Error-Reduced Digital Elevation Model of the Qinghai-Tibet Plateau using ICESat-2 and Fusion Model.

The Qinghai-Tibet Plateau (QTP) holds significance for investigating Earth's surface processes. However, due to rugged terrain, forest canopy, and snow accumulation, open-access Digital Elevation Models (DEMs) exhibit considerable noise, resulting in low accuracy and pronounced data inconsistency. Furthermore, the glacier regions within the QTP undergo substantial changes, necessitating updates. This study employs a fusion of open-access DEMs and high-accuracy photons from the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2). Additionally, snow cover and canopy heights are considered, and an ensemble learning fusion model is presented to harness the complementary information in the multi-sensor elevation observations. This innovative approach results in the creation of HQTP30, the most accurate representation of the 2021 QTP terrain. Comparative analysis with high-resolution imagery, UAV-derived DEMs, control points, and ICESat-2 highlights the advantages of HQTP30. Notably, in non-glacier regions, HQTP30 achieved a Mean Absolute Error (MAE) of 0.71 m, while in glacier regions, it reduced the MAE by 4.35 m compared to the state-of-the-art Copernicus DEM (COPDEM), demonstrating its versatile applicability.

Evaluating the relative influence of climate and human activities on recent vegetation dynamics in West Bengal, India.

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.

Quantifying climate variability and regional anthropogenic influence on vegetation dynamics in northwest India.

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (-0.07 °C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 °C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R2 = 0.92), although a negative relationship is apparent between LST and vegetation (R2 = -0.83). Additionally, increased LST in the low-elevation parts of the study area impacted PET (R2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.

Plasma exosomes induce inflammatory immune response in patients with acute myocardial infarction.

Exosomes are a kind of nanoscale extracellular vesicles with diameters of 30-100 nm and act as intracellular communication vehicles to influence cellular activities. Emerging pieces of evidence have indicated that exosomes play important roles in inflammation. However, the biological roles of plasma exosomes in acute myocardial infarction (AMI) patients have remained largely unexplored. In the current study, we found the plasma exosome levels were notably increased in patients with AMI in comparison with healthy controls (HCs), and AMI exosomes could induce endothelial cell injury. Furthermore, our data demonstrated that AMI exosomes triggered a pro-inflammatory immune response, at least partly depending on the activation of the NF-ĸB signalling. Together, AMI exosomes have pro-inflammatory properties and play a significant role in inflammation in AMI patients.

Solar photovoltaic program helps turn deserts green in China: Evidence from satellite monitoring.

Solar energy is considered one of the key solutions to the growing demand for energy and to reducing greenhouse gas emissions. Thanks to the relatively low cost of land use for solar energy and high power generation potential, a large number of photovoltaic (PV) power stations have been established in desert areas around the world. Despite the contribution to easing the energy crisis and combating climate change, large-scale construction and operation of PV power stations can change the land cover and affect the environment. However, few studies have focused on these special land cover changes, especially vegetation cover changes, which hinders understanding the effects of the extensive development of solar energy. Here, we used Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA) based on Landsat images to monitor changes in vegetation abundance before and after the PV power stations deployment. To reduce the interference of PV shading on vegetation abundance estimation, we improved the vegetation (VG) fraction from SMA and developed the Photovoltaics-Adjusted Vegetation (PAVG) fraction for vegetation abundance measurements in PV power stations. Results show that PV power stations in China's 12 biggest deserts expanded from 0 to 102.56 km2 from 2011 to 2018, mainly distributed in the central part of north China. The desert vegetation in the deployment area of PV power stations presented a significant greening trend. Compared to 2010, the greening area reached 30.80 km2, accounting for 30% of the total area of PV power stations. Overall, the large-scale deployment of PV power stations has promoted desert greening, primarily due to government-led Photovoltaic Desert Control Projects and favorable climatic change. This study shows the great benefits of PV power stations in combating desertification and improving people's welfare, which bring sustainable economic, ecological and social prosperity in sandy ecosystems.

Hydrothermal Synthesis of the CuWO4/ZnO Composites with Enhanced Photocatalytic Performance.

Photocatalytic technology aiming to eliminate organic pollutants in water has been rapidly developed. In this work, we successfully synthesized CuWO4/ZnO photocatalysts with different weight ratios of CuWO4 through facile hydrothermal treatment. Crystal structures, forms, and optical properties of these as-prepared materials were investigated and analyzed. 3% CuWO4/ZnO showed the optimum photodegradation efficiency toward methylene blue under the irradiation of simulated sunlight for 120 min, the degradation rate of which was 98.9%. The pseudo-first-order rate constant of 3% CuWO4/ZnO was ∼11.3 and ∼3.5 times bigger than that of pristine CuWO4 and ZnO, respectively. Furthermore, the material exhibited high stability and reusability after five consecutive photocatalytic tests. In addition, free radical capture experiments were conducted and the possible mechanism proposed explained that the synergistic effect between CuWO4 and ZnO accelerates the photodegradation reaction. This work provides a feasible technical background for the efficient and sustainable utilization of photocatalysts in wastewater control.

High performance of boehmite/polyacrylonitrile composite nanofiber membrane for polymer lithium-ion battery.

In this study, a novel boehmite/polyacrylonitrile (BM/PAN) composite nanofiber membrane was prepared using the electrospinning technique. The physical and electrochemical properties of different contents of BM/PAN composite nanofiber membranes were investigated as separators for lithium ion batteries (LIBs). Compared to the commercial polypropylene (PP) separator, the experimental results show that the BM/PAN composite nanofiber separator possesses a unique three-dimensional (3D) interconnected structure and exhibits higher porosity, greater electrolyte up-take, higher thermal stability and better electrochemical performance in a LiCoO2/Li cell. Besides, batteries containing 30 wt% BM/PAN membranes display the highest ionic conductivity (2.85 mS cm-1), widest electrochemical stability window (5.5 V vs. Li+/Li), leading to the highest initial discharge capacity (162 mA h g-1) and the largest capacity retention ratio (90.7%) at 0.5C after 100 cycles. These findings reveal that the BM/PAN composite nanofiber membranes are promising candidates as commercial separators for high performance LIBs.

Enhanced visible light photocatalytic activity of ZnIn2S4 modified by semiconductors.

To improve the visible light photocatalytic activity of a ZnIn2S4 sample, we synthesized two kinds of coupled-photocatalysts: TiO2@ZnIn2S4 core-shell type heterostructure composites by a simple and flexible hydrothermal route using TiO2 as the precursor and CuO/ZnIn2S4 contact type heterostructure composites incorporated with different amounts of CuO by the impregnation-calcination method. These as-prepared samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-Visible absorption spectra (UV-Vis) and nitrogen adsorption measurements. An enhancement in photocatalytic activity was observed after the addition of TiO2 and CuO. It was found that the as-synthesized TiO2@ZnIn2S4 photocatalyst was more efficient than TiO2 and ZnIn2S4 in the photocatalytic degradation of methylene blue (MB). TEM images confirmed that the TiO2@ZnIn2S4 nanoparticles possessed a well-proportioned core-shell morphology. On the other hand, the effects of CuO loading amount on the crystal structure, and photocatalytic properties of CuO/ZnIn2S4 samples for MB degradation under visible light irradiation were investigated, suggesting that the introduction of CuO could influence the morphology and BET specific surface area of the ZnIn2S4 sample and enhance the visible light absorption of photocatalysts. The photocatalytic degradation performance of MB was remarkably improved in the presence of CuO/ZnIn2S4 compared to pure ZnIn2S4 and 10 mol% CuO/ZnIn2S4 was found to possess the optimal photocatalytic performance. Moreover, mechanisms for the enhanced photocatalytic activity of the TiO2@ZnIn2S4 and CuO/ZnIn2S4 composites were proposed.