Over time, the number of smart grids installed worldwide is gradually increasing. However, the major portion of the required electricity is still being produced by traditional large-scale and centralized power systems. The main requirement, then, is to study and develop mathematical methods that attend the integration between the two systems previously announced. In this paper, a novel model that addresses this issue is presented. The model minimizes the total operating cost of the large-scale system considering the participation of the smart grid as a dynamic entity, entailing a close relationship between both systems. This approach distinguishes the novel proposal from others that solve similar situations by taking into account the two systems in isolation. Besides, the models that represent the most common organizational structures of the smart grids are also presented in this paper. They are needed to develop the integrated model. Many similar problems in the literature are solved by implementing decomposition techniques, which might obtain a local optimum different from the global one. By contrast, problems with this proposal are solved by using mixed-integer linear programming models that ensure the reaching of a global optimum. The real test case is the integrated Argentine large-scale system and the Armstrong smart grid. Results indicate that the novel model can reach solutions that are 5% lower in comparison with the traditional techniques of considering in isolation. Efficient CPU times enable the possibility of promptly obtaining solutions if there is any change in the parameters. In addition, other benefits, apart from the economical reductions, are also achieved. Operating information closer to the reality of both systems is obtained because it considers the effects of the smart grid in large-scale system solving.

The global economy, including the banking sector in the ASEAN region, has experienced significant impacts due to the COVID-19 pandemic. To understand its impact more deeply, this research aims to evaluate banking stability and performance during the pandemic period, with a focus on risk governance and financial factors. A total of 272 banks in the ASEAN region were included in this study, using specific criteria depicting risk governance and financial factors. The research findings indicate a positive relationship between risk governance factors (RC, RCS, RCM and CRO) towards Financial Sustainability. The implications of these findings not only have theoretical relevance in understanding banking dynamics during crisis periods but also have important practical implications for decision-makers in the banking sector and financial regulation. Further discussion on theoretical and practical implications is provided, offering a better understanding of the challenges and opportunities in maintaining financial sustainability in the context of uncertain economic situations, such as those brought about by the global pandemic.

This study aims to examine the influence of the psychosocial work environment on the proclivity for asset misuse in the context of local government management, with a focus on the perceptions of administrators in Central Sulawesi Province. Employing purposive sampling, a total of 39 government units constituted the study's population, with a final sample size of 114 participants, comprising administrators, officers, and managers. WarpPLS software was employed to analyze the data. The findings reveal a positive relationship between rationalization and the inclination toward asset misuse. Additionally, rationalization exhibits a negative impact on the psychosocial work environment. Finally, the psychosocial work environment demonstrates a negative influence on the propensity for asset abuse. These outcomes suggest that the psychosocial work environment plays a pivotal role in mitigating the inclination for asset misuse within the local government of Central Sulawesi Province. This research sheds light on the significance of fostering a positive psychosocial work environment to enhance decision-making processes and reduce the likelihood of fraudulent activities in the management of government assets. Understanding these dynamics is crucial for the development of strategies to promote ethical and responsible asset management in local government entities.

Hyperbranched polyester polyols have emerged as a promising candidate for polyurethane coatings due to their unique structure and properties. In this context, this paper aims to synthesize a new hyperbranched polyester polyol and evaluate its potential as a polyol for polyurethane coating applications. In this study, the synthesis of hyperbranched polyester polyol involves the reaction between a multifunctional alcohol and a multifunctional carboxylic acid or anhydride. It is further modified by incorporating 2-hydroxyethyl methacrylate and styrene. The properties of the polyester polyol were characterized using various analytical techniques, including FTIR, NMR, SEM and TGA. This paper also provides a discussion on the potential applications of the synthesized hyperbranched polyester polyol in several industries such as automotive, aerospace and construction.

This research investigates the relationships between investors’ behavioral biases and compares their relative importance. For this purpose, a survey is conducted, and analytical methods are used. The sample for this study has been 512 individual investors of the Tehran Stock Exchange who completed an online questionnaire. The respondents replied about their behavior in different situations to analyze the prevalence of asymmetric discounting, mental accounting, shifting risk preference, loss aversion, regret aversion, overconfidence, proxy decision making, ambiguity aversion bias, anchoring, and herd behavior as significant fields of behavioral biases in their investment decisions. The data is analyzed using two different analytical techniques. A model based on structural equations is designed and tested to analyze the relations between these fields. Another integrated method, the DEMATEL-based analytic network process, is also used to prioritize and rank these behavioral biases. Finally, the results are compared and confirmed by each other. Analyzing the results proves the existence of 19 positive and statistically significant relations between these fields. Thus, an increase or decrease in the intensity of a particular field of behavioral biases in one’s decisions significantly affects the intensity of other fields. The present study finds that shifting risk preference, anchoring, loss aversion, and regret aversion are the most important fields of behavioral biases based on their prevalence among investors and their correlations with other biases.

Due to its proactive impact on the serviceability of components in a system, preventive maintenance plays an important role particularly in systems of geographically spread infrastructure such as utilities networks in commercial buildings. What makes such systems differ from the classical schemes is the routing and technicians' travel times. Besides, maintenance in commercial buildings is characterized by its short tasks’ durations and spatial distribution within and between different buildings, a class of problems that has not been suitably investigated. Although it is not trivial to assign particular duties solely to multi-skilled teams under limited time and capacity constraints, the problem becomes more challenging when travel routes, durations and service levels are considered during the execution of the daily maintenance tasks. To address this problem, we propose a Mixed Integer Linear Programming Model that considers the above settings. The model exact solution recommends collaborative choices that include the number of maintenance teams, the selected tasks, routes, tasks schedules, all detailed to days and teams. The model will reduce the cost of labor, replacement parts, penalties on service levels and travel time. The optimization model has been tested using different maintenance scenarios taken from a real maintenance provider in the UAE. Using CPLEX solver, the findings demonstrate an inspiring time utilization, schedules of minimal routing and high service levels using a minimum number of teams. Different travel speeds of diverse assortment of tasks, durations and cost settings have been tested for further sensitivity analysis.

This study examines the interaction effect between transformational leadership, transactional leadership, wireless IT competence, ambidexterity and supply chain management capability in increasing innovation capability. By using a knowledge-based view and dynamic capability theory basis, this research has provided an exploration of the supply chain of a merchant marine college and its impact on innovation capability using a quantitative method approach. The authors collected data from a cross-section of 673 questionnaires distributed to Managers in 3 managerial classifications from top, middle and bottom in the technical service unit of the merchant marine college under the Indonesian Ministry of Transportation. A total of 523 data were collected from questionnaires that could be continued for data analysis. The results of this study indicate that all the hypotheses put forward in this study are accepted, and the role of mediating variables in this research has succeeded in demonstrating their role in mediating each antecedent variable to increase innovation capability. The theoretical implication of this research is the growth of cloud or virtual supply chains facilitated by digital wireless communications, and internet technology is advancing logistics and supply chain innovations. Also, it can reinforce theory and dynamic capability.

Pyrazolones are a class of heterocyclic compounds that contain a pyrazole ring fused to a ketone group. Recent scientific research has focused extensively on the potential anti-inflammatory properties of pyrazolone compounds due to their diverse pharmacological effects in alleviating inflammation and reducing fever. This motivated us to focus on the preparation of these derivatives in a simple and eco-friendly manner. A convenient new green methodology was modified for the preparation of 1-phenyl-3,5-pyrazolidinedione by the sonicated MCR of diethyl malonate, phenylhydrazine, and a catalytic amount imidazole as homogenous organic catalyst in water green solvent in a good yield. On the other hand, some of 4-arylidinepyrazolidinedione derivatives are prepared in the same manner via the treatment of a mixture of diethyl malonate, phenylhydrazine, aromatic aldehydes, and a catalytic amount of imidazole in an aqueous medium. Our target synthesized pyrazolidinediones were elucidated via elemental and several spectral analyses. Due to the importance of pyrazolidinediones in the field of treating inflammation and relieving pain, a number of prepared compounds were chosen to test their efficacy as anti-inflammatory agents using carrageenan-induced foot edema in rats and compare the results with indomethacin, the standard drug. We found that the majority of derivatives yield promising results spanning from good to wonderful, so derivatives (15k, 15b, 15h, 15a, and 15j) yield the best results while derivative (15i) yields an average result. As for the derivative (15f), it yields the lowest results compared to the standard drug. This is due to the difference in the structural composition of these derivatives, which increases the likelihood of their use as anti-inflammatory derivatives.

The socio-economic development of each country requires the contribution of businesses to social goals and the state budget. Improving tax compliance behavior is consistent with improving the ability of businesses to contribute to the budget. The objective of the study is to evaluate factors affecting tax compliance behavior for businesses. The study is conducted on 202 enterprises in Thai Nguyen, a locality located in the key economic region of Vietnam and with a high level of economic development. Through quantitative analysis of the research results, it found that: the system legislation and socio-economic conditions have the strongest influence on businesses' tax compliance behavior. However, the influence of business characteristics and tax authority characteristics on tax compliance behavior is lower.

The Refrigerated Capacitated Vehicle Routing Problem (RCVRP) considers a homogeneous fleet with a refrigerated system to decide the selection of routes to be performed according to customers' requirements. The aim is to keep the energy consumption of the routes as low as possible. We use a thermodynamic model to understand the unloading of products from trucks and the variables' efficiency, such as the temperature during the day influencing energy consumption. By considering various neighborhoods and a shaking procedure, this paper proposes a Granular Tabu Search scheme to solve the RCVRP. Computational tests using adapted benchmark instances from the literature demonstrate that the suggested method delivers high-quality solutions within short computing times, illustrating the refrigeration system's effect on routing decisions.