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This study takes Aba Tibetan and Qiang Autonomous Prefecture in China as the research object, and establishes an ecological sensitivity evaluation index system based on the current ecological environment of the state using land use data, combined with field surveys and socio-economic and other data. And the ecological sensitivity evaluation was carried out based on Geographic Information System (GIS) and Remote Sensing (RS) using a hierarchical analysis method. The results of the study showed that the overall ecological sensitivity of Aba Tibetan and Qiang Autonomous Prefecture showed spatial variability with low in the northwest and high in the southeast; among them, the extremely sensitive area accounted for only 3.53% of the total area, the moderately sensitive area accounted for 30.10% of the total area, and the slightly sensitive area and insensitive area accounted for 47.82% of the total area. The study provides a theoretical basis for the ecological economy and sustainable development of the state.

Over the past two decades, due to the combined effects of natural and human factors, the ecological environment and resources of the Qinghai–Tibet Plateau (QTP) have faced serious threats, profoundly impacting its ecosystem and the lives of its residents. Therefore, the establishment of the ecological security pattern (ESP) is crucial to cope with climate change, maintain ecosystem function, and sustainable development. Based on the Pressure–State–Response (PSR) model, this study constructed an evaluation index system for the ecological security (ES) of the QTP, evaluated the ES of the QTP during 2000–2020, and predicted the ES of the QTP during 2025–2035 based on the deep learning model. Combined with the residents' perception of ES, the ES of the QTP was evaluated comprehensively. The results showed that: (1) From 2000 to 2020, the ES value of the QTP continued to rise, the number of dangerous and sensitive counties decreased, and the number of other counties increased. The overall spatial distribution features higher values in the southeast and lower values in the northwest and central regions. (2) From 2000 to 2020, both hot spots and cold spots on the QTP decreased, with the hot spots mainly concentrated in the southeast of the QTP, represented by Yunnan Province, and the cold spots shifting from west to east, mainly concentrated in the central QTP, represented by Qinghai Province. (3) The Long Short-Term Memory (LSTM) model demonstrates high prediction accuracy. Based on the prediction of LSTM, the ES value of the QTP will continue to rise from 2025 to 2035, and the number of safe counties will reach the highest level in history. The spatial distribution is still higher in the southeast and lower in the northwest and central regions. (4) By analyzing residents' perception of 25 potential factors that may affect the ES of the QTP, the results show that residents generally believe that these factors have an important impact on ES, and their evaluation is between "important" and "very important". In addition, there is a significant correlation between these factors and the predicted values of ES. The results of the study will help to improve our understanding of the overall ecological environment of the QTP, provide accurate positioning and reasonable help for the government to formulate relevant protection strategies, and lay a methodological and practical foundation for the sustainable development of the QTP. [ABSTRACT FROM AUTHOR]

Sustainability has become an indispensable core consideration when nations formulate their development policies. This study delves into the dynamic correlations between ecosystem services (ESs) and localized Sustainable Development Goals (SDGs) in a typical hilly region in southern China. Various ESs were computed using the InVEST model, while spatial econometric models were employed to assess ES responses to SDG targets at the county, sectoral, and overall spatial levels. The findings revealed the following. (1) From 2005 to 2020, there were differences in the development rates of various SDG targets in Ganzhou. Except for SDG 15, which declined, the development of the other targets showed an overall increasing trend. The development of the various SDG targets was relatively balanced, but SDG 9 and SDG 7 had the highest growth rates, ranging from 9.4% to 10.7% and 9.4% to 10.3%, respectively. The comprehensive SDG assessment index exhibited significant spatiotemporal variation, with a general trend of higher values in the north and lower values in the south. (2) The local ES showed a delayed response to SDG 1 and SDG 2, but there was a significant positive response to SDG 3, SDG 4, SDG 6, SDG 8, and SDG 9. However, responses to SDG 7, SDG 11, SDG 13, and SDG 15 showed regional differences. This study not only provides valuable insights for sustainable development in Ganzhou and other regions of China but also offers Chinese perspectives and experiences that may inform global efforts towards SDG implementation. This study fills the gap in existing research by constructing a localized SDG indicator system and quantifying each SDG indicator, further exploring the response of the ES to each SDG in the region. Looking ahead, we anticipate further research to deepen the understanding of the relationship between ESs and SDG targets on a broader geographical scale and over longer timeframes, aiming to provide a more robust scientific foundation for building a harmonious coexistence between humans and nature in the future. [ABSTRACT FROM AUTHOR]

The interlayer proximity effect induced by spin-orbital coupling between the monolayers of borophosphene (BP) and MoSe2 in the stacked heterostructure is studied by first principles calculations. The proximity effect originates from the hybridization of the d orbital of the Mo atoms and the p orbital of the B atoms. This hybridization greatly improved the strength of spin-orbital coupling of the BP layer, bringing the spin-dependent valley and spin splitting about 13 meV at the K point of the conduction band of BP layer. Moreover, the existence of BP layer destroyed the mirror symmetry of MoSe2 layer, causing the Rashba splitting at the Γ point of the valence band. In addition, the calculation results indicate that both the Zeeman splitting and Rashba splitting can be modulated by the transverse electric field and the interlayer distance. [ABSTRACT FROM AUTHOR]

The interlayer proximity effect induced by spin-orbital coupling between the monolayers of borophosphene (BP) and MoSe2 in the stacked heterostructure is studied by first principles calculations. The proximity effect originates from the hybridization of the d orbital of the Mo atoms and the p orbital of the B atoms. This hybridization greatly improved the strength of spin-orbital coupling of the BP layer, bringing the spin-dependent valley and spin splitting about 13 meV at the K point of the conduction band of BP layer. Moreover, the existence of BP layer destroyed the mirror symmetry of MoSe2 layer, causing the Rashba splitting at the Γ point of the valence band. In addition, the calculation results indicate that both the Zeeman splitting and Rashba splitting can be modulated by the transverse electric field and the interlayer distance. [ABSTRACT FROM AUTHOR]