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Objectives: Patients with type 1 diabetes (T1D) face unique challenges in glycaemic control due to the complexity and uniqueness of the dietary structure in China, especially in terms of postprandial glycaemic response (PPGR). This study aimed to establish a personalized model for predicting PPGR in patients with T1D. Materials and methods: Data provided by the First People's Hospital of Yunnan Province, 13 patients with T1D, were recruited and provided with an intervention for at least two weeks. All patients were asked to wear a continuous glucose monitoring (CGM) device under free-living conditions during the study period. To tackle the challenge of incomplete data from wearable devices for CGM measurements, the GAIN method was used in this paper to achieve a more rational interpolation process. In this study, patients' PPGRs were calculated, and a LightGBM prediction model was constructed based on a Bayesian hyperparameter optimisation algorithm and a random search algorithm, which integrated glucose measurement, insulin dose, dietary nutrient content, blood measurement and anthropometry as inputs. Results: The experimental outcomes revealed that the PPGR prediction model presented in this paper demonstrated superior accuracy (R=0.63) compared to both the carbohydrate content only model (R=0.14) and the baseline model emulating the standard of care for insulin administration (R=0.43). In addition, the interpretation of the model using the SHAP method showed that blood glucose levels at meals and blood glucose trends 30 minutes before meals were the most important features of the model. Conclusion: The proposed model offers a heightened precision in predicting PPGR in patients with T1D, so it can better guide the diet plan and insulin intake dose of patients with T1D. [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of single-sensor sensing information characterization ability, which is easily interfered with by external environmental factors, a method of intelligent perception is proposed in this paper. This method integrates multi-source and multi-level information, including spindle temperature field, spindle thermal deformation, operating parameters, and motor current. Firstly, the internal and external thermal-error-related signals of the spindle system are collected by sensors, and the feature parameters are extracted; then, the radial basis function (RBF) neural network is utilized to realize the preliminary integration of the feature parameters because of the advantages of the RBF neural network, which offers strong multi-dimensional solid nonlinear mapping ability and generalization ability. Thermal-error decision values are then generated by a weighted fusion of different pieces of evidence by considering uncertain information from multiple sources. The spindle thermal-error sensing experiment was based on the spindle system of the VMC850 (Yunnan Machine Tool Group Co., LTD, Yunnan, China) vertical machining center of the Yunnan Machine Tool Factory. Experiments were designed for thermal-error sensing of the spindle under constant speed (2000 r/min and 4000 r/min), standard variable speed, and stepped variable speed conditions. The experiment's results show that the prediction accuracy of the intelligent-sensing model with multi-source information fusion can reach 98.1%, 99.3%, 98.6%, and 98.8% under the above working conditions, respectively. The intelligent-perception model proposed in this paper has higher accuracy and lower residual error than the traditional BP neural network perception and wavelet neural network models. The research in this paper provides a theoretical basis for the operation, maintenance management, and performance optimization of machine tool spindle systems. [ABSTRACT FROM AUTHOR]

The rural B&B industry is a key component of rural tourism, local economic development, and the wider rural revitalization strategy. Despite the abundance of tourism resources in Yunnan, the B&B sector faces significant challenges. It is therefore imperative to accurately identify the most pressing issues within the current B&B industry and formulate appropriate solutions to advance Yunnan's rural revitalization efforts. This study uses recent reviews of rural B&Bs on Ctrip.com and employs machine learning techniques, including Bert, CNN, LSTM, and GRU, to identify the key management challenges currently facing Yunnan's rural B&B industry. An analysis is then conducted to identify the key stakeholders involved in the process of improving the management of Yunnan's B&Bs. To assess the willingness of each stakeholder to support the improvement of the rural B&B industry, this paper establishes a three-party evolutionary game model and examines the dynamic evolutionary process of management improvement within Yunnan's rural B&B industry. Two scenarios of evolutionarily stable strategies are analyzed, and parameters impacting stakeholders' strategy choices are simulated and evaluated. The results show that: i) Improving the "human factor" is the top priority for the current management improvement because tourists are most concerned about the emotional experience. Operators need to focus on improving service attitude and emotional experience; ii) The main stakeholders in the current management optimization process of Yunnan B&Bs are the local government, B&B operators, and tourists. Under appropriate conditions, the evolutionarily stable strategy of (1, 1, 1) is reachable. iii) variables such as additional costs, tourists' choice preferences, and government penalties significantly affect the strategy choices of stakeholders, especially B&B operators. This paper offers effective strategies for improving B&B management that can benefit the government, B&B operators, and tourists, and ultimately contribute to the promotion of quality rural revitalization. The paper not only identifies focal areas for improving B&B management in rural Yunnan, but also provides an in-depth understanding of stakeholder dynamics. As a result, it provides valuable insights to further the cause of quality rural revitalization. [ABSTRACT FROM AUTHOR]

Based on our fieldwork in Yunnan Province and Ningxia Hui Autonomous Region, this paper explores the different ways in which Chinese rural women engage with the rising industry of e-commerce livestreaming related to agricultural products and villages. Our analytical framework is informed by feminist political economy, which pays heed to the gendered social settings, operation of power, and entanglement between women's domesticity and productivity that underpin people's economic activities. We argue that Chinese rural women's simultaneous empowerment and disempowerment by e-commerce livestreaming are characterized by "mobile immobility", a term inspired by Wallis's (2013) research on rural women's technological empowerment by mobile phones a decade ago. On the one hand, this latest form of e-commerce has created an apparently accessible path for rural women, who tend to be geographically immobile, to achieve social mobility by becoming professional webcasters and/or vloggers. On the other hand, this enablement is in fact classed, aged, and preconditioned on in-laws' support and willingness to share these women's domestic duties, which are not guaranteed. The urban-oriented digital economy of e-commerce livestreaming capitalizes on rural young women's femininity, docile bodies and labor as well as the reproductive labor performed by their family members at the microlevel, reinforcing the urban–rural disparity at the macrolevel. The paper ends with reflections on the role of information and communication technologies and e-commerce in the development of rural China. [ABSTRACT FROM AUTHOR]

Northwest Yunnan is nested in the border areas of Tibet, Myanmar, and Southwest China. The religiously and ethnically diverse region has astonishingly seen a lack of "conflict", as is often assumed in regions of ethnic and religious differences. This paper argues that there is an organic form of pluralism through frequent inter-ethnic and inter-religious marriages, multi-lingual daily interactions, and strategic ethnicity registrations. Ethnic and religious boundaries are made permanently or temporarily permeable through the celebration of boundary-crossing rituals such as weddings and funerals and other shared experiences such as collective labor and migrant work. Despite an increasingly strong push to be integrated into the state power through various top-down developmental projects, minority peoples here still use kinship, collective rituals, and other shared experiences to foster group formation that is fluid, porous, and malleable, instilling empathy and obligation as the basis of this pluralistic borderland society. This organic form of pluralism presents an alternative to the nation as the standard modern form of community. This paper ultimately argues that this specific type of plurality requires us to think beyond the normative liberal notions of religious tolerance and diversity that are still promoted within the frame of the exclusivist nation-state. [ABSTRACT FROM AUTHOR]

Under the background of the continuous progress of China's agricultural reform, the development of characteristic agriculture is an important field of agricultural development in the country and even the world. Yunnan has unique advantages in geography, location, climate, and human resources, and has unique conditions for the development of agriculture with plateau characteristic. However, the sustainable development of agriculture with plateau characteristic is affected and restricted by many factors. How to promote the sustainable development of agriculture with plateau characteristic is an important research topic, and it is also the main purpose of this study. Therefore, through literature analysis and investigation, this study studies the advantages and disadvantages, development status, main problems, countermeasures and suggestions, macro development direction, and theoretical research methods of characteristic agriculture in the Yunnan plateau. This paper analyzes the advantages and disadvantages of the Decision-making Trial and Evaluation Laboratory (DEMATEL) and the Adversarial Interpretation Structure Modeling Method (AISM) and proposes to combine the two models to make up for each other and improve the accuracy of model analysis. On this basis, a set of identification and evaluation systems of factors affecting the sustainable development of agriculture with plateau characteristic is established, which can comprehensively and accurately identify and evaluate various influencing factors, and provide a scientific basis for the sustainable development of agriculture with plateau characteristic. Finally, combined with the relevant statistical data of Yunnan Province from 2009 to 2020 and many results calculated by the model, the factors affecting the sustainable development of agriculture with plateau characteristic were comprehensively analyzed. The results show that transportation, environment, and insurance support factors are the root factors that affect the sustainable development of agriculture with plateau characteristic, while the regional economy, scientific and technological support, and the development of agricultural enterprises are of high importance. Financial support, the level of agricultural mechanization, the quality of labor, and other factors can not be ignored. Finally, according to the results of the analysis, the corresponding policy recommendations are put forward to provide a reference for the sustainable development of plateau characteristic agriculture in Yunnan Province. [ABSTRACT FROM AUTHOR]

Introduction: In the era of the Internet, online digital traces have become a new way to study the online attention of scenic spots and tourists’ purchase behavior. The public’s information search on major search platforms is a series of manifestations of potential tourists’ attention and interest in scenic spots, but there are few studies on how attention, interest and information search affect potential tourists to generate real purchase behavior. Method: This paper selects four dimensions of short video platform, travel website, search engine and social media to comprehensively measure the online attention of high-quality scenic spots in Yunnan Province, and then establishes a gray association analytic hierarchy process based on the relevant variables of the AISAS model to empirically analyze the primary and secondary factors affecting tourists’ purchase behavior. Results: (1) From the perspective of the online attention of scenic spots on different platforms, the intensity of the public’s scenic spots online attention on the four types of media platforms is in the order of travel websites, search engines, short videos and social media (2) From the perspective of spatial distribution characteristics, the online attention of high-quality scenic spots in Yunnan Province is unevenly distributed, that is, there is a big difference between the attention of higher star scenic spots and their star rating and popularity, while the attention of low-star scenic spots is not much different from their star rating and popularity (3) From the perspective of spatial agglomeration characteristics, the comprehensive online attention of high-quality scenic spots in Yunnan Province presents the spatial agglomeration characteristics of “the multi-core linkage of high-density in the east and north, and sub-high-density in the south” (4) The factors influencing the purchase behavior of potential tourists are sharing experience, attracting attention, generating interest and searching information. Discussion: By exploring the formation mechanism of high-quality scenic spots online attention in Yunnan Province and the mechanism of its spatial differentiation, this study not only enriches the logical chain of “tourism information source → potential tourists → demand driven → tourism information search → travel preference → destination selection → purchase decision → travel experience → real tourists → feelings after traveling → focus on feedback → tourism information source,” but also broadens the application scenarios and application boundaries of travel preference theory and AISAS behavior model to a certain extent. [ABSTRACT FROM AUTHOR]

To qualify the risk of extreme weather events for power supply security during the long-term power system transformation process, this paper proposes a risk probability evaluation method based on probabilistic production simulation. Firstly, the internal relationship of extreme weather intensity and duration is depicted using the copula function, and the influences of extreme weather on power security are described using the guaranteed power output ability coefficient, which can provide the extreme scenario basis for probabilistic production simulation. Then, a probabilistic production simulation method is proposed, which includes a typical-year scenario and extreme weather events. Meanwhile, an index system is proposed to qualify the power security level, which applies the loss of load expectation (LOLE) and time of loss of load expectation (TOLE) under different scenarios and other indices to reveal the long-term power security trend. Finally, the long-term power supply risks for the Yunnan provincial power system are analyzed using the proposed method, validating that the proposed method is capable of characterizing the influences of extreme weather on power security. The security level of different long-term power transformation schemes is evaluated. [ABSTRACT FROM AUTHOR]

This study aims to report three new species of Conoideocrella and Moelleriella from Yunnan Province, Southwestern China. Species of Conoideocrella and Moelleriella parasitize scale insects (Coccidae and Lecaniidae, Hemiptera) and whiteflies (Aleyrodidae, Hemiptera). Based on the phylogenetic analyses of the three-gene nrLSU, tef-1α, and rpb1, it showed one new record species (Conoideocrella tenuis) and one new species (Conoideocrella fenshuilingensis sp. nov.) in the genus Conoideocrella, and two new species, i.e., Moelleriella longzhuensis sp. nov. and Moelleriella jinuoana sp. nov. in the genus Moelleriella. The three new species were each clustered into separate clades that distinguished themselves from one another. All of them were distinguishable from their allied species based on their morphology. Morphological descriptions, illustrations, and comparisons of the allied taxa of the four species are provided in the present paper. In addition, calculations of intraspecific and interspecific genetic distances were performed for Moelleriella and Conoideocrella. [ABSTRACT FROM AUTHOR]

This paper studied the impact of education investment on regional poverty alleviation of Yunnan's poor counties, especially the dynamic constraints and marginal benefits of education input. This paper takes 30 poor counties in Yunnan province from 2007 to 2020 as the research object. A double fixed effect model, a systematic GMM model, and a quantile regression model are used to study the effect of education investment on regional poverty alleviation from static and dynamic levels. The results show that education investment has a significant positive effect on regional poverty alleviation at both static and dynamic levels. At the same time, under different poverty levels, the effect of education investment on poverty alleviation shows a law of diminishing marginal effect. As for the current situation of poor counties in Yunnan Province, the effect of education investment on poverty alleviation is increasing at a decreasing rate. The research object of this paper has achieved the goal of getting rid of absolute poverty, so the conclusion of this paper has more reference value. [ABSTRACT FROM AUTHOR]

By constructing the analytical framework of "farmland transfer—farmland function—income structure—rural household consumption", based on the sample data of 537 rural households in 50 villages in Yunnan Province of China, this paper uses the OLS model to explore the impact of farmland transfer on rural household consumption and uses an intermediary effect model to further explore its internal transmission mechanism. The research finds that: (1) Farmland transfer (farmland transfer-out or farmland transfer-in) can stimulate rural household consumption. (2) The coefficient of farmland transfer-out to non-food consumption is 0.118, which is greater than its coefficient of food consumption of 0.016; the rural households of farmland transfer-out are more willing to increase non-food consumption expenditure, which is conducive to the optimization of their consumption structure. (3) The coefficient of farmland transfer-in to food consumption is 0.028, which is greater than its coefficient to non-food consumption of 0.009; the rural households of farmland transfer-in are more willing to increase food consumption expenditure, which is not conducive to the optimization of their consumption structure. (4) Rural household consumption expenditure will show a downward trend with the increase in the age of the head of the rural household, and the consumption structure will also show a deterioration. (5) The more family assets rural households have, the stronger their consumption expenditure capacity, which is conducive to optimizing their consumption structure. (6) The results of the intermediary effect model show that farmland transfer affects rural households' consumption and consumption structure by affecting rural households' income under different livelihood modes. Accordingly, the paper puts forward some suggestions on establishing the benefit coordination mechanism of farmland transfer, improving the non-agricultural employment mechanism of the rural surplus labor force, raising the expected return on farmland investment, increasing the proportion of household income saved appropriately and strengthening the social security mechanism in order to further promote the orderly transfer of farmland, improve the consumption capacity and consumption level of rural households, expand rural domestic demand and promote rural consumption upgrading. [ABSTRACT FROM AUTHOR]

Algal blooms caused by eutrophication are a major global problem, and the monitoring and prediction of algal densities in lakes are important indicators of eutrophication management. However, the reliability of the commonly used chlorophyll-a (Chl-a) to characterize phytoplankton density in lake environments needs to be further investigated. In this paper, we sampled and analyzed 365 samples from nine plateau lakes in Yunnan Province during the dry and rainy seasons. The Chl-a data measured by the laboratory spectrophotometric method and the portable YSI multi-parameter water quality meter (YSI) directly used in the field were compared, and regression analysis and correlation analysis with phytoplankton density were performed. Most of the Chl-a values measured by the laboratory instrument were greater than those measured by the YSI, and the correlation between the two methods was weak (0.492, p < 0.001). The correlation between Chl-a and phytoplankton density measured by the YSI reached 0.67 (p < 0.001) in the dry season, while the laboratory methods used to measure Chl-a to characterize phytoplankton density may have led to an overestimation of phytoplankton density due to nonspecific sources of Chl-a. However, both methods are relatively inaccurate for characterizing phytoplankton density. For different trophic states of lakes, nutrient concentration changes affect the Chl-a concentration of phytoplankton. During different seasons, changes in the fluorescence intensity of phytoplankton in response to environmental conditions prevent the YSI results from reflecting the authentic phytoplankton density. Furthermore, high species diversity can lead to inconsistent changes in Chl-a and phytoplankton because the content of Chl-a in individual cells of different phytoplankton is different. The relationship between Chl-a and phytoplankton density was species specific. Therefore, when applying Chl-a to characterize phytoplankton density in lakes, it is necessary to consider environmental conditions, phytoplankton community structure and other practical conditions. In addition, laboratory analytical methods and instrumental techniques and instruments need to be improved. [ABSTRACT FROM AUTHOR]

The non-tectonic deformation caused by hydrological loads is an important influencing factor in GNSS vertical displacement. Limited by the temporal and spatial resolution of global models and model errors, the hydrological load results calculated by traditional methods are difficult to meet the high temporal and spatial resolution requirements of small to medium-scale regions. This paper introduces the idea of the remove–restore method, assimilates regional high-resolution hydrological data, and obtains higher temporal and spatial-resolution hydrological load results. Subsequently, utilizing data from 12 CORS observed in the western Yunnan region between January 2018 and December 2020, the quantitative relationship and variation characteristics between GNSS vertical displacement and hydrological load displacement were analyzed in detail. Furthermore, the annual signals of both were extracted using the SSA method for comparative analysis. After removing the effects of atmospheric load and non-tidal ocean load, the average correlation coefficient between GNSS vertical displacement and hydrological load displacement is 0.84, with an average reduction of WRMS (%) reaching 37.17%. The average correlation coefficient of the annual signals between GNSS vertical displacement and hydrological load deformation is 0.94, with an average reduction of WRMS (%) reaching 46.5%, indicating that the contribution of hydrological load to the GNSS non-tectonic vertical displacement annual signal is close to 50%. The research results provide scientific support and important references for studying surface tectonic deformation by removing non-tectonic deformations such as hydrological loads from GNSS vertical displacement. Additionally, it helps to explore the mechanisms of interaction between water storage migration and surface deformation. [ABSTRACT FROM AUTHOR]

In order to efficiently identify early tea diseases, an improved YOLOv8 lesion detection method is proposed to address the challenges posed by the complex background of tea diseases, difficulty in detecting small lesions, and low recognition rate of similar phenotypic symptoms. This method focuses on detecting tea leaf blight, tea white spot, tea sooty leaf disease, and tea ring spot as the research objects. This paper presents an enhancement to the YOLOv8 network framework by introducing the Receptive Field Concentration-Based Attention Module (RFCBAM) into the backbone network to replace C2f, thereby improving feature extraction capabilities. Additionally, a mixed pooling module (Mixed Pooling SPPF, MixSPPF) is proposed to enhance information blending between features at different levels. In the neck network, the RepGFPN module replaces the C2f module to further enhance feature extraction. The Dynamic Head module is embedded in the detection head part, applying multiple attention mechanisms to improve multi-scale spatial location and multi-task perception capabilities. The inner-IoU loss function is used to replace the original CIoU, improving learning ability for small lesion samples. Furthermore, the AKConv block replaces the traditional convolution Conv block to allow for the arbitrary sampling of targets of various sizes, reducing model parameters and enhancing disease detection. the experimental results using a self-built dataset demonstrate that the enhanced YOLOv8-RMDA exhibits superior detection capabilities in detecting small target disease areas, achieving an average accuracy of 93.04% in identifying early tea lesions. When compared to Faster R-CNN, MobileNetV2, and SSD, the average precision rates of YOLOv5, YOLOv7, and YOLOv8 have shown improvements of 20.41%, 17.92%, 12.18%, 12.18%, 10.85%, 7.32%, and 5.97%, respectively. Additionally, the recall rate (R) has increased by 15.25% compared to the lowest-performing Faster R-CNN model and by 8.15% compared to the top-performing YOLOv8 model. With an FPS of 132, YOLOv8-RMDA meets the requirements for real-time detection, enabling the swift and accurate identification of early tea diseases. This advancement presents a valuable approach for enhancing the ecological tea industry in Yunnan, ensuring its healthy development. [ABSTRACT FROM AUTHOR]

Old landslides in the Loess Plateau, Northwest China usually occurred over a relatively long period, and their sizes are usually smaller compared to old landslides in the alpine valley areas of Sichuan, Yunnan, and Southeast Tibet. These landslide areas may have been changed either partially or greatly, and they are usually covered with vegetation and similar to their surrounding environment. Therefore, it is a great challenge to detect them using high-resolution remote sensing images with only orthophoto view. This paper proposes the optimal-view and multi-view strategic hybrid deep learning (OMV-HDL) method for old loess landslide detection. First, the optimal-view dataset in the Yan'an area (YA-OP) was established to solve the problem of insufficient optical features in orthophoto images. Second, in order to make the process of interpretation more labor-saving, the optimal-view and multi-view (OMV) strategy was proposed. Third, hybrid deep learning with weighted boxes fusion (HDL-WBF) was proposed to detect old loess landslides effectively. The experimental results with the constructed optimal-view dataset and multi-view data show that the proposed method has excellent performance among the compared methods—the F1 score and AP (mean) of the proposed method were improved by about 30% compared with the single detection model using traditional orthophoto-view data—and that it has good detection performance on multi-view data with the recall of 81.4%. [ABSTRACT FROM AUTHOR]

Nanhong agate has attracted public attention as the most distinctive gemstone in China. Owing to the limited data on Nanhong agates from a new production area in northeastern Yunnan, this paper presents the first data from gemological studies on these agates. Complex investigations using Fourier-transform infrared (FTIR) spectrometry, ultraviolet–visible (UV–VIS) luminescence spectrometry, Raman spectroscopy, polarizing microscopy, scanning electron microscopy (SEM), electron microprobe (EPMA), and laser ablation–inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses were carried out to obtain basic data concerning the gemological properties, microstructure, and spectroscopic and geochemical characteristics of this interesting material. The results illustrate that Nanhong agates from northeastern Yunnan are mainly composed of α-quartz and also contain certain amounts of moganite, illite, goethite, and hematite. The typical red (yellow) and white appearance can be attributed to the microstructure of the agates, the contents of Fe and Al impurities, and trace elements. The Raman spectra, microstructure, and chemical composition of the unique "yellow-skinned" agates from northeastern Yunnan are significantly different from those of other types of Nanhong agate. This work lays a foundation for the future identification and research of this type of Nanhong agate. [ABSTRACT FROM AUTHOR]

China is highly rich in diversity of Begonia, and in which Guangxi Zhuangzu Autonomous Region, following Yunnan province, has the second highest number of Begonia species. As a distribution center of Begonia sect. Coelocentrum, Guangxi already had 58 species recognized in this section. In this paper, Begonia ornithopedata, a new taxon of B. sect. Coelocentrum from southwestern Guangxi is described. With the bird-foot-shape lobed leaves, the new species is easily distinguished from any of other taxa, excepting few similarities only in leaf morphology of B. laminariae Irmsch. and B. circumlobata Hance. Its conservation status is assigned as the Endangered according to The Guidelines for Using the IUCN Red List Categories. [ABSTRACT FROM AUTHOR]

In this study, eight new species are described from the subtropical parts of Yunnan Province in southwestern China: Belisana honghe Zhang, Li & Yao, sp. nov. (♂♀), B. jiuxiang Zhang, Li & Yao, sp. nov. (♂♀), B. lincang Zhang, Li & Yao, sp. nov. (♂♀), B. luxi Zhang, Li & Yao, sp. nov. (♂♀), B. tengchong Zhang, Li & Yao, sp. nov. (♂♀), B. tongi Zhang, Li & Yao, sp. nov. (♂♀), B. yongsheng Zhang, Li & Yao, sp. nov. (♂), and B. yunnan Zhang, Li & Yao, sp. nov. (♂♀). They add up to a total of 31 Belisana species from Yunnan in an updated list provided in this paper. [ABSTRACT FROM AUTHOR]

Accurate parameter estimation of extreme wind speed distribution is of great importance for the safe utilization and assessment of wind resources. This paper emphatically establishes a novel grey generalized extreme value method for parameter estimation of annual wind speed extremum distribution (AWSED). Considering the uncertainty and frequency characteristics of the parent wind speed, the generalized extreme value distribution (GEVD) is selected as the probability distribution, and the Weibull distribution is utilized as the first-order accumulation generating operator. Then, the GEVD differential equation is derived, and it is transformed into the grey GEVD model using the differential information principle. The least squares method is used to estimate the grey GEVD model parameters, and then a novel estimation method is proposed through grey parameters. A hybrid particle swarm optimization algorithm is used to optimize distribution parameters. The novel method is stable under different sample sizes according to Monte Carlo comparison simulation results, and the suitability for the novel method is confirmed by instance analysis in Wujiaba, Yunnan Province. The new method performs with high accuracy in various indicators, the hypothesis test results are above 95%, and the statistical errors such as MAPE and Wasserstein distance yield the lowest, which are 3.33% and 0.2556, respectively. [ABSTRACT FROM AUTHOR]

Shoshonitic rocks are widely distributed in post-collisional settings and provide key information on deep geodynamic mechanisms and magmatic evolution. In this paper, we present petrographic, zircon U-Pb age-related, trace elemental, Hf isotopic, bulk-rock elemental, and Sr-Nd isotopic data of the Dalongtan shoshonitic syenite porphyries (DSSPs) in central Yunnan, southeastern Tibet. The DSSPs formed at 33.2 ± 0.3 Ma in a post-collisional setting. They define linear trends on Harker diagrams, and they display similar trace element patterns and enriched bulk-rock Sr-Nd isotopes [(87Sr/86Sr)i = 0.70964–0.70968, εNd(t) = −12.9 to −12.7] and zircon Hf isotopes (εHf(t) = −15.7 to −13.1) to the coeval mantle-derived potassic mafic rocks. This suggests that the DSSPs were fractionated from the lithospheric mantle-derived mafic magmas. The DSSPs, along with the coeval felsic and mafic magmatic rocks (37.2–32.3 Ma), exhibit a planar distribution on the SE Tibet and predate the left-lateral shearing of the Ailaoshan–Red River shear zone (ARSZ) (32–22 Ma), suggesting that there are no genetic relationships between them. The DSSPs have geochemical characteristics similar to those of A-type granites, with high total alkalinity (10.39–11.17 wt.%), HFSE concentrations (Zr + Nb + Ce + Y = 890.2–1054.3 ppm), Ga/Al ratios (10,000 × Ga/Al = 2.95–3.46), whole-rock zircon saturation temperatures (906–947 °C), and oxygen fugacity (ΔFMQ = +3.30–+4.65), indicating that they are products of the high-temperature melting of the lithosphere as a result of asthenosphere upwelling in extensional settings. Based on our data and regional observations, it is proposed that the generation of the DSSPs may be linked to the convective thinning of the thickened lithospheric mantle following the India–Asia collision. [ABSTRACT FROM AUTHOR]

With the rapid development of road engineering today, a large number of high-grade highways need to pass through expansive soil distribution areas. At present, the research on expansive soil slope mainly focuses on the newly excavated cutting slope. However, according to engineering experience, a landslide of fill embankment on expansive soil foundation is also very common. The expansive soil layer is heterogeneous. There are many weak intercalations or large fissures under the ground, which are generally parallel to the trend, with low strength and high permeability. After rainfall, the strength of the weak interlayer and large fissures will be further reduced after moisture absorption, and the sliding surface is easily formed under the load of filler, which is the main factor inducing embankment landslide. On the basis of landslide investigation and a laboratory test, a FORTRAN calculation program is developed in this paper, which can comprehensively consider the special moisture absorption and softening characteristics of expansive soil. Taking a high fill embankment slope with a soft interlayer in the Baoshan area of Yunnan Province as an example, the stability and instability characteristics of the fill slope on the expansive soil foundation are analyzed, and the influence of moisture absorption and softening on the expansive soil slope is emphatically discussed. Finally, this paper puts forward the reinforcement method of the high fill embankment slope on the soft expansive soil foundation, which is proven to have a good reinforcement effect through calculation analysis and field practice. For expansive soil foundation with weak interlayer, it is better to directly reinforce the weak layer through rigid piles. [ABSTRACT FROM AUTHOR]

Pu-erh tea, Camellia sinensis is a traditional Chinese tea, one of the black teas, originally produced in China's Yunnan Province, named after its origin and distribution center in Pu-erh, Yunnan. Yunnan Pu-erh tea is protected by geographical Indication and has unique quality characteristics. It is made from Yunnan large-leaf sun-green tea with specific processing techniques. The quality formation of Pu-erh tea is closely related to the soil's environmental conditions. In this paper, time-by-time data of the soil environment of tea plantations during the autumn tea harvesting period in Menghai County, Xishuangbanna, Yunnan Province, China, in 2021 were analyzed. Spearman's correlation analysis was conducted between the inner components of Pu'er tea and the soil environmental factor. The analysis showed that three soil environmental indicators, soil temperature, soil moisture, and soil pH, were highly significantly correlated. The soil environmental quality evaluation method was proposed based on the selected soil environmental characteristics. Meanwhile, a deep learning model of Long Short Term Memory (LSTM) Network for the soil environmental quality of tea plantation was established according to the proposed method, and the soil environmental quality of tea was classified into four classes. In addition, the paper also compares the constructed models based on BP neural network and random forest to evaluate the coefficient of determination (R2), mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE) of the indicators for comparative analysis. This paper innovatively proposes to introduce the main inclusions of Pu'er tea into the classification and discrimination model of the soil environment in tea plantations, while using machine learning-related algorithms to classify and predict the categories of soil environmental quality, instead of relying solely on statistical data for analysis. This research work makes it possible to quickly and accurately determines the physiological status of tea leaves based on the establishment of a soil environment quality prediction model, which provides effective data for the intelligent management of tea plantations and has the advantage of rapid and low-cost assessment compared with the need to measure the intrinsic quality of Pu-erh tea after harvesting is completed. [ABSTRACT FROM AUTHOR]

Numerous scholars have used traditional thermal anomaly extraction methods and time series prediction models to study seismic anomalies based on longwave infrared radiation data. This paper selected bidirectional long short-term memory (BILSTM) as the research algorithm after analyzing and comparing the prediction performance of five time series prediction models. Based on the outgoing longwave radiation (OLR) data, the time series prediction model was used to predict the infrared longwave radiation values in the spatial area of 5° × 5° at the epicenter for 30 days before the earthquake. The confidence interval was used as the evaluation criterion to extract anomalies. The examples of earthquakes selected for study were the Yangbi Ms6.4-magnitude earthquake in Yunnan on 21 May 2021 and the Luding Ms6.8-magnitude earthquake in Sichuan on 5 September 2022. The results showed that the observed values of the Yangbi earthquake 15 to 16 days before the earthquake (5 May to 6 May) exceeded the prediction confidence interval over a wide area and to a large extent. This indicates a strong and concentrated OLR anomaly before the Yangbi earthquake. The observations at 27 days (9 August), 18 days (18 August), and 8 days (28 August) before the Luding earthquake exceeded the prediction confidence interval in a local area and by a large extent, indicating a strong and scattered OLR anomaly before the Luding earthquake. Overall, the method used in this paper extracts anomalies in both spatial and temporal dimensions and is an effective method for extracting infrared longwave radiation anomalies. [ABSTRACT FROM AUTHOR]

The main path of development credit funds in rural poverty alleviation in Y province is crucial. This paper studies the rural poverty alleviation work in extreme poverty areas in Yunnan and puts forward targeted and instructive policy suggestions for specific difficult areas. Research the relationship between credit resource allocation and rural poverty alleviation. The existing research is mainly based on the relationship between financial development and economic growth, income growth, income distribution, and, on the surface, the relationship between the scale of financial development and the efficiency of financial development and other indicators. The purpose is to put forward targeted measures and suggestions on the basis of theoretical research and model analysis to help the Yunnan banking industry support poverty alleviation. The results of the study show that there is a causal relationship between agriculture-related loans. [ABSTRACT FROM AUTHOR]

In China, slope engineering occasionally faces landslides in rocky slopes containing muddy interlayers, primarily triggered by excavation activities. These incidents lead to considerable human casualties and substantial economic losses. However, existing studies predominantly concentrate on the excavation-induced impacts on the stability of rocky slopes characterized by single-layered soft and weak interlayers. Conversely, reports on how excavation influences the stability of bedding cataclastic rock mass high slope containing multimuddy interlayers remain notably absent in the literature. Moreover, unloading due to excavation can swiftly compromise the mechanical integrity and overall quality of the rock mass, consequently impacting the stability of slopes postexcavation. Therefore, this paper modeled the unstable slope excavated at a waste incineration power plant in Yuxi, Yunnan, using the finite element strength reduction method. This approach was employed to comprehensively simulate the entire process of artificial multilevel excavation in a bedding cataclastic rock mass high slope containing multimuddy interlayers. This study investigated the impact of multilevel artificial excavation on slope stability by thoroughly considering factors including alterations in slope morphology, unloading effects, and the degradation of geotechnical parameters. The research yielded the subsequent conclusions. Multimuddy interlayers were the key to the slope's instability. For slopes subjected to such multilevel excavation, efforts were made to minimize the exposure of muddy interlayers. Slopes above exposed muddy interlayers did not require additional support, while those below needed prioritized reinforcement. The likely instability mode of the actual slope was local destabilization leading to landslides. Furthermore, when using numerical simulation methods to study the impact of excavation disturbances on the stability of such slopes, it was necessary to consider the deterioration of geotechnical parameters to obtain results more reflective of actual conditions. These research findings provided valuable theoretical and empirical support for studies on similar excavated slopes. [ABSTRACT FROM AUTHOR]

Background: Earthquakes and landslides pose significant threats to human safety and property, necessitating early warning systems. However, the high construction costs of earthquake early warning systems present a challenge. Purpose: Landslide warnings are more prevalent, so linking them to earthquake warnings could address cost concerns. Hence, it is crucial to validate the feasibility of utilizing GNSS landslide monitoring as assistance for earthquake early warning systems. Methods: This paper analyzes acceleration anomaly data from 31 GNSS landslide monitoring points near the epicenter of the May 2, 2023, MW = 5.2 Baoshan earthquake in Yunnan. The response time was determined as the time difference between an earthquake's occurrence and GNSS's acceleration anomalies. This calculation helps measure the time delay and sensitivity between these two events. Data were obtained from the geological disaster monitoring and early warning management system. Results: GNSS landslide monitoring showed high sensitivity to nearby earthquakes. The fastest response time among the 31 data points was 8 seconds, while the slowest was 56 seconds, all falling within the one-minute mark. A linear correlation was found between acceleration anomaly response time and distance from the epicenter, indicating the feasibility of GNSS landslide monitoring-assisted earthquake monitoring. Conclusion: A proposal is made for a GNSS landslide monitoring cluster to establish a multi-dimensional landslideearthquake disaster warning system. This approach offers new methods for combining earthquake and landslide early warning systems, leveraging existing infrastructure for cost-effectiveness and enhancing disaster preparedness. [ABSTRACT FROM AUTHOR]

Yunnan is located in the center of the east-Asian karst area, one of the three largest karst areas in the world. Rocky desertification is widespread in the area, which seriously restricts the sustainable development of local social economy. In this study, we summarize the research status and achievements of rocky desertification in Yunnan mainly from three aspects, rocky desertification zoning, governance model and vegetation restoration in rocky desertification areas. The results show that rocky desertification areas in Yunnan are divided into 2 large areas and 5 small ones. After years of exploration, 23 kinds in 4 categories of rocky desertification control models have been formed, and 435 kinds of plant species can be used for ecological restoration in rocky desertification areas, including 376 species of shrubs and 59 species of herbs. Finally, combined with geographical location, climate and altitude, this paper preliminarily summarizes the suitable restoration vegetation, and points out the shortcomings in the studies on the control of rocky desertification, so as to provide an important theoretical reference for the subsequent research on the restoration and control of rocky desertification vegetation. [ABSTRACT FROM AUTHOR]

In this paper, we describe a new species, Melanoseris penghuana, from Mt. Jiaozi Xueshan located in North-central Yunnan, China. Despite its morphological similarities to M. likiangensis, M. penghuana exhibits distinct differences in leaf texture, shape of terminal lobes, indumentum of leaves, peduncles, and involucres, as well as the length of the achenes. Additionally, the conservation status of this species is classified as Vulnerable through data analysis from two field surveys. [ABSTRACT FROM AUTHOR]

In this experiment, a pellet preparation method was investigated to study the drying, preheating, and roasting properties of limonitic iron ore from a plant in Yunnan. The aim was to improve the subsequent iron-making process of limonitic iron ore and make it a substitute for sintered ore. This substitution would reduce the amount of blast furnace slag in the iron-making process. Bentonite is commonly used as a primary binder in many pelletizing plant operations. However, its excessive usage leads to a higher risk of slagging and coking in the furnace. In this paper, we aim to decrease the quantity of bentonite added, enhance the iron content in the pellets, and reduce impurities to improve the grade of limonite pellets. The results show that the optimal drying, preheating, and roasting temperatures of limonite pellets are 200 °C, 700 °C, and 1250 °C, respectively, and the optimal roasting time is 20 min, when the diameter of the pellets is 8–13 mm. The compressive strength of limonite pellets with the addition of 1.5% bentonite was the highest, meeting the demands of a general blast furnace, based on which the iron grade of limonite pellet ore was increased by 10.63%. [ABSTRACT FROM AUTHOR]

Frame beams with anchor cables constitute a crucial method for slope reinforcement projects. With the development of fabricated structures, there has been an increasing focus on precast prestressed frame beams with anchor cables. This paper presents a field test conducted in Yunnan, China and numerical simulations to analyze the structure behavior of three types of frame beams with a 600 kN anchoring force: cast-in-situ frame beams, precast prestressed frame beams, and precast prestressed frame beams with connections. The results showed that: (1) Although all three types of frame beams met the design requirements for a 600 kN anchoring force capacity, the volume of precast prestressed frame beams constituted only 57% of that of the cast-in-situ frame beams. (2) The maximum bending moment for the precast prestressed frame beams with connections was 60 kN·m less than that for the cast-in-situ frame beams. (3) The field test results for bending moments exceeded the values obtained from the numerical simulation. When using a numerical simulation to study the bending moments of the anchor frame beams, it is acceptable to apply appropriate amplifications to the numerical results. (4) Among the three types of frame beams with cables, the precast prestressed frame beams with connections exhibited the best structural performance. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, a new Pareas species of the P. hamptoni complex is described from southern Yunnan Province, China, based on morphological and molecular evidence. Genetically, the new species is most closely related to P. hamptoni sensu stricto, for which we confirm the distribution in China. Morphologically, the new species can be distinguished from P. hamptoni sensu stricto and all other congeners by a combination of morphological characteristics. The discovery of the new species brings the total number of recognized species of the genus Pareas to 31, of which 25 occur in China. We describe a new species of the genus Pareas, based on three specimens collected from Guanyinshan Provincial Nature Reserve in Yuanyang County, Honghe Prefecture, Yunnan Province, China. The new species is distinguished from its congeners by one preocular, one postocular or postocular fused with subocular, loreal not bordering the orbit, one row enlarged vertebral scales, five rows keeled mid-dorsal scales at the middle of the body, 189–192 ventral scales and 72–89 subcaudal scales. The dorsal surfaces of the head and body are yellowish red or yellowish brown, and the belly and ventral surfaces of the head and tail are pinkish yellow or yellow with more or less small black spots. Phylogenetic analyses of mitochondrial DNA recovered the new species being the sister taxon to P. hamptoni sensu stricto. The genetic divergences between the new species and P. hamptoni sensu stricto were 4.2% in the Cyt b sequences and 5.0% in the ND4 sequences. In addition, based on specimens collected from Honghe and Wenshan prefectures, we confirmed that P. hamptoni sensu stricto is distributed in China. [ABSTRACT FROM AUTHOR]

In order to explore the carbon emission reduction potential of farmland ecosystems in cities (prefectures) of Yunnan Province, based on the Panel data related to farmland carbon emissions in cities (prefectures) of Yunnan Province from 2011 to 2020, this paper establishes an indicator system of farmland carbon emission reduction capacity from three aspects of energy factors, technical factors and economic factors, uses the Game theory combination weighting method to determine the comprehensive weight of indicators, introduces set pair analysis, cloud matter element coupling model and set pair analysis partial coefficient algorithm. It conducts a comprehensive evaluation and analysis of the carbon reduction capacity and development trend of farmland in Yunnan Province. The evaluation results indicate that:CDThe spatial layout of farmland carbon reduction capacity in Yunnan Province shows a pattern of strong in the southeast, weak in the southwest, and moderate in the east and west. Among them, the industrial development pattern and regional economic output value are the main influencing factors on farmland carbon reduction capacity. ©In the analysis of the development trend of carbon reduction capacity in farmland, it is found that Yunnan Province as a whole shows a negative development trend. By clarifying the current development status of carbon emissions from farmland ecosystems in Yunnan Province and identifying key regulatory areas, planning and formulating industry layout and cultivation management measures to reduce carbon emissions from farmland according to local conditions, this paper serves as a reference and decision-making basis for the development of low-carbon agriculture in Yunnan. [ABSTRACT FROM AUTHOR]

The diversity of nematode-trapping fungi (NTF) holds significant theoretical and practical implications in the study of adaptive evolution and the bio-control of harmful nematodes. However, compared to terrestrial ecosystems, research on aquatic NTF is still in its early stages. During a survey of NTF in six watersheds in Yunnan Province, China, we isolated 10 taxa from freshwater sediment. Subsequent identification based on morphological and multigene (ITS, TEF1-α, and RPB2) phylogenetic analyses inferred they belong to five new species within Arthrobotrys. This paper provides a detailed description of these five novel species (Arthrobotrys cibiensis, A. heihuiensis, A. jinshaensis, A. yangbiensis, and A. yangjiangensis), contributing novel insights for further research into the diversity of NTF and providing new material for the biological control of aquatic harmful nematodes. Additionally, future research directions concerning aquatic NTF are also discussed. [ABSTRACT FROM AUTHOR]

The karst area in Southwest China is characterized by complex terrain and karst development, with a large area of exposed carbonate rocks and a wide distribution of karst depressions and valleys on the surface. Therefore, this area is highly subject to water inflow in tunnel construction. The Dapozi tunnel area of the central Yunnan Province is a deep-buried tunnel in the karst area, in which exist many faults and very complex hydrogeological conditions. Therefore, it is necessary to predict the tunnel inflow during construction by analyzing the water inflow conditions and identifying its sources, which can ensure the safety of tunnel construction. Currently, numerical and analytical methods are commonly used to predict water inflow. The analytical methods mainly calculate the water inflow of tunnel through empirical calculation formulas. However, most of these methods are based on some assumptions and specific boundary conditions, which may limit their applicability in complex cases. The numerical method can simulate complex geological conditions by obtaining accurate data about geological characteristic, but its accuracy is restricted by the accuracy of borehole data in numerical calculation. Therefore, the mutual supplementation of numerical and analytical methods can significantly improve the efficiency and accuracy of water inflow prediction. Besides, most of the previous studies only predicted the water inflow of tunnel in the survey and design stage. But they did not describe the actual construction progress in the model, and the accuracy of prediction results conducted separately with numerical or analytical methods were not verified by the actual water inflow data. By analyzing the stratigraphic lithology and geological structure of the strata in the study area, we preliminarily identified the construction sections with the risks of water inflow. Based on hydrogeological surveys, we collected water samples from tunnels, springs, and wells in the study area to measure the geochemical characteristics of groundwater. Furthermore, we analyzed the sources for tunnel inflow and degrees of karst development, using Piper trilinear diagrams and Gibbs diagrams. Based on the procedures above, we used analytic and numerical methods to calculate the maximum and average water inflow of each tunnel unit, and compared the predicted values with the actual ones. We have also built a numerical groundwater flow model based on FEFLOW, which couples the simulation of regional macroscopic groundwater distribution and employs a method that combines multiple time series with the comprehensive assignment of various internal boundaries to depict the dynamic construction process. The results show the study area is developed with three main faults in. Although the permeability of these faults is weak, the gullies formed by these faults will gather atmospheric precipitation and surface water, increasing water inflow risk during tunnel construction. The TDS of groundwater in the area gradually increases from south to north, indicating that groundwater flows from the south to the north of the study area. The δD and δ18O isotope results prove that the water inflow in tunnel is from the low altitude; the distance of the groundwater runoff path is medium; atmospheric precipitation is the primary supply source. Gibbs diagram shows that the ions in the groundwater are mainly from rock weathering, suggesting that there may be karst fissures in carbonate rocks due to water-rock interaction within the area. In addition, the analytical method can efficiently calculate the water inflow of tunnel in the preliminary survey and design stage of the project. However, this method cannot dynamically predict the change in the water inflow. In essence, it is an analytical formula derived from the theory on the stable movement of the phreatic aquifer to the complete well. Therefore, the groundwater table dramatically affects the result, and the prediction accuracy in the section of the high groundwater table of analytical method is lower than that of the numerical method. The numerical method focuses on the high-accuracy model of engineering scale in the karst system, which is controlled by the macroscopic groundwater distribution. It pays attention to the description of the dynamic process and the conditions of the project area. Specifically, it describes the dynamic construction process by multi-time series. The working conditions of the excavating and lining are described by "GAP" in FEFLOW, which can accurately predict the change of water inflow in construction. Therefore, based on the actual hydrogeological conditions, the analytical-numerical method can significantly improve the efficiency and accuracy of water inflow prediction. The methods and models used in this paper are significant for preventing and controlling water inflow disasters in high-risk tunnels. [ABSTRACT FROM AUTHOR]

As a traditional and popular dietary supplement, lotus rhizome starch (LRS) has health benefits for its many nutritional components and is especially suitable for teenagers and seniors. In this paper, the approximate composition, apparent amylose content (AAC), and structural characteristics of five LRS samples from different regions were investigated, and their correlations with the physicochemical properties of granular and gelatinized LRS were revealed. LRS exhibited rod-shaped and ellipsoidal starch granules, with AAC ranging from 26.6% to 31.7%. LRS-3, from Fuzhou, Jiangxi Province, exhibited a deeper hydrogel color and contained more ash, with 302.6 mg/kg iron, and it could reach the pasting temperature of 62.6 °C. In comparison, LRS-5, from Baoshan, Yunnan Province, exhibited smoother granule surface, less fragmentation, and higher AAC, resulting in better swelling power and freeze-thaw stability. The resistant starch contents of LRS-3 and LRS-5 were the lowest (15.3%) and highest (69.7%), respectively. The enzymatic digestion performance of LRS was positively correlated with ash content and short- and long-term ordered structures but negatively correlated with AAC. Furthermore, the color and network firmness of gelatinized LRS was negatively correlated with its ash content, and the retrograde trend and freeze-thaw stability were more closely correlated with AAC and structural characteristics. These results revealed the physicochemical properties of LRS from different regions and suggested their advantages in appropriate applications as a hydrogel matrix. [ABSTRACT FROM AUTHOR]

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The Tropical Niche Conservatism Hypothesis (TCH) tries to explain the generally observed latitudinal gradient of increasing species diversity towards the tropics. To date, few studies have used phylogenetic approaches to assess its validity, even though such methods are especially suited to detect changes in niche structure. We test the TCH using modeled distributions of 1898 woody species in Yunnan Province (southwest China) in combination with a family level phylogeny. Unlike predicted, species richness and phylogenetic diversity did not show a latitudinal gradient, but identified two high diversity zones, one in Northwest and one in South Yunnan. Despite this, the underlying residual phylogenetic diversity showed a clear decline away from the tropics, while the species composition became progressingly more phylogenetically clustered towards the North. These latitudinal changes were strongly associated with more extreme temperature variability and declining precipitation and soil water availability, especially during the dry season. Our results suggests that the climatically more extreme conditions outside the tropics require adaptations for successful colonization, most likely related to the plant hydraulic system, that have been acquired by only a limited number of phylogenetically closely related plant lineages. We emphasize the importance of phylogenetic approaches for testing the TCH. [ABSTRACT FROM AUTHOR]

The rational use of natural wind in extra-long tunnels for feedforward operation ventilation control can dramatically reduce tunnel operation costs. However, traditional tunnel natural wind calculation theory lacks a prediction function. This paper proposes a three-stage tunnel natural wind prediction method relying on the Yanglin Tunnel in Yunnan, China based on the massive meteorological parameters provided by the open-source national meteorological stations around the tunnel, which make up for the partial deficiency of the meteorological parameters of the tunnel portal. The multi-layer perceptron model (MLP) was used to predict the real-time meteorological parameters of the tunnel portal using the data from four national meteorological stations. The nonlinear autoregressive network model (NARX) was used to predict the meteorological parameters of the tunnel portal in the next period based on the predicted and measured real-time data. The natural wind speed in the tunnel was obtained by a theoretical calculation method using the predicted meteorological parameters. The final tunnel natural wind prediction results are in good agreement with the field measured data, which indicates that the research results of this paper can play a guiding role in the feedforward regulation of tunnel operation fans. [ABSTRACT FROM AUTHOR]

Kunming city is located in the middle of Yunnan Province. Due to large-scale groundwater exploitation and urban development in recent years, this area has been affected by surface subsidence. In this paper, Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) data are used to monitor the surface subsidence in Kunming city area for better analysis and understanding. The study used data of Sentinel-1A from 2018 to 2020 with atmospheric correction based on GACOS to calculate the average annual subsidence rate in Kunming city area, and the results show that the maximum subsidence rate is 48 mm/year. The subsidence obtained by InSAR is compared with the vertical deformation information obtained by eight GNSS stations in continuous operation in the study area. The subsidence rate trend show by the two methods is consistent, which further verifies the validity of InSAR data to reflect the local deformation. Experimental results shown that the eastern and northeastern Dianchi lake areas were affected by underground resources mining, and the induced surface subsidence characteristics were obvious, with the surface subsidence rate reachde 48 mm/year and 37 mm/year respectively. The Kunyang Phosphate Mine also had different degrees of mining subsidence disaster, with the maximum subsidence rate reached 36 mm/year. The subsidence rate of InSAR and GNSS has the same trend on the whole. However, GNSS sites are generally located in stable areas, the settlement amount obtained in the same time period is somewhat different from that of InSAR. [ABSTRACT FROM AUTHOR]

In this paper we update the knowledge on the species of Serica McLeay, 1819 (sensu lato) occurring in Yunnan, Sichuan, and Shaanxi provinces, China. Three new species are described: Serica allonanhua Liu, Ahrens, Li & Su, sp. nov., S. breviantennalis Liu, Ahrens, Li & Su, sp. nov., and S. fengensis Liu, Ahrens, Li & Su, sp. nov. The key to the species groups and species is updated. The habitus and male genitalia of the new species are illustrated, and a map showing their distribution is provided. New distributional data are given for four species. [ABSTRACT FROM AUTHOR]

Background: Scutellaria amoena (SA) is the root of S. amoena C.H. Wright of Labiatae, also known as Scutellaria southwestern. This is mainly distributed in Sichuan, Yunnan, and Guizhou in China. In southwest China, SA is used as an alternative method to genuine medicine for the treatment of allergy, diarrhea, inflammation, hepatitis, and bronchitis. Thus far, studies on the effects of SA on non-alcoholic steatohepatitis (NASH) are lacking. This paper investigated the effect of SA on the regulation of gut microbiota and its metabolites in NASH rats by inhibiting the NOD-like receptor 3 (NLRP3)/apoptosis-associated specklike protein (ASC)/caspase-1 axis. Methods: A NASH rat model was induced by a high-fat diet (HFD) for 12 weeks, and rats were orally given different doses of SA extracts (150 and 300 mg/kg/d) for 6 weeks. Changes in histological parameters, body weight, organ indexes, cytokines, and biochemical parameters related to NLRP3 in NASH rats were checked. 16S rRNA gene sequencing and UPLC-MS/MS technology were used to analyze the changes in the gut microbiota composition and its metabolites in NASH rats. Results: SA significantly inhibited the HFD-induced increase in body weight, lipid levels, and inflammatory infiltration. SA notably inhibited the HFD-induced increase in the upper and lower factors of NLRP3, such as transforming growth factor (TGF)-β, tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-18, pro-IL-18, IL-1β, pro-IL-1β, NLRP3, ASC, and caspase-1. Additionally, mRNA expressions of caspase-1, NLRP3, and ASC were significantly downregulated after SA treatment. The results of the intestinal flora showed that SA could increase the diversity of flora and change its structure and composition in NASH rats by reducing Firmicutes/Bacteroidetes (F/B) ratio, Blautia (genus), Lachospiraceae (family), and Christensenellaceae R-7 group (genus), and increasing Muribaculaceae (family) and Bacteroides (genus). The metabolomics revealed that 24 metabolites were possibly the key metabolites for SA to regulate the metabolic balance of NASH rats, including chenodeoxycholic acid, xanthine, and 9-OxoODE. Nine metabolic pathways were identified, including primary bile acid biosynthesis, bile secretion, purine metabolism, and secondary bile acid biosynthesis. Conclusion: SA can regulate the intestinal microbial balance and metabolic disorder by inhibiting the NLRP3/ASC/caspase-1 axis to relieve NASH. [ABSTRACT FROM AUTHOR]

Anthropogenic forcing caused the biodiversity loss and stability decline of communities. There is still controversy over whether the decline in biodiversity will lead to a decrease in community stability. The stability of biological communities is related to both biodiversity and structure, and this paper aims to reveal the human impacts on diatom communities' biodiversity and structure. We studied the richness, β‐diversity and network distance of diatom communities in Qinghai‐Xizang, Yunnan‐Sichuan and Lower Yangtze River Basin, China through empirical dataset and simulation method. The results showed that the diatoms richness in the Qinghai‐Xizang and the Yunnan‐Sichuan region was lower and the network distance was higher than that of the Lower Yangtze River Basin. β‐diversity in the Lower Yangtze River Basin was the lowest and the diatom network distance responds negatively to human population densities in China. The simulation showed that the network distance kept constant during random species loss, and declined while specialist species were lost or replaced by generalist species. The results suggested diatom communities' homogeneity and stability decline were associated with human activities. Human impacts may cause biodiversity loss targeted to specialist species or no biodiversity loss while generalist species replace those specialist species. This study showed that how diversity changes determined ecological stability depends on the type of species changes. [ABSTRACT FROM AUTHOR]

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Zhaotong City in Yunnan Province is one of the largest apple growing bases in China. However, the terrain of Zhaotong City is complicated, and the rainy weather is more frequent, which brings difficulties to the identification of apple orchards by remote sensing. In this paper, an improved spectral angle feature is proposed by combining the Spectral Angle Mapper and Sentinel-1 data. Based on the Google Earth Engine and Sentinel image, a random forest classifier was used to extract apple orchards in the Ganhe Reservoir area, Zhaoyang District, Zhaotong City, which provides a theoretical basis for extracting the spatial distribution and sustainable development of the local apple industry. The classification results show that the improved spectral angle characteristics can improve the overall accuracy and F1 score of apple orchards. The RGB band combined with NDVI, GLCM, and improved spectral angle features obtained the most favorable results, and the F1 score and overall accuracy were 88.89% and 84.44%, respectively, which proved the reliability of the method in identifying apple orchards in Zhaotong City. [ABSTRACT FROM AUTHOR]

In order to strengthen the improvement and optimization of eco-environment management in the Yangtze River Economic Belt, the paper studies the use of KPCA to build a judgment model of eco-environment management capacity, and analyzes the factors affecting the governance capacity in combination with the panel data regression model, so as to propose strategies for improving the governance capacity. The research outcomes indicate that from 2012 to 2021, the environmental and ecological governance capacity of the Yangtze River Economic Belt maintained an upward trend, and the governance capacity of the lower reaches was the best, with Shanghai, Jiangsu and Zhejiang ranking the top three, and Yunnan and Guizhou ranking the worst. The regression coefficients of industrial development, urbanization, economic development and opening to the outside world are − 3.4896, − 3.7891, 2.3489 and 0.1148 respectively. It is required to strengthen environmental and ecological governance from four aspects of industrial transformation, urban construction, green economy and open communication, and improve the eco-environment management capacity and level of the Yangtze River Economic Belt. [ABSTRACT FROM AUTHOR]

Based on various velocity fields from Global Positioning System (GPS) data over nearly 20 years in the Sichuan–Yunnan region, this paper calculated the strain rate field and its spatiotemporal characteristics by using an improved least squares collocation method. We evaluated the calculated strain field by extensively discussing the impact of non-tectonic factors on the calculation. Subsequently, we described the present-day strain rate features and their spatiotemporal variations. The results indicate the necessity of considering the influence of non-tectonic factors when calculating the strain rate field by using GPS velocity data. Widespread strain accumulation is observed in the Sichuan–Yunnan region, and significant second strain rate invariant with an average value of 33.1 nanostrain/yr primarily occurs along the eastern boundary faults of the Sichuan–Yunnan rhomboid block, specifically the Xianshuihe–Anninghe–Zemuhe–Xiaojiang fault systems. These fault systems also demarcate the zones with negative and positive dilation strain. According to the spatiotemporal variations of strain rate fields, the northern and southern segments of the Xianshuihe Fault, the Anninghe Fault and its eastern adjacent faults, and the Xiaojiang Fault are undergoing intensifying strain. Consequently, these zones should be paid more attention due to their relatively higher seismic risk in the Sichuan–Yunnan region. [ABSTRACT FROM AUTHOR]

Tectonic extrusion bypassing the eastern Himalayan syntaxis results in a significant increase in regional stress instability and the associated frequent occurrence of earthquakes in southern Yunnan, China. However, the stress field, and the relationship between the focal mechanism of earthquakes and stress evolution in southern Yunnan, remain enigmatic. In this paper, using a modified grid point test method, we calculated the focal mechanism of ML ≥ 2.5 earthquakes in southern Yunnan (22–25° N, 100–104° E) from January 2009 to June 2023. Utilizing the solutions of historical earthquake focal mechanisms, we obtained the present-day regional tectonic stress field in southern Yunnan via inversion. The results indicate complex and diverse seismic focal mechanisms, and the main types of earthquakes are strike-slip events, followed by normal fault and reverse fault events. The orientations of the maximum and minimum principal stress axes rotate in a clockwise direction from northeast to southwest. The internal stress orientation distribution of the rhombic Sichuan–Yunnan block in the study area is consistent, and the block boundary zone is the site where stress deflection occurs, and the regional tectonic stress field is influenced by the interaction among different blocks. The distribution of R-value in the Lamping–Simao block gradually increases from north to south, indicating that the compressive stress required for material transport becomes relatively small. Combined with the geological and tectonic background of the study area, our results suggest that the speed of block movement gradually decreases from north to south; the distribution of R-value in the South China block is significantly smaller than that of the interior of the Sichuan–Yunnan rhombus, and the proportion of compressive stresses is larger, indicating a stronger extrusion in this region, which may be related to the fact that the Sichuan–Yunnan rhombus is strongly resisted by the South China block in the east. [ABSTRACT FROM AUTHOR]

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The traditional classical sampling statistics method ignores the spatial location relationship of survey samples, which leads to many problems. This study aimed to propose a spatial sampling method for sampling estimation and optimization of forest biomass, achieving a more efficient and effective monitoring system. In this paper, we used Sequential Gaussian Conditional Simulation (SGCS) to obtain the biomass of four typical forest types in Shangri-La, Yunnan Province, China. In addition, we adopted a geostatistical sampling method for sample point layout and optimization to achieve the purpose of improving sampling efficiency and accuracy, and compared with the traditional sampling method. The main results showed that (1) the Gaussian model, exponential model, and spherical model were used to analyze the variogram of the four typical forests biomass, among which the exponential model had the best fitting effect (R2 = 0.571, RSS = 0.019). The range of the exponential model was 8700 m, and the nugget coefficient (C0/(C0 + C)) was 11.67%, which showed that the exponential model could be used to analyze the variogram of forest biomass. (2) The coefficient of variation (CV) based on 323 biomass field plots was 0.706, and the CV based on SGCS was 0.366. In addition, the Overall Estimate Consistency (OEC) of the simulation result was 0.871, which can be used for comparative analysis of traditional and spatial sampling. (3) Based on the result of SGCS, with 95% reliability, the sample size of traditional equidistant sampling (ES) was 191, and the sampling accuracy was 95.16%. But, the spatial sampling method based on the variation scale needed 92 samples, and the sampling accuracy was 93.12%. On the premise of satisfying sampling accuracy, spatial sampling efficiency was better than traditional ES. (4) The accuracy of stratified sampling (SS) of four typical forest areas based on 191 samples was 97.46%. However, the sampling accuracy of the biomass variance stratified space based on the SGCS was 93.89%, and the sample size was 52. Under the premise of satisfying the sampling accuracy, the sampling efficiency was obviously better than the traditional SS. Therefore, we can obtain the conclusion that the spatial sampling method is superior to the traditional sampling method, as it can reduce sampling costs and solve the problem of sample redundancy in traditional sampling, improving the sampling efficiency and accuracy, which can be used for sampling estimation of forest biomass. [ABSTRACT FROM AUTHOR]

Ecological science focuses on the structure and function of the natural environment. However, the study of ecological environments primarily focuses on single-element research and lacks a comprehensive perspective. To examine ecological environmental trends on different scales, the present paper selected Yunnan Province as the study area. Chemical oxygen demand, rocky desertification, forest coverage, natural disaster data and spatial analysis methods were used to obtain the ecological environmental characteristics of each county and construct a comprehensive evaluation method of the ecological environment. The present paper revealed that the environmental capacity in Yunnan Province was at a moderate level, the ecological environment fragility was remarkable, the significance of the ecological environment was very high, natural disasters occurred frequently, and spatial differentiation between ecological environments was obvious. The province may be divided into three functional areas: the comprehensive-balanced area, the efficiency-dominated area and the environment-dominated area. Central Yunnan was a key development zone and the main area for the manufacturing and service industries, which were built as a modern industrial system in Yunnan Province. The ecological environment in northwestern Yunnan and southern Yunnan is of high significance, and this region was an ecological environment protection area that was important area for the construction of the modern agricultural system in Yunnan Province. To achieve sustainable development of the ecological environment, the spatial characteristics of the ecological environment must be determined at the county scale. [ABSTRACT FROM AUTHOR]