Space is a product of society. Driven by industrialization, urbanization, informatization and government policies, China’s rural space is undergoing drastic reconstruction. As one of the core contents of international rural geography research, rural space research are multi-disciplinary, multi perspective, multi-dimensional and multi-method, forming a rich research field. In order to comprehensively grasp the progress of rural space research abroad, this study reviewed international rural space research literature in recent 40 years. The study found that foreign scholars described the connotation of rural space from the aspects of material, imagination and practice, emphasize the importance of daily life practice. It introduced living space to construct a more systematic research framework of rural space by establishing a “three-fold model of rural space”. With regard to the theoretical perspective, international research on rural space has experienced three stages: functionalism, political economics and social constructivism. In the evolution of time, it has realized the transformation from productivism to post-productivism; in the spatial dimension, it realizes the multiple superposition of settlement space, economic space, social space and cultural space. As a whole, international research on rural space has realized the transformation from material level to social representation, from objective space to subjective space, and from static one-dimensional space to dynamic multi-dimensional space, which enlightens us on the importance of interdisciplinary research and “social cultural” research on rural space. The construction of rural space in China needs to pay attention to the subject status of farmers and multifunction of rural space, respect the role of locality and difference of various places, and recover the function of production of meaning of rural space.

As China’s urbanisation continues, the building area is expanding, of which the occupancy of rural residential buildings is also very large. However, most rural buildings have poor thermal performance. This paper analyses the energy-saving potential of green facades for rural buildings in China by simulating typical buildings with different types of facades in rural China. The simulation results show that indirect green façades can achieve good energy savings. Buildings with four types of facades: red brick, rubble, hollow brick, and concrete achieve energy savings of 18.39%, 17.85%, 14.47%, and 11.52%, respectively, after retrofitting with green facades.

As one of the key initiatives promoted by the Chinese government, precision poverty alleviation aims to lift information-blocked areas out of poverty and ensure their sustainable economic development. Yunnan Province, characterized by its combination of old, young, border, and poor areas, is the province with the most diverse types of poverty, the widest poverty coverage, and the deepest poverty levels in the country. Yunnan has carried out anti-poverty work in tandem with the national efforts for 42 years in a planned and organized manner, ultimately achieving the goal of zero absolute poverty. In this process, digital rural development has played a very important role. Based on the current experience of digital construction in developed regions, completing regional digitalization requires meeting the needs of information resources, information environment, and information supply and demand. Through keyword search, text analysis, and field visits, we summarized the factors considered by local governments in policy formulation. We also attempted to map out the path for rural governments to build digital villages. With the ultimate goal of bridging the urban-rural gap, the study of digital rural development in Yunnan will provide an effective case.

The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

The study’s goal is to evaluate how microfinance initiatives affect women’s empowerment in Bangladesh. For this study, we analyzed data on a variety of women’s empowerment-related issues, including both beneficial and detrimental elements that stand in the way of women’s empowerment. Therefore, in order to accomplish the specified goal, we choose a suitable and intentional methodology. We employ diverse data gathering approaches to examine the gathered data and achieve the primary goal of the research project. It presents the positive effects of microfinance on women, such as (1) the enhancement of women’s authority in financial affairs; and (2) the augmentation of their ability to make decisions in household; and (3) community matters following their participation in the microfinance program. This also provides an analysis of the data pertaining to the adverse effects of microfinance on women. It examines how women encounter various challenges and engage in unethical behaviors after obtaining a loan, leading to heightened levels of stress following their participation in the microfinance program. This study looks into the advantages and disadvantages of Grameen Bank’s microcredit program for women. A questionnaire gathered primary data for this study from women participating in the microfinance program in Gopalgonj. To collect information and comprehend respondent behavior, I used case study, analytical and descriptive study design. Regression analysis, correlation, and percentage are used to examine the data. The findings indicate that women’s decision-making skills have improved due to their financial stability, but they have also experienced increased life challenges and high levels of stress.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.