For many years, the construction industry damages have been overlooked such as unreasonable consumption of resources in addition to producing a lot of construction waste but with global awareness growth towards the sustainable development issues, the sustainable construction practices have been adopted, taking into account the environment and human safety. The research aims to propose a management system for construction practices which could be adopted during constructing different types of sustainable buildings besides formulating flowcharts which clarify the required whole phases of sustainable buildings life cycle. The research includes two parts: theoretical part which generally ,handles the sustainability concepts at construction i

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

There are  many  economic issues that  concern society at the local and international levels and which constitute  a serious  challenge to the societies  and governments , perhaps  including  the issue of corruption  in all its  forms and manifestations and effects , which  now attract the attention  the issue of human society everywhere .                                                      

The developed financial system is essential for increasing economic growth and poverty reduction in the world. The financial development helps in poverty reduction indirectly via intermediate channel which is the economic growth. The financial development enhancing economic development through mobilization of savings and channel them to the most efficient uses with higher economic and social returns. In addition, the economic growth reduces the poverty through two channels. The first is direct by increasing the introduction factors held by poor and improve the situations into the sectors and areas where the poor live. The second is indirect through redistribution the realized incomes from the economic growth as well as the realiz

Concentrations 25, 50 and 100 mg of nano-capsules linolenic acid and non-capsulated fatty acid for 1kg of Milk was used for yogurt manufacture. The results showed no significant differences in the ratio of titration acidity and pH values between all processed treatments at the beginning and during of period storage. The treatments was added to it coated omega-3 by nano method were the least exposed to the oxidation process from the non-capsules omega-3, And for shield of The poly lactic acid had a significant role in the protection of alpha-linolenic acid against lipolysis by the formation of a protective layer to protect the acid from the activity of lipases enzymes, and the addition of fatty acid linolenic to milk was determined the gr

Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn

 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

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.