Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Prediction of constrained modulus for granular soil using 3D discrete element method and convolutional neural networks

To efficiently predict the mechanical parameters of granular soil based on its random micro-structure,this study proposed a novel approach combining numerical simulation and machine learning algorithms.Initially,3500 simulations of one-dimensional compression tests on coarse-grained sand using the three-dimensional(3D)discrete element method(DEM)were conducted to construct a database.In this process,the positions of the particles were randomly altered,and the particle assemblages changed.Interestingly,besides confirming the influence of particle size distribution parameters,the stress-strain curves differed despite an identical gradation size statistic when the particle position varied.Subsequently,the obtained data were partitioned into training,validation,and testing datasets at a 7:2:1 ratio.To convert the DEM model into a multi-dimensional matrix that computers can recognize,the 3D DEM models were first sliced to extract multi-layer two-dimensional(2D)cross-sectional data.Redundant information was then eliminated via gray processing,and the data were stacked to form a new 3D matrix representing the granular soil’s fabric.Subsequently,utilizing the Python language and Pytorch framework,a 3D convolutional neural networks(CNNs)model was developed to establish the relationship between the constrained modulus obtained from DEM simulations and the soil’s fabric.The mean squared error(MSE)function was utilized to assess the loss value during the training process.When the learning rate(LR)fell within the range of 10-5e10-1,and the batch sizes(BSs)were 4,8,16,32,and 64,the loss value stabilized after 100 training epochs in the training and validation dataset.For BS?32 and LR?10-3,the loss reached a minimum.In the testing set,a comparative evaluation of the predicted constrained modulus from the 3D CNNs versus the simulated modulus obtained via DEM reveals a minimum mean absolute percentage error(MAPE)of 4.43%under the optimized condition,demonstrating the accuracy of this approach.Thus,by combining DEM and CNNs,the variation of soil’s mechanical characteristics related to its random fabric would be efficiently evaluated by directly tracking the particle assemblages.

Human-induced landslide on a high cut slope: a case of repeated failures due to multi-excavation

The paper attempts to represent a case of repeated failures on a high cut slope due to multi-excavation. The characteristics of each failure induced by excavation are analyzed through geological investigation, and then a geological model at different failure stages is proposed. The geological analysis shows that the excavation-induced repeated failures are related to the exposure of the weak bedding plane and the toe unloading of the cut slope, Numerical modeling is conducted based on a sequential method, taking into account the main failure stages of cut slope. The simulation results fairly coincide with the practical phenomena observed in field. It is shown that the decrease in normal stress of displaced mass on cut slope will induce the increase in shear stress in bedding planes and that at the toe of the cut slope. The released stress leads to repeated gravitational instabilities of cut slope due to the decrease in normal stress and the increase in shear stress along the bedding planes of mudstone.

Ferric acetylacetonate/covalent organic framework composite for high performance photocatalytic oxidation

Ferric acetylacetonate/covalent organic framework(Fe(acac)_(3)/COF)composite was synthesized by interfacial polymerization method at room temperature.The crystal structure,morphology and porosity property of the composite were characterized by X-ray diffraction,scanning electron microscope,transmission electron microscope and nitrogen adsorption.The interaction between Fe(acac)_(3) and COF was investigated by Fourier transform infrared spectra and X-ray photoelectron spectroscopy.The Fe(acac)_(3)/COF composite was used as a photocatalyst for the oxidation of benzyl alcohol under mild conditions.It exhibits high activity and selectivity for the reaction,of which the mechanism was investigated by determining its photoelectric properties.The Fe(acac)_(3)/COF catalyst developed in this work has application potential in other photocatalytic reactions.

Ultra-small UiO-66-NH_(2)nanoparticles immobilized on g-C_(3)N_(4)nanosheets for enhanced catalytic activity

UiO-66-NH_(2),an important metal-organic framework,is usually synthesized by solvothermal method and the particle size is generally larger than 200 nm,which limits its catalytic applications in chemical reactions.It is very meaningful to produce UiO-66-NH_(2) nanoparticles with ultrasmall size,but remains challenging.Herein,we synthesized UiO-66-NH_(2) nanoparticles in size of 8-15 nm that are immobilized on g-C_(3)N_(4)nanosheets.Compared with the UiO-66-NH_(2) synthesized by the traditional solvothermal method(>200 nm),the ultra-small UiO-66-NH_(2) nanoparticles immobilized on g-C_(3)N_(4)have more unsaturated coordination positions and increased Lewis acidity.Owing to these combined advantages,the ultra-small UiO-66-NH_(2)nanoparticles exhibit greatly improved catalytic activity for Meerwein-Ponndorf-Verley reaction than larger UiO-66-NH_(2)particles.

Mutation of SlARC6 leads to tissue-specific defects in chloroplast development in tomato

The proliferation and development of chloroplasts are important for maintaining the normal chloroplast population in plant tissues.Most studies have focused on chloroplast maintenance in leaves.In this study,we identified a spontaneous mutation in a tomato mutant named suffulta(su),in which the stems appeared albinic while the leaves remained normal.Map-based cloning showed that Su encodes a DnaJ heat shock protein that is a homolog of the Arabidopsis gene AtARC6,which is involved in chloroplast division.Knockdown and knockout of SlARC6 in wild-type tomato inhibit chloroplast division,indicating the conserved function of SlARC6.In su mutants,most mesophyll cells contain only one or two giant chloroplasts,while no chloroplasts are visible in 60%of stem cells,resulting in the albinic phenotype.Compared with mature tissues,the meristem of su mutants suggested that chloroplasts could partially divide in meristematic cells,suggesting the existence of an alternative mechanism in those dividing cells.Interestingly,the adaxial petiole cells of su mutants contain more chloroplasts than the abaxial cells.In addition,prolonged lighting can partially rescue the albinic phenotypes in su mutants,implying that light may promote SlACR6-independent chloroplast development.Our results verify the role of SlACR6 in chloroplast division in tomato and uncover the tissue-specific regulation of chloroplast development.

水/二氧化碳体系的性质及其应用研究

水和二氧化碳是地球上储量最为丰富的两种溶剂,对其性质和应用进行研究具有极其重要的意义。二者作为溶剂利用时各有优缺点,如水对极性物质有着较高的溶解能力,但对很多有机物的溶解能力较差;二氧化碳性质容易调控,对低极性物质具有较好的溶解能力,而对极性物质的溶解能力较差。如果将水和二氧化碳相结合,不仅可以克服两者作为溶剂的局限性,而且还会产生一些新的性质。本文综述了水/二氧化碳体系的性质及其在材料制备和化学反应中的应用研究。按研究体系,可分为溶解二氧化碳的水溶液、表面活性剂稳定的水/液体(或超临界)二氧化碳体系和纳米粒子稳定的水/液体(或超临界)二氧化碳体系。

Ionic liquids produce heteroatom-doped Pt/TiO2 nanocrystals for efficient photocatalytic hydrogen production

It is of great importance to develop facile strategies to synthesize catalysts with desirable compositions and structures for high-performance photocatalytic hydrogen generation. In this work, we put forward an ionic liquid assisted one-pot route for the synthesis of heteroatom-doped Pt/TiO2 composite material. This route is simple, environmentally benign and adjustable owing to the designable properties of ionic liquids. The as-synthesized Pt/TiO2 nanocrystals exhibit high activity and stability for the photocatalytic hydrogen generation under simulated solar irradiation. This method can be easily applied to the synthesis of various kinds of metal/TiO2 composites doped with desirable heteroatoms (e.g., F, Cl, Br, etc).

Supercritical CO2 produces the visible-light-responsive TiO2/COF heterojunction with enhanced electron-hole separation for highperformance hydrogen evolution

To construct the heterojunctions of TiO2 with other compounds is of great importance for overcoming its inherent shortages and improving the visible-light photocatalytic performance.Here we propose the construction of TiO2/covalent organic framework(COF)heterojunction with tight connection by a supercritical CO2(SC CO2)method,which helps bridging the transformation paths for photo-induced charge between T i02 and COF.The produced T i02/COF heterojunction performs a H2 evolution of 3,962 nmol·g^-1·h^-1 under visible-light irradiation,which is-25 times higher than that of pure TiO2 and 4.5 folds higher than that of TiO2/COF synthesized by the conventional solvothermal method.This study opens up new possibilities for constructing heterojunctions for solar energy utilization.