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D-dimer level and Wells score in women undergone Lymphadenectomy in Gynecological Cancer to Assess Risk of Deep Venous Thrombosis
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Background: One of the most important prognostic indicators in cancer is the lymph node dissection. Lymphadenectomy considered as a risk factor for deep vein thrombosis in patients with gynecological malignancy who underwent surgery. D-dimer was used to detect deep vein thrombosis, thus, it’s important to predict complications of post-operative Lymphadenectomy.

Objective: To predict the  risk of deep venous thrombosis by used serum D-dimer and wells score after pelvic lymphadenectomy in gynecological cancer.

Patients and method:  A cross sectional study conducted in Obstetrics and Gynecology/ ward in medical city, from 1st, January 2021 to 30th, Dec. 2021. A total number of 45 (22 endometrial, 12 ovarian and 11 cervical cancers). 

Results: The mean±SD level of pre-operative D-dimer in patients with endometrial cancer was (423.2±123.9) while the mean±SD post-operative level was (987±125.1), the mean±SD level of pre-operative D-dimer in patients with ovarian cancer was (602±320.7) while the post-operative was (901.5± 412), mean±SD level of pre-operative D-dimer in patients with cervical cancer was (339±157) while the postoperative was (1214±327), and the mean±SD level of pre-operative D-dimer in all gynecological cancers was (541±167) while the post-operative was (1016±302). The mean±SD of wells score of those who are likely to developed DVT (n=7) in pre-operative was (2.3±0.02) while for those who are unlikely to develop deep vein thrombosis (n=38) was (2.03±0.4) with statistically significant difference (p=0.04) while highly significant difference found in pre- and post-operatively between the group of deep vein thrombosis (p˂0.001).

Conclusion: Highly significant increase of post-operative D-dimer in all gynecological cancer patients.

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Publication Date
Mon Aug 16 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Statistic Assessment of Spreading Cases (Total Confirmed, Recovered, Death) From Different AreasContain Novel Coronavirus (2019-n Cov)
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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
A Direct Solution Scheme for Wide-Angle Electromagnetic Scattering Problems Using Compressive Sensing-Based Method of Moments
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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering Science And Technology
NUMERICAL SIMULATION OF SHEET PILES AS A SEEPAGE CUTTER OFF: AL-KIFIL REGULATOR AS A CASE STUDY
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Sheet piles are necessary with hydraulic structures as seepage cut-off to reduce the seepage. In this research, the computational work methodology was followed by building a numerical model using Geo-Studio program to check the efficiency of using concrete sheet piles as a cut-off or reducer for seepage with time if the sheet piles facing the drawdown technique. Al-Kifil regulator was chosen as a case study, an accurate model was built with a help of observed reading of the measuring devices, which was satisfactory and helped in checking the sheet piles efficiency. Through the study, three scenarios were adopted (with and without) drawdown technique, it was found that at the short time there's no effect of the drawdown technique on

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Publication Date
Mon Feb 19 2024
Journal Name
Journal Of Engineering
Predicting Biochemical Oxygen Demand at the Inlet of Al-Rustumiya Wastewater Treatment Plant Using Different Mathematical Techniques
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Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin

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Publication Date
Sun Jun 26 2022
Journal Name
Electrical Engineering
Optimal insulation design of form-wound stator winding with stress grading system under fast rise-time excitation
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The effective insulation design of the stress grading (SG) system in form-wound stator coils is essential for preventing partial discharges and excessive heat generation under pulse-width modulation excitation. This paper proposes a method to find the optimal insulation design of the SG system aimed at reducing the dielectric and thermal stresses in the machine coil. The non-uniform transmission line model is used to predict the voltage propagation along the overhang, SG, and slot regions considering the variation in the physical properties of the insulation layers. The machine coil parameters for different insulation materials are calculated by using the finite element method. Two optimization algorithms, fmincon and particle swarm optimiz

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Publication Date
Sat Apr 30 2022
Journal Name
Kufa Journal Of Engineering
Numerical Analysis for the Response of Skirt Circular Shallow Footing Resting on Sandy Soil under vertical loads
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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
IoT-Key Agreement Protocol Based on The Lowest Work-Load Versions of The Elliptic Curve Diffie-Hellman
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     A key agreement protocol (KAP) is a fundamental block in any cryptosystem since it ensures secure communication between two parties. Furthermore, KAP should include advanced features in limited-resource environments such as IoT, in which this protocol must be lightweight and efficient in consuming resources. Despite the Elliptic Curve Diffie-Hellman (ECDH) algorithm having often been considered efficient in providing an acceptable security degree with less resource consumption, it has suffered from weakness against Man-In-The-Middle Attacks (MITMA). This paper presents two versions of the Variant Elliptic Curve Diffie-Hellman (VECDH) algorithms as a key agreement protocol. The security analysis indicates that the proposed algori

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Publication Date
Tue Aug 03 2021
Journal Name
Key Engineering Materials
Study the Behavior of Castellated Steel Column Encasing by Different Reactive Powder Concrete Thickness with Laced Reinforcement
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Castellated columns are structural members that are created by breaking a rolled column along the center-line by flame after that rejoining the equivalent halves by welding such that for better structural strength against axial loading, the total column depth is increased by around 50 percent. The implementation of these institutional members will also contribute to significant economies of material value. The main objectives of this study are to study the enhancement of the load-carrying capacity of castellated columns with encasement of the columns by Reactive Powder Concrete (RPC) and lacing reinforcement, and serviceability of the confined castellated columns. The Castellated columns with RPC and Lacing Reinforcement improve com

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Publication Date
Tue Jun 21 2022
Journal Name
Peerj Computer Science
Performance evaluation of frequency division duplex (FDD) massive multiple input multiple output (MIMO) under different correlation models
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Massive multiple-input multiple-output (massive-MIMO) is considered as the key technology to meet the huge demands of data rates in the future wireless communications networks. However, for massive-MIMO systems to realize their maximum potential gain, sufficiently accurate downlink (DL) channel state information (CSI) with low overhead to meet the short coherence time (CT) is required. Therefore, this article aims to overcome the technical challenge of DL CSI estimation in a frequency-division-duplex (FDD) massive-MIMO with short CT considering five different physical correlation models. To this end, the statistical structure of the massive-MIMO channel, which is captured by the physical correlation is exploited to find sufficiently

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Approach for estimating the unknown Scale parameter of Erlang Distribution Based on General Entropy Loss Function
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We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

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