Background: Measuring the concentration of hepatitis B surface antigen (HbsAg) in HBV patients can be determined with immunoassay techniques. This study aimed to measure the HbsAg titers in chronic HBV patients and to assess its correlation with patients' ages, gender, and with the levels of liver enzymes and total serum bilirubin. Materials and Method: Fifty-eight chronic hepatitis B infected patients were enrolled in this study. Age and gender of the patients were recorded. HbsAg concentration was tested with automated Immunoanalyzer. The patients were also tested for ALT, AST, ALP, and TSB by automated chemistry analyzer. Results: All the chronic HBV patients have positive HBsAg titers above the negative cutoff (0.05U/L) with mea

MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

Objective: to assessthe impact of psychological and social climacteric changes on quality of life among
middle age women in Baghdad city
Methodology: : A descriptive analytic study was conducted to study the quality of life among middle age
women due topsychological and social climacteric changes from February 2013- July 2013. A purposive
sampleconsisted of three hundred (300) womenaged (40-65) years who were attending health centers in two
sectors in Baghdad / AL- Russafa andAL- karhk . The data were collected through using interview technique ,
and questionnaire format , which comprises two parts, first part consist (socio-demographic characteristic , the
second part quality of life domains (psychological and socia

This paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings an

A set of hydro treating experiments are carried out on vacuum gas oil in a trickle bed reactor to study the hydrodesulfurization and hydrodenitrogenation based on two model compounds, carbazole (non-basic nitrogen compound) and acridine (basic nitrogen compound), which are added at 0–200 ppm to the tested oil, and dibenzotiophene is used as a sulfur model compound at 3,000 ppm over commercial CoMo/ Al2O3 and prepared PtMo/Al2O3. The impregnation method is used to prepare (0.5% Pt) PtMo/Al2O3. The basic sites are found to be very small, and the two catalysts exhibit good metal support interaction. In the absence of nitrogen compounds over the tested catalysts in the trickle bed reactor at temperatures of 523 to 573 K, liquid hourly space v

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T