231 research outputs found

    Large-scale soil organic carbon mapping based on multivariate modelling: The case of grasslands on the Loess Plateau

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    The Loess Plateau is considered one of the world's regions with severe soil erosion. Grasslands are widely distributed on the Loess Plateau, accounting for approximately 40% of the total area. Soil organic carbon (SOC) plays an important role in the terrestrial carbon cycle in this region. We compiled more than 1,000 measurements of plant biomass and SOC content derived from 223 field studies of grasslands on the Loess Plateau. Combined with meteorological factors (precipitation and air temperature) and the photosynthetically active radiation factor, the topsoil SOC contents of grasslands were predicted using the random forest (RF) regression algorithm. Predicted grassland SOC content (1.70-40.34gkg(-1)) decreased from the southeast to the northwest of the Loess Plateau, with approximately 1/5 of the grassland exhibiting values lower than 4gkg(-1). Observed SOC content was positively correlated with observed plant biomass, and for predicted values, this correlation was strong in the desert steppe and the steppe desert of rocky mountains. Air temperature was the most important factor affecting SOC contents in the RF model. Moreover, the residual error of observations and predictions increased as the grazing intensity varied from none to very severe in the temperate desert steppe, and this RF model may not perform well in plains. The use of the RF model for SOC prediction in Loess Plateau grasslands provides a reference for C storage studies in arid and semi-arid regions, and aboveground biomass and temperature should receive more attention due to increasing C sequestration

    Estimates of carbon storage in grassland ecosystems on the Loess Plateau

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    Grassland ecosystems play an important role in the carbon (C) balance of arid and semi-arid regions. These ecosystems provide C for grass growth and soil microbial activities and represent one of the main sources of atmospheric C. In this study, we estimated the C density and storage of 223 sampling sites in grassland ecosystems on the Loess Plateau using elevation, vegetation indexes, precipitation, air temperature, day and night land surface temperature (LSTd and LSTn, respectively), evapotranspiration (ET), percent tree cover and the non-vegetated area to build decision regression tree and generalized linear regression models (GLMs). The results showed that the C density decreased from south to north and ranged from 0.22 to 29.29 kg C/m(2). The average amount of C stored in the ecosystems was 1.46 Pg. The typical steppe and forest steppe stored the most C, and the steppe desert stored the least. The soil (0-1 m) stored most of the organic C, accounting for > 90%, and the belowground biomass (BGB) contained > 3 times the amount of C as the aboveground biomass (AGB). This study provides reference information for the loss of C and associated mitigation strategies on the Loess Plateau

    Suboptimal Safety-Critical Control for Continuous Systems Using Prediction-Correction Online Optimization

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    This paper investigates the control barrier function (CBF) based safety-critical control for continuous nonlinear control affine systems using more efficient online algorithms by the time-varying optimization method. The idea of the algorithms is that when quadratic programming (QP) or other convex optimization algorithms needed in the CBF-based method is not computation affordable, the alternative suboptimal feasible solutions can be obtained more economically. By using the barrier-based interior point method, the constrained CBF-QP problems are transformed into unconstrained ones with suboptimal solutions tracked by two continuous descent-based algorithms. Considering the lag effect of tracking and exploiting the system information, the prediction method is added to the algorithms, which achieves exponential convergence to the time-varying suboptimal solutions. The convergence and robustness of the designed methods as well as the safety criteria of the algorithms are studied theoretically. The effectiveness is illustrated by simulations on the anti-swing and obstacle avoidance tasks

    Impact of wind farm wake steering control on blade root load

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    Yaw misalignment is known to affect blade root loads on wind turbines. Most of previous studies concentrate on yaw misalignment in the context of wake steering control, aiming at increasing the total output power of the wind farm. There, wake steering is compared with greedy control, in which yaw misalignment is considered to be 0. In reality, yaw misalignment also occurs in greedy control due to changes in wind direction arising from varying inflow conditions (e.g. turbulence). This paper aims at comparing these two sources of yaw misalignment-naturally changing wind direction versus active yaw in wake steering-in terms of blade root loads. To this end, SCADA data from a real wind farm is used to get yaw misalignment statistics in actual greedy control conditions. FAST.Farm is used to simulate three wind turbines arranged in series, to study maximum and damage-equivalent loads corresponding to in-plane and out-of-plane bending moments on the blades. The results show that compared with actual greedy control, wake steering control reduces the maximum load from the upstream wind turbine, but increases it from other wind turbines. Concerning the damage-equivalent loads from all wind turbines, the blade's in-plane moment is reduced, but the blade's out-of-plane moment is increased.Impact of wind farm wake steering control on blade root loadacceptedVersio

    Ligand Selectivity in the Recognition of Protoberberine Alkaloids by Hybrid-2 Human Telomeric G-Quadruplex: Binding Free Energy Calculation, Fluorescence Binding, and NMR Experiments

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    The human telomeric G-quadruplex (G4) is an attractive target for developing anticancer drugs. Natural products protoberberine alkaloids are known to bind human telomeric G4 and inhibit telomerase. Among several structurally similar protoberberine alkaloids, epiberberine (EPI) shows the greatest specificity in recognizing the human telomeric G4 over duplex DNA and other G4s. Recently, NMR study revealed that EPI recognizes specifically the hybrid-2 form human telomeric G4 by inducing large rearrangements in the 50-flanking segment and loop regions to form a highly extensive four-layered binding pocket. Using the NMR structure of the EPI-human telomeric G4 complex, here we perform molecular dynamics free energy calculations to elucidate the ligand selectivity in the recognition of protoberberines by the human telomeric G4. The MM-PB(GB)SA (molecular mechanics-Poisson Boltzmann/Generalized Born) Surface Area) binding free energies calculated using the Amber force fields bsc0 and OL15 correlate well with the NMR titration and binding affinity measurements, with both calculations correctly identifying the EPI as the strongest binder to the hybrid-2 telomeric G4 wtTel26. The results demonstrated that accounting for the conformational flexibility of the DNA-ligand complexes is crucially important for explaining the ligand selectivity of the human telomeric G4. While the MD-simulated (molecular dynamics) structures of the G-quadruplex-alkaloid complexes help rationalize why the EPI-G4 interactions are optimal compared with the other protoberberines, structural deviations from the NMR structure near the binding site are observed in the MD simulations. We have also performed binding free energy calculation using the more rigorous double decoupling method (DDM); however, the results correlate less well with the experimental trend, likely due to the difficulty of adequately sampling the very large conformational reorganization in the G4 induced by the protoberberine binding

    Beating signals in CdSe quantum dots measured by low-temperature 2D spectroscopy

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    Advances in ultrafast spectroscopy can provide access to dynamics involving nontrivial quantum correlations and their evolutions. In coherent 2D spectroscopy, the oscillatory time dependence of a signal is a signature of such quantum dynamics. Here we study such beating signals in electronic coherent 2D spectroscopy of CdSe quantum dots (CdSe QDs) at 77 K. The beating signals are analyzed in terms of their positive and negative Fourier components. We conclude that the beatings originate from coherent LO-phonons of CdSe QDs. No evidence for the quantum dot size dependence of the LO-phonon frequency was identified.Comment: 18 page
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