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Wetlands, as a crucial component of urban green spaces, provide important leisure services for residents. Construction of wetlands has increased with the rapid urban expansion and population growth in China over recent decades, especially in semi-arid regions with scarce water resources. However, the residents’ satisfaction with wetland leisure demand remains unclear. This study evaluated the residents’ satisfaction with wetland leisure demand by a framework of physical calculation, taking Yinchuan City, the capital city of Ningxia Hui Autonomous Region, in the semi-arid region of Western China as a case study area. Spatial variations in residents’ satisfaction and their causes were revealed by a supply–demand relationship between the population capacity of wetlands and the total population of communities under a framework of physical calculation. The results indicated that 4.22% of the study area, which covered 7.38% of the total population, was fully satisfied with wetland leisure demand. Residents’ satisfaction in the urban area as a whole is low at 0.49, with a concentric distribution pattern increasing as the distance from the central urban area increases. The high population density and scanty wetlands mainly induced a relative-low residents’ satisfaction in the central urban area, accounting for 12.02% of the area and 32.70% of the population. Meanwhile, a relative-high residents’ satisfaction in the outer ring of the central urban area accounting for 59.10% of the area and 20.63% of the population was primarily due to the adequate capacity of wetlands. Medium residents’ satisfaction was mainly attributed to the road network density, which partially transferred local wetland leisure demand to adjacent areas. Wetland constructions and internal structural optimization to improve the capacity for leisure in densely populated central urban areas could provide a feasible path to alleviate unbalanced conditions. These results could deepen the understanding of supply–demand dynamics in the wetland leisure service and provide valuable information for optimizing wetland allocation in urban construction in semi-arid regions.

The Lower Paleozoic of the Awati Sag and its periphery is a region with relatively low levels of exploration and stands as a frontier for ultra-deep hydrocarbon exploration. Based on outcrop and core samples, this study integrated organic geochemical analysis, total organic carbon (TOC) logging interpretation, and one-dimensional and two-dimensional hydrocarbon accumulation simulations, to clarify the primary source rock of the Lower Paleozoic and its characteristics, as well as its hydrocarbon accumulation mode. The findings indicate the following: (1) The Lower Paleozoic features two sets of industrial source rocks. The Yuertusi Formation, with its considerable thickness (approximately 200 m), widespread distribution, and elevated TOC (averaging approximately 5% from experimental data and logging interpretation), stands out as the Lower Paleozoic’s most pivotal source rock. (2) The Yuertusi and Saergan Formations are in a high-to-over-mature stage, with the Yuertusi initiating oil generation in the early Silurian and transitioning to gas by the late Permian. The Saergan began producing oil in the Carboniferous, followed by gas in the late Permian. (3) The potential ultra-deep gas reservoirs in the Awati Sag are mainly distributed in the structural traps closer to the deep faults in five potential target formations. Deep natural gas typically exhibits mixed-source signatures, with the mixing notably pronounced along the Shajingzi Fault Belt due to influential basin-controlling faults.

The biogeography-based optimization (BBO) algorithm is known for its simplicity and low computational overhead, but it often struggles with falling into local optima and slow convergence speed. Against this background, this work presents a multi-strategy enhanced BBO variant, named MSBBO. Firstly, the example chasing strategy is proposed to eliminate the destruction of the inferior solutions to superior solutions. Secondly, the heuristic crossover strategy is designed to enhance the search ability of the population. Finally, the prey search–attack strategy is used to balance the exploration and exploitation. To verify the performance of MSBBO, we compare it with standard BBO, seven BBO variants (PRBBO, BBOSB, HGBBO, FABBO, BLEHO, MPBBO and BBOIMAM) and seven meta-heuristic algorithms (GWO, WOA, SSA, ChOA, MPA, GJO and BWO) on multiple dimensions of 24 benchmark functions. It concludes that MSBBO significantly outperforms all competitors both on convergence accuracy, speed and stability, and MSBBO basically converges to the same results on 10,000 dimensions as on 1000 dimensions. Further, MSBBO is applied to six real-world engineering design problems. The experimental results show that our work is still more competitive than other latest optimization techniques (COA, EDO, OMA, SHO and SCSO) on constrained optimization problems.

This paper presents an anti-swing control method to prevent situations where inspection robots detach and fall off transmission lines during obstacle crossing due to excessive swing angles caused by the rotation of the robot around the transmission line. Firstly, an obstacle-crossing model for the inspection robot was constructed and the causes of robot swinging phenomena were analyzed, in addition to their impact on obstacle crossing stability. By combining this with the obstacle-crossing model, a moment balance equation was established for the inspection robot. This equation can be used to solve mapping relationships between body offset and the tilt angle of transmission line gripping arms. We propose an anti-swing control strategy by adjusting the angle of the transmission line gripping arm’s pitching joint to make the body offset approach zero, and by utilizing the advantages of fuzzy logic in the fuzzy PID algorithm compared with the traditional PID algorithm, it can adaptively avoid the occurrence of robot swinging phenomena. The experimental results of obstacle-crossing experiments under no wind and wind turbulence conditions indicated that the proposed anti-swing control method in this study can effectively keep the body offset to within 3 mm. Compared with the methods of not using anti-swing control and using traditional PID anti-swing control, in the absence of wind effects, the peak values of body offset were reduced by 96.53% and 18.85%, respectively. Under the influence of wind turbulence, the peak values of body offset were reduced by 97.02% and 27.12%, respectively. The effectiveness of the anti-swing control method proposed in this paper has thus been verified.

When a remote sensing camera work in push-broom mode, the obtained image usually contains significant stripe noise and random noise due to differences in detector response and environmental factors. Traditional approaches typically treat them as two independent problems and process the image sequentially, which not only increases the risk of information loss and structural damage, but also faces the situation of noise mutual influence. To overcome the drawbacks of traditional methods, this paper leverages the double low-rank characteristics in the underlying prior of degraded images and presents a novel approach for addressing both destriping and denoising tasks simultaneously. We utilize the commonality that both can be treated as inverse problems and place them in the same optimization framework, while designing an alternating direction method of multipliers (ADMM) strategy for solving them, achieving the synchronous removal of both stripe noise and random noise. Compared with traditional approaches, synchronous denoising technology can more accurately evaluate the distribution characteristics of noise, better utilize the original information of the image, and achieve better destriping and denoising results. To assess the efficacy of the proposed algorithm, extensive simulations and experiments were conducted in this paper. The results show that compared with state-of-the-art algorithms, the proposed method can more effectively suppress random noise, achieve better synchronous denoising results, and it exhibits a stronger robustness.

Most scholars believe that transgression events can contribute positively to organic matter enrichment and shale gas sweet spot development, while whether or not regression events are conducive to shale gas sweet spot development remains to be further discussed. Variations in organic carbon content (TOC), and major and trace elements at the Rhuddanian–Aeronian stage in the Luzhou area, the southern margin of Sichuan Basin, were analyzed in this paper. We discuss differences in paleoenvironment organic matter enrichment and shale sweet spot development during transgression and regression. A transgressive system tract (TST) occurred during the early Rhuddanian stage, while early highstand system tracts (Ehst-1 and Ehst-2) occurred during the late Rhuddanian stage and Aeronian stage, and a late highstand system tract (LHST) developed during the late Aeronian stage. A rise in sea level during the TST in the upper Yangtze resulted in an anoxic environment, where a continuous upwelling current brought about a large number of nutrients in the seawater, significantly increasing paleoproductivity. Strong tectonic subsidence, weak chemical weathering, and a rising sea level together led to a low terrigenous debris supply in the catchment area. Therefore, paleoproductivity and redox conditions were the primary controlling factors of organic matter enrichment at the TST stage, with a clastic supply of secondary importance. With the advance of the Guangxi orogeny, the organic matter enrichment at the EHST-1, EHST-2, and LHST stages was mainly controlled by redox conditions and debris supply. A comparison of the key physical parameters and geochemical indicators of shale reservoirs from these four system tracts suggests that two shale sweet spot types (type I and II) were developed during the Rhuddanian–Aeronian stage, occurring in the TST and EHST-2 stages. High TOC and high microcrystalline quartz content are key to developing type I sweet spots, while enhanced anoxic conditions in the bottom water caused by ephemeral, small-scale sea level rises are the main determinant of class II sweet spots in the later EHST stage.

OTUD6A is a deubiquitinase that plays crucial roles in various human diseases. However, the precise regulatory mechanism of OTUD6A remains unclear. In this study, we found that OTUD6A significantly inhibited the production of type I interferon. Consistently, peritoneal macrophages and bone marrow-derived macrophages from Otud6a−/− mice produced more type I interferon after virus infection compared to cells from WT mice. Otud6a−/−− mice also exhibited increased resistance to lethal HSV-1 and VSV infections, as well as LPS attacks due to decreased inflammatory responses. Mechanistically, mass spectrometry results revealed that UBC13 was an OTUD6A-interacting protein, and the interaction was significantly enhanced after HSV-1 stimulation. Taken together, our findings suggest that OTUD6A plays a crucial role in the innate immune response and may serve as a potential therapeutic target for infectious disease.

With the development of the Internet, it is more convenient for people to obtain information, which also facilitates the spread of rumors. It is imperative to study the mechanisms of rumor transmission to control the spread of rumors. The process of rumor propagation is often affected by the interaction of multiple nodes. To reflect higher-order interactions in rumor-spreading, hypergraph theories are introduced in a Hyper-ILSR (Hyper-Ignorant–Lurker–Spreader–Recover) rumor-spreading model with saturation incidence rate in this study. Firstly, the definition of hypergraph and hyperdegree is introduced to explain the construction of the model. Secondly, the existence of the threshold and equilibrium of the Hyper-ILSR model is revealed by discussing the model, which is used to judge the final state of rumor propagation. Next, the stability of equilibrium is studied by Lyapunov functions. Moreover, optimal control is put forward to suppress rumor propagation. Finally, the differences between the Hyper-ILSR model and the general ILSR model are shown in numerical simulations.

Soilless cultivation has increased in China. Like vegetables or ornamental plants, tomatoes can be cultivated in soilless culture systems. Fusarium wilt (FW) is an economic tomato disease. The nature and amount of volatile organic compounds in Trichoderma asperellum PT-15 were investigated, and 6-pentyl-α-pyrone (6-PP) was detected. Furthermore, the effect of 6-PP on Fusarium oxysporum HF-26 was evaluated. Results revealed that 25 mg/L 6-PP was the optimal concentration inhibiting F. oxysporum HF-26 and that the content of fusaric acid decreased considerably compared to that of the control. FUB1, FUB4, and FUB10 toxin synthesis and transport genes were downregulated. Additionally, VelA, velB, and LaeA genes were downregulated, reducing F. oxysporum mycelial growth and hyphae formation. 6-PP was added to the soilless culture solution in a greenhouse experiment. The results showed that an antifungal–nutrient solution containing 25 mg/L 6-PP significantly suppressed FW with 70.71% efficacy and a 27.23% disease index (DI), which were higher efficacy and lower DI than that of the control. Furthermore, treatment with an antifungal–nutrient solution containing 6-PP increased the levels of defence enzymes 24 h post-inoculation (hpi) compared with those at other time periods. The relative expression levels of the PR1, NPR1, PR2, and PR5 genes were considerably upregulated at 24 hpi.

The remote sensing imaging environment is complex, in which many factors cause image blur. Thus, without prior knowledge, the restoration model established to obtain clear images can only rely on the observed blurry images. We still build the prior with extreme pixels but no longer traverse all pixels, such as the extreme channels. The features are extracted in units of patches, which are segmented from an image and partially overlap with each other. In this paper, we design a new prior, i.e., overlapped patches’ non-linear (OPNL) prior, derived from the ratio of extreme pixels affected by blurring in patches. The analysis of more than 5000 remote sensing images confirms that OPNL prior prefers clear images rather than blurry images in the restoration process. The complexity of the optimization problem is increased due to the introduction of OPNL prior, which makes it impossible to solve it directly. A related solving algorithm is established based on the projected alternating minimization (PAM) algorithm combined with the half-quadratic splitting method, the fast iterative shrinkage-thresholding algorithm (FISTA), fast Fourier transform (FFT), etc. Numerous experiments prove that this algorithm has excellent stability and effectiveness and has obtained competitive processing results in restoring remote sensing images.

For high-energy π0 mesons, the angle between the two final-state photons decreases with the increase in the energy of the π0, which enhances the probability of overlapping electromagnetic showers. The performance of the cluster splitting algorithm in the EMC reconstruction is crucial for the mass resolution measurement of π0 with high energy. The cluster splitting algorithm is based on the theoretical lateral distribution of the electromagnetic showers. A simple implementation of the lateral distribution can be described as a (multi-)exponential function. In a realistic electromagnetic calorimeter, considering the granularity of the detector, the measured energy in a cell is actually the integral of the theoretical energy deposition, which deviates from the exponential function. Based on the simulation of the barrel EMC in the P¯ANDA experiment, a cluster splitting algorithm with a new lateral energy development function is developed. The energy resolution of overlapping showers with high energy has been improved.

In this study, we aimed to provide systematic and critical research to investigate the shear performance and reveal the corresponding structural response and fracture characteristics of the monolayer GK membrane. The results demonstrate that the kirigami structure significant alters the shear performance of graphene-based sheets. Tuning the porosity by controlling the incision size, pore distribution, and incision direction can effectively adjust the shear strength and elastic modulus of GK membranes. The trade-off of the stress and strain of the GK membrane is critical to its shear behaviour. The microstructural damage processes and failure characteristics further reveal that making more carbon atoms on the GK structure sharing the strain energy is the key to reinforcing the shear performance of membranes. Based on this, we found that adding the shear loading in the direction of perpendicular to the incisions on the GK membrane can significantly improve the shear strength and stiffness of the membrane by 26.2–32.1% and 50.2–75.3% compared to applying shear force parallel to GK incisions. This research not only broadens the understanding of shear properties of monolayer GO membrane but also provides more reference on the fracture characteristics of GK membranes for future manufacturing and applications.

In this paper, an algorithm based on local binary pattern (LBP) is proposed to obtain clear remote sensing images under the premise of unknown causes of blurring. We find that LBP can completely record the texture features of the images, which will not change widely due to the generation of blur. Therefore, LBP prior is proposed, which can filter out the pixels containing important textures in the blurry image through the mapping relationship. The corresponding processing methods are adopted for different types of pixels to cope with the challenges brought by the rich texture and details of remote sensing images and prevent over-sharpening. However, the existence of LBP prior increases the difficulty of solving the model. To solve the model, we construct the projected alternating minimization (PAM) algorithm that involves the construction of the mapping matrix, the fast iterative shrinkage-thresholding algorithm (FISTA) and the half-quadratic splitting method. Experiments with the AID dataset show that the proposed method can achieve highly competitive processing results for remote sensing images.

Stripe noise is a common condition that has a considerable impact on the quality of the images. Therefore, stripe noise removal (destriping) is a tremendously important step in image processing. Since the existing destriping models cause different degrees of ripple effects, in this paper a new model, based on total variation (TV) regularization, global low rank and directional sparsity constraints, is proposed for the removal of vertical stripes. TV regularization is used to preserve details, and the global low rank and directional sparsity are used to constrain stripe noise. The directional and structural characteristics of stripe noise are fully utilized to achieve a better removal effect. Moreover, we designed an alternating minimization scheme to obtain the optimal solution. Simulation and actual experimental data show that the proposed model has strong robustness and is superior to existing competitive destriping models, both subjectively and objectively.

As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) realizes the optimal allocation of resources in the product manufacturing process through the network. Task decomposition is a key problem of the CMfg system for resource scheduling. A high-quality task decomposition method can shorten product development time, reduce costs for resource service providers, and provide technical support for the application of CMfg. However, a cloud manufacturing system has to manage the allocation the correct amount of manufacturing resources, complex production processes, and highly dynamic production environments. At the same time, the tasks issued by service demanders are usually asymmetric and tightly coupled. We solve the complex task decomposition problem by using the traditional methods, that are hard to complete in CMfg. To overcome the shortcomings of CMfg, this paper proposed a task decomposition method based on the cloud platform. For achieving modular production, this approach creatively divides the product production process into four stages: design, manufacturing, transportation, and maintenance. Then a hybrid method, which combines with depth-first search algorithm, fast modular optimization algorithm, and artificial bee colony algorithm, is introduced. The method can obtain a multi-stage task optimization decomposition plan in CMfg. Simulation results demonstrate the proposed method can achieve complex task optimization decomposition in a CMfg environment.

Recovering correct or at least realistic colors of underwater scenes is a challenging issue for image processing due to the unknown imaging conditions including the optical water type, scene location, illumination, and camera settings. With the assumption that the illumination of the scene is uniform, a chromatic adaptation-based color correction technology is proposed in this paper to remove the color cast using a single underwater image without any other information. First, the underwater RGB image is first linearized to make its pixel values proportional to the light intensities arrived at the pixels. Second, the illumination is estimated in a uniform chromatic space based on the white-patch hypothesis. Third, the chromatic adaptation transform is implemented in the device-independent XYZ color space. Qualitative and quantitative evaluations both show that the proposed method outperforms the other test methods in terms of color restoration, especially for the images with severe color cast. The proposed method is simple yet effective and robust, which is helpful in obtaining the in-air images of underwater scenes.

A novel analytical model is proposed and validated in this paper to predict the velocity deficit in the wake downwind of a wind turbine. The model is derived by employing mass and momentum conservation and assuming a cosine-shaped distribution for the velocity deficit. In this model, a modified wake growth rate rather than a constant one is chosen to take into account the effects of the ambient turbulence and the mechanical turbulence generated. The model was tested against field observations, wind-tunnel measurements in different thrust operations and high-resolution large-eddy simulations (LES) for two aerodynamic roughness lengths. It was found that the normalized velocity deficit predicted by the proposed model shows good agreement with experimental and numerical data in terms of shape and magnitude in the far wake region ( x / d 0 > 3 ). Based on the proposed model, predictions from multiple views and at different locations are demonstrated to show the spatial distribution of streamwise velocity downwind of a wind turbine. The result shows that the model is suitable for predicting streamwise velocity fields and thus could provide some references for the selection of wind turbine spacing.