The article's proposed engineering uses are based on theories presented in the reviewed research articles and on findings from online investigations into companies that claim to use nanoengineering in their wares. Several pre-existing online consumer inventories and nanotechnology news were examined as part of the internet inquiry. The data about the nanoparticles (NP), or nanostructure, used in commercially available products comes from the remarks made by the manufacturer. Nanoengineered coating agents and textile additives are examples of commercial items developed for industrial clients that fall under the aforementioned uses.

The Government of Qatar is investing considerable resources in the development of integrated transport infrastructure as a solution to traffic congestion and environmental degradation. Autonomous vehicles are expected to be one of the methodologies for enhancing the quality of the built environment and fostering a more sustainable and environmentally conscious urban milieu. While autonomous cars have the potential to address urban difficulties and be utilized for personal, group, and public transit purposes, their implementation in the specific context of Doha has not been thoroughly analyzed. This research explores the potential impacts that autonomous vehicles are expected to have on travel demands, parking needs, and urban planning. It discusses the benefits and challenges associated with autonomous vehicles and predicts their likely implementation and development based on the different precedents. In addition, it explores how it will affect planning decisions such as drop-off and pick-up areas, parking and public transit. The research utilizes a qualitative approach through literature content analysis, field observations, and mobility analysis. Several case studies are analyzed to explore how autonomous vehicles can operate within a limited zone. The study uncovers the issue of ownership and mode of operation as essential factors that can affect the impact of autonomous vehicles (AVs). In addition, implementing AVs may create complex environmental concerns when greener and more sustainable transportation models are not integrated. It is recommended that Doha adopt integrated planning and implementation of AV technologies to ensure that AVs align harmoniously with the environmental stewardship requirement. The research study also presents urban design frameworks for how existing urban spaces can accommodate autonomous vehicles.

2050 building stock might be buildings that already exist today. A large percentage of these buildings fail today’s energy performance standards. Highly inefficient buildings delay progress toward a zero-carbon-building goal (SDGs 7 and 13) and can lead to investments in renewable energy infrastructure. The study aims to investigate how bioclimatic design strategies enhance energy efficiency in selected orthopaedic hospitals in Nigeria. The study objective includes Identifying the bioclimatic design strategies that improve energy efficiency in orthopaedic hospitals, assessing the energy efficiency requirements in an orthopaedic hospital in Nigeria and analysing the effects of bioclimatic design strategies in enhancing energy efficiency in an orthopaedic hospital in Nigeria. The study engaged a mixed (qualitative and quantitative) research method. The investigators used case study research as a research design and a deductive approach as the research paradigm. The research employed a questionnaire survey for quantitative data while the in-depth Interview (IDI) guide and observation schedule for qualitative data. The findings present a relationship between bioclimatic design strategies and energy conservation practices in an orthopaedic hospital building. Therefore, implementing bioclimatic design strategies might enhance energy efficiency in hospital buildings. The result of the study revealed that bioclimatic hospital designs may cost the same amount to build but can save a great deal on energy costs. Despite the challenges, healthcare designers and owners are finding new ways to integrate bioclimatic design strategies into new healthcare construction to accelerate patient and planet healing.

The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

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.

The increasing demand for electricity and the need to reduce carbon emissions have made optimizing energy usage and promoting sustainability critical in the modern economy. This research paper explores the design and implementation of an Intelligent-Electricity Consumption and Billing Information System (IEBCIS), focusing on its role in addressing electricity sustainability challenges. Using the Design Science Research (DSR) methodology, the system's architecture collects, analyses, and visualizes electricity usage data, providing users with valuable insights into their consumption patterns. The research involved developing and validating the IEBCIS prototype, with results demonstrating enhanced real-time monitoring, load shedding schedules, and billing information. These results were validated through user testing and feedback, contributing to the scientific knowledge of intelligent energy management systems. The contributions of this research include the development of a framework for intelligent energy management and the integration of data-driven insights to optimize electricity consumption, reduce costs, and promote sustainable energy use. This research was conducted over a time scope of two years (24 months) and entails design, development, pilot test implementation and validation phases.