The possibility of predicting the mass transfer controlled CaCO₃ scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO₃ scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

 The present study discusses one of the most relevant and required topics in the recent period during globalization, the modern Russian system of terms for the oil and gas industry as a whole acquired a complete form in the second half of the twentieth century. The period of the late XX - early XXI centuries. marked by cardinal transformations in all areas of the political, economic, social and cultural life of Russia. These changes could not but affect industrial production. Transition to a new vector of development of the Russian economy based on the development of commercial trade, on the change and improvement of the development of industrial enterprises in the context of the implementation of national projects and the introduction

The aim of the research is to find out the nature of the relationship between the interrelationships and the interrelationships between risk management strategies (avoiding danger, risk exposure, risk exhibition, preventive programs and activities to reduce risks) and the dangers of container transportation, as an independent variable in the dangers of container transportation as a dependent variable, the study started from the problem that the company suffers from The practical aspect of the study was applied at the National Insurance Corporation, and the researcher designed a diagram according to the study's schematic diagram. The study, and for the purpose of data and information related to that, it relied on the descriptive a

Determining risk indicators for dental implants is an essential strategy for preventing peri-implant diseases and effective diagnosis of dental implant success. To investigate the impact of certain potential factors on the osseointegrated dental implant. Eighty-four individuals were included in our study, 50 cases as a patient’s group and 34 participants as a control group. All cases were diagnosed based on certain criteria, 30 (60%) of patients had peri-implantitis, 20 (40%) with severe periimplantitis, 36(72%) were generalized, and 15 (30%) as localized peri-implantitis cases. The study has indicated that 44.7% of dental implants were in the anterior maxilla, followed by (27.3%) posterior maxilla, (17.4%) posterior mandible, and (10.4%)

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

Type 2 diabetes mellitus which abbreviate as T2DM is a complex endocrine and metabolic disorder arisingfrom genetic and environmental factors interaction which in turn induce various degrees of insulin functionalalteration on peripheral tissues. Globally, T2DM has develop into a public health problem. Therefore, Thestudy included (75) patients(37 female and 38 males) suffering from T2DM who visit al-kadhimiya teachinghospital with age range 20-80 years and (70) as healthy controls with age range 20-70 years. All studiedgroups were evaluated CMV IgG by ELISA,B. urea, S. Creatinine, cholesterol and triglyceride the resultsshowed that B.urea, S.creatinine and serum cholesterol showed a non-significant differences between studiedgroup,

The objective of the research is to evaluate the risk management practices of the variables (risk management structure, risk management methods, key components of risk management) and their relation to the principled behavior of managers behavior(innovation, proactive, risk acceptance) By adopting the questionnaire as a main tool in collecting data from managers in the National and raq insurance companies of (50) officials Department manager, department administrator, unit administrator, and analyzed their answers using the SPSS In calculating arithmetic mean, standard deviation, percentage weight and simple correlation coefficient. The most prominent conclusions were:1.There is a positive trend in the sample in both companies and a high