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The effects of deoxidation methods on the inclusion characteristics and corrosion behaviour of high-strength low-alloy steels were examined in marine environments using various microcharacterisation techniques and first-principles calculations. After Ca treatment, MnS–MgO–Al2O3inclusions were modified to CaS–MgO–Al2O3and microcrevices were existed at the interface between inclusions and Fe. After Zr–Ti-RE deoxidation, spherical CaS + TiN + ZrO2+MgAl2O4+(Ca, La) Al3O7inclusions appeared. (Ca, La)Al3O7in steel displayed similar mechanical properties to Fe, reducing the degree of lattice distortion and the formation of microcrevices around the inclusions. Micro-galvanic corrosion between Fe and MnS accelerated the localised corrosion rate and promoted the formation of large pits on the surface. However, the chemical activity of CaS resulted in dissolution of the inclusion, which relatively inhibited the localised corrosion propagation. The enrichment of Cr in the rust layer after Zr–Ti-RE deoxidation improved the compactness, contributed to a reduction in the localised corrosion rate and long-term corrosion rate. Finally, the underlying mechanism influencing corrosion behaviour was established.

The effects of hydrostatic pressure, dissolved oxygen, temperature and flow velocity, and their interaction on the corrosion rates of E690 high-strength steel (HSS) in simulated marine environments were studied using response surface methodology. The results show that the flow velocity exerts the most significant influence on the corrosion rate of E690 HSS. Consequently, the corrosion behavior of E690 HSS under varying flow velocities were analyzed profoundly from initial pitting corrosion to long-term corrosion properties. The results indicate that the flow state facilitates the mass transfer and enhances the adsorption tendency of Cl−by enhancing the electrochemical activity of the steel surface. These factors accelerate the electrochemical reactions, resulting in increased pitting density, depth and the long-term corrosion rates in dynamic seawater environments.

Based on the five main activation mechanisms, this study explored the potential activating elements in Al-based sacrificial anodes (SAs) combining electrochemical experiments and theoretical calculation. Mn, Y, Zr, Nb, and Ta, aligning with several activation mechanisms, are expected to be the potential activating elements besides the acknowledged activating elements (In, Sn, Ga, Zn, Bi). In addition, the negative shift of potential effect of In to Al matrix is denied both experimentally and theoretically. This study will contribute to establish a comprehensive understanding for the development of Al SAs.

Temperature is an essential parameter in the silicon-based micro electro mechanical system (MEMS) fabrication process, and the uneven temperature distribution on a wafer surface could significantly impact the whole fabrication process. This research aims to observe the wire bonding system’s heating process from 30 °C to 110 °C. A temperature sensor network consisting of multiple fiber Bragg gratings (FBGs) is proposed for real-time wafer surface temperature monitoring. The temperature points measured by FBG sensors are used to construct the temperature distribution of the entire wafer surface, enabling tracking of the hotspots during the heating processes. Additionally, a comparative analysis of the FBG sensor network’s results was conducted using those gathered by infrared thermal imager and thermocouple (TC) sensors. The results indicate the existence of a temperature gradient along the wafer’s surface in the radial direction, with a maximum temperature difference of 11.94 °C and the temperature distribution taking the shape of approximate concentric circles. The FBG sensor network offers a clear and intuitive illustration of the wafer’s surface temperature distribution during heating, providing real-time responses. Therefore, the proposed temperature measurement network based on FBG sensors can effectively monitor the temperature defects on the wafer surface during the MEMS process.

Metatranscriptomics uncovers the dynamic expression of functional genes in soil environments, providing insights into the intricate metabolic activities within microbial communities.mRNA enrichment from soil samples remains a formidable challenge due to the presence of inhibitory compounds, low RNA yields, and sample heterogeneity.Soil metatranscriptomics unravels the expression levels of genes involved in the real-time molecular dialogues between plants and rhizobionts, uncovering the dynamics of nutrient exchange, symbiotic interactions, and plant-microbe communication.Metatranscriptomics unlocks the active expression of the soil resistome, elucidating the mechanisms of resistance dissemination under anthropogenic activities.Metatranscriptomics provides comprehensive data regarding the identification, quantification, and evolutionary history of RNA viruses. Metatranscriptomics is a cutting-edge technology for exploring the gene expression by, and functional activities of, the microbial community across diverse ecosystems at a given time, thereby shedding light on their metabolic responses to the prevailing environmental conditions. The double-RNA approach involves the simultaneous analysis of rRNA and mRNA, also termed structural and functional metatranscriptomics. By contrast, mRNA-centered metatranscriptomics is fully focused on elucidating community-wide gene expression profiles, but requires either deep sequencing or effective rRNA depletion. In this review, we critically assess the challenges associated with various experimental and bioinformatic strategies that can be applied in soil microbial ecology through the lens of functional metatranscriptomics. In particular, we demonstrate how recent methodological advancements in soil metatranscriptomics catalyze the development and expansion of emerging research fields, such as rhizobiomes, antibiotic resistomes, methanomes, and viromes. Our review provides a framework that will help to design advanced metatranscriptomic research in elucidating the functional roles and activities of microbiomes in soil ecosystems.

Background: The short-term prognosis of stroke patients is mainly influenced by the severity of the primary disease at admission and the trend of disease development during the acute phase (1–7 days after admission). Objective: The aim of this study is to explore the relationship between the bioelectrical impedance analysis (BIA) parameter trajectories during the acute phase of stroke patients and their short-term prognosis, and to investigate the predictive value of the prediction model constructed using BIA parameter trajectories and clinical indicators at admission for short-term prognosis in stroke patients. Methods: A total of 162 stroke patients were prospectively enrolled, and their clinical indicators at admission and BIA parameters during the first 1–7 days of admission were collected. A Group-Based Trajectory Model (GBTM) was employed to identify different subgroups of longitudinal trajectories of BIA parameters during the first 1–7 days of admission in stroke patients. The random forest algorithm was applied to screen BIA parameter trajectories and clinical indicators with predictive value, construct prediction models, and perform model comparisons. The outcome measure was the Modified Rankin Scale (mRS) score at discharge. Results: PA in BIA parameters can be divided into four separate trajectory groups. The incidence of poor prognosis (mRS: 4–6) at discharge was significantly higher in the “Low PA Rapid Decline Group” (85.0%) than in the “High PA Stable Group “ (33.3%) and in the “Medium PA Slow Decline Group “(29.5%) (all P< 0.05). In-hospital mortality was the highest in the “Low PA Rapid Decline Group” (60%) compared with the remaining trajectory groups (P< 0.05). Compared with the prediction model with only clinical indicators (Model 1), the prediction model with PA trajectories (Model 2) demonstrated higher predictive accuracy and efficacy. The area under the receiver operating characteristic curve (AUC) of Model 2 was 0.909 [95% CI 0.863, 0.956], integrated discrimination improvement index (IDI), 0.035 (P< 0.001), and net reclassification improvement (NRI), 0.175 (P= 0.031). Conclusion: PA trajectories during the first 1–7 days of admission are associated with the short-term prognosis of stroke patients. PA trajectories have additional value in predicting the short-term prognosis of stroke patients.

Objective:Recent studies have revealed that hemoglobin beta (HBB) plays an important role not only in blood disorders but also in malignancies. The aim of this study is to investigate the clinical significance, diagnostic value, and biological function of HBB in lung cancer. Methods:HBB expression was examined in lung cancer tissues and plasma samples using quantitative real-time polymerase chain reaction, and its relationship with clinical pathological characteristics was analyzed. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic value of HBB in lung cancer. The proliferation of A549 and SPCA1 cells was analyzed using a cell counting kit-8 assay and protein expressions were detected by western blot. Results:The expressions of HBB were found to be down-regulated in both lung cancer tissues and plasma samples. Notably, plasma HBB levels were significantly elevated in postoperative samples when compared to their preoperative counterparts. Across 66 cases of lung cancer tissues, a correlation was observed between HBB levels and both gender and tumor, node, metastasis staging. ROC curve analysis further confirmed the high diagnostic potential of HBB expression in lung cancer. Moreover, the combination of HBB and carcinoembryonic antigen (CEA) had greater significance than HBB or CEA alone in the diagnosis of lung cancer. Knocking out or overexpressing HBB could affect lung cancer cell proliferation through the ERK1/2 signaling pathway. Conclusion:HBB can serve as a novel biomarker for the diagnosis and monitoring of lung cancer, regulating cell proliferation via the ERK1/2 pathway and playing a pivotal role in the oncogenesis and progression of the disease.

A novel series of peptidomimetic aldehydes was designed and synthesized to target 3C protease (3Cpro) of enterovirus 71 (EV71). Most of the compounds exhibited high antiviral activity, and among them, compound 18pdemonstrated potent enzyme inhibitory activity and broad-spectrum antiviral activity on a panel of enteroviruses and rhinoviruses. The crystal structure of EV71 3Cproin complex with 18pdetermined at a resolution of 1.2 Å revealed that 18pcovalently linked to the catalytic Cys147 with an aldehyde group. In addition, these compounds also exhibited good inhibitory activity against the 3CLproand the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), especially compound 18p(IC50= 0.034 μM, EC50= 0.29 μM). According to our previous work, these compounds have no reasons for concern regarding acute toxicity. Compared with AG7088, compound 18palso exhibited good pharmacokinetic properties and more potent anticoronavirus activity, making it an excellent lead for further development.

Precisely predict the current on the node circuit in advance, which can facilitate the manager to manage and control the risk in advance. The current, voltage, residual current, cable temperature, ambient temperature, and ambient humidity on the circuit constitute a multi-dimensional sequence characteristic sequence data. This paper proposes an improved Long Short-Term Memory (LSTM) cyclic neural network method, which combines multi-dimensional Train the neural network in a specific way to obtain the LSTM current prediction model. The experiment is validated with the perception data in an intelligent building, and compared with the classic neural network and Recurrent Neural Network (RNN) prediction method. The experimental results show that, compared with the prediction methods such as BP neural network and RNN network, the multi-dimensional LSTM has a higher accuracy in predicting the current in the circuit, and the MSE index is as low as 0.5. And this method can detect potential electrical fire hazards and give early warning 1–2 time intervals in advance to avoid electrical fires.

An efficient regioselective palladium(II)-catalyzed C(sp2)–H 4-acetoxylation of tryptophan and tryptophan-containing peptides is described. This transformation achieves the direct construction of C–O bonds at the tryptophan C4-position and features good functional group tolerance. The 4-hydroxyl compound was obtained by removing acetyl after C4-acetoxylation of tryptophan derivatives and tryptophan-containing dipeptides. This method provides a novel strategy for the synthesis of 4-substituted tryptophan derivatives and modification of tryptophan-containing peptides.

Soil ammonia-oxidizing archaea (AOA) play a crucial role in converting ammonia to nitrite, thereby mobilizing reactive nitrogen species into their soluble form, with a significant impact on nitrogen losses from terrestrial soils. Yet, our knowledge regarding their diversity and functions remains limited. In this study, we reconstructed 97 high-quality AOA metagenome-assembled genomes (MAGs) from 180 soil samples collected in Central Germany during 2014–2019 summers. These MAGs were affiliated with the order Nitrososphaeralesand clustered into four family-level clades (NS-α/γ/δ/ε). Among these MAGs, 75 belonged to the most abundant but least understood δ-clade. Within the δ-clade, the amoAgenes in three MAGs from neutral soils showed a 99.5% similarity to the fosmid clone 54d9, which has served as representative of the δ-clade for the past two decades since even today no cultivated representatives are available. Seventy-two MAGs constituted a distinct δ sub-clade, and their abundance and expression activity were more than twice that of other MAGs in slightly acidic soils. Unlike the less abundant clades (α, γ, and ε), the δ-MAGs possessed multiple highly expressed intracellular and extracellular carbohydrate-active enzymes responsible for carbohydrate binding (CBM32) and degradation (GH5), along with highly expressed genes involved in ammonia oxidation. Together, these results suggest metabolic versatility of uncultured soil AOA and a potential mixotrophic or chemolithoheterotrophic lifestyle among 54d9-like AOA.

High-manganese steels, due to their unique combination of strength and elongation, have been widely used in aerospace, petrochemical and rail transportation. However, a prevalent challenge in advancing the utilization of high-manganese steel is the need for corresponding welding consumables. The deformation mechanism of high-manganese steel encompasses three primary mechanisms: martensitic phase transformation, twinning and dislocation movement. The stacking fault energy (SFE) is a critical factor in determining the dominant deformation mechanism in high-manganese austenitic steels. Furthermore, the magnitude of the SFE is principally influenced by the alloying elements present and the temperature at which deformation occurs. Alloying elements can significantly influence the microstructure and mechanical properties of wire arc additive manufacturing (WAAM) of high-manganese steels. The metal powder-cored wire of high-manganese steel with full austenitic microstructure was designed in this paper. The effects of C, Mn and Cu on the microstructure, solute segregation and properties of WAAM of high-manganese steels were systematically investigated by optical microscopy, electron microscopy and mechanical testing. The influence of SFE on the microstructure characteristics and work hardening behaviour were also studied. The results showed that as an increase of the C content, the tensile strength and elongation of deposited metals were improved. The corresponding low-temperature impact toughness increased at first and then decreased. The highest value of impact toughness was 68.5 J with 0.79%C. As the Mn increased, the strength decreased, the elongation increased and the low-temperature impact toughness value displayed an initial increase followed by a subsequent decrease. With the increase of Cu, the yield strength and elongation improved significantly. The tensile strength exhibited a marginal initial increase followed by a decrease, whereas the change was not substantial. In contrast, the low-temperature impact toughness value showed a substantial increase followed by a decrease. The developed M3 wire containing 1.10%C-21%Mn-0.3%Cu possessed the optimum performance (yield strength of 551 MPa, tensile strength of 909 MPa, elongation at break of 30.2%, impact toughness value of 57.5J), with the good mechanical stability and low solidification cracking sensitivity.

Maleimide is widely applied in many fields, especially in antibody–drug conjugations and peptide drugs. Herein, we develop a strategy for the C–H alkenylation of tryptophan and tryptophan-containing peptides, providing a synthetic route of decorating maleimide on peptides. The method has a high tolerance of functional groups and protecting groups. Furthermore, this method was applied to prepare peptide conjugation with molecules such as drugs and fluorescence probes. Moreover, macrocyclic peptides were obtained via this reaction.

Interfaces between materials provide an intellectually rich arena for fundamental scientific discovery and device design. However, the frustration of magnetization and conductivity of perovskite oxide films under reduced dimensionality is detrimental to their device performance, preventing their active low-dimensional application. Herein, by inserting the ultrathin 4d ferromagnetic SrRuO3layer between ferroelectric BaTiO3layers to form a sandwich heterostructure, we observe enhanced physical properties in ultrathin SrRuO3films, including longitudinal conductivity, Curie temperature, and saturated magnetic moment. Especially, the saturated magnetization can be enhanced to ∼3.12 μB/Ru in ultrathin BaTiO3/SrRuO3/BaTiO3trilayers, which is beyond the theoretical limit of bulk value (2 μB/Ru). This observation is attributed to the synergistic ferroelectric proximity effect (SFPE) at upper and lower BaTiO3/SrRuO3heterointerfaces, as revealed by the high-resolution lattice structure analysis. This SFPE in dual-ferroelectric interface cooperatively induces ferroelectric-like lattice distortions in RuO6oxygen octahedra and subsequent spin-state crossover in SrRuO3, which in turn accounts for the observed enhanced magnetization. Besides the fundamental significance of interface-induced spin–lattice coupling, our findings also provide a viable route to the electrical control of magnetic ordering, taking a step toward low-power applications in all-oxide spintronics.

Anti-reflection layers, which comprise one or more films of dielectric or metallic materials, are widely used in many applications, such as solar cells, to reduce unwanted reflection loss or overcome undesirable color features. Many conventional anti-reflection layers are based on multilayer interference, index matching, surface texturing and plasmonic phenomena. Here, we present a novel paradigm that suppresses the reflection of light from a metallic surface by using an ultrathin, conductive CuO coating. This new anti-reflection concept relies on the strong inference inside the ultrathin, absorptive CuO coating. We derive the optimal conditions for minimal reflectance and expound how the film thickness impacts the reflectance. It is shown that zero reflectance can almost be obtained at a wavelength of ca. 550 nm over a wide range of incident angles. As a proof-of-concept experiment, a transparent conductive electrode with a record figure of merit was fabricated based on a CuO/Cu double-layer structure, of which CuO was used to tune the chromaticity of the resultant TCEs and protect Cu from oxidation. This technology has the potential for many applications, especially for photoelectrochemical cells, which can be used to simultaneously enhance the total absorption and reduce the minority charge carrier collection length. A simple material for reducing reflection from shiny surfaces has been developed by scientists in China. Reflection of light from a surface reduces the optical intensity transmitted to an underlying detector. Stacks of thin films on the surface can reduce reflection by making the backscattered light from each layer destructively interfere, but fabricating numerous layers with very precise thicknesses can be tricky. Now, Xiaoli Wang from the National Center for Nanoscience and Technology, Beijing, and co-workers have taken a different approach in which reflection is suppressed by harnessing the strong inference inside a single ultrathin layer of absorptive copper oxide. The thin copper oxide coating could improve the efficiency of optoelectronic devices such as solar cells. The team demonstrated the potential of their approach by constructing transparent conductive electrodes, which are needed in optoelectronics. we present a novel paradigm that suppresses the reflection of light from a metallic surface by using an ultrathin CuO coating. This antireflection concept relies on the strong inference inside the ultrathin absorptive CuO coating. We derive the optimal conditions for minimum reflectance and expound how the film thickness impacts the reflectance. Almost zero reflectance can be obtained at wavelength of ca. 550 nm over a wide range of incident angles. This technology has the potential for many applications, especially viable for photoelctrochemical cells, which requires strong absorption and short carrier collection length.

The addition of Ca in anaerobic digestion will passivate the heavy metals in digestate. The effects of CaCl2, Ca(OH)2and CaCO3addition on the anaerobic digestion process and the speciation changes of Cu and Zn in solid fraction of anaerobic digestate (SFD) after digestion were studied. Then the effects of Ca-containing solid fraction digestate (SFD-Ca) application on the speciation changes of Cu and Zn in soil and the effects of ryegrass on the enrichment of Cu and Zn were also explored through pot experiments. The results indicated that: The addition of Ca(OH)2was beneficial to the transfer of Cu and Zn from the liquid fraction of anaerobic digestate (LFD) to SFD, and the transfer effect was the best. The transfer amount of Cu and Zn increased by about 10.0% and 4.2%, respectively, compared with the blank group. The SFD-Ca promoted the increase of biomass, inhibited the enrichment of Cu and Zn by ryegrass, and the effect of a high concentration of Ca(OH)2was the best. Ryegrass biomass increased by 19.7%, and the enrichment of Cu and Zn decreased by 39.3% and 31.1%, respectively. High concentration of Ca(OH)2-containing solid fraction digestate (SFD-Ca(OH)2) had the best passivation effect on Cu and Zn in soil, the residual state of Cu and Zn in soil increased by 4.3% and 7.8%, respectively. Adding a high concentration of Ca(OH)2had a positive effect on ryegrass biomass and reduced the risk of Cu and Zn when SFD was used as biofertilizer.

•This is the first time to verify the targeting regulation of miR-96-5p on LDB2.•MiR-96-5p/LDB2 regulates cellular behaviors through ERK1/2 signaling pathway in lung cancer H1299 cell.

Objective: To observe the effect of citicoline in promoting the repair of acute peripheral nerve injury in rats. Method: A total of 64 adult SD rats were equally randomized into citicoline group and blank control group. The rat models of acute sciatic nerve injury were established by making an incision at the right thigh for sharp sciatic nerve transection. In the citicoline group, citicoline (80mg/ml) was applied for intraoperative and postoperative treatment; in the blank control group, an equal volume of isotonic saline was administered. Specimens were sampled in the first and third postoperative months for gross and microscopic examination. Electrophysiological examination of the nerve was performed in the third postoperative month, along with motor function scoring. Results: Gross and microscopic examination in the third postoperative month showed that the improvements in nerve edema and adhesion were significantly better in the citicoline group than in the control group. Electrophysiological assessment showed that the latency was shorter, the amplitude was higher, and the nerve conduction velocity was faster in citicoline group than in control group in the third postoperative month (all P<0.05). The time required for the MFS score reaching 2 and 1 was also significantly shorter in citicoline group (P<0.05 compared with control group). Conclusion: Citicoline has certain effects in rehabilitating the acute peripheral nerve injuries.

Nonlinear matrix equation X-∑i=1mAi∗X-1Ai=Qhas wide applications in control theory, dynamic planning, interpolation theory and random filtering. In this paper, a fixed-point accelerated iteration method is proposed, and based on the basic characteristics of the Thompson distance, the convergence and error estimation of the proposed algorithm are proved. Numerical comparison experiments show that the proposed algorithm is feasible and effective.

We investigate charge transfer, orbital reconstruction, and the emergence of exchange bias in (La,Sr)MnO3/LaNiO3heterostructures. We demonstrate that charge transfer from Mn3+ions to Ni3+ions is accompanied by the formation of hybridized Mn/Ni 3z2– r2orbits at the interface, instead of strain-stabilized Mn and Ni x2– y2orbits in the bulk films. In the heterostructures with ultrathin LaNiO3, orbital reconstruction induced by charge transfer results in magnetization frustration of (La,Sr)MnO3at the interface. But the strain effect exerted by the growth of the LaNiO3top layer plays a dominant role on orbital reconstruction in the heterostructures with thick LaNiO3, stabilizing 3z2– r2orbits. In this case, robust spin glass, associated with larger magnetization frustration, accounts for the exchange bias effect. Our work builds a bridge between the microscopic electronic structure and the macroscopic magnetic property, providing the possibility of manipulating the exotic states with the aid of strain engineering in oxide-based electronics.

Coarse-resolution satellite albedo products are important for climate change and energy balance research because of their capability to characterize the spatiotemporal patterns of land surface parameters at both the regional and global scales. The accuracy of coarse-resolution products is usually assessed via comparison with in situmeasurements. The key issue in the comparison of remote sensing observations with in situmeasurements is scaling and uncertainty. This paper presents a strategy for validating 1-km-resolution remote sensing albedo products using field measurements and high-resolution remote sensing observations. Field measurements were collected to calibrate the high-resolution (30 m) albedo products derived from HJ-1a/b images. Then, the calibrated high-resolution albedo maps were resampled (i.e., upscaled) to assess the accuracy of the coarse-resolution albedo products. The samples of field measurements and high-resolution pixels are based on an uncertainty analysis. Two types of coarse-resolution albedo datasets, from global land surface satellite (GLASS) and moderate-resolution imaging spectroradiometer (MODIS), are validated over the middle reaches of the Heihe River in China. The results indicate that the upscaled HJ (Huan Jing means environment in Chinese and this refers to a satellite constellation designed for environment and disaster monitoring by China) albedo, which was calibrated using field measurements, can provide accurate reference values for validating coarse-resolution satellite albedo products. However, the uncertainties in the upscaled HJ albedo should be estimated, and pixels with large uncertainties should be excluded from the validation process.

Land surface albedo plays a critical role in climate, hydrological and biogeochemical modeling, and weather forecasting. It is often assigned in models and satellite retrievals by albedo climatology look‐up tables using land cover type and other variables; however, there are considerable differences in albedo simulations among models, which partially result from uncertainty in obsolete albedo climatology. Therefore, this study introduces a new global 500 m daily blue‐sky land surface albedo climatology data set under both actual and snow‐free surface conditions utilizing 20‐year Moderate Resolution Imaging Spectroradiometer products from Google Earth Engine. In situmeasurements from 38 long‐term‐maintained sites were utilized to validate the accuracies of different albedo climatology datasets. The root‐mean‐square error, bias, and correlation coefficient of the new climatology are 0.031, −0.003, and 0.96, respectively, which are more accurate than the Global Land Surface Satellite, GlobAlbedo, and 16 model datasets. Data intercomparison suggests that ERA5 exhibits better performance than Modern‐Era Retrospective Analysis for Research and Applications Version 2 (MERRA2) and 14 Coupled Model Intercomparison Projects Phase 6 models. However, it contains positive biases in the snow‐free season, while MERRA2 underestimates the snow albedo. Global albedo variation associated with basic surface plant functional types was also characterized, and snow impact was considered separately. Temporal variability analysis indicates that traditional climatology datasets with coarser temporal resolutions (≥8 days) cannot capture albedo variation over areas with distinct snow seasons, especially in central Eurasia and boreal regions. These results confirm the high reliability and robustness of the new albedo climatology in model assessment, data assimilation, and satellite product retrievals. Surface albedo represents the Earth's surface ability to reflect solar energy, and thus directly influences atmospheric and water circulations by controlling available energies. As an essential variable estimated in current climate models, surface albedo is assigned by searching look‐up tables based on the land cover and soil types. However, there are large differences in simulated albedo among various models, partially because the albedo climatology in these tables was generated in the 1980s and needs to be updated. As global surface albedo has been accurately retrieved from satellite data for decades, we were able to produce a new albedo climatology data set under actual and snow‐free conditions with high spatiotemporal resolutions. Ground validation and data comparison indicate that the new data set performs with higher accuracy compared with other datasets. Moreover, assessment by the new climatology data set shows that albedo from advanced climate models and reanalysis datasets has clear uncertainties, especially over high latitudes and the Tibetan Plateau. Temporal variation in global albedo is better characterized at basic vegetation types. The new albedo climatology data set shows great potential for use in model assessment, modeling improvement, and satellite retrieval of other variables. A global 500 m daily blue‐sky land surface albedo climatology data set in actual and snow‐free surface conditions was produced from Moderate Resolution Imaging SpectroradiometerSite validation and data comparison reveal its reliability and robustness in model assessment, data assimilation, and satellite retrievalsSimulated albedo data by state‐of‐art reanalysis and Coupled Model Intercomparison Projects Phase 6 models still have a clear bias in polar regions and the Tibetan Plateau A global 500 m daily blue‐sky land surface albedo climatology data set in actual and snow‐free surface conditions was produced from Moderate Resolution Imaging Spectroradiometer Site validation and data comparison reveal its reliability and robustness in model assessment, data assimilation, and satellite retrievals Simulated albedo data by state‐of‐art reanalysis and Coupled Model Intercomparison Projects Phase 6 models still have a clear bias in polar regions and the Tibetan Plateau

Pyrene, a representative polycyclic aromatic hydrocarbon (PAH) compound produced mainly from incomplete combustion of fossil fuels, is hazardous to ecosystem health. However, long-term exposure studies did not detect any significant effects of pyrene on soil microorganism. In this study, short-term microcosm experiments were conducted to identify the immediate effect of pyrene on soil bacterial communities. A freshlycollected pristine red soil was spiked with pyrene at 0, 10, 100, 200, and 500 mg·kg−1and incubated for one day and seven days. The bacterial communities in the incubated soils were analyzed using 16S rRNA sequencing and terminal restriction fragment length polymorphism (TRFLP) methods. The results revealed high bacterial diversity in both unspiked and pyrene-spiked soils. Only at the highest pyrene-spiking rate of 500 mg·kg−1, two minor bacteria groups of the identified 14 most abundant bacteria groups were completely suppressed. Short-term exposure to pyrene resulted in dominance of Proteobacteria in soil, followed by Acidobacteria, Firmutes, and Bacteroidetes. Our findings showed that bacterial community structure did respond to the presence of pyrene but recovered rapidly from the perturbation. The intensity of impact and the rate of recovery showed some pyrene dosage-dependent trends. Our results revealed that different levels of pyrene may affect the bacterial community structure by suppressing or selecting certain groups of bacteria. It was also found that the bacterial community was most susceptible to pyrene within one day of the chemical addition.

The leaf area index (LAI) is one of the most important parameters of vegetation canopy structure, which can represent the growth conditions of vegetation effectively. The accuracy, availability, and timeliness of LAI data can be improved greatly, which is of great importance to vegetation‐related research. There are various types of vegetation and terrain conditions in the Heihe River Basin, the second largest inland river basin in northwest China. It is not only helpful to evaluate the accuracy of LAI retrieval algorithms for the complex land surface but also useful to understand the fragile ecological status of the Heihe River Basin. In contrast to previous LAI inversion models, the bidirectional reflectance distribution function unified model can be applied for both continuous and discrete vegetation, and it is appropriate for analyzing heterogeneous vegetation distributions. In this work, we produced 30‐m LAI products once a month in the growing season of 2012. Results show that the algorithm can effectively retrieve LAIs. We verified the LAI product using field measurement data. The mean absolute errors in forest, farmland, and sparse grassland are 0.44, 0.56, and 0.38 respectively, and the R2is 0.8736. Further analysis shows that main errors come from three parts: errors in the parameters, mistakes in the vegetation classification, and interval of the look‐up table. Mixed pixel is also a problem for this model. Despite this, high resolution and applicability means this algorithm can be a good approach for LAI retrieval. LAI retrieval algorithms based on a unified model can be applied to various vegetation conditionsThe ratio of the sky scattering and the clumping index are of great importance for LAI retrievalLeaf reflectance holds the biggest impact on the reflectance ascertained from satellite images, which need to be determined accurately