Dicephalus parapagus twinning (DPT) is the rarest conjoined twinning entity of all conjoined twins. The presence of DPT is always associated with mortality before or after delivery. Antenatal diagnosis is crucial for planning labor, assembling a team, and providing counseling. Case presentation: A 23-year-old patient (G2P1A0) at 21 weeks of pregnancy attended the ultrasound clinic for routine care. A monoamniotic-monochorionic pregnancy was observed; the twin fetuses had two heads but one body, which corresponded to dicephalus parapagus twinning. A detailed ultrasound and fetal echocardiography reveal one heart without congenital anomalies. The liver, kidneys, and bladder appeared to be normally developed. Fetal MRI and karyotyping wer

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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

Introduction: The introduction of analytics tools in sports indicates that artificial neural networks can be one of the intelligent approaches to process complex data and identify patterns that help players move according to their most suitable positions. Objective: The purpose of this research is to investigate the possibility of using artificial neural networks to determine the physical and motor abilities of football players and determine their suitable playing positions based on exact quantitative indicators. Method: The study sample consists of 45 youth players aged (15–16) years from the Espanyol Football Academy in Baghdad. The results are analyzed using a multilayer perceptron (MLP) artificial neural network model to ident

Background: Colorectal cancer, the most common gastrointestinal cancer, is a significant health issue globally. Mucin 16 plays a critical role in cancer signal transduction pathways and is a potential glycoprotein target for cancer therapy. The miRNA-200 family also regulates the expression of numerous genes that play vital roles in cancer cells. This study aimed to investigate the changes in mucin 16 and miRNA-200a in patients with colorectal cancer (CRC). Subjects and Methods: Fifty-six patients with CRC, including 26 in stage 3 and 30 in stage 4, were included in this study, along with 38 healthy volunteers as a control group. Parameters such as mucin 16, miRNA-200a, total protein, albumin, globulin, and the albumin/globulin rati