The prospects of digital infrastructure in promoting rural economic growth and development are by and large immense. The paper found that rural development is considerably important for economic development and for achievement of sustainable livelihoods that increases people’s ability to achieve good health and wellbeing that enable the achievement of sustainable development. The paper found that digital imbalance and digital illiteracy in the rural areas hinder implementation of digital infrastructure to lead to rural economic growth. Digital infrastructure is the source of economic opportunities that enables local people in the rural areas to be more creative in achieving development success. It enables them to have a unique sense of place and fashioning of vibrant economic and financial opportunities that ensure the achievement of sustainable rural economic development. However, the paper found that the application of digital infrastructure to South Africa’s rural areas in the bid to promote rural economic growth has been hindered by factors like the digital divide, financial constraints, digital illiteracy and the failure to own a smart phone. These factors hinder digital infrastructure from leading to sustainable rural economic development and growth. The paper used secondary data gathered from existing literature. The use of qualitative research methodology and document and content analysis techniques became vital in the process of collecting and analyzing collected data.

In wealthy nations, biofuel usage has grown in importance as a means of addressing climate change concerns, ensuring energy security, and promoting agricultural development. Because they understand the potential advantages of biofuel for rural development and job creation, governments have created policies and legislation to encourage the production of biofuel. However, the province of Limpopo hasn’t fully taken advantage of the potential to use biofuel production as a vehicle for job development, despite a higher demand for the fuel. There is currently a lack of understanding of the role of biofuel in promoting local development in developing regions. For this reason, this study made use of semi-structured interviews to explore how biofuel production can be used as an instrument for Local Economic Development (LED) in the Limpopo province of South Africa. The research investigated the determinants of empowerment that could impact the commercial feasibility of biofuel production in the province. It also identified the need for human resource development to get workers ready for jobs in Limpopo’s biofuel sector. The results showed that, provided certain conditions were met, the production of biofuel in Limpopo may be a useful instrument for creating local jobs. By highlighting the potential for job creation and the importance of human resource development, this research aims to facilitate evidence-based decision-making that can harness biofuel production for sustainable rural development in the region. The value of this study lies in its contribution to the understanding of biofuel’s role in LED, offering actionable insights for policymakers and stakeholders in Limpopo. 

Historically, women have faced progressive and persistent obstacles and prejudices preventing them from fully participating in and receiving recognition for scientific research in academia. In Panama, local gender studies specifically targeting the area of academia are scarce. However, to close the gender gap, this article tries to uncover the realities of women academics who dare to research and do science in Panama, beyond statistics. A virtual survey was distributed from May to August 2023, in which 921 academics (45% men and 55% women) affiliated with public universities in Panama were surveyed. Through an empirical analysis from a gender perspective, participants’ attitudes and perceptions on the effects of the covid-19 pandemic on research, the quality of higher education in Panama, the dissemination and transmission of knowledge, and research as an adjuvant to higher education were revealed. Findings reiterate the gender bias and underrepresentation of women in Panamanian public universities and the lack of commitment to their capacity building, research, and dissemination of results. It also confirmed that, despite the covid-19 pandemic and its negative effects in all areas, the importance and recognition of scientific research were highlighted, allowing women academics to excel competitively and take advantage of new opportunities in their career development.

Photovoltaic systems have shown significant attention in energy systems due to the recent machine learning approach to addressing photovoltaic technical failures and energy crises. A precise power production analysis is utilized for failure identification and detection. Therefore, detecting faults in photovoltaic systems produces a considerable challenge, as it needs to determine the fault type and location rapidly and economically while ensuring continuous system operation. Thus, applying an effective fault detection system becomes necessary to moderate damages caused by faulty photovoltaic devices and protect the system against possible losses. The contribution of this study is in two folds: firstly, the paper presents several categories of photovoltaic systems faults in literature, including line-to-line, degradation, partial shading effect, open/close circuits and bypass diode faults and explores fault discovery approaches with specific importance on detecting intricate faults earlier unexplored to address this issue; secondly, VOSviewer software is presented to assess and review the utilization of machine learning within the solar photovoltaic system sector. To achieve the aims, 2258 articles retrieved from Scopus, Google Scholar, and ScienceDirect were examined across different machine learning and energy-related keywords from 1990 to the most recent research papers on 14 January 2025. The results emphasise the efficiency of the established methods in attaining fault detection with a high accuracy of over 98%. It is also observed that considering their effortlessness and performance accuracy, artificial neural networks are the most promising technique in finding a central photovoltaic system fault detection. In this regard, an extensive application of machine learning to solar photovoltaic systems could thus clinch a quicker route through sustainable energy production.

It is important for society to know the actions implemented by companies in the construction sector to reduce the environmental pollution generated by this industry and to contribute to the solution of economic and social problems in their environment; however, the variables that allow identifying their contributions and impacts are not known. Based on this problem, the study focuses on identifying the factors that influence sustainability management within the construction sector in Colombia. The research presents a predictive approach and uses a quantitative methodology, applying statistical modeling techniques. The sample corresponds to 84 Colombian companies. As a result, a system of equations of the form y=mx+b is presented to describe the deviation of the environmental, economic, social, compensation measures, management, indicators and sustainability reports. The analysis of the intersections constitutes a projective tool to evaluate the relationships and balance points between the dimensions analyzed, helping to identify strengths and opportunities for improvement.