In this review, numerous analytical methods to distinguish pigments in tattoo, paint, and ink items are discussed. The selection of a method was dependent upon the purpose, e.g., quantification or identification of pigments. The introductory part of this review focuses on describing the importance of setting up a pigment-associated safety profile. The formation of different degradation chemical substances as well as impurity trends can be indicated through the chemical investigation of pigments in tattoo products. It is noteworthy that pigment recognition in tattoo inks can work as a preliminary method to identify the pigments in a patient's tattoo before being removed by laser therapy. Contrary to the study of banned pigments, the identification process usually requires only a few indication substances for positive dyes. In general, tattoo pigments are almost insoluble in aqueous solutions, and many organic solvents and various pigment analyses have been conducted. It is proposed that in the future, laboratories concerned with tattoo substance analysis should have access to extensive pigment specifications and spectroscopic databases. The most important and recent physiological side effects of tattooing have been discussed in this review.
Many patients with advanced type 2 diabetes mellitus (T2DM) and all patients with T1DM require insulin to keep blood glucose levels in the target range. The most common route of insulin administration is subcutaneous insulin injections. There are many ways to deliver insulin subcutaneously, such as vials and syringes, insulin pens, and insulin pumps. Though subcutaneous insulin delivery is the standard route of insulin administration, it is associated with injection pain, needle phobia, lipodystrophy, noncompliance, and peripheral hyperinsulinemia. Therefore, the need exists to deliver insulin in a minimally invasive or noninvasive way and in the most physiological way. Inhaled insulin was the first approved noninvasive and alternative way
... Show MoreIn this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method and the least squares method and that using the method of simulation model first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.
Abstract The Object of the study aims to identify the effectiveness of using the 7E’s learning cycle to learn movement chains on uneven bars, for this purpose, we used the method SPSS. On a sample composed (20) students on collage of physical education at the university of Baghdad Chosen as two groups experimental and control group (10) student for each group, and for data collection, we used SPSS After collecting the results and having treated them statistically, we conclude the use 7E’s learning cycle has achieved remarkable positive progress, but it has diverged between to methods, On this basis, the study recommended the necessity of applying 7E’s learning cycle strategy in learning the movement chain on uneven bar
... Show MoreThis study involves the synthesis of a new class of silicon polymers, designated as P1-P7, derived from dichlorodimethylsilane (DCDMS) in combination with various organic compounds (Schiff bases prepared from different amines and appropriate aldehydes or ketones) [I-V] through condensation polymerization. The structures of all monomers and polymers were characterization by FTIR and 1HNMR spectroscopy (for some polymers). The results of thermogravimetric analysis (TGA) and differential scanning calorimetry DSC test show stable thermal behaviour. Polymers with a higher concentration of aromatic rings in their repeating structural units exhibited a higher temperature for weight loss, indicating increased thermal stability. Thermal meas
... Show MoreAn experiment was carried out on the fields of the college of Agriculture - Abu Ghraib, of a silty clay loam soil that has moisture of 15-16%, to study the effect of plowing and pulverization systems on some plant indicators of onion. The experiment included plowing systems with three levels (plowing with a moldboard plow, plowing by chisel plow and zero tillage plowing) as a primary factor. The second factor was that pulverization for only one time and repeating the pulverization twice through the use of the rotary tiller. The plant indicators of onion that are studied: plant length, onion diameter, onion weight and onion neck diameter. The experiment has carried out according to SPLIT PLOT design according to RCBD design by three replicat
... Show MoreThis study involves the synthesis of a new class of silicon polymers, designated as P1-P7, derived from dichlorodimethylsilane (DCDMS) in combination with various organic compounds (Schiff bases prepared from different amines and appropriate aldehydes or ketones) [I-V] through condensation polymerization. The structures of all monomers and polymers were characterization by FTIR and 1HNMR spectroscopy (for some polymers). The results of thermogravimetric analysis (TGA) and differential scanning calorimetry DSC test show stable thermal behaviour. Polymers with a higher concentration of aromatic rings in their repeating structural units exhibited a higher temperature for weight loss, indicating increased thermal stability. Thermal meas
... Show More: zonal are included in phraseological units, form metaphorical names for a person, give him various emotional and evaluative characteristics. This article examines the topic of zoomorphic metaphors that characterize a person in the Russian and Arabic languages in the aspect of their comparative analysis, since the comparative analysis of the metaphorical meanings of animalisms is an important method for studying cultural linguistics, since zoomorphic metaphors are a reflection of culture in a language.
The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
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