The current research aims to identify the most important green productivity tools GPT and the possibility of applied in industrial companies in general and the companies operating in the province of Nineveh, in particular, as well as the study of some personality characteristics and functional, which is believed to be an impact on the application of these tools in industrial companies. Accordingly, the research community of managers in the company of medicines and medical supplies ready-made clothes _ operating in the province of Nineveh, who are (80) while the manager was subjected to research procedures (49) Director representing (61.25%)

Search procedures on the treatment research has tended include what cam followers Astaratejaat available to the business organizations to achieve competitive advantage and continued benefits of the form in which the organization can maintain its success in the race competitive and increase production efficiency. 

The objectives of the study , the study came with  the number of goals and the most important one the  knowledge of the relationship and the influence between the variables of the study and review of the latest literature frameworks intellectual and philosophical to the variables of the study and come up with recommendations that could help the organization improve its performance .

      The Green Productivity topic is considered as one of  the more conceptual novelty in the field of Production and Operations Management, and one of the least topics addressed in the literature competent, Green Productivity (GP) is a strategy for enhancing a business's Productivity and environmental performance at the same time, for overall socio - economic development, It is  the application of appropriate techniques , technologies , and management systems to produce environmentally compatible goods and services. the research aimed to find the contribution of this concept for success the industrial Organizations.

The Evaluation of the immune response in Golden Hamsters experimentally infected with Leishmania donovani was determined in this study, particularly, the cellular immune response. Follow up has maintained to determine the Delayed Type of Hypersensitivity using skin test both in infected and control lab animals. Chicken red blood cells were used as a parameter to evaluate the immune system; they are dull and have the ability of immunization. Two concentrations of chicken R.B.C were examined to determine which gives the higher titration in Hamsters and those were 1.5 X 109 cell/ml and 3 X 109 cell/ml , the second concentration gave the maximum titration where then used in this work. After sensitization with Chicken R.B.C for both infected a

The Evaluation of the immune response in Golden Hamsters experimentally infected with Leishmania donovani was determined in this study, particularly, the cellular immune response. Follow up has maintained to determine the Delayed Type of Hypersensitivity using skin test both in infected and control lab animals. Chicken red blood cells were used as a parameter to evaluate the immune system; they are dull and have the ability of immunization. Two concentrations of chicken R.B.C were examined to determine which gives the higher titration in Hamsters and those were 1.5 X 109 cell/ml and 3 X 109 cell/ml , the second concentration gave the maximum titration where then used in this work. After sensitization with Chicken R.B.C for both in

            This study tests the effect of a large number of independent variables that control the growth of the total productivity, which amounted to 112 variables, gathered from what is mentioned in the specialized theoretical and applied literature. The data for these variables were taken from global reports of sound international organizations and reliable databases covering the period 1991-2016. The data of the dependent variable, the growth of the total factor productivity, were taken from the database of the world development indicators. The study covered 61 countries for which data were available. The study included three regression models to explain

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty