Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo

The holmium plasma induced by a 1064-nmQ-switched Nd:YAG laser in air was investigated. This work was done theoretically and experimentally.  Cowan code was used to get the emission spectra for different transition of the holmium target. In the experimental work, the evolution of the plasma was studied by acquiring spectral images at different laser pulse energies (600,650,700, 750, and 800 mJ). The repetition rates of (1Hz and 10Hz) in the UV region (200-400 nm). The results indicate that, the emission line intensities increase with increasing of the laser pulse energy and repetition rate. The strongest emission spectra appeared when the laser pulse energy is 800mJ and 10 Hz repetition rate at λ= 345.64nm, with the maximum intensi

The characterization of ZnO and ZnO:In thin films were confirmed by spray pyrolysis technique. The films were deposited onto glass substrate at a temperature of 450°C. Optical absorption measurements were also studied by UV-VIS technique in the wavelength range 300-900 nm which was used to calculate the optical constants. The changes in dispersion and Urbach parameters were investigated as a function of In content. The optical energy gap was decreased and the wide band tails were increased in width from 616 to 844 eV as the In content increased from 0wt.% to 3wt.%. The single–oscillator parameters were determined also the change in dispersion was investigated before and after doping.

Exploring the antibacterial potential of neem oil (Azadirachta indica) in combination with gentamicin (GEN) against pathogenic molds, especially Pseudomonas aeruginosa, has drawn concern due to the quest for natural treatment options against incurable diseases. Prospective research directions include looking for natural cures for many of the currently incurable diseases available now. microbial identification system, were used to identify the isolates. The research utilized a range of methods, such as the diffusion agar well (AWD) assays, TEM (transmission electron microscopy) analysis, minimum inhibitory concentration (MIC) assays, and real-time PCR (RT-qPCR) to analyze bacterial expression and the antibacterial action of neem oil (Azadira

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

The integration of nanomaterials in asphalt modification has emerged as a promising approach to enhance the performance of asphalt pavements, particularly under high-temperature conditions. Nanomaterials, due to their unique properties such as high surface area, exceptional mechanical strength, and thermal stability, offer significant improvements in the rheological properties, durability, and resistance to deformation of asphalt binders. This research reviewed the application of various nanomaterials, including nano silica, nano alumina, nano titanium, nano zinc, and carbon nanotubes in asphalt modification. The incorporation of these nanomaterials into asphalt mixtures has shown potential to increase the stiffness and high-tempera

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise