Cybersecurity 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

Cybersecurity 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

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Software-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

Chitinase-3-like 1 protein (YKL-40) is a glycoprotein primarily produced in the arthritic joint and plays a crucial role in inflammatory processes. The aim of the study is to establish the role of YKL-40 as a biomarker for rheumatoid arthritis (RA) compared to proinflammatory biomarkers and disease activity. The study included 58 patients and 18 control. Diseases activity score (DAS-28) and clinical disease activity index (CDAI) were measured. Serum level of YKL-40, tumor necrosis factor-α (TNF-α), interleukin-1B (IL-1β), erythrocyte sedimentation (ESR), rheumatoid factor (RF), C-reactive protein (CRP), and anti-citrullinated protein antibody (ACPA) were assessed. The results showed that the median serum YKL-40 level which was 5.42 

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

This study was done at Al-Balad City Hospital on 60 diabetic patients (25 male and 35 female). The study included Fasting Blood Sugar and fungal diagnosis (systemic and superficial fungus). The results showed that the high concentration of blood sugar belonged to the group > 70 years among the diabetic patients with high significant differences in comparison with other groups P<0.001 . The result showed that percentage of female systemic fungus infection was higher than male systemic fungus infection ( female 63% and male 24%) and vice versa about superficial fungus infection (female 37% and male 76%) . Data showed that the percentage of nail fungus infection among female diabetic patients was higher than the percentage of male diabetic p

Breast cancer is the most common malignancy affecting women's health, with an increasing incidence worldwide. This study aimed to measure the intracellular concentration of the hypoxia-inducible factor 1 α (HIF-1α), tumor suppression protein p53, and estradiol (E2) in tumor tissues of adult females with breast cancer and their relation to tumor grade, tumor size, and lymph node metastases (LNM). The study was conducted on 65 adult female participants with breast mass admitted to the operating theater in Al-Hussein Teaching Hospital and Al-Habboby Teaching Hospital in Nasiriyah, Iraq, from January to November 2021. Fresh breast tumor tissues were collated and homogenized for intracellular biochemical analysis using the enzyme-linked immuno