Abstract his study involved evaluation of side effects of two weight reduction pills that had been widely distributed in the last period. Two weight reduction compounds are studied, Reductil (containing chemical substances) and Chinese’s weight reduction herbs (containing natural substances). Two doses for each compound are used in this research; 5mg/ml and 0.5mg/ml for Reductil, while 30mg/ml and 10mg/ml for Chinese weight reduction herbs. To evaluate the toxic effects of these compounds, the following parameters were determined which include mitotic index (cytogenetic analysis), serum FSH and LH hormones level (follicles stimulation hormone/FSH and lutenising hormone/LH) and histological examination of female mice ovaries. Control group

Background: The Titanium and its alloys are suitable for dental implant and medical applications. Biocompatibility of the materials is a major factor in determining the success of the implant and has a great impact on their rate of osseointegration. The aim of this study was to evaluate the biocompatibility and cytotoxicity of Ti2AlC in comparison to CPTi & Ti6Al7Nb in rabbits. Materials and Methods: 10 male New Zealand White rabbits, weighing (2-2.5 kg), aged (10-12 months) were used in this study. Cylindrical implants were prepared from the study materials (CPTi, Ti6Al7Nb and Ti2AlC) with (8mm) height and (3mm) diameter for the evaluation of tissue response and disc specimens were prepared with (6 mm) diameter and (2 mm) thickness for ev

The measurement of minority carrier lifetime (MCLT) ofp-n Si fabricated with aid of laser doping technique was reported. The measurement is achieved by using open circuit voltage decay (OCVD) technique. The experiment data confirms that the value of MCLT and proftle of Voc decay were very sensitive to the doping laser energy.

The discovery of novel therapeutic molecules is always difficult, and there are a variety of methodologies that use the most diverse and innovative medicinal chemistry approaches. One such approach is the deuteration technique: Deuteration is the process of substituting deuterium for hydrogen in a molecule. When compared to the drug molecule, its deuterated analogues may retain the features of the original molecule and, in some cases, improve its pharmacological activity, with fewer side effects and lower toxicity. Metronidazole is a commonly used antibiotic to treat anaerobic bacterial infections, protozoal and microaerophilic bacterial infections. Met

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k