Research aims to shed light on the concept of corporate failures , display and analysis the most distinctive models used to predicting corporate failure; with suggesting  a model to reveal the probabilities of corporate failures which including internal and external financial and non-financial indicators, A tested is made for the research objectivity and its indicators weight and by a  number of academics professionals experts, in addition to  financial analysts  and have concluded a set of conclusions ,  the most distinctive of them that failure is not considered a sudden phenomena for the company and its stakeholders , it is an Event passes through numerous stages; each have their symptoms that lead eve

Abstracts:

Background: The oral cavity is a complex environment, both structurally and functionally, the hard and soft tissues are in close a proximity. Oral tissues subjected to wear throughout the life, that threatened the vitality of the pulp or increase the sensitivity of dentinal tubules. One of the common dental problems is loss of enamel or cementum, which stimulate the nerve ending in or near the pulp and manifested as pain sensation. Aim of the study: This study had done to evaluate the effects of 980nm diode Laser in diameters reduction of exposed dentinal tubules analyze the results and morphological changes of irradiated dentine surface by FE-SEM (field emission scann

A simple, precise, rapid, and accurate reversed – phase high performance liquid chromatographic method has been developed for the determination of guaifenesin in pure from pharmaceutical formulations.andindustrial effluent. Chromatography was carried out on supelco L7 reversed- phase column (25cm × 4.6mm), 5 microns, using a mixture of methanol –acetonitrile-water: (80: 10 :10 v/v/v) as a mobile phase at a flow rate of 1.0 ml.min-1. Detection was performed at 254nm at ambient temperature. The retention time for guaifenesin was found 2.4 minutes. The calibration curve was linear (r= 0.9998) over a concentration range from 0.08 to 0.8mg/ml. Limit of detection (LOD) and limit of quantification ( LOQ) were found 6µg/ml and 18µg/ml res

Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

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