Over the last 40 years, rate of cesarean delivery has risen from less than10% to over 30% around the world, and almost simultaneously a 10-foldraise in the incidence of placenta accrete spectrum. Fine coordinationamong vascular endothelial growth factor, soluble fms-like tyrosine kinase1 and placental growth factor is important for normal placentaldevelopment and trophoblast invasion. To measure and compare the levelsof circulating vascular endothelial growth factor, placental growth factorand soluble fms-like tyrosine kinase 1 in pregnant women with placentaaccreta to a control group. A case control study which involved one hundredpregnant females were recruited from the Obstetric ward in BaghdadTeaching Hospital who were pregnant with 28 weeks of gestation or more,through the period from October 2018 to June 2019. Fifty patients werechosen with placenta accreta that ended with caesarean sectionhysterectomy and the other fifty patients were with normal placentallocation as a control. Means of VEGF, PlGF, and sFlt-1 were significantlylower among case group than that in controls. Cut point of VEGF level was111.83 ng/L, of PlGF level was 23.29 ng/L, and of sFlt-1 was 5.32 ng/ml;so VEGF level < 111.83 ng/L, PlGF level < 23.29 ng/L, and sFlt-1 level <5.32 ng/ml are predictors for risk of placenta accrete. No statisticalsignificant correlations between markers’ level and all characteristics.Angiogenic and anti-angiogenic markers may have a role in thedevelopment of placenta accreta spectrum. VEGF, PIGF and sFlt-1 aredecreased in patients with placenta accreta
This paper aims to evaluate the reliability analysis for steel beam which represented by the probability of Failure and reliability index. Monte Carlo Simulation Method (MCSM) and First Order Reliability Method (FORM) will be used to achieve this issue. These methods need two samples for each behavior that want to study; the first sample for resistance (carrying capacity R), and second for load effect (Q) which are parameters for a limit state function. Monte Carlo method has been adopted to generate these samples dependent on the randomness and uncertainties in variables. The variables that consider are beam cross-section dimensions, material property, beam length, yield stress, and applied loads. Matlab software has be
... Show MoreNowadays, the field of radionuclide treatment is enjoying an exciting stage and preparing for further growth and progress in the future. For instance, in Asia, the large spread of liver and thyroid diseases has resulted in several new developments/clinical trials using molecular radiotherapy (i.e. targeted radionuclide therapy). Iodine-124 has unique physical properties including long half-life that adding an advantage for pharmacokinetics and radiopharmaceutical analysis. One of its applications in nuclear medicine is in Positron Emission Tomography (PET).
Traditional tree management is laborious and costly, thus this work aimed to study the performance of two different types of frond cutting saws (reciprocating saw and vibrating saw) and examine the two saws on five date palm varieties. Four parameters were examined, including cutting time for a single frond, the power needed for cutting a single frond, frond cutting productivity expressed as tree/h, and vibration conveyed to the worker’s hand. A field experiment was designed according to the nested randomized complete block design, including five date palm varieties as the main plot and the type of saw as a sub-plot. Means were compared using the least significant differences (LSD 0
Objective: This study aims to evaluate nurses' practices regarding electronic nursing documentation
Methodology: 40 nurses have been chosen for a pre experimental sample using a non-probability (purposive) method between November 20, 2021, and March 1, 2023. The pretest and posttest comparisons included the same group that had been exposed to the software.
Results : table the nurses' practices toward electronic nursing documentation was described as poor and fair it means that nurses practices need to be improved and developed by an interventional program. there is no significant differences between age, gender and years of employment variables and nurses practices.
... Show MoreThis study aimed to determine the measurements and classification of Schneider membrane thickness correlated to age and sex factors using cone beam computed tomography (CBCT). Methods: The study included CBCT images for 100 maxillary sinuses of 50 consecutive patients, and the thickness of the maxillary sinus membrane (Schneiderian membrane) was measured in coronal view from the lowest point in the floor of the maxillary sinus to the highest point. The thickness of the Schneiderian membrane was classified into 4 types. Results: The study result revealed that out of the total cases, 45% of sinus membranes were classified as type 2, while only 10% were classified as type 4. The most frequent type of membrane thickness diagnosed in the age gro
... Show MoreIn this investigation, the mechanical properties and microstructure of Metal Matrix Composites (MMCs) of Al.6061 alloy reinforced by ceramic materials SiC and Al2O3 with different additive percentages 2.5, 5, 7.5, and 10 wt.% for the particle size of 53 µm are studied. Metal matrix composites were prepared by stir casting using vortex technique and then treated thermally by solution heat treatment at 530 0C for 1 hr. and followed by aging at 175 0C with different periods. Mechanical tests were done for the samples before and after heat treatment, such as impact test, hardness test, and tensile test. Also, the microstructure of the metal matrix composites was examine
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show More