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Understanding the decision-making mechanisms of stakeholders in land use changes within wetland areas is critical for managing land resources effectively and mitigating conflicts. This study applies a game-theoretic approach to examine the strategic interactions among key stakeholders—managers, developers, and residents—within the Caohai National Nature Reserve (CNNR) in China. By integrating real data on land use changes, ecological quality indices, and economic incentives, this study identifies the driving forces behind stakeholder behavior and land use evolution from 2000 to 2020. The land use changes and ecological effects in the CNNR can be divided into two main stages: From 2000 to 2010, the primary direction of land use change was the conversion of grassland into construction land and farmland, resulting in the deterioration of ecological environment quality. From 2010 to 2020, the main direction of land use change shifted to the conversion of farmland into grassland and forest land, leading to an improvement in ecological environment quality. Game-theoretic analysis demonstrates that managers play a decisive role in shaping stakeholder strategies through regulatory mechanisms, such as land rent adjustments, penalties, subsidies, and ecological compensation. Stronger enforcement of penalties and incentives significantly enhances cooperative behavior among stakeholders, reducing land use conflicts and promoting ecological recovery. These findings emphasize the necessity of targeted governance strategies to align stakeholder interests and balance ecological conservation with socio-economic development. The insights from this study provide valuable guidance for policymakers and land managers in designing effective land use policies and improving conservation efforts in wetland-protected areas.

Water-related problems are mostly caused by water imbalances between supply and demand. This study adopts the ecological footprint method to conduct an empirical study on the sustainable utilization of water resources in Japan. According to the basic principles and calculation methods of water ecological footprint (WEF), the characteristics of Japan’s water ecological footprint were investigated from the time and space dimensions, and a comparative analysis was made with the water ecological footprint of China. The results show that: from 1980 to 2020, the total water ecological footprint in Japan showed a downward trend in both the traditional account and pollutant account, and its spatial pattern was characterized by the relation that the higher the urbanization rate, the larger the water ecological footprint. In terms of water ecological footprint efficiency, Japan’s agricultural water ecological footprint efficiency was the lowest, and the domestic water ecological footprint efficiency was the highest. The water resources policies and measures that Japan and other developing countries should take to ensure the sustainability of water resources were analyzed separately.

There is a close link between water resources and economic development. To understand the relationship between water resources and economic development in Qian’nan, Guizhou, the study utilized the water resources ecological footprint and decoupling model to analyze the relationship between water resource ecological footprint and economic growth in the region. Data from 2009 to 2019 were collected and analyzed to understand the trends and patterns. The results indicate that from 2009 to 2019, the ecological footprint of water resources in Qian’nan remained less than the ecological carrying capacity, indicating a surplus of water resources and low ecological pressure. However, the water resources ecological footprint gradually increased over the study period. Furthermore, the ecological footprint of water resources was found to be higher in the northern areas compared to the southern regions. Additionally, areas with higher economic levels exhibited larger ecological footprints of water resources, while areas with lower economic levels had smaller ecological footprints. Although some counties (cities) showed an increasingly severe relationship between water resource ecological footprint and economic growth, overall, most counties (cities) demonstrated a weak decoupling state, suggesting that economic development is not significantly constrained by water resources. The findings suggest that Qian’nan, Guizhou, has experienced a surplus of water resources with low ecological pressure over the past decade. However, the increasing water resources ecological footprint warrants attention to ensure sustainable management. The spatial disparities in the ecological footprint of water resources highlight the need for targeted interventions in different regions. Additionally, the weak decoupling state between water resources ecological footprint and economic growth indicates the potential for further economic development without significant constraints from water resources. However, proactive measures should be implemented to maintain this balance and promote sustainable development in the region.

In this study, the large eddy simulation method and the actuator line model are used to investigate the wake redirection of two turbines. Different turbine spacings and yaw-based control of the upstream turbine are considered. The effects of yaw angle and turbine spacing on the output power of two turbines are comprehensively analyzed, and the physical mechanisms of the wake deficit, deflection and interaction are revealed from the distributions of the wake velocity, turbulence intensity and the structures of wake vortices. The results show that the overall power of two turbines is related to the yaw angle of the upstream turbine and the spacing between two turbines. We find yaw angle is the dominant factor in the total power improvement compared to turbine spacing. Still, a large yaw angle causes significant power fluctuations of the downstream turbine. The deficit of wake velocity and the change of output power are determined by the characteristics of the wake flow field, which the yaw control regulates.

Background: Targetable drug delivery is an important method for the treatment of liver tumors. For the quantitative analysis of drug diffusion, the establishment of a method for information collection and characterization of extracellular space is developed by imaging analysis of magnetic resonance imaging (MRI) sequences. In this paper, we smoothed out interferential part in scanned digital MRI images. Materials and Methods: Making full use of priors of low rank, nonlocal self-similarity, and regularized sparsity-promoting entropy, a block-matching regularized entropy minimization algorithm is proposed. Sparsity-promoting entropy function produces much sparser representation of grouped nonlocal similar blocks of image by solving a nonconvex minimization problem. Moreover, an alternating direction method of multipliers algorithm is proposed to iteratively solve the problem above. Results and Conclusions: Experiments on simulated and real images reveal that the proposed method obtains better image restorations compared with some state-of-the-art methods, where most information is recovered and few artifacts are produced.

Digital image inpainting is an interpolation problem, inferring the content in the missing (unknown) region to agree with the known region data such that the interpolated result fulfills some prior knowledge. Low-rank and nonlocal self-similarity are two important priors for image inpainting. Based on the nonlocal self-similarity assumption, an image is divided into overlapped square target patches (submatrices) and the similar patches of any target patch are reshaped as vectors and stacked into a patch matrix. Such a patch matrix usually enjoys a property of low rank or approximately low rank, and its missing entries are recoveried by low-rank matrix approximation (LRMA) algorithms. Traditionally, \\(n\\) nearest neighbor similar patches are searched within a local window centered at a target patch. However, for an image with missing lines, the generated patch matrix is prone to having entirely-missing rows such that the downstream low-rank model fails to reconstruct it well. To address this problem, we propose a region-wise matching (RwM) algorithm by dividing the neighborhood of a target patch into multiple subregions and then search the most similar one within each subregion. A non-convex weighted low-rank decomposition (NC-WLRD) model for LRMA is also proposed to reconstruct all degraded patch matrices grouped by the proposed RwM algorithm. We solve the proposed NC-WLRD model by the alternating direction method of multipliers (ADMM) and analyze the convergence in detail. Numerous experiments on line inpainting (entire-row/column missing) demonstrate the superiority of our method over other competitive inpainting algorithms. Unlike other low-rank-based matrix completion methods and inpainting algorithms, the proposed model NC-WLRD is also effective for removing random-valued impulse noise and structural noise (stripes).

Hepatic echinococcosis (HE) is a life-threatening liver disease caused by parasites that requires a precise diagnosis and proper treatments. To assess HE lesions accurately, we propose a novel automatic HE lesion segmentation and classification network that contains lesion region positioning (LRP) and lesion region segmenting (LRS) modules. First, we used the LRP module to obtain the probability map of the lesion distribution and the position of the lesion. Then, based on the result of the LRP module, we used the LRS module to precisely segment the HE lesions within the high-probability region. Finally, we classified the HE lesions and identified the lesion types by a convolutional neural network (CNN). The entire dataset was delineated by the hospital’s senior radiologist. We collected CT slices of 160 patients from Qinghai Provincial People’s Hospital. The Dice score of the final segmentation result reached 89.89%. The Dice scores, indicating the classification accuracy, for cystic vs. alveolar echinococcosis and calcified vs. noncalcified lesions were 80.32% and 82.45%, the sensitivities were 72.41% and 75.17%, the specificities were 83.72% and 86.04%, the NPVs were 80.01% and 86.96%, the PPVs were 80.45% and 81.74%, and the areas under the ROC curves were 0.8128 and 0.8205, respectively.

To rebuild the three-dimensional (3-D) model of the anterior segment by high-speed swept-source optical coherence tomography (SSOCT) and evaluate the repeatability of measurement for the parameters of capsule-intraocular lens (C-IOL) complex. Twenty-two pseudophakic eyes from 22 patients were enrolled. Three continuous SSOCT measurements were performed in all eyes and the tomograms obtained were used for 3-D reconstruction. The output data were used to evaluate the measurement repeatability. The parameters included postoperative aqueous depth (PAD), the area and diameter of the anterior capsule opening (Area and D), IOL tilt (IOL-T), horizontal, vertical, and space decentration of the IOL, anterior capsule opening, and IOL-anterior capsule opening. PAD, IOL-T, Area, D, and all decentration measurements showed high repeatability. Repeated measure analysis showed there was no statistically significant difference among the three continuous measurements (all P > .05). Pearson correlation analysis showed high correlation between each pair of them (all r >0.90, P<0.001). ICCs were all more than 0.9 for all parameters. The 95% LoAs of all parameters were narrow for comparison of three measurements, which showed high repeatability for three measurements. SSOCT is available to be a new method for the 3-D measurement of C-IOL complex after cataract surgery. This method presented high repeatability in measuring the parameters of the C-IOL complex.

Multi-axle autonomous mobile robots (AMRs) are set to revolutionize the future of robotics in logistics. As the backbone of next-generation solutions, these robots face a critical challenge: managing and minimizing the swept volume during turns while maintaining precise control. Traditional systems designed for standard vehicles often struggle with the complex dynamics of multi-axle configurations, leading to inefficiency and increased safety risk in confined spaces. Our innovative framework overcomes these limitations by combining swept volume minimization with Signed Distance Field (SDF) path planning and model predictive control (MPC) for independent wheel steering. This approach not only plans paths with an awareness of the swept volume but actively minimizes it in real-time, allowing each axle to follow a precise trajectory while significantly reducing the space the vehicle occupies. By predicting future states and adjusting the turning radius of each wheel, our method enhances both maneuverability and safety, even in the most constrained environments. Unlike previous works, our solution goes beyond basic path calculation and tracking, offering real-time path optimization with minimal swept volume and efficient individual axle control. To our knowledge, this is the first comprehensive approach to tackle these challenges, delivering life-saving improvements in control, efficiency, and safety for multi-axle AMRs. Furthermore, we will open-source our work to foster collaboration and enable others to advance safer, more efficient autonomous systems.