This research aims to find out the relationship of risk behavior & job satisfaction for workers in the emergency program in the international relief agency (UNRWA) in the Gaza Strip and the level of each of them, and to achieve that we have been conducting research on the strength of "210" sample employees of the emergency program staff in the international relief agency in Gaza governorates, and try to answer the research questions the researcher through the use of measurements of risk behavior and job satisfaction are two of the researcher, The researcher has used several statistical methods to identify the validity and reliability of scales and access to research and interpretations of the results, and these methods: the mean, standard deviation and relative weight, Pearson correlation coefficient, test "t", scheffe test, variance and variance analysis bilateral analysis test (2 × 2), results showed that the level of risk-taking behavior is located at the average level of relative weight (68.5%), and job satisfaction level is at a good level relative weight (73.5%) among respondents, as well as the presence of a statistically significant relationship between job satisfaction and risk taking behavior in general, and the presence of statistically significant differences in the level of risk-taking behavior is attributable to gender, educational qualification, the nature of the profession, the workplace, and to maintain, and the lack of statistically significant differences in the level of risk-taking behavior attributed to marital status, years of experience, and the lack of statistically significant differences in the level of satisfaction differences career due to the variable gender, marital status, educational qualification, years of experience and the workplace, and the presence of significant differences in the level of job satisfaction differences due to the variable nature of the profession, the province, and the presence of the effect statistically significant interaction between gender "male, female" job satisfaction "low , high "after the distinctive capabilities of personal risk, while the results did not show statistically significant impact indicative of the rest of the dimensions of the total degree of risk taking behavior have, And the existence of the effect statistically significant interaction between qualification and job satisfaction "low, high," a motivated risk, while the results did not show significant influential statistically for the rest of the overall dimensions and the degree of risk taking behavior they have, and the presence of the effect statistically significant interaction between the nature of the profession and job satisfaction "low, high "Just risk decision-making, while the results did not show significant influential statistically for the rest of dimensions and the total score for the behavior of the risk they have, and the presence of the effect statistically significant interaction between the workplace and job satisfaction" low, high, "the dimensions accept the risk, and the motives of the risk, while not shown Results statistically significant effect on the rest of the dimensions of the total degree of risk taking behavior.
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Tirzepatide is a revolutionary and promising medication with a high impact in the treatment of Obesity and T2DM with their complications. Its efficacy was proven through different trials in achieving favorable weight loss and a significant reduction in glycemic index. It also treated a large diversity of related co-morbidities, including fatty liver, cardiovascular disease, dyslipidemia, and more. Tirzepatide is well tolerated, has a good safety profile, and is highly reliable and suitable for use in a population.
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Abstract
Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.
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Desulfurization of a simulated diesel fuel by different adsorbents was studied in a fixed-bed adsorption process operated at ambient temperature and pressure. Three different adsorption beds were used, commercial activated carbon, Cu-Y zeolite, and layered bed of 15wt% activated carbon followed by Cu-Y zeolite.Initially Y-zeolite was prepared from Iraqi rice husk and then impregnated with copper. In general, the adsorbents tested for total sulfur adsorption capacity at break through followed the order Ac/Cu-Y zeolite>Cu-Y zeolite>Ac. The best adsorbent, Ac/Cu-Y zeolite is capable of producing more than 30 cm3 of simulated diesel fuel per gram of adsorbent with a weighted average content of 5 ppm-S, while Cu-Y zeolite producing of
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria. Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core. Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um
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The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.