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

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

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

Poly methyl methacrylate PMMA polymer could be considered the main material that used mostly in the recent years in denture base fabrication. It commonly known by it is poor strength properties such as low impact strength. The aim of the present research was to enhance the performance of PMMA denture base through the addition of two kind of nanoparticles (nano particles that selected from artificial and natural sources). Nano -particles from both Al2O3 and crushed peanut Peel were used for comparing purposes.Various weight fraction used in this study for both kinds of the additive (1%, 2% and 3%). Moreover, in this work a study and evaluation in impact strength (I.S.) value were done before and after immersion. The new prepared nanocompo

The experiment was conducted in the old botanical garden belong to Biology Department/ College of Education for Pure Science - Ibn Al-Haitham/Baghdad University for growing season 2015-2016 to study the effect of irrigation with four concentrations of sodium chloride (0, 50, 100, 150) mM.L-1 and spraying with selenium in three concentrations (0, 10, 20) mgL-1 on growth of broad bean plant using clay pots. The experiment was design according to completely randomized design (CRD) with three replications. Results indicated that broad bean plant irrigated with saline water and increasing concentrations of sodium chloride in growth medium caused a significant decreased in the plant growth parameters (plant height, no. of compound leaves. Plant-1

A fluorescence microscopy considered as a powerful imaging tool in biology and medicine. In addition to useful signal obtained from fluorescence microscopy, there are some defects in its images such as random variation in brightness, noise that caused by photon detection and some background pixels in the acquired fluorescence microscopic images appear wrongly auto-fluorescence property. All these practical limitations have a negative impact on the correct vision and analysis of the fluorescent microscope users. Our research enters the field of automation of image processing and image analysis using image processing techniques and applying this processing and analysis on one of the very important experiments in biology science. This research

Background: L. sativum, are traditionally used for the treatment of various diseases and thought to have medicinal value. Isolates from many part of the world is now multidrug resistant. Therefore, there is an urgent need to look for and test an alternative herbal drug.

Objective: The present study aimed to evaluate the antibacterial activity of L. Sativum seed extract against multi drug resistant (MDR) and sensitive Pseudomonas aeruginosa clinical isolates.

Subjects and Methods: An ethanolic and aqueous stock extracts were prepared from L.  sativum seed plant then serial dilutions were prepared and the obtained concentrations (50, 25, 12.5 and 6.2 mg/ml) were tested against 30 multidrug-resistan

The pandemic SARS-CoV-2 is highly transmittable with its proliferation among nations. This study aims to design and exploring the efficacy of novel nirmatrelvir derivatives as SARS entry inhibitors by adapting a molecular modeling approach combined with theoretical design. The study focuses on the preparation of these derivatives and understanding their effectiveness, with a special focus on their binding affinity to the S protein, which is pivotal for the virus’s access to the host cell. Considering molecular docking aspects in the scope of a study on nirmatrelvir derivatives and S protein, dynamics simulations with 25 nanoseconds of their binding are explored. The study shows that these derivatives might work as effective antivi