Biodiesel production from microalgae depends on the biomass and lipid production. Both biomass and lipid accumulation is controlled by several factors. The effect of various culture media (BG11, BBM, and Urea), nutrients stress [nitrogen (N), phosphorous (P), magnesium (Mg) and carbonate (CO₃)] and gamma (γ) radiation on the growth and lipid accumulation of   Dictyochloropsis splendida were investigated. The highest biomass and lipid yield of D. splendida were achieved on BG11 medium. Cultivation of D. splendida in a medium containing 3000 mg L⁻¹ N, or 160 mg L⁻¹ P, or 113 mg L⁻¹ Mg, or 20 mg L^-1 CO_3, led to enhanced growth rate. While u

Interleukin-38 (IL-38), an inflammatory cytokine discovered in recent years, has been implicated in the pathogenesis of systemic lupus erythematosus (SLE). IL-38 is encoded by the IL1F10 (interleukin 1 family member 10) gene. Genetic variants of this gene have been associated with susceptibility to a number of autoimmune and inflammatory diseases, while their association with SLE risk has not been explored. In this case–control study, two novel variants of the 5 prime untranslated region (5′UTR) of the IL1F10 gene, rs3811050 C/T and rs3811051 T/G, were investigated

This study is concerned with the effect of Deep Cryogenic Treatment (DCT) at liquid nitrogen temperature (-196 o C) on the mechanical properties and performance of low carbon steel (A858). The tests specimens were divided in to two groups, the first group was subjected to the conventional heat treatment of normalizing, and the second group was also normalized then subjected to (DCT). The results have shown that after (DCT), the Hardness, Tensile properties and the impact energy absorbed were all slightly increased. However the fatigue test showed some positive improvement in fatigue limit by 20(N/mm2 ), and the volume wear rates at different loads were significantly decreased after (DCT). The changes in microstructure due to (DCT) were c

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

the researchers pointed that the poet relied on several means in the form of poetic images, including analogy, and the metaphor with its various elements, The chromatic component has also been used in the formation of its poetic image,and resorted to the correspondence of the senses and the symbol of two types:Self-code, public code : And we find a variety of symbolic stems from different sources, from these symbols, what is religious, including what is historical and what is legendary, and such symbols, which resorted to the rare places of his poems confined to the myths contained in the Bible, His use of the general symbols was ineffective in the poetic picture, relying on the metaphor and metaphor.

Success in selecting the best among the sources of supply is one of the most important factors in the efficiency of the procurement activity in the company, because the proper selection of the source of the supply significantly affect the achievement of what is desired by the factors of quality, quantity, price and service, and the ability of the competent supplier to meet everything associated with this Factors of commitments, hereby supporting the procurement function's efforts to fully discharge its responsibilities, and in view of adopting of Al-Furat company quality management system by applying the standards of ISO (9001: 2015) and purpose of getting the on-demand benefits from the application of international standards reg

  This paper deals with proposing new lifting scheme (HYBRID Algorithm) that is capable of preventing images and documents which are fraud through decomposing there in to the real colors value arrays (red, blue and green) to create retrieval keys for its properties and store it in the database and then check the document originality by retrieve the query image or document through the decomposition described above and compare the predicted color values (retrieval keys)  of the query document with those stored in the database. The proposed algorithm has been developed from the two known lifting schemes (Haar and D4) by merging them to find out HYBRID lifting scheme. The validity and accuracy of the proposed algorithm have been ev

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s