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Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details provided by the X-ray images dataset, the study showed that the using of X-ray data set in our deep learning algorithm could provide promising results by getting accuracy of validation for both Convolution Neural Network and SequeezeNet models 93%, 76%, respectively while the validation loss in both models Convolution Neural Network and SequeezeNet 34%, 30% respectively, these promise results will make the physician give a swift decision in diagnosis of lung cancer and keeping the patients away from exposing to unnecessary extra radiation dose during the Computed Tomograph exam as well as the low cost of X-ray examination comparing with Computed Tomograph exam.

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Publication Date
Wed Jul 29 2020
Journal Name
Frontiers In Physiology
Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) in Human Lung Microvascular Endothelial Cells Controls Oxidative Stress, Reactive Oxygen-Mediated Cell Signaling and Inflammatory Responses
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Publication Date
Tue Jun 16 2020
Journal Name
Synthetic Communications
Synthesis, identification and molecular docking studies of N-functionalized piperidine derivatives linked to 1,2,3-triazole ring
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Publication Date
Wed Feb 15 2017
Journal Name
Global Journal Of Bio-science And Biotechnology
ISOLATE AND IDENTIFICATION OF PSEUDOMONAS AERUGINOSA FROM CONTAMINATED SOIL WITH HYDROCARBONS DISCHARGED FROM GAS FILLING REFINERIES
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Petroleum is one of the most important substances consumed by man at present times, a major energy source in this century, petroleum oils can cause environmental pollution during various stages of production, transportation, refining and use, petroleum hydrocarbons pollutions ranging from soil, ground water to marine environment, become an inevitable problem in the modern life, current study focused on bioremediation process of hydrocarbons contaminants that remaining in the bottom of gas cylinders and discharged to the soil. Twenty-four bacterial isolates were isolated from contaminated soils all of them gram negative bacteria, bacterial isolates screening to investigate the ability of biodegradation of hydrocarbons, these isolates inocula

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Morphological and Molecular Identification of Limnodrilus Claparede,1862 Species(clitellata: naiDIDAE) IN Tigris River, Baghdad/Iraq
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Sludge worm samples were collected from the Tigers River sediment during the period from November 2018 to June 2019 in Al Sarafiya District/ Baghdad- Iraq. Biometric morphological measurements focusing on the form of penis sheath and chaetal morphology were used for species identification, in addition to molecular analysis by amplification of conserved 18s rRNA encoding gene using ITS1 and ITS4 universal primers.According to the morphological measurement records, the results revealed the existence of Limnodrilus hoffmeisteri Claparede 1862, L. claparedeianus Ratzel, 1868 and L. cervix Brinkhurst 1963. Other two groups of specimens, with short penis sheath, were identified by molecular technology as L

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Identification of Candida species Isolated From Vulvovaginal Candidiasis Patients by Chromgen agar and PCR-RFLP Method
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This study focuses on diagnosis of Candida species causing Vulvovaginal Candidiasis using phenotype and genotype analyzing methods, and frequencies of candida species also using Vulvovaginal Candidiasis patients. 130 samples (100 from patients and 30 from non infected women) were collected and cultured on biological media. Identifying the yeasts, initially some phenotypic experiments were carried out such as germ tube, from motion of pseudohyphae and clamydospores in CMA+TW80 medium, API20 candida and CHROMagar Candida. Genomic DNA of all species were extracted and analyzed with PCR and subsequent Polymerase Chain Reaction - Restriction Fragments Length Polymorphism (PCR-RFLP) methods. Frequency of C. albicans, C. krusei, C. tropicalis , C.

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Publication Date
Fri Dec 20 2024
Journal Name
Bulletin Of The Iraq Natural History Museum
ISOLATION AND IDENTIFICATION OF EIMERIA SCHNEIDER, 1875 SPECIES (APICOMPLEXA, EIMERIIDAE) FROM GOATS IN WASIT PROVINCE, IRAQ
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Eimeriosis is a major problem affecting ruminants worldwide. The disease is primarily caused by Eimeria species, which are specialized for each host and grow in the small and large intestine of animals. The losses due to subclinical infections (especially weight loss) and clinical disease (diarrhea) make the species of this genus a very significant economic concern. Therefore, this study was conducted in some areas of Wasit Province. A total of 180 fecal samples from goats, of both sexes and covering different age groups and months, were collected. All fecal samples were examined microscopically, and 75 positive fecal samples were taken for molecular examination and further analyzed using conventional PCR, sequencing and phylogeneti

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Publication Date
Fri Apr 16 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education
Effective reading skills and their relationship to deep understanding of chemistry among middle school students in Iraq
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Publication Date
Fri Jul 01 2022
Journal Name
Health Science Reports
Immunohistochemical expression of angiotensin‐converting enzyme 2 in superficial and deep maxillofacial tissues: A cross‐sectional study
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Abstract<sec><title>Background and Aims

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

Methods

The immunohistochemical expression of ACE2 was analyzed in 95 specimens from maxillofacial tissues and 10 specimens o

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Transient response and performance of prestressed concrete deep T-beams with large web openings under impact loading
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Abstract<p>This study reports testing results of the transient response of T-shape concrete deep beams with large openings due to impact loading. Seven concrete deep beams with openings including two ordinary reinforced, four partially prestressed, and one solid ordinary reinforced as a reference beam were fabricated and tested. The effects of prestressing strand position and the intensity of the impact force were investigated. Two values for the opening’s depth relative to the beam cross-section dimensions were inspected under the effect of an impacting mass repeatedly dropped from different heights. The study revealed that the beam’s transient deflection was increased by about 50% with gre</p> ... Show More
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Deep Desulfurization of Diesel Fuel by Guard Bed Adsorption of Activated Carbon and Locally Prepared Cu-Y Zeolite
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Desulfurization of a simulated diesel fuel by different adsorbents was studied in a fixed-bed adsorption process operated at ambient temperature and pressure.  Three different adsorption beds were used, commercial activated carbon, Cu-Y zeolite, and layered bed of 15wt% activated carbon followed by Cu-Y zeolite.Initially Y-zeolite was prepared from Iraqi rice husk and then impregnated with copper. In general, the adsorbents tested for total sulfur adsorption capacity at break through followed the order Ac/Cu-Y zeolite>Cu-Y zeolite>Ac. The best adsorbent, Ac/Cu-Y zeolite is capable of producing more than 30 cm3 of simulated diesel fuel per gram of adsorbent with a weighted average content of 5 ppm-S, while Cu-Y zeolite producing of

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