Light is an important factor that influences the growth and photosynthetic efficiency of microalgae; however, little is known about how light intensity together with the wavelength affect the photosynthetic capacity and growth of marine microalgae. In the present study, the growth of the marine green microalga Dunaliella parva was studied and optimized under different light intensities (25 ~ 70 μmol m^-2 s^-1) and qualities (blue, green, and red) in comparison with white light at 40 μmol m^-2 s^-1 as a control. The growth was monitored by counting the cell number, pigment content, Chl a, Chl b, and carotenoids concentrations. The optimal growth and highest photosyntheti

The study aims to identify the theoretical literature for all the variables of the study (ICT, GDP) as well as to identify the practical side of the impact of ICT on the per capita GDP in Iraq for the period (2004-2021). The study was based on the hypothesis that ICT impacts per capita GDP in Iraq. The problem of the study was to answer the question: does ICT contribute to per capita GDP? The study concluded that an increase in the rate of internet users per 100 people by one unit would increase. Increasing the landline telephone rate per 100 people by one unit will increase GDP per capita. In addition, increasing the mobile phone rate per 100 people by one unit will increase GDP per capita. The study recommended adopting rational poli

In the present study, the growth and total lipid contents of two oleaginous fungal isolates Aspergillus terreus, Aspergillus fumigatus were compared in different nitrogen and organic carbon sources.  Artificially the fungi were cultured on media consisting of various mono- or di- or polysaccharides and  peptone or yeast extract as elementary sources for carbon and nitrogen, respectively. Media containing sucrose /yeast extract or glucose/ yeast extract were the most effective for lipid production from fungal, during  two weeks  incubation period, the highest biomass of dry weight was (19.6 , 18.8) g / L , (25.8 , 30.5) g /L  and  lipid yield (1, 0.97 )g/L, (0.65, 0.65) g/ L for two isolates Aspergillus terreus

Back ground: Diabetic nephropathy is rapidly becoming the leading cause of end-stage renal disease (ESRD). The onset and course of DN can be ameliorated to a very significant degree if intervention institutes at a point very early in the course of the development of this complication.
Objective: The aim of this study was to characterize risk factors associated with nephropathy in type I diabetes and construct a module for early prediction of diabetic nephropathy (DN) by analyzing their risk factors.
Methods: Case control design of 400 patients with type I diabetes mellitus (IDDM), aged 19-45 years. The cases were 200 diabetic patients with overt protein urea while the controls were 200 diabetic patients with no protein urea or micr

Abstract:

Recently, there is a widespread attention about the service at the level of each of the research and academic studies, and at the organizational level as well. The subject of orientation towards the service aspect is starting to be of this attention being of the modern subjects, relatively, which appeared at the end of the last century, as well as the link of this subject with the relationship between the organization and its customers, and how to provide high quality services to get their satisfaction. Thus, the specialists from researchers were interested in this field to develop an appropriate scale to measure the organizational orientation toward service, and it was the most prominen

The removal of congo red (CR) is a critical issue in contemporary textile industry wastewater treatment. The current study introduces a combined electrochemical process of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of this dye. Moreover, it discusses the formation of a triple composite of Co, Mn, and Ni oxides by depositing fixed salt ratios (1:1:1) of these oxides in an electrolysis cell at a constant current density of 25 mA/cm2. The deposition ended within 3 hours at room temperature. X-ray diffractometer (XRD), field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and energy dispersive X-ray (EDX) characterized the structural and surface morphology of the multi-oxide sedim

In this research, the Williamson-Hall method and of size-strain plot method was employed to analyze X- ray lines for evaluating the crystallite size and lattice strain and of cadmium oxide nanoparticles. the crystallite size value is (15.2 nm) and (93.1 nm) and lattice strain (4.2 x10−4 ) and (21x10−4) respectively. Also, other methods have been employed to evaluate the crystallite size. The current methods are (Sherrer and modified Sherrer methods ) and their results are (14.8 nm) and (13.9nm) respectively. Each method of analysis has a different result because the alteration in the crystallite size and lattice strain calculated according to the Williamson-Hall and size-strain plot methods shows that the non-uniform strain in nan

In this study, the effects of blending the un-branched acrylate polymer known as Poly (n-decyl acrylate), and the branched acrylate polymer known as Poly (iso-octyl acrylate), on the viscosity index (VI), and the pour point of the Iraqi base stocks 40, and 60 respectively, were investigated. Toluene was used as a carrier solvent for both polymer types. The improvement level of oils (VI, & pour point) gained by blending the oil with the acrylate derived polymers was compared with the values of (VI, and pour point) gained by blending the oil with a commercial viscosity index, and pour point improver. The commercial lubricant additive was purchased and used by Al-Daura Refineries. It consisted of an un-known olefin copolymer dissolved i

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le