Two prevalent neurodevelopment disorders in children are attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The fifth version of the Diagnostic and Statistical Manual of Mental Disorders describes autism as a condition marked by limitations in social communication as well as restricted, repetitive behavior patterns. While impulsivity, hyperactivity, and lack of concentration are signs of attention deficit hyperactivity disorder. Boys experience it more frequently than girls do. This study sought for possible factors that put children at risk for autism and attention deficit hyperactivity disorder, and it investigated the association between neurodevelopment disorders in children and parental risk factor in Iraqi population. This was a cross sectional, comparative study applied in The National Center for Autism/Medical City Complex from January to April 2022.In which120 child withneuro development disorders and 120 controls participated. The data collected from the questionnaires was analyzed using SPSS 25. Independent T-test and Chi-Square test were carried out for the bivariate analysis of the data. Among the tested variables four parent-related factors were significantly (P-value < 0.05) associated with neurodevelopment disorders in children: Family history of psychiatric illness, smoking of any parent, pregnancy and labor complications, used progesterone during pregnancy. In addition to these significant parent-related risk factors, paternal age at conception time were significantly (P-value < 0.05) associated with neurodevelopment disorders of children. Based on this case control study, mothers with pregnancy & labor complications, paternal age at conception, smoking of any parent,mothers used progesterone during pregnancy and family history of psychiatric illness, had higher risk of neurodevelopment disorders.
Non uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at
... Show MoreThe compressive residual stresses generated by shot peening, is increased in a direct proportional way with shot peening time (SPT). For each metal, there is an optimum shot peening time (O.S.T) which gives the optimum fatigue life. This paper experimentally studied to optimize shot peening time of aluminium alloy 6061-T651 as well as using of and analysis of variance (ANOVA).
Two types of fatigue test specimens’ configuration were used, one without notch (smooth) and the other with a notch radius (1,25mm), each type was shot peened at different time. The (O.S.T) was experimentally estimated to be 8 minutes reaching the surface stresses at maximum peak of -184.94 MPa.
A response surface methodology (RSM) is presen
... Show MoreIn this paper, the satellite in low Earth orbit (LEO) with atmospheric drag perturbation have been studied, where Newton Raphson method to solve Kepler equation for elliptical orbit (i=63 , e = 0.1and 0.5, Ω =30 , ω =100 ) using a new modified model. Equation of motion solved using 4th order Rang Kutta method to determine the position and velocity component which were used to calculate new orbital elements after time step ) for heights (100, 200, 500 km) with (A/m) =0.00566 m2/kg. The results showed that all orbital elements are varies with time, where (a, e, ω, Ω) are increased while (i and M) are decreased its values during 100 rotations.The satellite will fall to earth faster at the lower height and width using big values for ecce
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra
... Show MoreThis paper sheds the light on the vital role that fractional ordinary differential equations(FrODEs) play in the mathematical modeling and in real life, particularly in the physical conditions. Furthermore, if the problem is handled directly by using numerical method, it is a far more powerful and efficient numerical method in terms of computational time, number of function evaluations, and precision. In this paper, we concentrate on the derivation of the direct numerical methods for solving fifth-order FrODEs in one, two, and three stages. Additionally, it is important to note that the RKM-numerical methods with two- and three-stages for solving fifth-order ODEs are convenient, for solving class's fifth-order FrODEs. Numerical exa
... Show MoreThe rheological behavior among factors that are present in Stokes law can be used to control the stability of the colloidal dispersion system. The felodipine lipid polymer hybrid nanocarriers (LPHNs) is an interesting colloidal dispersion system that is used for rheological characteristic analysis. The LPHNs compose of polymeric components and lipids. This research aims to prepare oral felodipine LPHNs to investigate the effect of independent variables on the rheological behavior of the nanosystem. The microwave-based technique was used to prepare felodipine LPHNs (H1-H9) successfully. All the formulations enter the characterization process for particle size and PDI to ascertain the colloidal properties of the prepared nanosystem t
... Show MoreThe control of water represents the safe key for fair and optimal use to protect water resources due to human activities, including untreated wastewater, which is considered a carrier of a large number of antibiotic-resistant bacterial species. This study aimed to investigate the prevalence of antibiotic-resistance to E. coli in Tigris River by the presence of resistance genes for aminoglycoside(qepA( ,quinolone (gyrA), and sulfa drugs( dfr1 ,dfr17) due to the frequent use of antibiotics and their release into wastewater of hospitals. Samples were collected from three sites on Tigris River: S1( station wastewater in Adhamiya), S2 (station wastewater in Baghdad Medical city hospital), S3 (station wastew
... Show MoreWisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.
This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
... Show MoreIn this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.