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bsj-1527
Rapid Detection of Aspergillus flavus isolates producing aflatoxin using UV light on different culture media
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This study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able to produce aflatoxin .results also indicated that the best medium for toxin production was (COA) followed by (PDA and YEA), whereas the suitable temperature and incubation period for toxin production was 35?c and 7 days.

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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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
Sat Jun 15 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Proteoytic Activity and Swarming Growth of Proteus spp. Isolates.
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Many clinical isolates of proteus spp. (30 isolates of P
mirabilis and 30 isolates of P. vulgaris) from patients with urinary
tract infections (UTIs) were examined for their ability to produce
proteolytic enzymes and their ability to form swarming growth. Most
(90%) of P. mirabilis and 60% of P. vulgaris isolates secreta
proteolytic enzymes. A strong correlation was found between the
ability of a strain to secreted proteases and it's ability to form
swarming growth. Non- swarming isolates invariably appeared to be
non- proteolytic. However, some isolates (12 isolates of P. vagaries)
were non- proteolytic even when they formed swarming growth

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Publication Date
Wed Oct 31 2018
Journal Name
Iraqi Journal Of Science
Identification of Cryptococcus neoformans Isolates by PCR-ITS regions
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The aim of the study was molecular detection of C. neoformans that isolated from 150 (88 female and 62 male) clinical samples (sputum samples) from pulmonary patients in Baghdad. The diagnoses of Cryptococcus neoformans in samples was done by using direct microscopic examination, culture media and PCR Technology. Microscopic examination and cultured revealed that 65 out of 150 (43.33 %) samples were positive and the others samples were Negative. Results of the genetic diagnosis looking for the fungi causing cryptococcosis using primers specific for ITS gene which were specially designed for this study revealed that 6 (4 %) of sputum samples were positive. In this study used the PCR technology due to the present

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Impact of Porous Media on Peristaltic Transport of Tangent Hyperbolic Nanofluid in Asymmetric Channel
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The purpose behind this paper is to discuss nanoparticles effect, porous media, radiation and heat source/sink parameter on hyperbolic tangent nanofluid of peristaltic flow in a channel type that is asymmetric. Under a long wavelength and the approaches of low Reynolds number, the governing nanofluid equations are first formulated and then simplified. Associated nonlinear differential equations will be obtained after making these approximations. Then the concentration of nanoparticle exact solution, temperature distribution, stream function, and pressure gradient will be calculated. Eventually, the obtained results will be illustrated graphically via MATHEMATICA software.

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
The Effects of Media Coverage on the Dynamics of Disease in Prey-Predator Model
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In this paper, an eco-epidemiological model with media coverage effects is established and studied. An -type of disease in predator is considered.  All the properties of the solution of the proposed model are discussed. An application to the stability theory was carried out to investigate the local as well as global stability of the system. The persistence conditions of the model are determined. The occurrence of local bifurcation in the model is studied. Further investigation of the global dynamics of the model is achieved through using a numerical simulation.

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Publication Date
Mon Apr 24 2023
Journal Name
Materials Research Innovations
Surface modification of poly(methyl methacrylate)-sulphadiazine complexes as self photostabilizer against Ultraviolet (UV) Irradiation
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Publication Date
Wed Oct 23 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
EXTRACTION OF JOJOBA OIL USING VARIOUS CONCENTRATIONS OF TWO DIFFERENT SOLVENTS
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The aim of this study was extraction of jojoba oil using different solvents. A mixture of waterhexane and water-ethanol are used as solvents to extract jojoba oil in a batch extraction process and compared with a pure solvent extraction process. The effects of particle size of crushed seeds, solvent-to-water ratio and time on jojoba oil extraction were investigated. The best recovery of oil was obtained at the boiling temperature of the solvent and four hour of extraction time. When seed particle size was 0.45 mm and a pure ethanol was used (45% yield of oil extraction), whereas, it was 40% yield of oil at 25% water-hexane mixture. It was revealed that the water-ethanol and water-hexane mixtures have an effect on the oil extraction yield. T

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