To reveal the seismogenic mechanism of the Luding earthquake, we employed the 118 China Seismic Network stations to collect the P-wave polarity data from each station, which was then used in the ...P-wave first motion approach to calculate the focal mechanism solution of the M6.8 Luding earthquake that occurred on September 5, 2022. We have also studied the loading effect of tectonic stress on the Luding earthquake fault based on the stress field data for the research area. The results indicate that this earthquake was a strike-slip type, the nodal plane I: strike 167°, dip Angle 78°, slip Angle 2°; Nodal plane Ⅱ: strike 77°, dip Angle 88°, slip Angle 168°. The two fault planes’ instability coefficients of the Luding earthquake are examined considering the region’s background stress field’s condition. The nodal plane I in the Moho circle is discovered to practically coincide with the Coulomb failure line and the tangent point of the Moho circle, indicating that this nodal plane has a high instability coefficient compared to the nodal plane II. The conclusion is that the nodal plane I has a higher likelihood of being the seismogenic fault plane, which is congruent with the seismogenic fault plane suggested by the aftershock distribution, the earthquake radiation energy distribution of a single station, and seismic intensity distribution. The Luding earthquake’s focal mechanism is highly like the theoretical focal mechanism of the fault situated at the location where the Coulomb failure line intersects the Mohr circle, demonstrating that background stress is what caused the earthquake. The substantial fault instability and similarity between the solved and theoretical focal mechanisms make it easier to comprehend the loading effect of tectonic stress on the Luding earthquake fault.
Monitoring the capacity of lithium-ion battery is a crucial task to ensure its safety and reliability during long-term use. However, conventional capacity estimation methods heavily rely on the ...specially designed operating conditions or durations of charge/discharge cycles, limiting their applications in real-world operations. To address such challenges, in this paper, a fast and flexible method is proposed to accurately estimate battery capacity based on a residual convolutional neural network using only small pieces of raw measurement data. And Bayesian optimization as well as network slimming are introduced to optimize and prune the network structure. Then, the proposed model is validated in two public battery degradation data sets, containing two types of batteries and six types of charging strategies in total. It's shown that the model is flexible enough to cope with the application scenarios of different charging strategies, different sampling frequencies and different voltage ranges starting at arbitrary initial SOCs, while still achieving fast and accurate capacity estimation. The mean absolute errors on 38 LFP batteries and 8 LCO batteries with a four-fold cross validation approach are all below 0.5% throughout the whole life of the batteries. Comprehensive case studies are also carried out to investigate the influence of capacity increment size, compression ratio of input data and the depth of network on the trade-offs between the model accuracy and its practicability for wide applications.
•A compact residual convolutional network is proposed for fast capacity estimation.•The estimation requires only a small piece of charging data at arbitrary SOCs.•The model size is reduced by 79% with a minimal accuracy loss by network slimming.•The model is flexible in input and structure to meet demands of diverse scenarios.
The electronic structure, work function, complex dielectric function, absorption coefficient and reflectivity of defective MoSe2 models containing point defects as well as alkali metal doping have ...been calculated based on the first principles of density flood theory. The effect of alkali metal doping on the optoelectronic properties of MoSe2 under defect conditions is investigated. Alkali metal elements were doped separately on the basis of a single Se atom defect, and the results show that the doped systems can all be stable. The introduction of the defect decreases the band gap of MoSe2 from 1.498 eV to 0.816 eV. The alkali-metal-doped defective MoSe2 systems have semiconductor-metal transitions with collisions between the bottom of the conduction band and the top of the valence band for each of the systems, except for the K doping. The K-doped defective MoSe2 is a narrow band gap semiconductor with a band gap of 0.202 eV. Overall, alkali metal doping under defective conditions improves the electrical conductivity of MoSe2, resulting in enhanced conductivity of the crystal. The work function analysis reveals that the work function of the alkali metal doped defective MoSe2, except for K doping, decreases gradually with the increase of its atomic radius, while the electrical conductivity of each system is enhanced. Optical property analyses revealed that the absorption coefficient of alkali-metal doped defective MoSe2 was significantly higher than that of intrinsic MoSe2 in the infrared light region, which compensated for the lack of zero absorption of the intrinsic material in the infrared light region, and enhanced its light-absorbing ability in the infrared light region and part of the visible light region. The reflectivity of each defective MoSe2 system doped by alkali metals is much smaller than that of the intrinsic, and the reflection peaks are red-shifted in the direction of the low-energy region. Overall, the doping of alkali metal atoms reduces the average reflectivity of the defective MoSe2 materials, which is conducive to the enhancement of light absorption and photoelectron emission from the materials. It is hoped that the research results in this paper will contribute to expanding the potential applications of MoSe2 materials in solar cells, photovoltaic devices, and photodetectors.
•Luminescent materials of practical value all rely on impurity and defect states for luminescence..•Optoelectronic properties of 2D materials are affected by factors such as impurity atoms and defects.•This study will expand the applications of MoSe2 materials in solar cells, photovoltaic devices and photodetectors.
Aims
Biological soil crusts (BSCs) are widely considered critical for soil fertility in arid ecosystems. However, how microbial communities regulate the C and N cycles during BSC succession is not ...well understood.
Methods
We utilized GeoChip 5.0 to analyze the functional potential of bacteria and fungi involved in the C and N cycles of BSCs along a 61-year revegetation chronosequence.
Results
The normalized average signal intensities of different functional genes involved in C and N metabolism in 61-year-old BSCs were significantly different from those in younger BSCs and most functional gene subcategories and the corresponding dominant functional populations were derived from bacterial rather than fungal communities. Most C degradation genes (dominated by the starch-degrading gene
amyA
) were derived from Actinobacteria (mainly
Streptomyces
) in bacteria, but Ascomycota (mainly
Aspergillus
) was the key population for lignin degradation (dominated by the
phenol oxidase
gene) during BSC succession. N cycle genes involved in denitrification (such as
narG
,
nirK/S
, and
nosZ
) and N fixation (
nifH
) were mainly derived from
Unclassified Bacteria
, whereas genes involved in ammonification (
ureC
) were mainly derived from
Streptomyces
. Moreover, redundancy analysis showed that soil biogeochemical properties were closely related to bacterial and fungal functional gene structures during BSC succession.
Conclusions
These findings indicate that bacteria play a crucial role in the regulation of C and N cycles during BSC succession in arid ecosystems, while fungi perform supplementary degradation of lignin, and these communities can successfully stimulate an increase in C and N metabolism in soil during the later successional stages of BSCs.
•The asynchrony in population dynamics and tree growth may be due to the spatial and temporal heterogeneity of NSR fire.•The NSR fire can only suppresses radial growth in the short term (1–2 years) ...at the stand level.•Non-stand replacing fire promotes Larix gmelinii forest rejuvenation.•Combining the age distribution and growth release signal can reveal the disturbance mechanism of forest stands.
The population dynamics and individual growth dynamics of dominant tree species in boreal forests are associated with fire regimes. Fire regimes in the boreal forests of eastern Siberia are dominated by non-stand replacing (NSR) fire types. Fire drives population demographics by triggering tree mortality and births, and affects the post-fire growth dynamics of surviving individuals. When a non-stand replacing fire occurs, population dynamics fluctuate and individual growth changes occur simultaneously. The Great Xing’an Mountains is located at the southern edge of the eastern Siberia boreal forest and research on fire regimes and stand dynamics in this region are scarce. Understanding the effect of fire on the population structure and individual growth of the dominant species in the stand and the disturbance mechanisms are essential to understand the develop of boreal forests in the context of climate warming. In this study, three Larix gmelinii stands disturbed by NSR fire in the Great Xing’an Mountains were selected and established plots, and control stand plots were established at similar site conditions. We conducted a forest inventory and used dendrochronological methods to reveal the short- and long-term effects of NSR fire disturbance on the population dynamics and individual growth of the dominant species of L. gmelinii. Specifically, the effects of NSR fire on stand structure, the relationship between L. gmelinii demographics and disturbance, and the response of growth dynamics to disturbance were analyzed. Finally, the history of potential disturbance at stand level was reconstructed. The study found that common NSR fire affect the biomass and species composition of L. gmelinii forests. Fire disturbance contributes to the younger age structure of L. gmelinii populations. However, The NSR fire may limit the size of L. gmelinii populations but does not necessarily destroy population resilience depending on stand conditions. Irregular fluctuations in population survival and mortality curves are directly related to historical disturbance events. The NSR fire can inhibit the growth of surviving trees for 1–2 years, resulting in temporary growth asynchrony. The population dynamics fluctuations and temporal patterns of growth release signals can reconstruct historical disturbance events at the stand level. For example, the MH intra-group (Mohe Luogu River Nature Reserve burned stand&Mohe Luogu River Nature Reserve unburned stand) probably experienced a high-severity fire in 1880–1900, the TH intra-group (Tahe Nature Reserve burned stand&Tahe Nature Reserve unburned stand) experienced a high-severity fire around 1930, and THB (Tahe Nature Reserve burned stand) suffered stand-replacing. Overall, irregular fluctuations in population survival and mortality curves have been directly related to historical disturbance events. These findings provide direct evidence of the short- and long-term effects of fire on the survival and growth of L. gmelinii populations.
Convenient and ultrasensitive detection of pesticides is demanded for healthcare and environmental monitoring, which can be realized with a dual-modal strategy. In this paper, based on a ...biotin-labeled IgG-modified gold nanoparticle (AuNP@IgG-bio) probe, a dual-modal immunosensor was proposed for detecting chloroacetamide herbicides. This platform is relied on the dephosphorylation of ascorbic acid 2-phosphate (AA2P) by alkaline phosphatase (ALP). In addition to this process, ascorbic acid (AA)-triggered deposition of silver on gold nanostars (AuNSs) and the fluorogenic reaction of dehydrogenated AA and o-phenylenediamine (OPD) occur sequentially. Thus, the dual readout of the color change of red-green-blue (RGB) and fluorescence generation in situ induced by crystal growth can be used. The limits of detection (LODs) were as low as 1.20 ng/mL of acetochlor (ATC), 0.89 ng/mL of metolachlor, 1.22 ng/mL of propisochlor, and 0.99 ng/mL of their mixture by a smartphone and 0.44 ng/mL of ATC, 1.59 ng/mL of metolachlor, 2.80 ng/mL of propisochlor, and 0.72 ng/mL of their mixture by a spectrofluorometer. The recoveries from corn were 91.4–105.1% of the colorimetric mode and 92.4–106.2% of the fluorescent mode. Due to its simple observation mode and good performance, this dual-modal immunosensor possesses considerable application prospects.
Abstract Spinal cord injuries (SCIs) often result in secondary damage; therefore, interventions beyond current cell transplantation methods must be explored. The innate phagocytic propensity of ...macrophages are exploited for artificially aged erythrocytes and developed a delivery system fusing erythrocytes with reactive oxygen species (ROS)‐reactive nanoparticles prepared from a diselenide‐bond cross‐linked organic compound. The system targets peripheral blood macrophages, delivering anti‐glutamate drug‐loaded nanoparticles to the SCI site, releasing the drug upon ROS stimulation. This efficiently enables targeted drug delivery and reprograms peripheral macrophages through synergistic action with erythrocytes and encapsulated nucleic acids, effectively modulating the immune microenvironment in the SCI zone (significantly reduces neuronal apoptosis and alters the macrophage phenotype in the SCI region). The approach effectively addresses glutamate toxicity and immune inflammation by effectively regulating the lesion microenvironment, providing protection to neurons and creating favorable conditions for regeneration. Departing from the conventional “red blood cell backpack” model, the “chocolate chip cookie” concept is paradigm‐altering, enabling multifaceted erythrocyte functions. Collectively, the system comprehensively enhances the post‐SCI microenvironment. Its efficacy in SCI treatment and innovative drug delivery approach open new possibilities for neural function recovery. By laying the groundwork for future clinical applications, the research pioneers a transformative path toward advancing SCI therapeutics.
Accurately evaluating the adsorption properties of various adsorbents by some parameter is of great significance to select an appropriate adsorbent and remove volatile organic compounds (VOCs) ...efficiently. In this study, we successfully found a new parameter as a common standard in selecting adsorbents. Six classical adsorbents containing three carbon materials and three porous polymeric resins were used, and their surface energy (γst) and corresponding gas-solid partition coefficients (K) of eleven VOCs were measured by inverse gas chromatography (IGC) at three different column temperatures of 343 K(or 353 K), 373 K and 403 K. Then, these values at 303 K were calculated according to the linear relationship between lnK and 1/T. It was found that surface energy was significantly correlated with K values for a specific VOC, and could be used as a common standard to well evaluate the adsorption properties of various adsorbents. Furthermore, we employed it to develop a model for predicting the adsorption properties of low-concentration VOCs on various adsorbents at 303 K. The developed model exhibited an excellent predictive ability by external validation. Moreover, the model showed wide applicability and predicted the lnK values of VOCs at 373 K and 403 K in R2 of 0.910 and 0.889.
Display omitted
•K values of VOCs and γst values of adsorbents were measured by IGC exactly.•γst was successfully found as a common standard in selecting adsorbents.•A prediction model comprising of parameters P, S, A, B and γst was developed.•The model accurately predicted various VOCs adsorption on various adsorbents.•Main interactions were dispersion, dipole-type interaction and hydrogen bonding.
•The atmospheric water cycle behind two droughts is quantified based on the land–atmosphere water balance.•Moisture sources, pathways and transport are tracked for both droughts by using the HYSPLIT ...model.•The controls of moisture transportation during the two droughts are identified and quantified.
The influence of moisture recycling and transport on major drought events is poorly understood, but essential to enhance our knowledge of the atmospheric water cycle. Here, we investigate this for two record-breaking droughts over the Mid-to-Lower Reaches of the Yangtze River (MLRYR), the winter-spring (WS) drought of 2011 and summer-autumn (SA) drought of 2019. Using a land–atmosphere water balance framework, we find the precipitation recycling ratio (the percentage of precipitation in a region derived from the same region’s evaporation) increased during both droughts, especially for the SA drought (from 14.5% to 22.9%). The WS drought was characterized by a 27.8% reduction in external advected moisture, originating principally from the northeast China and Bohai Sea (reduced by 22.3%) and from the northwest Pacific and South China Sea (25.7%). The SA drought was driven by a 43.8% reduction in external advected moisture, originating mainly from a southwesterly path, i.e. the Bay of Bengal and the South China Sea (reduced by 26.8%). From a regional viewpoint, moisture transportation from the Pacific Ocean (and South China Sea) decreased during the WS (SA) droughts, mainly resulting in moisture deficit over the MLRYR. Analyses reveal that this reduction was driven by strong negative convergence, which was unfavorable for precipitation formation and enhanced air flow out of the MLRYR. The weakened moisture transport was principally driven by seasonal mean flow rather than transient eddies. Changes in wind (i.e. dynamic processes), rather than specific humidity (i.e. thermodynamic processes) were dominant in regulating the seasonal mean moisture transport. Our study helps understand the atmospheric water cycle anomalies driving extreme drought events, and advances knowledge on moisture transportation and its controlling processes.
