grown rapidly over the past decades with many different optimization methods that could be used to produce a structure of minimum weight. This research deals with two aspects, in the first, a general numerical technique based on the finite element analysis and it suggests to investigate the preliminary behavior of metal stiffened plate under action of static load environment. The technique was included a finite element model of the structures using high- order isoparimetric plate elements to be used to create a certain models to obtain their optimum design. The models are characterized such that, each model is builded using different types of stiffener configuration. The second as
... Show MoreThe Hopfield network is one of the easiest types, and its architecture is such that each neuron in the network connects to the other, thus called a fully connected neural network. In addition, this type is considered auto-associative memory, because the network returns the pattern immediately upon recognition, this network has many limitations, including memory capacity, discrepancy, orthogonally between patterns, weight symmetry, and local minimum. This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of t
... Show MoreRisks are confronting the foundations of buildings and structures when exposed to earthquakes which leads to high displacements that may cause the failure of the structures. This research elaborates numerically the effect of the earthquake on the vertical and lateral displacement of footing resting on the soil. The thickness of the footing and depth of soil layer below the footing was taken as (0.5, 1.0, and 2.0 m) and (10, 20 and 40m), respectively. The stiffness ratio of soil to footing was also elaborated at 0.68, 0.8, 1.0, and 1.7. The results showed an increase in the verticle displacement of footing as the duration of the earthquake increases. The increase of soil layer thickness below the footing leads to a reduction in the vertical
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