The present study was performed to detect the molecular and the phylogenetic identification of species that belonging to the genus of Moniezia Blanchard, 1891 which affected intestines of sheep in Al-Diwaniyah city, Iraq; fifty intestine samples were sought for the infestation of Moniezia spp. from the city slaughterhouse from 1 October to 30 November 2017, this tapeworm was found to infest the intestines of 13 sheep.

    For morphological identify the genus of this tapeworm, eggs from one gravid proglottid of the thirteen worms were examined, polymerase chain reaction (PCR) and the PCR-product-based sequencing were applied on 4 Moniezia tapeworms targeti

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

The current study was conducted on goats in various parts of Wasit Province, Iraq, from November 2021 to April 2022. The study aims to find and identify intestinal parasites (IPs) in goats in Wasit province. The goat's fresh fecal specimens (n=180) include cysts, eggs, oocysts, trophozoites and larval stages. One hundred eighty sheep feces samples were collected, and more than one parasite was isolated from one sample (mixed infection). According to the data acquired, the overall prevalence of intestinal parasites in goats was 52.77 (95 samples). In the current investigation, eleven distinct (IPs) species with infection rates were identified, including Toxocara vitulorum (Goeze, 1782) (16.66 %), Cryptosporidium sp.( Tyzzer, 1907) (1

Let G be a graph with p vertices and q edges and  be an injective function, where k is a positive integer. If the induced edge labeling   defined by for each is a bijection, then the labeling f is called an odd Fibonacci edge irregular labeling of G. A graph which admits an odd Fibonacci edge irregular labeling is called an odd Fibonacci edge irregular graph. The odd Fibonacci edge irregularity strength ofes(G) is the minimum k for which G admits an odd Fibonacci edge irregular labeling. In this paper, the odd Fibonacci edge irregularity strength for some subdivision graphs and graphs obtained from vertex identification is determined.

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)

Keys for 22 species representing ten genera Thripidae collection carried out during 1999-2001 in different localities in the middle of Iraq. Of them four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another thirteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.); Microcephalothrips abdominils (Crawford); Scolothrips pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Mar

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

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