As a result of the unique geographical characteristics, pastoral lifestyle, and economic conditions in Mongolia, its fragile natural ecosystems are highly sensitive to climate change and human ...activities. The normalized difference vegetation index (NDVI) was employed in this study as an indicator of the growth status of vegetation. The Sen’s slope, Mann–Kendall test, and geographical detector modelling methods were used to assess the spatial and temporal changes of the NDVI in response to variations in natural conditions and human activities in Mongolia from 1982 to 2015. The corresponding individual and interactive driving forces, and the optimal range for the maximum NDVI value of vegetation distribution were also quantified. The area in which vegetation was degraded was roughly equal to the area of increase, but different vegetation types behaved differently. The desert steppe and the Gobi Desert both in arid regions have degraded significantly, whereas the meadow steppe and alpine steppe showed a significant upward trend. Precipitation can satisfactorily account for vegetation distribution. Changes of livestock quantity was the dominant factor influencing the changes of most vegetation types. The interactions of topographic factors and climate factors have significant effects on vegetation growth. In the region of annual precipitation between 331 mm and 596 mm, forest vegetation type and pine sandy soil type were found to be most suitable for the growth of vegetation in Mongolia. The findings of this study can help us to understand the appropriate range or type of environmental factors affecting vegetation growth in Mongolia, based on which we can apply appropriate interventions to effectively mitigate the impact of environmental changes on vegetation.
Selective hydrogenation of biomass to value-added products plays a crucial role in the development of renewable energy resources. Herein, two heterogonous Ni catalysts supported on mixed metal oxides ...(MMO) were prepared via structural topological transformation from hydrotalcites (LDHs) precursors with carbonate or nitrate in interlayer region (denoted as Ni/MMO-CO3 and Ni/MMO-NO3), which were featured by highly exposed Ni(111) facets as well as multifacets with abundant steps/vacancies, respectively. Interestingly, the selectivity of furfural hydrogenation can be switched by using these two catalysts: Ni/MMO-NO3 exhibits a high selectivity (97%) to furfural alcohol (FOL) (hydrogenation product of CO bond), whereas Ni/MMO-CO3 shows an exclusive selectivity (99%) toward tetrahydrofurfuryl alcohol (THFOL, hydrogenation product of both CO and furan ring). A combination study including high-resolution transmission electron microscopy (HRTEM), extended X-ray analysis fine structure (EXAFS), and in situ CO-IR confirms a large proportion of steps/edges of Ni nanoparticles in Ni/MMO-NO3 catalyst, which suppresses the adsorption of the furan ring and only facilitates activated adsorption of the CO group. In contrast, a high exposure of Ni(111) plane in Ni/MMO-CO3 promotes activated adsorption of both furan ring and CO group, resulting in the production of THFOL. In situ FT-IR measurements and DFT calculations reveal that the adsorption configuration of substrate plays a key role in determining the hydrogenation pathway and selectivity. This work provides a feasible approach for a control over hydrogenation selectivity of biomass molecules by tuning the surface microstructure of metal catalysts.
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•Mapping of Mongolian desertification, based on GEE platform.•The maximum entropy method can obtain the most accurate desertification information.•2005 was the turning year of ...desertification land area change.•Precipitation is the dominant factor of desertified land area change.
Desertification is one of the most serious ecological and environmental problems in arid regions. Low-cost, wide-ranging, and high-precision methods are essential for the formulation of appropriate strategies for quantitatively monitoring desertification. In this study, based on Google Earth Engine and Landsat images, six machine learning methods were used to monitor desertification dynamics in 1990–2020 in Mongolia. The spatiotemporal distributions and changes in desertification at different stages were analyzed using gravity center change and intensity analysis models. Subsequently, we quantitatively investigated the factors driving desertification in Mongolia. The results indicate that the maximum entropy method can obtain the most accurate assessment of the degree of desertification in comparison with the other five methods, with an accuracy of 96%. In 1990–2005, the area of desertified land increased significantly, afterward, a decreasing trend was observed. Lightly and moderately desertified lands had the highest change intensities and were most sensitive to environmental factors. Although the desertification dynamics are under the influence of both natural and anthropogenic factors, precipitation plays a dominant role in Mongolia. This study provides a comprehensive analysis of the desertification status and trends in Mongolia, and presents desertification maps that can be used to formulate preventive measures and guide desertification prevention and control.
•The albedo-MSAVI point-to-point model is the most suitable feature space model for desertification monitoring in the Sahel.•The level of desertification has reduced from 2000 to 2020 in the ...Sahel.•Light, moderate desertification lands undergoing greater change intensity.•Precipitation is the dominant factor of desertified land area change.
The transitional characteristics of desert grasslands in the Sahel determine the ecosystem’s fragility, which is extremely susceptible to the expansion and reversal of land desertification under the influence of climate change and anthropogenic activities. Accordingly, monitoring desertification dynamics is essential to combat this process. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, this study analysed the applicability of different feature space models to monitor desertification levels in the Sahel from 2000 to 2020, revealing the optimal monitoring model, analysing the spatiotemporal changes and primary driving factors. The results were as follows: In the Sahel, the albedo-modified soil adjusted vegetation index (MSAVI) based on the point-to-point model is the best for desertification monitoring, with an overall accuracy of 86.78%. Generally, the level of desertification was reduced from 2000 to 2020, the area of extremely severe desertification decreased by retreating northward; and the areas of light, moderate, and severe desertification increased slowly by expanding northward. Light, moderate, and severe desertification lands were more sensitive to climate change and anthropogenic activities, undergoing greater change intensity. Precipitation was the most influential factor determining the spatial distribution of desertification in the Sahel, with anthropogenic activities also having a significant effect on the desertification level. This study comprehensively analysed desertification patterns in the Sahel and identified the primary driving factors, which are essential to inform Sahelian desertification control mechanisms in the future.
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•The NiZn alloy catalysts were prepared by virtue of structure transformation from layered double hydroxides.•These NiZn alloy catalysts were employed for hydrodeoxygenation reaction ...of furfural to 2-methylfuran.•The optimal catalyst exhibited excellent catalytic performance with a 2-methylfuran yield of 95%.•The charge-separated metal-couple-site stabilizes a η2(C, O) configuration to improve 2-methylfuran selectivity.
Catalytic conversion of biomass furfural (FAL) to high value-added products (e.g., 2-methylfuran, MF) has attracted considerable attention, in which control over catalytic selectivity plays a crucial issue. Herein, a series of heterogonous NiZn alloy supported on the mixed metal oxides (MMO) were synthesized derived from layered double hydroxides (LDHs) with various Ni/Zn ratio (3/1, 1/1 or 1/3). XRD, HRTEM and XAFS measurements confirm that with the increase of Zn content, the corresponding NiZn alloy transforms from α-NiZn (Ni3Zn1-MMO and Ni1Zn1-MMO) to β-NiZn (Ni1Zn3-MMO). Dramatically, the selectivity of MF displays an improvement from 12% to 95% along with this phase transformation process; and the MF yield reaches to 95% over Ni1Zn3-MMO sample. A combination study including XPS, CO-DRIFTS, in situ FT-IR and DFT calculation verifies that metallic Ni serves as active site, resulting in an effective suppression of side reactions (furan ring hydrogenation). Moreover, a charge-separated metal-couple-site (Niδ--Znδ+) is on the surface of Ni1Zn3-MMO originating from electron transfer between Ni and Zn. This active structure stabilizes a η2(C, O) adsorption configuration of intermediate, in which C atom is bonded to the Niδ− site and O atom is attached to the Znδ+ site. Then, this adsorption configuration facilitates the CO cleavage, giving rise to the production of MF. This work provides an efficient and cost-effective catalyst that can simultaneously inhibit CC hydrogenation and promote CO cleavage, which would be potentially used in catalytic conversion of biomass-derived platform molecules.
Since type 2 diabetes mellitus (T2DM) is a risk factor for Alzheimer's disease (AD) and both have the same pathogenesis (e.g., insulin resistance), drugs used to treat T2DM have been gradually found ...to reduce the progression of AD in AD models. Of these drugs, glucagon-like peptide 1 receptor (GLP-1R) agonists are more effective and have fewer side effects. GLP-1R agonists have reducing neuroinflammation and oxidative stress, neurotrophic effects, decreasing Aβ deposition and tau hyperphosphorylation in AD models, which may be a potential drug for the treatment of AD. However, this needs to be verified by further clinical trials. This study aims to summarize the current information on the mechanisms and effects of GLP-1R agonists in AD.
...ASCs subjected to a dynamic culture with cyclic uniaxial strain (10% at 1 Hz) produced more MHC-positive cells with enhanced gene expression of MYOD1 and MyoG as compared to culture conditions ...with growth factor supplementation alone. ...clarification of the differentiation strategies for ASCs is crucial to gaining a greater appreciation of the differentiation processes and to modify current strategies to control the myogenic differentiation of ASCs. Perfusable adipose decellularized extracellular matrix biological scaffold co-recellularized with adipose-derived stem cells and L6 promotes functional skeletal muscle regeneration following volumetric muscle loss. Beneficial effect of IL-4 and SDF-1 on myogenic potential of mouse and human adipose tissue-derived stromal cells.
•Asian desertification land significantly changed in 30 years, mainly increasing.•Soil moisture shifts dominated Asia's desertification process.•Post-2009, desertification land reversed, highlighting ...intervention success.•Sustainable land management is key to combating Asia's desertification.
Owing to the combined effects of climate change and human activities, the type of desertification in the arid regions of Asia has undergone profound changes, and the problem of desertification has become increasingly prominent. To help address this problem, this study clarifies the transformation trends and characteristics of desertification types across Asia and discusses key areas for desertification prevention and control. Based on a series of Landsat satellite images, combined with the classification method of the desertification degree and a machine learning model, the desertification types, trends, and conversion degrees in the arid regions of Asia were systematically evaluated. In addition, the impact mechanism of climate change on the conversion between desertification types was evaluated. The primary results were as follows: (1) Various desertification types in the arid areas of Asia from 1990 to 2022 exhibited evident time series characteristics. Extremely severe desertification expanded from 1990 to 2009 and subsequently shrunk; (2) The degree of desertification in the arid regions of Asia exhibited different change characteristics in different periods, and the converted area of the same conversion type was different in different periods; (3) Different desertification conversion types in different periods have different drivers; however, overall, soil moisture has the greatest contribution to desertification conversion type. These results provide a scientific reference for the formulation of reasonable desertification prevention and control policies.
Global environment changes rapidly alter regional hydrothermal conditions, which undoubtedly affects the spatiotemporal dynamics of vegetation, especially in arid and semi-arid areas. However, ...identifying and quantifying the dynamic evolution and driving factors of vegetation greenness under the changing environment are still a challenge. In this study, gradual trend analysis was applied to calculate the overall spatiotemporal trend of the normalized difference vegetation index (NDVI) time series of Xinjiang province in China, the abrupt change analysis was used to detect the timing of breakpoint and trend shift, and two machine learning methods (boosted regression tree and random forest) were used to quantify the key factors of vegetation change and their relative contribution rate. The results have shown that vegetation has experienced overall recovery over the past 20 years in Xinjiang, and greenness increased at a rate of 17.83 10
−4
year
−1
. Cropland, grassland, and sparse vegetation were the main biome types where vegetation restoration is happening. Nearly 10% of the pixels (about 166000 km
2
) were detected to have breakpoints from 2004 to 2016 of the monthly NDVI, and most of the breakpoints were concentrated in the ecotone of various biomes. CO
2
concentration was the most prevalent environmental factor to increase vegetation greenness, because continuous emission of CO
2
greatly enhanced the fertilization effect, further promoted vegetation growth. Besides, cropland expansion and desertification control were the vital anthropogenic factors to vegetation turning “green” in Xinjiang, and most areas under anthropogenic were mainly in oasis areas. These findings provide new insights and measures for the regional response strategies and terrestrial ecosystem protection.
Pervious concrete has been widely used in parking lots and other lightweight streets. Performances of pervious concrete are strongly dependent on its pore structure characteristics. This paper ...investigates the relationship among porosity, permeability, compressive strength, durability and the pore structure characteristics of pervious concrete. The influences of basalt fiber and fine aggregate on the pervious concrete are also discussed. Pervious concrete specimens with different pore structures were prepared by combining basalt aggregate with size of 5–10 mm and 10–15 mm at different proportion. The pore structure characteristics such as area porosity, pore sizes, and pore distribution of pervious concrete were obtained and analyzed using image analysis method. Experimental results showed that the pore structure characteristics of pervious concrete have effects on its mechanical and durability behaviors. Homogeneous pore distribution and large distances between pores increase the compressive strength and improve freeze–thaw durability of pervious concrete. Due to the difference in the internal pore structure of pervious concretes, specimens with similar volumetric porosities had different permeability coefficients. A series of numerical models were regenerated through a MATLAB code using pore structural parameters derived from the image analysis method, then the numerical models were fed to ANSYS for meshing and further simulation. The comparison of the simulation and experimental results showed close accuracy, which verified the applied simulation analysis method based on image analysis technology.
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