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Stability and convergence of the L1 formula on nonuniform time grids are studied for solving linear react ion-sub diffusion equations with the Caputo derivative. A discrete fractional Gronwall inequality is developed for the nonuniform L1 formula by introducing a discrete convolution kernel of Riemann-Liouville fractional integral. To simplify the consistency analysis of the nonuniform L1 formula, we bound the local truncation error in a discrete convolution form and consider a global convolution error involving the discrete Riemann-Liouville integral kernel. With the help of discrete fractional Gronwall inequality and global consistency error analysis, a sharp error estimate reflecting the regularity of solution is obtained for a simple L1 scheme. Numerical examples are provided to verify the sharpness of the error analysis.

Over the past decades, benefiting from the development of computing capacity and the free access to Landsat and Sentinel imagery, several fine-resolution global land cover (GLC) products (with a resolution of 10 m or 30 m) have been developed (GlobeLand30, FROM-GLC30, GLC_FCS30, FROM-GLC10, European Space Agency (ESA) WorldCover and ESRI Land Cover). However, there is still a lack of consistency analysis or comprehensive accuracy assessment using a common validation dataset for these GLC products. In this study, a novel stratified random sampling GLC validation dataset (SRS_Val) containing 79,112 validation samples was developed using a visual interpretation method, significantly increasing the number of samples of heterogeneous regions and rare land-cover types. Then, we quantitatively assessed the accuracy of these six GLC products using the developed SRS_Val dataset at global and regional scales. The results reveal that ESA WorldCover achieved the highest overall accuracy (of 70.54% ± 9%) among the global 10 m land cover products, followed by FROM-GLC10 (68.95% ± 8%) and ESRI Land Cover (58.90% ± 7%) and that GLC_FCS30 had the best overall accuracy (of 72.55% ± 9%) among the global 30 m land cover datasets, followed by GlobeLand30 (69.96% ± 9%) and FROM-GLC30 (66.30% ± 8%). The mapping accuracy of the GLC products decreased significantly with the increased heterogeneity of landscapes, and all GLC products had poor mapping accuracies in countries with heterogeneous landscapes, such as some countries in Central and Southern Africa. Finally, we investigated the consistency of six GLC products from the perspective of area distributions and spatial patterns. It was found that the area consistencies between the five GLC products (except ESRI Land Cover) were greater than 85% and that the six GLC products showed large discrepancies in area consistency for grassland, shrubland, wetlands and bare land. In terms of spatial patterns, the totally inconsistent pixel proportions of the 10 m and 30 m GLC products were 23.58% and 14.12%, respectively, and these inconsistent pixels were mainly distributed in transition zones, complex terrains regions, heterogeneous landscapes, or mixed land-cover types. Therefore, the SRS_Val dataset well supports the quantitative evaluation of fine-resolution GLC products, and the assessment results provide users with quantitative metrics to select GLC products suitable for their needs.

With the development of remote sensing technology, a number of fine-resolution (30-m) global/national land cover (LC) products have been developed. However, accuracy assessments for the developed LC products are commonly conducted at global and national scales. Due to the limited availability of representative validation observations and reference data, knowledge relating to the accuracy and applicability of existing LC products on a regional scale is limited. Since Xinjiang, China, exhibits diverse surface cover and fragmented urban landscapes, existing LC products generally have high classification uncertainty in this region. This makes Xinjiang suitable for assessing the accuracy and consistency of exiting fine-resolution land cover products. In order to improve knowledge of the accuracy of existing fine-resolution LC products at the regional scale, Xinjiang province was selected as the case area. First, we employed an equal-area stratified random sampling approach with climate, population density, and landscape heterogeneity information as constraints, along with the hexagonal discrete global grid system (HDGGS) as basic sampling grids to develop a high-density land cover validation dataset for Xinjiang (HDLV-XJ) in 2020. This is the first publicly available regionally high-density validation dataset that can support analysis at a regional scale, comprising a total of 20,932 validation samples. Then, based on the generated HDLV-XJ dataset, the accuracies and consistency among three widely used 30-m LC products, GLC_FCS30, GlobeLand30, and CLCD, were quantitatively evaluated. The results indicated that the CLC_FCS30 exhibited the highest overall accuracy (88.10%) in Xinjiang, followed by GlobeLand30 (with an overall accuracy of 83.58%) and CLCD (81.57%). Moreover, through a comprehensive analysis of the relationship between different environmental conditions and land cover product performance, we found that GlobeLand30 performed best in regions with high landscape fragmentation, while GLC_FCS30 stood out as the most outstanding product in areas with uneven proportions of land cover types. Our study provides a novel insight into the suitability of these three widely-used LC products under various environmental conditions. The findings and dataset can provide valuable insights for the application of existing LC products in different environment conditions, offering insights into their accuracies and limitations.

Proton exchange membrane fuel cell (PEMFC) has been extensively developed due to its benefits, such as high efficiency and zero emission. Durability and lifespan are currently the main factors impeding the widespread commercialization of fuel cells. During operational conditions, fuel cell experience continuous variations in temperature, pressure, humidity, and the concentration of reaction gases. These differential distributions ultimately lead to non-uniform degradation. Based on the analysis of degradation mechanism, the main factors contributing to the inconsistent degradation of the catalyst layer (CL), platinum, and ionomer have been identified. Furthermore, new trends in study of improving the consistency of fuel cells have been proposed, including gradient design of the CL and the design of novel electrodes and flow field structures. This review intends to guide further research in improving the consistency in fuel cells.

Accurate assessment of erythrocyte osmotic fragility (EOF) is essential for diagnosing hemolytic disorders, yet traditional methods are labor-intensive and time-consuming, limiting their clinical efficiency. This study aimed to evaluate the performance of a fully automated EOF analysis system developed by Shenzhen Pumen Technology Co., Ltd., which utilizes scatter turbidimetry, and to determine its accuracy and consistency compared with the conventional spectrophotometric method. A total of 114 whole blood samples were analyzed using the automated system with reagents from Changchun Huili Biotechnology Co., Ltd., and results were compared with those obtained from the Shimadzu UV-2450 spectrophotometer as the reference method. Consistency between the two systems was assessed using linear regression, Kappa statistics, Bland-Altman analysis, and medical decision level bias evaluation. The automated EOF system demonstrated a strong linear correlation with the reference method, achieving a Kappa value of 1.00, indicating complete agreement in classification results. Moreover, 99.11% of data points fell within acceptable ranges, and bias confidence intervals at the medical decision level were below threshold values. These findings indicate that the fully automated EOF system provides stable and reliable results that align with clinical needs and offer high consistency with traditional methods, supporting its potential for broader clinical application and promotion.

Land cover products provide the key inputs for terrestrial change monitoring and modeling. Numerous land cover products have been generated in the past few decades, but their performance on the southeastern Tibetan Plateau remains unclear. This study analyzed 15 land cover products for consistency through compositional similarity and overlay analyses. Additionally, 1305 validation samples from four datasets were employed to construct confusion matrices to evaluate their accuracy. The results indicate the following: (1) Land cover products exhibit relatively high consistency in 62.92% of the region. (2) Land cover products are strongly influenced by terrain fluctuations, showing lower consistency at elevation below 200 m and instability in land cover classification with increasing elevation, particularly between 2800–4400 m and 4800–5400 m. (3) The accuracy for forest, water, and snow/ice is relatively high. However, there is a relatively lower accuracy for wetland and shrubland, necessitating more field samples for reference to improve classification. (4) The average values of the four validation datasets show that the overall accuracy of the 15 products ranges from 50.97% to 73.50%. For broad-scale studies with lower resolution requirements, the CGLS-LC100 product can be considered. For studies requiring a finer scale, a combination of multiple land cover products should be utilized. ESRI is recommended as a reference for built-up land, while FROM-GLC30 can be used for cropland, although misclassification issues should be noted. This study provides valuable insights for analyzing land cover types on plateaus to refine classification. It also offers guidance for selecting suitable land cover products for future research in this region.

This paper presents consistent finite-volume schemes for the two-dimensional Bevilacqua–Galeão–Costa (BGC) anomalous diffusion equation on a uniform structured grid. Custom compact stencils are used to discretise the biharmonic operator in both interior and boundary control volumes, ensuring conservative spatial operators. A von Neumann stability analysis compares fully implicit and explicit time integrations, while verification via the method of manufactured solutions confirms second-order spatial and first-order temporal accuracy. Transient simulations across a range of retention factors demonstrate how the fourth-order term influences anomalous diffusion behaviour.

Land-use and land-cover changes in the Eastern European Plain have important implications for regional and global ecological environments, food security, and socio-economic development. Here, three 30 m resolution global land cover data products (FROM_GLC, GlobeLand30, and GLC_FCS30) from the Eastern European Plain were analyzed and evaluated for component similarity, type confusion degree, spatial consistency, and accuracy verification. The research found that the three products provided consistent descriptions of land-cover types in the East European Plain. There was a strong correlation in the type area between the different products, with a correlation coefficient >0.85. Medium-to-high-consistency areas represented 92.31% of the total plains area. The low-consistency areas were mainly concentrated on Yuzhny Island, Kola Peninsula, and Pechora River Basin. The comparison revealed high consistency among the three products in identifying forest, cropland, water, and permanent ice/snow types. However, the consistency was poor for shrubs, wetlands, and bare land. Using the GLCVSS_V1 validation dataset, the highest overall accuracy among the assessed land cover data products was observed in the FROM_GLC (73.96%), followed by GlobeLand30 (69.80%) and GLC_FCS30 (67.29%). The FROM_GLC dataset is suitable for studying forests, tundra, water, and providing an overall representation of the region’s land cover. The GLC_FCS30 dataset is more suitable for agricultural research. The differences between products arise from the differences in classification systems, algorithms, and data correction. In the future, it will be necessary to utilize the advantages of different products for data fusion, focusing on areas with high heterogeneity and easily confused types, and improving the reliability of land-cover data products.

Pyramid-structured abrasive belts are characterized by their regular microgeometry and self-sharpening, layer-by-layer wear. The coupling of this wear evolution with material removal behavior may significantly influence the surface residual stress during grinding. In this study, pyramid belts at various wear stages were utilized to perform constant-load and constant-speed plane grinding of Mn13 high-manganese steel plates on a force-controlled robotic platform. Surface residual stress distributions in different directions were measured using X-ray diffraction, and their consistency was evaluated through repeated trials and statistical indices. The results indicate that the ground surfaces predominantly exhibit tensile stress, whereas compressive stress or a transition toward compression tends to occur at the entry and exit regions of the grinding path. In the transverse direction, σ x displays a symmetric distribution that diminishes in the final wear stage, while σ y evolves from initial compression to tensile stress with increasing magnitude. As belt wear progresses, the removal mode transitions from cutting to plowing and friction, resulting in σ x gradually shifting toward compression and σ y toward tensile. Consistency analysis reveals that the Relative Uniformity Index (RUI) remains stable across wear stages, with lower values observed in the transverse direction compared to those along the grinding path. This stability is closely related to the layer-by-layer wear and self-sharpening characteristics of the pyramid belts. Together, these results provide a systematic link between pyramid-belt wear evolution, material removal mode and three-dimensional residual stress distribution, offering a basis for controlling surface integrity in robotic belt finishing.

Recombinant human erythropoietin (rhEPO) is a glycoprotein that acts as the main hormone involved in regulating red blood cell production to treat anemia caused by chronic kidney disease or chemotherapy, which has three N-glycosylation sites and one O-glycosylation site. It contains a variety of different glycosylation modifications, such as sialyation, O-acetylation on sialic acids, etc., which causes a big challenge for the glycosylation analysis of rhEPO. In this study, a liquid chromatography-mass spectrometry (LC–MS) method combined with electron-activated dissociation (EAD) technology was used in qualitative and quantitative characterization of rhEPO N-glycosylation and O-glycosylation in just one injection. The usage of EAD not only generated abundant MS/MS fragment ions of glycopeptides and improved the MS/MS sequence coverage but also preserved the glycan structures in the MS/MS fragment ions and the integrity of the glycosidic bond between the glycans and peptides. Three N-glycosylation sites (N24, N38, and N83) and one O-glycosylation site (S126) of rhEPO samples were successfully identified. Among them, the glycosylation ratios of N24, N38, and N83 sites were 82.7%, 100%, and 100% respectively, and 15, 10, and 12 different N-glycans could be identified at the glycopeptide level. The total average number of sialic acids, N-hydroxyacetylneuraminoic acid, and O-acetylation on sialic acid were 7.28, 4.21, and 0.66 at the intact protein level, respectively. For O-glycosylation site S126, O-glycosylation ratios analyzed at the intact protein level and the glycopeptide level were 80.2% and 80.3%, respectively, and two O-glycans were identified, including Core1_S1 and Core1_S2. This study also compared the difference of the glycans and their relative contents in batch-to-batch rhEPO samples. The results proved that the workflow using EAD fragmentation in LC–MS method could be effectively applied for characterizing the glycosylation analysis of rhEPO samples and batch-to-batch consistency analysis, which would help to reasonably guide the optimization of rhEPO production process.