Background: Obesity typically results from a variety of causes and factors which contribute, genetics included, and style of living choices, and described as excessive body fat accumulation of body fat lead to excessive body, is a chronic disorder that combines pathogenic environmental and genetic factors. So, the current study objective was to investigate the of the FTO gene rs9939609 polymorphism and the obesity risk. Explaining the relationship between fat mass and obesity-associated gene (FTO) rs9939609 polymorphism and obesity in adults. Methods: Identify research exploring the association between the obesity risk and the variation polymorphisms of FTO gene rs9939609. We combined the modified odds ratios (OR) as total groups and subgroups. A stable and random effect processes with standard mean division was used to evaluate the outcomes of this study in dominant and recessive groups. The purpose of the current meta-analysis was to explain the relationship of FTO rs9939609 and obesity. Results: This meta-analysis comprised 8 eligible studies including 4109 participants, comprising of 2441 cases and 1668 control measures. Meta-analysis outcomes exposed that a significant difference (P < 0.05) of the FTO genotypes appeared between the obese and the control groups. The FTO rs9939609 polymorphisms were associated significantly with the increased risk of obesity in five genotypes of adults: the AA + AT vs. TT genotypes, OR = 1.54, 95% CI = 1.34–1.77, p = 0.00001; the AA vs. AT + TT genotypes, OR = 1.40, 95% CI = 1.16–1.69, p = 0.0004; the AA vs. TT genotypes, OR = 1.79, 95% CI = 1.45–2.21, p = 0.00001; the AT vs. TT genotypes, OR = 1.47, 95% CI = 1.26–1.72, p = 0.00001; and the A vs. T alleles, OR = 1.38, 95% CI = 1.26–1.53, p = 0.00001). Conclusion: This meta-analysis reveals that the FTO gene polymorphism rs9939609 is correlated with the increasing obesity risk and A allele is also considered as a risk factor for the obesity susceptibility.
As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec
... Show MoreThe rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which
... Show MoreThe aim of this study is to achieve the best distinguishing function of the variables which have common characteristics to distinguish between the groups in order to identify the situation of the governorates that suffer from the problem of deprivation. This allows the parties concerned and the regulatory authorities to intervene to take corrective measures. The main indicators of the deprivation index included (education, health, infrastructure, housing, protection) were based on 2010 data available in the Central Bureau of Statistics
This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB
... Show MoreAt the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat
... Show MoreSentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreGreen areas are an essential component of city planning, as they serve as an outlet for them to spend their free time, in addition to the environmental role that these green areas play in improving the city’s climate by purifying the air and beautifying the city. The study’s problem is summarized in identifying the appropriateness of the current spatial distribution of green areas in the city of Najaf with the current population densities and the pattern in which green areas are distributed using GIS and knowing the per capita share of those green areas in the city, the research assumes that the inconsistency of spaces between regions Green and residential neighbourhoods need to c
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
... Show MoreResearch studies show that urban green spaces promote physical activity, the health of urban residents, and psychological well-being. Taking the community park in Duhok city as the research object, the spatial service area in terms of accessibility of to the Community Park under the mode of pedestrian transportation is analyzed by using the network analysis service area function of the geographic information system (GIS). The results show that under the walking mode in the research area, Parks are concentrated in the north and south of the city, but community parks are few in disadvantaged neighborhoods. In addition, there is a significant disparity between the number of community parks and the number of communities. Only 11 communities
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