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The Characterisation of the Craniofacial Morphology of Infants Born With Zika Virus; Innovative Approach for Public Health Surveillance and Broad Clinical Applications
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Background: This study was carried out in response to the Zika virus epidemic, which constituted a public health emergency, and to the 2019 WHO calling for strengthened surveillance for the early detection of related microcephaly. The main aim of the study was to phenotype the craniofacial morphology of microcephaly using a novel approach and new measurements, and relate the characteristics to brain abnormalities in Zika-infected infants in Brazil to improve clinical surveillance.

Methods: 3D images of the face and the cranial vault of 44 Zika-infected infants and matched healthy controls were captured using a 3D stereophotogrammetry system. The CT scans of the brain of the infected infants were analysed. Principal component analysis (PCA) was applied to characterise the craniofacial morphology. In addition to the head circumference (HC), a new measurement, head height (HH), was introduced to measure the cranial vault. The level of brain abnormality present in the CT scans was assessed; the severity of parenchymal volume loss and ventriculomegaly was quantified. Student's t-test and Spearman's Rho statistical test have been applied.

Findings: The PCA identified a significant difference (p < 0.001) between the cranial vaults and the face of the Zika infants and that of the controls. Spearman's rank-order correlation coefficients show that the head height (HH) has a strong correlation (0.87 in Zika infants; 0.82 in controls) with the morphology of the cranial vaults, which are higher than the correlation with the routinely used head circumference (HC). Also, the head height (HH) has a moderate negative correlation (−0.48) with the brain abnormalities of parenchymal volume loss.

Interpretation: It is discovered that the head height (HH) is the most sensitive and discriminatory measure of the severity of cranial deformity, which should be used for clinical surveillance of the Zika syndrome, evaluation of other craniofacial syndromes and assessment of various treatment modalities.

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Publication Date
Thu Nov 01 2018
Journal Name
Italian Journal Of Vascular And Endovascular Surgery
Retroperitoneal versus transperitoneal approach for aortoiliac occlusive disease: a comparative study
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Publication Date
Wed Jul 05 2017
Journal Name
Neural Computing And Applications
Hybrid soft computing approach for determining water quality indicator: Euphrates River
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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Efficient approach for solving high order (2+1)D-differential equation
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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Publication Date
Fri Jun 28 2024
Journal Name
The Iraqi Journal Of Veterinary Medicine
Aryl Hydrocarbon Receptor Modulation and Resveratrol Influence on Dnah1 Expression: Implications for Male Reproductive Health
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Male reproductive health is intricately regulated by molecular and physiological processes, with the aryl hydrocarbon receptor (AhR) playing a crucial role. AhR is activated by various ligands and influences the onset and progression of diseases. The aim of this study was to evaluate the role of AhR on spermatogenesis in adult male rats were affected by resveratrol (RES) and CH223191, an AhR antagonist. The study include forty rats were randomly divided into four equal groups: Control group, DMSO group, RES group and AhR‾ group, the rats received respective treatments intraperitoneally twice weekly for 60 days, and various parameters related to male reproductive health were evaluated. The AhR that activation by the RES treatment w

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Publication Date
Sat Feb 14 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Cranial base morphology in different skeletal classes (A cross-sectional lateral cephalometric study)
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Background: It was stated in scientific literatures that the entire craniofacial complex is influenced by the growth of the cranial base structures. Nevertheless, many times this is not the case, and this point is subject to great controversy so the aim of this study is to evaluate the possible differences in cranial base shape and flexure between different skeletal classes for both genders and to investigate any possible correlation between cranial base variables and other skeletal base variables. Materials and Methods: The sample include 75 lateral cephalometric radiographs of Iraqi adults aged between 18-25 years (39 males, 36 females), collected from patients and undergraduate students in the orthodontic department of College of Dentist

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using the Balanced Performance Approach to Increase the Effectiveness of Strategic Planning in order to Maximize the Job Satisfaction Rates at the Faculties of Bisha University
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Purpose: To use the balanced measurement approach as a strategic link for increasing the effectiveness of strategic planning in the direction of achieving satisfaction rates at Bisha University in Saudi Arabia

Design / methodology / approach –The questionnaire survey was used to collect the data of the study from the faculty members at University of Bisha.

Findings –Prove the assumption that the use of the balanced measurement approach - as a strategic planning tool - leads to maximize the satisfaction rates among faculty members at the University of Bisha.

Research limitations/implications-  adopt effective strategic planning in order to achieve

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