Bagasse fiber from sugarcane waste is used with epoxy resin to make natural composites. The raw fibers are treated chemically to improve compatibility and adherence with the epoxy polymer. It’s anticipated that epoxy resin matrix composites reinforced with bagasse particles would work as a trustworthy replacement for conventional materials utilized in the building and automobile sectors. The amount and distribution of reinforcing particles inside the matrix are two factors that impact the composite’s strength. Furthermore, the precise proportion of reinforcing elements—roughly 20–30 weight percent—into the matrix plays a critical role in providing a noticeable boost in improving the properties of the composites. This research investigates the impact of reinforcing alkali-treated bagasse and untreated bagasse powder into an epoxy matrix on aspects of mechanical and morphological characteristics. The hand layup technique is used to create alkali-treated bagasse and untreated bagasse powder-reinforced epoxy composites. Composites are designed with six levels of reinforcement weight percentages (5%, 10%, 15%, 20%, 25%, and 30%). Microstructural analysis was performed using SEM and optical microscopes to assess the cohesion and dispersion of the reinforcing particles throughout the hybrid composites’ matrix phase. With reinforcement loading up to 20 wt%, the tensile strength, impact strength, and toughness of epoxy-alkali-treated bagasse and untreated bagasse powder-reinforced composites increased. In contrast, treated bagasse epoxy composites were superior to untreated epoxy composites in terms of efficacy. The results indicate that 20 wt% alkali bagasse powder provides better mechanical properties than other combinations.

Rapid global warming and continuous climate change threaten the construction industry and human existence, especially in developing countries. Many developed countries are engaging their professional stakeholders on innovation and technology to mitigate climate change on humanity. Studies concerning inclusive efforts by developing countries’ stakeholders, including Nigeria, are scarce. Thus, this study investigates the construction industry’s practitioners’ preparedness to mitigate climate change through pre- and post-planning. Also, the study appraises climate change’s impact on construction activities and proffered measures to mitigate them. The research employed face-to-face data collection via a qualitative approach. The researchers engaged 33 knowledgeable participants. The study covered Abuja, Benin City, Owerri, and Lagos and achieved saturation at the 30th participant. The research employed a thematic approach to analyse the collected data. Findings reveal that Nigerian construction practitioners cannot cope with climate change impacts because of lax planning and inadequate technology to mitigate the issues. Also, the government’s attitude towards climate change has not helped matters. Also, the study suggested measures to mitigate the impact of climate change on construction activities in Nigeria. Therefore, as part of the research contributions, all-inclusive and integrated regulatory policies and programmes should be tailored toward mitigating climate change. This includes integrated stakeholder sensitisation, investment in infrastructure that supports anti-climate change, prioritising practices in the industry to achieve sustainable project transformation, and integration of climate change interventions into pre- and post-contract administration.

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.

Strengthening the integration of elementary school mental health education and moral education is of great significance in comprehensively cultivating students' ideological and moral qualities as well as values. In order to fully implement quality education, schools need to carry out diversified teaching in conjunction with family forces to further optimize the integration effect of elementary school mental health education and moral education, cultivate high-quality talents for the country and society, and contribute to the construction of socialism with Chinese characteristics in the new era. This paper discusses the integration strategy of elementary school mental health education and moral education.

Three-dimensional (3D) bioprinting is a promising technological approach for various applications in the biomedical field. Natural polymers, which comprise the majority of 3D printable “bioinks”, have played a crucial role in various 3D bioprinting technologies during the layered 3D manufacturing processes in the last decade. However, the polymers must be customized for printing and effector function needs in cancer, dental care, oral medicine and biosensors, cardiovascular disease, and muscle restoration. This review provides an overview of 3D bio-printed natural polymers—commonly employed in various medical fields—and their recent development.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.