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Renal stone density on native CT-scan as a predictor of treatment outcomes in shock wave lithotripsy
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Extracorporeal shock wave lithotripsy (ESWL) is considered a standard treatment for nephrolith or kidney stones measuring less than 20 mm. Anatomical, machine-related, and stone factors play pivotal roles in treatment outcomes, the latter being the leading role. This paper examined the relationship between stone density on native CT scans and ESWL treatment to remove renal stones concerning several treatments. One hundred and twenty patients (64 males and 56 females) were enrolled and completed the study from April 2019 to September 2020. Inclusion criteria were a single renal pelvis stone of 5–20 mm to be treated for the first time in adult patients with no urinary or musculoskeletal anatomical abnormalities. We assessed patients' renal function and obtained stone characteristics using a native CT scan. Patients were then scheduled for ESWL by the same machine and operator under fluoroscopy, with two-week intervals between treatment sessions when more than one treatment session was required. Before each new session, a new KUB-US was performed to reevaluate the stone. One hundred and twenty patient records were analyzed, 64 (53.3%) males and 56 (46.7%) females, with a mean age of 38.6 years and a mean stone size of 13.15 mm. Treatment with ESWL cleared stones in 76 (63.3%) patients, while 44 (36.7%) failed the treatment. The mean stone density in patients whose stones were cleared was significantly lower (661 vs. 1001) (P<0.001). Estimating renal calculus (or kidney stone) density on a native CT scan might help prognosticate ESWL treatment outcomes regarding stone clearance rates and the number of sessions required to clear a stone.

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Publication Date
Sun Dec 05 2010
Journal Name
Baghdad Science Journal
Immunoglobulins assessment (IgE,G,A,M) in some Iraqi patients with acute and chronic urticaria
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60 patients diagnosed as having urticaria were included in the study ; 30 patients were effected with acute urticaria and 30 patients were affected with chronic urticaria. In addition, 30 healthy adult volunteers were selected as control group .The patients and control groups sera were examined with enzyme linked immunosorbent assay ( ELISA) to detect total level IgE and radial immunodiffusion (RID) to detect levels of IgG , IgA and IgM . The total level of IgE in acute urticaria ( 1.45±0.13) IU/mL and chronic urticaria (2.12 ± 0.10) IU/mL patients were significantly higher than the control groups ( 0.85 ± 0.10)IU/mL (p<0.05). The level of IgG in acute urticaria ( 12.5± 0.42) g/L and chronic (13.16±0.40) g/L patients , IgA in acute (2.

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Publication Date
Mon May 01 2017
Journal Name
2017 24th International Conference On Telecommunications (ict)
Load balancing by dynamic BBU-RRH mapping in a self-optimised Cloud Radio Access Network
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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
A Destructive Parenthood : The Problematic Motherhood in Selected Poems by Salvia Plath: Fatin Kaleel Ismael
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A Destructive Parenthood : The Problematic Motherhood in Selected Poems by Salvia Plath

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Language Teaching And Research
Islamification vs. Islamophobia: A Message to the Youth in the Occident: Critical &amp; Rhetorical Inquiries
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Drawing upon the recent theoretical framework of Burkean concept of identification (ID), the current study aims at probing the interaction of content and form in two letters penned by Iran’s Supreme Leader and addressed to the Youth on Jan. and Nov. 2015. To this end, the study seeks (i) to determine a role ID takes in the conveyance of intended assumptions to the targeted readers; and (ii) to observe if the writer’s objectives, i.e. to identify himself with the readers and to realize his politically-religiously-infused creeds, result in success or failure; moreover, (iii) it seeks to determine how he achieved his end to attenuate the impacts of blazing inferno of Islamophobia and anti-Islam sentiments in his addressees. The who

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Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Transport Assessment Using Bayesian Method to Determine Ride-Hailing in Kula Lumpur: A Case Study
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This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Sensors
WDARS: A Weighted Data Aggregation Routing Strategy with Minimum Link Cost in Event-Driven WSNs
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Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost

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Publication Date
Mon Oct 12 2020
Journal Name
Molecules
Phase Change Process in a Zigzag Plate Latent Heat Storage System during Melting and Solidification
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Applying a well-performing heat exchanger is an efficient way to fortify the relatively low thermal response of phase-change materials (PCMs), which have broad application prospects in the fields of thermal management and energy storage. In this study, an improved PCM melting and solidification in corrugated (zigzag) plate heat exchanger are numerically examined compared with smooth (flat) plate heat exchanger in both horizontal and vertical positions. The effects of the channel width (0.5 W, W, and 2 W) and the airflow temperature (318 K, 323 K, and 328 K) are exclusively studied and reported. The results reveal the much better performance of the horizontal corrugated configuration compared with the smooth channel during both melti

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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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