Diurnal Temperature Variation and Plants Drive Latitudinal Patterns in Seasonal Dynamics of Soil Microbial Community

Seasonality, an exogenous driver, motivates the biological and ecological temporal dynamics of animal and plant communities. Underexplored microbial temporal endogenous dynamics hinders the prediction of microbial response to climate change. To elucidate temporal dynamics of microbial communities, temporal turnover rates, phylogenetic relatedness, and species interactions were integrated to compare those of a series of forest ecosystems along latitudinal gradients. The seasonal turnover rhythm of microbial communities, estimated by the slope (w value) of similarity-time decay relationship, was spatially structured across the latitudinal gradient, which may be caused by a mixture of both diurnal temperature variation and seasonal patterns of plants. Statistical analyses revealed that diurnal temperature variation instead of average temperature imposed a positive and considerable effect alone and also jointly with plants. Due to higher diurnal temperature variation with more climatic niches, microbial communities might evolutionarily adapt into more dispersed phylogenetic assembly based on the standardized effect size of MNTD metric, and ecologically form higher community resistance and resiliency with stronger network interactions among species. Archaea and the bacterial groups of Chloroflexi, Alphaproteobacteria, and Deltaproteobacteria were sensitive to diurnal temperature variation with greater turnover rates at higher latitudes, indicating that greater diurnal temperature fluctuation imposes stronger selective pressure on thermal specialists, because bacteria and archaea, single-celled organisms, have extreme short generation period compared to animal and plant. Our findings thus illustrate that the dynamics of microbial community and species interactions are crucial to assess ecosystem stability to climate variations in an increased climatic variability era

Synthesize of silicon/carbon nanosheets with NaCl template and its application as anode material of lithium-ion batteries

Lithium-ion batteries (LIBs) are used extensively in various applications such as mobile phones and portable computer. Silicon (Si) is regarded as a kind of promising anode material in LIBs because of its high theoretical capacity and low working potential. The major challenges related to Si anodes are their huge volume changes and poor conductivity during lithiation-delithiation. Herein, a two-dimensional structure of Si/petroleum pitches based carbon nanosheets (Si/CNSs) was successfully synthesized via a green and recyclable NaCl template method. This peculiar structural feature of Si/CNS can effectively accommodate the volume expansion of Si anodes and improve their electrochemical performance. A typical sample of Si/CNS-2 exhibits a high reversible capacities of 901mAhg(-1) at 100mAg(-1), good cycling stability (capacity retention of 655mAhg(-1) after 100 cycles at 300mAg(-1)) and excellent rate capability (533mAhg(-1) at 2Ag(-1)). This approach is simple and environment-friendly, which may supply a practicality way to prepare Si-based anode materials for high-performance LIBs

Electrochemical performance of novel mesocarbon microbeads as lithium ion battery anode

Mesocarbon microbeads (MCMB) are known to be one of the most important carbonaceous anode materials. In this study, novel mesocarbon microbeads (NMCMB) were prepared by two-step treatment including thermal polymerization and heat treatment under vacuum, which was then applied as anode materials for lithium ion batteries (LIBs). The morphologies, structures, and other properties of NMCMB were investigated by scanning electron microscope (SEM), X-ray diffractometer (XRD), thermogravimetric analyses (TGA), Raman spectroscopy, and N-2 adsorption-desorption isotherms. The results indicated that NMCMB had rough surface, high specific surface, and better thermal stability. After carbonized, NMCMB have relatively higher disorder degree and bigger interlayer distance. As the anode material of LIBs, NMCMB exhibit better electrochemical performance than MCMB, and provide a high reversible specific capacity of 379 mAh g(-1) at a current density of 50 mA g(-1), with almost 100% capacity retention for up to 50 cycles at 100 mA g(-1), and a good rate performance (256 mAh g(-1) at 1 A g(-1)). This synthetic method paves a new way to improve electrochemical performance of MCMB, which may expand MCMB utilizationaEuro,for LIBs.</p

Ammonia-Oxidizing Archaea Are More Resistant Than Denitrifiers to Seasonal Precipitation Changes in an Acidic Subtropical Forest Soil

Seasonal precipitation changes are increasingly severe in subtropical areas. However, the responses of soil nitrogen (N) cycle and its associated functional microorganisms to such precipitation changes remain unclear. In this study, two projected precipitation patterns were manipulated: intensifying the dry-season drought (DD) and extending the dry-season duration (ED) but increasing the wet-season storms following the DD and ED treatment period. The effects of these two contrasting precipitation patterns on soil net N transformation rates and functional gene abundances were quantitatively assessed through a resistance index. Results showed that the resistance index of functional microbial abundance (-0.03 ± 0.08) was much lower than that of the net N transformation rate (0.55 ± 0.02) throughout the experiment, indicating that microbial abundance was more responsive to precipitation changes compared with the N transformation rate. Spring drought under the ED treatment significantly increased the abundances of both nitrifying (amoA) and denitrifying genes (nirK, nirS, and nosZ), while changes in these gene abundances overlapped largely with control treatment during droughts in the dry season. Interestingly, the resistance index of the ammonia-oxidizing archaea (AOA) amoA abundance was significantly higher than that of the denitrifying gene abundances, suggesting that AOA were more resistant to the precipitation changes. This was attributed to the stronger environmental adaptability and higher resource utilization efficiency of the AOA community, as indicated by the lack of correlations between AOA gene abundance and environmental factors [i.e., soil water content, ammonium (NH4+) and dissolved organic carbon concentrations] during the experiment

Retrieval of Soil Moisture Content Based on Multisatellite Dual-Frequency Combination Multipath Errors

Global navigation satellite system interferometric reflectometry (GNSS-IR) is a new type of microwave remote sensing technology that can measure soil moisture content (SMC). GNSS-IR soil moisture retrieval methods based on the satellite signal-to-noise ratio (SNR) and triple-frequency signal combination have the following shortcomings: SNR does not always exist in the original GNSS file, and the number of triple-frequency signal observation satellites is small, resulting in GNSS-IR soil moisture observation time resolution being low. Based on the above problems, in this study, we constructed a soil moisture inversion method based on multisatellite dual-frequency combined multipath error is proposed: the multipath error calculation model of dual-frequency carrier phase (L4 Ionosphere Free, L4_IF) and dual-frequency pseudorange (DFP) without ionospheric effect is constructed. We selected the data of the five epochs before and after the time point of the effective satellite period to construct the multipath error model and error equation, and we solved the delay phase for soil moisture retrieval. We verified the method using Plate Boundary Observatory (PBO) P041 site data. The results showed that the Pearson correlation coefficients (R) of L4_IF and DFP methods at P041 station are 0.97 and 0.91, respectively. To better verify the results&rsquo; reliability and the proposed method&rsquo;s effectiveness, the soil moisture data of the MFLE station about 210 m away from P041 station are used as the verification data in this paper. The results showed that the delay phase solved by multipath error and soil moisture strongly correlate. Pearson correlation coefficients (R) of L4_IF and DFP methods at MFLE station are 0.93 and 0.86, respectively. In order to improve the inversion accuracy of GNSS-IR soil moisture, this paper constructs the prediction model of soil moisture by using the linear regression (ULR), back propagation neural network (BPNN) and radial basis function neural network (RBFNN), and evaluates the accuracy of each model. The results showed that the soil moisture retrieval method based on multisatellite dual-frequency combined multipath error can replace the traditional retrieval method and effectively improve the time resolution of GNSS-IR soil moisture estimation. To perform highly dynamic monitoring of soil moisture, higher retrieval accuracy can only be obtained with a small epoch multipath error

Understanding clinical characteristics influencing adverse outcomes of Omicron infection: a retrospective study with propensity score matching from a Fangcang hospital

ObjectivesThe epidemic of coronavirus disease 2019 (COVID-19) is causing global health concerns. The aim of this study was to evaluate influence of clinical characteristics on outcomes during the Omicron outbreak.MethodsA total of 25182 hospitalized patients were enrolled, including 39 severe patients and 25143 non-severe patients. Propensity score matching (PSM) was applied to balance the baseline characteristics. Logistic regression analysis was used to assess the risk of severe disease, as well as the risk of prolonged viral shedding time (VST) and increased length of hospital stay (LOS).ResultsBefore PSM, patients in the severe group were older, had higher symptom scores, and had a higher proportion of comorbidities (p&lt;0.001). After PSM, there were no significant differences in age, gender, symptom score and comorbidities between severe (n=39) and non-severe (n=156) patients. Symptoms of fever (OR=6.358, 95%CI 1.748-23.119, p=0.005) and diarrhea (OR=6.523, 95%CI 1.061-40.110, p=0.043) were independent risk factors for development of severe disease. In non-severe patients, higher symptom score was associated with prolonged VST (OR=1.056, 95% CI 1.000-1.115, p=0.049) and LOS (OR=1.128, 95% CI 1.039-1.225, p=0.004); older age was associated with longer LOS (OR=1.045, 95% CI 1.007-1.084, p=0.020).ConclusionThe overall condition of the Shanghai Omicron epidemic was relatively mild. Potential risk factors for fever, diarrhea, and higher symptom score can help clinicians to predict clinical outcomes in COVID‐19 patients