Cultivation of the green seaweed Enteromorpha compressa was performed under natural laboratory spring environmental conditions of temperature, light intensity and photoperiod to study the salinity tolerance of this intertidal green macroalga. Cultivation was carried out under artificial seawater (ASW) of different concentrations (18, 35, 53 and 106 g/l sea salt) compared to the control using natural seawater (NSW). Growth rate and pigment content of the cultivated alga were recorded at regular intervals during the experimental duration. Antioxidant activity of the crude ethanolic extract and its fractions (petroleum ether, chloroform, ethyl acetate and acetone) was performed against DPPH radical scavenging assay and compared to

Myelosuppression is a serious disease that is related to the malfunction of blood cells production that leads to cytopenia which is the most serious hematologic toxicity of cancer chemotherapies including cyclophosphamide, which is a strong oxazaphosphorine [a nitrogen mustard alkylating agent] that can be used alone or combined with other chemotherapeutic agents for the treatment of different malignant diseases. It induces severe bone marrow suppression by damaging hematopoietic stem cells through the generation of oxidative stress. Fisetin is a hydrophobic polyphenolic compound with a wide range of pharmacological properties such as antioxidant, anti-inflammatory, antimicrobial, osteoprotective, antidiabetic, and anti-carcinogenic activit

Myelosuppression is a serious disease that is related to the malfunction of blood cells production that leads to cytopenia which is the most serious hematologic toxicity of cancer chemotherapies including cyclophosphamide, which is a strong oxazaphosphorine [a nitrogen mustard alkylating agent] that can be used alone or combined with other chemotherapeutic agents for the treatment of different malignant diseases. It induces severe bone marrow suppression by damaging hematopoietic stem cells through the generation of oxidative stress. Fisetin is a hydrophobic polyphenolic compound with a wide range of pharmacological properties such as antioxidant, anti-inflammatory, antimicrobial, osteoprotective, antidiabetic, and anti-carcinogenic

The current study performs an explicit nonlinear finite element simulation to predict temperature distribution and consequent stresses during the friction stir welding (FSW) of AA 7075-T651 alloy. The ABAQUS® finite element software was used to model and analyze the process steps that involve plunging, dwelling, and traverse stages. Techniques such as Arbitrary Lagrangian–Eulerian (ALE) formulation, adaptive meshing, and computational feature of mass scaling were utilized to simulate sequence events during the friction stir welding process. The contact between the welding tool and workpiece was modelled through applying Coulomb’s friction model with a nonlinear friction coefficient value. Also, the model considered the effect of nonlin

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca