BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjected for digital and transvaginal ultrasound cervical length measurement and the outcome measures were occurrence of preterm delivery within 48 hours and within 7 days. RESULTS: Assessment of cervical length measurement using transvaginal ultrasound for the 200 women presented with preterm labour with intact membrane revealed that 8 (4%) delivered within 48 hours and 16 (8%) delivered within 7 days. According to the Bishop score, the test was positive if the Bishop score was ≥8, or 4-7 with cervical length ≤30 mm. The cut-off value for transvaginal ultrasound cervical length considered as 30 mm in the study group. CONCLUSION: Transvaginal sonographic measurement of cervical length can predict imminent preterm delivery in women presented with preterm uterine contractions and Bishop score between 4 - 7 compared with digital cervical length measurement.
Autorías: Nuha Mohsin Dhahi, Muhammad Hamza Shihab. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.
In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
... Show MoreOrganizational learning is one of the most important means of human resource development in organizations, but most of the organizations, especially public ones do not realize the importance of organizational learning enough, and estimated his role accurately in building intellectual capital, the resource competitive importantly for organizations of the third millennium and who suffers is other end of lack of understanding of its meaning and how to prove its presence and measured in public organizations, so there is the need for this research, which aims to investigate the effect of organizational learning its processes (knowledge acquisition, Information transfer, Interpreting the information, Organizational me
... Show MoreA robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreIn this paper, a relationship between the liquid limit and the coefficient of consolidation of Iraqi soils are studied. The samples of soil used in study are undisturbed silty clay. These samples are taken from different locations and depths of Middle and South of Iraq by cooperation with Consulting Engineering Bureau- University of Baghdad- College of Engineering. The depth reached about 20 meters. The experimental work is made to calculate the liquid limit and the coefficient of consolidation. From these sites, 280 points are obtained. The relationship between the liquid limit and the coefficient of consolidation is drawn as a curve. This curve is studied and compared with the curve that obtained from other studies. From these curves, it
... Show MoreStudy was done in the period between (2015–2017) in biology department in college of Education for pure science/Ibn Al-Haitham at Baghdad University and in Pathology department/college of medicine at Al-Nahrain University. The study was retrospectively designed. The clinicopathological parameters were obtained from patients’ admission case sheets and pathology reports (age, gender). The presents study included 120 patients having thyroid nodules, classified according to results of histopathology into 4 groups, 30 patients within each; the first group included patients with follicular adenoma, the second group included patients with follicular carcinoma, the third group included patients with follicular variant of papillary carcinoma (FV
... Show MoreBackground: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver. Objectives: To assess age, sex, and body mass index (BMI) as
... Show MoreThis research presents a comparison of performance between recycled single stage and double stage hydrocyclones in separating water from water/kerosene emulsion. The comparison included several factors such as: inlet flow rate (3,5,7,9, and 11 L/min), water feed concentration (5% and 15% by volume), and split ratio (0.1 and 0.9). The comparison extended to include the recycle operation; once and twice recycles. The results showed that increasing flow rate as well as the split ratio enhancing the separation efficiency for the two modes of operation. On the contrary, reducing the feed concentration gave high efficiencies for the modes. The operation with two cycles was more efficient than one cycle. The maximum obtained effici
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