Search

Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively understand public preferences. This paper proposes a method to evaluate public landscape preference from the perspective of seeing and thinking, takes the examples of seven parks around the Dianchi Lake in Kunming, China, and analyses the social media data by using natural language processing technology and image semantic segmentation technology. The conclusions are as follows: (1) The public exhibits significantly high positive sentiments towards various UBGSs, with over 93% of comments expressed positive sentiments. (2) Differences exist in the frequency and perception of landscape features between image and text modalities. Landscape elements related to stability are perceived more in images than in text, while dynamic and experiential elements are perceived more in text than in images. (3) In both modalities, the distinctive landscape features of parks are more frequently perceived and preferred by the public. In the end, the intrinsic links between landscape elements and public sentiment and preferences are discussed, and suggestions for design and management improvements are made to consolidate their health benefits to the public. [ABSTRACT FROM AUTHOR]

Traffic congestion prediction has become an indispensable component of an intelligent transport system. However, one limitation of the existing methods is that they treat the effects of spatio-temporal correlations on traffic prediction as invariable during modeling spatio-temporal features, which results in inadequate modeling. In this paper, we propose an attention-based spatio-temporal 3D residual neural network, named AST3DRNet, to directly forecast the congestion levels of road networks in a city. AST3DRNet combines a 3D residual network and a self-attention mechanism together to efficiently model the spatial and temporal information of traffic congestion data. Specifically, by stacking 3D residual units and 3D convolution, we proposed a 3D convolution module that can simultaneously capture various spatio-temporal correlations. Furthermore, a novel spatio-temporal attention module is proposed to explicitly model the different contributions of spatio-temporal correlations in both spatial and temporal dimensions through the self-attention mechanism. Extensive experiments are conducted on a real-world traffic congestion dataset in Kunming, and the results demonstrate that AST3DRNet outperforms the baselines in short-term (5/10/15 min) traffic congestion predictions with an average accuracy improvement of 59.05%, 64.69%, and 48.22%, respectively. [ABSTRACT FROM AUTHOR]

Due to the complex interaction of urban and mountainous floods, assessing flood susceptibility in mountainous urban areas presents a challenging task in environmental research and risk analysis. Data-driven machine learning methods can evaluate flood susceptibility in mountainous urban areas lacking essential hydrological data, utilizing remote sensing data and limited historical inundation records. In this study, two ensemble learning algorithms, Random Forest (RF) and XGBoost, were adopted to assess the flood susceptibility of Kunming, a typical mountainous urban area prone to severe flood disasters. A flood inventory was created using flood observations from 2018 to 2022. The spatial database included 10 explanatory factors, encompassing climatic, geomorphic, and anthropogenic factors. Artificial Neural Network (ANN) and Support Vector Machine (SVM) were selected for model comparison. To minimize the influence of expert opinions on model training, this study employed a strategy of uniformly random sampling in historically non-flooded areas for negative sample selection. The results demonstrated that (1) ensemble learning algorithms offer higher accuracy than other machine learning methods, with RF achieving the highest accuracy, evidenced by an area under the curve (AUC) of 0.87, followed by XGBoost at 0.84, surpassing both ANN (0.83) and SVM (0.82); (2) the interpretability of ensemble learning highlighted the differences in the potential distribution of the training data's positive and negative samples. Feature importance in ensemble learning can be utilized to minimize human bias in the collection of flooded-site samples, more targeted flood susceptibility maps of the study area's road network were obtained; and (3) ensemble learning algorithms exhibited greater stability and robustness in datasets with varied negative samples, as evidenced by their performance in F1-Score, Kappa, and AUC metrics. This paper further substantiates the superiority of ensemble learning in flood susceptibility assessment tasks from the perspectives of accuracy, interpretability, and robustness, enhances the understanding of the impact of negative samples on such assessments, and optimizes the specific process for urban flood susceptibility assessment using data-driven methods. [ABSTRACT FROM AUTHOR]

Kunming is the capital city of Yunnan Province and a bridgehead city facing South Asia and Southeast Asia. With the rapid development of Kunming's economy and society, the urbanization rate continues to increase, and the quality of the ecological environment in this area is also changing rapidly. How to quickly and accurately obtain the temporal and spatial pattern evolution of Kunming's ecological environment quality and explore the driving factors is of great significance to the realization of ecological environmental protection and sustainable development of Kunming. In this paper, the Google Earth Engine (GEE) platform is used to use the long-term Landsat remote sensing image data to mask the water body, extract greenness, dryness, humidity and heat, and construct the remote sensing ecological index RSEI through PCA. Using spatial analysis methods such as cold and hot spot analysis and center of gravity migration to explore the evolution of the spatio-temporal pattern of ecological environment quality in Kunming from 2000 to 2019, and use single-factor analysis and interactive detection in geographic detectors to analyze its internal driving forces. The results show, (1) From 1995 to 2019, the quality of the ecological environment in Kunming showed a trend of first increasing-then decreasing-then increasing. The overall ecological environment quality was in a general state in the past 25 years, but the ecological environment continued to improve. (2) In the past 25 years, the ecological environment quality grade area of Kunming City is, medium ecological environment area > good ecological environment area > poor ecological environment area > poor ecological environment area > excellent ecological environment area. From the perspective of spatial distribution, the ecological environment quality presents The spatial distribution pattern of high in the southwest and poor in the northeast. (3) From 1995 to 2019, the centers of the standard deviation ellipse of Kunming's ecological environment were relatively close to each other, and the major axes all showed a south-north direction. (4) In Kunming, the ecological environment quality is poor in areas with concentrated rocky desertification, concentrated water and soil erosion, concentrated population and rapid urban expansion, while areas with better ecological environment mostly have higher vegetation coverage. Population and slope are the human activity factors and natural factors that dominate the spatial distribution of ecological environment in Kunming, respectively. Slope, population and GDP, together with other factors, have a significant impact on the quality of ecological environment in Kunming. (5) In the future, Kunming City should rigorously prioritize the protection of key ecological areas, enhance ecological conservation and restoration efforts, optimize land use and development, continuously enhance the quality of the ecological environment, and achieve synchronous and sustainable development of the ecological environment and the economy. [ABSTRACT FROM AUTHOR]

This paper examines the morphologies of Villages-in-the-City (ViCs) in Kunming in China and Hanoi in Vietnam, that are undergoing rapid urbanisation and urban transformation. In China, the term Chengzhongcun refers to development of rural settlements that have been included in the urban districts arising from city expansion. Meanwhile, in Vietnam, the phrase Làng trong phố is used to describe settlements in urban areas that used to be rural villages. Both types of settlements share many common characteristics linked to rural background, and to social and economic policies in these two countries. The findings illustrate that spatial transformations are generated by fundamental economic and social changes, and that the influences of land policies and roles played by local government in each country have significant impacts on the formation of the ViCs. Although the planning processes are managed though top-down systems, the diverse practices and small scale and cost-effective tactics contribute to the transitions of the ViCs. The morphological differences between ViCs development in two countries are due to differences in management modes and land use rights. The outcome of this paper contributes to the deeper understanding about similarities and differences of ViCs in the Global South. • This paper examines and compare the morphologies of Villages-in-the-City in Kunming in China and Hanoi in Vietnam. • The diverse practices and small scale tactics contribute to the transition from rural to urban live styles in both places. • The differences between ViCs developments are due to different modes of management and land use rights. [ABSTRACT FROM AUTHOR]

Background: Jianqu has been used to alleviate symptoms in patients with functional dyspepsia, but its specific anti-functional dyspepsia effect is still unclear. Therefore, our study aimed to investigate the impact of Jianqu on functional dyspepsia in mice. Methods: The phytochemical profile of Jianqu was analyzed by UPLC-Q-TOF-MS. Subsequently, Kunming mice were fed a high-calorie or high-protein diet (HCHP) for 7 days, and then orally treated with vehicle or Jianqu (1.62 g/kg body weight (b. w.) and 3.25 g/kg b. w.) for 10 days. A carbon powder solution was used to detect the gastric emptying and intestinal transit rate. The pathological changes in stomach and duodenum were evaluated by hematoxylin-eosin staining. The occludin, claudin-1, ZO-1 and CD45 expression was measured by immunocytochemical staining. Importantly, the serum gastrointestinal hormones were detected by ELISA. In addition, the gut microbiota composition was determined using 16S rRNA gene sequencing. The cecal short chain fatty acids were assessed by gas chromatography. Results: In general, 17 phytochemical compounds were identified from Jianqu, which significantly improved the gastric emptying rate and intestinal transit rate (p < 0.01), increased the body weight and food intake (p < 0.0001) in HCHP mice as well. Though HCHP did not cause significant pathological lesions in the gastrointestinal tract, increased the expression of CD45 in the duodenum (p < 0.05) was observed. Notably, Jianqu attenuated this abnormal expression of CD45 (p < 0.05). The levels of serum gastrointestinal hormones were significantly normalized by Jianqu intervention (p < 0.05). Moreover, Jianqu increased the relative abundance of Roseburia as well as short chain fatty acids levels in cecum (p < 0.05). Conclusion: The present results showed that Jianqu alleviated dyspeptic symptoms in HCHP mice possibly through reducing the duodenal leukocyte infiltration, and regulating the expression of gastrointestinal hormones. These effects may be partly related to the increasing cecal short chain fatty acids levels probably via gut microbial modulation. [ABSTRACT FROM AUTHOR]

Revealing the relationship between land use changes and soil erosion provides a reference for formulating future land use strategies. This study simulated historical and future soil erosion changes based on the RULSE and GeoSOS-FLUS models and used a random forest model to explain the relative importance of natural and anthropogenic factors on soil erosion. The main conclusions are as follows: (1) From 1990 to 2020, significant changes in land use occurred in Kunming, with a continuous reduction in woodland, grassland, and cropland, being converted into construction land, which grew by 195.18% compared with 1990. (2) During this period, the soil erosion modulus decreased from 133.85 t/(km²·a) in 1990 to 130.32 t/(km²·a) in 2020, with a reduction in soil loss by 74,485.46 t/a, mainly due to the conversion of cropland to construction and ecological lands (woodland, grassland). (3) The expansion of construction land will continue, and it is expected that by 2050, the soil erosion modulus will decrease by 3.77 t/(km²·a), 4.27 t/(km²·a), and 3.27 t/(km²·a) under natural development, rapid development, and ecological protection scenarios, respectively. However, under the cropland protection scenario, the soil erosion modulus increased by 0.26 t/(km²·a) compared with 2020. (4) The spatial pattern of soil erosion is influenced by both natural and anthropogenic factors, and as human activities intensify in the future, the influence of anthropogenic factors will further increase. Traditionally, the expansion of construction land is thought to increase soil loss. Our study may offer a new perspective and provide a reference for future land use planning and soil loss management in Kunming. [ABSTRACT FROM AUTHOR]

Background: Polygonatum sibiricum (PS) is a traditional Chinese medicine (TCM) first recorded in Mingyi Bielu. The book documents that PS can nourish five internal organs, be taken for a long time, relax the body and prolong lifespan. Presently, PS is widely used in TCM to prevent premature graying of hair. Based on TCM theory and clinical trials, the wine steaming processed product from PS provides a better effect. However, no published study has elucidated the antiaging mechanism. Purpose: The study aim was to investigate the anti-aging mechanism of PS and its wine steaming processed product in mice, specifically focusing on the effect of D-galactose (D-gal) surrounding the intestinal flora and the Kelch-like ECH-associated protein 1-nuclear factor erythroid 2-related factor 2-antioxidant response elements (Keap1/Nrf2/ARE) pathway. Methods: The chemical components in Raw PS (RPS) and Wine-steamed PS (WPS) were identified by ultra-performance liquid chromatography--hybrid quadrupole-Orbitrap high-resolution mass spectrometry (UPLC-Q-Orbitrap HRMS). An aging model using Kunming mice was established through intraperitoneally injected D-gal. Concentrations of RPS and WPS at 5, 10, or 15 g/kg/day levels were administered intragastrically, respectively. The body weight, liver and spleen indexes, superoxide dismutase (SOD), glutathione peroxidase (GSH-PX), and malondialdehyde (MDA) activities in serum and brain tissue were recorded. Hematoxylin and eosin (HE) stained brain tissue was histopathologically examined. The expressions of Keap1, Nrf2 and heme oxygenase 1 (HO-1) in the brain tissue at the mRNA and protein levels were respectively detected by reverse transcription-polymerase chain reaction (RTPCR) and western blot (WB). Moreover, an Illumina Hiseq platform was used for 16S ribosomal RNA (16S rRNA) high-throughput sequencing to evaluate the proportions of intestinal flora in aging mice. Results: The proportions of saccharides, flavonoids, and triterpene acids were different between RPS and WPS. In the aging model mice, WPS outperformed RPS in improving body weight and mental state by increasing the spleen index, SOD and GSH-PX activities, decreasing the liver index and MDA activities, and restoring the histopathological morphology in D-gal-induced aging mice. At the mRNA levels, RPS and WPS significantly reduced the expression of Keap1 and increased the expressions of Nrf2 and HO-1. The trend in protein expressions was similar to that of the mRNA results, and WPS had a stronger effect than RPS. Fecal microbiota analysis showed that RPS and WPS restored intestinal microbiota proportions to normal levels. Conclusion: The results demonstrated that PS and its WPS had a positive effect in relieving oxidative stress in aging mice. WPS outperformed RPS, which might be related to the activation of the Keap1/Nrf2/ARE pathway and regulation of intestinal flora. [ABSTRACT FROM AUTHOR]

In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming's main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type's rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type's rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types. [ABSTRACT FROM AUTHOR]

Climate change threatens human survival and development. Cities, as the main gathering places for human production and life, serve as the focal points for the implementation of the policies related to energy efficiency, energy transition, and environmental protection. This study constructs an index system for the evaluation of carbon-neutral cities from the perspectives of carbon sources and carbon sinks. The system includes thirteen indicators under six dimensions. It combines objective and subjective data (i.e., statistical data and expert evaluations) by integrating two approaches: the fuzzy analytic hierarchy process (fuzzy AHP) and vise kriterijumska optimizacija i kompromisno resenje with hesitant fuzzy sets (HFS-VIKOR). We verify the efficacy of the proposed approach through a case study of thirteen low-carbon pilot cities in China. The results indicate that among these cities, Shenzhen performs the best, followed by Guangzhou and Hangzhou, while Kunming, Baoding, and Tianjin show poor performance in terms of carbon neutrality. Kunming and Baoding exhibit shortcomings mainly in carbon sources, while Tianjin faces deficiencies in both carbon sources and carbon sinks. Sensitivity analysis and comparative analysis show the availability and effectiveness of the proposed method. The proposed radar chart further highlights the improvement directions for each city to achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

As a city undergoes large-scale construction and expansion, there is an urgent need to monitor the stability of the ground and infrastructure. The time-series InSAR technique is an effective tool for measuring surface displacements. However, interpreting these displacements in a built environment, where observed displacements consist of mixed signals, poses a challenge. This study uses principal component analysis (PCA) and the k-means clustering method for exploring deformation series within an unsupervised learning context. The PCA method extracts the dominant components in deformation series, whereas the clustering method identifies similar deformation series. This method was tested on Kunming City (KMC) using C-band Sentinel-1, X-band TerraSAR-X, and L-band ALOS-2 PALSAR-2 data acquired between 2017 to 2022. The experiment demonstrated that the suggested unsupervised learning approach can group PS points with similar kinematic characteristics. Five types of deformation kinematic characteristics were discovered in the three SAR datasets: upward, slight upward, stability, slight downward, and downward. According to the results, less than 20% of points exhibit significant motion trends, whereas 50% show small velocity values but still demonstrate movement trends. The remaining 30% are relatively stable. Similar clustering results were obtained from the three datasets using unsupervised methods, highlighting the effectiveness of identifying spatial–temporal patterns over the study area. Moreover, It was found that clustering based on kinematic characteristics enhances the interpretation of InSAR deformation, particularly for points with small deformation velocities. Finally, the significance of PCA decomposition in interpreting InSAR deformation was discussed, as it can better represent series with noise, enabling their accurate identification. [ABSTRACT FROM AUTHOR]

To effectively combat environmental challenges, it is necessary to evaluate urban residential building carbon emissions and implement energy-efficient, emission-reducing strategies. The lack of a specialized carbon emission monitoring system complicates merging macro- and micro-level analyses to forecast urban residential emissions accurately. This study employs a system dynamics (SD) model to examine the influence of social, economic, energy, and environmental factors on carbon emissions in urban residences in Kunming, China. The SD model forecasts household carbon emissions from 2022 to 2030 and establishes three scenarios: a low-carbon scenario (LCS), a medium low-carbon scenario (MLCS), and a high low-carbon scenario (HLCS) to assess emission reduction potentials. It predicts emissions will climb to 4.108 million tons by 2030, significantly surpassing the 2014 baseline, with economic growth, urbanization, residential energy consumption, and housing investment as key drivers. To curb emissions, the study suggests enhancing low-carbon awareness, altering energy sources, promoting research and development investment, and expanding green areas. The scenarios indicate a 5.1% to 16.1% emission reduction by 2030 compared to the baseline. The study recommends an 8.3% to 11.4% reduction in MLCS as a practical short-term target for managing urban residential emissions, offering a valuable SD approach for optimizing carbon strategies and aiding low-carbon development. [ABSTRACT FROM AUTHOR]

Pectocaris species are intermediate- to large-sized Cambrian bivalved arthropods. Previous studies have documented Pectocaris exclusively from the Cambrian Series 2 Stage 3 Chengjiang biota in Yu'anshan Formation, Chiungchussu Stage in SW China. In this study, we report Pectocaris paraspatiosa sp. nov., and three other previously known Pectocaris from the Xiazhuang section in Kunming, which belongs to the Hongjingshao Formation and is a later phase within Cambrian Stage 3 than the Yu'anshan Formation. The new species can be distinguished from its congeners by the sparsely arranged endopodal endites and the morphologies of the abdomen, telson, and telson processes. We interpret P. paraspatiosa sp. nov. as a filter-feeder and a powerful swimmer adapted to shallow, agitated environments. Comparison among the Pectocaris species reinforces previous views that niche differentiation had been established among the congeneric species based on morphological differentiation. Our study shows the comprehensive occurrences of Pectocaris species outside the Chengjiang biota for the first time. With a review of the shared fossil taxa of Chengjiang and Xiaoshiba biotas, we identify a strong biological connection between the Yu'anshan and Hongjingshao Formations. [ABSTRACT FROM AUTHOR]

This study explored the effects of peer interactions on kindergarten children's construction of conservation and conflict resolution knowledge during storybook reading. Previous studies have identified that peer interactions can support the meaning-making processes of children in social relationships and problem-solving, but little is known about whether the interaction with mixedage or more competent peers is more important in supporting knowledge construction. Sixty-four younger children in K2 and older children in K3 with similar socioeconomic backgrounds were recruited from a Montessori kindergarten in Kunming, China. An experimental design was applied to explore age group and conserver dominance effects on conservation and conflict resolution. Children were assigned randomly to eight groups in three 30-to-40-min intervention sessions. Each session had a different theme for the children to learn about conservation and conflict resolution concepts and a handson activity to practice and discuss. ANOVAs were performed to test group effects, while multiple regression analyses were conducted to explore individual variations in age and pre-test scores in predicting post-test scores. Conservation knowledge was significantly better among children who differed in age groups in the post-test, but differences were not found in conflict resolution knowledge. Groups balanced with equal conservers and non-conservers improved the best, suggesting that peer social interactions can facilitate conservation and conflict resolution construction. These results provide new insights for early childhood educators to support peer interactions and children's development. Implications, limitations, and future research are discussed. [ABSTRACT FROM AUTHOR]

Introduction Themed "Better Sub-Regional and Urban Development from the Perspective of the Belt and Road Initiative," the 2023 Annual Conference of the International Urban Planning Branch of the Urban Planning Society of China (UPSC) was successfully held in Kunming from Jun. 23 to 25, 2023. The conference, organized by the International Urban Planning Branch and hosted by the School of Architecture and Planning, Yunnan University, coincided with the 10th anniversary of the Belt and Road Initiative. Thus it aimed to share new insights and practices related to sub-regional cooperation, sustainable development, global industrial restructuring, urban vitality, cross-border cultural exchanges, and more, both in China and internationally. Furthermore, the conference presented in-depth research and analysis on the strategic advantages of the Belt and Road Initiative and held dialogues and case studies on high-quality sub-regional and urban development worldwide. The goal was to provide innovative perspectives for China to implement high-quality cross-border collaboration under the framework of the Belt and Road Initiative. The keynote speeches given at the conference have been collected by China City Planning Review and meticulously proofread by the respective speaker. [ABSTRACT FROM AUTHOR]

Background: With the development of healthcare services, drug efficacy, and safety have become the focus of drug use, and processing alters drug toxicity and efficacy, exploring the effects of processing on Evodiae fructus (EF) can guide the clinical use of drugs. Methods: Fifty male Kunming mice were randomly divided into the control group (CCN), raw small-flowered EF group (CRSEF), raw medium-flowered EF group (CRMEF), processing small-flowered EF group (CPSEF), and processing medium-flowered EF group (CPMEF). The CRSEF, CRMEF, CPSEF, and CPMEF groups were gavaged with aqueous extracts of raw small-flowered EF dry paste (RSEF), medium-flowered EF dry paste (RMEF), processing small-flowered EF dry paste (PSEF) and processing medium-flowered EF dry paste (PMEF), respectively, for 21 days at 5 times the pharmacopeial dosage. Upon concluding the experiment, histopathological sections of liver and kidney tissues were examined. Additionally, levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), serum creatinine (SCr), and blood urea nitrogen (BUN) were determined. DNA from the intestinal contents of the mice was extracted, and 16S rRNA full-length high-throughput sequencing was performed. Results: After fed EF 21 days, mice exhibited a decreasing trend in body weight. Comparative analysis with the CCN group revealed an upward trend in SCr, BUN, AST, and ALT levels in both CRSEF and CRMEF groups. The CRMEF group displayed notably elevated BUN and AST levels, with an observed increasing trend in Scr and ALT. Kidney sections unveiled cellular edema and considerable inflammatory cell infiltrates, whereas significant liver damage was not evident. Compared with CRSEF, Bun levels were significantly lower while AST levels were significantly higher in the CPMEF group. Additionally, the intestinal microbiota diversity and the relative abundance of Psychrobacter decreased significantly, and the relative abundance of Staphylococcus, Jeotgalicoccus, and Salinicoccus increased significantly in the CPMEF group. AST, ALT, and SCr were positively correlated with Staphylococcus, Jeotgalicoccus, and Salinicoccus. Conclusion: In conclusion, PMEF significantly increased harmful bacteria (Staphylococcus, Jeotgalicoccus, and Salinicoccu) and decreased beneficial bacteria. SEF with 5 times the clinical dose showed nephrotoxicity and SEF nephrotoxicity decreased after processing, but EF hepatotoxicity was not significant, which may be due to insufficient dose concentration and time. [ABSTRACT FROM AUTHOR]

Biodiversity is crucial for ecosystem functioning, but it is rapidly declining due to human activities and climate change. Protecting biodiversity has become a key priority for global environmental conservation actions. Rare and endangered species have a great impact on the ecosystem, yet due to their limited survival capacity, they are more prone to extinction, thus exerting a significant impact on biodiversity. However, current research reveals a lack of information concerning the potential distribution and changes of these species. This study used the maximum entropy model to predict the present and future potential habitats of rare and endangered species in Yunnan Province. After superimposing model results, four richness regions are divided by the natural breakpoint method and analyzed. Existing protected areas are compared with hotspots, and the land-use composition of hotspots is also analyzed. The results revealed that, in both current and future scenarios, rare and endangered species in Yunnan Province are primarily found in the western mountainous region, the Xishuangbanna–Wenshan high temperature area, and the Kunming–Qujing dense vegetation cover area. These species are also expanding their distribution towards the western mountainous area. However, under the low carbon emission scenario (RCP2.6), these species will spread from the high abundance regions to the low altitude hotspots by 2070. In the high carbon emissions scenario (RCP8.5), there will be fewer high abundance areas in 2070 than in 2050. The transfer matrix analysis reveals regional richness variations over time. Furthermore, the analysis revealed significant conservation gaps and found that existing hotspot areas were heavily affected by human activities. To improve conservation efficiency, it is necessary to enhance the protection of existing hotspots in Yunnan Province. Climate change plays a significant role in species migration, with precipitation levels being a key factor. The necessary actions should be taken to address the insufficient protection, resolve conflicts between human activities and land use in critical areas, and formulate effective strategies for adapting to future climate changes. Yunnan Province, with its rich species resources, has the potential to become a global innovator in biodiversity conservation by implementing improved conservation strategies. [ABSTRACT FROM AUTHOR]

Cyclophosphamide (CTX) is a broad-spectrum alkylated antitumor drug. It is clinically used in the treatment of a variety of cancers, and renal toxicity is one of the adverse reactions after long-term or repeated use, which not only limits the therapeutic effect of CTX, but also increases the probability of kidney lesions. The total flavonoids of Epimedium stem and leaf (EBF) and Icariin (ICA) are the main medicinal components of Epimedium, and ICA is one of the main active substances in EBF. Modern pharmacological studies have shown that EBF has a variety of biological activities such as improving osteoporosis, promoting cell proliferation, antioxidant and anti-inflammatory properties, etc. However, few studies have been conducted on the nephrotoxicity caused by optimized CTX extraction, and protein-ligand binding has not been involved. This research, through the response surface optimization extraction of EBF, obtained the best extraction conditions: ethanol concentration was 60%, solid-liquid ratio of 25:1, ultrasonic time was about 25 min. Combined with mass spectrometry (MS) analysis, EBF contained ICA, ichopidin A, ichopidin B, ichopidin C, and other components. In this study, we adopted a computational chemistry method called molecular docking, and the results show that Icariin was well bound to the antioxidant target proteins KEAP1 and NRF2, and the anti-inflammatory target proteins COX-2 and NF-κB, with free binding energies of −9.8 kcal/mol, −11.0 kcal/mol, −10.0 kcal/mol, and −8.1 kcal/mol, respectively. To study the protective effect of EBF on the nephrotoxicity of CTX, 40 male Kunming mice (weight 18 ± 22) were injected with CTX (80 mg/kg) for 7 days to establish the nephrotoxicity model and were treated with EBF (50 mg/kg, 100 mg/kg) for 8 days by gavage. After CTX administration, MDA, BUN, Cre, and IL-6 levels in serum increased, MDA increased in kidney, GPT/ALT and IL-6 increased in liver, and IL-6 increased in spleen and was significant ((p < 0.05 or (p < 0.01)). Histopathological observation showed that renal cortex glomerular atrophy necrosis, medullary inflammatory cell infiltration, and other lesions. After administration of EBF, CTX-induced increase in serum level of related indexes was reduced, and MDA in kidney, GPT/ALT and IL-6 in liver, and IL-6 in spleen were increased. At the same time, histopathological findings showed that the necrosis of medullary and corticorenal tubular epithelium was relieved at EBF (50 mg/kg) dose compared with the CTX group, and the glomerular tubular necrosis gradually became normal at EBF (100 mg/kg) dose. Western blot analysis of Keap1 and Nrf2 protein expression in kidney tissue showed that compared with model CTX group, the drug administration group could alleviate the high expression of Keap1 protein and low expression of Nrf2 protein in kidney tissue. Conclusion: After the optimal extraction of total flavonoids from the stems and leaves of Epimedium, the molecular docking technique combined with animal experiments suggested that the effective component of the total flavonoids of Epimedium might activate the Keap1-Nrf2 signaling pathway after treatment to reduce the inflammation and oxidative stress of kidney tissue, so as to reduce kidney damage and improve kidney function. Therefore, EBF may become a new natural protective agent for CTX chemotherapy in the future. [ABSTRACT FROM AUTHOR]

Implementation and funding mechanisms to reverse biodiversity loss formed the core of the discussion focusing on the Post‐2020 Global Biodiversity Framework ("the Framework"), at the 15th Conference of Parties at the Convention on Biological Diversity hosted by China. Before financial support emerged from the private sector in China, biodiversity conservation had primarily been financed by the government. By the end of the 20th‐century international nongovernmental organizations and China's local philanthropists began to launch pilot programs in the country. In the past 5 years, biodiversity conservation across China has received CNY 1.757 billion (approximately $279 million) from the philanthropy sector. It represents the largest‐ and fastest‐growing share (69%) of environmental philanthropic funding; however, it accounted for <1% of all the philanthropic in all sectors nationwide. We suggested Foundations and NGOs review and adjust their strategies to align with the Kunming‐Montreal global biodiversity framework. Proactive connection and engagement with the philanthropies is required to expand its contributions while providing better pathways and support mechanisms for philanthropic funding for biodiversity conservation. Despite the philanthropic funding provided has been relatively modest over the past few decades, the philanthropic organizations have achieved significant positive results for biodiversity conservation in China. However, the funding for biodiversity conservation falls far short of what is needed to achieve the goals under the Kunming‐Montreal global biodiversity framework. This study provides a comprehensive overview of biodiversity philanthropic funding in China. Based on the collection of data related to environmentally relevant grants provided by companies, foundations, and individuals, we conducted a visualization analysis to reveal China's philanthropic funding flows between 2016 and 2020 in China. The profiles of donors and the receipts of the funding have been described. [ABSTRACT FROM AUTHOR]

Multi-temporal Interferometric Synthetic Aperture Radar technique (MTInSAR) has emerged as a valuable tool for measuring ground motion in a wide area. However, interpreting displacement time series and identifying dangerous signals from millions of InSAR coherent targets is challenging. In this study, we propose a method combining stacked autoencoder (SAE) and convolutional neural network (CNN) to classify InSAR time series and ease the interpretation of movements. The InSAR time series are classified into five categories, including stable, linear, accelerating, deceleration, and phase unwrapping error (PUE). The accuracy of labeled samples reaches 95.1%, reflecting the performance of the proposed method. This method was applied to the InSAR results for Kunming extracted from 171 ascending Sentinel-1 images from January 2017 to September 2022. The classification map of the InSAR time series shows that stable coherent points dominate around 79.28% of the area, with linear patterns at 10.70%, decelerating at 5.30%, accelerating at 4.72%, and PUE patterns at 3.60%. The results demonstrate that this method can distinguish different ground motion features and detect nonlinear deformation signals on a large scale without human intervention. [ABSTRACT FROM AUTHOR]