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Wireless capsule endoscopy (WCE) has become an important tool for gastrointestinal examination due to its non-invasive nature and minimal patient discomfort. However, the quality of WCE images is often limited by built-in lighting and the complex gastrointestinal environment, particularly in the region filled with small intestinal villi. Additionally, the morphology of these villi usually serves as a crucial indicator for related diseases. To address this, we propose a novel method to enhance the clarity of small intestinal villi in WCE images. Our method uses a guided filter to separate the low- and high-frequency components of WCE images. Illumination gain factors are calculated from the low-frequency components, while gradient gain factors are derived from Laplacian convolutions on different regions. These factors enhance the high-frequency components, combined with the original image. This approach improves edge detail while suppressing noise and avoiding edge overshoot, providing clearer images for diagnosis. Experimental results show that our proposed method achieved a 45.47% increase in PSNR compared to classical enhancement algorithms, a 12.63% improvement in IRMLE relative to the original images, and a 31.84% reduction in NIQE with respect to the original images. [ABSTRACT FROM AUTHOR]

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant. [ABSTRACT FROM AUTHOR]

Simple Summary: China is a major goose-raising country, and the geese industry plays a significant role in animal husbandry. Goose growth performance (body weight) is a critical topic. This study used 16S rRNA sequencing to comprehensively analyze the cecal flora of healthy 70-day-old Yangzhou geese with varying weights but identical feeding methods to investigate the correlation between their intestinal microorganisms and body weight. Correlation analysis of production performance indicators between cecal microflora and body weight revealed a significant positive correlation between birth weight and Deferribacterota at the phylum level. At the genus level, leg and chest muscle weights exhibited significant positive correlations with Prevotellace-ae_Ga6A1_group, suggesting its critical role in promoting the growth and development of goose leg and chest muscles. These findings offer a crucial theoretical foundation for studying gastrointestinal microorganisms and provide insights into the development and formulation of poultry probiotics. China is a major goose-raising country, and the geese industry plays a significant role in animal husbandry. Therefore, goose growth performance (body weight) is a critical topic. Goose gut microbiota influences weight gain by regulating its energy metabolism and digestion. Additionally, the impact of cecal microbial community structure on goose growth and development, energy metabolism, and immunity has been examined. However, most studies have used different additives or feeds as variables. Improving the understanding of the dynamic changes in gut microbial communities in geese of different body weights during their growth and development and their correlation with the host's body weight is necessary. In this study, the cecal microbiota of healthy Yangzhou geese with large (L) and small (S) body weights, all at the same age (70 days old) and under the same feeding conditions, were sequenced using 16S rRNA. The sequencing results were annotated using QIIME2 (classify-sklearn algorithm) software, and the linkET package was used to explore the correlation between intestinal microorganisms and the body weight of the Yangzhou goose (Spearman). At the phylum level, the Firmicutes/Bacteroidetes ratio in the large body weight group was approximately 20% higher than that in the small body weight group, with Bacteroidetes and Firmicutes exhibiting a highly significant negative correlation. At the genus level, Bacteroides constituted the most abundant microbial group in both groups, although the Prevotellaceae_Ga6A1_group exhibited a higher abundance in the large than the small weight group. Spearman correlation analysis and the linkET package were used to analyze the correlation between cecal microflora and production performance indicators that showed significant differences between the two groups and showed that birth weight was significantly positively correlated with Deferribacterota at the phylum level. At the genus level, leg and chest muscle weights exhibited significant positive correlations with Prevotellace-ae_Ga6A1_group, suggesting its critical role in promoting the growth and development of goose leg and chest muscles. A significant negative correlation was observed between [Ruminococ-cus]_torque and Prevotellaceae_Ga6A1_group. These findings offer a crucial theoretical foundation for the study of gastrointestinal microorganisms and provide insights into the development and formulation of poultry probiotics. [ABSTRACT FROM AUTHOR]

Without mechanical compliance robots rely on controlled environments and precision equipment to avoid clashes and large contact forces when interacting with an external workpiece, e.g., a peg-in-hole (PiH) task. In such cases, passive compliance devices are used to reduce the insertion force (and in turn the robot payload) while guiding corrective motions. Previous studies in this field are limited to small misalignments and basic PiH geometries inapplicable to prevalent robotic and autonomous systems (RASs). In addition to these issues, our work argues that there is a lack of a unified approach to the development of passive compliance systems. To this end, we propose a higher-level design approach using robust engineering design (RED) methods. In a case study, we demonstrated this general approach with a Taguchi design framework, developing a remote centre compliant (RCC) end-effector for robotic train fluid servicing. For this specific problem, a pseudo-rigid-body model (PRBM) is suggested in order to save enormous computation time in design, modelling, and optimisation. Our results show that the compliant end-effector is capable of significantly reducing the insertion force for large misalignments up to 15 mm and 6 degrees. [ABSTRACT FROM AUTHOR]

Sea ice regulates the overall energy exchange and radiation budget of the Arctic region, and understanding this relationship requires an accurate determination of snow depth. However, methods for deriving snow depth have a large error through the annual winter and early spring periods due to the potential complexity of surface melting during early summer. In this study, we explore the potential of retrieving snow depth during the early summer using optical satellite imagery of the sea-ice cover. Measurements using VIS/IR (visible and infrared) usually feature much higher spatial resolution than L-band satellite data and can provide additional surface melting and leads information; in addition, considering the snow grain size–snow surface temperature interaction, there is co-variability between the observed sea-ice surface broadband albedo using an optical satellite sensor, the sea-ice surface temperature, and the retrieval target of snow depth on the spatial scale of optical imagery samples. We applied a surface classification procedure to optical satellite imagery and introduce an approach to derive snow depth from optical satellite imagery and ice surface temperature data using two solar radiation transfer models: the Delta-Eddington solar radiation model, which is the shortwave radiative scheme of the Los Alamos sea-ice model, and a simplified snow albedo scheme, which is tuned to the observational data of buoys. The snow depth was inversed from the model simulation results using a lookup-table-based method. For comparison with the observational data, using the Delta-Eddington solar radiation model, about 55% of the differences are below 5 cm, and thicker snowpack has a larger bias; using the simplified snow albedo scheme, a mean difference of 4.1 cm between retrieval and measurements was found, with 93% of the differences being smaller than 5 cm. This approach can be applied to optical satellite imagery acquired under clear-sky conditions and can serve as an addition to overcome the limitations of existing methods. [ABSTRACT FROM AUTHOR]

Estimating the critical slope angle (CSA) for sheet erosion is important for the precision estimation of sheet erosion and the development of erosion control practices. This study developed mathematical equations considering rainfall intensity and soil infiltration to efficiently estimate both instantaneous (at a given instant during rainfall) and cumulative CSAs, while also providing a valuable explanation for the change in CSA. The mathematical equations were consistent with observations from runoff plots (NSE = −1.01) of loess soils from Zhangjiakou (China) and simulation results (NSE = 0.96) from the Water Erosion Prediction Project model for a loam soil in Montana (USA). Estimated instantaneous CSA determined by the mathematical equations increased as the ratio of rainfall intensity to soil infiltration (I/f) increased, resulting in higher observed cumulative CSA after heavy versus normal rainfall events. Heavy rainfall, compacted soil, and varying rainfall duration affected the CSA by changing the I/f ratio. Maximum instantaneous CSA provided a better prediction of changes in soil erosion dynamics than that obtained from CSAs determined by field observations or experimental simulations. The mathematical equations illustrate the underlying physical mechanisms by which rainfall intensity and soil infiltration affect the CSA through changing the shear stress of overland flow. The results of this study provide critical information for guiding the development of effective soil erosion control strategies. [ABSTRACT FROM AUTHOR]

The development and utilization of biomass can not only address the demand for low-carbon energy and reduce environmental pollution, but can also facilitate the achievement of carbon neutrality. However, there are many factors justifying the case for low utilization of agricultural residues. These factors could be well controlled by producing top-quality pellets. Production of pellets is generally accompanied by the problems of high energy consumption and serious mold wearing. To eliminate these deficiencies, pretreatment has attracted scholars' attention. In this review, the effects of four pretreatments on the properties of pellets were assessed. Thermal pretreatment can improve the hydrophobicity of pellets, and optimize their properties, while degradation of diverse extractives is noteworthy. Hydrothermal pretreatment improves the physical properties of pellets, through the increase of polar functional groups on the surface of the biomass. Ultrasonic vibration-assisted (UV-A) pelleting produces pellets under low pressure without a heating process; however, it is still not applied to large-scale production. Supercritical fluid extraction can achieve the graded utilization of extracts and bioactive substances in biomass, and the residues can be subsequently utilized as pellet feedstock. Mild hydrothermal treatment is a promising approach to improving the quality of agricultural pellets. Additionally, the effects of process parameters on the physical and chemical properties of pellets should be systematically analyzed. [ABSTRACT FROM AUTHOR]

The tribological performance of the friction pair between the rotor and finger feet is a crucial index affecting the service life of finger seals. In recent years, the surface texture has attracted a considerable number of researchers owing to its extraordinary potential in improving antifriction and wear resistance. This paper, inspired by snakeskins, introduces three texture forms (e.g., diamond, ellipse, and hexagon) into the rotor. The effects on finger-sealing performance are analyzed by considering finger seals' varied working conditions. First, a numerical model of textured finger seals under hydrodynamic lubrication is established based on the Reynolds equation. Then, the sealing performance analysis of textured finger seals is performed considering varied working conditions given rotation speed, pressure difference, seal clearance, and working temperature. The numerical results show that: (1) the textured domain produces a noticeable hydrodynamic pressure effect and cavitation, which effectively improves the bearing capacity of the fluid film; (2) the higher the rotation speed or the lower the inlet/outlet pressure difference, the stronger the dynamic pressure effect of textured finger seals and the better the antifriction and wear resistance; (3) for good antifriction and wear resistance of a textured finger seal, the seal clearance should be as shallow as possible (≤10 μm), and the working temperature should be as low as possible (≤120 °C); and (4) the ellipse texture has a higher average dimensionless pressure and a lower friction coefficient, which is superior to diamond and hexagon ones in terms of friction and wear performance. [ABSTRACT FROM AUTHOR]

The formation and distribution of melt ponds have an important influence on the Arctic climate. Therefore, it is necessary to obtain more accurate information on melt ponds on Arctic sea ice by remote sensing. The present large-scale melt pond products, especially the melt pond fraction (MPF), still require verification, and using very high resolution optical satellite remote sensing data is a good way to verify the large-scale retrieval of MPF products. Unlike most MPF algorithms using very high resolution data, the LinearPolar algorithm using Sentinel-2 data considers the albedo of melt ponds unfixed. In this paper, by selecting the best band combination, we applied this algorithm to Landsat 8 (L8) data. Moreover, Sentinel-2 data, as well as support vector machine (SVM) and iterative self-organizing data analysis technique (ISODATA) algorithms, are used as the comparison and verification data. The results show that the recognition accuracy of the LinearPolar algorithm for melt ponds is higher than that of previous algorithms. The overall accuracy and kappa coefficient results achieved by using the LinearPolar algorithm with L8 and Sentinel-2A (S2), the SVM algorithm, and the ISODATA algorithm are 95.38% and 0.88, 94.73% and 0.86, and 92.40%and 0.80, respectively, which are much higher than those of principal component analysis (PCA) and Markus algorithms. The mean MPF (10.0%) obtained from 80 cases from L8 data based on the LinearPolar algorithm is much closer to Sentinel-2 (10.9%) than the Markus (5.0%) and PCA algorithms (4.2%), with a mean MPF difference of only 0.9%, and the correlation coefficients of the two MPFs are as high as 0.95. The overall relative error of the LinearPolar algorithm is 53.5% and 46.4% lower than that of the Markus and PCA algorithms, respectively, and the root mean square error (RMSE) is 30.9% and 27.4% lower than that of the Markus and PCA algorithms, respectively. In the cases without obvious melt ponds, the relative error is reduced more than that of those with obvious melt ponds because the LinearPolar algorithm can identify 100% of dark melt ponds and relatively small melt ponds, and the latter contributes more to the reduction in the relative error of MPF retrieval. With a wider range and longer time series, the MPF from Landsat data are more efficient than those from Sentinel-2 for verifying large-scale MPF products or obtaining long-term monitoring of a fixed area. [ABSTRACT FROM AUTHOR]

We present an algorithm for computing ice drift in the marginal ice zone (MIZ), based on partial shape recognition. With the high spatial resolution of Sentinel-1 and Sentinel-2 images, and the low sensitivity to atmospheric influences of Sentinel-1, a considerable quantity of ice floes is identified using a mathematical morphology method. Hausdorff distance is used to measure the similarity of segmented ice floes. It is tolerant to perturbations and deficiencies of floe shapes, which enhances the density of retrieved sea ice motion vectors. The PHD algorithm can be applied to sequential images from different sensors, and was tested on two combined image mosaics consisting of Sentinel-1 and Sentinel-2 data acquired over the Fram Strait; the PHD algorithm successfully produced pairs of matched ice floes. The matching result has been verified using shape and surface texture similarity of the ice floes. Moreover, the present method can naturally be extended to the problem of multi-source sea ice image registration. [ABSTRACT FROM AUTHOR]

Aggregate is the basic unit of soil structure, which is crucial to the sustainability of soil system functions such as structural stability and Fertility Maintenance. Three Gorges Dam (TGD) has extensively led to a dramatic hydrological regime alteration, which may consequently affect various soil physical properties. The aim of this study was to investigate the long-run temporal variation of soil aggregate stability as induced by water-level fluctuations in the riparian zone of the Three Gorges Reservoir (TGR). Sampling plots were established along different elevations considering the interval of 5 m, starting from 150 m to 175 m. A Laser Diffraction based analysis that allows the measurement of soil aggregate stability after the removal of soil organic matter helped to particularly study the effect of external factors on soil aggregate stability of the study area. In addition, wet-sieving method considering the effect of chemical binding agents was used to quantify aggregate stability. The present results indicated a significant increase of Mean Volume Diameter, MVD (p < 0.05) within the study period. Continuous drying-wetting cycles mended soil aggregate stability with a 14.25% increase of the MVD from 2012 to 2016. In the Water-Level Fluctuation Zone (WLFZ), the lower land has predominantly contributed to the increase of soil aggregate stability compared to upper land, with an increase of 62.19% and 37.81% for MVD, 60.88% and 39.12% for D10, 95.34% and 4.66% for D90 at lower and upper elevations, respectively. Sediment deposition below 165 m has precluded a direct effect of water stress on soil aggregates, which certainly declined soil disaggregation. The removal of SOM while analyzing aggregate stability by LD may explain the contradiction between the resulted MVD, and the MWD and GMD. The increase of MWD and GMD was mainly attributed to the increase of SOM with r2 = 0.89 (p < 0.01) and r2 = 0.90 (p < 0.01), while the increase of MVD was highly predicted by the decrease of SOM with r2 = 0.88 (p < 0.01). Since this study presents a remarkable change of soil in the riparian area due to dry-wet cycles, our results may help to deeply understand the soil ecology and environmental changes in the WLFZ. [ABSTRACT FROM AUTHOR]

We report a red-fluorescent drug delivery system formed by biodegradable and biocompatible amphiphilic A-B-A block copolymers. Each polymer consists of a red fluorescent dye covalently bonded in the middle of hydrophobic block (B) of polylactone, tethered at both ends with poly[(oligo ethylene glycol) methyl ether methacrylate] (POEGMA) as the hydrophilic block. Two types of polylactones, i.e., semicrystalline poly(ε-caprolactone) (PCL) and amorphous poly(δ-decalactone) (PDL), respectively, were incorporated as the hydrophobic segment in the block copolymers. Using transmission electron microscopy, we characterized the self-assembled nanostructures formed by these amphiphilic block copolymers in mixtures of water/tetrahydrofuran or water/dimethylformamide. All of these polymers remained highly fluorescent in water, although some extent of aggregation-induced fluorescence quenching was still observed. Among the three types of polymers presented here, the polymer (RPO-3) containing an amorphous block of PDL showed the highest drug-loading capacity and the largest extent of drug release in acidic media. RPO-3 micelles loaded with doxorubicin as a model of anticancer drug showed sustainable intracellular release and cytotoxicity against HeLa cells. [ABSTRACT FROM AUTHOR]

This paper refines the fuzzy logic method, while constructing a theoretical model of the relationship between economic resilience, social resilience and ecological resilience, and evaluates the coupling coordination between the economic-social-ecological resilience of 197 prefecture-level cities in China's urban agglomerations in 2019. Findings include: (1) The mean ecological resilience of China's urban agglomerations in 2019 was the highest, followed by economic and social resilience. (2) Promoting urban agglomerations had higher resilience scores in the three dimensions, especially in the economic dimension. Growing urban agglomerations had low resilience values on the whole, especially economic resilience. (3) The mean coupling coordination degree of economic-social-ecological resilience ranged from near-incoordination to narrow balance. (4) The coupling coordination degree between the two coincided with the positioning of existing urban agglomerations. (5) Economic resilience had the most significant impact on the coupling coordination. Finally, we give differentiated countermeasures to improve the resilience of urban agglomerations. This study aims to contribute to the promotion of urban resilience research, and helps to plan and design more rational urban economic-social-ecological systems, thereby enhancing the ability of cities to cope with any uncertainties and contingencies.