Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

EGFR-mutant non–small cell lung cancer (NSCLC) initially responds well to EGFR tyrosine kinase inhibitors (EGFR-TKIs), yet resistance is nearly inevitable and responses to immune checkpoint inhibitors (ICIs) remain limited. In a retrospective cohort of 57 patients with advanced EGFR-mutant NSCLC treated with nivolumab or pembrolizumab, the objective response rate was 12.3%, although responses were concentrated in a small subgroup with concurrent high PD-L1 expression and dense intratumoral CD8⁺ immune-cell infiltration. Emerging evidence links these outcomes to chemokine-network dysregulation that alters immune trafficking and spatial organization. Oncogenic EGFR signaling shifts chemokine networks away from effector T-cell recruitment

Background: A successful endodontic treatment is aimed at the sterilization of the entire pulp space. The use of extracts from Rhamnus prinoides as a novel irrigating material for root canal has not been studied . Hence, the antimicrobial efficacy of the alcoholic extract of Rhamnus prinoides as an irrigation material against E. faecalis was evaluated in comparison with the 2.5% sodium hypochlorite (NaOCL) solution used for root canals of permanent teeth. Methods: A total of 30 single-rooted human permanent teeth were thoroughly cleaned, shaped, and disinfected. Then, each tooth was subjected to a two-week infection with Enterococcus faecalis at 37 °C . Afterward, the samples were divided into three groups (10 teeth per group): 0.9

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

The limitations of wireless sensor nodes are power, computational capabilities, and memory. This paper suggests a method to reduce the power consumption by a sensor node. This work is based on the analogy of the routing problem to distribute an electrical field in a physical media with a given density of charges. From this analogy a set of partial differential equations (Poisson's equation) is obtained. A finite difference method is utilized to solve this set numerically. Then a parallel implementation is presented. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a processing element. All nodes then execute computations in parall

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p