Bioethanol production from sugar fermentation is one of the most sustainable alternatives to substitute fossil fuel. production of bioethanol from low grade dates which are rich of sugars. An available sugar from a second grade dates (reduction sugar) was 90g/l in this study. Sugar can be served as essential carbon sources for yeast growth in aerobic condition and can also be converted to bioethanol in anaerobic condition. The effect of various parameters on bioethanol production, fermentation time, pH-values, inoculum size and initial sugar concentration were varied in order to determine the optimal of bioethanol production. The highest bioethanol yield was 33g/l which was obtained with sugar concentration 90 g/l, inocu

This work was influenced the separation and preconcentration steps were carried out to determination of metformin (MET) in pharmaceutical preparations and human serum samples. Complex formation method and cloud-point extraction (CPE) coupling with UV-Visible spectrophotometry were used to investigated of study target.The results has showed the best optical characteristic for calibration curve and statistical data which were obtained under optimum conditions. The first method is based on the reaction of MET with nickel (II) in alkaline medium an absorption maximum ?)max) at 434nm. ''Beer's low'' is obeyed in the concentration range (10-100µg.ml-1) with molar absorptivity of 3.9x103 L.mol-1.cm-1.The limit of detection and quantitation valu

Emulsion Liquid Membrane (ELM) is an emerging technology that removes contaminants from water and industrial wastewater. This study investigated the stability and extraction efficiency of ELM for the removal of Chlorpyrifos Pesticide (CP) from wastewater. The stability was studied in terms of emulsion breakage. The proposed ELM included n-hexane as a diluent, span-80 as a surfactant, and hydrochloric acid (HCl) as a stripping agent. Parameters such as mixing speed, aqueous feed solution pH, internal-to-organic membrane volume ratio, and external-to-emulsion volume ratio were investigated. A minimum emulsion breakage of 0.66% coupled with a maximum chlorpyrifos extraction and stripping efficiency were achieved at 96.1% and 95.7% at b

Aqueous Two Phase System (ATPS) or liquid-liquid extraction is used in biotechnology to recover valuable compounds from raw sources. In Aqueous Two-Phase Systems, many factors influence the Partition coefficient, K, (which is the ratio of protein concentration in the top phase to that in the bottom phase) and the Recovery percentage (Rec%). In this research, two systems of ATPS were used: first, polyethylene glycol (PEG) 4000/Sodium citrate (SC), and the second, PEG8000/ Sodium phosphate (SPH), for the extraction of Bovine Serum Albumin (BSA). The behavior of Rec% and K of pure (BSA) in ATPS has been investigated throughout the study by the effects of five parameters: temperature, concentration of polyethylene glycol (P

As the major role of oil sector in financing and development of Iraqi economy this study tried to research on the factors which influencing the future of oil production in Iraq and for that study addressed the hypothesis (the production and export of crude oil in Iraq , influenced by many factors divided into internal and external factors this factors shared the effect varies in the size of their participation and runs from different sectors economic , political and social , in order to test the study hypothesis study addressed the subject of three axes(an overview of the history and facts of crude oil production in Iraq and factors internal Affecting the future of oil production in Iraq and external factors affecting the future

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class