Bovine theileriosis, caused by Theileria annulate, is disease affecting cattle and buffaloes worldwide. The current study aimed to screen the blood samples of 30 naturally suspected local buffaloes infected with Theileria species. The blood samples were initially examined by light microscopic and then the positive samples were subjected to PCR reactions. All 30 animals indicated clinical symptoms, such as high fever, loss of appetite, the presence of the hard tick, and enlargement of lymph nodes. The amplified products of 18S rRNA were analyzed, along with molecular detection of the drug-binding site alterations and interrelated changes in the cytochrome b (cyto b) gene. Blood smears revealed the presence of infected erythrocytes with Theileria spp. The PCR results confirmed infection in samples when DNA amplified with partial 18S rRNA and cyto b genes. The sequencing data were obtained from GeneBank using the accession numbers OM937770.1, ON207523.1, ON207525.1, ON207524.1, ON207526.1, and ON207527.1 Following BLAST analysis (Basic Local Alignment Search Tool), genetic differences were observed between the Iraqi isolate OM937770.1 and strains from India, Iran, and Turkey. The data obtained from the current study may reveal the genetic alteration of the local strain in the drug-target codons, which are found in one isolate and are different from the GenBank isolates. The results suggest that the failure of buparvaquone therapy might be due to the resistance to cyto b gene.
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.
One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad
... 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 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 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 MoreObjective: Detection the level of YKL-40 biochemical marker and vitamin D level in sera of Iraqi uterine cancer
females' patients.
Methodology: This study included 90 female volunteers, 30 of them were healthy volunteers who were
considered as a control group, while sixty serum samples were collected from women patients suffering from
uterine tumors (30 malignant and 30 fibroid benign tumors), benign cases were considered as a disease
control group for malignant tumors. The average age of those females was 30-75 years, which matched the
control group. All the samples were collected from Azady hospital in Kirkuk and the gynecologic department at
Medical City in Baghdad during October /2012 to May /2013. All the serum
Objective: The aim of this study is to detect the effect of continuous exposure to Sodium Nitrite on 8-oxoguanine
DNA glycosylase (OGG1) gene which responsible on DNA repairs. DNA repair play a major role in maintaining
genomic stability when DNA exposure to damage. Genomic stability is very important for keeping body cells
healthy and to prevent many types of tumor development. Many genes are responsible for this job; one of them is
OGG1 gene.
Methodology: In current study two groups of mice were chronically exposed to sodium nitrite for six months and
eighteen months while third group was used as a control. Then sizes of OGG1 were estimated.
Results: The results exhibited in the unexposed (control) mice had two dif
Polycystic ovarian syndrome (PCOS) is increasingly recognized as a significant health concern among women of reproductive age, exerting its influence on the reproductive system and overall female physiology. Paraoxonase-1 (PON1) gene polymorphism, -108 C >T in the promoter region, have been identified as factors that influence both the stability of the enzyme and its active site. This, in turn, contributes to increase oxidative stress, a recognized risk factor associated with PCOS. This study aimed to investigate the connection between paraoxonase-1-108 C >T gen polymorphisms with PCOS in Iraqi women in a case-control study included 40 women with PCOS and 40 women with normal cycles and no symptoms of
... Show MoreThere are many events which causes nonproductive time (NPT) in the drilling industry. The mostly effective in this NPT is pipe sticking event. A considerable amount of time and resources can be spent in efforts to free a stuck pipe. In addition, Unsuccessful fishing operations results in costly alternatives including side-tracking. The drilling in Khabaz oil field poses many operational challenges among of them stuck pipe , lost circulation, flow of salt water during drilling, and hole caving. Stuck pipe can be considered the quite difficult problem in Khabaz oil field due to associated incidents which lead to NPT activities.Well Khabaz -34 was selected to study the problem of stuck pipe in this field. An analysis of stuck pipe even
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