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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
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
ZnO: MWCNT optical hybrid filter a promising nanomaterial for wastewater treatment and antimicrobial applications
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Publication Date
Thu Dec 11 2014
Journal Name
Sensors
Automatic Frequency Controller for Power Amplifiers Used in Bio-Implanted Applications: Issues and Challenges
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With the development of communication technologies, the use of wireless systems in biomedical implanted devices has become very useful. Bio-implantable devices are electronic devices which are used for treatment and monitoring brain implants, pacemakers, cochlear implants, retinal implants and so on. The inductive coupling link is used to transmit power and data between the primary and secondary sides of the biomedical implanted system, in which efficient power amplifier is very much needed to ensure the best data transmission rates and low power losses. However, the efficiency of the implanted devices depends on the circuit design, controller, load variation, changes of radio frequency coil’s mutual displacement and coupling coef

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Publication Date
Sat Oct 28 2023
Journal Name
Journal Of Optics
Advancements and challenges in pulsed laser-deposited hydrophobic CeO2 film for broadband antireflection applications
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Due to the remarkable progress in photovoltaic technology, enhancing efficiency and minimized the costs have emerged as global challenges for the solar industry. A crucial aspect of this advancement involves the creation of solar cell antireflection coating, which play a significant role in minimizing sunlight reflection on the cell surface. In this study, we report on the optimization of the characteristics of CeO2 films prepared by pulsed laser deposition through the variation of laser energy density. The deposited CeO2 nanostructure films have been used as an effective antireflection coating (ARC) and light-trapping morphology to improve the efficiency of silicon crystalline solar cell. The film’s thickness increases as laser fluence i

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Sun Nov 17 2019
Journal Name
Journal Of Interdisciplinary Mathematics
Fuzzy preinvexity via ranking value functions with applications to fuzzy optimization problems
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Publication Date
Mon Mar 30 2026
Journal Name
Iraqi Journal Of Science
A modified time series model using conditional and unconditional estimations with applications to a real dataset
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Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
The Necessity of Teaching Diabetic Patients the Correct way of Insulin Administration: A Clinical Trial to Improve Glycemic Control
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Background: It is important to achieve good glycemic control to avoid long-term diabetic complications. It has been largely debated about the role of correct way of insulin administration to get the desired glycemic control.
Objective: To evaluate the effect of teaching diabetic patients who are on insulin therapy the correct way of injecting insulin and its effect on glycemic control.
Methods: A non randomized clinical trial with 820 diabetic patients on insulin therapy on whom A1 c estimation was performed before and after three months of teaching them the right injection technique.
Results : Sixty seven patients (8.17%) had A1 c 6.5% before they were enrolled in the study while the majority (753 patents, 91.82%) had A1 c 6.5%

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
The Necessity of Teaching Diabetic Patients the Correct way of Insulin Administration: A Clinical Trial to Improve Glycemic Control
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Background: It is important to achieve good glycemic control to avoid long-term diabetic complications. It has been largely debated about the role of correct way of insulin administration to get the desired glycemic control.
Objective: To evaluate the effect of teaching diabetic patients who are on insulin therapy the correct way of injecting insulin and its effect on glycemic control.
Methods: A non randomized clinical trial with 820 diabetic patients on insulin therapy on whom A1 c estimation was performed before and after three months of teaching them the right injection technique.
Results : Sixty seven patients (8.17%) had A1 c 6.5% before they were enrolled in the study while the majority (753 patents, 91.82%) had A1 c 6.5%

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of The College Of Basic Education
Preparation of Chalcones and their Applications in Heterocycles Synthesis
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Some new heterocyclic compounds containing, cyclohexenone, indazole, isoxazoline, pyrmidine and pyrazoline ring system were prepared from chalcones (1a,b). The starting chalcones (1a,b) were obtained by a base catalyzed condensation of appropriately substituted benzaldehydes and 2-acetylbenzofuran. The reaction of the prepared chalcones with ethylacetoacetate/hydrazine hydrate, hydroxylamine hydrochloride, urea, thiourea, hydrazine hydrate, phenyl hydrazine or hydrazide derivatives gave the mentioned heterocycles. All synthesized compounds have been characterized by physical and spectral methods.

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