In this paper, a solar tracking device that can continuously track the sun by adjusting the direction and angle of the solar panel in real time is designed and fabricated to improve the power generation efficiency of the solar cell panel. The mechanical parts as well as the automatic control part of the passive sun-tracking system are described, and the efficiency enhancement with the sun-tracking solar panel is characterized in comparison with the fixed panel system. The test results show that in the spring season in Qingdao city of eastern China, the sun-tracking system can improve the solar cell power generation efficiency by 28.5%–42.9% when comparing to the direction and elevation angle fixed system in sunny days. Even in partly cloudy days, the PV power output can increased by 37% with using the passive sun-tracking system. Economic analysis results show the cost-benefit period is about 10 years, which indicates that the passive sun tracking device can substantially contribute to the solar energy harvest practices.

Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.

The ultimate objective of the study was to investigate the effects of being landlocked on the living standards in Sub-Saharan African (SSA) countries from 1991 to 2019. Adopting the two-step estimation technique of System GMM (generalized method of moments), the study found that being landlocked has a negative and significant effect on the living standards in SSA countries when using GDP per capita as the living standard measure. Moreover, the historical living standard experiences of SSA countries have a positive and significant influence on the current living standard level. In addition, the population growth rate has a positive and significant effect on the living standards in SSA countries. On the other hand, the official exchange rate, broad money as a percentage of GDP, and inflation have a negative and significant effect on the living standards in SSA countries. Generally, the estimated result reveals the existence of a significant variation in the living standards in landlocked and coastal SSA countries. This study suggests that regional integration between landlocked and transit countries should be improved to minimize entry costs and increase access to global markets for landlocked countries. We argue that this study is of interest to landlocked and coastal countries to increase trade integration and promote the development of both groups, and it will contribute to the scarce empirical evidence.

In this paper, we deal with one of the most urgent and relevant topics nowadays, i.e., water pollution. The problem is finding a valid candidate for the absorption and removal of different kinds of pollutants commonly found in water. There are already some indications about graphene oxide as a potential candidate. In the present work, we take a step forward to show how graphene nanoplatelets (rather than the oxide form of this material) are capable of decontaminating water. In this starting step, we use a specific substance as a model pollutant, i.e., acetonitrile, leaving for the future steps, to extend the analysis to additional types of pollutants. In addition to laboratory-produced graphene nanoplatelets, we already examined in the past; now we wish to consider also commercially available ones, so that the new results will not be bound to a laboratory (low technology readiness level) material, but will become interesting also from the industrial point of view, thanks to the scalability of the nanoplatelets production. For this aim, we compare the performance of two types of filters based on two classes of nanomaterials, i.e., those produced by microwave and ultrasound assisted exfoliation, already analyzed in our earlier works, with those commercially distributed by an Italian company, i.e., NANESA, http://www.nanesa.com/. The latter is an innovative SME involved in the production of graphene-based nanomaterials. We focus here in the graphene nanoplatelets, commercially available in industrial batches (GXNan grades). The present study leads to determine which filtering membrane, among the various types of commercial graphene considered, shows the greatest stability, and the lack of breakage of the membrane, concentrating on such accessory features, given that all types of graphene showed excellent adsorption properties.

Scholars widely agree that modular technologies can significantly improve environmental sustainability compared to traditional building methods. There has been considerable debate about the viability of replacing traditional cast-in-place structures with modular construction projects. The primary purpose of this study is to determine the feasibility of using modular technology for construction projects in island areas. Thus, it is necessary to investigate the potential problems and suitable solutions associated with modular building project implementation. This study is accomplished through the use of qualitative and quantitative methods. It systematically examines desk research based on the wide academic literature and real case studies, collating secondary data from government files, news articles, professional blogs, and interviews. This research identifies several important barriers to the use of modular construction projects. Among the issues are the complexity of stakeholder engagement, limited practical skills and construction methodologies, and a scarcity of manufacturing capacity specialised for modular components. Fortunately, these unresolved challenges can be mitigated through fiscal incentives and governmental regulations, induction training programmes, efficient management strategies, and adaptive governance approaches. As a result, the findings support the feasibility of starting and advancing modular building initiatives in island areas. Project developers will likely be more willing to embrace and commit resources to initiate modular building projects. Additional studies can be undertaken to acquire the most recent first-hand data for detailed validation.

The food industry progressively requires innovative and environmentally safe packaging materials with increased physical, mechanical, and barrier properties. Due to its unique properties, cellulose has several potential applications in the food industry as a packaging material, stabilizing agent, and functional food ingredient. A coffee pod is a filter of cellulosic, non-rigid, ready-made material containing ground portions and pressed coffee prepared in dedicated machines. In our study, we obtained, with homogenization and sonication, cellulose micro/nanoparticles from three different coffee pods. It is known that nanoparticulate systems can enter live cells and, if ingested, could exert alterations in gastrointestinal tract cells. Our work aims to investigate the response of HT-29 cells to cellulose nanoparticles from coffee pods. In particular, the subcellular effects between coffee-embedded nanocellulose (CENC) and cellulose nanoparticles (NC) were compared. Finally, we analysed the pathologic condition (Cytolethal Distending Toxin (CDT) from Campylobacter jejuni) on the same cells conditioned by NC and CENC. We evidenced that, for the cellular functional features analysed, NC and CENC pre-treatments do not worsen cell response to the C. jejuni CDT, also pointing out an improvement of the autophagic flux, particularly for CENC preconditioning.