The economy of Bali heavily relies on the tourism sector, leading to economic vulnerability. There are numerous challenges in Bali's economy, with COVID-19 being one of the most prominent examples. During the COVID-19 pandemic, Bali's economy experienced the deepest contraction and slowest recovery compared to other provinces in Indonesia. Amid this economic vulnerability, it is important to conduct research on the financial resilience of SMEs in Bali. This research aims to analyze the influence of financial literacy on financial resilience, as well as the mediating role of financial performance and fintech adoption on the impact of financial literacy on financial resilience among SMEs in Bali. The research method used is a quantitative approach with a sample of 177 SMEs in Bali, selected through non-probability sampling techniques. Data were analyzed using descriptive and inferential statistics, with SEM-PLS in SmartPLS 3.0 program. The test results indicate that financial literacy has a positive and significant influence on financial resilience, financial performance, and fintech adoption. Financial performance and fintech adoption also have a positive and significant impact on financial resilience. Furthermore, financial performance and fintech adoption can partially mediate the influence of financial literacy on financial resilience in SMEs in Bali. The findings of this research are beneficial for the development of Knowledge-Based View theory and Technology Acceptance Model, as well as for SMEs in Bali and the government as policy makers in efforts to enhance financial resilience.

It is argued that managers took advantage of Covid-19 pandemic lockdowns and remote auditing and used earnings management (EM) practices extensively. Furthermore, the Covid-19 pandemic created new unsearched crisis-related incentives. This study, therefore, tests whether Covid-19 created a new incentive for managers to manipulate earnings. It also examines the association between corporate social responsibility (CSR) and board independence and EM during Covid-19. A data set of 384 firm-year observations from 2018 to 2021 of non-financial firms listed on the Amman Stock Exchange (ASE) was investigated. Results indicate that Jordanian firms engaged in EM during Covid-19 considerably more than when compared to pre-Covid-19, suggesting that Covid-19 created a new incentive for managers to manipulate earnings. Furthermore, Jordanian firms used income-increasing EM much more when compared to income-decreasing EM. However, when taking Covid-19 into account, no significant association was found between board independence and EM. In addition, the ability of CSR to constrain EM decreased. This adds to the current debate in the literature that even well-established monitoring mechanisms like board independence and CSR are unable to constrain EM practices in a unique business environment caused by Covid-19.

A series of new pyrrole-coupled carboxamide derivatives had been synthesized and amply characterized by various techniques, viz FTIR, 1H-NMR, 13C-NMR, and LCMS. All these compounds had undergone evaluation for their PASS, BBB, pharmacophore model, ADME, and bioactive score. The antibacterial properties of all the derivatives were examined and compound 5i demonstrated strong antibacterial activity against MRSA. A membrane damage investigation supported by SEM pictures, cellular content leakage, potassium efflux, and bacterial respiration suppression showed that compound 5i had anti-MRSA properties. A good binding score of -9.11 was found for compound 5i against the MRSA protein 6FTB in an in silico molecular docking analysis, compared to a score of -10.25 for streptomycin. Based on these findings, compound 5i can be further studied in order to develop it as a drug to treat MRSA infections.

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.

Offshore oil exploration in deeper waters has necessitated the development of lighter mooring systems to replace traditional steel cable and chain platforms. This study focuses on evaluating the mechanical behavior and fatigue degradation mechanism of high modulus polyethylene (HMPE) fibers in yarn-on-yarn abrasion tests. Initial characterization tests, including linear density, rupture force, and thermal analysis, were conducted on HMPE yarns. Yarn-on-yarn abrasion tests were performed under dry, wet, and salty conditions, with varying loads, while statistical analysis examined the influence of environmental factors and load levels on yarn performance. Scanning electron microscopy (SEM) analysis provided insights into material degradation mechanisms. Results showed superior performance in freshwater-immersed yarns due to cooling and lubrication effects, while dry conditions led to material melting. SEM analysis revealed critical degradation zones, particularly in interwoven regions, where increased friction and heat concentration caused material fusion. Degradation evolution mechanisms highlighted fatigue-induced rupture of yarns, knot formation, and material melting near failure points. This comprehensive analysis enhances understanding of HMPE yarn performance and degradation in offshore mooring applications, laying the groundwork for developing advanced mooring systems capable of withstanding deep-sea environments.

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.

Low-speed impacts are common occurrences in industries such as aviation, automotive, and marine. Yet they have received relatively little attention compared to medium and high-speed impacts. Understanding the behavior of materials under low-speed impact is crucial for ensuring impact resistance and damage absorption in engineering structures. This study presents an experimental investigation into the low-speed impact behavior of 1050 aluminum alloy plates. Impact tests were conducted using a CEAST 9340 drop-weight testing machine, varying impact energies and temperatures to analyze their effects on the material. The findings highlight the importance of understanding the dynamic response of engineering materials under low-speed impact loading conditions. The insight gained from this study informs the design and optimization of aerospace and automotive structures to enhance their impact resistance and structural integrity. The results of the study indicate an inverse relation between the temperature of the impacted specimen and the maximum contact force.

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.