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Transfocation Technique to Overcome Atmospheric Scintillation Effect on a Laser Detection and Tracking System (LDTS)
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Atmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geometric optical law. So tracking is possible only in the range from 3 to 11 km, depending on tracking criteria. Target image size minimized to required ratio by using transfocation technique to overcome tracking filler, this technique uses zoom lens.
We find that atmospheric scintillation is affective parameter which reduced the maximum tracking range, and to avoid tracking failure at minimum and maximum range, the transfocation technique is suitable

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Publication Date
Fri Jun 03 2016
Journal Name
Al- Kindy College Medical Journal
Laser Diode Enhances Autologous Cartilage Graft's Expansibility
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Background: Cartilage forms most of the temporary skeleton of the embryo and provides a model in which most bones develop Objective: Using laser therapy to enhance autologous cartilage grafts expansibility and to analyze whether this "enhancement" results in reduced rates of cartilage resorption and greater preservation of normal architectural features compared with "unenhanced" grafts. Type of the study: Cross sectional study. Methods: 24 New Zealand rabbits were divided into two groups (control and treated with 904nm, 10mW diode laser). Auricular cartilage segments measuring 1 cm2 were harvested from both ears of each rabbit, and were implanted in to the subcutaneous region of the left flank. 3 rabbits from each group were anaesthetized a

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Laser Diode Enhances Autologous Cartilage Graft's Expansibility
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Background: Cartilage forms most of the temporary skeleton of the embryo and provides a model in which most bones developObjective: Using laser therapy to enhance autologous cartilage grafts expansibility and to analyze whether this "enhancement" results in reduced rates of cartilage resorption and greater preservation of normal architectural features compared with "unenhanced" grafts. Type of the study: Cross sectional study.Methods: 24 New Zealand rabbits were divided into two groups (control and treated with 904nm, 10mW diode laser). Auricular cartilage segments measuring 1 cm2 were harvested from both ears of each rabbit, and were implanted in to the subcutaneous region of the left flank. 3 rabbits from each group were anaesthetized

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Publication Date
Thu Jul 20 2023
Journal Name
Polymers In Medicine
Effect of subinhibitory doses of rifaximin on in vitro Pseudomonas aeruginosa adherence and biofilm formation to biotic and abiotic surface models
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Publication Date
Sat Oct 03 2009
Journal Name
Proceeding Of 3rd Scientific Conference Of The College Of Science
Research Address: New Multispectral Image Classification Methods Based on Scatterplot Technique
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Detection, purification and characterization of a bacteriocin produced by Bacillus subtilis NK16 exhibits a significant antimicrobial activity against clinical Staphylococcus spp.
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Bacteriocin is an important antimicrobial peptide that can be used in industrial and medical fields due to its characteristics of antibacterial, food preservation and anticancer activities. Fifty isolates of Bacillus sp were collected from different soil samples which were already recognized via morphological and biochemical identification process. The isolates were screened for bacteriocin production effective against Staphylococcus spp in order to select the highest producing isolate. The isolate NK16 showed the maximum bacteriocin production (80 AU/ml) which was further characterized as Bacillus subtilis NK 16 through using API identification system (API 20E and API 50CHB). Then, next step was to detect the optimal conditions for maximum

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Publication Date
Tue Feb 17 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of incorporating carbon nanotubes on impact, transverse strength, hardness, and roughness to high impact denture base material
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Background: One of the most common complications of dentures is its ability to fracture, so the aim of this study was to reinforce the high impact denture base with carbon nanotubes in different concentrations to improve the mechanical and physical properties of the denture base. Materials and methods: Three concentrations of carbon nanotubes was used 0.5%, 1%, 1.5% in a pilot study to see the best values regarding transverse strength, impact, hardness and roughness test, 1 wt% was the best concentration, so new samples for control group and 1wt% carbon nanotubes and the previous tests were of course repeated. Results: There was a significant increase in impact strength and transverse strength when we add carbon nanotubes in 1wt%, compared

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Publication Date
Thu Jun 15 2017
Journal Name
Pakistan Journal Of Nutrition
Effect of Adding Dietary Conjugated Linoleic Acid to Broiler Diets on Production Performance and Fatty Acid Content in Meat
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Conjugated Linoleic Acid (CLA) is an essential polyunsaturated omega fatty acid that occurs naturally in vegetable oils. It also plays an important role in preserving meat for longer periods by preventing oxidation of other fats. Thus, it can be used in the production of functional foods with high biological value and low cholesterol levels by adding poultry diets. Objective: The aim of the present study was to evaluate the effect of adding CLA to broiler diets on production performance and fatty acid content in the meat. Methodology: One-day-old Ross-308 chicks were randomly distributed into four dietary treatment groups: control (0 g CLA kgG1 diet; A1), 0.5 g CLA kgG1 diet (A2), 0.75 g CLA kgG1 diet (A3) and 1 g CLA kgG1 diet (A4). Diets

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