The Iranian nuclear program was one of the most prominent issues in the international arena, in light of Iran's insistence on using it in various ways, and according to international changes, it came under pressure from the American side to impose packages of sanctions, which continued to our time, as it went to Russia and China to gain support in developing its nuclear activities. And, by virtue of the common interests that are linked between them, Iran has received great support from the last two countries in all fields to reach the final agreement in 2015, regarding asserting the peace of these activities, in addition to lifting all restrictions represented in the previous sanctions according to the Security Council resolutions, Aldo

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

Background: This study evaluates transdermal delivery of tamoxifen (TXN) as an alternative to the oral route of administration in treating breast cancer, which is the leading cause of cancer-related death in women globally. Oral TXN, a Class II drug, is associated with first-pass metabolism and serious side effects, including secondary cancers. Objectives: To enhance transdermal delivery, lipid-based transethosomes (TRS) were formulated using three different 24 factorial designs with various non-ionic surfactants, including Tween 20®, Span 20®, and Span 80®. Methods: Optimized TRS formulations were incorporated into HPMC-based gels and characterized for morphology, drug content, pH, viscosity, spreadability, ex vivo skin penetrat

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

Arabic language processing with artificial intelligence has evolved significantly in the past decades, from traditional rule- and dictionary-based techniques, through statistical models to modern deep and transformer models. This review intends to present an overview of the most well-known Arabic models as well as datasets used for its training, and the main practical applications such as sentiment analysis, machine translation, speech recognition, and smart assistant. AI-based Arabic NLP has had good progress in the previous decades, from rule and dictionary-based approaches to statistical methods and deep transformative learning models nowadays. In addition to it, the most popular state-of-the-art models that are fine-tuned for the Arabi

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to t

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A