Explore the vast range of titles available.

Investigating the characteristics of urban expansion is helpful in managing the relationship between urbanization and the ecological and environmental issues related to sustainable development. The Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) collects visible and near-infrared light from the Earth’s surface at night without moonlight. It generates effective time series data for mapping the dynamics of urban expansion. As a major urban agglomeration in the world, the Yangtze River Delta Urban Agglomeration (YRDUA) is an important intersection zone of both the “Belt and Road Initiative” and the “Yangtze River Economic Belt” in China. Therefore, this paper analyses urban expansion characteristics of the YRDUA for 1993–2012 from urban extents extracted from the DMSP/OLS for 1993, 1997, 2002, 2007, and 2012. First, calibration procedures are applied to DMSP/OLS data, including intercalibration, intra-annual composition, and inter-annual series correction procedures. Spatial extents are then extracted from the corrected DMSP/OLS data, and a threshold is determined via the spatial comparison method. Finally, three models are used to explore urban expansion characteristics of the YRDUA from expansion rates, expansion spatial patterns, and expansion evaluations. The results show that the urban expansion of the YRDUA occurred at an increasing rate from 1993–2007 and then declined after 2007 with the onset of the global financial crisis. The Suxichang and Ningbo metropolitan circles were seriously affected by the financial crisis, while the Hefei metropolitan circle was not. The urban expansion of the YRDUA moved from the northeast to the southwest over the 20-year period. Urban expansion involved internal infilling over the first 15 years and then evolved into external sprawl and suburbanization after 2007.

The purpose of the paper is to evaluate the quality and hydrological utility of four popular satellite precipitation products, including the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product (3B42V7), near real-time product (3B42RT), and the Climate Prediction Center (CPC) MORPHing technique (CMORPH) satellite–gauge merged product (CMORPH BLD) and bias-corrected product (CMORPH CRT) over Fujiang River basin, China. First, we provided a statistical assessment of the four precipitation products at multiple spatiotemporal scales. The results show that: (1) all the products except 3B42RT capture the spatial pattern of annual precipitation fairly well; (2) in general, CMORPH BLD benefits from the application of the probability density function-optimal interpolation (PDF-OI) gauge adjustment algorithm and performs best among all the products with Pearson correlation coefficients (CC) of 0.84 and 0.94, equitable threat score (ETS) of 0.56 and 0.63 in grid and basin scales, respectively, followed by 3B42V7 and CMORPH CRT; whereas 3B42RT performs worst across all the metrics; (3) according to the occurrence frequencies of rainfall, satellite estimates mainly fall into the bin of 0–1 mm/day and tend to underestimate light precipitation. In addition, the performance of all the products in warm season is much better than in cold season in both grid and basin scales. Subsequently, a physically based distributed model is established to further evaluate the hydrological utility of different precipitation products. The results reveal that: (1) the errors in precipitation products mainly propagate into hydrological simulations, resulting in the best hydrological performance in CMORPH BLD in both daily and monthly scales after recalibrating the model, while 3B42RT shows limited skills in reproducing the daily observed hydrograph; (2) after recalibrating the model with the respective satellite data, significant improvements are observed for all the products; (3) CMORPH BLD no longer shows its superiority during near-real-time monitoring of floods. There is still a great challenge for the application of current satellite-based estimates into local flood monitoring. This study could be used as guidance for choosing alternative satellite precipitation products for hydrological applications in a local community, particularly in basins in which rainfall gauges are scarce.

An empirical simulation method to simulate the possible position of shallow rainfall-induced landslides in China has been developed.This study shows that such a simulation may be operated in real-time to highlight those areas that are highly prone to rainfall-induced landslides on the basis of the landslide susceptibility index and the rainfall intensity-duration（I-D） thresholds.First,the study on landslide susceptibility in China is introduced.The entire territory has been classified into five categories,among which high-susceptibility regions（Zone 4-＇High＇ and 5-＇Very high＇） account for 4.15%of the total extension of China.Second,rainfall is considered as an external triggering factor that may induce landslide initiation.Real-time satellite-based TMPA3B42 products may provide real rainfall spatial and temporal patterns,which may be used to derive rainfall duration time and intensity.By using a historical record of 60 significant past landslides,the rainfall I-D equation has been calibrated.The rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours.The combination of these two aspects can be exploited to simulate the spatiotemporal distribution of rainfall-induced landslide hazards when rainfall events exceed the rainfall I-D thresholds,where the susceptibility category is ＇high＇ or ＇very high＇.This study shows a useful tool to be part of a systematic landslide simulation methodology,potentially providing useful information for a theoretical basis and practical guide for landslide prediction and mitigation throughout China.

Multi-source data-fusion approaches have been developed for estimating regional precipitation. However, studies considering the specific upper limits of the improved gridded rainfall data for different fusion approaches are limited. Here, the potential ranges of accuracy improvement for satellite and reanalysis rainfall products were addressed using various machine learning fusion approaches, including multivariate linear regression (MLR), feedforward neural network (FNN), random forest (RF), and long short-term memory (LSTM), over the Chinese mainland. All four fusion methods reduce errors in the original precipitation products. The upper limits of accuracy improvement in terms of correlation coefficient (CC) and root mean square error (RMSE) were 30.65 and 15.27%, respectively. M-RF showed the best average CC (0.828) and RMSE (4.62 mm/day) in the four seasons. LSTM performed the best under light rainfall events, whereas MLR and RF exhibited better performance under moderate and heavy rainfall events, respectively. Overall, these results serve as a basis for the fusion approach and technique selection, based on the comprehensive validation in different climate zones, altitudes, and seasons over the Chinese mainland.

A novel Symmetric Sparse Representation (SSR) method has been presented to solve the band selection problem in hyperspectral imagery (HSI) classification. The method assumes that the selected bands and the original HSI bands are sparsely represented by each other, i.e., symmetrically represented. The method formulates band selection into a famous problem of archetypal analysis and selects the representative bands by finding the archetypes in the minimal convex hull containing the HSI band points (i.e., one band corresponds to a band point in the high-dimensional feature space). Without any other parameter tuning work except the size of band subset, the SSR optimizes the band selection program using the block-coordinate descent scheme. Four state-of-the-art methods are utilized to make comparisons with the SSR on the Indian Pines and PaviaU HSI datasets. Experimental results illustrate that SSR outperforms all four methods in classification accuracies (i.e., Average Classification Accuracy (ACA) and Overall Classification Accuracy (OCA)) and three quantitative evaluation results (i.e., Average Information Entropy (AIE), Average Correlation Coefficient (ACC) and Average Relative Entropy (ARE)), whereas it takes the second shortest computational time. Therefore, the proposed SSR is a good alternative method for band selection of HSI classification in realistic applications.

The internal organs of sea cucumbers (SCV) are a byproduct of the seafood processing industry and hold untapped potential as a functional food. This study investigates the antioxidant capacity of SCV and its regulatory effects on the gut microbiota in a mouse model of oxidative stress induced by chronic cold exposure. The results indicate that SCV possesses a rich nutritional composition, containing various components such as calcium, phosphorus, and polysaccharides, and exhibit strong scavenging activity against three types of free radicals in vitro: DPPH, OH−, and O2−. SCV significantly reduced MDA levels in both serum and liver, while activating the Keap1-Nrf2/HO-1 pathway, leading to a significant decrease in the expression of HSP70 and HSP90 genes and a marked increase in Nrf2 gene expression, thereby alleviating oxidative damage. Histological analysis revealed that SCV alleviated liver damage, reducing hepatocellular vacuolization and inflammatory cell infiltration. Additionally, SCV modulated the diversity of the gut microbiota, increasing the abundance of Allobaculum, Turicibacter, Bifidobacterium, and Akkermansia, while enriching the synthesis pathway of vitamin B12 (PWY-7377). This study is the first to repurpose sea cucumber viscera waste into a functional food, demonstrating its dual mechanism of alleviating oxidative stress by activating the Keap1-Nrf2/HO-1 antioxidant pathway and regulating the gut microbiota. These findings offer an innovative strategy for the high-value utilization of agricultural by-products and the development of multifunctional health-promoting products.

This paper uses remote sensing data from the Sanjiangyuan National Park (SNP) to explore the divergence between the boundaries of national parks and the distribution of natural habitats. Results are used to argue that these discrepancies evolve along with the potential impact of global warming. Using the example of the habitat change of snow leopards and the conflicts between local people and snow leopards, we reflect on the consequences of this divergence. Results show that divergence between the political boundaries and natural habitats as well as the consequent influence on the living conditions of local people are strikingly visible, and the effects of global warming on such conflicts are apparent. The authors conclude that both notions of ‘political boundaries’ and ‘natural habitats’ are expected to come together as the SNP region is spatially configured, while ‘global warming’ seems to be relevant as an essential reference when delimiting the region in the future. Finally, the proposal for the establishment of cooperative conservation areas is presented, emphasizing the role of cooperative governance in/around national parks.

Objective This study explored the feasibility of using high‐frame‐rate ultrasound vector flow imaging (VFI) to quantitatively assess hemodynamics in atherosclerotic internal carotid artery stenosis (ICAS) by evaluating dual‐parameters, turbulence index (Tur), and wall shear stress (WSS). Their efficacy in evaluating carotid artery stenosis was also analyzed. Methods Fifty‐nine patients with ICAS were enrolled. B‐mode ultrasound and V Flow (a high‐frame‐rate VFI) were performed using the Resona R9 system. The stenosis rate was measured in grayscale mode, whereas the time‐averaged Tur index, the time‐averaged WSS (WSSmean), and maximum WSS (WSSmax) around stenosis were measured. The combined diagnostic efficacy of Tur inand WSS was also investigated. Results Compared to proximal to stenosis (Tur index, 2.88% ± 3.65%), highly disordered blood flow was observed in the stenotic (23.17% ± 15.52%, p < 0.001) and distal segment (25.86% ± 17.29%, p < 0.001). WSSmax ([11.91 ± 6.73] vs. [4.43 ± 5.4] Pa, p < 0.001) and WSSmean ([3.42 ± 2.67] vs. [0.86 ± 1.21] Pa, p < 0.001) were significantly bigger in stenotic than those in the distal segment. The differences in the ratio WSSmax/Tur or WSSmean/Tur among different segments around stenosis were statistically significant (p < 0.001). The combination of Tur index and WSS had the best diagnostic performance in ICAS (AUC, 0.899). Conclusion The application of Tur index and WSS for quantitative assessment of ICAS hemodynamic changes is feasible, with the combined evaluation of these two parameters providing incremental diagnostic value for carotid artery stenosis. VFI‐based dual quantitative parameters may offer promising noninvasive diagnostic tools for carotid artery stenosis in high‐stroke‐risk populations. Evaluation of hemodynamics around atherosclerotic carotid stenosis using turbulence and wall shear stress based on ultrasound vector flow imaging may offer promising noninvasive diagnostic tools for high‐stroke‐risk patients with carotid artery stenosis.

Landslides are occurring more frequently in China under the conditions of extreme rainfall and changing climate, according to News reports. Landslide hazard assessment remains an international focus on disaster prevention and mitigation, and it is an important step for compiling and quantitatively characterizing landslide damages. This paper collected and analyzed the historical landslide events data of the past 60 years in China. Validated by the frequencies and distributions of landslides, nine key factors (lithology, convexity, slope gradient, slope aspect, elevation, soil property, vegetation coverage, flow, and fracture) are selected to construct landslide susceptibility (LS) empirical models by back-propagation artificial neural network method. By integrating landslide empirical models with surface multi-source geospatial and remote sensing data, this paper further performs a large-scale LS assessment throughout China. The resulting landslide hazard assessment map of China clearly illustrates the hot spots of the high landslide potential areas, mostly concentrated in the southwest. The study implements a complete framework of multi-source data collecting, processing, modeling, and synthesizing that fulfills the assessment of LS and provides a theoretical basis and practical guide for predicting and mitigating landslide disasters potentially throughout China.

Background Sense organ diseases represent the leading causes of years lived with disability. Despite its major impact, a comprehensive understanding of sense organ diseases burden remains limited. Methods Based on the data from the Global Burden of Disease Study 2021 and nighttime light exposure data from remote-sensing satellites, we did secondary analysis and described the epidemiological characteristics of sense organ diseases globally and nationally. The relationship between the specific causes of blindness and vision loss and nighttime light exposure was further explored. We assessed the trends, causes and cross-country inequalities related to sense organ diseases and forecasted the burden of disease until 2050. Results Here we show that in 2021, there are more than 2 billion prevalent cases and more than 77 million years lived with disability cases of sense organ diseases globally. Both age-related macular degeneration and near vision loss show positive correlations with nighttime light exposure. The global burden of sense organ diseases continues to rise from 1990 to 2021, primarily driven by population growth and ageing. Health inequalities exist between different countries and increase over time. Projections of years lived with disability for sense organ diseases from 2022 to 2050 show that although the age-standardized rate remains stable, the number increases significantly. Conclusions Over the past 32 years, the global burden of sense organ diseases has increased, and cross-country inequalities have intensified due to the trends of population growth and aging. Therefore, it is urgently necessary to formulate more targeted and effective prevention and management strategies. Plain language summary Sense organ diseases (SODs: vision, hearing and other sensory losses) causes the most years lived with disability (YLDs: time spent in poor health). Despite its major impact, a comprehensive understanding of SODs burden remains limited. We assessed the trends, causes and cross-country inequalities related to SODs and forecasted the burden of disease until 2050 based on the Global Burden of Disease Study 2021 and nighttime light exposure (NLE) from remote-sensing satellites. Both age-related macular degeneration and near-vision loss were positively correlated with NLE. From 1990 to 2021, the global burden of SODs rose, mainly owing to population growth and aging, with increasing health inequalities among countries. By 2050, the YLDs due to SODs will increase. Targeted strategies are essential to mitigate this growing disability burden. Ma, Zan, Li et al. assess the global burden of sense organ diseases from 1990-2021 using Global Burden of Disease data from 204 countries. Results reveal increasing global burden of sensory organ diseases linked to aging populations and nighttime light exposure, with YLDs projected to rise by 2050, underscoring the need for targeted interventions.