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Land-use/land-cover changes （LUCCs） have links to both human and nature inter- actions. China＇s Land-Use/cover Datasets （CLUDs） were updated regularly at 5-year inter- vals from the late 1980s to 2010, with standard procedures based on Landsat TM／ETM＋ im- ages. A land-use dynamic regionalization method was proposed to analyze major land-use conversions. The spatiotemporal characteristics, differences, and causes of land-use changes at a national scale were then examined. The main findings are summarized as fol- lows. Land-use changes （LUCs） across China indicated a significant variation in spatial and temporal characteristics in the last 20 years （1990-2010）. The area of cropland change de- creased in the south and increased in the north, but the total area remained almost un- changed. The reclaimed cropland was shifted from the northeast to the northwest. The built-up lands expanded rapidly, were mainly distributed in the east, and gradually spread out to central and western China. Woodland decreased first, and then increased, but desert area was the opposite. Grassland continued decreasing. Different spatial patterns of LUC in China were found between the late 20th century and the early 21st century. The original 13 LUC zones were replaced by 15 units with changes of boundaries in some zones. The main spatial characteristics of these changes included （1） an accelerated expansion of built-up land in the Huang-Huai-Hai region, the southeastern coastal areas, the midstream area of the Yangtze River, and the Sichuan Basin; （2） shifted land reclamation in the north from northeast China and eastern Inner Mongolia to the oasis agricultural areas in northwest China; （3） continuous transformation from rain-fed farmlands in northeast China to paddy fields; and （4） effective- ness of the ＂Grain for Green＂ project in the southern agricultural-pastoral ecotones of Inner Mongolia, the Loess Plateau, and southwestern mountainous areas. In the last two decades, although climate change in the north affected the change in cropland, policy regulation and economic driving forces were still the primary causes of LUC across China. During the first decade of the 21st century, the anthropogenic factors that drove variations in land-use pat- terns have shifted the emphasis from one-way land development to both development and conservation. The ＂dynamic regionalization method＂ was used to analyze changes in the spatial patterns of zoning boundaries, the internal characteristics of zones, and the growth and decrease of units. The results revealed ＂the pattern of the change process,＂ namely the process of LUC and regional differences in characteristics at different stages. The growth and decrease of zones during this dynamic LUC zoning, variations in unit boundaries, and the characteristics of change intensities between the former and latter decades were examined. The patterns of alternative transformation between the ＂pattern＂ and ＂process＂ of land use and the causes for changes in different types and different regions of land use were explored.

Background Membranous nephropathy (MN) and kidney renal clear cell carcinoma (KIRC) are distinct kidney diseases with potential shared molecular mechanisms. Identifying common biomarkers may improve our understanding of disease pathogenesis and provide novel diagnostic and therapeutic targets. Methods The study primarily employed bioinformatics tools to analyze publicly available datasets to identify differentially expressed genes (DEGs) and hub genes in KIRC and MN. Functional interactions of the common DEGs were explored using protein–protein interaction (PPI) networks, and hub genes were further investigated through gene expression databases such as GSCA and UALCAN. Gene Set Enrichment Analysis (GSEA) was used to assess functional enrichment and tumor-driving potential. These bioinformatic results were then experimentally validated by knocking down FYN and LGALS8 in 786-O cells using siRNA, followed by RT-qPCR, protein analysis, and functional assays. Results The study identified four hub genes (FYN, LGALS8, MAGI2, and WT1) in KIRC and MN, with FYN and LGALS8 upregulated and MAGI2 and WT1 downregulated. Bioinformatics validation showed excellent diagnostic performance and confirmed methylation and mutation patterns. Higher FYN and LGALS8 expression were linked to poorer survival. miRNA downregulation was validated in KIRC cell lines. Functional analysis revealed that FYN and LGALS8 promote KIRC progression through the ErbB signaling pathway, and knockdown experiments reduced cell proliferation, migration, and colony formation. Conclusion Our findings identify FYN, LGALS8, MAGI2, and WT1 as hub genes in KIRC, with potential diagnostic and prognostic value. These genes play significant roles in methylation, mutation, and immune regulation in KIRC. However, the results from the limited MN samples suggest possible roles of these genes in MN pathology, but further studies are required to fully assess the relevance of these findings to MN.

The proteasome is an ATP-dependent, 2.5-megadalton molecular machine that is responsible for selective protein degradation in eukaryotic cells. Here we present cryo-electron microscopy structures of the substrate-engaged human proteasome in seven conformational states at 2.8–3.6 Å resolution, captured during breakdown of a polyubiquitylated protein. These structures illuminate a spatiotemporal continuum of dynamic substrate–proteasome interactions from ubiquitin recognition to substrate translocation, during which ATP hydrolysis sequentially navigates through all six ATPases. There are three principal modes of coordinated hydrolysis, featuring hydrolytic events in two oppositely positioned ATPases, in two adjacent ATPases and in one ATPase at a time. These hydrolytic modes regulate deubiquitylation, initiation of translocation and processive unfolding of substrates, respectively. Hydrolysis of ATP powers a hinge-like motion in each ATPase that regulates its substrate interaction. Synchronization of ATP binding, ADP release and ATP hydrolysis in three adjacent ATPases drives rigid-body rotations of substrate-bound ATPases that are propagated unidirectionally in the ATPase ring and unfold the substrate. Cryo-electron microscopy structures and dynamics of a substrate-engaged human 26S proteasome reveal in atomic detail three principal modes of coordinated ATP hydrolysis that regulate different steps in the degradation of a ubiquitylated protein.

We introduce an interferometric single-molecule localization method for super-resolution fluorescence microscopy. Fluorescence molecules are located by the intensities of multiple excitation patterns of an interference fringe, providing around a twofold improvement in the localization precision compared with the conventional imaging with the same photon budget. We demonstrate this technique by resolving nanostructures down to 5 nm in size over a large 25 × 25 μm2 field of view.

The financial market is a complex system, which has become more complicated due to the sudden impact of the COVID-19 pandemic in 2020. As a result there may be much higher degree of uncertainty and volatility clustering in stock markets. How does this “black swan” event affect the fractal behaviors of the stock market? How to improve the forecasting accuracy after that? Here we study the multifractal behaviors of 5-min time series of CSI300 and S&P500, which represents the two stock markets of China and United States. Using the Overlapped Sliding Window-based Multifractal Detrended Fluctuation Analysis (OSW-MF-DFA) method, we found that the two markets always have multifractal characteristics, and the degree of fractal intensified during the first panic period of pandemic. Based on the long and short-term memory which are described by fractal test results, we use the Gated Recurrent Unit (GRU) neural network model to forecast these indices. We found that during the large volatility clustering period, the prediction accuracy of the time series can be significantly improved by adding the time-varying Hurst index to the GRU neural network.

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science （LCS） in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km × 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21 st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the ＂Grain for Green＂ policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of ＂Western Development＂, ＂Revitalization of Northeast＂, coupled with rapidly economic development during this period.

Adenosine triphosphatases (ATPases) associated with a variety of cellular activities (AAA+), the hexameric ring-shaped motor complexes located in all ATP-driven proteolytic machines, are involved in many cellular processes. Powered by cycles of ATP binding and hydrolysis, conformational changes in AAA+ ATPases can generate mechanical work that unfolds a substrate protein inside the central axial channel of ATPase ring for degradation. Three-dimensional visualizations of several AAA+ ATPase complexes in the act of substrate processing for protein degradation have been resolved at the atomic level thanks to recent technical advances in cryogenic electron microscopy (cryo-EM). Here, we summarize the resulting advances in structural and biochemical studies of AAA+ proteases in the process of proteolysis reactions, with an emphasis on cryo-EM structural analyses of the 26S proteasome, Cdc48/p97 and FtsH-like mitochondrial proteases. These studies reveal three highly conserved patterns in the structure–function relationship of AAA+ ATPase hexamers that were observed in the human 26S proteasome, thus suggesting common dynamic models of mechanochemical coupling during force generation and substrate translocation.

Wind speed prediction has an important impact on the planning, economic operation and safe maintenance of wind power systems. However, the high volatility and intermittency of wind speed make it difficult to predict accurately. To improve the prediction accuracy, we developed a hybrid multistep wind speed prediction model named EWP‐CS‐RELM. In this model, a secondary decomposition technique of ensemble empirical mode decomposition (EEMD) and wavelet packet transform (WPT) is used, and it is called the EWP decomposition technique. This decomposition technique can achieve an adaptive processing of the data and accurately extract the characteristic components of the signal, avoiding the occurrence of pattern overlap and reducing the mutual interference between components. At the same time, the high and low‐frequency parts of the complex signal (component) can be decomposed into different frequency bands, and the corresponding frequency band can be selected adaptively to match the signal spectrum. The subsequence obtained after EWP decomposition is then predicted using a regularised extreme learning machine (RELM) optimised by the cuckoo search (CS) algorithm with strong global search ability to obtain the results. The hybrid prediction model is validated using four seasons of wind speed data from two wind farms in Shandong, China, and compared with seven other prediction models. Simulation results illustrate that the EWP‐CS‐RELM model outperforms the other seven models with the smallest statistical errors.

The height of the atmospheric boundary layer (ABLH) or the mixing layer height (MLH) is a key parameter characterizing the planetary boundary layer, and the accurate estimation of that is critically important for boundary layer related studies, which include air quality forecasts and numerical weather prediction. Aerosol lidar is a powerful remote sensing instrument frequently used to retrieve the ABLH through detecting the vertical distributions of aerosol concentration. Presently available methods for ABLH determination from aerosol lidar are summarized in this review, including a lot of classical methodologies as well as some improved versions of them. Some new recently developed methods applying advanced techniques such as image edge detection, as well as some new methods based on multi-wavelength lidar systems, are also summarized. Although a lot of techniques have been proposed and have already given reasonable results in several studies, it is impossible to recommend a technique which is suitable in all atmospheric scenarios. More accurate instantaneous ABLH from robust techniques is required, which can be used to estimate or improve the boundary layer parameterization in the numerical model, or maybe possible to be assimilated into the weather and environment models to improve the simulation or forecast of weather and air quality in the future.

In the current context of global urbanization and climate change, balancing ecological protection and economic development is a particular challenge in the optimal allocation of regional land use. Here, we propose a research framework for the optimal allocation of land use that considers the regional ecological security pattern (ESP) and allocates space for land-use activities to areas with low ecological risk. Taking Baicheng, China as our study area, ecological sources were first identified by integrating their ecological importance and landscape connectivity, and ecological corridors and functional zones were extracted using the minimum cumulative resistance difference and circuit theory. The ecological source areas were then taken as limiting factors, and four future scenarios were established for 2030 using the parcel-level land-use simulator (PLUS) model. The ecological corridors and functional zones served as areas having restricted ecological conditions, and the four future scenarios were coupled into the corresponding functional zones to optimize the land-use structure in 2030. The results indicate that under the coupled ESP–PLUS scenario, the spatial distribution and structure of land use in Baicheng balance the needs of ecological source area protection and economic development, resulting in greater sustainability. By 2030, the cultivated land area will steadily increase, but attention will also be given to the protection of ecological land (e.g., woodland and marshland), aligning with current policy planning demands. An analysis of the landscape indices for each future scenario found all scenarios to be effective in reducing negative changes in landscape patterns. These findings provide a novel perspective for the rational allocation of future land resources and the optimization of land-use structures.