Biosynthesis of nanoparticles has received considerable attention due to the growing need to develop environmentally benign nanoparticle synthesis processes that do not use toxic chemicals. Therefore, biosynthetic methods employing both biological agents such as bacteria and fungus or plant extracts have emerged as a simple and a viable alternative to chemical synthetic and physical method .It is well known that many microbes produce an organic material either intracellular or extracellular which is playing important role in the remediation of toxic metals through reduction of metal ions and acting as interesting Nano factories. As a result, in the present study Ag NPs were syn

In this study, (50–110 nm) magnetic iron oxide (α-Fe2O3) nanoparticles were synthesized by pulsed laser ablation of iron target in dimethylformamide (DMF) and sodium dodecyl sulfate (SDS) solutions. The structural properties of the synthesized nanoparticles were investigated by using Fourier Transform Infrared (FT-IR) spectroscopy, UV–VIS absorption, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD). The effect of laser fluence on the characteristics of these nanoparticles was studied. Antibacterial activities of iron oxide nanoparticles were tested against Gram-positive; Staphylococcus aureus and Gram-negative; Escherichia coli, Pseudomonas aeruginosa and Serratia marcescens. The results sh

Many previous investigations have found quercetin to be a powerful antioxidant and antitumor flavonoid, but its poor bioavailability has limited its use. This current study investigated the effects of two newly synthesized Quercetin Schiff bases containing 2-amino thiadiazole-5-thiol (Q1), and its benzyl derivatives (Q2) on MCF-7 human breast cancer cells. Cell viability and apoptosis were assessed to determine the toxic effects of Q1 and Q2. Cytotoxicity valuation showed that both compounds inhibited MCF-7 cell growth, and lactate dehydrogenase (LDH) activity increased in a dose-dependent aspect compared to the control group. Comet assay results observed that Q1 and Q2 induce more serious DNA damage than the control (untreated cell

The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from

The research aims to identify the obstacles facing the application of electronic management in our university libraries, including the central library of the University of Baghdad and the central library of Al-Mustansiriya University, the research sample, as they are among the main libraries that used electronic technologies in managing some of their work and in providing their services, and they have a website via the Internet. The research relied on the case study method to identify the obstacles by visiting the two libraries, interviewing their managers and employees responsible for the departments, and answering inquiries about the obstacles that prevent the application of electronic management in order to identify them and find appropr

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia