Microalgae have been used widely in bioremediation processes to degrade or adsorb toxic dyes. Here, we evaluated the decolorization efficiency of Chlorella vulgaris and Nostoc paludosum against two toxic dyes, crystal violet (CV) and malachite green (MG). Furthermore, the effect of CV and MG dyes on the metabolic profiling of the studied algae has been investigated. The data showed that C. vulgaris was most efficient in decolorization of CV and MG: the highest percentage of decolorization was 93.55% in case of MG, while CV decolorization percentage was 62.98%. N. paludosum decolorized MG dye by 77.6%, and the decolorization percentage of CV was 35.1%. Metabolic profiling of C. vulgaris and N. paludosum were performed using NMR spectroscopy. Based on 1D and 2D NMR data, 43 compounds were identified in the polar extract of C. vulgaris, while 34 polar metabolites were successfully determined in N. paludosum. The identified compounds included carbohydrates, amino acids, organic acids, dipeptides, steroids and phenols. Statistical analysis was carried out to recognize the pattern of metabolite variation between control and dye treated samples. Principal component analysis (PCA) and hierarchical cluster analysis showed that samples treated with MG are clearly separated from the control in both types of algae. Based on heat map data, the level of carbohydrates and amino acids concentrations are strongly affected by bioremediation of MG dye compared with CV dye. In conclusion, the present study proved that CV and MG dyes are considered as stress factors and the studied algae species exert their bioremediation activity without the dyes being absorbed into the cells.
Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
... Show MoreA collection of pictures of traditional Kurdish women's national clothing and contemporary clothing was collected. A visit was also made to the city of Sulaymaniyah and the city of Halabja to find out the foundations of traditional clothing for the Kurdish regions and the impact of contemporary fashion on traditional dress. Which represents the culture and regionalism and reflects the picturesque nature of northern Iraq, and in order to complete the study, the parametric measurements of the clothes were analyzed and the graphs of the dress and its accessories were re-drawn to understand and make a comparison between them to study the clear influences and changes and examine the possibility of benefiting from them in sewing contemporary f
... Show MoreThe analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.
The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.
In the analysis of d
... Show MoreThis study was designed to evaluate the effect of major surgery on thyroid hormones and thyrotropin in patient undergoing major lower abdominal surgery. The study included fifty patients scheduled for elective major lower abdominal surgery, the serum levels of T3, T4 and TSH were determined one day preoperatively, intraoperative, one day postoperatively, two days postoperatively, and rT3 was determined one day preoperatively, and one day postoperatively. We observed that the levels of (T3, T4, TSH) increased significantly (P<0.05) intraoperatively, one day postoperatively the levels of T3 and T4 reduced significantly (P<0.05), while TSH reduced not significantly (P>0.05), and two days postoperatively T4 and TSH returned to increase si
... Show MoreIn this research, we sought to identify the nature of the relationship between the exchange rate of the Chinese yuan and the value of Chinese exports, through the formulation of a standard model based on the model of common integration, and based on the data of the study and using the test "Angel-Granger" It reflects the relationship between the two research variables, through which the relationship between the RMB exchange rate and the value of Chinese exports was estimated during the period 1978-2017.
This paper deals with a new Henstock-Kurzweil integral in Banach Space with Bilinear triple n-tuple and integrator function Ψ which depends on multiple points in partition. Finally, exhibit standard results of Generalized Henstock - Kurzweil integral in the theory of integration.
Abstract
The decision maker needs to understand the strategic environment to be addressed through different means and methods. It is obvious that there is a difference between the three strategic environments (conflict environment, peace environment, post- peace environment) in terms of inputs and strategies to deal with each one of them. There is an urgent need to understand each pattern separately, analyze its inputs, and identify the factors and variables that affect the continuity of this situation (conflict, peace, post-peace). It is not appropriate to identify treatment without diagnosis of the condition, so it is very important to understand the type of strategic environment to be dealt with it.
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
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