In today’s manufacturing sector, high-quality materials that satisfy customers’ needs at a reduced cost are drawing attention in the global market. Also, as new applications are emerging, high-performance biocomposite products that complement them are required. The production of such high-performance materials requires suitable optimization techniques in the formulation/process design, not simply mixing natural fibre/filler, additives, and plastics, and characterization of the resulting biocomposites. However, a comprehensive review of the optimization strategies in biocomposite production intended for infrastructural applications is lacking. This study, therefore, presents a detailed discussion of the various optimization approaches, their strengths, and weaknesses in the formulation/process parameters of biocomposite manufacturing. The report explores the recent progress in optimization techniques in biocomposite material production to provide baseline information to researchers and industrialists in this field. Therefore, this review consolidates prior studies to explore new areas.

Nanotechnology is recognized as one of the high and new technologies in the 21st century. Carbon nanotubes have been widely used in molecular sieve, drug transport and seawater desalination due to their unique mechanical, electrical, optical and other excellent properties. As the main representative of carbon nanotube macroscopic materials, carbon nanotube film not only retains the microscopic properties of carbon nanotube, but also has good mechanical properties and stable chemical properties. The preparation and application of carbon nanotubes (CNTS) have attracted extensive attention from scholars at home and abroad. In this paper, the research on carbon nanotube films in recent years is reviewed. Based on the preparation of carbon nanotube films, chemical vapor deposition, LB (Langmuir-Blodgett) film and electrostatic layer-by-layer self-assembly techniques are briefly described. In addition, the applications of carbon nanotubes in biological field, photoelectric nano devices, water treatment, seawater desalination and other fields are also described.

The fifth-generation technology standard (5G) is the cellular technology standard of this decade and its adoption leaves room for research and disclosure of new insights. 5G demands specific skillsets for the workforce to cope with its unprecedented use cases. The rapid progress of technology in various industries necessitates a constant effort from workers to acquire the latest skills demanded by the tech sector. The successful implementation of 5G hinges on the presence of competent individuals who can propel its progress. Most of the existing works related to 5G explore this technology from a multitude of applied and industrial viewpoints, but very few of them take a rigorous look at the 5G competencies associated with talent development. A competency model will help shape the required educational and training activities for preparing the 5G workforce, thereby improving workforce planning and performance in industrial settings. This study has opted to utilize the Fuzzy Delphi Method (FDM) to investigate and evaluate the perspectives of a group of experts, with the aim of proposing a 5G competency model. Based on the findings of this study, a model consisting of 46 elements under three categories is presented for utilization by any contingent of 5G. This competency model identifies, assesses, and introduces the necessary competencies, knowledge, and attributes for effective performance in a 5G-related job role in an industrial environment, guiding hiring, training, and development. Companies and academic institutions may utilize the suggested competency model in the real world to create job descriptions for 5G positions and to develop curriculum based on competencies. Such a model can be extended beyond the scope of 5G and lay the foundation of future wireless cellular network competency models, such as 6G competency models, by being refined and revised.

Illegal, unreported, and unregulated fishing (IUU fishing) crimes by rogue fisheries companies are rife in the sea waters of Riau Province. However, this issue is rarely reported by those provincial journalists in the online media where they work. In fact, in Riau, there are 163 online media companies and 600 competent journalists; 200 of them live in capture fisheries center areas. Apart from the journalist competency factor, the decision to make IUU fishing news can also be influenced by the fisheries company intervention that committed the crime. Besides, the policy role of media leaders—editors, editors-in-chief, and media owners—also determines journalists’ decisions to make those news stories. This research aims to analyze the influence of journalist competence and fishing company intervention on the decision to make IUU fishing news, as well as the role of media leader policy as mediators in these influences. This survey involved 100 competent journalists as respondents. Data collection was carried out through a questionnaire containing a number of closed statements measured on a 5-point Likert scale, which was distributed to respondents. The data were analyzed using the Structural Equation Modeling (SEM) method. The research results show that the fishing company intervention has a negative and significant influence on the decision to make IUU fishing news in Riau, while journalist competence does not. Additionally, media leader policy was found to play a significant role in mediating the influence of fisheries company intervention and journalist competence on the decision to make IUU fishing news. The leader policy could prevent journalists from making IUU fishing news if fisheries companies, who are responsible for those crimes, intervene and request it. Those actions of media leaders need to be questioned because they can hamper the media’s function as a means of disseminating information, educating the public, and implementing social control, especially those related to combating IUU fishing crimes.

This study investigated the relationship between telecommunications development, trade openness and economic growth in South Africa. It determined explicitly if telecommunications development and trade openness directly impact economic growth or whether telecommunications strengthen or weaken the link between trade openness and economic growth using the ARDL bounds test methodology. The findings reveal that both telecommunications development indicators and trade openness significantly and positively impact South Africa’s GDP in the short and long terms. The study also found that control variables like internet usage and gross fixed capital formation significantly and positively influence GDP. Conversely, inflation was found to consistently affect GDP negatively and significantly. The findings from the ARDL cointegration analysis affirm a long-run economic relationship between the independent variables and GDP. The study also established that telecommunications development slightly distorts trade in the foreign trade-GDP nexus in South Africa. Despite this, the negative interaction effect is not substantial enough to overshadow the positive impact of trade openness on economic growth. From a policy perspective, the study recommends that South African policymakers prioritise enhancing local goods’ competitiveness in global markets and reducing trade barriers. It also advocates for improving the accessibility and affordability of telecommunications technologies to foster economic development.

This study examines the effectiveness of Kazakhstan’s grant funding system in supporting research institutions and universities, focusing on the relationship between funding levels, expert evaluations, and research outputs. We analyzed 317 projects awarded grants in 2021, using parametric methods to assess publication outcomes in Scopus and Web of Science databases. Descriptive statistics for 1606 grants awarded between 2021 and 2023 provide additional insights into the broader funding landscape. The results highlight key correlations between funding, evaluation scores, and journal publication percentiles, with a notable negative correlation observed between international and national expert evaluations in specific scientific fields. A productivity analysis at the organizational level was conducted using non-parametric methods to evaluate institutional efficiency in converting funding into research output. Data were manually collected from the National Center of Science and Technology Evaluation and supplemented with publication data from Scopus and Web of Science, using unique grant numbers and principal investigators’ profiles. This comprehensive analysis contributes to the development of an analytical framework for improving research funding policies in Kazakhstan.