Search Results (70,273)

Soil fertility is a critical factor in agricultural production, directly impacting crop growth, yield, and quality. To achieve precise agricultural management, accurate spatial interpolation of soil parameters is essential. This study developed a new interpolation prediction framework that combines Radial Basis Function (RBF) neural networks with Inverse Distance Weighting (IDW), termed the IDW-RBFNN. This framework initially uses the IDW method to apply preliminary weights based on distance to the data points, which are then used as input for the RBF neural network to form a training dataset. Subsequently, the RBF neural network further trains on these data to refine the interpolation results, achieving more precise spatial data interpolation. We compared the interpolation prediction accuracy of the IDW-RBFNN framework with ordinary Kriging (OK) and RBF methods under three different parameter settings. Ultimately, the IDW-RBFNN demonstrated lower error rates in terms of RMSE and MRE compared to direct RBF interpolation methods when adjusting settings based on different power values, even with a fixed number of data samples. As the sample size decreases, the interpolation accuracy of OK and RBF methods is significantly affected, while the error of IDW-RBFNN remains relatively low. Considering both interpolation accuracy and resource limitations, we recommend using the IDW-RBFNN method (p = 2) with at least 60 samples as the minimum sampling density to ensure high interpolation accuracy under resource constraints. Our method overcomes limitations of existing approaches that use fixed steady-state distance decay parameters, providing an effective tool for soil fertility monitoring in delta regions. Full article

Forest ecosystems, as the primary component of terrestrial ecosystems, provide essential ecosystem services (ESs) critical for sustainable human development. However, changes in climate and vegetation can alter these forest ESs. Understanding the complex relationships between regional climate, vegetation, and ESs is key to ensuring the sustainable management of forest ESs. Therefore, this study, using Baishanzu National Park as a case example, analyzed the impacts of regional climate and vegetation dynamics (vegetation coverage, forest type, and forest structure) on forest ESs, specifically water yield (WY), soil conservation (SC), net primary productivity (NPP), and habitat quality (HQ). The results indicate that from 2000 to 2020, the forest Composite Index of Ecosystem Services (CIES) in Baishanzu National Park increased. Climate and vegetation dynamics have significant effects on forest ESs. Specifically, changes in WY and SC are primarily influenced by climate change, while changes in NPP and HQ are mainly affected by changes in forest type and structure. Complex trade-offs and synergies exist among different ESs, and the driving mechanisms of climate and vegetation changes on ES variations are also complex, involving both direct and indirect effects, with significant spatial heterogeneity. This study provides important references for the sustainable management and appropriate restoration of regional forest ESs. Full article

In the rapid process of urbanization, revealing the patterns and driving forces behind the evolution of blue–green spaces holds significant value for optimizing urban blue–green environments. This study systematically investigates the spatial–temporal evolution characteristics and driving forces of blue–green space in the Chengdu–Chongqing Economic Circle from 1990 to 2020, utilizing GIS technology, landscape pattern analysis, and geographic detectors. The research findings indicate the following: (1) The area of blue–green space in the study area exhibits a general trend of initial growth followed by decline, with significant changes occurring between 2010 and 2020. (2) The fragmentation degree of blue–green space is gradually increasing, while connectivity among landscapes is decreasing; however, there has been an increase in landscape distribution uniformity. More than 90% of blue–green spaces expanded mainly through adjacency patterns. (3) In examining driving forces, it was found that temperature, topographic relief, elevation, population density, and construction intensity are the primary driving factors. Notably, the influence of natural factors has diminished over time while human social factors have significantly intensified. This study offers solutions for optimizing the configuration of blue–green spaces within the Chengdu–Chongqing Economic Circle. It also serves as a reference case for promoting high-quality urbanization in developing countries undergoing rapid urbanization. Full article

Background: Recent advancements in dental implantology have significantly improved outcomes, with success rates of 90–95% over a 10-year period. Key improvements include enhanced preplanning processes, such as precise implant positioning, model selection, and optimal insertion depth. However, challenges remain, particularly in achieving correct spatial positioning and alignment of implants for optimal occlusion. These challenges are pronounced in patients with reduced bone substance or complex anthropometric features, where even minor misalignments can result in complications or defects. Methods: This paper introduces a vision-guided robotic system designed to improve spatial positioning accuracy during dental implant surgery. The system incorporates advanced force-feedback control to regulate the pressure applied to bone, minimizing the risk of bone damage. A preoperative CBCT scan, combined with real-time images from a robot-mounted camera, guides implant positioning. A personalized marker holder guide, developed from the initial CBCT scan, is used for patient–robot calibration. The robot-mounted camera provides continuous visual feedback of the oral cavity during surgery, enabling precise registration of the patient with the robotic system. Results: Initial experiments were conducted on a 3D-printed mandible using a personalized marker holder. Following successful patient–robot registration, the robotic system autonomously performed implant drilling. To evaluate the accuracy of the robotic-assisted procedure, further tests were conducted on 40 identical molds, followed by measurements of implant positioning. The results demonstrated improved positioning accuracy compared to the manual procedure. Conclusions: The vision-guided robotic system significantly enhances the spatial accuracy of dental implants compared to traditional manual methods. By integrating advanced force-feedback control and real-time visual guidance, the system addresses key challenges in implant positioning, particularly for patients with complex anatomical structures. These findings suggest that robotic-assisted implant surgery could offer a safer and more precise alternative to manual procedures, reducing the risk of implant misalignment and associated complications. Full article

Urbanization has significantly altered urban landscape patterns, leading to a continuous reduction in the proportion of green spaces. As critical carbon sinks in urban carbon cycles, urban green spaces play an indispensable role in mitigating climate change. This study aims to evaluate the carbon capture and storage potential of urban green spaces in Luohe, China, and identify the landscape factors influencing carbon sequestration. The research combines on-site data collection with high-resolution remote sensing, utilizing the i-Tree Eco model to estimate carbon sequestration rates across areas with varying levels of greenery. The study reveals that the carbon sequestration capacity of urban green spaces in Luohe City is 1.30 t·C·ha⁻¹·yr⁻¹. Among various vegetation indices, the Enhanced Vegetation Index (EVI) explains urban green space carbon sequestration most effectively through an exponential model (R² = 0.65, AIC = 136.5). At the city-wide scale, areas with higher greening rates, better connectivity, and more complex edge morphology exhibit superior carbon sequestration efficiency. The explanatory power of key landscape indices on carbon sequestration is 78% across the study area, with variations of 71.5%, 62%, and 84.9% for low, medium, and high greening rate areas, respectively. Moreover, when greening rates reach a certain threshold, maintaining and optimizing the quality of existing green spaces becomes more critical than simply expanding the green area. These insights provide valuable guidance for urban planners and policymakers on enhancing the ecological functions of urban green spaces during urban development. Full article

Accurate high-resolution soil moisture maps are crucial for a better understanding of hydrological processes and energy cycles. Mapping strategies such as downscaling and interpolation have been developed to obtain high-resolution soil moisture maps from multi-source inputs. However, research on the optimization performance of integrating downscaling and interpolation, especially through the use of mutual covariates, remains unclear. In this study, we compared four methods—two standalone methods based on downscaling and interpolation strategies and two combined methods that utilize soil moisture maps as mutual covariates within each strategy—in a case study of daily soil moisture mapping at a 1 km resolution in the Tibetan Plateau. We assessed mapping performance in terms of prediction accuracy and differences in spatial coverage. The results indicated that introducing interpolated soil moisture maps into the downscaling strategy significantly improved prediction accuracy (RMSE: −5.94%, correlation coefficient: +14.02%) but was limited to localized spatial coverage (6.9% of grid cells) near in situ sites. Conversely, integrating downscaled soil moisture maps into the interpolation strategy resulted in only modest gains in prediction accuracy (RMSE: −1.07%, correlation coefficient: +1.04%), yet facilitated broader spatial coverage (40.4% of grid cells). This study highlights the critical differences between downscaling and interpolation strategies in terms of accuracy improvement and spatial coverage, providing a reference for optimizing soil moisture mapping over large areas. Full article

At present, the extraction of irrigation canal network distribution information is of great significance for developing a digital twin irrigation district. However, due to the low resolution of remote sensing images, it is difficult to effectively identify the canal networks, especially for channels with a width of less than 1 m, where recognition is insufficient. Therefore, the purpose of this study is to extract canal networks of different widths in an irrigation district in Shaanxi Province as the research area. A rule-based object-oriented classification method was employed, utilizing image data collected by the DJI Mavic 3 multispectral UAV (Unmanned Aerial Vehicle) to explore the accuracy of this method in extracting canal distribution information. Based on UAV multispectral remote sensing imagery, the segmentation parameters for the remote sensing imagery were determined using ENVI 5.6 software, with the segmentation threshold set at 60 and the merging threshold set at 80. By combining the spectral and spatial differences between the canals and other ground objects, rules for extracting canal network distribution information were established, and the information on the distribution of channels in this irrigation area was finally obtained. The experimental results showed a maximum recall rate of 91.88% and a maximum precision rate of 57.59%. The overall recall precision rates for the irrigation district were 85.74% and 55.08%, respectively. This method provides a new solution for identifying and extracting canal systems in irrigation districts, offering valuable insights for acquiring canal distribution information and providing a scientific basis for precision irrigation. Full article

Agricultural green development is crucial for achieving the United Nations 2030 Sustainable Development Goals, with the digital technology revolution acting as a catalyst for both China’s green agricultural transformation and global sustainable development efforts. This study utilizes panel data from 30 Chinese provinces (including autonomous regions and municipalities) from 2012 to 2022 to assess the digitalization level and agricultural green development through a combined entropy weight and TOPSIS method. It also investigates the spatial agglomeration of agricultural green development using Moran’s I index and empirically evaluates the impact of digitalization on agricultural green development through OLS and spatial Durbin models. The findings reveal that, while China’s agricultural green development has progressed slowly yet steadily during the study period, it demonstrates significant spatial agglomeration, driven primarily by agricultural production efficiency and resource recycling. Notably, a non-linear U-shaped relationship exists between digitalization and agricultural green development, suggesting that digitalization fosters agricultural green development only after surpassing a certain threshold. Additionally, digitalization has spatial spillover effects: advancements in neighboring provinces correlate with local agricultural green development in a U-shaped manner, with an initial “siphon effect” followed by a “trickle-down effect.” These insights inform policy recommendations aimed at optimizing the use of digital technology to facilitate green agricultural transformation, offering valuable guidance for policymakers. Full article

The bi- or multinucleated Reed–Sternberg cell (RS) is the diagnostic cornerstone of Epstein–Barr Virus (EBV)-positive and EBV-negative classical Hodgkin lymphoma (cHL). cHL is a germinal center (GC)-derived B-cell disease. Hodgkin cells (H) are the mononuclear precursors of RS. An experimental model has to fulfill three conditions to qualify as common pathogenic denominator: (i) to be of GC-derived B-cell origin, (ii) to be EBV-negative to avoid EBV latency III expression and (iii) to support permanent EBV-encoded oncogenic latent membrane protein (LMP1) expression upon induction. These conditions are unified in the EBV-, diffuse large B-Cell lymphoma (DLBCL) cell line BJAB-tTA-LMP1. 3D reconstructive nanotechnology revealed spatial, quantitative and qualitative disturbance of telomere/shelterin interactions in mononuclear H-like cells, with further progression during transition to RS-like cells, including progressive complexity of the karyotype with every mitotic cycle, due to BBF (breakage/bridge/fusion) events. The findings of this model were confirmed in diagnostic patient samples and correlate with clinical outcomes. Moreover, in vitro, significant disturbance of the lamin AC/telomere interaction progressively occurred. In summary, our research over the past three decades identified cHL as the first lymphoid malignancy driven by a disturbed telomere/shelterin/lamin AC interaction, generating the diagnostic RS. Our findings may act as trailblazer for tailored therapies in refractory cHL. Full article

Major function-oriented zoning, a key spatial planning strategy in China, aims to coordinate resource endowments, socio-economic development, and subsequent planning initiatives. However, the existing framework for major function-oriented zoning relies predominantly on socio-economic statistical indicators at the regional level, often neglecting the critical role of carrying capacity. To address this limitation, we assessed both the current state and dynamic trends of the carrying capacity to identify risk and advantageous zones for major functions, with the objective of optimizing major function-oriented zoning in the Yangtze River Delta region, China. Our findings indicate that 47 counties are experiencing significant pressure under the current carrying capacity, while 57 counties exhibit a deteriorating trend in their capacity. Over half of the counties are categorized as having an overloaded carrying capacity. Based on this analysis, 66 counties have been designated as risk zones for major functions. Consequently, the optimization of major function-oriented zoning requires adjustments in 10 counties, incorporating the identified risk and advantageous zones to enhance spatial planning efficacy. This study proposes an enhanced methodological framework for major function-oriented zoning by fully integrating carrying capacity assessments, offering substantial support for territorial spatial planning in China. We believe that these improvements contribute significantly to more resilient and sustainable regional development strategies. Full article

Ecological suitability evaluation is a critical component of regional sustainable development and construction, serving as a foundation for optimizing spatial patterns of regional growth. This is particularly pertinent in karst mountainous regions characterized by limited land resources and heightened ecosystem vulnerability, where a quantitative assessment of ecological suitability for land development is both crucial and urgent. Based on the fundamental principles of structural and functional dynamics in landscape ecology, this study focuses on Gui’an New Area, a designated urban development zone situated in the karst landscape of Guizhou Province. An index system was established encompassing three dimensions: ecological elements, ecological significance, and ecological resilience, utilizing the integrated ecological resistance (IER) model to evaluate the suitability of regional development and construction. The results reveal that the eastern region exhibits higher suitability compared to the central and western regions, with the northwest region demonstrating the lowest suitability overall. Relatively speaking, the evaluation of geological environment suitability and the comprehensive ecological constraints associated with development and construction indicates that the areas currently planned and ongoing reflect flat terrain and low ecological risk. Furthermore, within the scope of ecosystem dynamic adaptation, developmental activities in these regions exert minimal impact on the natural ecosystem, thereby demonstrating a high suitability for development and construction. In terms of future key development zones, areas with gentle slopes ranging from 8 to 15 degrees are recommended, aligning with the actual requirements for cultivated land protection. The total area designated as prohibited development zones constitutes the smallest proportion, representing only 9.45%, which is significantly lower than that of priority development zones (38.75%) and moderate development zones (22.45%). From the perspective of landscape ecology, this paper provides a comprehensive investigation into the ecological suitability evaluation system for development and construction in the karst regions of Southwest China, offering valuable insights for assessing ecological suitability in similar areas. Full article

Water system connectivity is an important measure to optimize the balanced spatial allocation of water resources and water security patterns. Inland river basins in arid zones are generally insufficiently connected, so the scientific evaluation of the current status of water system connectivity and the centrality of its nodes in the water system network has practical significance for the scientific construction of regional water networks. Taking the Tarim River Basin in Xinjiang, China, as an object, this study conducted a comprehensive evaluation of basin water system connectivity by constructing a water system connectivity evaluation system with a total of 12 indicators for the three aspects of pattern connectivity, structural connectivity and functional connectivity. Subsequently, the TOPSIS model, with combined weights of the analytic hierarchy process and the entropy weight method, was used to comprehensively evaluate the connectivity of the watershed’s water system. The research evaluated the node centrality of the water system network that was closely related to the basin water system connectivity by using complex network analyses. The study results indicated the following: (1) among the source streams in the Tarim River Basin, the connectivity of the Aksu Basin was the best and that of the Keriya Basin was the worst and (2) the distribution patterns of the eigenvector centrality and betweenness centrality of the basin hydrological network nodes were similar, with nodes of highest centrality concentrated in the vicinity of the mainstems and the source–mainstem intersections. This work provides a basis and reference for the construction of water system connectivity and the selection of key control sections for ecological flow in the Tarim River Basin. Full article

The gut microbiota is a complex ecosystem that influences digestion, immune response, metabolism, and has been linked to health and well-being. Choline is essential for neurotransmitters, lipid transport, cell-membrane signaling, methyl-group metabolism and is believed to have neuroprotective properties. It is found in two forms, water-soluble and lipid-soluble, and its metabolism is different. Long-term choline deficiency is associated with many diseases, and supplements are prescribed for improved health. Choline supplements can improve cognitive function in adults but not significantly. Choline is a precursor of phospholipids and an acetylcholine neurotransmitter precursor and can be generated de novo from phosphatidylcholine via phosphatidylethanolamine-N-methyltransferase and choline oxidase. Choline supplementation has been found to have a beneficial effect on patients with neurodegenerative diseases, such as Alzheimer’s disease (AD), by increasing amyloid-β, thioflavin S, and tau hyper-phosphorylation. Choline supplementation has been shown to reduce amyloid-plaque load and develop spatial memory in an APP/PS1 mice model of AD. Choline is necessary for normative and improved function of brain pathways and can reduce amyloid-β deposition and microgliosis. Clinical research suggests that early neurodegenerative diseases (NDs) can benefit from a combination of choline supplements and the drugs currently used to treat NDs in order to improve memory performance and synaptic functioning. Full article

Infrared multi-band small and dim target detection is an important research direction in the fields of modern remote sensing and military surveillance. However, achieving high-precision detection remains challenging due to the small scale, low contrast of small and dim targets, and their susceptibility to complex background interference. This paper innovatively proposes a dual-band infrared small and dim target detection method (MM-IRSTD). In this framework, we integrate a convolutional self-attention mechanism module and a self-distillation mechanism to achieve end-to-end dual-band infrared small and dim target detection. The Conv-Based Self-Attention module consists of a convolutional self-attention mechanism and a multilayer perceptron, effectively extracting and integrating input features, thereby enhancing the performance and expressive capability of the model. Additionally, this module incorporates a dynamic weight mechanism to achieve adaptive feature fusion, significantly reducing computational complexity and enhancing the model’s global perception capability. During model training, we use a spatial and channel similarity self-distillation mechanism to drive model updates, addressing the similarity discrepancy between long-wave and mid-wave image features extracted through deep learning, thus improving the model’s performance and generalization capability. Furthermore, to better learn and detect edge features in images, this paper designs an edge extraction method based on Sobel. Finally, comparative experiments and ablation studies validate the advancement and effectiveness of our proposed method. Full article

Ecological environmental protection and poverty alleviation are of great significance for the study of human–land relationship coordination and sustainable development, and they have also been a focus of attention in China in the past few decades. In this study, we chose 13 contiguous poverty-stricken areas in China as the study area. Using MODIS Leaf Area Index (LAI) data from 2000 to 2020, the spatial–temporal changes in greenness were obtained using the Bayesian spatial–temporal model (BYM). Spatial autocorrelation was used to identify the spatial distribution of poverty using socio-economic statistical data. Driving factors, including natural factors, poverty factors, and the Grain for Green Policy (GTGP), and their influence on greenness were analyzed by using the Geodetector model for detecting spatial differentiation and factors’ interactions. The results showed the following: (1) In 13 contiguous poverty-stricken areas (CPSAs) in China, 59% of the area presented an increasing trend of greenness. (2) In 2000, the high poverty levels with larger MPI values were widely distributed. After 20 years, the overall MPI value was lower, except in some northwest regions with increased MPI values. The spatial autocorrelation of poverty, which relates to the mutual influence of poverty in adjacent areas, also decreased. (3) In the study area, 65.24% of the regions showed strong synergistic effect between greening progress and poverty reduction in the interaction between poverty status and green development. With the improvement of greenness level, the positive correlation between poverty alleviation and ecological environment improvement has become increasingly close. (4) The impacts of interaction factors with the highest q values changed from temperature interacting with precision to regional division interacting with the Grain for Green Policy. The conclusions are that from 2000 to 2020, the impact of natural factors, geographical division, and poverty status on greenness has shown a decreasing trend; The effect of the Grain for Green Policy is gradually increasing; At the same time, the interaction and overlapping effects between the Grain for Green Policy and poverty were increasing. Taking into account the needs of ecological environment, poverty alleviation, and rural revitalization, this research provides valuable reference for formulating and implementing relevant policies based on the actual situation in different regions to promote harmonious coexistence between human-land relationship. Full article