Explore the vast range of titles available.

Background Nanoparticles (NPs) are extensively used in many areas of our daily life. Thus, human exposure to a mixture of the NPs is likely to occur. However, most of the previous studies have investigated the toxicity of the individual NPs. Therefore, the current study investigated the genotoxicity and oxidative stress induced by an acute oral administration of the nano-sized nickel oxide (NiO) and/or cobalt oxide (Co 3 O 4 ) in the brain, liver, and kidney of the rats. Results After 1 day of an administration with NiO-NPs or Co 3 O 4 -NPs, at the dose levels of 0.5 and 1.0 g/kg, remarkable elevations in malondialdehyde (MDA) levels, percentage of DNA damage (%DNA), tail length (TL), and tail moment (TM), accompanied by marked reductions in the levels of zinc (Zn), glutathione (GSH) as well as the activities and expression levels of the superoxide dismutase (SOD) were recorded in all the studied groups, as compared to the controls. The changes in the levels of all the studied parameters were in a time- and dose-dependent manner. Excessive productions of the reactive oxygen species (ROS) associated with the genomic DNA fragmentation were observed in the experimental groups, as compared to the controls. However, in the groups administered with NiO-NPs and Co 3 O 4 -NPs together, the alterations in all the studied parameters were improved as compared to those administered NiO-NPs or Co 3 O 4 -NPs solely. Conclusion The NiO-NPs and Co 3 O 4 -NPs antagonized each other leading to an alleviation of the genotoxicity induced by each of them.

This research examines the direct and indirect impact of Perceived ethical work climate on proactive behavior at Tax Authority in Gharbia Governorate. A field study was then conducted using a sample of 259 employee working at all at all levels at the Authority and 235 questionnaires were completed, Results revealed that all dimensions of the Perceived ethical work climate have a statistically significant positive direct impact on proactive behavior at Tax Authority in Gharbia. It was found also that all dimensions of Perceived ethical work climate have a statistically significant positive direct impact on psychological empowerment. Moreover, results revealed that psychological empowerment has statistically significant direct impact on proactive behavior Finally,, findings showed that psychological empowerment plays a fully mediating role in the relationship between Perceived ethical work climate and proactive behavior at Tax Authority in Gharbia Governorate.

Statistical matching methods goal is to combine several data sources to build datasets. The main goal of statistical matching is to make helpful and informative synthetic data without collecting more data or making new surveys. The study aims to use the goal programming approach in statistical matching to complete the data in two files, where the first file contains variables different from the second file, with one or more of the common variables. To reach this goal, a linear regression model is designed for each of the variables in each file in terms of the variables in the two files. The goal programming approach was used to estimate the parameters of the two regression models, and from it the estimated value of the variables presents in the first file and not present in the second file, and so on, hence we get a file with all the variables. The goal programming approach has the advantage of minimizing the effect of outliers with estimates because it uses minimization of the sum of absolute deviations. Moreover, the proposed approach has a constraint that guarantees significant estimations of the parameters. In addition to formulating the model, A simulation study evaluates the proposed approach's performance by generating and imputing data for dependent variables from different distributions. Results show the efficacy of the approach in accurately estimating missing values while maintaining data quality and minimizing errors.

In this paper, a meta goal programming model (MGP) is introduced to determine the optimum allocation of stratified random sample. The main objectives in this research are using the suggested model which is flexible enough to interactive with the decision maker and find practical solutions, in addition to minimize the estimated variance in the sampling, beside minimize the variance of estimated variance, and also minimize the cost and time of users in the study

The Environmental Impact Assessment of projects is based on several variables. It is desirable to select the most important variables needed for classifying any project in only one of three classes according to severity of possible environmental impact. In this paper, the selection of variables in Discriminant Analysis between more than two groups using the Mathematical Programming Approach is applied to Egypt Environmental Impact Assessment survey 2000 data to select the most important variables for classifying new projects in the true classes. The results are compared with those of the stepwise method. The comparison shows that, according to the percent of correct classification, the Mathematical Programming model is better than the stepwise method.

This study’s aim was to determine the pesticide residues in 10 different vegetable commodities from the Asir region, Saudi Arabia. We evaluated 211 vegetable samples, collected from supermarkets between March 2018 and September 2018, for a total of 80 different pesticides using ultrahigh-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) and gas chromatography–tandem mass spectrometry (GC-MS/MS) after extraction with a multi-residue method (the QuEChERS method). The results were assessed according to the maximum residue limit (MRL) provided by European regulations for each pesticide in each commodity. All lettuce, cauliflower, and carrot samples were found to be free from pesticide residues. A total of 145 samples (68.7%) contained detectable pesticide residues at or lower than MRLs, and 44 samples (20.9%) contained detectable pesticide residues above MRLs. MRL values were exceeded most often in chili pepper (14 samples) and cucumber (10 samples). Methomyl, imidacloprid, metalaxyl, and cyproconazole were the most frequently detected pesticides. Based on the results of this study, we recommend that a government-supported program for the monitoring of pesticide residues in vegetables be established to promote consumers’ health and achieve sustainable farming systems.