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

Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit

Objectives: The study aims to: (1) assess psychological distress in parents of autistic children, (2) identify the
relationship between psychological distress and parents' socio-demographic characteristics such as (age, marital
status, relationship with child, educational level and monthly income) and (3) identify the relationship between
parent's distress and some of children' socio-demographic characteristics such as (gender, age, birth order and
mean number of children).
Methodology: A descriptive–analytical study that was carried out from December 12th, 2011 to May 1st, 2012.
on a purposive (non- probability) sample of 120 parents (father and mother) who have children with autism and
send their children to the

The quality of groundwater should be improved by keeping safe water sources from contaminants in protective way by doing regular measuring and checkup before it supplied for usage. Private Wells do not receive the same services that wells supplying the public do. Well owners are responsible for protecting their drinking water. This work was carried out in Badra city, Iraq from December 2017 to May 2018, six wells water were investigated to determine the general characteristics of wells as well as studying the effect of environmental factors on the quality of water. The average of six wells were eleven parameters that is out of permissible limits were EC, Sal., Alk., TH, TDS, Na, Ca, Cl, SO₄, Fe, Zn (4402-5183 /cm, 2.76-3.9 ppt

The flavonoglycone hesperidin is recognized as a potent anti-inflammatory, anticancer, and antioxidant agent. However, its poor bioavailability is a crucial bottleneck regarding its therapeutic activity. Gold nanoparticles are widely used in drug delivery because of its unique properties that differ from bulk metal. Hesperidin loaded gold nanoparticles were successfully prepared to enhance its stability and bioactive potential, as well as to minimize the problems associated with its absorption. The free radical scavenging activities of hesperidin, gold nanoparticles, and hesperidin loaded gold nanoparticles were compared with that of Vitamin C and subsequently evaluated in vitro using 2,2-diphenyl-1-picrylhydrazyl assay. The antioxi

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

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