ABSTRACT this paper extends the literature on the elements and effect of financial literacy by investigating the elements of financial literacy and the impact of financial literacy on financial inclusion and savings. This research confirms the results of researches of other economies but exposes some dissimilarities as well. The principal factors of financial literacy are discovered to be government efficiency, educational level, income, economic performance and infrastructure. Both education levels and financial literacy are found to be meaningfully and positively linked to financial inclusion and savings in G20 economies

There are different types of corruptions such as administrative, political, economic and financial corruption. The corruption forms also varied such as bribery, nepotism and extortion. All types and forms of corruption play significant role in the all economic variables generally and on investments in particular, and the corruption used to be an intermediate means in reducing the rate of economic growth.  The corruption contributes in reducing the domestic investments via pay bribery by investors to officials’ persons for supplemental contracts and tenders which finally leads to reduction in the investment efficiency. The corruption also contributes in rise of operational costs for the investment projects.  In additio

   Probit analysis is a type of regression used to analyze the relationship between a stimulus and the quantal response. Allelopathy refers to direct or indirect negative or positive effects of one plant on another through the release of chemical compounds into the environment. This study was carried out to apply probit analysis in investigating the allelopathic effects of the leaves aqueous extracts of apple of Sodom [Calotropis procera (Aiton) W.T.] on the inhibition of seed germination of African rattlebox (Crotalaria saltiana Andr.). A laboratory experiments were carried out at the Faculty of Agricultural Sciences, University of Gezira, Sudan in season 2014/15. Ten concentrations (2.3, 4.6

Abstract

                  The study aimed to prepare a practical guide for procedures for auditing the strategies of municipal institutions in achieving sustainable development by adopting the idea of ​​the audit matrix through which a classified report is prepared according to the dimensions of sustainable development, by preparing a specialized audit program for the purpose of auditing strategies for achieving sustainable development and emptying the results of the application of each of the paragraphs The program in the audit matrix that was prepared for the purpose of determining the impact of each observation and linkin

Hepatitis B virus (HBV) infection is a significant global health problem. Populations of different ethnicities show great heterogeneity in HBV genotype frequency distributions. A cross-sectional study was conducted during June–October 2018 to determine frequency of HBV genotypes among chronic HBV patients from Baghdad, Iraq. The method of detection was nested polymerase chain reaction system. Further, the study assessed the impact of HBV genotypes on serum level of liver-function tests: total serum bilirubin, alkaline phosphatase, alanine aminotransferase and aspartate aminotransferase. Eighty chronic HBV patients were enrolled in the study. Six HBV genotypes were identified (A, B, C, D, E and F). The most frequently encountered genotypes

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m³

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti