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Detection of Genetic Relationship Between Eucalyptus Species in Iraq
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Abstract<p>Environmental factors that damage plant cells by dehydrating them, such cold, drought, and high salinity, are the most common environmental stresses that have an impact on plant growth, development, and productivity in cultivated regions around the world. Several types of plants have several drought, salinity, and cold inducible genes that make them tolerant to environmental challenges. The purpose of this study was to investigate several species in <italic>Eucalyptus</italic> plants and determined the evolutionary descent between different species of <italic>Eucalyptus</italic>. Samples from plants were used to extract genomic DNA. After sequence methods with phylogenetic analysis using MEGA6, program. According to our findings, demonstrate that the sequences of several spp. were submitted to Gene Bank: <italic>E. alba</italic> (OP696606.1), <italic>E. bortryoides</italic> (OP696601.1), <italic>E. camaldulensis</italic> (OP696607.1), <italic>E. curtisii</italic> (OP696596.1), <italic>E. delegatensis</italic> (OP696604.1), <italic>E. erythrocorys</italic> (OP696599.1), <italic>E. globoidea</italic> (OP696597.1), <italic>E. leucoxylon</italic> (OP696598.1), <italic>E. macarthurii</italic> (OP696610.1), <italic>E. nicholii</italic> (OP696602.1), <italic>E. pauciflora</italic> (OP696603.1), <italic>E. siderophloia</italic> (OP696605.1), <italic>E. tereticornis</italic> (OP696611.1), and <italic>E. vicina</italic> (OP696608.1). These genes can be used to create crop plants that are resistant to drought.</p>
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Publication Date
Thu Jul 01 1999
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
Insects associated with inflorescence rot disease of date in Iraq
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Four species of insects, Carpophillus obsoletus Er., Carpophilus sp., Bitoma lycnformis Wall and Scatopse sp., were found in association with infected spathes of date palm with Mauginella scaettae Cav. The later fungus was the dominant species isolated in pure cultures both from diseased spathes and from contaminated insects. Bitoma lycriformis is the first record for Iraq.

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Plant Pathology
Molecular characterization of potyviruses infecting potato and vegetables in Iraq
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Pharmaceutical Research
Characters anatomy of CorchorusolitoriusL. from Malvaceae family cultivated in Iraq
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Publication Date
Sun Jul 17 2022
Journal Name
Pharmacy Education
Students' experience and evaluation of community pharmacy internship in Iraq
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Background: Pharmacy internship programmes are driven by most developed countries to outweigh the ongoing growth in the pharmacy career which encourages pharmacists to play a significant role as healthcare providers.    Objectives: This study examines pharmacy students' perception, satisfaction, challenges, and limitations with the internship curriculum.    Method: A cross-sectional study was conducted using an online survey with different elements to examine students' perceptions of various aspects.    Result: Most students reported a positive impression regarding their internships, however, they were less satisfied with the allowance for filling prescriptions and compounding also, the college's follow-up was inadequate. F

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Publication Date
Fri Dec 03 2021
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
The Influence E-Learning Platforms of Undergraduate Education in Iraq
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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Thu Apr 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Automatic human ear detection approach using modified adaptive search window technique
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Publication Date
Tue Oct 01 2019
Journal Name
2019 International Conference On Electrical Engineering And Computer Science (icecos)
An Evolutionary Algorithm for Community Detection Using an Improved Mutation Operator
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Publication Date
Wed Jun 24 2015
Journal Name
Chinese Journal Of Biomedical Engineering
Single Channel Fetal ECG Detection Using LMS and RLS Adaptive Filters
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ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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