The antiviral activity of leaf extracts from Datura stramonium and tomato plants inoculated with TMV, combined with 20% skimmed milk, was investigated. A TMV isolate was confirmed using bioassay, serological, and molecular approaches and subsequently used to inoculate plants. Tomato plants, both pre- and post-inoculated with TMV, were sprayed with leaf extracts from either TMV-free or infected plants, alone or mixed with 20% skimmed milk. Enzyme-linked immunosorbent assay (ELISA) using tobamovirus-specific antibodies and local lesion tests were conducted to assess antiviral activity based on virus concentration and infectivity in treated plants. The experiment followed a completely randomized design (CRD), and the Least Significant Difference (LSD) test was applied to evaluate ELISA optical density (OD) values. OD data revealed that the combination treatment (inoculated tomato leaf extract + 20% skimmed milk) inhibited TMV in tomato plants by up to 56%, showing the highest antiviral activity. This study is the first to investigate the antiviral potential of leaf extracts from TMV-infected plants.
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.
The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
... Show MoreData mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu
... Show MoreThe aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di
... Show MoreWith 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
... Show MoreBackground: Legionella pneumophila (L. pneumophila) is gram-negative bacterium, which causes Legionnaires’ disease as well as Pontiac fever. Objective: To determine the frequency of Legionella pneumophila in pneumonic patients, to determine the clinical utility of diagnosing Legionella pneumonia by urinary antigen testing (LPUAT) in terms of sensitivity and specificity, to compares the results obtained from patients by urinary antigen test with q Real Time PCR (RT PCR) using serum samples and to determine the frequency of serogroup 1 and other serogroups of L. pneumophila. Methods: A total of 100 pneumonic patients (community acquired pneumonia) were enrolled in this study during a period between October 2016 to April 2017; 92 sam
... Show MoreBackground: 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
... Show MoreThis research deals with the study of the obstacles to peaceful coexistence in Iraq. Therefore, our hypothesis is that these obstacles are not attributed to one reason or to one source. Therefore, peaceful coexistence among the components of Iraqi society remains fragile and vulnerable to collapse and threat at any moment. This society, which is already in need of social relations, needs more than ever to coexist and consolidate it. Through the exercise of democracy in Iraq in a manner that guarantees rights and duties for all, to restore mutual trust between the components of this community in a way that feels they are citizens of the state.
Shifting Sand of English in Iraq language Policy and Planning
Anticyclone of synoptic studies that influence weather and climate of Iraq, The aim of
the study is to clarify the effect variation of repetition of Anticyclone and effect on thermal
characteristic in Iraq were pressure level has been analyzed (1000) millibars and that because
of pressure level is the closet to the earth surface and the clarity of climatic phenomenon
based on a systematic analysis of synoptic seeking maps and observation and (12:00)
according to timing GMT for five climatic stations which is (Mosul, Kirkuk, Baghdad, Rutba,
and Basra) and so far three consecutive climatic cycles which is first climatic cycle for period
(1986-1976). and second climatic cycle for period (1997-1987) and third climatic cy