Shatt Al-Arab River in Al Basrah, Iraq, has recently recorded massive levels of TDS values (Total Dissolved Solids) in the water as a result of reduced fresh water discharge from sources, causing the river to become salinized due to salt wedge intrusion. Therefore, a block dam in the south reach is required to salt intrusion prevention. The main objective of this research is to simulate the hydraulic impact of a suggested barrage in Ras Al Besha on the Shatt Al-Arab River. The HEC-RAS (5.0.7) model was used to develop a one-dimensional unsteady model to gaining an understanding of the proposed barrage's influence on river behaviour. The daily discharges of the Tigris River provided as the upstream boundary conditions, wh

Background Molluscum contagiosum is skin disease caused by the molluscum contagiosum virus (MCV) usually causing one or more small dome shaped umbilicated papules with symptoms that maybe self-resolve. MCV was once a disease primarily of children, but it has evolved to become a sexually transmitted disease in adults. It is believed to be a member of the pox virus family. In addition to the classic presentation of the disease; it can also come in different clinical forms that simulate large number of dermatolological disease.
Objective: To study different clinical forms of Molluscum contagiosum presentation in different age groups of Iraqi patients.
Method:This clinical descriptive study was performed in the outpatient department of

Normal thyroid function is essential for neonatal growth and brain development. In a newborn infant with severe disease, endocrine regulation of hormones can be affected by abnormal metabolism. The assessment of thyroid parameters results in the recognition of a dysfunction and its association with disease severity

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

Locking of the knee is a one of the commonest orthopedic outpatient presentation. This patient usually need magnetic resonance imaging (MRI) when there is suspected lesion in the soft tissue clinically. Meniscal tears is the first differential diagnosis when accompany with painful knee. (1, 2)
Giant cell tumor (GCT) is benign a localized nodular tenosynovitis often occur in the tendon sheath , Mostly involve the hand tendons in middle age group between 30 and 50 years old , female affect more than male.(3,4) The WHO defines two well-known kinds of giant cell tumor: (1) pigmented villonodular synovitis ( generalized type), which mainly involve the joints of the lower limb and (2) giant cell tumor of the tendon sheath ( localized type)

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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

The sustainable development according to the United Nation, listed firms throughout globally now routinely provide sustainability data. However, there is not enough information on Sustainability Performance Quality (SPQ) in the majority of emerging economies, including Malaysia. This study looks at how the SPQ of the top 100 Malaysian-listed businesses is affected by factors as connected with corporate governance (e.g., board meeting, board size, and board ethnic diversity). Utilizing 500 firm-year data, a longitudinal sample of 500 nonfinancial firms on the Bursa Malaysia for 2015-2019 is employed in this study. The findings from the analysis using the panel regression demonstrated that: ethnic diversity and board siz