Electrical energy is known as an essential part of our day-to-day lives. Renewable energy resources can be regenerated through the natural method within a reasonably short time and can be used to bridge the gap in extended power outages. Achieving more renewable energy (RE) than the low levels typically found in today’s energy supply network will entail continuous additional integration efforts into the future. This study examined the impacts of integrating renewable energy on the power quality of transmission networks. This work considered majorly two prominent renewable technologies (solar photovoltaic and wind energy). To examine the effects, IEEE 9-bus (a transmission network) was used. The transmission network and renewable sources (solar photovoltaic and wind energy technologies) were modelled with MATLAB/SIMULINK^®. The Newton-Raphson iteration method of solution was employed for the solution of the load flow owing to its fast convergence and simplicity. The effects of its integration on the quality of the power supply, especially the voltage profile and harmonic content, were determined. It was discovered that the optimal location, where the voltage profile is improved and harmonic distortion is minimal, was at Bus 8 for the wind energy and then Bus 5 for the solar photovoltaic source.

This paper aims to advance the knowledge in the domain of youth entrepreneurship and empowerment in the United Arab Emirates (UAE). The rationale is to address the gap in knowledge on entrepreneurship and youth empowerment in the UAE by analyzing strategies and initiatives that support empowering millennials to achieve sustainable development, with the aim of promoting youth entrepreneurship and supporting sustainable economic development. The primary research question guiding this study is: “What strategies and initiatives in the UAE foster the empowerment of the millennial generation for sustainable development?” This study relies on a mixed methodology that combines a descriptive approach, content analysis, and data meta-analysis, with the aim of exploring the relationship between youth entrepreneurship and sustainable development in the United Arab Emirates. with a focus on the future sustainability leaders (FSL) program. While the FSL program demonstrates its significance in promoting youth entrepreneurship and empowerment, it also reveals certain limitations in its design and implementation that may hinder sustainable economic development. To address these challenges and support youth entrepreneurship, the paper proposes three essential action-oriented approaches: promoting participatory diversity and engagement, managing entrepreneurship drivers, and ensuring access to essential support mechanisms. These recommendations are intended to guide multilateral agencies, voluntary sectors, and private entities in the UAE in designing, evaluating, and implementing effective youth entrepreneurship programs. This paper underscores the importance of continued discourse and critical input to refine existing theories and establish a normative framework for youth entrepreneurship and empowerment. Such efforts are crucial for poverty reduction, sustainable development, and the promotion of intergenerational equity.

This study uses the opening of the new Mass Rapid Transit (MRT) in stages between 2010 and 2012 in Singapore as the exogenous event to empirically test the impact of the new Circle Line (CL) on housing wealth. Applying a "differences-in-differences" approach to the non-landed private housing transaction data covering the period from 2009 to 2013, we find that the average housing prices increase by 1.6% in the post-opening of the CL. We find significant capitalization of the new CL into housing prices, especially households living within a 400-meter radius (the treatment zone) from the closest MRT stations on the CL. The treatment effects that are measured by the "marginal willingness to pay" for houses located within the treatment zone is 13.2% relative to houses located outside the treatment zone. The new CL opening creates an estimated S$1.23 billion housing wealth effects for households living in close proximity to the CL MRT stations. However, we do not find significant "anticipative" effects on house prices in the six-month window prior to the opening of CL. The strongest treatment effect is found after the opening of the phase 1 of CL, and the treatment intensity declines in phases 2 and 3 of the CL opening.

Cyclically, the debate on Keynes’ economic policies reemerge. The economic impact of the pandemic caused by COVID-19 has relaunched the discussion about the importance of Keynesian policies, the multipliers effects, and their impact on stimulating economies. This paper aims to analyze the importance and relevance of the Keynesian multiplier before the pandemic, in a period without experiencing exceptional aggregate shocks. The main focus of the research is to examine the shortcomings of the public investment multiplier, which plays a central role in Keynesian theory. Despite the undeniable relevance of the concept, the issue is to understand the extent to which the multiplier is still relevant in specific contexts. The research presents empirical evidence which suggests that the effects of public investment depend on structural characteristics of economies specifically trade liberalization, the dimension of internal markets, the question of countries having the freedom to issue their currency, and the issue of currencies being accepted as an international reserve. A sample of 35 OECD countries was used for the period 2010–2018. The Keynesian public investment multiplier was calculated for several countries and the obtained values were related to various correlations carried out to assess the relationship between public investment, national income, and specific characteristics of the economies to which the multipliers are sensitive. The results obtained contrast in terms of short-term and long-term impacts so, is at least dubious, that one can rely on Keynesian public policies to boost economies at least in the absence of substantial shocks to aggregate demand.

As a product of the integration of AI technology and media, the debate surrounding the potential replacement of human anchors by AI anchors has persisted since their inception. This paper conducts a systematic literature review of research on AI anchors in China from 2000 to 2023, grounded in theories of personalization within the field of communication studies. The analysis aims to compare the differences in personalized representation between AI anchors and human anchors, summarizing the advancements, challenges, and future directions of AI anchor communication based on personality. This contribution seeks to enhance the existing knowledge base surrounding AI anchor research.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.