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A novel method for non-invasively detecting the severity and location of aortic aneurysms
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The influence of an aortic aneurysm on blood flow waveforms is well established, but how to exploit this link for diagnostic purposes still remains challenging. This work uses a combination of experimental and computational modelling to study how aneurysms of various size affect the waveforms. Experimental studies are carried out on fusiform-type aneurysm models, and a comparison of results with those from a one-dimensional fluid–structure interaction model shows close agreement. Further mathematical analysis of these results allows the definition of several indicators that characterize the impact of an aneurysm on waveforms. These indicators are then further studied in a computational model of a systemic blood flow network. This demonstrates the methods’ ability to detect the location and severity of an aortic aneurysm through the analysis of flow waveforms in clinically accessible locations. Therefore, the proposed methodology shows a high potential for non-invasive aneurysm detectors/monitors.

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Publication Date
Mon Nov 10 2025
Journal Name
International Journal Of Dentistry
The Impact of Overweight Among Children on Salivary Vitamin D, Calcium, and Magnesium in Relation to Dental Caries Severity
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Vitamin D is one of several nutrients essential for calcium metabolism. Body weight status and magnesium may influence vitamin D activity. To determine whether salivary vitamin D, magnesium, and calcium levels are associated with body weight status and dental caries severity in children, this cross‐sectional research was conducted.

Methods

The sample consisted of 180 boys aged 6–8 years. According to their body mass index (BMI), children were assigned to three groups of 60 boys (normal weight, overweight, and obese). Moreover,

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Publication Date
Mon Jul 27 2026
Journal Name
Indonesian Journal Of Clinical Pathology And Medical Laboratory
The Value of Cardiac Troponin I and Midkine in predicting coronary artery obstruction severity in Chronic Coronary Syndromes (CCS)
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High-sensitive cardiac troponin I (hs-cTnI) is a recognized marker of myocardial injury in acute coronary syndromes, but its utility in chronic coronary syndromes (CCS) remains unclear. Midkine (MK), a heparin-binding growth factor, plays a role in inflammation and vascular remodeling in atherosclerosis. This cross-sectional study aimed to evaluate the predictive value of serum hs-cTnI and MK in determining the severity of coronary artery obstruction in patients with CCS. The study included 125 subjects undergoing coronary angiography (CAG) at the Iraqi Center of Heart Disease/ Medical City/Baghdad, from March to December 2024. Subjects were classified into three groups based on CAG findings: no CAD, 1- or 2-vessel disease, and 3-ve

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Publication Date
Tue Dec 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Reasons for Partial Compliance and Non-compliance to the Routine Childhood Vaccination Schedule in Al-Karkh District
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Abstract

      Objective (s): To evaluate reasons for partial compliance and non-compliance to the

                              routine childhood vaccination schedule in Al-Karkh district 

Methodology: Descriptive study , using the evaluation approach, is carried throughout the present study to determine the reasons for the Routine Childhood Vaccination at  health care sectors and primary health care centers at  Al-Karkh District in Baghdad City, Convenient, non-probability, sample of (90) mother who are recruited from health care sectors at Al-Karkh District in Baghdad City. All mothers, who ha

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Publication Date
Mon Mar 31 2025
Journal Name
Iraqi Statisticians Journal
Hypothesis Testing for Non-Normal Multiple Compact Regression Model
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

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Publication Date
Fri Sep 01 2017
Journal Name
Ce/papers
16.15: Experimental evaluation of a novel demountable shear connector for accelerated repair or replacement of precast steel‐concrete composite bridges
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A novel demountable shear connector for precast steel‐concrete composite bridges is presented. The connector uses high‐strength steel bolts, which are fastened to the top flange of the steel beam with the aid of a special locking nut configuration that prevents slip of bolts within their holes. Moreover, the connector promotes accelerated construction and overcomes typical construction tolerances issues of precast structures. Most importantly, the connector allows bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (i) precast deck panels can be rapidly uplifted and replaced; (ii) connectors can be rapidly removed and replaced; and (iii) steel beams can b

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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Publication Date
Sun May 01 2022
Journal Name
Expert Systems With Applications
Novel large scale brain network models for EEG epileptic pattern generations
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Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
Static Shear Strength of a Non-Prismatic Beam with Transverse Openings
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In this study, a predicated formula is been proposed to find the shear strength of non-prismatic beams with or without openings. It depends on the contributions of concrete shear strength considering the beam depth variation and existing openings, shear steel reinforcements and defines the critical shear section, the effect of diagonal shear reinforcement, the effect of inclined tensile steel reinforcement, and the compression chord influence. The verification of the proposed formula has been conducted on the experimental test results of 26 non-prismatic beams with or without openings at the same loading conditions. The results reflect that the predicted formula finds the shear capacity of non-prismatic beams with openings, it is co

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Publication Date
Wed Apr 02 2025
Journal Name
Current Studies On Probability And Statistics
SAR-HDP: Non-parametric Topic Model for Aspect categorisation based on online reviews
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Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

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Publication Date
Mon Aug 06 2018
Journal Name
Indian Journal Of Applied Research
STATISTICAL METHOD FOR SOLVING TRANSPORTATION PROBLEMS OF USING THE PROGRAMMING LANGUAGE MATLAB
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Original Research Paper Mathematics 1-Introduction : In the light of the progress and rapid development of the applications of research in applications fields, the need to rely on scientific tools and cleaner for data processing has become a prominent role in the resolution of decisions in industrial and service institutions according to the real need of these methods to make them scientific methods to solve the problem Making decisions for the purpose of making the departments succeed in performing their planning and executive tasks. Therefore, we found it necessary to know the transport model in general and to use statistical methods to reach the optimal solution with the lowest possible costs in particular. And you know The Transportatio

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