This study aimed to detect Anaplasma phagocytophilum in horses through hematological and molecular tests. The 16S rRNA gene of the Anaplasma phagocytophilum parasite was amplified by polymerase chain reaction (PCR), then sequenced, and subjected to phylogenetic analysis to explore "Equine Granulocytic Anaplasmosis" (EGA) infection in three important gathering race horses areas in Baghdad governorate, Iraq. Blood samples were obtained from 160 horses of varying ages, three breeds, and both sexes, between January and December 2021. Prevalence and risk variables for anaplasmosis were analyzed using statistical odds ratio and chi-square tests. Results demonstrated that clinical anaplasmosis symptoms comprised jaundice, wei

Background: The Epstein-Barr virus (EBV) relates to the torch virus family and is believed to have a substantial impact on mortality and perinatal events, as shown by epidemiological and viral studies. Moreover, there have been documented cases of EBV transmission occurring via the placenta. Nevertheless, the specific location of the EBV infection inside the placenta remains uncertain. Methods: The genomic sequences connected to the latent EBV gene and the levels of lytic EBV gene expression in placental chorionic villous cells are examined in this work. A total of 86 placentas from patients who had miscarriage and 54 placentas from individuals who had successful births were obtained for analysis. Results: The research employed QPCR to dete

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Background : Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy of upper extremities and Open carpal tunnel release is the most frequent surgical procedure and the gold standard for cases that do not respond to conservative treatment. Aims :This study is used to evaluate the functional outcome of limited palmar mini-incision of carpal tunnel release. This study aims to determine the safety and symptomatic and functional efficacy of median nerve decompression with limited incision in carpal tunnel syndrome surgery. Patients and methods:Carpal tunnel release with a 1.5-2 cm limited palmar incision was performed on 20 patients. Patients were evaluated initially at one month after treatment according to symptom severity

The main aim of this study was to molecular identification and determine the antagonistic impact of rhizosphere Trichoderma spp. against some phytopathogenic fungi, including (Magnaporthe grisea) pyricularia oryzae, Rhizoctonia solani and Macrophomina phasolina. Four Trichoderma isolates were isolated from rhizosphere soils of the different host plants in different locations of Egyptian governorates. The morphological characterization of isolated Trichoderma as well as using of (ITS1-5.8S-ITS2) ribosomal gene sequence acquisition and data analyses. By comparing the results of DNA sequences of ITS region, the fungi represented one isolate were positively identified as T. asperellum (1 isolate T1) and one as T. longibrachiatum (1 isolate T2)

Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene