Countering cyber extremism is a crucial challenge in the digital age. Social media algorithms, if designed and used properly, have the potential to be a powerful tool in this fight, development of technological solutions that can make social networks a safer and healthier space for all users. this study mainly aims to provide a comprehensive view of the role played by the algorithms of social networking sites in countering electronic extremism, and clarifying the expected ease of use by programmers in limiting the dissemination of extremist data. Additionally, to analyzing the intended benefit in controlling and organizing digital content for users from all societal groups. Through the systematic review tool, a variety of previous literature related to the applications of algorithms in the field of online radicalization reduction was evaluated. Algorithms use machine learning and analysis of text and images to detect content that may be harmful, hateful, or call for violence. Posts, comments, photos and videos are analyzed to detect any signs of extremism. Algorithms also contribute to enhancing content that promotes positive values, tolerance and understanding between individuals, which reduces the impact of extremist content. Algorithms are also constantly updated to be able to discover new methods used by extremists to spread their ideas and avoid detection. The results indicate that it is possible to make the most of these algorithms and use them to enhance electronic security and reduce digital threats.
Although public-private partnership (PPP) is regarded as one of the key effective tools in the development of many countries, various challenges surrounding PPPs are not well understood. This paper explores nine key challenges in PPP implementation: (1) different organizational cultures and goals between the partners, (2) poor institutional environment and support, (3) weak political and legal frameworks, (4) unreliable mechanisms for sharing risk and responsibility, (5) inadequate procedures for the selection of PPP partners, (6) inconsistency between resource inputs and quality, (7) inadequate monitoring and evaluation of PPP processes, (8) lack of transparency, and (9) the inherent nature of PPPs. This paper aims to provide the perceptions in the existing literature on many of these challenges, as well as provide solutions to each challenge.
Given the increasing demand for sustainable energy sources and the challenges associated with the limited efficiency of solar cells, this review focuses on the application of gold quantum dots (AuQDs) in enhancing solar cell performance. Gold quantum dots, with their unique properties such as the ability to absorb ultraviolet light and convert it into visible light expand the utilization of the solar spectrum in solar cells. Additionally, these quantum dots, through plasmonic effects and the enhancement of localized electric fields, improve light absorption, charge carrier generation (electrons and holes), and their transfer. This study investigates the integration of quantum dots with gold plasmonic nanoparticles into the structure of solar cells. Experimental results demonstrate that using green quantum dots and gold plasmonic nanoparticles as intermediate layers leads to an increase in power conversion efficiency. This improvement highlights the significant impact of this technology on solar cell performance. Furthermore, the reduction in charge transfer resistance and the increase in short-circuit current are additional advantages of utilizing this technology. The findings of this research emphasize the high potential of gold quantum dots in advancing next-generation solar cell technology.
Poly(methyl methacrylate) (PMMA) is a versatile and widely used polymer that has gained significant attention in various industries due to its unique combination of properties and ease of processing. PMMA, also known as acrylic or plexiglass, is a transparent thermoplastic with exceptional optical clarity, high-impact resistance, and excellent weatherability. This scholarly article endeavors to offer an exhaustive examination of the composition, characteristics, and broad utilization of poly(methyl methacrylate) (PMMA). This study aims to conduct an in-depth analysis of the molecular composition and chemical attributes inherent to PMMA. Furthermore, it intends to examine the mechanical and physical attributes exhibited by PMMA meticulously. Additionally, an exploration of varied methodologies employed in the processing and fabrication of PMMA will be undertaken. The extensive array of applications of PMMA spanning multiple industries will be underscored, followed by a comprehensive discourse on its merits, constraints, contemporary advancements, and prospective avenues. Understanding the properties and applications of PMMA is crucial for engineers, scientists, and professionals working in fields such as automotive, aerospace, medical, and signage, where PMMA finds extensive use.
The potential role of self-regulated learning as mediator has been deeply investigated by researchers in recent years. There is limited systematic literature review being done to investigate the role of self-regulated learning as mediator in the students’ academic learning. Therefore, searching studies in the databases WOS (Web of Science), SCOPUS, APA (American Psychological Association) PsycInfo, and ERIC (Education Resources Information Center), the present study conducted a systematic literature review on 32 studies published between 2015 and 2024 to summarize what kind of psychological factors influence students’ academic performance through self-regulated learning and assess the potential mediating role of self-regulated learning in this process. The results show that self-efficacy, emotions and motivation are significant predictors of academic achievement and self-regulated learning act as an important mediator in this relationship. An important implication was obtained that researchers can probe into the influence of specific dimensions of self-efficacy on learning performance through self-regulated learning and the influence of positive emotions such as resilience on learning outcomes with self-regulated learning as mediator.
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