Listeria spp. is one of the abortion causative agents in animals, especially in ruminants. This work aimed to detect Listeria spp. in milk and aborted fetus cows in Iraq. A total of 50 organ samples from aborted cow fetuses, including (brain, liver, and spleen), and 50 milk samples from the same aborted cows were collected from Baghdad farms, Iraq from (October 2023- March 2024). The bacteria were identified by conventional culture methods, biochemical tests, and the VITEK2 compact system, followed by molecular confirmation. The antimicrobial resistance pattern assay was performed using the disc diffusion method against eight antibiotic agents, and the L.monocytogenes virulence genes involving prfA,actA, and hylA genes were detected using the PCR. The results revealed that only L. monocytogenes was detected at 2/50(4%) from aborted fetuses isolated from the brain and liver, while not in milk samples. The L.monocytogenes showed 100% resistance against erythromycin, ampicillin, cotrimoxazole, chloramphenicol, vancomycin, and tetracycline. At the same time, all the isolates had a high MDR and MAR (Multiple Antibiotic Resistance) index. This study concluded that L.monocytogenes is one of the abortion causative agents in cattle in Iraq, and the high antibiotic resistance of Listeria leads to economic loss and a possible risk to humans.
Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E
... Show MoreCybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
... Show MoreCybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
... Show MoreSoftware-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
... Show MoreAbstract The study aimed at reviewing translation theories proposed to address problems in translation studies. To the end, translation theories and their applications were reviewed in different studies with a focus on issues such as critical discourse analysis, cultural specific items and collocation translation.
The most important recommendations of this research are:-
1.The benefit of the other countries experiences about the transparency of the government performance, without depending on the transparency that imitating the other experiences; that may not fit with the Iraqi government units.
2.The Ministry of Finance has to prepare the citizen guidebook about the government performance which is considered an essential document, it should be simple and available for all the parties of relation; and for not specialized citizen for the purpose of simplifying the understanding of government performance details.
3.The benefit of the government units websites of inte
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