A High-Entropy Intergrowth Layered-Oxide Cathode with Enhanced Stability for Sodium-Ion Batteries.

Layered transition metal oxides are widely considered as ideal cathode materials for SIBs. However, the existing P2 and O3 structures possess specific issues, which limit their practical applications. To address these issues, this work designed a novel intergrowth layered oxide cathode with P2 and O3 phases by implementing Cu and Ti into the structure with the formation of high-entropy cathode materials with superior performance for SIBs. The electrochemical test results show that the optimized high-entropy cathode with the P2/O3 intergrowth structure possesses a high initial discharge capacity of 157.85 mAh g-1 at 0.1 C, an excellent rate performance of 84.41 mAh g-1 at 10 C, and long-term stability with capacity retention of 83.25% after 500 cycles at 5C. Furthermore, the analysis results of ex situ XRD and in situ XRD indicate that the adverse phase transition of P2-O2 under high voltage is effectively suppressed. This work indicates that the integration of high-entropy strategy with the two-phase intergrowth structure can effectively stabilize the layered structure, suppress the slipping of transition metal layers, and improve electrochemical performance, which provides a new approach for designing high-performance and practical layered transition metal oxide cathode materials for advanced SIBs.

[Research status and rapid detection methods of antibiotic residues in agricultural products]. / å†œäº§å“æŠ—ç”Ÿç´ æ®‹ç•™çŽ°çŠ¶åŠå¿«é€Ÿæ£€æµ‹æ–¹æ³•ç ”ç©¶è¿›å±•.

Antibiotics are widely utilized in agriculture for the prevention and treatment of animal diseases. How-ever, the abuse and overuse of antibiotics progressively increase the risks of antibiotic residues and antibiotic resis-tance. The bioaccumulation and biomagnification of antibiotics through food chains will negatively affect ecological safety, and finally threaten human health. There are many shortages of traditional antibiotic detection techniques, such as complex procedures, complicated operation and time consuming, and thus are difficult to meet the demand of instant, efficient and accurate on-site detection. Therefore, it is crucial to develop rapid detection techniques of antibiotics to manage the application of antibiotics in agriculture. We reviewed the utilization, and management of antibiotics in animal husbandry, residual characteristics, and potential hazards of antibiotics in agricultural products, summarized the advancements in rapid detection techniques of antibiotics in agricultural products over the past five years, compared the advantages and disadvantages of different rapid detection techniques, and prospected the future development in this area. This review would provide a valuable reference to the control and point-of-care test of antibiotics in agricultural products.

Effects of different grassland utilization methods on the germinable soil seed bank of the Hulunbuir meadow steppe.

Seed banks are crucial regenerative resources for aboveground vegetation. The pattern of their changes holds immense significance in understanding alterations in the belowground seed bank. This understanding is pivotal for uncovering both short-term and long-term shifts in plant communities. Additionally, it contributes to the restoration of grassland ecosystems. To better protect grassland biodiversity and provide a theoretical basis for the restoration of degraded grasslands, in this study, the germination characteristics of soil seed banks in free-grazed, enclosed and mown areas were compared, and the results were combined with those of previous studies for a comprehensive analysis. The density of soil seed bank and perennial forage soil seed bank were significantly affected by different grassland utilization and soil depths. Grazing and enclosure grassland utilization methods increased the content of the soil seed bank, and mowing reduced the content of the seed bank. The soil seed bank density of perennial grasses accounted for the highest proportion under grazing, followed by mowing, and its lowest proportion was observed in the enclosures. Grazing not only facilitated the germination of the perennial grass seed bank but also substantially augmented its content. Mowing inhibited the germination of the upper growth grasses seed bank, which was particularly significant in the 0-2 cm soil layer under grazing. The content of the upper growth grasses seed bank affected the total seed bank to a certain extent, mainly in the 5-10 cm layer. The general correlations among the perennial grasses, upper growth grasses and soil germination seed bank resulted in 84.58% information extraction, and this information has practical significance for grassland ecological restoration.

The extreme wet and large precipitation size increase carbon uptake in Eurasian meadow steppes: Evidence from natural and manipulated precipitation experiments.

The distribution of seasonal precipitation would profoundly affect the dynamics of carbon fluxes in terrestrial ecosystems. However, little is known about the impacts of extreme precipitation and size events on ecosystem carbon cycle when compared to the effects of average precipitation amount. The study involved an analysis of carbon fluxes and water exchange using the eddy covariance and chamber based techniques during the growing seasons of 2015-2017 in Bayan, Mongolia and 2019-2021 in Hulunbuir, Inner Mongolia, respectively. The components of carbon fluxes and water exchange at each site were normalized to evaluate of relative response among carbon fluxes and water exchange. The investigation delved into the relationship between carbon fluxes and extreme precipitation over five gradients (control, dry spring, dry summer, wet spring and wet summer) in Hulunbuir meadow steppe and distinct four precipitation sizes (0.1-2, 2-5, 5-10, and 10-25 mm d-1) in Bayan meadow steppe. The wet spring and summer showed the greatest ecosystem respiration (ER) relative response values, 76.2% and 73.5%, respectively, while the dry spring (-16.7%) and dry summer (14.2%) showed the lowest values. Gross primary production (GPP) relative response improved with wet precipitation gradients, and declined with dry precipitation gradients in Hulunbuir meadow steppe. The least value in net ecosystem CO2 exchange (NEE) was found at 10-25 mm d-1 precipitation size in Bayan meadow steppe. Similarly, the ER and GPP increased with size of precipitation events. The structural equation models (SEM) satisfactorily fitted the data (χ2 = 43.03, d.f. = 11, p = 0.215), with interactive linkages among soil microclimate, water exchange and carbon fluxes components regulating NEE. Overall, this study highlighted the importance of extreme precipitation and event size in influencing ecosystem carbon exchange, which is decisive to further understand the carbon cycle in meadow steppes.

Extreme wet precipitation and mowing stimulate soil respiration in the Eurasian meadow steppe.

The imbalance of terrestrial carbon (C) inputs versus losses to extreme precipitation can have consequences for ecosystem carbon balances. However, the current understanding of how ecosystem processes will respond to predicted extreme dry and wet years is limited. The current study was conducted for three years field experiment to examine the effects of environmental variables and soil microbes on soil respiration (Rs), autotrophic respiration (Ra) and heterotrophic respiration (Rh) under extreme wet and dry conditions in mowed and unmowed grassland of Inner Mongolia. Across treatments (i.e. control, dry spring, wet spring, dry summer and wet summer), the mean of Rs was increased by 24.9 % and 24.1 % in the wet spring and wet summer precipitation treatments, respectively in mowed grassland. In other hand, the mean of Rs was decreased by -22.1 % and -3.5 % in dry spring and dry summer precipitation treatments, respectively in mowed grassland. The relative contribution of Rh and Ra to Rs showed a significant (p < 0.05) change among simulated precipitation treatments with the highest value (76.18 %) in wet summer and 26.41 % in dry summer, respectively under mowed grassland. Rs was significantly (p < 0.05) affected by the interactive effect of extreme precipitation and mowing treatments in 2020 and 2021. The effects of precipitation change via these biotic and abiotic factors explained by 52 % and 81 % in Ra and Rh, respectively in mowed grassland. The changes in microbial biomass carbon (MBC) and nitrogen (MBN) had significant (p < 0.05) direct effects on Rh in both mowed and unmowed grasslands. The influence of biotic and abiotic factors on Rs was stronger in mowed grasslands with higher standardized regression weights than in unmowed grassland (0.78 vs. 0.69). These findings highlight the importance of incorporating extreme precipitation events and mowing in regulating the responses of C cycling to global change in the semiarid Eurasian meadow steppe.

[Research progress on sensitivity of indices for ecotoxicological assays using rotifers.] / è½®è™«ç”Ÿæ€æ¯’ç†å­¦æµ‹è¯•æŒ‡æ ‡çš„æ•æ„Ÿæ€§ç ”ç©¶è¿›å±•.

Human activities have severely polluted environments during industrialization. Rotifers are commonly used as model species for ecotoxicological assays. The sensitivities of ecotoxicological indices of rotifers highly depend on different pollutants. We summarized available ecotoxicological indices of rotifers, and reviewed their sensitivity to commonly investigated pollutants. Under the stress of heavy metals, the life-table demographic parameters, physiological and biochemical indices generally show high sensitivity. In response to persistent organic pollutants, sexual indices generally show higher sensitivity than asexual ones. Some studies showed that swimming speed revealed higher sensitivity after exposure to several pollutants compared with life-table demographic and population growth indices. We suggested to consider swimming speed of rotifer as an alternative index for ecotoxicological assays. Overall, this study would provide a guideline for rotifer ecotoxicological studies in the future.

Estimating Grassland Carbon Stocks in Hulunber China, Using Landsat8 Oli Imagery and Regression Kriging.

Accurately estimating grassland carbon stocks is important in assessing grassland productivity and the global carbon balance. This study used the regression kriging (RK) method to estimate grassland carbon stocks in Northeast China based on Landsat8 operational land imager (OLI) images and five remote sensing variables. The normalized difference vegetation index (NDVI), the wide dynamic range vegetation index (WDRVI), the chlorophyll index (CI), Band6 and Band7 were used to build the RK models separately and to explore their capabilities for modeling spatial distributions of grassland carbon stocks. To explore the different model performances for typical grassland and meadow grassland, the models were validated separately using the typical steppe, meadow steppe or all-steppe ground measurements based on leave-one-out crossvalidation (LOOCV). When the results were validated against typical steppe samples, the Band6 model showed the best performance (coefficient of determination (R2) = 0.46, mean average error (MAE) = 8.47%, and root mean square error (RMSE) = 10.34 gC/m2) via the linear regression (LR) method, while for the RK method, the NDVI model showed the best performance (R2 = 0.63, MAE = 7.04 gC/m2, and RMSE = 8.51 gC/m2), which were much higher than the values of the best LR model. When the results were validated against the meadow steppe samples, the CI model achieved the best estimation accuracy, and the accuracy of the RK method (R2 = 0.72, MAE = 8.09 gC/m2, and RMSE = 9.89 gC/m2) was higher than that of the LR method (R2 = 0.70, MAE = 8.99 gC/m2, and RMSE = 10.69 gC/m2). Upon combining the results of the most accurate models of the typical steppe and meadow steppe, the RK method reaches the highest model accuracy of R2 = 0.69, MAE = 7.40 gC/m2, and RMSE = 9.01 gC/m2, while the LR method reaches the highest model accuracy of R2 = 0.53, MAE = 9.20 gC/m2, and RMSE = 11.10 gC/m2. The results showed an improved performance of the RK method compared to the LR method, and the improvement in the accuracy of the model is mainly attributed to the enhancement of the estimation accuracy of the typical steppe. In the study region, the carbon stocks showed an increasing trend from west to east, the total amount of grassland carbon stock was 79.77 ⅹ 104 Mg C, and the mean carbon stock density was 47.44 gC/m2. The density decreased in the order of temperate meadow steppe, lowland meadow steppe, temperate typical steppe, and sandy steppe. The methodology proposed in this study is particularly beneficial for carbon stock estimates at the regional scale, especially for countries such as China with many grassland types.

[CO, release characteristics from Stipa baicalensis meadow steppe in the Hulunbeir region, Inner Mogolia, China].

Based on the measurement of soil CO2 evolution with the Li-8150 from June 2009 to June 2010, the characteristics of soil CO2 flux from the Stipa baicalensis meadow steppe in the Hulunbeir, Inner Mongolia were analyzed. The daily dynamics of soil respiration rate in this study area presented a peak curve in growing season, the daily maximum value appeared in 13:00-15:00 p. m., while the minimum value appeared in 5:00-6:00 a. m. The soil respiration had obviously seasonal dynamics, similar with the dynamics of soil temperature and soil water content. The relationships of soil respiration with soil temperature and soil water content could be better expressed with linear or exponential-power equation. Using the Van' t Hoff exponential equation to fit soil respiration and soil temperature, the results showed that they all had good exponential regression relationships in growing season and in non-growing season. Q10 was slightly different at different depths, varying from 1.68 to 2.14 in growing season and from 3.03 to 3.60 in non-growing season. The effect of soil temperature on soil respiration was more sensitive in non-growing season than in growing season. There was significant a correlation between soil respiration and soil water content at the depth of 10 cm. The annual soil CO2 fluxes were 488.47 g C x a(-1) and 507.20 g C x a(-1) in 2009 and 2010, respectively. The contribution of soil respiration in growing season to the annual soil CO2 flux was about 90%.

[Spatiotemporal characteristics of MODIS NDVI in Hulunber Grassland].

Time-series MODIS NDVI datasets from 2000 to 2008 were used to study the spatial change trend, fluctuation degree, and occurrence time of the annual NDVImax of four typical grassland types, i.e., lowland meadow, temperate steppe, temperate meadow steppe, and upland meadow, in Hulunber Grassland. In 2000-2008, the vegetation in Hulunber Grassland presented an obvious deterioration trend. The mean annual NDVImax of the four grassland types had a great fluctuation, especially in temperate steppe where the maximum change in the mean value of annual NDVImax approximated to 50%. As for the area change of different grade grasslands, the areas with NDVImax between 0.4 and 1 accounted for about 91% of the total grassland area, which suggested the good vegetation coverage in the Grassland. However, though the areas with NDVImax values in (0.4, 0.8) showed an increasing trend, the areas with NDVImax values in (0.2, 0.4) and (0.8, 1) decreased greatly in the study period. Overall, the deteriorating grassland took up about 66.25% of the total area, and the restoring grassland took the rest. There was about 62.85% of the grassland whose NDVImax occurred between the 193rd day and the 225th day in each year, indicating that this period was the most important vegetation growth season in Hulunber Grassland.