Dueto their ability to providefood for people, sheep and goats areimportant to the economiesofmanynations.Toxoplasmagondii,orT.gondii,isaprotozoanparasite that often infects sheep. Stillbirth, early embryonic death and resorption, neonatal mortality, fetal death and mummification, and parasite infection are examples of possible negative effects. Theconsequences aremoreseverethe earlier in gestation the infection arises. The stage of pregnancy at which the infection occurs in thesheep and goats is connected with the severity of the illness. T.gondii may infect humansandcarnivorousanimalsvia the meatofinfectedsheepandgoats.Lessthan 4%ofsheep thatareconsistently infected withT.gondiicarrytheparasitevertically to their offspring. The majority o

BACKGROUND: Anemia during pregnancy is still a challenge throughout the world, and it may cause severe health consequences in the maternal and fetal sides. AIM: This study aims to find out the prevalence of maternal anemia and potential adverse outcomes in Iraq. METHODS: In Medical City Tertiary Center in Baghdad, singleton pregnant ladies came for delivery were involved over 6 months’ period. Based on hemoglobin (Hb) readings; they were divided into no anemia group (Hb>11 g/l) and anemia group which were further subdivided into mild, moderate, and severe (Hb =10–10.9, =7.1–9.9, and <7 g/l, respectively). Full history and examination were performed by attending obstetrician and pediatrician for the upcoming b

    This paper is intended to apply data mining techniques for real Iraqi biochemical dataset to discover hidden patterns within tests relationships. It is worth noting that preprocessing steps take remarkable efforts to handle this type of data, since it is pure data set with so many null values reaching a ratio of 94.8%, then it becomes 0% after achieving these steps. However, in order to apply Classification And Regression Tree (CART) algorithm, several tests were assumed as classes, because of the dataset was unlabeled. Which then enabled discovery of patterns of tests relationships, that consequently, extends its impact on patients’ health, since it will assist in determining test values by performing only relevant

    The Mawat Ophiolite Complex located in north-eastern Iraq represents part of the Iraqi Zagros Suture Zone, located at the border between the Arabian-Iranian plates. It consists of peridotite, gabbro, subvolcanic sheeted dykes and volcanic pillow lava. The geochemical signatures of the gabbro show a significant variation in major elements concentration, low concentrations of TiO₂ (0.06-0.36 wt.%), Na₂O (0.44-0.98 wt.%), K₂O (0.024-0.48 wt.%), P₂O₅ (0.002-0.009 wt.%) and moderate variations in SiO₂ (46.13-53.77 wt.%) with wide ranges and high concentration of Al₂O₃ (13.87-22.18 wt.%), Fe₂O₃ (0.04-2.95 wt.%), FeO (2.68-8.76 w

Spergularia iraqensis sp. nov. is described as a new species from Iraq. This species has been collected from Diyala Province in the central east of Iraq; it is closely related to Spergularia rubra (L.) J. Presl & C. Presl, 1819 and Spergularia bocconei (Scheele) Graebn., 1919.
The distinguishing of the morphological characteristics of the new species alongside the two similar species are discussed with photographs, and an identification key is given for Spergularia iraqensis and other closely related species.

يتنامى يوما بعد يوم استخدام السيارات وتتعاضم اعدادها ، فهذا هو عصر السرعة، وخاصة في مجال النقل والمواصلات، والتي تتحقق باستخدام وسائل النقل المختلفة ومن بينها السيارات، وبالتالي اصبحت هذه الوسيلة ضرورية لتحقيق هذه السرعة ومن ضرورات الحياة في انجاز الاعمال.

وتتبارى مصانع السيارات فيما بينها لانتاج انواع السيارات بمواصفات عالية من المتانة والامان والراحة، وفي ذات الوقت اصبحت هندسة الطرق

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.&nbsp; A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with mis

Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traff