The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

Magnesium hydroxide/melamine phosphate borate (nano MH/MPB), a novel nano-composition intumescent flame retardant, was synthesized with the in-situ reaction method from MgCl₂·6H₂O sodium hydroxide (NaOH) and melamine phosphate borate (MPB) in the absence of H₂O. The structure of the product was confirmed by EDAX IR and XRD. The effects of reaction temperature and time on the dimension of magnesium hydroxide were observed. The effects of mass ratio of magnesium hydroxide to MPB on the flame retardancy of nano-MH/MPB/EP were examined with the limiting oxygen test. The results show that the optimal condition of synthesis of MH/MPB is m_MH/m_MPB = 0.25, reacting under 75 ℃ for 30 minutes. Finally, the mechanism for flame retardancy of nano-MH/MPB/EP was pilot studied by means of IR of char layer and TG of MH/MPB.

This study employs a transfer matrix, dynamic degree, stability index, and the PLUS model to analyze the spatiotemporal changes in forest land and their driving factors in Yibin City from 2000 to 2022. The results reveal the following: (1) The land use in Yibin City is predominantly characterized by cultivated land and forest land (accounting for over 95% of the total area). The area of cultivated land initially increased and then decreased, while forest land continued to decline and construction land expanded significantly. The rate of forest land loss has slowed (with the dynamic degree decreasing from −0.62% to −0.04%), and ecosystem stability has improved (the F-value increased from 2.27 to 2.9). The conversion of cultivated land to forest land is the primary driver of forest recovery, whereas the conversion of forest land to cultivated land is the main cause of reduction; (2) cultivated land is concentrated in the central and northeastern regions, while forest land is distributed in the western and southern mountainous areas. Construction land is predominantly located in urban areas and along transportation routes. Areas of forest land reduction are mainly found in the central and southern regions with rapid economic development, while areas of forest land increase are concentrated in high-altitude zones or key ecological protection areas. Stable forest land is distributed in the western and southern ecological conservation zones; (3) changes in forest land are primarily influenced by annual precipitation, elevation, and distance to rivers. Road accessibility and GDP have significant impacts, while slope, annual average temperature, and population density exert moderate influences. Distance to railways, aspect, and soil type have relatively minor effects. The findings of this study provide a scientific basis for the sustainable management of forest resources and ecological conservation in Yibin City.

This study employs logistic regression to investigate determinants influencing active living among elderly individuals, with “Active Living” (1 = Active, 0 = Inactive) as the dependent variable. Analysing data from 500 participants, findings reveal significant associations between active living and variables such as chronic conditions (OR = 0.29, p < 0.001), mental well-being (OR = 1.57, p < 0.001), social support (OR = 5.75, p < 0.001), access to parks/recreational facilities (OR = 2.59, p < 0.001), income levels (OR = 1.82, p = 0.003), cultural attitudes (OR = 2.72, p < 0.001), and self-efficacy (OR = 2.01, p < 0.001). These findings highlight the complex interplay of factors influencing active living among elderly populations. Recommendations include implementing targeted interventions to manage chronic conditions, enhance mental well-being, strengthen social networks, improve access to recreational spaces, provide economic support for fitness activities, promote positive cultural attitudes towards aging, and empower older adults through self-efficacy programs. Such interventions are crucial for promoting healthier aging and fostering sustained engagement in physical activity among older adults.

Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.

It increased the demands on ground-water supplies that prolonged drought and improper maintenance of water resources. So it is necessary to evaluate ground-water resources in the hard rock terrain. In recent years, Remote-Sensing methods have been increasingly recognized as a means of obtaining crucial geoscientific data for both regional and site-specific investigations. This work aims to develop and apply integrated methods combining the information obtained by geo-hydrological field mapping and those obtained by analyzing multi-source remotely sensed data in a GIS environment for better understanding the Groundwater condition in hard rock terrain. In this study, digitally enhanced Landsat ETM+ data was used to extract information on geology, geomorphology. The Hill-Shading techniques are applied to SRTM DEM data to enhance terrain perspective views, and extract Geomorphological features and morphologically defined structures through the means of lineament analysis. A combination of Spectral information from Landsat ETM+ data plus spatial information from SRTM-DEM data is used to address the groundwater potential of alluvium, colluvium, and fractured crystalline rocks in the study area. The spatial distribution of groundwater potential zones shows regional patterns related to lithologies, lineaments, drainage systems, and landforms. High-yielding wells and springs are often related to large lineaments and corresponding structural features such as dykes. The results show that the combination of remote sensing, GIS, traditional fieldwork, and models provide a powerful tool for water resources assessment and management, and groundwater exploration planning.