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Microbiological Identification of Bacteria with Leukemic Children
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The most common form of childhood cancer is leukemia, Calculation for more than one third of all childhood cancers among those ages 1 day – 14 years. The diseases of leukemia are worldwide, it occurred in both genders from male and females and in all age. A total of 80 different samples of patient children were collected from the central teaching hospital of pediatric in Baghdad. Obtained during the period from 1st Sept. 2019 till the 31 th of Aug. 2020. Each isolates identification by using Vitek 2. Isolated organism in leukemic children show 18 (22.5 %) gram positive and 62 (77.5 %) gram negative from the total sample 80 (100.0 %). The percent of male is 45 more than female which represents 35 in most age groups between age (1 day-3 year) 33 (100.0 %). In most distribution of organism according to the type of sample for gram positive is Staphylococcus aureus 13 (16.2 %) and gram negative Escherichia coli 21 (26.3 %), Klebsiella pneumoniae 13 (16.2 %), Pseudomonas aeruginosa 11 (13.8 %) from the total results 80 (100.0 %). In conclusion, the gram negative bacteria is more than gram positive bacteria and especially effect with Escherichia coli, and Staphylococcus aureus, in males for the age group 1 day to 3 years. And the most antibiotic sensitive to Escherichia coli is Imipenem, Amikacin, Gentamycin, Piperacillin/ Tazobactam and resist to Cefotazidime, Tobramycin, Cefepime, Ceftriaxone, Ciprofloxacin and Staphylococcus aureus most sensitive to Vancomycin, Gentamycin, Clindamycin, and resist to Penicillin, Cefotaxime, Ceftriaxone, Oxacillin.

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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Antibacterial Activity of Lactiplantibacillus plantarum‎ from Dairy Products ‎Against Some ‎Foodborne Bacteria
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Lactiplantibacillus plantarum‎, one of lactic acid bacteria (LAB), is found in various foods, ‎‎including dairy products, meat, and vegetables, and most of these bacteria offer beneficial ‎‎effects to humans and animals as potential probiotics with broad-spectrum antimicrobial ‎‎activities. The aim of this study was evaluating the antibacterial efficacy of L. ‎plantarum‎ ‎against ‎some foodborne bacteria isolated from dairy products. This research involved 34 dairy ‎products, ‎including local and imported milk, cheese, and yogurt sold locally in Baghdad ‎province, Iraq, during May ‎‎2022. For the isolation of L. ‎plantarum‎, a special medium called ‎MRS (de Man Rogosa and ‎Sharpe) was applied. Colonie

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Publication Date
Thu Aug 01 2019
Journal Name
2019 2nd International Conference On Engineering Technology And Its Applications (iiceta)
Human Gait Identification System Based on Average Silhouette
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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Proposed Hybrid Sparse Adaptive Algorithms for System Identification
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Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Tools for Drought Identification and Assessment: A Review
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Drought is a natural phenomenon in many arid, semi-arid, or wet regions. This showed that no region worldwide is excluded from the occurrence of drought. Extreme droughts were caused by global weather warming and climate change. Therefore, it is essential to review the studies conducted on drought to use the recommendations made by the researchers on drought.  The drought was classified into meteorological, agricultural, hydrological, and economic-social. In addition, researchers described the severity of the drought by using various indices which required different input data.  The indices used by various researchers were the Joint Deficit Index (JDI), Effective Drought Index (EDI), Streamflow Drought Index (SDI), Sta

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
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 p

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Publication Date
Sat May 27 2023
Journal Name
Online Journal Of Animal And Feed Research
Phylogenetic identification of Anaplasma phagocytophilum in horses in Baghdad, Iraq
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This study aimed to detect Anaplasma phagocytophilum in horses through hematological and molecular tests. The 16S rRNA gene of the Anaplasma phagocytophilum parasite was amplified by polymerase chain reaction (PCR), then sequenced, and subjected to phylogenetic analysis to explore "Equine Granulocytic Anaplasmosis" (EGA) infection in three important gathering race horses areas in Baghdad governorate, Iraq. Blood samples were obtained from 160 horses of varying ages, three breeds, and both sexes, between January and December 2021. Prevalence and risk variables for anaplasmosis were analyzed using statistical odds ratio and chi-square tests. Results demonstrated that clinical anaplasmosis symptoms comprised jaundice, wei

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Molecular Identification of Aspergillus fumigatus Using ISSR and RAPD Markers
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The aim of this stud to isolate and identified of A. fumigatus from different sources and study the genetic diversity among these isolates by using RAPD and ISSR markers.Collected 20 samples from 7samples were isolated A. fumigatusisolates were characterized depending on its morphological, then extracted DNA from its.RAPD markersrandomly bandingwith sitesof genome more than ISSR markers where the primer OPN-07 achieved discriminative power (19.1) and 43 bands, while ISSR6 achieved discriminative power (17.1) with 32 bands.ISSR were more efficiency in specific binding then RAPD, ISSR primers has great a binding to production unique band, when 9 primers from 01 primers, ISSR9 was produce (5) unique bands, while RAPD markers was low ability

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Publication Date
Sun Dec 31 2023
Journal Name
Advancements In Life Sciences
Molecular identification of Epstein-Barr virus in human placental tissue
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Background: The Epstein-Barr virus (EBV) relates to the torch virus family and is believed to have a substantial impact on mortality and perinatal events, as shown by epidemiological and viral studies. Moreover, there have been documented cases of EBV transmission occurring via the placenta. Nevertheless, the specific location of the EBV infection inside the placenta remains uncertain. Methods: The genomic sequences connected to the latent EBV gene and the levels of lytic EBV gene expression in placental chorionic villous cells are examined in this work. A total of 86 placentas from patients who had miscarriage and 54 placentas from individuals who had successful births were obtained for analysis. Results: The research employed QPCR to dete

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Molecular identification of dermatophytes by arbitrarily primed polymerase chain reaction
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Publication Date
Mon Jan 01 2024
Journal Name
Communications In Computer And Information Science
Automatic Identification of Ear Patterns Based on Convolutional Neural Network
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

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