The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injectio

 The objective of this study is to evaluate plasma levels of total Sialic acid TSA and Lipid –associated Sialic acid LSA as a marker of Rheumatoid Arthritis AR. Plasma Sialic acid is known as a parameter of inflammation. In the present study, in order to explore the potential role of sialic acid in arthritis rheumatoid, plasma sialic acid levels, plasma LSA and total protein in patients with arthritis rheumatoid were measured. A total 40 patients were compared with 40 healthy control subjects. Plasma TSA, LSA and TP level were determined spectrophotometrically in plasma samples. Plasma Sialic acid levels were significantly increased in RA (88.48±14.15 mg/dl, P<0.05) and LSA level were significantly increased in RA (26.3

Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

ABSTRACT Background: chronic periodontitis and rheumatoid arthritis are widely prevalent diseases and are characterized by tissue destruction due to chronic inflammation. Recently, there is growing evidence that the two diseases share many pathological features the aims of the study To determine the periodontal health status in patient have chronic periodontitis with rheumatoid arthritis and compare it with those having chronic periodontitis without Rheumatoid arthritis and determine the serum levels of interleukin -17(IL-17), tumor necrosis factor- alpha (TNF-α ) in both groups and compare with the control group (subject samples neither have periodontitis nor arthritis ) and correlate these immunological markers with the periodontal p

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

Thrust blocks and restraint joints are the two most popular methods of counteracting the thrust force that generated at pipe fittings (bends, Tee, wye, reducers, dead ends, etc…). Both systems perform the same function, which is to prevent the joints from separating from the pipes. The aim of the study is to review previous studies and scientific theories related to the study and design of thrust blocks and restraint joints to study the behavior of both systems under thrust force and to study the factors and variables that affect the behavior of these systems. The behavior of both systems must be studied because they cannot be abandoned, as each system has conditions whose use is more feasible, scientific, and economic