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The purpose of this paper is to introduce a new concept in selecting the values of the DC source voltages in cascaded multi‐level inverters in order to improve the output voltage THD.

In cascaded multi‐level inverters, it is usually assumed that the DC sources have the same constant voltage and output harmonics minimization is accomplished by applying proper switching angles. Employing different DC voltages with proper ratios can result in further reduction of the harmonics. After formulation of the system, i.e. describing the inverter's output voltage components in terms of the switching angles and unequal DC source voltages, a rule is applied to obtain the step heights of the staircase output waveform (DC source voltages), so that the output waveform becomes as close to the required fundamental sine wave as possible. Substituting the obtained DC source voltages into the harmonics elimination equations results in a set of equations, which are functions of switching angles only. Solving these equations leads to proper switching angles, which, regardless of the fundamental component's value, provide the specified harmonic conditions. The output voltage is then controlled by DC sources voltage regulation.

Computer simulations show that employing the proposed concept results in substantial improvement in the harmonic minimization, as well as, extending the operating range of the inverter, compared to the conventional methods with equal DC source voltage multi‐level inverters.

The proposed concept according to which the ratio of the DC source voltages are determined, is original.

This study examines the social acceptance and potential for residential solar integration in Abu Dhabi to support sustainable urban innovation and prosperity. A survey of 216 Abu Dhabi residents analyzed four scenarios for incentivizing household solar panel adoption. Results demonstrate high interest and preference for governmental financial support mechanisms to spur solar integration. This research contributes an assessment framework and citizen engagement insights that could inform smart city development strategies focused on renewable energy transformation across the Gulf region. As urban centers like Abu Dhabi strive to enact their visions for economic diversification and environmental sustainability, understanding citizen perspectives on innovations like distributed solar will be critical to align technology advancement with societal needs and values. The methodology and findings of this Abu Dhabi case study provide a model to catalyze stakeholder buy-in for new energy solutions, with potential applications for other Gulf cities aiming to transition their energy systems and build integrative renewables infrastructure to power next-generation smart development. This solar integration acceptance research lays the groundwork for continued scholarly discourse and policymaker collaboration around smart cities in the Gulf that realize multidimensional progress for society, economy, and environment.

Mauritius is a Small Island Development State (SIDS) with limited resources, and it has been witnessed that many containers used for storing household and industrial products are made from plastic. When discarded as waste, those plastic containers pose a serious environmental and economic challenge for Mauritius. Moreover, landfill space is getting increasingly scarce, and plastic waste is contaminating both land and water. Therefore, it is of the utmost necessity to develop solutions for Mauritius' plastic wastes. Due to its abundance and accessibility, plastic waste is a promising material for recycling and energy production. One potential solution is the use of machine learning and artificial intelligence (AI) to predict household plastic consumption, allowing policymakers to design effective strategies and initiatives to reduce plastic waste. Such information is a critical component to be able to efficiently plan for the collection and routing of trucks when collecting recyclable plastics. The development of new strategies for the recycling of plastic waste and development of new industry can address the import and export potential of the country to achieve self-sustainability as well as contribute to reduction in plastic pollution and amount of waste landfilled. These plastics can thereafter be used effectively for recycling and for the making of 3D printing filaments which fall under the SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible consumption and production).

In this study, leadership, social and technical system and organizational behavior theories were used to test the research model, consisting of six variables. The purpose of this study was to observe the impact of leadership styles (i.e. transformational leadership and empowering leadership) on organizational performance and innovation. In addition, the mediating role of shared leadership and mediating role of organizational culture in the model were measured.

This study relied on a quantitative design, specifically, a questionnaire, to obtain data from 301 employees in the health sector (three public-sector hospitals in the Basra Governorate).

Data analysis results showed that most of the relationships in the research model were positive. In addition, the results demonstrated the importance of the mediating variable in strengthening the relationship between the independent and dependent variables. The results of this study also clearly depicted the role of the mediating variable. Theoretical and practical implications were discussed, and proposals for future studies were presented.

This research focused on the use of modern leadership styles, collected data on such styles and included them in one model to enhance organizational output. This study was conducted in the context of the Iraqi health sector and can be distinguished from other studies by its adoption of a large sample to obtain clear and important results, thereby making it an important reference for researchers to improve organizational performance.

States that a major problem in dealing with information‐systems reliability is the design of a metric that combines the customer’s needs and preferences with the technical specifications and modular reliability of information systems. Develops one such metric, combining the customer’s requirements and utility with the technical structure of the system. The result is a single metric that can be used for tracking the performance of an information system and as an early signal of the system’s persistent malfunction and low quality of service. This metric can also contribute to the continuous improvement of system reliability by identifying the components whose improved reliability could make the most significant contribution to the overall reliability of the system.

The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.

Despite the growing interest in closed-loop manufacturing, there is a lack of comprehensive frameworks that integrate product development, production processes, people and policies (4Ps) to optimize sustainable manufacturing performance. This study investigates the influence of the four Ps of closed-loop manufacturing systems (product development, production processes, people and policies) on sustainable manufacturing performance (SMP).

To investigate the influence of the four Ps on SMP, a hybrid analytical model was employed, combining structural equation modeling (SEM) with artificial neural networks (ANN). Data were collected through a structured survey administered to 353 manufacturing firms in Malaysia. SEM was used to assess the relationships between the variables, while ANN was employed to capture nonlinear relationships and improve prediction accuracy.

The research findings demonstrate that product development practices, including eco-design, life cycle assessment and resource planning, exert the most significant influence on SMP. Furthermore, implementing green and lean manufacturing techniques, energy modeling and material utilization/toxicity planning significantly enhances sustainability outcomes. While the social setting (employee motivation, turnover and work–life quality) does not directly impact SMP, it plays a pivotal role in facilitating the implementation of internal environmental policies. Moreover, environmental management practices, both mandatory and voluntary, serve as intermediaries between the four Ps and SMP within closed-loop manufacturing systems.

The findings offer valuable insights for policymakers, industry leaders and manufacturing organizations. By prioritizing product development, implementing green and lean manufacturing practices and fostering a positive social setting, organizations can significantly enhance their sustainable performance. Additionally, the study highlights the importance of effective environmental management practices in mediating the relationship between other factors and SMP.

This study contributes to the literature by providing a comprehensive framework for understanding the factors that drive sustainable manufacturing performance. The hybrid SEM-ANN model offers a robust and innovative approach to analyzing the complex relationships between the four Ps and SMP.

Supply chain management has become critical in today’s globalized environment, with growingly intense competition on the international level. The particular characteristics of modern trade have led companies to globalize and devise increasingly sophisticated supply chains to meet customer demand worldwide. Motivated by the need to address these challenges, we have developed a new model for a global supply chain that incorporates uncertainties in exchange rates, demand fluctuations, and the quantity of produce.

The objective of the proposed model is to maximize supply chain profitability. Our model optimizes several critical decisions in the proposed global supply chain, including the location of domestic and foreign distribution centers, allocating the centers to customers, transportation mode selection, storage temperature, optimal farm purchase quantities, product flows across the network, and the shelf-life of products. Scenario-based stochastic programming approach is employed to account for the inherent uncertainties within the model. A pistachio supply chain is examined as a case study in this article, and the efficiency of the proposed model is demonstrated through computational results.

The model was solved using the CPLEX solver in GAMS and the results, the Sirjan DDC and Turkey FDC have been selected. In general, 40% of demand for customers from FDC (turkey) and 60% of demand from DDC (sirjan) is provided. Changes in the demand of foreign customers make the net profit more effective than changes in the demand for domestic customers. The decrease in exchange rate decreases the network profit with a higher slope and the increase in exchange rate will increase network profit with a relatively stable slope.

While research on GSCs for perishable products has been ongoing for several years, the importance of the subject necessitates continued investigation in this area. This paper aimed to address this gap by presenting an optimization model for designing GSCs for perishable products under uncertainty and with various transportation modes. The proposed model was designed with the aim of improving supply chain performance and real-world applicability.

This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic, tactical and operational decisions of three levels of blood collection, processing and distribution leads to satisfying the demand at the right time.

This paper proposes an integrated BSCN in disaster conditions to consider four categories of facilities, including temporary blood collection centers, field hospitals, main blood processing centers and medical centers, to optimize demand response time appropriately. The proposed model applies the location of all permanent and emergency facilities in three levels: blood collection, processing and distribution. Other essential decisions, including multipurpose facilities, emergency transportation, inventory and allocation, were also used in the model. The LP metric method is applied to solve the proposed bi-objective mathematical model for the BSCN.

The findings show that this model clarifies its efficiency in the total cost and blood delivery time reduction, which results in a low carbon transmission of the blood supply chain.

The researchers proposed an integrated BSCN in disaster conditions to minimize the cost and time of blood delivery. They considered multipurpose capabilities for facilities (e.g. field hospitals are responsible for the three purposes of blood collection, processing and distribution), and so locating permanent and emergency facilities at three levels of blood collection, processing and distribution, support facilities, emergency transportation and traffic on the route with pollution were used to present a new model.

The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design.

The study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies.

The results of the study present the researchers’ tendencies and preferences when designing their BSC network models.

The study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs.

The study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.