The present study aimed to evaluate the concentration of Malon dialdehyde (MDA) in pregnant women during different stages of pregnancy (stage of pregnancy, abortion, contraceptives and parity number).The study included (120) blood samples from normal pregnant women in age of the procreating were subdivided into three trimesters of pregnancy (40/group), and (40) samples from non-pregnant women as a control group. The results showed a significant increase in MDA in three stages of pregnancy compared with the control group. The concentration of MDA increased significantly in pregnant women with multipregnancy when compared with pregnant women for the first time, and in pregnant women whom was using contraceptions compared with p

Background: With the increasing trends of global culinary boom and food revolution, and since adolescents are one of the most important age groups that intereact actively with new emerging waves, the health impacts of overweight adolescent pregnancy could be an evolving issue. Additionally, prematurity has different risks of disease and fatality in different areas and nations. Objectives: We aimed to measure the prevalence of complications of prematurity in 1000 neonates in Baghdad city born to overweight adolescent mothers and general maternal characteristics. Methods: Data of 1000 premature (case) and full-term (control) neonates were collected from hospital records in Baghdad over 12 years. The mothers of our samples were overwei

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used

Abstract: Microfluidic devices present unique advantages for the development of efficient drug assay and screening. The microfluidic platforms might offer a more rapid and cost-effective alternative. Fluids are confined in devices that have a significant dimension on the micrometer scale. Due to this extreme confinement, the volumes used for drug assays are tiny (milliliters to femtoliters).

 In this research, a microfluidic chip consists of micro-channels carved on substrate materials built by using Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO₂) laser machine. The CO2 parameters have influence on the width, depth, roughness of the chip. In order to have regular

This paper investigated the treatment of textile wastewater polluted with aniline blue (AB) by electrocoagulation process using stainless steel mesh electrodes with a horizontal arrangement. The experimental design involved the application of the response surface methodology (RSM) to find the mathematical model, by adjusting the current density (4-20 mA/cm2), distance between electrodes (0.5-3 cm), salt concentration (50-600 mg/l), initial dye concentration (50-250 mg/l), pH value (2-12 ) and experimental time (5-20 min). The results showed that time is the most important parameter affecting the performance of the electrocoagulation system. Maximum removal efficiency (96 %) was obtained at a current density of 20 mA/cm2, distance be

The main objective of the audit is The asset is maintained and operated efficiently and is done through to detect fraud and errors in the financial statements and to verify the accuracy and accuracy of the information contained therein and to give a neutral technical opinion on the basis of that, thus the auditor has a professional responsibility in achieving this goal, and that the effects of issuing a wrong opinion works on The loading of the beneficiaries is significant damage, And therefore the presence of any error or bias of the auditor when taking personal judgments in relation to the determination of the relative importance and the selection of audit samples and determine the adequacy and validity of evidence and implemen

The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra